determination of individual competencies by statistical methods yuksek lisans tezi tulay bozkurt...
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T.C. MARMARA ÜNİVERSİTESİ
SOSYAL BİLİMLER ENSTİTÜSÜ İNGİLİZCE İŞLETME ANABİLİM DALI SAYISAL YÖNTEMLER BİLİM DALI
DETERMINATION OF INDIVIDUAL COMPETENCIES BY STATISTICAL
METHODS
YÜKSEK LİSANS TEZİ
TÜLAY BOZKURT
İSTANBUL, 2009
T.C. MARMARA ÜNİVERSİTESİ
SOSYAL BİLİMLER ENSTİTÜSÜ İNGİLİZCE İŞLETME ANABİLİM DALI SAYISAL YÖNTEMLER BİLİM DALI
DETERMINATION OF INDUVIDUAL COMPETENCIES BY STATISTICAL
METHODS
YÜKSEK LİSANS TEZİ
TÜLAY BOZKURT
Danışman: Prof. Dr. RAUF NİŞEL
İstanbul, 2009
i
PREFACE
In today’s fast changing environmental conditions are transforming the ways of
conducting business for individuals and organizations. Such a fast changes together with
ups and downs in the economy increase the uncertainty in the business world. Adapting to
these conditions requires different approaches and abilities. Since the past experience and
success stories can be trivial to sustain in this transition periods. Furthermore being a
competent person, having excellent leadership skills and other superior performance
characteristics of a business professional can be insufficient to achieve successful
outcomes. Such a major changes refers “New World Order” for every piece of business
life. Effects of the environmental changes on the individuals bring more risks and different
responsibilities. It also accelerates the necessity of adapting new situation. At this point the
arising question mark is which individual characteristics are vital to gather successful
outcome for today and for the future in the conditions of uncertainty and change. In this
study effect of the environmental sources as external influencing factors to the individual’s
competencies which is effective to gather the successful outcome at workplace searched
and proposed in a new competency set. In addition various definitions, approaches,
methods and stages of competency modeling and the relationship with human resource
management functionalities explained at the beginning of the study.
I would like to thank you my supervisor, Prof Dr. Mr. Rauf Nişel for his valuable
thoughts, comments and contribution to this study and his teaching philosophy with deep
knowledge and experience. Besides I thank you my parents Tanay Bozkurt and Kılıç
Bozkurt for their valuable and continuous support and each of my family members.
Istanbul, 2009 Tülay BOZKURT
ii
TABLE OF CONTENTS
Page No
TABLE LIST...............................................................................................................VI FIGURE LIST ............................................................................................................VII INTRODUCTION......................................................................................................... 1
1. COMPETENCY.................................................................................................... 4 1.1. Definitions of Competency...................................................................................... 4
1.1.1. Historical Development of Competency Studies....................................................... 5 1.1.1.1. Competency Studies by David McClelland............................................. 5 1.1.1.2. Competency Studies of Richard Boyatsiz............................................... 7 1.1.1.3. Competency Studies of L.M. Spencer and S.M. Spencer...................... 9 1.1.1.4. Competency Studies of David Dubois .................................................. 10 1.1.1.5. Competency Studies of Kleins .............................................................. 10 1.1.1.6. Competency Studies of Woodruff ......................................................... 11 1.1.1.7. Competency Studies of Robert A. Roe ................................................. 13
1.1.2. Evaluation of The Competency Definitions ............................................................. 14 1.1.3. Relationship Between Competencies, Knowledge, Skill and Performance........... 18
1.1.3.1. Definition of Knowledge......................................................................... 19 1.1.3.2. Definition of Skill..................................................................................... 20 1.1.3.3. Definition of Performance ...................................................................... 20
2. COMPETENCY MODELS................................................................................. 23 2.1. Development of Competency Models.................................................................. 24 2.2. Types of The Competency Models....................................................................... 25
2.2.1. Occupational Competency Model ........................................................................... 26 2.2.2. Job Competency Model ........................................................................................... 26 2.2.3. Core Competency Model ......................................................................................... 27 2.2.4. Leadership Competency Model............................................................................... 27
2.3. Competency Matrix................................................................................................. 28 3. USAGE OF COMPETENCIES .......................................................................... 30
3.1. Function of Human Resource Management in The Organizations .................32 3.1.1. Competency Based Search and Selection Process............................................... 34 3.1.2. Competency Based Training System...................................................................... 39 3.1.3. Competency Based Performance Management System ....................................... 42 3.1.4. Competency Based Succession Planning System................................................. 45
3.2. Change Management and Competencies ........................................................... 45 3.3. Globalization, Crisis Management and Competencies ..................................... 49
4. MEASURING COMPETENCIES....................................................................... 51
5. PROPOSED MODEL......................................................................................... 55 5.1. The Proposed Competency Model ....................................................................... 58
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5.1.1. Dependent Variables List of The Proposed Competency Model ........................... 59 5.1.2. Independent Variables List of The Proposed Competency Model......................... 60
5.2. Definition of Dependent and Independent Variables ........................................ 61 5.2.1. Definitions of Dependent Variables - Individual Competencies ............................. 61
5.2.1.1. Management Competencies ................................................................. 61 5.2.1.2. Specialties Competencies ..................................................................... 62 5.2.1.3. Entrepreneurship Competencies........................................................... 62 5.2.1.4. Personal Competencies ........................................................................ 63
5.2.2. Definitions of Independent Variables....................................................................... 64 5.2.2.1. Company Core Competencies .............................................................. 64 5.2.2.2. Human Resource Management Competencies ................................... 64 5.2.2.3. Environmental Conditions...................................................................... 65 5.2.2.4. Work Competencies .............................................................................. 67
6. METHODOLOGY .............................................................................................. 68 6.1. Research Design ..................................................................................................... 68
6.1.1. Aim of The Research ............................................................................................... 69 6.1.2. Sources For Collecting of The Research Information............................................. 69
6.1.2.1. Population and Sampling....................................................................... 69 6.1.3. Methods For Data Collection ................................................................................... 70
6.1.3.1. Questionnaire Design ............................................................................ 70 6.1.4. Methods for The Data Analysis ............................................................................... 72
6.1.4.1. Definition of The Relaibility Analysis ..................................................... 72 6.1.4.1.1. Stability of Measures ...........................................................................73 6.1.4.1.2. Internal Consistency of Measures.......................................................76
6.1.4.2. Definition of Multivariate Analysis of Variance (MANOVA) .................. 79 6.1.4.2.1. Analysis Design, Statistical Tests and Effects in MANOVA ...............80 6.1.4.2.2. Assumptions for MANOVA..................................................................83
6.1.4.3. Definition of Analysis of Variance (ANOVA) ......................................... 86 6.1.4.3.1. Statistical Tests in ANOVA..................................................................87 6.1.4.3.2. Assumptions for ANOVA.....................................................................89
6.1.4.4. Definition of Measure of Correlation Analysis (MAC) ........................... 89 6.1.4.5. Definition of Multiple Regression Analysis ............................................ 90
6.2. Data Analysis for The Proposed Model............................................................... 95 6.2.1. Reliability Analysis for the Proposed Model ............................................................ 95 6.2.2. MANOVA Analysis for the Modifed Proposed Model ........................................... 104 6.2.3. ANOVA Analysis for the Proposed Model............................................................. 105 6.2.4. MAC for the Proposed Model ................................................................................ 105 6.2.5. Multiple Regression Analysis for the Proposed Model ......................................... 106
7. FINDINGS........................................................................................................ 107 7.1. Findings of Reliability Analysis (RA) .................................................................107
7.1.1. RA for Dependent Variables.................................................................................. 107 7.1.1.1. RA for 64 Dependent Items All Together ............................................ 107 7.1.1.2. RA for C1.............................................................................................. 109 7.1.1.3. RA for C2.............................................................................................. 110 7.1.1.4. RA for C3.............................................................................................. 111 7.1.1.5. RA for C4.............................................................................................. 113 7.1.1.6. RA for SC1 ........................................................................................... 114 7.1.1.7. RA for SC2 ........................................................................................... 115 7.1.1.8. RA for SC4 ........................................................................................... 117 7.1.1.9. RA for SC5 ........................................................................................... 117
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7.1.1.10. RA for SC6 ........................................................................................... 118 7.1.1.11. RA for SC7 .......................................................................................... 118 7.1.1.12. RA for SC8 ........................................................................................... 119 7.1.1.13. RA for SC9 ........................................................................................... 119 7.1.1.14. RA for SC10 ......................................................................................... 121 7.1.1.15. RA for SC11 ......................................................................................... 121 7.1.1.16. RA for SC12 ......................................................................................... 122 7.1.1.17. RA for SC13 ......................................................................................... 122 7.1.1.18. RA for SC14 ......................................................................................... 123 7.1.1.19. RA for SC15 ......................................................................................... 123 7.1.1.20. RA for SC16 ......................................................................................... 124 7.1.1.21. RA for Modified C1............................................................................... 125 7.1.1.22. RA for Modified C2............................................................................... 125 7.1.1.23. RA for Modified C3............................................................................... 126 7.1.1.24. RA for Modified C4............................................................................... 126 7.1.1.25. RA for CC............................................................................................. 127 7.1.1.26. RA for Modified C5............................................................................... 128 7.1.1.27. RA for Modified C6............................................................................... 128 7.1.1.28. RA for Modified C7............................................................................... 129 7.1.1.29. RA for Modified C8............................................................................... 130
7.1.2. RA for Independent Variables ............................................................................... 131 7.1.2.1. RA for 30 Independent Items All Together.......................................... 131 7.1.2.2. RA for C5.............................................................................................. 132 7.1.2.3. RA for C6.............................................................................................. 132 7.1.2.4. RA for C7.............................................................................................. 133 7.1.2.5. RA for C8.............................................................................................. 133 7.1.2.6. RA for SC17 ......................................................................................... 134 7.1.2.7. RA for SC18 ......................................................................................... 134 7.1.2.8. RA for SC19 ......................................................................................... 135 7.1.2.9. RA for SC20 ......................................................................................... 135 7.1.2.10. RA for SC21 ......................................................................................... 136 7.1.2.11. RA for SC23 ......................................................................................... 136 7.1.2.12. RA for SC25 ......................................................................................... 137 7.1.2.13. RA for SC26 ......................................................................................... 137 7.1.2.14. RA for Modified C5............................................................................... 138 7.1.2.15. RA for Modified C6............................................................................... 138 7.1.2.16. RA for Modified C7............................................................................... 139 7.1.2.17. RA for Modified C8............................................................................... 139
7.2. MANOVA.................................................................................................................141 7.3. ANOVA....................................................................................................................243
7.3.1. ANOVA for CC and Marital Status ........................................................................ 243 7.3.2. ANOVA for CC and Education............................................................................... 244 7.3.3. ANOVA for CC and Department............................................................................ 245 7.3.4. ANOVA for CC and Title ........................................................................................ 246
7.4. MAC.........................................................................................................................248 7.4.1. MAC for CCC and Gender..................................................................................... 248 7.4.2. MAC for CCC and Marital Status........................................................................... 249 7.4.3. MAC for CCC and Education................................................................................. 250 7.4.4. MAC for CCC and Department.............................................................................. 251 7.4.5. MAC for CCC and Title .......................................................................................... 252 7.4.6. MAC for CC and Age ............................................................................................. 253 7.4.7. MAC for CC and Total Years of Emplooyed ......................................................... 253
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7.4.8. MAC for CC and Total Years of Emplooyement in Existing Company ................ 254 7.4.9. MAC for CC and Monthly Salary ........................................................................... 254
7.5. Multiple Regression..............................................................................................255 8. CONCLUSION................................................................................................. 263
9. LIMITATIONS .................................................................................................. 264
10. APPENDICES.................................................................................................. 265 10.1. Description of The Competency List ...............................................................265 10.2. Questionnaire ......................................................................................................277
10.2.1. Questionnaire in Turkish ........................................................................................ 277 10.2.2. Questionnaire in English........................................................................................ 294
10.3. Outputs of Findings............................................................................................311 11. REFERENCES ................................................................................................ 312
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TABLE LIST
Page No Table 1: Difference between Competence and Competency ................................................. 12 Table 2: Evaluation of Competency Approach and Definition................................................. 14 Table 3: Format of Competency Model for Each Function of Human Resource Management System........................................................................................................................................ 31 Table 4: Benefits of Competency Models in Human Resource Management Systems........ 33 Table 5: Competency Evaluation Form during the Interview .................................................. 38 Table 6: Competency Based Individual Development Plan .................................................... 41 Table 7: Advantages and Disadvantages of Data Collection Methods Interviews, Questionnaires and Observations ............................................................................................ 52 Table 8: Stages of Research Design........................................................................................ 68 Table 9: Advantages and Disadvantages of Data Collection Methods................................... 70 Table 10: Population and Sample Mean, Variance and Standart Deviation .......................... 74 Table 11: Statistical Tests Accoriding to Number of Dependent Variables and Groups ....... 80 Table 12: Different Error Probabilities in The Hypothetical Setting of Testing ....................... 82 Table 13: Null Hypothesis Testing for ANOVA ........................................................................ 87 Table 14: Multivariate Data Analysis in Regression ................................................................ 94 Table 15: List of Dependent and Indenependent Variables in Subgroup............................... 95 Table 16: List of Subgroups in the Dependent and Independent Variables the Initial Proposed Model......................................................................................................................... 96 Table 17: Modified Dependent and Independent List After Reliability Analysis ..................... 97 Table 18: First Modified Model - Total Scores of Sub Componets in Dependent and Independent Variables............................................................................................................... 99 Table 19: Second Modified Model ..........................................................................................100 Table 20: Core Concept in The Proposed Model ..................................................................100
vii
FIGURE LIST
Page No Figure 1: Factors Influencing Individual Competencies in Business Life.................................. 4 Figure 2: Competency Definition by David Mc Clelland ............................................................ 6 Figure 3: Identifying Success Factors Offered by David McClelland........................................ 6 Figure 4: Competency Definition by Richard Boyatsiz .............................................................. 8 Figure 5: The Iceberg Model of Competence Defined by Spencer L.M. JR. and Spencer S.M. .............................................................................................................................................. 9 Figure 6: Competency Definition by Dubois............................................................................. 10 Figure 7: Competency Definition by Klein ................................................................................ 11 Figure 8: Competency Definition by Woodruff'......................................................................... 11 Figure 9: Architectural model of competences Robert A. Roe................................................ 13 Figure 10: Layers of Factors Influencing Individual Competencies ........................................ 17 Figure 11: Proposed Competency Definition after the Evaluation of the All Definitions ........ 18 Figure 12: Relationship between Competency, Knowledge, Skills and Performance ........... 19 Figure 13: Competency Matrix.................................................................................................. 28 Figure 14: Competency Centric HRM System......................................................................... 30 Figure 15: Human Resource Management Role in Organization ........................................... 32 Figure 16: Aim of Competency Based Search and Selection Process................................... 34 Figure 17: Aim of Competency Based Interview...................................................................... 35 Figure 18: Competency Based Training Approach - Defining the Development Areas of a Person by GAP Analysis ........................................................................................................... 40 Figure 19: Competency Based Performance Management Assessment Card ..................... 44 Figure 20: The Elements of Continuous Change Management.............................................. 47 Figure 21: Proposed Competency Model................................................................................. 58 Figure 22: Dependent Variable List in Proposed Model .......................................................... 59 Figure 23: Independent Variable List in Proposed Model ....................................................... 60 Figure 24: Structure of Questionnaire Used in the Study........................................................ 71 Figure 25: Forms of Reliability .................................................................................................. 73 Figure 26: Split Half Reliability .................................................................................................. 78 Figure 27: Null Hypothesis Testing of MANOVA ..................................................................... 79 Figure 28: Modified Proposed Model......................................................................................101 Figure 29: Dependent Variable List in Modified Proposed Model.........................................102 Figure 30: Independent Variable List in Modified Proposed Model ......................................103
viii
FORMULA LIST Formula 1: Observed and True Scores with Error ................................................................... 73 Formula 2: Reliability of the Observed Test Scores ................................................................ 74 Formula 3: Expected Correlation between Test-Re Test Scores............................................ 75 Formula 4: Kuder Richardson Formula 20 ............................................................................... 77 Formula 5: Consistency Reliability Coefficient Cronbach Alpha ............................................. 77 Formula 6: General Forms of Multivariate Analysis of Variance............................................. 79 Formula 7:Statistic Value for Skewness................................................................................... 84 Formula 8: Statistic Value for Kurtosis...................................................................................... 84 Formula 9: General Forms of Analysis of Variance ................................................................. 87 Formula 10: t Statistics .............................................................................................................. 88 Formula 11: F Statistics............................................................................................................. 88
1
INTRODUCTION
Ups and downs in the economy are transforming the ways of conducting the
business for individuals and organizations. Adapting to such a fast changing environment
requires different approaches and abilities. Since the past experience and success stories
can be trivial to sustain in this transition periods. Furthermore being a competent person,
having excellent leadership skills and other superior performance characteristics of a
business professional can be insufficient to achieve successful outcomes. Such a major
changes refers “New World Order” for every piece of business life. Effects of the
environmental changes on the individuals bring more risks and different responsibilities. It
also accelerates the necessity of adapting new situation. At this point the arising question
mark is which individual characteristics are vital to gather successful outcome for today
and for the future in the conditions of uncertainty and change.
In the history the major tragic events like many wars, financial crisis and socio-
political conflicts refer the major downturns and transformation in the business life. For
recovering and renewing the structure of existing business life after these chaos new
ideas, methodologies, solutions, products and services are emerged. These occur
because of in any conditions every organization aims to sustain a portion of profit and
business continuity. Achieving these targets requires not only the new investments but
also the effectiveness of business processes and individuals as two main components of
business. The activity area of the quality management and the business process
management provides various methodologies to increase the effectiveness of the business
processes. Same as the human resource management professionals studies on the
specific components of the individual’s performance to increase their contribution into the
company’s success.
Today the functionality of HR activities are covering very wide range of
applications such as starting from planning and analyzing based on the business
strategies, business activities and tasks, acquiring the right person for the right job,
developing personal capacities, managing and assessing the personal performance for
2
today and future. Each of these stages individual competences are strongly linked to the
business goals and its content. Therefore if the business affected by environmental
changes in positive or negative manner the competencies of individuals are effected as
well. If business needs transformation in changing environment to be able to sustain,
same as individual competencies need a transformation to survive.
The aim of this study is to identify the key competencies for the employees to be
able gather successful outcome under the fast changing conditions and the effects of
environmental sources on the individual’s competencies.
In the first section of the study the theoretical information collecting from various
academic and non-academic studies presents to explain the competency approach.
Besides an evaluation and interpretation for seven approaches examined specifically are
covered in the study. Furthermore the relationship between performance, skills and
competencies are showed. As a result of the evaluation of all definitions a competency
definition are proposed.
In the second section the usage of the competency in business life especially in
the area of human resource management are represented. Moreover the advantages and
disadvantaged of competency based approaches are discussed.
In the third section aim of the competency models are explained by showing the
various competency models. Furthermore the stages of competency model development
are represented. The difficulties to prepare a competency model are discussed as well.
In the fourth section the methods of measuring a competency are explained. As
example three different occupational inventories are examined. The advantages and
disadvantages of occupational inventories evaluated. Also two different methods
observation and interviews are explained to define the individual competencies.
In the fifth section proposed competency model of the study are introduced. The
variables as listed in the model are explained. Also the relationship between the main
factors is showed.
3
In the sixth section the methodologies of the research study explained. The aim of
the study, sources for collecting the research data information, method for collecting the
data and methods of data analysis are explained.
In the seventh section the findings of the analysis and modified model of the
proposed model are showed. According to all findings the result are discussed.
In the eight section conclusion of the study are represented. In the night section
limitation during the studies are explained. In the tenth appendices are listed. In the last
section references used in the study are listed.
4
1. COMPETENCY
1.1. Definitions of Competency
Importance of competency term has been increasing in business life due to the
strategic role of human resource management’s in the organizations. In addition to this
performance and efficiency issues depending on individuals’ competencies became more
critical subjects to sustain the profitable business in a competitive business world. In
changing and competitive business environment facing with the fast technological
development an individual competency interacts with various internal and external variables.
In this study it’s classified in three category level as shown in figure 1.
Figure 1: Factors Influencing Individual Competencies in Business Life Source: Prepared by Tulay Bozkurt
Basically competency term is a sort of two-edge notion including the components
related with the personal characteristic and activity area of a work. Therefore in the literature
Competency
Personal Characteristic
Work Content
Company Competencies
Environment Sources
Personal level
Organizational level
Socio-Economical level
5
there are many different definitions of the competency depending on the task or human
based approaches.
As a result of literature search there is no unique definition of competency. Although
there is no uniform explanation it is very obvious that performing a task successfully it is
needed to have some distinguished personal attributes and skills besides having required
knowledge. Those required personal competencies vary from task to task. For instance
concerning a person attributes whose specialist about mathematics varies depending on that
person’s job. If that person is teaching mathematic then the ability of act of telling is more
important as well as mathematics knowledge. On the other hand if that person is
academician then the deep analytical ability is required as well to gather successful
outcome.
In this study a number of definitions and methods will be examined to be able to
identify the context of the competency world.
1.1.1. Historical Development of Competency Studies
1.1.1.1. Competency Studies by David McClelland
Studying in the competency area was initiated by David McClelland defined
competency variables that could be used in predicting job performance. He claimed that
competencies were not biased by race, gender or socioeconomic factors. His study helped
to identify performance aspects not attributable to a worker's intelligence or degree of
knowledge and skill. 1
McClelland's competency methodology can be summed up by two factors as
using of criterion samples which is systematically comparing superior performing persons
1Scott Cooper, Eton Lawrence, James Kierstead, Brian Lynch and Sally Luce, April 1998
http://managementtrainingcourses.org/Lesson15CompetencyBasedHRM_Training.pdf
6
with less successful persons to identify success factors and identifying specific thoughts
and behaviors that are causally related to successful outcomes. 2
Figure 2: Competency Definition by David Mc Clelland Source: This representation is interpretation of Mc Clleland Competency Approach. Prepared by Tulay Bozkurt
Figure 3: Identifying Success Factors Offered by David McClelland Source: This representation is interpretation of David Mc Clleland Competency Approach. Prepared by Tulay Bozkurt
2 Scott Cooper, Eton Lawrence, James Kierstead, Brian Lynch and Sally Luce, April 1998 http://managementtrainingcourses.org/Lesson15CompetencyBasedHRM_Training.pdf
D e f i n i n g
C o m p a r i n g
Superior Performing Person
Less Successful Person
Specific Thoughts
Specific Behaviors
Success Factors I d e n t i f y i n g
Competencies Job Performance
P r e d i c t i n g
Gender, Race or Socioeconomic Factors
Intellegence & Degree of Knowledge
Not biased by
7
The main advantages of Mc Cleland he claims that intelligence and school grade
can not be a major factor that influences the level of individual’s performance. He states that
an intelligent person can show poor performance at work when compared with less
intelligent person. Therefore it is not always valid to determine performance criteria’s
according to intelligence level and school grade.
On the other hand economic conditions in fast chancing environment affect the
business activities strongly. Since there is a relationship between individual competencies
and business competencies at organizational level the socio-economic conditions affects the
individual’s performance and competencies. Besides continuous learning empowered the
knowledge of individual and gathering more information brings new ideas and creativity to
the business there is also strong relations between usage of competencies and the degree
of knowledge.
Comparing superior performance with less successful person can not be a model
for every situation since the competency level can be changed depending different business
case and tasks. A person can be more competent on a job but same person can be less
competent on other task since the different level of experiences varies.
In the proposed model of this study, various competencies including personal
behaviors, knowledge, degree of specialties and environmental sources like economic
conditions, company core competencies will be in the set of competencies.
1.1.1.2. Competency Studies of Richard Boyatsiz
The McClelland approach and the concept of competencies as key drivers of
organizational success found a widespread audience and popularity with Richard Boyatzis.
Boyatzis notes that a person’s knowledge and skills are the traditional competencies that
individuals bring with them to their jobs or acquire while on the job. This is only part of an
individual’s compendium of job competencies. Motives or social roles can be considered
8
competencies when use can be shown to directly contribute to the successful achievement
of one or more job outputs or results. 3
Boyatzis defines work competency as an underlying characteristic of a person
which can be a motive, a trait, a skill, an aspect of his personal image or of his social role,
or a body of knowledge which he or she uses. This definition shows competency to be a
mix of a number of things (motivation, personal traits, skills, knowledge, etc.), but it can be
seen the evidence of these things in the way in which the person behaves. 4
Figure 4: Competency Definition by Richard Boyatsiz Source: This representation is interpretation of Richard Boyatsiz Competency Approach. Prepared by Tulay Bozkurt
According to Boyatsiz’ approach the set of characteristics of a person defines the
competencies and these competencies shape the behaviors. Performance indicators are the
behaviors as underlying characteristics of competencies. Basically behaviors are the
outcome of the underlying characteristic of a person such as motives, desires, feelings and
thinking styles. The various behaviors indicators form specific competencies.
3 Scott Cooper, Eton Lawrence, James Kierstead, Brian Lynch and Sally Luce, April 1998 http://managementtrainingcourses.org/Lesson15CompetencyBasedHRM_Training.pdf 4 Richard Boyatsiz, The Competent Manager, 1982
Performing
Evidence of a Person Behaviors Underlying Characteristic of a Person
Motives
Traits
Skills
Knowledge
Competencies
Acting
Performing
Relating to Others
Behaving
Underlying
9
1.1.1.3. Competency Studies of L.M. Spencer and S.M. Spencer
The definition and structure of the competence given by L.M Spencer and S.M.
Spencer as five types of competence characteristics in the Iceberg Model, the competence
is an individual underlying characteristic (the competence is a fairly deep and enduring
part of a person personality and can predict behavior in a wide variety of situation and job
tasks) that is causally related (that the competence causes or predicts behavior and
performance) to criterion referenced effective and superior performance in a job or
situation (that the competence actually predicts who does something well or poorly as
measured on a specific criterion or standard)5
Figure 5: The Iceberg Model of Competence Defined by Spencer L.M. JR. and Spencer S.M. Source: Spencer, L. M. JR. & Spencer, S. M., Competence at Work: Model for Superior Performance, John Wiley & Sons, p.11, 1993.
The visible part of the iceberg knowledge and skill called as qualification is
important but not the deepest level of the competence structure. Knowledge understand
information a person has in specific content areas and a skill describe as the ability to
perform a certain physical or mental task are in a certain way cautious while giving
comments on knowledge as visible elements of the competence.
5 Spencer, L. M. JR. & Spencer, S. M., Competence at Work: Model for Superior Performance, John Wiley & Sons, p.11, 1993.
Skills Knowledge
Self Concept Personel Characteristics
Motives
Hidden Part
Visible Part
10
1.1.1.4. Competency Studies of David Dubois
David Dubois defines competence as the employee's capacity to meet (or
exceed) a job's requirements by producing the job outputs at an expected level of quality
within the constraints of the organization's internal and external environments.
He goes on to adapt Boyatzis' definition of competency and states that a job
competency is an underlying characteristic of an employee like motive, trait, skill, aspects
of one's self-image, social role or a body of knowledge-- which results in effective and/or
superior performance in a job.6
Figure 6: Competency Definition by Dubois Source: This representation is interpretation of David Dubois Competency Approach. Prepared by Tulay Bozkurt
1.1.1.5. Competency Studies of Kleins
Klein's definition diverges the most from the others by suggesting that
competencies are a collection of observable behaviors, or behavioral indicators. These
behavioral indicators are grouped according to a central theme, which then becomes the
6 Scott Cooper, Eton Lawrence, James Kierstead, Brian Lynch and Sally Luce, April 1998 http://managementtrainingcourses.org/Lesson15CompetencyBasedHRM_Training.pdf
Motive
Trait
Social Role
Knowledge
u n d e r l y i n g Competencies Effective Performance
r e s u l t i n
11
competency. 7Klein suggests that the behaviors underlie the competency; this is contrary
to other definitions which suggest that competencies underlie behaviors8.
Figure 7: Competency Definition by Klein Source: This representation is interpretation of Klein Competency Approach. Prepared by Tulay Bozkurt
1.1.1.6. Competency Studies of Woodruff
Woodruff raised the issue of distinguishing between competence and competency
and proposed that competence is a performance criterion while competencies are the
behaviors driving the competence. 9
Figure 8: Competency Definition by Woodruff' Source: This representation is interpretation of Woodruff Competency Approach. Prepared by Tulay Bozkurt
7 Scott Cooper, Eton Lawrence, James Kierstead, Brian Lynch and Sally Luce, April 1998 http://managementtrainingcourses.org/Lesson15CompetencyBasedHRM_Training.pdf 8 Andrew L. Klein, Validity and Reliability for Competency-Based Systems: Reducing Litigation Risks, 1996, p. 31-37 9 Woodruff, C. What is meant by a competency? Leadership and Organizational Development Journal, 1993 p 14
Competencies = Behaviours d r i v i n g
Competence = Performance Criterion
Set of Behaviours
Underlying Competencies
12
In general definition competence is the basic requirement to perform a job. On
the other hand competencies are the knowledge, skills and attributes (KSA) that
distinguish superior performers from average performers.
Table 1: Difference between Competence and Competency No Term Main Focus Definition
1 Competence Competences Task - Job
Competences are the tasks a person is capable of performing
2 Competency Competencies Person
Competencies are the personal characteristics which make work performance possible
The competence term basically states for the area of activities which a person is
competent. These are specific, observable ways conducting a given task which an
individual is capable of carrying out according to a prescribed performance standard. In
this case, indicating a person’s competences means listing the main tasks of a particular
job he/she is capable to performing. For instance it can be making a presentation, writing a
research paper for an academic work.10
On the other hand the competency term focuses on personal characteristic
allowing an individual to perform in an area of the competence. Competencies can be
attributes which allows the optimum execution of a particular task in a given organization.
Each personal characteristic generally utilize in the workplace regardless of the nature of
the work or level of performance achievable through its use. For instance personal
characteristic which allows a person to be able to make a presentation, write a research
paper.
10 Woodruff, C. What is meant by a competency? Leadership and Organizational Development Journal, 1993 p 14
13
1.1.1.7. Competency Studies of Robert A. Roe
The concept of competence is defined as ‘the acquired ability to adequately
perform a task, mission or role’ and offers the opportunity to arrange and relate a diversity of
competence concepts by Dr. Leo. This way it becomes possible to indicate how
competences relate to a person’s other features. Thus it is the key to the integration of
theory and practice. 11The model is shaped like a Greek temple and can be interpreted –
without the pretence of literal translation – as follows:
Figure 9: Architectural model of competences Robert A. Roe
Source: Robert A. Roe Architectural model of competences
Competences are based on sub competences and on knowledge, skills and
attitudes. They are created by means of a learning process in the actual (or simulated) work
situation. Knowledge, skills and attitudes in their turn are created by means of learning
11 Robert A. Roe, Architectural model of competences
Personality
Other characteristics
Capacity
Competences
Subcompetence / Basic competences
Know
ledg
e
Skills
Attit
ude
14
processes that have taken place partly at work, partly at school and partly in daily life.
Intellectual aptitude, personality and other features determine what is learned. Knowledge,
skills and attitudes (represented by the columns in the figure) are therefore based on the
foundation of rudimentary dispositions (the foundation of the temple), whereas they in their
turn carry the sub-competences and competences.
1.1.2. Evaluation of The Competency Definitions
Although there is lack of a uniform definition, there are three common
components to these definitions as following
1. Knowledge, skills, abilities and other characteristics underlie effective or
successful job performance
2. Underlying attributes observable and measurable
3. Underlying attributes distinguish between superior and other performers
First, most of these definitions suggest that competencies are the knowledge,
skills, abilities and other characteristics that underlie effective or successful job
performance. These underlying attributes must be observable or measurable and these
underlying attributes must distinguish between superior and other performers.
Competencies are measurable attributes that distinguish outstanding performers from
others in a defined job context.
In this section of the study an evaluation of all definition is presented in table 2.
Table 2: Evaluation of Competency Approach and Definition
No Theory Definition Evaluation
1 David Mc
Clelland
Determine the individuals
performance based on their
competencies not only school
There are various factors
effecting the individual
competencies as classified
15
grade or level of intelligence
Competencies are not biased by
gender, degree of knowledge,
socio-economic factors
To define success factors it’s
suggested to compare the
competencies of superior
performance with poor
performance
internal factors related with
individuals characteristics
and external factors
influencing by task,
organization and
environment
Comparing superior
performance and poor
performance to define the
success factors can not be
used every situation since
the competency level of an
individual changes for
different tasks.
2 Richard
Boyatsiz
There are several underlying
characteristics of a competencies
like motives, knowledge, skills
and social roles
The behaviors and performance
are the outcome of the
competencies
Basically competencies
include a set of behaviors
underlying by motives,
thinking styles, knowledge
and other personal
characteristics
Performance occurs as a
result of specific behaviors
and competencies
3 Spencer&Spenc
er
5 characteristics as hidden and
visible part of the competencies
showed in the iceberg model
Competence can predict the
behaviors specific to a job as
success factors
Iceberg model effectively
present the dynamics of a
person characteristics
External factors effecting
internal factors can be
added to the model as
competencies
16
Set of competency can be
defined for each job profiles
as pre-required qualification
for a person
4 David Dubois Competency is the employee’s
capacity to meet a job
requirement by producing the
performance output
Competencies are not only
the capacity of a person. It
can be defined as a
dynamic term effecting by
external and internal factors
and changes in positive
and negative manners.
5 Klein Competencies the underlying
characteristic of the different
behaviors
Competencies include
various behaviors
depending on a person
characteristics and job
requirements.
It can be defined as in
different levels.
6 Woodroof Competency is characteristic of a
person. Competence is a
requirement for a job
Competency term includes
both personal
characteristics and specific
requirements for a job
7 Robert Roe Competencies include sub
competencies that represented in
temple model. Sub-
competencies are the outcome of
eight different characteristics of a
person.
External factors can be
added to the model
Source: This evaluation is prepared by Tulay Bozkurt
17
As a result of evaluation of all definitions a competency is a set of behaviors that
determines the level of performance in a particular work context (job, role or group of jobs,
function, or whole organization). Competencies enable employees to achieve results,
thereby creating value. It provides a roadmap for the range of behaviors. It follows that
competencies aligned with business objectives help foster an organization’s success.
Organizations should understand their core competency needs, the skills, knowledge,
behaviors and abilities that are necessary for people in key roles to deliver the results. All
of the organization interacts with their surroundings. In this context the environment as
sector, market, competitors, dealers, vendors, governments, and countries affects the
organization activities in positive or negative perspective.
Figure 10: Layers of Factors Influencing Individual Competencies Source: Prepared by Tulay Bozkurt
Individual
Work-Team
Organisation
Environment
18
Figure 11: Proposed Competency Definition after the Evaluation of the All Definitions Source: This representation is prepared by Tulay Bozkurt as a result of the evaluation of all
definitions
1.1.3. Relationship Between Competencies, Knowledge, Skill and Performance
“Competent performance” occurs when an individual achieves or produces some
result or output at the level of quality established for it within the constraints or opportunities
of the performer’s internal and external environments. In organizations, employees are
frequently faced with the dilemma that they know how to perform the work that is expected
of them, but there are constraints, or performance roadblocks which they are powerless to
remove and that impede their “competent performance.” The organization’s customers,
clients, or constituents are the victims of this situation. 12
12 David Dubois, Competency-Based Performance Improvement: A strategy For Organizational Change, 1993
Set o
f Com
pete
ncie
s
Personal Characteristic
Work Content
Company Competencies
Environment Sources
Set o
f Beh
avio
rs
Success Factors
19
Figure 12: Relationship between Competency, Knowledge, Skills and Performance
1.1.3.1. Definition of Knowledge
Knowledge is defined variously as expertise and skills acquired by a person
through experience or education; the theoretical or practical understanding of a subject,
what is known in a particular field or in total; facts and information or awareness or familiarity
gained by experience of a fact or situation.
Knowledge acquisition involves complex cognitive processes: perception, learning,
communication, association and reasoning. The term knowledge is also used to mean the
confident understanding of a subject with the ability to use it for a specific purpose if
appropriate.
competency
motives& attitıdes
skills
knowledge& experience
20
1.1.3.2. Definition of Skill
A skill is the learned capacity to carry out pre-determined results often with the
minimum outlay of time, energy, or both. Skills can often be divided into domain-general and
domain-specific skills. For example, in the domain of work, some general skills would include
time management, teamwork and leadership, self motivation and others, whereas domain-
specific skills would be useful only for a certain job. Skill usually requires a certain
environmental stimuli and situation to assess the level of skill being shown and used13
1.1.3.3. Definition of Performance
Performance is a deliberate and purposeful action or set of actions that an
individual takes in order to achieve a desired result or output of some kind that is of value to
the individual or to others. An “output” or “result” is a product or a service, respectively, that
an individual delivers to others, possible including coworkers, clients, customers, or
constituents. 14
Performance of any kind occurs in a context, such as in one’s home, the workplace,
in a public meeting, or even when one is sleeping. The performance context includes the
circumstances that are part of the performer’s internal and external environments. The terms
“internal” and “external” can be defined relative to the individual’s inner versus outer states,
the geographic location where the performance takes place or if in an organization context,
that which is part or not part of the organization.
Work performance in terms of quantity and quality expected from each employee.
Job performance most commonly refers to whether a person performs their job well. Despite
the confusion over how it should be exactly defined, performance is an extremely important
criterion that relates to organizational outcomes and success. John Campbell describes job
performance as an individual level variable. That is, performance is something a single
13 http://en.wikipedia.org/wiki/Skill 14 David D. Dubois, What are Competencies and Why are They Important? http://www.careertrainer.com/Request.jsp?lView=ViewArticle&Article=OID%3A112397
21
person does. This differentiates it from more encompassing constructs such as
organizational performance or national performance which are higher level variables.15
There are several key features to this conceptualization of job performance which
help clarify what job performance means. Performance is defined as behavior done by the
employee. This concept differentiates performance from outcomes. Outcomes are the result
of an individual’s performance, but they are also the result of other influences. In other
words, there are more factors that determine outcomes than just an employee’s behaviors
and actions. Campbell allows for exceptions when defining performance as behavior. For
instance, he clarifies that performance does not have to be directly observable actions of an
individual. It can consist of mental productions such as answers or decisions. However,
performance needs to be under the individual's control, regardless of whether the
performance of interest is mental or behavioral.16
The difference between individual controlled action and outcomes is best conveyed
through an example. On a sales job, a favorable outcome is a certain level of revenue
generated through the sale of something. Revenue can be generated or not, depending on
the behavior of employees. When the employee performs this sales job well, he is able to
move more business. However, certain factors other than employees’ behavior influence
revenue generated. For example, sales might slump due to economic conditions, changes in
customer preferences, production bottlenecks. In these conditions, employee performance
can be adequate, yet sales can still be low. The first is performance and the second is the
effectiveness of that performance. These two can be decoupled because performance is not
the same as effectiveness.
Another closely related construct is productivity. This can be thought of as a
comparison of the amount of effectiveness that results from a certain level of cost associated
with that effectiveness. In other words, effectiveness is the ratio of outputs to inputs- those
inputs being effort, monetary costs, and resources. Utility is another related construct which
is defined as the value of a particular level of performance, effectiveness, or productivity.
Utilities of performance, effectiveness, and productivity are value judgments.
15 Campbell, J. P., McCloy, R. A., Oppler, S. H., & Sager, C. E. A theory of performance, 1993 16 http://en.wikipedia.org/wiki/Job_performance
22
Campbell also suggested determinants of performance components. Individual
differences on performance are a function of three main determinants: declarative
knowledge, procedural knowledge and skill, and motivation17.Declarative knowledge refers
to knowledge about facts and things. It represents the knowledge of a given task’s
requirements. For instance, declarative knowledge includes knowledge of principles, facts. If
declarative knowledge knows what to do, procedural knowledge and skill knows how to do it.
For example, procedural knowledge and skill includes cognitive skill, perceptual skill, and
interpersonal skill.
The third predictor of performance is motivation, which refers to “a combined effect
from three choice behaviors, choice to expend effort, choice of level of effort to expend, and
choice to persist in the expenditure of that level of effort”. It reflects the direction, intensity,
and persistence of volitional behaviors. Campbell emphasized that the only way to discuss
motivation as a direct determinant of behavior is as one or more of these choices.
As a result performance is conceptualized as a multidimensional construct. This
means that performance consists of more than one kind of behavior. There are various
concepts to proposed factor based model of performance based on factor analytic research.
17 Campbell, J. P., McCloy, R. A., Oppler, S. H., & Sager, C. E. A theory of performance, 1993
23
2. COMPETENCY MODELS
A competency model is a collection of competencies that together define
successful performance in a particular work setting. A competency model refers to a group
of competencies required in a particular job and usually number seven to nine in total. The
number and type of competencies in a model will depend upon the nature and complexity
of work along with the culture and values of the organization in which the work takes place.
Competency models can be developing for specific jobs, job groups, organizations,
occupations or industries.18
Competency models are the foundation for important human resource functions
such as recruitment and hiring, training and development and performance management
since they specify what is essential to select for or to train and develop.
Competency models specifically include the following elements:
1. Competency names and detailed definitions
2. Descriptions of activities or behaviors associated with each competency.
3. A diagram of the model presenting of the model in graphical form to help
users quickly grasp the key feature of the model
In the organization, competency models and systems can help:
1. Improve the selection of people for jobs
2. Develop skills and characteristics that lead to improve effectiveness and
productivity
3. Provide a consistent framework for Human Resource applications
4. Build alignment with organizational values and strategy
18 Spencer, L. M., & Spencer, S. M. (1993). Competence at Work
24
2.1. Development of Competency Models
Competency models are developed through a process of clarifying the business
strategy and determining how models would be used in for example hiring and selection,
assessment, performance management, training and development and career
development. After that data is gathered in structured interviews, observations, surveys or
some other ways. As final step data is analyzed and used to develop a model of success
criteria. 19
Steps for competency model development process:
1. Performance criteria: Defining the criteria for superior performance in the
role
2. Criterion sample: Choosing a sample of people performing the role for data
collection
3. Data collection: Collecting the sample data about the role for data collection
4. Data analysis: Developing hypothesis about the competencies of
outstanding performers and how these competencies work together to
produce desired results.
5. Validation: Validating the results of the data and analysis
6. Application: Applying the competency model in human resource activities,
as needed.
The elements of a competency model are identified by performing inquiries in the
organization or setting in which the performance described in the model will occur. At the
beginning the detailed information are gathered on the desired performance and defined
how it relates to the organization’s strategic setting. Furthermore the performance outputs
or results expected of an employee are enumerated. Opportunities for, and constraints
19 http://www.schoonover.com/competency_faqs.htm
25
upon performance are identified, and the tasks that persons perform to achieve the results
or outputs are documented. Next, the performance tools, or competencies an individual
uses to successfully complete the tasks and achieve the results or outputs are researched
and documented.
When competencies are being identified, impacts of the organization’s culture
upon the use of them for successful or exemplary performance are determined. This
information is reflected in the behavioral indicators for each competency. Behavioral
indicators describe when an individual is using a competency in appropriate ways within
an organization’s cultural context to achieve outputs or results. They help an observer of
the performance answer the question: is the employee doing their assigned work “the
company way?” Organization employees must, in order to be fully successful, conform to
certain organization cultural norms and ways of accomplishing work outputs or results.
Behavioral indicators help employees and their managers know how to do that. Further,
behavioral indicators provide both parties to work transactions with a common foundation
for holding performance and development planning discussions.
2.2. Types of The Competency Models
As stated in the competency development there are different types of competency
models including the specific competencies depending on the function of a work and
required role for a position? Therefore each the models are including the set of
competencies to do the job successfully.
Some examples of the basic models are listed as following:
1. Occupational competency models
2. Job, Functional or Role competency models
3. Core competency models
4. Leadership competency models
26
2.2.1. Occupational Competency Model
An occupational competency model covers a broad occupational area and
includes multiple levels of work20. Each of the elements of competencies is changing
according to occupations as Accountant, Engineer, Doctor or Teacher.
1 Relevant to specific types of work
2 Behaviors that contribute to success in the occupation
3 Include necessary knowledge and skills
Typically competencies in occupational models include sub categories.
Occupational models provide the foundation for identifying the critical knowledge
competencies in that occupation. These models have broad based applicability to multiple
work units and jobs.
2.2.2. Job Competency Model
A job competency model describes job or role competencies often those specific
to a certain type of job within a specific work unit. The competencies can various for the
sales, finance, manufacturing and service functions of the company. 21
1 Specific to a position or group of positions or roles
2 Related to work unit goals and objectives
3 Linked to organization’s vision and business strategy
These models provides a good foundation for building performance appraisals or
individual training and development plans since specific behavioral and knowledge
competencies tie directly to certain types of jobs or roles within a work unit or organization.
20 A Guide to Integrating Competencies into human Resource Program, 2000 21 A Guide to Integrating Competencies into human Resource Program, 2000
27
A job competency model is a description of those competencies possessed by the
top performers in a specific job or job family. In effect, a competency model is a "blueprint
for outstanding performance". Models usually contain 8-16 competencies with definitions,
often grouped into "clusters" along with behavioral descriptors. As an Individual, job
competency models can guide career development.
2.2.3. Core Competency Model
Core competency models are built through a process of continuous improvement
and enhancement. They focus for corporate strategy. Core competencies are those
capabilities that are critical to a business achieving competitive advantage. The starting
point for analyzing core competencies is recognizing that competition between businesses
is as much a race for competence mastery as it is for market position and market power.
1 The key core competencies here are those that enable the creation of new
products and services
2 Skills in customer relationship management
2.2.4. Leadership Competency Model
Leadership translates vision into reality by inspiring followers to want to
experience the change process. And to influence their followers to willingly jump into that
experience, leaders need a specific set of competencies to guide their actions. Although
competencies will always differ from one leader to the next, having a core set to draw from
increases their chance for success. These competencies can be thought of as the inner
tools for motivating employees, directing systems and processes, and guiding the
business towards common goals that allow the organization to increase its value.
28
2.3. Competency Matrix
The competency matrix includes a list of behavioral statements and the
associated quality values for each competency at several employee levels as managers,
supervisors, executives, subordinates. The purpose is to help employees understand their
contribution, through their individual performance, to the companies commitment to
commitment to quality and to help supervisors evaluate the demonstration of these
competencies through the use of observable behavioral statements.
Figure 13: Competency Matrix Source: http://www.intechenvironmental.com/competence_matrix.jpg
29
A competency matrix consists of several competency models depending on the
occupation, job, position and a role in the organization. In the matrix weight of each
competency can be defined according to the personal, functional and organizational level.
Besides a competency matrix provide a sort of competency map that enable to plan
individual development needs, performance management assessment criteria’s and
succession planning. An organization can have specific information about the
competencies of their total number of employee and predict the work force needs for future
in a flexible and easy to control system.
30
3. USAGE OF COMPETENCIES
A competency based approach provides many advantages for use in human
resource planning, selection and development. It provides a clear framework for both
defining what response the business needs from personnel, and for assessing the
potential fit of applicants.22
Competencies provide significant help with the key problems of organizations
such as:
1. Clarifying workforce standards and expectations
2. Aligning individuals, teams and managers with the organization’s business
strategies
3. Creating empowerment, accountability and alignment of managers, team
members and employers in performance development
Figure 14: Competency Centric HRM System Source: Spencer, L. M. JR. & Spencer, S. M., Competence at Work: Model for Superior Performance pg.315,
1993
22 Spencer, L. M. JR. & Spencer, S. M., Competence at Work: Model for Superior Performance, 1993
Organization capabilities and HRM strategy
Competency Centric
Team Building
Pay & Reward
Career Planning Performance management
Management Development/ Succession
Training & Development
Recruitment
31
Table 3: Format of Competency Model for Each Function of Human Resource Management System
Use Formats
Selection Competency with definition
List of interview questions to elicit information about relevant behaviors
Interviewee rating from providing a continuum of unacceptable to acceptable
behavior examples
Training and
Development
Three to six behavior examples for each competency that describes
exceptional performance
Rating scale for frequency or effectiveness of competency
Rating scale of importance or future role
List of workshops or development experiences available for skill
improvement
Performance
Appraisal
Description of three to five levels of effectiveness for each competency form
above standard to below standard
Checklist with each specific behavior
Succession
Planning
Competency with description of behavior/ability required to perform the job
Rating process to indicate current level of ability
Suggestions for how to develop competency
Source: Lucia&Lepsinger, the Art and Science of Competency Model, 1999
32
3.1. Function of Human Resource Management in The Organizations
The goal of human resource management (HRM) is to help an organization to meet
strategic goals by attracting and maintaining employees and also to manage them
effectively. HRM approach seeks to ensure a fit between the management of an
organization's employees, and the overall strategic direction of the company.23
The HRM function includes a variety of activities, and key among them is deciding
what staffing needs, recruiting and training the best employees, ensuring they are high
performers, dealing with performance issues, and ensuring the personnel and management
practices conform to various regulations. Activities also include employee benefits and
compensation, employee records and personnel policies.
Figure 15: Human Resource Management Role in Organization
23 http://en.wikipedia.org/wiki/Human_Resource_Management
ORGANISATION Mission, Vision, Objectives
ORGANISATION STRATEGY HUMAN RESOURCE MANAGEMENT STRATEGY
Human Resource Policy and Process
Organization Structure&Planning Search and Selection
Management by Objectives Performance Management
Training and Development Talent & Succession Management
Compansation Management Adminisration
33
Table 4: Benefits of Competency Models in Human Resource Management Systems Function Benefits
Selection Provides a complete picture of the job requirement
Increase the likelihood of hiring people who will succeed in the job
Minimizes the investment(both time and money) in people who may not
meet the company’s expectations
Ensures a more systematic interview process
Helps distinguish between competencies that are trainable and those that
are more difficult to develop
Training and
Development
Enables people to focus on the skills, knowledge and characteristics that
have the most impact on the effectiveness
Ensures that training and development opportunities are aligned with
organizational values and strategies
Makes the most effective use of training and development time and money
Provides a framework for ongoing coaching and feedback
Appraisal Provides a shared understanding of what will be monitored and measured
Focuses and facilitates the performance appraisal discussion
Provides focus for gaining information about behavior on the job
34
Succession
Planning
Clarifies the skills, knowledge and characteristics required for the job or role
in question
Provides a method to assess a candidate’s readiness for the role
Focuses training and development plans to address missing competencies
Allows an organization to measure its number of high-potential performers
Source: Lucia, &Lepsinger, pg.23
3.1.1. Competency Based Search and Selection Process
A competency based search and selection process provides to find the appropriate
people with an appropriate selection process. Each of the candidate’s skills and interests
can be different as well as the different job requirements. Competency based selection is the
process of matching these skills and interests of a person to the requirements of a job.
Finding a good job "fit" is exceptionally important and it’s more accurate with competency
based approach. After defining the competency factors for each positions it’s important to
conduct a competency based interview to find the best job-fit for candidates and employees.
Figure 16: Aim of Competency Based Search and Selection Process Source: This representation is prepared by Tulay Bozkurt
Candidate Competency
Company&Job Competency BEST
FIT
35
Competency-based interviews are based on the premise that past behavior is the
best predictor of future behavior. Interviewers seek to obtain information about candidates
past behavior in a certain situations to predict their future behavior. Basically competency-
based interviews are structured with questions that relate directly to the essential criteria and
competencies required for the post.
Figure 17: Aim of Competency Based Interview Source: It is prepared by Tulay Bozkurt
A good recruitment and selection interview should assess candidates against each
essential criteria or competency, asking questions about:
1. Past behaviors and performance
2. Learning from past behaviors
3. Future adaptability to new post
4. Knowledge and understanding of issues in relation to the post
Past Today
Future
CV Education Experience
Interview Appearance Communication Motives Ability
Fit into Company and Team
36
Examples of competency-based interview questions are here:
1. Leadership
a. What makes you a good leader?
b. What type of leadership style do you adopt?
c. How would those you have leaded describe you?
2. Delegating
a. Explain a mistake you have made in delegating- what were the
consequences?
b. In what instance would you delegate a task?
c. What are the advantages of delegating?
3. Conflict&Pressure
a. Give an example of an instance when you have had an argument
with someone at work? What was the outcome?
b. How do you react if your boss asks you to do something which
conflicts with your own deadlines?
4. Teamwork
a. Do you prefer to work alone or in a group?
b. When you joined your last company, how did you get on with your
co-workers?
5. Staff Motivation and Development
a. What makes a good manager?
37
b. How you motivate staff?
6. Personal Motivation
a. What are the three most important events in your career to date?
b. What are your standards of success in your job?
7. Decision Making
a. What is the toughest decision you have had to make while at your
present company? Tell me about it. What alternatives did you
consider?
b. What has been the effect of your decisions on others and what was
the wider impact?
38
Table 5: Competency Evaluation Form during the Interview Communication: Clearly conveys and receives information and ideas through a variety of media to individuals or groups in a manner that engages the listener, helps them understand and retain the message and invites response and feedback. Keeps others informed as appropriate. Demonstrates good written, oral, and listening skills.
Greatly
Exceeds Expectations
Exceeds Expectations
Meets Expectations
Occasionally Meets
Expectations Unsatisfactory
Key Element
Organization and Clarity
Listening Skills
Keeping Others Informed
Written Communication
Sensitivity to Others
Comments:
Source: http://portal.cornerstones4kids.org/stuff/contentmgr/files/ 5c06cb455ff52c94d8a9d0294e75469f/folder/gapclose_tool_4perf_mgmt.doc
39
3.1.2. Competency Based Training System
Competency based training provides the improvement in specific areas of
individuals and flexibility for the training management in the organizations. At the first stage
evaluation of individual competencies identifies the strengths and development points of
each individual.
The characteristics of competency based training as Kirkpatrick and Parry specified
are as follows24:
1. Competency-based training addresses and integrates all three components
of human behaviors: knowledge, attitudes and skills.
2. Competency-based approach is generic and universal; the effectiveness
evaluation for composition of KAS training is much. Therefore there is greater return on
investment if not focus only single K, A, or S.
3. There is a close correlation between competency-based training and
organization learning. Courses promote team building and common culture where everyone
speaks the same language of competencies.
24 Case Study On Training Needs Survey Using Competency-Based Approach Eric Tseng, Human Resource & Services Center 1999 Asia Pacific Decision Sciences Institute Conference, Shanghai, 1999.
40
02468
Leadership
Communication
Flexibility
Responsibility
Decisiveness
TodayFuture
Figure 18: Competency Based Training Approach - Defining the Development Areas of a Person by GAP Analysis
Source: It is prepared by Tulay Bozkurt
Training programs for each level of positions should be specific, inappropriate
training programs may create negative impacts on individual performance. Therefore before
conducting the training programs individual and team needs related with the goals that the
organization is attaining should be examined. Furthermore, job analysis to determine the
competencies that employees’ hold is critical in order to ensure the accountabilities
achievable. A successful competency-based training have to deal with the needs and
personal interest of the employees and all level of organization needs.
41
Table 6: Competency Based Individual Development Plan
Individual Development Plan
Competency to Develop Developmental Activities Target Date Date
Completed Supervisory Comments
1 Attend 1-day workshop on “Improve Your Listening Skills” 4/15/200x
2 Complete web-based training - “Enhancing your Presentation Skills”
6/30/200x
3 Read book “Communicate with Confidence” 9/30/200x
Communication
4 Join Toastmasters and attend at least 4 meetings during the year. 12/31/200x
Competency to Develop
1 Attend workshop “Strengthening the Agency Through a Diverse Workforce”
2/17/200x
2 Read book: Understanding Yourself from the Perspective of Others”
7/30/200x
3 Join the agency’s Diversity Coalition and attend all meetings during the year
12/31/200x Cultural Competence
4
Competency to Develop
1 Attend “Team Decision Making” training 3/22/200x
2 Establish an ongoing working relationship with a colleague from 3 community agencies.
12/31/200x
3 Using one of my cases as an example prepare and deliver a 10-minute presentation at staff meeting about how family/community involvement provided a positive case outcome.
5/30/200x Collaboration
4 Source: http://portal.cornerstones4kids.org/stuff/contentmgr/files/ 5c06cb455ff52c94d8a9d0294e75469f/folder/gapclose_tool_4perf_mgmt.doc
42
3.1.3. Competency Based Performance Management System
Performance management is the process of creating a work environment or setting
in which people are enabled to perform to the best of their abilities. Performance
management is a whole work system that begins when a job is defined as needed. It ends
when an employee leaves the organization25.
Competency-Based Performance Management includes
1. Setting performance objectives
2. Determining the competency expectations
3. Fairly evaluating employees
4. Giving constructive feedback and
5. Continuously communicating and dealing with difficult evaluations.
Performance objectives can be setting on determined the competencies in the job
descriptions. Job descriptions are the first step in selecting the right person for the job, and
setting that person up to succeed. Competency based job descriptions provide a framework
so the applicants and new employees understand the expectations for the position. 26
Assessment through predetermined competency sets creates more transparent
and objective performance management process for the employees and supervisors.
Through the competencies it is also easy to manage and measure the performance.
Besides competency based performance management system provides effective
orientation, education, and training. Before a person can do the best job, he or she must
have the information necessary to perform. This includes job-related, position-related, and
company-related information; an excellent understanding of product and process use and
requirements; and complete knowledge about customer needs and requirements. The
25 http://humanresources.about.com/od/performanceevals/a/performancemgmt.htm 26 Ferdinand F. Fournies, Why Employees Don’t Do What They’re Supposed to Do and What to Do About It, 1999
43
system provides on-going coaching and feedback based on competency level. By the help
of conducting quarterly competency based performance development discussions provides
supervisors giving employees frequent feedback and coaching.
Output of competency based performance management system link to the
compensation and recognition systems that reward people for their contributions. It also
provides promotional and career development opportunities for employees.
44
Competency Based Performance Management Assessment Card
Competencies are defined as the knowledge, skills, behaviors, personal attributes and other characteristics needed for successful performance of the job.
Required Competencies for the Child Welfare Caseworker
Greatly Exceeds Expectations
Exceeds Expectations
Meets Expectations
Occasionally Meets Expectations
Collaboration: Builds constructive working relationships with clients/customers, other work units, community organizations and others to meet mutual goals and objectives. Behaves professionally and supportively when working with individuals from a variety of ethnic, social and educational backgrounds. Builds Relationships Seeks and Contributes ideas Facilitates agreements Comments:
Unsatisfactory
Greatly Exceeds Expectations
Exceeds Expectations
Meets Expectations
Occasionally Meets Expectations
Communication: Clearly conveys and receives information and ideas through a variety of media to individuals or groups in a manner that engages the listener, helps them understand and retain the message, and invites response and feedback. Keeps others informed as appropriate. Demonstrates good written, oral, and listening skills. Organization and clarity Listening skills Keeps others informed Written Communication Sensitivity to others Comments:
Unsatisfactory
Greatly Exceeds Expectations
Exceeds Expectations
Meets Expectations
Occasionally Meets Expectations
Cultural Competence: Cultivates opportunities through diverse people; respects and relates well to people from varied backgrounds, understands diverse worldviews, and is sensitive to group differences; sees diversity as an opportunity, challenges bias and intolerance. Shows respect and tolerance Challenges bias and intolerance Seeks opportunities to be inclusive Comments:
Unsatisfactory
Figure 19: Competency Based Performance Management Assessment Card Source: http://portal.cornerstones4kids.org/stuff/contentmgr/files/
5c06cb455ff52c94d8a9d0294e75469f/folder/gapclose_tool_4perf_mgmt.doc
45
3.1.4. Competency Based Succession Planning System
Succession planning is an ongoing system of selecting competent employees
ready to move into key jobs in the organization should these become vacant. Job-person
matches are made between existing employees and future jobs they might assume.27
These future jobs were usually higher level positions. In the current environment of
downsizing and rapid organizational change, succession planning can be used for key jobs
above. At the same level
The usual criteria for succession planning system include
1. One preferably two well qualified internal candidates are identified as ready
to assume and key job should it become vacant
2. A record of successful promotions or other job placements
3. Few superior performers leave the organization because of lack of
opportunity
Competency based succession planning systems identify the competency
requirements for critical jobs, assess candidate competencies and evaluate possible job-
person matches.
3.2. Change Management and Competencies
Change management is a structured approach to transitioning individuals, teams,
and organizations from a current state to a desired future state. The current definition of
change management includes both organizational change management processes and
individual change management models, which together are used to manage the people side
27 L.Spencer&S.Spencer, Competence At Work, 1993
46
of change.28 Three factors must be present for meaningful organizational change to take
place. These factors are:29
D = Dissatisfaction with how things are now;
V = Vision of what is possible;
F = First, concrete steps that can be taken towards the vision.
If the product of these three factors is greater than
R = Resistance,
Then change is possible. Because of the multiplication of D, V and F, if any one is
absent or low, then the product will be low and therefore not capable of overcoming the
resistance.
In the condition of fast changing environment it is important to ensure a successful
change since the change appears in negative way too. Therefore it is necessary to use
influence and strategic thinking in order to create vision and identify those crucial things for
effective change management. Organization must recognize and accept the dissatisfaction
that exists by communicating industry trends, leadership ideas, best practice and
competitive analysis to identify the necessity for change.
In the model of PCI six critical success factors that must be managed to build
commitment to change initiatives and create behavior change. 30
1. Shared Change Purpose - create and share a powerful case for change in
the organization
2. Effective Change Leadership - develop strong change leadership for the
initiative
28 http://en.wikipedia.org/wiki/Change_management_(people) 29 Beckhard, R 1969 Organization Development: Strategies and Models 30 http://new.changefirst.com/pci_methodology
47
3. Powerful Engagement Processes - build and deliver plans to engage people
in the change
4. Committed Local Sponsors - build understanding and commitment of middle
and front-line managers
5. Strong Personal Connection - create commitment and behavior changing
actions for front-line people
6. Sustained Personal Performance - support people as they learn to adapt,
managing their resistance sensitively and empathetically.
Continues change management is also designed as a systemic approach to
change management. 31
Figure 20: The Elements of Continuous Change Management Source: http://www.almc.army.mil/alog/issues/marapr02/ms723.htm32
31 http://www.almc.army.mil/alog/issues/marapr02/ms723.htm 32 http://www.almc.army.mil/alog/issues/marapr02/ms723.htm
Product Process
People
Press (Climate, Culture, Environment)
GROWTH
Function New Ideas& Imporvement
Feedback&Quality
48
People refers to be effective, any change system must account for how people
interact with others, gather information, make decisions, and solve problems. This
information provides indicators that correlate significantly with job selection, reaction under
stress, conflict management, and learning and teaching preferences.
Process refers to the processes people perform during the course of the normal
workday. The issues here, of course, are how well the processes are performing and how
they can be improved or redesigned to meet the changing needs of the organization.
The area of intersection between people and process is functions. People run
processes, and processes are grouped into functions. Multifunctional teams break down
traditional functional stovepipes. These teams require each member to have a complete
understanding of the interaction of each function within the team and the organization.
Understanding the key functions within the organization allows the team to focus quickly on
the key process changes needed in areas such as new training requirements, policies,
structure, and job requirements and to determine the impact of those changes on people.
The product can be transactional, production, or both. It is the result of people and
process. Where process and product overlap is the focus of quality efforts. This is refining a
process to reproduce consistently a service or product at high standards of quality.
Traditionally, this area has been the home of the Total Quality Management, Six Sigma, and
ISO 9001 quality improvement programs. In most cases, these methodologies are overlaid
onto the business strategy.
Where product and people intersect it is the realm of option development. These
options include ideas designed to improve existing products or ideas that result in new
products or ways of doing business. This intersection is essential to the future growth of the
organization.
Press is short form for pressure. The term "press" is used because it describes the
context within which people, process, and product operate. It is the environment, both
internal and external to the organization, that presses in on and out from the organization.
49
Press also encompasses the climate (observed patterns of behavior of people
within the organization) and culture (values and belief system of the organization). Climate,
on the other hand, is the result of behavioral patterns that see in organizations. Climate acts
as the filter between leadership and productivity.
Growth is a systemic approach to change management. The area where people,
product, and process intersect is growth—more specifically, market growth. The growth
includes people (new skills, better communications, less conflict, high performance teams),
process (coordinated continuous improvement, determination of impact on people), and
product (faster, better, cheaper or new innovations) and increases in the probability of
market-share growth.
3.3. Globalization, Crisis Management and Competencies
Economic globalization has intensified on the basis of new international links,
especially in the field of foreign direct investment, financial capital flows and
telecommunications liberalization. These and other development like major crisis have
reinforced international independence and raise new issues for international organizations
as well as for strategic behavior of major actors 33
The effect of globalization causes sudden crisis and increases the importance of
effective crisis management. Crisis management is the process by which an organization
deals with any major unpredictable event that threatens to harm the organization, its
stakeholders, or the general public. 34
Three elements are common to most definitions of crisis:
1. A threat to the organization,
33 Tilly, Richard; Welfens, Paul J.J. (Eds.) Economic Globalization, International Organizations and Crisis Management Contemporary and Historical Perspectives on Growth, Impact and Evolution of Major Organizations in an Interdependent World, 2000 34 http://en.wikipedia.org/wiki/Crisis_management
50
2. The element of surprise, and
3. A short decision time
Whereas risk management involves assessing potential threats and finding the best
ways to avoid those threats, crisis management involves dealing with the disasters after they
have occurred. It is a discipline within the broader context of management consisting of skills
and techniques required to assess, understand, and cope with any serious situation,
especially from the moment it first occurs to the point that recovery procedures start.
Crisis management consists of
Methods used to respond to both the reality and perception of crises.
Establishing metrics to define what scenarios constitute a crisis and should
consequently trigger the necessary response mechanisms.
Communication that occurs within the response phase of emergency
management scenarios.
During the crisis management process, it is important to identify types of crises in
that different crises necessitate the use of different crisis management strategies. Potential
crises are enormous, but crises can be clustered.
51
4. MEASURING COMPETENCIES
During past few decades business professionals seek to find the best ways for the
measurable criteria’s to define the performance and the potential of the employees at work
place. Personality inventories, intelligence test, stress level test, perception test, verbal
and numerical reasoning test and some technical knowledge test like language test,
mathematic and general ability test are used as different inventories to measure the
knowledge, capacity, potential and characteristic of a person.
As David McClelland states that the aptitude and intelligence tests are not all that
valid35 to define the work performance of a person. In his research he found that students
who did poor in the school (as long as they passed) did just as well in life as the top
students. 36McClelland argues that tests should be designed to reflect changes in what
people have learned. He writes that it is difficult, if not impossible to find a characteristic
that cannot be modified by training and/or experience.
At this point he goes on to what most competencies should try to measure --
clusters of life outcomes. McClelland says that if you move towards criterion based job
analysis, there is the danger that the tests will become extremely specific to the criterion
involved. Thus one could end up with hundreds or even thousands of specific tests for
each job. Thus it might be more useful to assess competencies that are more useful in
"clusters of life outcomes." This could include occupational, leadership, and interpersonal
skills. 37 McClelland did cluster personality or traits into competencies, rather than separate
them into attributes. Rather he wrote that there is no solid evidence that this trait of any
other trait cannot be changed. Thus if you cannot find the people with all the competencies
you need, you can always train or develop them.
Specifically there are using three methods for the measure the competencies as
observation, interview and questionnaire. All of the methods have some advantages and
disvantages as shown in Table 5.
35 David Mc Clelland, Testing Competence rather Than for Intelligence, 1973, 37 http://www.nwlink.com/~donclark/hrd/case/McClelland.html
52
Table 7: Advantages and Disadvantages of Data Collection Methods Interviews, Questionnaires and Observations
Mode of Data Collection
Advantages Disadvantages
Personal or Face-
to-Face Interviews
Can establish rapport and
motivate respondents
Can clarify the questions, clear
doubts, add new questions
Can read non-verbal cues
Can use visual aids to clarify
points
Rich data can be obtained
Take personal time
Cost more when a wide
geographic region covered
Respondents may be
concerned about confidentially
of information given
Interviewers need to be trained
Can introduce interviewers
biases
Respondents can terminate
the interview at any time
Telephone
Interview
Less costly and speedier than
personal interviews
Can reach a wide geographic
area
Greater anonymity than personal
interviews
Nonverbal cues cannot be
read
Interviews will have to be kept
short
Obsolete telephone numbers
could be contacted and
unlisted ones omitted from the
sample
Personally
Administered
Questionnaire
Can establish rapport and
motivate respondent
Organizations may be reluctant
to give up company time for
the survey with groups of
53
Doubts can be clarified
Less expensive when
administered to groups of
respondents
Almost 100% response ensured
Anonymity of respondents is high
employees assembled for the
purpose
Questionnaires
Anonymity is high
Wide geographic regions can be
reached
Token gifts can be enclosed to
seek compliance
Respondent can take more time
to respond at convenience
Can be administered
electronically if desired
Response rate is always low. A
30% rate is quite acceptable
Cannot clarify questions
Follow-up procedures for non-
responses are necessary
Electronic
Questionnaire
Easy to administer
Can reach globally
Very inexpensive
Fast delivery
Respondents can answer at their
convenience like the mail
questionnaire
Computer literacy is a must
Respondents must have
access to the facility
Respondents must be willing to
complete survey
Observation The data obtained through
observation of events
Long period of time
54
Easy to observe certain group of
people
Easy to note the effects of
environmental influence on
specific outcomes
More reliable outputs from
respondents
Observers have to be trained
Source: Uma Sekaran, Research Methods for Business, 2003
55
5. PROPOSED MODEL
The proposed model is consisting of three sections as individual competencies,
independent variables and demographic variables. The first section called as initial
competencies is core concept of the model. These variables are dependent variables
consisting of sixty four items. The second section called dependent variables is consisting of
thirty items. The third section called demographic variables is consisting of twelve factual
questions.
In the first section individual competencies are defined as cluster of four sub
competencies which has the significant importance to execute successful business. These
competencies are defining the management of a function, task and source, the degree of
knowledge and the way of its usage, the ability to aware and use own source. Sub
competencies are consisting of management, specialties, entrepreneurship and personal
competencies. The first sub competency called as management competencies includes four
sub competencies as leadership, planning&organisation, quality awareness and influencing
others competencies. These four sub-competencies are also consisting of seventeen sub-
competencies related with the execution the management function of a work, source, task,
projects and relationship with people. These are listed as motivate others, taking
responsibility, decision making, flexibility, delegation, independent, long term view, focus on
details, evaluative, committed, effective time planning, organizing, planning, quality
orientation, agreeable, influencing others and being friendly. The second sub competency
called as specialties competencies includes four sub components as specialist knowledge,
problem solving& analysis, verbal communication and written communication competencies.
These four cub-competencies are also including of fourteen sub-competencies related with
the functionality and quality level of output of a performance to do a work, task or a project.
These are listed as conceptual thinking, follow-up technology, numerical evaluation, open to
learn, confident about knowledge, evaluate of alternative solution, evaluate of difficulties,
problem solving, effective speaking, speaking thoughtfully, outspoken, presenting, cares
writing rules and effective writing. The third sub competency called as entrepreneurship
competencies are including four sub competencies called as commercial approach,
creativity&innovation, action oriented and strategic acting competencies. These four sub
competencies are also including of thirteen cub-competencies very critical competencies to
56
sustain in hard competition and changing environment. These are listed as competitive,
decisive, customer orientation, balance between work & private life problems, risk taker,
creative, conventional, innovative approach, action oriented, result & goal oriented, loyalty,
confident visionary and strategic. The fourth sub competency in the fist block called personal
competencies are consisting of four sub competencies called as interpersonal relations,
flexibility, self awareness and motivation competencies. These four sub competencies are
consisting of twenty sub competencies defining the inner source of a person and relationship
with others. These are listed as team work, supportive, encouraging, responsive, trust to
others, behavioral, adaptable, situational, adaptable to change, vigorous, calm, patient, open
to critics, emotionally controlled, anxious, energetic, optimistic, achieving, confident and
ambitious.
In the second section independent competencies are defined as cluster of four sub
competencies as well. These competencies are defining the strata’s of environment
surrounding of an individual. Since an individual in business world are continue sly
interaction with its surroundings business world can be defined a living organism for an
individual. In this living organism there are defined major factor in four sub competencies in
the model. These sub competencies are consisting of company core competencies, human
resource management competencies, environmental changes and work related
competencies. The first sub competency called as management competencies includes four
sub competencies as company management, area of business activity, customer care and
business ethic. These four sub-competencies are also consisting of eleven sub-
competencies related with company core activates, functions defining the targets, tasks,
sources and executing the way of work of an employee. These are listed as company
leadership, flexibility, responsibility, vision mission, profitability, product service, innovation,
customer relationship management, quality orientation, equality and transparency. The
second sub competencies called as human resource management competencies including
HR strategy, performance management, individual development and crisis management.
These four sub-competencies are also consisting of eight sub-competencies defining the
standards and procedure for the management of employees. These are listed as HR
strategy, employee support program, recruitment, firing, performance management,
individual development, career planning and crisis management. The third sub
57
competencies called as environmental changes including four sub factors as economic
conditions, competition, social life balance, family life balance. These four sub factors are
consisting of seven sub-competencies affecting an individual economically, socially and
emotionally. These are listed as economic crisis, stability, globalization, and technological
development, competition in the market, social life balance and family life balance. The
fourth and last sub competencies called as work competencies including four sub
competencies work content as job description, business process as workflow, work load and
job responsibility area. These competencies are defining the requirements, qualifications
and job description and profile for an employee.
The third section is consisting of the demographic variables. On the demographic
variables there are twelve factual questions about an employee. The age, gender, marital
status, education, occupation, total years of employed, type of company, department,
position, and total years of employed in current company, total number of employee in the
company and monthly salary.
As a result of evaluation of all definitions and models it was defined that individual
competencies are underlying characteristics of various behaviors and these competencies
are affecting by the work content, companies core competencies, human resource
management application and environmental changes. Basically individual competency is a
cluster of actual life conditions. Therefore in the proposed model a cluster of individual
competencies are offered as four major competencies which is a set of various behaviors.
58
5.1. The Proposed Competency Model
Figure 21: Proposed Competency Model
CC-Individual Competencies C5-Company Core
Competencies
C6-HRM Competencies
C7-Environmental Changes
C8-Work Competencies
C1-Management Competencies
C2-Specialties Competencies
C3-Entrepreneurship Competencies
C4-Personal Competencies
Dependent Variables
Independent Variables
Demographic Variables
2. Age 3. Gender 4. Marital Status 5. Education 6. Occupation 7. Years of Employed 8. Type of Company 9. Department 10. Position 11. Total years of
Employed in Current Company
12. Total Number of Employee
13. Monthly Salary
59
5.1.1. Dependent Variables List of The Proposed Competency Model
Figure 22: Dependent Variable List in Proposed Model
C1-Management Competencies
C2-Specialties Competencies
C3-Entrepreneurship Competencies
C4-Personal Competencies
SC1-Leadership S1-Motivate Others S2-Taking Responsibility S3-Decision Making S4-Flexibility S5-Delegation S6-Independent S7-Long Term View
SC2-Planning& Organization
S8-Focus on Details S9-Evaluative S10-Committed S11-Effective Time Planning S12-Organizing S13-Planning
SC3-Quality Awareness
S14-Quality Orientation
SC4-Influencing Others
S15-Agreeable S16-Influencing S17-Friendly
SC5-Specialist Knowledge
S18-Conceptual S19-Follows Technology S20-Numerical Evaluation S21-Open to learn S22-Confident about knowledge
SC6-Problem Solving& Analysis
S23-Evaluate of alternative solution S24-Evaluate of difficulties S25-Problem Solving
SC7-Verbal Communication
S26-Effective speaking S27-Speaking Thoughtfully S28-Outspoken S29-Presenting
SC8-Written Communication
S30-Cares writing rules S31-Effective writing
SC9-Commercial Approach
S32-Competitive S33-Decisive S34-Customer Orientation S35-Balance Between Work & Private Life Problems S36-Risk Taker
SC10-Creativity &Innovation
S37-Creative S38-Conventional S39-Innovative Approach
SC11-Action Oriented
S40-Action Oriented S41-Result Oriented Goal Oriented
SC12-Strategic S42-Loyalty S43-Visionary S44-Strategic
SC13-Interpersonal Relations
S45-Team Work S46-Supportive S47-Encouraging S48-Responsive S49-Trust to Others S50-Behavioral
SC14-Flexibility S51-Adaptable S52-Situational S53-Adaptable to Change
SC15-Self Awareness
S54-Vigorous S55-Calm S56-Patient S57-Open to Critics S58-Emotionally Controlled S59-Anxious
SC16-Motivation S60-Energetic S61-Optimistic S62-Achieving S63-Confident S64- Ambitious
CC - Individual Competencies
60
5.1.2. Independent Variables List of The Proposed Competency Model
Figure 23: Independent Variable List in Proposed Model
C5-Company Core Competencies
C6-Human Resource Management
C7-Environmental Changes
C8-Work Competencies
SC17-Management S65- Leadership S66-Flexibility S67-Responsibility S68-Vision&Mission
SC18-Area of Business Activity
S69-Profitability S70-Product& Service S71-Innovation
SC19-Customer Care S72-Customer Relationship Management S73-Quality Orientation
SC20-Business Ethic S74-Equality S75-Transparancy
SC21-HR Strategy S76-HR Strategy S77-Employee Support Program S78-Recruitment S79-Firing
SC22-Performance Management
S80-Performance Management Assesment
SC23-Individual Development
S81-Individual Development S82-Career Planning
SC24-Crisis Management
S83-Crisis Management
SC25-Economic Conditions
S84-Economic Crisis S85-Stability S86-Globalisation
SC26-Competition S87-Technological development S88-Market Competition
SC27-Social Life Balance
S89-Social Life Balance
SC28-Family Life Balance
S90-Family Life Balance
SC29-Work Content
S91-Job Description
SC30-Business Process
S92-Workflow SC31-Work Load
S93-Work Load SC32-Responsibility Area
S94-Job Responsibility Area
61
5.2. Definition of Dependent and Independent Variables
5.2.1. Definitions of Dependent Variables - Individual Competencies
Individual competencies include four sub-competencies as cluster of management
competencies, specialties competencies, entrepreneurship competencies and personal
competencies.
Individual competencies are the underlying characteristics of individual internal
sources as motives, thinking styles, knowledge and learning styles. Each of components of
these competencies is related with a person behavior, knowledge and skills performed at
work in different business cases. These individual competencies define the way of
relationship with others, ways of conducting business, thinking and learning styles of a
person. It specifically includes the skills to how the perceive the business life.
5.2.1.1. Management Competencies
Management in all business and human organization activity is simply the act of
getting people together to accomplish desired goals and objectives. Management comprises
planning, organizing, staffing, leading or directing, and controlling an organization or effort
for the purpose of accomplishing a goal. Resourcing encompasses the deployment and
manipulation of human resources, financial resources, technological resources, and natural
resources. 38
Management competencies are general descriptions of the underlying
characteristics and behaviors needed to successfully perform a job.
In these study management competencies includes four sub-competencies
clustered as
38 http://en.wikipedia.org/wiki/Management
62
1. Leadership
2. Planning and organization
3. Quality awareness
4. Influencing others
5.2.1.2. Specialties Competencies
Specialty is a degree of expertise concerning a specific job or work. An expert
person is a reliable source for a technique or skill for judging or deciding rightly. An expert
person has the authority in specific knowledge or ability in a particular area of a study. This
person can call for advice on their respective subject. Level of specialty changes the degree
of knowledge and the level of experience. An expert person competency includes the high
capacity of knowledge.
In these study specialties competencies includes four sub-competencies clustered
as
1. Specialist Knowledge
2. Problem Solving&Analysis
3. Verbal Communication
4. Written Communication
5.2.1.3. Entrepreneurship Competencies
An entrepreneur is a person who is willing and able to convert a new idea or
invention into a successful innovation. Entrepreneurship forces "creative destruction" across
markets and industries, simultaneously creating new products and business models. In this
63
way, creative destruction is largely responsible for the dynamism of industries and long-run
economic growth.
Entrepreneurs have many of the same character traits as leaders. Entrepreneurs
are often contrasted with managers and administrators who are said to be more methodical
and less prone to risk-taking.
In these study entrepreneurship competencies includes four sub-competencies
clustered as
1. Commercial Approach
2. Creativity& Innovation
3. Action Oriented
4. Strategic Thinking
5.2.1.4. Personal Competencies
Personal competencies relate to the attitudes and behaviors of individuals
especially the coming from inner sources like motivation, basics instincts, feelings and
emotions. These competencies determine the relationship with other, understanding self and
ability, motivation factors and energy level. Basically these competencies can be assumed
as dynamics of a person.
In these study personal competencies includes four sub-competencies clustered as
1. Interpersonal Relations
2. Flexibility
3. Self Awareness
4. Motivation
64
5.2.2. Definitions of Independent Variables
5.2.2.1. Company Core Competencies
A core competency is a specific factor that a business sees as being central to the
way it or its employees work. A core competency can take various forms, including technical
matter know-how, a reliable process and relationships with customers and suppliers. It may
also include product development or culture, such as employee dedication.
Core competencies are particular strengths relative to other organizations in the
industry which provide the fundamental basis for the provision of added value. Core
competencies are the collective learning in organizations, and involve how to coordinate
diverse production skills and integrate multiple streams of technologies. It is communication,
an involvement and a deep commitment to working across organizational boundaries.
In these study company core competencies includes four sub-competencies
clustered as
1. Management
2. Area of Business Activity
3. Customer Relationship Management
4. Business Ethics
5.2.2.2. Human Resource Management Competencies
65
Human Resource Management is the function within an organization that focuses
on recruitment, management, and providing direction for the people who work in the
organization. It manages such as compensation, performance management, organization
development, safety, wellness, benefits, employee motivation, communication,
administration, training and crisis management. Besides HRM professionals HRM function
can also be performed by line managers as well.
In these study human resource competencies includes four sub-competencies
clustered as
1. HR Strategy
2. Performance Management
3. Individual Development
4. Crisis Management
5.2.2.3. Environmental Conditions
Environmental conditions are focusing on the interactions between an employee
and their surroundings. The term environment is broadly encompassing natural
environments, social settings, built environments, learning environments, and informational
environments.
When solving problems involving human-environment interactions, whether global
or local, one must have a model of human nature that predicts the environmental conditions
under which humans will behave in a decent and creative manner. With such a model one
can design, manage, protect and/or restore environments that enhance reasonable
behavior, predict what the likely outcome will be when these conditions are not met, and
66
diagnose problem situations. The field develops such a model of human nature while
retaining a broad and inherently multidisciplinary focus. 39
39 http://en.wikipedia.org/wiki/Environmental_psychology
67
In these study environmental sources includes four sub-cofactors clustered as
1. Economic Conditions
2. Competition
3. Social Life Balance
4. Family Life Balance
5.2.2.4. Work Competencies
A work competencies are similar to job competencies describes a job or role
competencies often those specific to a certain type of job within a specific work unit. The
competencies can various for the sales, finance, manufacturing and service functions of
the company. It can include the qualification specific to a task or project.
In these study work competencies includes four sub-competencies clustered as
1. Work Content
2. Business Process
3. Work Load
4. Responsibility Area
68
6. METHODOLOGY
6.1. Research Design
Having identified the variables in a problem situation and developed the theoretical
framework, the next step is to design the research in a way that the requisite data can be
gathered and analyzed to arrive at a solution.40
The research design involves a series of rational decision-making choices. In this
research study a systematic methodology used for data collection and analysis. The stages
of research design defined in Table 5. In each stage there is a certain question to be
answered through this research.
Table 8: Stages of Research Design
Source: Prof. Dr. Rauf Nişel, Survey Method Class Notes at Marmara University, autumn 2006
In the research design, the purpose of the study, the types of the investigation, data
collection methods, sampling design, the extent of researcher interference, the unit of
analysis defined and executed.
40 Uma Sekaran, Research Methods for Business, 2003 pg. 117
No Stages of Research Analysis
Questions to Be Answered
1 Objectives
What are the objectives of the research
2 Sources What are the sources of the research information to be
collected3 Tools
What are the necessary tools to reach those objectives
4 Analysis What are the methods to be used in research analysis
5 Profits
What are the probable profits if you reach objectives of the
research6 Strategies What are the probable strategies applicable after the research
69
6.1.1. Aim of The Research
The aim of this research is listed as follows:
1. The primary aim of this research is to define the consistency of sub
competencies as listed under the individual competency. There are sixty four sub
competencies in the proposed model as dependent variables.
2. The secondary aim of the study is to indentify if there are any effects of the
independent variables on the individual competency. There are thirty items in the proposed
model as independent variables.
3. The third aim of the study is to analyze if there is any difference at
dependent and independent variables between normal conditions and crisis situation.
4. The fourth aim of the study is to define the effects of demographic variables
on the dependent variables. There are twelve factual questions in the demographic
variables.
As a result of all analyses new set of competencies effecting individual
competencies will be defined.
6.1.2. Sources For Collecting of The Research Information
6.1.2.1. Population and Sampling
The source of this research is defined as the employees working in the Halkalı
factory of a leading private manufacturer of steel pipes and tubes based in Sefakoy, Istanbul
location. Total number of employees is 300 in June, 2009. 250 employees are joined the
survey.
70
6.1.3. Methods For Data Collection
Data collection methods are an integral part of research design. There is several
data collection methods, each with own advantages and disadvantages. Data can be
collected in a variety of ways and in different setting field or lab, from different sources
primary or secondary. Interviewing, administering questionnaires and observing people are
the three main data collection method in survey research. First method is interviews like face
to face or telephone interviews, computer assisted interviews. Second method is
questionnaires that are personally administered, sent through the mail or electronically
administered. Third method is observation of individuals and events.
Table 9: Advantages and Disadvantages of Data Collection Methods
Source: Prof.Dr. Rauf Nişel, Survey Methods, Autumn Class Notes at Marmara University, 2006
In this study the questionnaire method used in the field survey because the time
constraint of the study. 250 questionnaires are sent to the employees. The return rate is
50%.
6.1.3.1. Questionnaire Design
No Data Collection Method
Flexibility of Data
Standardization of Data
Difficultness of Application of Statistical Methods
Subjectivity of The Result of Data Analysis
1 Interview
+ - + -
2 Questionnaire
- + - -
3 Observation
+ + - +
71
Sound questionnaire design principles should focus on the three areas. The first is
wording of the questions. The second refers to planning of issues of how variables will be
categorized, scaled and coded after receipt of the responses. The third pertains to the
general appearance of the questionnaire. All three are important issues in questionnaire
design because they can minimize the biases in research41.
In this study designed questionnaire are consisting there section. In the first section
there are sixty four items as dependent variables. In the second section there are thirty items
as independent variables. All the statements in these two sections are designed as positive
statements. In the third section there are twelve factual questions as demographic
questions. For the first two sections itemized rating scale is designed to examine how
strongly subjects Disagree, Rarely Agree, Slightly Agree, Somewhat Agree, Strongly agree
and with statements on 6 point scale. The answers of the respondents are collected for
current situations and crisis situations.
Figure 24: Structure of Questionnaire Used in the Study Source: Prof. Dr. Rauf Nişel, Survey Method Class Notes, autumn 2006
41 Uma Sekaran, Research Methods for Business, 2003, pg. 237
Tools of Collecting Data
Questionnarie
Factual Question (12 questions)
Instruments – Itemized Rating Scale (94 Items - 6 Point Rating Scale)
Normal Conditions
Crisis Conditions
72
6.1.4. Methods for The Data Analysis
In the data analysis there are three main objectives as getting an interpretation of
data, testing the goodness of data and testing the hypotheses developed by the research.
The interpretation of the data gives the preliminary ideas of how good the scales are, how
well the coding and entering of the data have been done. Testing the goodness of data gives
how the instrument developed in good mood and the relationship between variables. 42
Once the data are collected, the information coded and appropriate data analysis
techniques applied. According to the aim of the research the data analysis methods are
defined in following steps
1. Reliability Analysis of the Dependent and Independent Variables (Measure
of Consistency - Value of Cronbach Alpha)
2. Multivariate Analysis of Variance (MANOVA for independent and dependent
variables)
3. Analysis of Variance (ANOVA for core concept and independent variables )
4. Measure of Correlation (MAC for demographic variables and dependent
variables)
5. Multiple Regression Analysis
6.1.4.1. Definition of The Relaibility Analysis
The reliability of a measure indicates the extent to which it is without bias and
hence ensures consistent measurement across the time and across various items in the
instrument. In other words the reliability of a measure is an indication of the stability and
consistency with which the instrument measure the concept and helps to assess the
“goodness” of a measure
42 Uma Sekaran, Research Methods For Business, 2003, pg. 306
73
Figure 25: Forms of Reliability Source: Uma Sekaran, Research Methods for Business, 2003 pg. 204
6.1.4.1.1. Stability of Measures
The ability of a measure to remain the same over time is indicative stability and low
vulnerability to changes in the situation. This attests to its “goodness” because the concept is
stably measured, no matter when it is done. Two test of stability are test-retest reliability and
parallel-form reliability.
Classical test theory assumes that each person has a true score that would be
obtained if there were no errors in measurement. Because instruments used for
measurement are imperfect, the score that is observed for each person most times is
different from the person's true abilities or characteristics. The theory concludes that the
difference between the true score and the observed score is the result of errors in
measurement.43
ETX +=
Formula 1: Observed and True Scores with Error
43 Allen, M.J., & Yen, W. M. Introduction to Measurement Theory, 2002.
Reliability (Accuracy in Measurement)
Stability Consistency
Test-Retest Reliablity
Paralel-form Reliability
Interitem Consistency
Reliability
Split-half Reliability
74
The above equations represent the assumptions that classical test theory makes at
the level of the individual person. However, the theory is never used to analyze individual
test scores; rather, the focus of the theory is on properties of test scores relative to
populations of persons.
Concerning the relations between the three variables X, T, and E in the population
these relations are used to say something about the quality of test scores. In this regard, the
most important concept is that of reliability. The reliability of the observed test scores X,
which is denoted as 2XTρ is defined as the ratio of true score variance to the observed score
variance :
22
2
2
22
EX
T
X
TXT σσ
σσσρ
+==
Formula 2: Reliability of the Observed Test Scores
The reliability of test scores becomes higher as the proportion of error variance in
the test scores becomes lower and vice versa. The reliability is equal to the proportion of the
variance in the test scores that we could explain if we knew the true scores. The square root
of the reliability is the correlation between true and observed scores.
Table 10: Population and Sample Mean, Variance and Standart Deviation Population Sample
Mean µ X
− Variance
( )2
12
n
XN
ii
X
∑=
−=
μσ
( )2
12
n
XXN
ii
X
∑=
−=σ
Standart Deviation ( )
2
1
n
XN
ii∑
=
−=
μσ
( )2
1
n
XXs
N
ii∑
=
−=
Source: Prof. Dr. Rauf Nişel, Survey Methods Class Notes at Marmara University, 2006
75
Measurements are reliable to the extent that they are repeatable and that any
random influence that tends to make measurements different from occasion to occasion or
circumstance to circumstance is a source of measurement error44 Reliability cannot be
estimated directly since that would require one to know the true scores. However, estimates
of reliability can be obtained by various means. One way of estimating reliability is by
constructing a parallel test. The fundamental property of a parallel test is that it yields the
same true score and the same observed score variance as the original test for every
individual. If we have parallel tests x and x', then this means that
( ) ( )
2
2
22
'
'
'
'
'
X
T
XX
XXXX
EE
ii
ii
XX
σσ
σσσ
ρ
σσ
εε
==
=
=
Formula 3: Expected Correlation between Test-Re Test Scores
The reliability coefficient obtained with a repitation of the same measure on a
second occasion is called test-retest reliability. That is, when a qestionnarie containing some
items that are supposed to measure a concept is administered to a set of respondents now,
and again to the same respondents, say several weeks to 6 months later, then the
correlation between the scores obtained at the two different times from one and the same
set of respondents is called the test-retest coefficient. The higher it is, the test-retest
reliability, and consequently, the stability of the measure of the measure across time.
44 Nunnally, J.,. Psychometric Theory. 1978, pg. 225
76
When responses on two comparable sets of measures tapping the same construct
are highly correlated, we have parallel-form reliability. Both forms have similar items and the
same response format, the changes being the wordings and the order or sequence of the
questions. Trying to establish here is the error variability resulting from wording and ordering
of the qestions. If two such comparable forms are highly correlated it may be fairly cetain
that the measures are reasonably reliable, with minimal error variance caused by wording,
ordering or other factors
6.1.4.1.2. Internal Consistency of Measures
The interal consistency of measures is indicative of the homogeneity of the items in
the measure that tap the construct. In other words, the items should hang together as a set
and be capable of independently measuring the same concept so that the respondents
attach the same overall meaning to each of the items. This can be seen by examining if the
items anad the subsets of items in the measuring the instrument are correlated highly.
Conssitency can be examined thorugh the inter-item consistency and split-half reliability test.
Interitem consistency reliability is a test of the consistency of respondents’ answers
to all the items in a measure. To the degree that items are independent measures of the
same concept, they will be correlated with one another. Cronbach’s alpha is a reliability
coefficient that indicates how well the items in a set are positively correlated to one another.
Cronbach’s alpha is computed in terms of the average intercorelations among the items
measuring the concept. The closer Cronbach’s alpha is to 1, the higher the internal
consistency reliability. 45
45 Uma Sekaran, Research Methods For Business, 2003, pg. 307
77
A general formula (α) of which a special case is the Kuder- Richardson coefficient
of equivalence is shown to be the mean of all split-half coefficients resulting from different
splittings of a test. α is therefore an estimate of the correlation between two random sam-
ples of items from a universe of items like those in the test. α is found to be an appropriate
index of equivalence and, except for very short tests, of the first-factor concentration in the
test.46
⎥⎥⎥⎥
⎦
⎤
⎢⎢⎢⎢
⎣
⎡
−−
=∑=
211
1 x
K
iiiqp
KK
σα
Formula 4: Kuder Richardson Formula 20
The Kuder-Richardson Formula 20 (KR-20) is the equivalent for dichotomous items.
Cronbach's α measures how well a set of variables or items measures a single,
unidimensional latent construct.
⎥⎥⎥⎥
⎦
⎤
⎢⎢⎢⎢
⎣
⎡
−−
=∑=
21
2
11 X
N
iiY
NN
σ
σα
Formula 5: Consistency Reliability Coefficient Cronbach Alpha
Cronbach's alpha generally increases when the correlations between the items
increase. For this reason the coefficient is also called the internal consistency or the internal
consistency reliability of the test.47
46 LF J. Cronbach, Coefficient Alpha and Internal Structure of Tests , 1951 Psychometrika, V:16 No: 3, 47 http://en.wikipedia.org/wiki/Cronbach's_alpha
78
Split half reliability reflects the correlations between two halves of an instrument.
The estimates would vary depending on how the items in the measure are split into two
halves. Split-hafl reliabilites could be higher than Cronbahc’s alpha only in the circumstance
of there being more than one underlying response deminesion tapped by the measure and
when certain other conditions are met as well.
Figure 26: Split Half Reliability Source: http://www.socialresearchmethods.net/kb/reltypes.php
In split-half reliability all items are randomly divided that purport to measure the
same construct into two sets. Administering the entire instrument to a sample of people and
calculate the total score for each randomly divided half. The split-half reliability estimate, as
shown in the figure, is simply the correlation between these two total scores
Measure
Item 1
Item 2
Item 3
Item 4
Item 5
Item 1 Item 3
Item 6
Item 4
Item 2 Item 5 Item 6
79
6.1.4.2. Definition of Multivariate Analysis of Variance (MANOVA)
Multivariate analysis of variance (MANOVA) is one of the multivariate statistical
techniques that can be used to simultaneously explore the relationship between several
categorical independent variables and two or more dependent variables. It can be stated in
the following general forms:48
nn XXXXYYYY ......................... 321321 +++=+++
Formula 6: General Forms of Multivariate Analysis of Variance
MANOVA is concerned with differences between groups. It is termed as
multivariate procedure because it is used to assess group differences across multiple
dependent variables. Each treatment group is observed on two or more dependent
variables. The null hypothesis tested is the equality of vectors of means on multiple
dependent variables.
Figure 27: Null Hypothesis Testing of MANOVA
48 Joseph F. Hair, William C. Black, Barry J. Babin, Rolph E. Anderson, Ronalds L. Tatham, Multivariate Data Analysis Sixth Edition, 2006, pg. 176
1
31
21
11
pμ
μμμ
Ho:
2
32
22
12
pμ
μμμ
= = -------------------- =
pk
k
k
k
μ
μμμ
3
2
1
Null hypothesis (Ho)=all group mean vectors are equal, that is they come from the same population μpk=means of variables p, group k
80
6.1.4.2.1. Analysis Design, Statistical Tests and Effects in MANOVA
Analysis Desing: General linear model (GLM) is used in the MANOVA analysis.
GLM is an estimation method based on three components. The one is variate formed by a
linear combination of independent variables. Each independent variable has an estimated
weight representing that variable’s contribution to the predicted value. The second is random
component as a probability distribution specified by the researcher based on the
characteristic of the dependent variables. The third a link function that denotes the
connection between the variate and the probability distribution.
In the analysis independent variables and demographic variables are determined
as following:
1. Factors: It is a nonmetric independent variable with a defined number of
levels. Each level represent a different conditions or characteristic that
affects the dependent variables. A factor can be an observed nonmetric
variable such as gender.
2. Covariates: Covariates are metric variables in the design. It is assumed to
be linearly related to the dependent variables.
Statistical Tests: In MANOVA there are four principal statistics for testing the
significance.
Table 11: Statistical Tests Accoriding to Number of Dependent Variables and Groups Number of Dependent Variables
Number of Groups in
Independent Variables
One
(Univariate)
Two or More
(Multivariate)
Two Groups t-test Hostelling’s 2T
Two or More Groups ANOVA MANOVA
81
Source: Joseph F. Hair, William C. Black, Barry J. Babin, Rolph E. Anderson, Ronalds L. Tatham, Multivariate Data Analysis Sixth Edition, 2006, pg. 176
1. Pillai’s Criterion: It consider all the characteristic roots. The discriminant
function specifşes a set of weigths that maximize the differences between
groups, thereby maximizinf the F value. The maximum F value enables to
compute directly the the greatest characteristic root which allows for the
statisticacl test of the first discriminant function. Any subsequent
discriminant functions are orthogonal, they maximize the differences among
groups baassed on the remaining variance.
2. Wilk’s Lambda: It is used for testing overall significance between groups.
Wilk’s Lamba considers all the discriminant functions that it examines
whether groups are somehow different without being concerned with they
differ on at least one linear combination of the dependent variables.
3. Hostelling’s 2T : It provides a statistical test of the variate formed from the
dependent variables, which produces the greatest group difference. It also
controls the Type I error rate by providing a single overall test of group
differences across all dependent variables at a specifies α level.
Type I error is the probability of incorrectly rejecting the null hypothesis, it
means saying difference or correlation exist when it actually does not. Type
II error is probability of incorrectly failing to reject the null hypothesis, the
chance of not finding a correlation or mean difference when it does exist.
Type II error is defined as power.
82
Table 12: Different Error Probabilities in The Hypothetical Setting of Testing Statistical Decision No Difference Difference
Ho: No Difference 1-α β
Type II error
H1: Difference α
Type I error
1-β
power
Source: Joseph F. Hair, William C. Black, Barry J. Babin, Rolph E. Anderson, Ronalds L. Tatham, Multivariate Data Analysis Sixth Edition, 2006
4. Roy’s Largest Root: It measures the differences on only the discriminant
function among the dependent variables. This criterion provides advantages
in power and specify of the test.
Effects
1. Main Effects: It means individual effect of each independent variable on the
dependent variables. When a significant effect of a factor is found it is called
main effect. It means that significant differences between two or more
groups. With two levels of the treatment, a siginificant main effect ensures
that two groups are significantly different. With three or more levels,
however a significant main effect doesn’t guarantee that all three groups are
significantly different; at least one significant difference is present between
pair of groups.
2. Interaction Effects: More then one factor is used, interaction effects are
created. The interaction term represents the joint effect or two or more
factor. It means that the difference between groups of one factor depends
on the values on another factor.
83
6.1.4.2.2. Assumptions for MANOVA
In MANOVA there are four main assumptions as independence, normality,
homoscedacity, linearity. Here are explanations of each aasumptions:
1. Independence: Dependent measures for each respondent be totally
uncorrelated with the responses from other respondents in the sample. A lack of
independence severely affects the staticticall validity of the analysis. Observations must be
independent.
2. Normality: This assumption for MANOVA to be valid concerns normality of
dependent variables. The dependent variable should be normally distributed within groups.
The assumption is that all the variables are multivariate normal. A multivariate normal
distribution assumes that the joint effect of two variables is normally distributed. Even though
this assumption underlies most multivariate techniques, no direct test is available for
multivariate normality. Therefore it is tested univariate normality of each variable. Tests for
outliers should be run before performing a MANOVA, and outliers (extreme points) should
be transformed or removed. Violating this assumption primarily creates problems in applying
Box’s M test. Violation of this assumption has little impact with larger sample sizes.
The simpliest diagnostic test for normality is a visual check of the histpogram that
compares the observed data values with a distribution approximatig the normal distribution.
In addition to examining the normal probability plot, one can also use statistical
tests to assess normality. A simple test is a rule of thumb based on the skewness and
kurtosis values. Skewness can be defined of the degree of departure from the symmetry.
The magnitude of the result of measure of skewness provides of information about the
selection of appropriate method of averaging. The sign of measure provide an information
selection appropriate method averaging. 49 (-) value states the distribution is left skewed, (+)
value states for the right skewed distribution. If skewness value is equal or larger than 0,5
then the extreme skewness can be considered.
The statistic value z for the skewness calculated as (where N is the sample size) : 49 Prof. Dr. Rauf Nisel, Survey Methods Class Notes at Marmara University, 2006
84
N
zskewness 63α=
Formula 7:Statistic Value for Skewness
A kurtosis measure which also reflects the degree of hetorogenity measures it
graphically graphically that’s kurtosis measure the level of heterogeneity but this measure
enables us to interprate the variation interms of hetoregenity or homogeneity when there is
only one set of data. According to the sign of kurtosis type of distribution defined as(+)
values for peak distribution, 0 for normal distribution, (-) values for flat distribution.
A z value can also be calculated for the kurtosis value using the following formula:
N
zkurtosis 244α=
Formula 8: Statistic Value for Kurtosis
If either calculated z value exceeds the specified critical value, then the distribution
is nonnormal in terms of that characteristic. The critical value is from z distribution (in annex),
based on the significance level desired. The most commonly used critical values are +/-
2.58(0.01 significance level) and +/- 1.96(0.05 significance level). With these tests, it can
easily assess the degree to which skewness and peaknesss of the distribution vary from the
normal distribution.
85
3. Homoscedasticity: The next assumption is related primarily to dependence
relationships between variables. Homoscedasticity refers to the assumption that dependent
variables exibit equal levels of variance across the range of the predictor variables.
Homoscedacity is desirable because the variance of the dependent variable being explained
in the dependence relationship should not be concentrated in only a limited range of the
independent values. In most situations, there is many different values of the dependent
variable at each value of the independent variable. For this relationship to b captured, the
variance of the dependent variable values must be relatively equal at each value of the
predictor variable. If this dispertion is unequal across values of the independent variable, the
relationship is said to be heteroscedatic. 50
A crticical assumption corncerns that the homocedacity of the variance and
covariance matrices among the two groups. This assumption is the equaivalance of
covariance matrices across the groups. Here it is concerned the substantial differences in
the amount of variance of one group versus another for the dependent variables. The
requirement of equivalence is a strict test because MANOVA examines all elements of the
covariance matrix of the dependent variables. 51
The statictical tests for equal variance dispersion assess the equality for equal
variance dispersion assess the equality of variances within groups formed by nonmetric
variables. The most common tests Levene test, is used to assess whether the variance of a
single metric variable are equal across any number off groups. If more then one metric
group variable is beign tested, so that the comparision involves the equality of
variance/covariance matrices, Box’s M test is applicable.
a. Univariate Test for Homocedaticity: In the homocedaticity analysis
assess also the univeriate homogeneity of variance across the two groups.
Levene’s Test for all dependent variables are nonsignificant (significance are
greater then 0.05)
50 Joseph F. Hair, William C. Black, Barry J. Babin, Rolph E. Anderson, Ronalds L. Tatham, Multivariate Data Analysis Sixth Edition, 2006, pg. 83 51 Joseph F. Hair, William C. Black, Barry J. Babin, Rolph E. Anderson, Ronalds L. Tatham, Multivariate Data Analysis Sixth Edition, 2006
86
b. Multivariate Test for Homocedasticity: MANOVA conduct the test for
equality of covariance matrices typically the Box’M test and provide significance
levels for the test statistic. The Box’M test for equality of the covariance matrices
shows a non sigfnificant (the significance value is bigger then 0.05) difference
between the two groups on the dependent variables collectively. Thus the
assumption of homoscedasticity is met for each individual variable separately and
the dependent variables collectively.
4. Linearity and Multicolinerity among the Dependent Variables: An implicit
assumption of multivariate methods based on correlational measures of association is
linearity. In the case of individual variables, linearity relates to the patterns of association
between each pair of variables and the ability of the correlation coefficient to edaquately
represent the relationship. The most common way to assess linearity is to examine the
scatter plots of the variables and to identify any nonlinear patterns in the data. Scatter plot
show the straight line depicting the lenar relationship. An alternative approach is to run a
simple regression analysis and to examine residuals. This technique will ve showed in the
regression analysis method.
Another key issue is the correlation among the independent variables. The ideal
situation for a model would be to have a number of independent variables highly correlated
with the dependent variable, but with little correlation among themselves. The simplest and
most obcious means of identfyng collinearity is an examination of the correlation matrix for
the independent variables. The presense of high correlation generally 0.90 and higher is the
fisrt indication of collinearity. Collinearity may be due to the combined effect of two or more
independent variables.
6.1.4.3. Definition of Analysis of Variance (ANOVA)
Analysis of variance (ANOVA) is a statistical technique used to determine whether
samples from two or more groups come from populations with equal means. It tests the
statistical significance of mean differences amougd different groups of scores. The different
groups of scores may correspond different levels of a single independent variables or to
87
different combinations of levels of two or more independent variables. The groups of scores
may come from different cases or from the same cases measured repeatedly. If a difference
between means is statistically significant, the difference is expected to reappear if the study
is replicated. 52
nXXXXY .............3211 +++=
Formula 9: General Forms of Analysis of Variance
ANOVA are used to assess the statistical of differences between grouos. The null
hypothesis is tested the equality of a single dependent variable means across groups.
Table 13: Null Hypothesis Testing for ANOVA
6.1.4.3.1. Statistical Tests in ANOVA
Two most common types of univariate procedures, t-test, which compares a
dependent variable across two groups and ANOVA which is used whenever the number of
groups in two or more.
52 Barbara G. Tabachnick, Linda S. Fidell, Experimental Designs Using Anova, California State University, 2007 pg.69
nH μμμ ==== .............210
Null Hypothesis(Ho)=all group means are equal, that is, they come from same population
88
t-test: The t-test asseses the statistical significance of the difference between two
independent sample means for a single dependent variable. The statdart error is an estimate
of the difference between means to be expected because of sampling error. If the actual
difference between the group means is sufficiently larger than the standart error, then we
conclude that these differences are statically significant. The determination of how large
must the t value be to consider the difference significant is made by comparing the t statistic
to the critical value of t statistic. Critical value is defined from the t table based on
siginificance level and degree of freedom calculating by sample size. Degree of freedom
calculated from the total number of observations minus 1.53
21
21
μμ
μμSE
tstatistics−
=
Formula 10: t Statistics
In ANOVA statistical test is two independent estimates of the variance for
dependent variable are compared. The first reflects the general variability of respondents
within the groups ( wMS ) and the second the represents the differences between groups
( BMS )
F Statistic: The ratio F distribution is a sampling distribution of the ratio of two
variances. In ANOVA, ( wMS )and ( BMS ) provide the variances fro the F ratio to the test null
hypothesis. If null hypthesis is true and there are no treatment effects F ratio downs and it is
value is around 1. Large value of the F statistic leads to rejection of the null hypothesis of no
difference in means of across groups.
w
Bstatistics MS
MSF =
Formula 11: F Statistics
53 Joseph F. Hair, William C. Black, Barry J. Babin, Rolph E. Anderson, Ronalds L. Tatham, Multivariate Data Analysis Sixth Edition, 2006, pg. 83
89
To determine whether the F statistic is sufficiently large to support rejection of the
null hypothesis (meaning that differences are present between the groups), follow a process
similar to t test. Determine the critical value for F statistics by referring the F distribution with
(k-1) and (N-1) degrees of freedom for a specified level of α (where k number of groups). F
crititcal values are just the t crtical values squared. If the calculated value of F statistics
exceeds the critical F value it is conluded that the means across all groups are not all equal.
6.1.4.3.2. Assumptions for ANOVA
1. Independence: Observvation must be independent as explained in
MANOVA.
2. Normality: An assumption of ANOVA is that the sampling distribution of the
means for each level of the individual variables is normal. The assumption is for the
sampling distribution, not the raw scores. If the raw scores are normally distributed, the
sampling distribution of their means is also normally distributed. However, even if the raw
scores are not normally distributed, the Central Limit Theorem assures that the sampling
distribution of means is normally distributed for large enough sample.
3. Homosedacity: Homogenity of variances aasumes that population variances
in different levels of the independent variables are equal. Levense test for homogeneity of
variance performs.
6.1.4.4. Definition of Measure of Correlation Analysis (MAC)
There are many measures of association used to measure the strength of
relationship. Each has advantages and disadvantages.
Cramer's V is one of several measures based on chi square. Chi square itself is not
a measure of association, but a test of the hypothesis that two variables are unrelated. V is
equal to the square root of the following value--chi square divided by the product of the
90
number of cases in the table and the smaller of two values--the number of rows minus one
and the number of columns minus one. Cramer's V is useful for tables larger than 2 by 2.
Phi coefficient is a measure of the degree of association between two binary
variables. This measure is similar to the correlation coefficient in its interpretation.
Spearman's rho is a measure of the linear relationship between two variables. It
differs from Pearson's correlation only in that the computations are done after the numbers
are converted to ranks. When converting to ranks, the smallest value on X becomes a rank
of 1, etc.
Kendall tau rank correlation coefficient is used to measure the degree of
correspondence between two rankings and assessing the significance of this
correspondence. In other words, it measures the strength of association of the cross
tabulations.
6.1.4.5. Definition of Multiple Regression Analysis
Multiple regression analysis is a statistical method that can be used to analyze the
relationship between a single dependent variable and several independent variables. The
objective of multiple regression analysis is to use the independent variables whose values
are known to predict the single dependent value selected by the researcher. Each
independent variable is weighted by the regression analysis procedure to ensure maximal
prediction from the set of independent variables. The set of weighted independent variables
forms the regression variate, a linear combination of the independent variables that best
predicts the dependent variables.54
Regression coefficient is the numerical value of the parameter estimate directly
associated with an independent variable. Assuming the model 110 XbbY += , the value b1 is
the regression coefficient for the variable X1. The regression coefficient represents the
amount of change in the dependent variable for a one-unit change in the independent
54 Joseph F. Hair, William C. Black, Barry J. Babin, Rolph E. Anderson, Ronalds L. Tatham, Multivariate Data Analysis Sixth Edition, 2006
91
variable. In multiple predictor model 22110 XbXbbY ++= regression coefficients sre partial
coefficiens between Y and 1X and between Y and 2X , but also between 1X and 2X . The
coefficient is not limited in range , as it is based on both the degree of associaton and the
sacle units of the independent variable.
The measure of the proportion of the variance of the dependent variable about its
mean that is explained by the independent or predictor variables is the coefficient of
determination called 2R . The coefficient can vary between 0 and 1. If the regression model
is propoerly applied and estimated, the higher value of 2R gathered. Higher value means
that the greater explanatory power of the regression equation and therefore the better
prediction of the dependent variable.
Assumptions
1. Linearity: The linearity of the relationship between dependent and independent
variables represents the degree in the dependent variable is associated with the
independent variable. The regression coefficient is constant across the range of values for
the independent variable. The concept of correlation is based on a linear relationship, thus
making it a critical issue in regression analysis. Linearity of any bivariate relationship easily
examined through residual plots.
2. Multicolinearity: Collinearity is the association, measured as the correlation,
between two independent variables. Identifying collinearity is an examination of the
correlation matrix for the independent variables. To asses the multicollinearity it is need a
measure expressing the degree to which each independent variable is explained by the set
of other independent variables. The two common measures for assessing both pairwise and
multiple variable collinearity are tolerance and variance inflation factor.
92
Analysis
1. Collinearity Statistics
a. Tolerance: A direct measure of multicollinearity is tolerance, which is
defined as the amount of variability of the selected independent variable
not explained by the other independent variables. The tolerance value
should be high, which means small degree of multicollinearity.
b. Variance Inflation Factor (VIF): The second measure of multicolinearity
is the VIF, which is calculated simply as the inverse of the tolerance
value. VIF is the degree to which the standart error has been increased
due to multicollinearity.
2. Collienarity Diagnostics
i. Eigenvalue:
ii. Condition Index:
iii. Variance Proportion:
3. Residual Statistics
c. Standardize Residual: Standardized residuals can be a transformation
of each predicted value into it standardized from. That means the eman
predicted value is subtracted from the predicted value ( bXaY += )and
the difference is divided by standard predicted values have a mean of
an standart deviation of 1.
d. Studendized Residual: It can be obtained by the residual devided by an
estimate of a standart deviation that varies from case to case.
Depending on the distance of each cases values on the independed
values from the means of independent variables.
93
e. Studendized Deleted Residual: The deleted residuals for a case
devided by a standart error. The difference between a stundized deleted
residual and studendized residual in the case that how much differemce
eliminated the case makes correspond prediction.
4. Leverage Statistics
f. Mahalonobis Distance: It is a measure of how much cases values on
the independent values differ from all values. A large mahalonobis
distance identifies a case having extreme values on one or more
independent variables
g. Cook’s Distance: A measure of how much residuals of all cases would
change if a particular case were excluded from the calculation of the
regression coefficient. A large cook distance indicates that excluding a
case from computation of regression statistics changes coefficients
substantioally.
h. Centered Leverage Value: Measures influence of a point on the fit of
regression centered leverage ranges from zero (no influence on the fit)
to ( )
nn 1−
5. Influence Statistics
i. Standardize Difference in β Value: The change in regression coefficient
that results from the exclusion of a particular case. Examining cases
with absolute values greater than 2 divided by the square root of the
sample size which is doneted by n ( n
2)
j. Standardize Dif. in Fit Value: The change in the predicted value that
results from the exclusion of a particular case. Examining standardize
values which in absulate value exceed to divided by square root of
94
(
np
2) where p is the number of independent values in the equation
and n is the sample size.
k. Covariance Ratio: It is the ratio of the determinant of the covariance
matrix with a particular case excluded from the calculation of the
regression coefficient to the determinant of the covariance matrix with
the all cases included. If the ratio is closes to the one the case doesn’t
significanlty alter the covariance matrix.
Table 14: Multivariate Data Analysis in Regression Residual Statistics Leverage Statistics Influence Statistics
1. Standardize Residual 1. Mahalonobis Distance 1. Df Beta
2. Studendized Residual 2. Cook’s 2. Dif Fit
3. Studendized Deleted
Residual
3. Centered Fev Values 3. Standardized Df. Fit
4. Covariance Ratio
Source: Prof. Dr. Rauf Nişel, Multivariate Data Analysis Class Notes at Marmara University, 2008
95
6.2. Data Analysis for The Proposed Model
6.2.1. Reliability Analysis for the Proposed Model
In this study consistency reliability will be analysed for dependent and independent
item scales. The reliability analysis will be done following order
1. In the first step consistency anaylsis will be done for 64 items as dependent
variables and 30 items as independent variables.
2. After that cronbach alpha for each of the first level of sub groups as
showed in the Table 10 will be gathered. The selected items will be exculeded from the
model if the value of Cronbach Alpha is lower then 0,7. The deleted items will selected
according to increase in Cronbach Alpha Value if that item is deleted.
Table 15: List of Dependent and Indenependent Variables in Subgroup No Label No Label Name Variables
1 C1 Management Competencies S1+S2+S3+S4+S5+S6+S7+ S8+S9+S10+S11+S12+S13+ S14+ S15+S16+S17
2 C2 Specialist Competencies S18+S19+S20+S21+S22+ S23+S24+S25+ S26+S27+S28+S29+ S30+S31
3 C3 Entrepreneurship Competencies S32+S33+S34+S35+S36+ S37+S38+S39+ S40+S41+ S42+S43+S44
4 C4 Personal Competencies
S45+S46+S47+S48+S49+S50+ S51+S52+S53+ S54+S55+S56+S57+S58+S59+ S60+S61+S62+S63+S64
5 C5 Company Core Competencies S65+S66+S67+S68+ S69+S70+S71+ S72+S73+S74+S75
6 C6 Human Resource Management S76+S77+S78+S79+S80+ S81+S82+S83
7 C7 Environmental Changes S84+S85+S86+S87+S88+S89+S90
96
8 C8 Work Competencies S91+S92+S93+S94
3. Then the Cronbach Alpha will be gathered for the second level of sub
groups as listed in Table 19.
Table 16: List of Subgroups in the Dependent and Independent Variables the Initial Proposed Model No Label No Label Name Variables
1 SC1 Leadership S1+S2+S3+S4+S5+S6+S7
2 SC2 Planning& Organization S8+S9+S10+S11+S12+S13
3 SC3 Quality Awareness S14
4 SC4 Influencing Others S15+S16+S17
5 SC5 Specialist Knowledge S18+S19+S20+S21+S22
6 SC6 Problem Solving& Analysis S23+S24+S25
7 SC7 Verbal Communication S26+S27+S28+S29
8 SC8 Written Communication S30+S31
9 SC9 Commercial Approach S32+S33+S34+S35+S36
10 SC10 Creativity &Innovation S37+S38+S39
11 SC11 Action Oriented S40+S41
12 SC12 Strategic S42+S43+S44
13 SC13 Interpersonal Relations S45+S46+S47+S48+S49+S50
14 SC14 Flexibility S51+S52+S53
15 SC15 Self Awareness S54+S55+S56+S57+S58+S59
16 SC16 Motivation S60+S61+S62+S63+S64
17 SC17 Management S65+S66+S67+S68
18 SC18 Area of Business Activity S69+S70+S71
19 SC19 Customer Care S72+S73
97
20 SC20 Business Ethic S74+S75
21 SC21 HR Strategy S76+S77+S78+S79
22 SC22 Performance Management S80
23 SC23 Individual Development S81+S82
24 SC24 Crisis Management S83
25 SC25 Economic Conditions S84+S85+S86
26 SC26 Competition S87+S88
27 SC27 Social Life Balance S89
28 SC28 Family Life Balance S90
29 SC29 Work Content S91
30 SC30 Business Process S92
31 SC31 Work Load S93
32 SC32 Responsibility Area S94
4. The number of sub-groups is 16 for dependent and 16 for independent
variables. The items will be exculeded from the sub-groups if the value of Cronbach Alpha is
lower then 0,65.
Table 17: Modified Dependent and Independent List After Reliability Analysis
No Label No Label Name Variables
1 SC1 Leadership S1+S2+S3+S4+S5+ S7
2 SC2 Planning& Organization S9+ S11+S12+S13
3 SC3 Quality Awareness S14
98
5 SC5 Specialist Knowledge S18+S19+S20+S21+S22
7 SC7 Verbal Communication S26+S27+S28+S29
8 SC8 Written Communication S30+S31
9 SC9 Commercial Approach S32+S33+S34
12 SC12 Strategic S42+S43+S44
13 SC13 Interpersonal Relations S45+S46+S47+S48+S49+S50
15 SC15 Self Awareness S54+S55+S56+S57+S58+S59
16 SC16 Motivation S60+S61+S62+S63+S64
17 SC17 Management S65+S66+S67+S68
18 SC18 Area of Business Activity S69+S70+S71
19 SC19 Customer Care S72+S73
20 SC20 Business Ethic S74+S75
21 SC21 HR Strategy S76+S77+S78+S79
22 SC22 Performance Management S80
23 SC23 Individual Development S81+S82
24 SC24 Crisis Management S83
25 SC25 Economic Conditions S84+S85+S86
27 SC27 Social Life Balance S89
28 SC28 Family Life Balance S90
29 SC29 Work Content S91
30 SC30 Business Process S92
31 SC31 Work Load S93
32 SC32 Responsibility Area S94
99
5. Total score for each sub-groups will be gathered into the main components
as showed in Table 12.
Table 18: First Modified Model - Total Scores of Sub Componets in Dependent and Independent Variables
No Label No Label Name Variables
1 C1 Management Competencies SC1+SC2+SC3
2 C2 Specialties Competencies SC5+ SC7+SC8
3 C3 Entrepreneurship Competencies SC9+SC12
4 C4 Personal Competencies SC13+ SC15+SC16
5 C5 Company Core Competency SC17+SC18+SC19+SC20
6 C6 Human Resource Management SC21+SC22+SC23+SC24
7 C7 Environmental Changes SC25+ SC27+SC28
8 C8 Work Competencies SC29+SC30+SC31+SC32
100
6. Consistency Analysis is performed for each group.
Table 19: Second Modified Model
7. As a result total score of main components will be gathered into core
concepts as main individual competency.
Table 20: Core Concept in The Propesed Model
No Label No Label Name Variables
1 C1 Management Competencies SC1+SC2
2 C2 Specialties Competencies SC5+ SC7+SC8
3 C3 Entrepreneurship Competencies SC9+SC12
4 C4 Personal Competencies SC13+ SC15+SC16
5 C5 Company Core Competency SC17+SC18+SC19+SC20
6 C6 Human Resource Management SC21+SC22+SC23+SC24
7 C7 Environmental Changes SC27+SC28
8 C8 Work Competencies SC29+SC30+SC31+SC32
No Label No Label Name Variables
5 CC Individual Competency C1+C2+C3+C4
101
8. Modified Proposed Model After RA
Figure 28: Modified Proposed Model
CC-Individual Competencies C5-Company Core
Competencies
C6-HRM Competencies
C7-Environmental Changes
C8-Work Competencies
C1-Management Competencies
C2-Specialties Competencies
C3-Entrepreneurship Competencies
C4-Personal Competencies
Dependent Variables
Independent Variables
Demographic Variables
1. Age 2. Gender 3. Marital Status 4. Education 5. Occupation 6. Years of Employed 7. Type of Company 8. Department 9. Position 10. Total years of
Employed in Current Company
11. Total Number of Employee
12. Monthly Salary
102
Figure 29: Dependent Variable List in Modified Proposed Model
C1-Management Competencies
C2-Specialties Competencies
C3-Entrepreneurship Competencies
C4-Personal Competencies
SC1-Leadership S1-Motivate Others S2-Taking Responsibility S3-Decision Making S4-Flexibility S5-Delegation S7-Long Term View
SC2-Planning& Organization
S9-Evaluative S11-Effective Time Planning S12-Organizing S13-Planning
SC5-Specialist Knowledge
S18-Conceptual S19-Follows Technology S20-Numerical Evaluation S21-Open to learn S22-Confident about knowledge
SC7-Verbal Communication
S26-Effective speaking S27-Speaking Thoughtfully S28-Outspoken S29-Presenting
SC8-Written Communication
S30-Cares writing rules S31-Effective writing
SC9-Commercial Approach
S32-Competitive S33-Decisive S34-Customer Orientation
SC12-Strategic S42-Loyalty S43-Visionary S44-Strategic
SC13-Interpersonal Relations
S45-Team Work S46-Supportive S47-Encouraging S48-Responsive S49-Trust to Others S50-Behavioral
SC15-Self Awareness
S54-Vigorous S55-Calm S56-Patient S57-Open to Critics S58-Emotionally Controlled S59-Anxious
SC16-Motivation S60-Energetic S61-Optimistic S62-Achieving S63-Confident S64- Ambitious
CC - Individual Competencies
103
Figure 30: Independent Variable List in Modified Proposed Model
C5-Company Core Competencies
C6-Human Resource Management
C7-Environmental Changes
C8-Work Competencies
SC17-Management S65- Leadership S66-Flexibility S67-Responsibility S68-Vision&Mission
SC18-Area of Business Activity
S69-Profitability S70-Product& Service S71-Innovation
SC19-Customer Care S72-Customer Relationship Management S73-Quality Orientation
SC20-Business Ethic S74-Equality S75-Transparancy
SC21-HR Strategy S76-HR Strategy S77-Employee Support Program S78-Recruitment S79-Firing
SC22-Performance Management
S80-Performance Management Assesment
SC23-Individual Development
S81-Individual Development S82-Career Planning
SC24-Crisis Management
S83-Crisis Management
SC27-Social Life Balance
S89-Social Life Balance
SC28-Family Life Balance
S90-Family Life Balance
SC29-Work Content
S91-Job Description
SC30-Business Process
S92-Workflow SC31-Work Load
S93-Work Load SC32-Responsibility Area
S94-Job Responsibility Area
104
6.2.2. MANOVA Analysis for the Modifed Proposed Model
Dependent Variables C1 C2 C3 C4
Covariates C5 C6 C7 C8 Age Total Year of Employement Years of Employementin
Company Monthly Salary
Fixed Factors Gender Marital Status Education Occupation Department Title
105
6.2.3. ANOVA Analysis for the Proposed Model
6.2.4. MAC for the Proposed Model
CC Individual Competency
Demographic Variables Age – Ordinal Scale Gender – Nominal Scale Marital Status – Nominal Scale Education – Nominal Scale Occupation – Nominal Scale Total Year of Employement – Ordinal
Scale Department – Nominal Scale Title – Ordinal Scale Years of Employement in Company –
Ordinal Scale Monthly Salary – Ordinal Scale
Dependent Variable CC=C1+C2+C3+C4
Demographic Variables Gender Marital Status Education Department Title
106
6.2.5. Multiple Regression Analysis for the Proposed Model
Dependent Variables CC
Independent Variables C5 C6 C7 C8
107
7. FINDINGS
7.1. Findings of Reliability Analysis (RA)
7.1.1. RA for Dependent Variables
7.1.1.1. RA for 64 Dependent Items All Together
The Cronbach’s Alpha is 0,885 > 0,65. The result is items are consistent
Reliability Statistics
Cronbach's Alpha N of Items
,885 64
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S1 252,0787 1091,051 ,541 ,882 S2 251,7079 1110,232 ,357 ,884 S3 252,0112 1094,875 ,586 ,882 S4 252,2135 1100,920 ,443 ,883 S5 252,5618 1107,135 ,270 ,884 S6 253,6854 1108,354 ,234 ,885 S7 252,3483 1097,548 ,419 ,883 S8 251,5618 1098,204 ,056 ,899 S9 251,8764 1105,996 ,448 ,883 S10 251,2697 1166,336 -,176 ,905 S11 252,0337 1110,965 ,322 ,884 S12 251,9551 1094,089 ,601 ,882 S13 252,2135 1094,011 ,562 ,882 S14 251,7753 1100,722 ,503 ,883 S15 251,8989 1101,319 ,454 ,883 S16 251,8315 1100,096 ,450 ,883 S17 251,4719 1110,343 ,512 ,883 S18 251,7416 1102,307 ,535 ,883 S19 251,8090 1101,384 ,533 ,883 S20 252,2472 1089,461 ,596 ,881 S21 252,0562 1088,008 ,594 ,881 S22 252,0674 1097,541 ,582 ,882
108
S23 252,1124 1100,760 ,462 ,883 S24 251,8427 1101,611 ,543 ,883 S25 251,9438 1092,781 ,683 ,881 S26 252,0337 1096,124 ,557 ,882 S27 251,8202 1102,263 ,511 ,883 S28 251,8652 1101,936 ,501 ,883 S29 252,3596 1100,369 ,426 ,883 S30 252,3371 1091,931 ,516 ,882 S31 251,8539 1100,853 ,549 ,882 S32 251,8315 1100,369 ,446 ,883 S33 252,1685 1094,664 ,451 ,882 S34 252,2247 1092,722 ,537 ,882 S35 251,4270 1049,838 ,230 ,893 S36 252,5281 1106,229 ,259 ,884 S37 252,6292 1088,827 ,529 ,882 S38 252,5056 1110,412 ,271 ,884 S39 251,7191 1108,113 ,470 ,883 S40 251,7753 1085,540 ,099 ,898 S41 252,2472 1092,825 ,494 ,882 S42 252,1011 1094,387 ,561 ,882 S43 252,0899 1089,333 ,601 ,881 S44 252,1124 1101,328 ,434 ,883 S45 251,7640 1105,228 ,542 ,883 S46 251,8989 1102,046 ,448 ,883 S47 252,0337 1094,942 ,562 ,882 S48 251,8652 1103,868 ,533 ,883 S49 253,1124 1101,055 ,336 ,883 S50 252,5056 1092,639 ,480 ,882 S51 251,5618 1103,317 ,563 ,883 S52 253,0449 1098,453 ,350 ,883 S53 252,9775 1103,886 ,323 ,884 S54 252,1461 1103,944 ,371 ,883 S55 252,5393 1107,615 ,252 ,884 S56 252,2921 1094,255 ,510 ,882 S57 252,7191 1098,363 ,355 ,883 S58 252,6966 1115,668 ,211 ,885 S59 252,2360 1095,160 ,454 ,882 S60 253,3034 1101,668 ,304 ,884 S61 252,4719 1091,002 ,483 ,882 S62 252,0449 1099,703 ,464 ,883 S63 251,8652 1102,323 ,562 ,883 S64 251,4719 1112,457 ,477 ,884
109
7.1.1.2. RA for C1
The Cronbach’s Alpha is 0,518 < 0,65. The result is items are inconsistent.
Cronbach’s Alpha if İtem Deleted in item total statistic table checked. Cronbach Alpha
increased to 0,657 if item S10 exluded.
Reliability Statistics
Cronbach's Alpha N of Items ,518 17
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S1 65,4808 86,155 ,404 ,475 S2 65,1250 89,373 ,322 ,491 S3 65,4135 86,148 ,489 ,471 S4 65,6923 90,099 ,209 ,501 S5 66,0192 90,737 ,116 ,512 S6 67,0962 91,214 ,080 ,519 S7 65,7212 85,310 ,393 ,473 S8 65,0385 69,571 ,145 ,565 S9 65,3077 87,089 ,477 ,476 S10 64,7500 86,519 -,091 ,657 S11 65,4904 90,699 ,192 ,503 S12 65,4519 85,609 ,486 ,469 S13 65,6635 86,303 ,430 ,474 S14 65,2115 86,732 ,479 ,474 S15 65,3365 88,284 ,324 ,488 S16 65,3365 91,080 ,155 ,507 S17 64,9423 91,880 ,253 ,503
Reliability Analysis performed after Item S10 deleted. Cronbach Alpha increased to
0,658 < 0,65. Items are consistent
110
Reliability Statistics
Cronbach's Alpha N of Items
,658 16
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S1 60,7238 75,048 ,523 ,617 S2 60,3714 80,332 ,318 ,642 S3 60,6762 77,356 ,478 ,627 S4 60,9333 79,274 ,297 ,641 S5 61,2571 79,212 ,212 ,650 S6 62,3524 80,538 ,135 ,661 S7 60,9619 76,383 ,393 ,629 S8 60,2857 61,995 ,128 ,779 S9 60,5524 78,365 ,459 ,631 S11 60,7524 79,592 ,297 ,642 S12 60,6952 77,022 ,467 ,626 S13 60,9143 77,656 ,415 ,631 S14 60,4571 78,424 ,436 ,632 S15 60,5810 78,361 ,374 ,635 S16 60,5810 79,419 ,282 ,643 S17 60,1905 80,656 ,423 ,639
7.1.1.3. RA for C2
The Cronbach’s Alpha is 0,724 > 0,65. Items are consistent
Reliability Statistics
Cronbach's Alpha N of Items
,724 14
111
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S18 52,9818 107,174 ,504 ,703 S19 53,0818 106,113 ,535 ,700 S20 53,5182 102,931 ,558 ,693 S21 53,3727 104,695 ,468 ,700 S22 53,3727 106,474 ,519 ,701 S23 52,9455 75,942 ,187 ,890 S24 53,1273 104,846 ,600 ,696 S25 53,2273 104,930 ,584 ,696 S26 53,3182 104,806 ,529 ,698 S27 53,0364 109,320 ,349 ,712 S28 53,2273 104,874 ,519 ,698 S29 53,6818 101,705 ,574 ,690 S30 53,6273 103,667 ,485 ,698 S31 53,2091 104,497 ,551 ,696
7.1.1.4. RA for C3
The Cronbach’s Alpha is 0,617 < 0,65. Items are inconsistent. Cronbach’s Alpha if
İtem Deleted in item total statistic table checked. Cronbach Alpha increased to 0,704 if item
S40 exluded.
Reliability Statistics
Cronbach's Alpha N of Items
,617 13
112
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S32 47,2768 95,517 ,432 ,584 S33 47,6250 91,966 ,515 ,569 S34 47,6518 95,688 ,415 ,585 S35 46,9107 81,397 ,137 ,681 S36 47,9464 96,087 ,277 ,597 S37 48,0000 93,297 ,494 ,574 S38 47,9643 95,873 ,365 ,589 S39 47,1696 98,521 ,417 ,593 S40 47,2946 85,237 ,071 ,706 S41 47,6964 93,330 ,459 ,576 S42 47,5804 94,660 ,465 ,580 S43 47,5089 93,748 ,504 ,575 S44 47,5893 96,496 ,383 ,589
Reliability Analysis performed after Item S40 deleted. Cronbach Alpha increased to
0,706 > 0,65. Items are consistent.
Reliability Statistics
Cronbach's Alpha N of Items ,706 12
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S32 43,0536 74,952 ,476 ,677 S33 43,4018 71,864 ,551 ,665 S34 43,4286 75,616 ,430 ,681 S35 42,6875 59,802 ,173 ,824 S36 43,7232 74,761 ,336 ,689 S37 43,7768 73,562 ,505 ,672 S38 43,7411 76,284 ,353 ,688 S39 42,9464 77,889 ,458 ,685 S41 43,4732 73,369 ,479 ,673 S42 43,3571 74,484 ,493 ,675 S43 43,2857 73,665 ,532 ,670 S44 43,3661 76,162 ,407 ,684
113
7.1.1.5. RA for C4
The Cronbach’s Alpha is 0,879 > 0,65. Items are consistent
Reliability Statistics
Cronbach's Alpha N of Items
,879 20
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S45 71,1308 150,303 ,588 ,872 S46 71,2617 147,837 ,578 ,871 S47 71,3645 147,404 ,609 ,870 S48 71,2056 149,769 ,613 ,871 S49 72,4299 146,436 ,455 ,875 S50 71,8224 146,110 ,518 ,873 S51 70,9813 148,886 ,625 ,871 S52 72,3271 146,071 ,453 ,875 S53 72,2523 148,587 ,418 ,876 S54 71,5794 149,227 ,417 ,876 S55 71,8037 152,291 ,280 ,881 S56 71,6168 146,729 ,589 ,870 S57 72,0467 145,460 ,474 ,874 S58 72,0467 151,271 ,367 ,878 S59 71,5701 146,757 ,525 ,872 S60 72,4953 149,366 ,333 ,880 S61 71,7757 146,270 ,523 ,872 S62 71,4206 145,869 ,617 ,870 S63 71,2897 149,868 ,567 ,872 S64 70,9252 151,881 ,510 ,874
114
7.1.1.6. RA for SC1
The Cronbach’s Alpha is 0,589 < 0,7. The items are inconsistent. Cronbach’s Alpha
if İtem Deleted in item total statistic table checked. Cronbach Alpha increased to 0, 631 if
item S6 deleted
Reliability Statistics
Cronbach's Alpha N of Items
,589 7
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S1 22,5135 14,107 ,526 ,477 S2 22,1441 17,343 ,197 ,584 S3 22,4685 15,142 ,470 ,506 S4 22,7477 15,845 ,263 ,566 S5 22,9820 15,054 ,251 ,576 S6 24,0901 15,683 ,136 ,631 S7 22,7297 14,144 ,430 ,505
Reliability Analysis performed after Item S6 deleted. Cronbach Alpha increased to
0,679 > 0,65. Items are consistent.
Reliability Statistics
Cronbach's Alpha N of Items
,679 6
115
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S1 19,9554 10,602 ,574 ,513 S2 19,5804 13,039 ,325 ,610 S3 19,9018 11,531 ,530 ,541 S4 20,1786 12,112 ,311 ,615 S5 20,4107 12,316 ,183 ,679 S7 20,1518 11,337 ,379 ,589
7.1.1.7. RA for SC2
The Cronbach’s Alpha is 0,233 < 0,65. The items are inconsistent. Cronbach’s
Alpha if İtem Deleted in item total statistic table checked. Cronbach Alpha increased to 0,
305 if item S10 deleted
Reliability Statistics
Cronbach's Alpha N of Items
,233 6
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S8 21,1161 23,311 ,091 ,252 S9 21,3750 37,750 ,315 ,158 S10 20,8661 25,108 ,052 ,305 S11 21,5714 41,004 -,020 ,255 S12 21,5179 36,973 ,322 ,143 S13 21,7679 36,829 ,305 ,143
Reliability Analysis performed after Item S8 deleted. Cronbach Alpha increased to
0,697 >0,65.
116
Reliability Statistics
Cronbach's Alpha N of Items
,304 5
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S8 16,3451 8,121 ,082 ,697 S9 16,6018 21,545 ,328 ,213 S11 16,8142 22,331 ,152 ,273 S12 16,7434 20,889 ,336 ,193 S13 17,0000 20,643 ,333 ,187
Cronbach Alpha increased to 0,697. The items are consistent.
Reliability Statistics
Cronbach's Alpha N of Items
,697 4
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S9 12,0708 5,549 ,454 ,651 S11 12,2832 5,080 ,420 ,673 S12 12,2124 4,794 ,545 ,591 S13 12,4690 4,698 ,515 ,610
117
7.1.1.8. RA for SC4
The Cronbach’s Alpha is 0,599 < 0,65. The items are inconsistent. All items are
deleted from the model.
Reliability Statistics
Cronbach's Alpha N of Items
,599 3
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S15 8,7073 2,717 ,339 ,597 S16 8,7967 1,885 ,499 ,355 S17 8,3984 3,110 ,434 ,499
7.1.1.9. RA for SC5
The Cronbach’s Alpha is 0,731 > 0,65. The items are consistent.
Reliability Statistics
Cronbach's Alpha N of Items
,731 5
118
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S18 16,1111 8,444 ,547 ,668 S19 16,2051 8,044 ,620 ,641 S20 16,6496 8,040 ,407 ,724 S21 16,4786 7,131 ,592 ,642 S22 16,5043 9,183 ,340 ,737
7.1.1.10. RA for SC6
The Cronbach’s Alpha is 0,214 < 0,65. The items are inconsistent. All items are
deleted from the model.
Reliability Statistics
Cronbach's Alpha N of Items
,214 3
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S23 8,2727 2,717 ,209 ,599 S24 8,3884 25,306 ,275 ,122 S25 8,5785 25,346 ,229 ,138
7.1.1.11. RA for SC7
The Cronbach’s Alpha is 0,669 > 0,65. The items are consistent.
Reliability Statistics
Cronbach's Alpha N of Items
,669 4
119
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S26 12,0593 5,048 ,606 ,494 S27 11,7542 6,785 ,279 ,700 S28 11,9746 5,085 ,576 ,514 S29 12,3898 5,642 ,369 ,663
7.1.1.12. RA for SC8
Reliability Statistics
Cronbach's Alpha N of Items
,713 2
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S30 4,1240 1,026 ,560 .(a) S31 3,7603 1,400 ,560 .(a)
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
7.1.1.13. RA for SC9
The Cronbach’s Alpha is 0,389 < 0,65. The items are inconsistent. Cronbach’s
Alpha if İtem Deleted in item total statistic table checked. Cronbach Alpha increased to 0,
616 if item S35 deleted
Reliability Statistics
Cronbach's Alpha N of Items ,389 5
120
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S32 16,0259 25,312 ,307 ,312 S33 16,3534 23,378 ,408 ,249 S34 16,3879 25,074 ,319 ,305 S35 15,6638 11,269 ,160 ,616 S36 16,6724 25,213 ,183 ,353
Reliability Statistics The Cronbach’s Alpha is 0,616 < 0,65. The items are inconsistent. Cronbach Alpha
increased to 0, 710 if item S36 deleted
Cronbach's Alpha N of Items
,616 4
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S32 11,4138 7,097 ,510 ,471 S33 11,7414 6,280 ,545 ,426 S34 11,7759 7,601 ,393 ,550 S36 12,0603 7,622 ,202 ,710
The Cronbach’s Alpha is 0,699 > 0,65. The items are consistent.
Reliability Statistics
Cronbach's Alpha N of Items
,699 3
121
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S32 7,8051 4,004 ,526 ,597 S33 8,1441 3,355 ,560 ,550 S34 8,1525 4,147 ,467 ,665
7.1.1.14. RA for SC10
The Cronbach’s Alpha is 0,589 < 0,65. The items are inconsistent. All items are
deleted from the model.
Reliability Statistics
Cronbach's Alpha N of Items
,589 3
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S37 7,8843 2,753 ,472 ,367 S38 7,8347 2,639 ,457 ,394 S39 7,0909 4,133 ,288 ,630
7.1.1.15. RA for SC11
The Cronbach’s Alpha is 0,097 < 0,65. The items are inconsistent. All items are
deleted from the model.
Reliability Statistics
Cronbach's Alpha N of Items
,097 2
122
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S40 3,8033 1,564 ,085 .(a) S41 4,2049 14,379 ,085 .(a)
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
7.1.1.16. RA for SC12
The Cronbach’s Alpha is 0,682 > 0,65. The items are consistent.
Reliability Statistics
Cronbach's Alpha N of Items
,682 3
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S42 7,9836 3,653 ,413 ,690 S43 7,9098 3,124 ,579 ,474 S44 8,0082 3,413 ,499 ,583
7.1.1.17. RA for SC13
The Cronbach’s Alpha is 0,771 > 0,65. The items are consistent.
Reliability Statistics
Cronbach's Alpha N of Items
,771 6
123
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S45 19,0085 14,778 ,582 ,726 S46 19,0932 14,017 ,612 ,714 S47 19,2627 13,597 ,639 ,706 S48 19,0508 15,211 ,574 ,730 S49 20,3220 14,460 ,320 ,804 S50 19,7034 13,527 ,505 ,743
7.1.1.18. RA for SC14
The Cronbach’s Alpha is 0,545 < 0,65. The items are inconsistent. All items are
deleted from model.
Reliability Statistics
Cronbach's Alpha N of Items
,545 3
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S51 6,3805 4,988 ,297 ,537 S52 7,6195 3,274 ,366 ,441 S53 7,5929 3,404 ,433 ,311
7.1.1.19. RA for SC15
The Cronbach’s Alpha is 0,671 > 0,65. The items are consistent.
124
Reliability Statistics
Cronbach's Alpha N of Items
,671 6
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S54 17,9391 15,566 ,404 ,628 S55 18,1391 16,507 ,268 ,677 S56 17,9913 15,079 ,585 ,575 S57 18,4609 15,216 ,354 ,649 S58 18,4348 16,143 ,366 ,641 S59 17,9913 15,096 ,477 ,603
7.1.1.20. RA for SC16
The Cronbach’s Alpha is 0,708 > 0,65. The items are consistent.
Reliability Statistics
Cronbach's Alpha N of Items
,708 5
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S60 16,3362 9,964 ,315 ,751 S61 15,6983 9,708 ,488 ,650 S62 15,3017 9,517 ,639 ,587 S63 15,1810 10,758 ,594 ,622 S64 14,8276 12,005 ,416 ,683
125
7.1.1.21. RA for Modified C1
Reliability Statistics
Cronbach's Alpha N of Items ,606 3
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC1 20,6698 11,347 ,539 ,417 SC2 28,2830 19,633 ,541 ,313 SC3 40,2547 35,239 ,506 ,643
Reliability Statistics
Cronbach's Alpha N of Items
,648 2
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC1 16,3458 8,153 ,506 .(a) SC2 23,9907 15,934 ,506 .(a)
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
7.1.1.22. RA for Modified C2
126
Reliability Statistics
Cronbach's Alpha N of Items
,832 3
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC5 24,0721 19,958 ,732 ,773 SC7 28,3784 24,692 ,776 ,681 SC8 36,6847 35,581 ,692 ,825
7.1.1.23. RA for Modified C3
Reliability Statistics
Cronbach's Alpha N of Items
,720 2
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC9 11,8879 6,709 ,563 .(a) SC12 12,0000 7,478 ,563 .(a)
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
7.1.1.24. RA for Modified C4
Reliability Statistics
Cronbach's Alpha N of Items
,788 3
127
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC13 41,0631 59,932 ,583 ,775 SC15 36,0450 38,480 ,673 ,683 SC16 38,6036 46,369 ,679 ,658
7.1.1.25. RA for CC
Reliability Statistics
Cronbach's Alpha N of Items ,875 4
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted C1 127,6667 384,116 ,757 ,837 C2 122,7957 328,425 ,820 ,803 C3 143,7419 425,172 ,793 ,850 C4 109,6344 265,734 ,750 ,873
128
7.1.1.26. RA for Modified C5
Reliability Statistics
Cronbach's Alpha N of Items ,846 4
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC17 26,0517 45,806 ,789 ,782 SC18 29,0000 60,487 ,800 ,753 SC19 31,8362 79,025 ,709 ,823 SC20 34,3534 71,987 ,590 ,841
7.1.1.27. RA for Modified C6
Reliability Statistics
Cronbach's Alpha N of Items
,752 4
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC21 12,5752 19,747 ,779 ,722 SC22 21,5841 56,584 ,760 ,685 SC23 17,8850 46,638 ,665 ,641 SC24 20,9912 60,312 ,585 ,734
129
7.1.1.28. RA for Modified C7
Reliability Statistics
Cronbach's Alpha N of Items
,484 3
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC25 8,3772 4,149 ,409 ,726 SC27 13,6053 18,347 ,420 ,396 SC28 13,6842 16,926 ,521 ,289
Reliability Statistics
Cronbach's Alpha N of Items
,761 2
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC27 4,1250 1,505 ,616 .(a) SC28 4,2000 1,287 ,616 .(a)
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
130
7.1.1.29. RA for Modified C8
Reliability Statistics
Cronbach's Alpha N of Items
,755 4
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC29 10,3814 10,221 ,632 ,651 SC30 10,6441 10,214 ,643 ,645 SC31 11,5339 9,687 ,568 ,693 SC32 9,9492 13,621 ,385 ,775
131
7.1.2. RA for Independent Variables
7.1.2.1. RA for 30 Independent Items All Together
Reliability Statistics
Cronbach's Alpha N of Items
,958 30
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S65 99,0882 702,477 ,722 ,956 S66 98,8431 712,688 ,587 ,957 S67 99,2549 700,687 ,660 ,957 S68 98,4706 713,361 ,624 ,957 S69 98,6275 707,820 ,628 ,957 S70 98,3235 722,657 ,540 ,957 S71 99,2157 698,587 ,698 ,956 S72 98,0392 726,771 ,524 ,958 S73 98,4216 710,405 ,670 ,957 S74 99,7549 697,118 ,667 ,957 S75 99,3039 695,659 ,714 ,956 S76 99,3235 695,548 ,757 ,956 S77 100,0000 703,248 ,639 ,957 S78 99,7647 700,063 ,699 ,956 S79 99,2745 705,686 ,596 ,957 S80 99,7451 699,222 ,705 ,956 S81 99,0000 707,208 ,667 ,956 S82 99,6078 696,736 ,734 ,956 S83 99,2745 699,171 ,713 ,956 S84 99,1765 693,810 ,775 ,956 S85 99,4608 699,182 ,740 ,956 S86 99,7451 706,984 ,557 ,957 S87 99,5588 694,685 ,740 ,956 S88 98,9020 724,921 ,421 ,958 S89 98,2353 732,063 ,384 ,958 S90 98,3627 720,332 ,531 ,957 S91 98,7745 701,523 ,685 ,956 S92 99,0000 699,149 ,723 ,956 S93 99,9412 694,630 ,692 ,956
132
S94 98,2941 729,081 ,427 ,958
7.1.2.2. RA for C5
Reliability Statistics
Cronbach's Alpha N of Items
,903 11
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S65 37,0172 88,852 ,702 ,891 S66 36,7759 91,306 ,638 ,895 S67 37,1638 88,695 ,642 ,895 S68 36,3362 92,538 ,648 ,895 S69 36,4828 90,391 ,645 ,895 S70 36,2328 95,345 ,583 ,898 S71 37,1121 87,770 ,687 ,892 S72 35,9655 95,686 ,625 ,897 S73 36,2845 90,397 ,743 ,890 S74 37,6379 89,816 ,553 ,901 S75 37,1293 87,540 ,668 ,894
7.1.2.3. RA for C6
Reliability Statistics
Cronbach's Alpha N of Items
,892 8
133
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S76 21,1416 57,783 ,706 ,875 S77 21,7876 57,579 ,691 ,876 S78 21,5664 57,123 ,719 ,873 S79 21,1150 58,978 ,611 ,884 S80 21,5841 56,584 ,760 ,869 S81 20,7876 62,026 ,565 ,888 S82 21,4425 57,499 ,710 ,874 S83 20,9912 60,312 ,585 ,886
7.1.2.4. RA for C7
Reliability Statistics
Cronbach's Alpha N of Items
,817 7
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S84 21,1416 30,837 ,636 ,779 S85 21,4336 30,194 ,711 ,765 S86 21,6549 31,032 ,554 ,795 S87 21,5221 31,037 ,599 ,786 S88 20,8584 34,533 ,481 ,805 S89 20,3274 36,436 ,411 ,815 S90 20,4071 34,458 ,510 ,801
7.1.2.5. RA for C8
Reliability Statistics
Cronbach's Alpha N of Items
,755 4
134
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S91 10,3814 10,221 ,632 ,651 S92 10,6441 10,214 ,643 ,645 S93 11,5339 9,687 ,568 ,693 S94 9,9492 13,621 ,385 ,775
7.1.2.6. RA for SC17
Reliability Statistics
Cronbach's Alpha N of Items
,803 4
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S65 11,0000 10,121 ,689 ,717 S66 10,7607 10,615 ,672 ,727 S67 11,1453 10,142 ,596 ,768 S68 10,3248 12,204 ,526 ,795
7.1.2.7. RA for SC18
Reliability Statistics
Cronbach's Alpha N of Items
,705 3
135
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S69 7,5085 4,560 ,563 ,562 S70 7,2627 5,614 ,557 ,598 S71 8,1271 4,488 ,478 ,688
7.1.2.8. RA for SC19
Reliability Statistics
Cronbach's Alpha N of Items
,811 2
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S72 4,1488 1,411 ,692 .(a) S73 4,4298 1,014 ,692 .(a)
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
7.1.2.9. RA for SC20
Reliability Statistics
Cronbach's Alpha N of Items
,839 2
136
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S74 3,3333 2,291 ,723 .(a) S75 2,8500 2,549 ,723 .(a)
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
7.1.2.10. RA for SC21
Reliability Statistics
Cronbach's Alpha N of Items ,825 4
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S76 8,5913 13,472 ,650 ,779 S77 9,2522 13,103 ,672 ,769 S78 9,0261 12,587 ,738 ,738 S79 8,5826 14,087 ,546 ,826
7.1.2.11. RA for SC23
Reliability Statistics
Cronbach's Alpha N of Items
,774 2
137
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S81 2,9417 2,106 ,635 .(a) S82 3,5667 1,676 ,635 .(a)
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
7.1.2.12. RA for SC25
Reliability Statistics
Cronbach's Alpha N of Items
,776 3
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S84 6,0948 6,608 ,644 ,664 S85 6,3793 6,951 ,606 ,706 S86 6,5948 6,330 ,591 ,726
7.1.2.13. RA for SC26
Reliability Statistics
Cronbach's Alpha N of Items
,473 2
138
Item-Total Statistics
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
7.1.2.14. RA for Modified C5
Reliability Statistics
Cronbach's Alpha N of Items
,846 4
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC17 26,0517 45,806 ,789 ,782 SC18 29,0000 60,487 ,800 ,753 SC19 31,8362 79,025 ,709 ,823 SC20 34,3534 71,987 ,590 ,841
7.1.2.15. RA for Modified C6
Reliability Statistics
Cronbach's Alpha N of Items ,752 4
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted S87 3,7265 1,528 ,315 .(a) S88 3,0171 2,172 ,315 .(a)
139
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC21 12,5752 19,747 ,779 ,722 SC22 21,5841 56,584 ,760 ,685 SC23 17,8850 46,638 ,665 ,641 SC24 20,9912 60,312 ,585 ,734
7.1.2.16. RA for Modified C7
Reliability Statistics
Cronbach's Alpha N of Items
,761 2
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC27 4,1250 1,505 ,616 .(a) SC28 4,2000 1,287 ,616 .(a)
a The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.
7.1.2.17. RA for Modified C8
Reliability Statistics
Cronbach's Alpha N of Items
,755 4
140
Item-Total Statistics
Scale Mean if Item Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Cronbach's Alpha if Item
Deleted SC29 10,3814 10,221 ,632 ,651 SC30 10,6441 10,214 ,643 ,645 SC31 11,5339 9,687 ,568 ,693 SC32 9,9492 13,621 ,385 ,775
141
7.2. MANOVA
Box's Test of Equality of Covariance Matrices(a)
Box's M 21,633F 1,222df1 10df2 280,605Sig. ,276
Tests the null hypothesis that the observed covariance matrices of the dependent variables are equal across groups. a Design: Intercept+C5+C6+C7+C8+AGE+TOTALYEAROFEMPLOYEED+TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY+MONTHLYSALARY+MARITALSTATUS+EDUCATION+DEPARTMENT+TITLE+GENDER+MARITALSTATUS * EDUCATION+MARITALSTATUS * DEPARTMENT+EDUCATION * DEPARTMENT+MARITALSTATUS * EDUCATION * DEPARTMENT+MARITALSTATUS * TITLE+EDUCATION * TITLE+MARITALSTATUS * EDUCATION * TITLE+DEPARTMENT * TITLE+MARITALSTATUS * DEPARTMENT * TITLE+EDUCATION * DEPARTMENT * TITLE+MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE+MARITALSTATUS * GENDER+EDUCATION * GENDER+MARITALSTATUS * EDUCATION * GENDER+DEPARTMENT * GENDER+MARITALSTATUS * DEPARTMENT * GENDER+EDUCATION * DEPARTMENT * GENDER+MARITALSTATUS * EDUCATION * DEPARTMENT * GENDER+TITLE * GENDER+MARITALSTATUS * TITLE * GENDER+EDUCATION * TITLE * GENDER+MARITALSTATUS * EDUCATION * TITLE * GENDER+DEPARTMENT * TITLE * GENDER+MARITALSTATUS * DEPARTMENT * TITLE * GENDER+EDUCATION * DEPARTMENT * TITLE * GENDER+MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE * GENDER
142
Multivariate Tests(d)
Effect Value F Hypothesis df Error df Sig. Noncent.
Parameter Observed Power(a)
Pillai's Trace ,407 2,055(b) 4,000 12,000 ,150 8,222 ,445Wilks' Lambda ,593 2,055(b) 4,000 12,000 ,150 8,222 ,445Hotelling's Trace ,685 2,055(b) 4,000 12,000 ,150 8,222 ,445
Intercept
Roy's Largest Root ,685 2,055(b) 4,000 12,000 ,150 8,222 ,445Pillai's Trace ,047 ,149(b) 4,000 12,000 ,960 ,597 ,072Wilks' Lambda ,953 ,149(b) 4,000 12,000 ,960 ,597 ,072Hotelling's Trace ,050 ,149(b) 4,000 12,000 ,960 ,597 ,072
C5
Roy's Largest Root ,050 ,149(b) 4,000 12,000 ,960 ,597 ,072Pillai's Trace ,133 ,462(b) 4,000 12,000 ,763 1,846 ,124Wilks' Lambda ,867 ,462(b) 4,000 12,000 ,763 1,846 ,124Hotelling's Trace ,154 ,462(b) 4,000 12,000 ,763 1,846 ,124
C6
Roy's Largest Root ,154 ,462(b) 4,000 12,000 ,763 1,846 ,124Pillai's Trace ,520 3,246(b) 4,000 12,000 ,051 12,983 ,655Wilks' Lambda ,480 3,246(b) 4,000 12,000 ,051 12,983 ,655Hotelling's Trace 1,082 3,246(b) 4,000 12,000 ,051 12,983 ,655
C7
Roy's Largest Root 1,082 3,246(b) 4,000 12,000 ,051 12,983 ,655Pillai's Trace ,134 ,464(b) 4,000 12,000 ,761 1,854 ,124Wilks' Lambda ,866 ,464(b) 4,000 12,000 ,761 1,854 ,124Hotelling's Trace ,155 ,464(b) 4,000 12,000 ,761 1,854 ,124
C8
Roy's Largest Root ,155 ,464(b) 4,000 12,000 ,761 1,854 ,124Pillai's Trace ,116 ,394(b) 4,000 12,000 ,809 1,574 ,112Wilks' Lambda ,884 ,394(b) 4,000 12,000 ,809 1,574 ,112Hotelling's Trace ,131 ,394(b) 4,000 12,000 ,809 1,574 ,112
AGE
Roy's Largest Root ,131 ,394(b) 4,000 12,000 ,809 1,574 ,112Pillai's Trace ,088 ,288(b) 4,000 12,000 ,880 1,153 ,094Wilks' Lambda ,912 ,288(b) 4,000 12,000 ,880 1,153 ,094Hotelling's Trace ,096 ,288(b) 4,000 12,000 ,880 1,153 ,094
TOTALYEAROFEMPLOYEED
Roy's Largest Root ,096 ,288(b) 4,000 12,000 ,880 1,153 ,094
143
Pillai's Trace ,224 ,864(b) 4,000 12,000 ,513 3,455 ,200Wilks' Lambda ,776 ,864(b) 4,000 12,000 ,513 3,455 ,200Hotelling's Trace ,288 ,864(b) 4,000 12,000 ,513 3,455 ,200
TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY
Roy's Largest Root ,288 ,864(b) 4,000 12,000 ,513 3,455 ,200Pillai's Trace ,270 1,108(b) 4,000 12,000 ,397 4,431 ,250Wilks' Lambda ,730 1,108(b) 4,000 12,000 ,397 4,431 ,250Hotelling's Trace ,369 1,108(b) 4,000 12,000 ,397 4,431 ,250
MONTHLYSALARY
Roy's Largest Root ,369 1,108(b) 4,000 12,000 ,397 4,431 ,250Pillai's Trace ,105 ,353(b) 4,000 12,000 ,837 1,411 ,105Wilks' Lambda ,895 ,353(b) 4,000 12,000 ,837 1,411 ,105Hotelling's Trace ,118 ,353(b) 4,000 12,000 ,837 1,411 ,105
MARITALSTATUS
Roy's Largest Root ,118 ,353(b) 4,000 12,000 ,837 1,411 ,105Pillai's Trace ,095 ,162 8,000 26,000 ,994 1,298 ,086Wilks' Lambda ,907 ,150(b) 8,000 24,000 ,995 1,199 ,083Hotelling's Trace ,100 ,138 8,000 22,000 ,996 1,101 ,079
EDUCATION
Roy's Largest Root ,062 ,200(c) 4,000 13,000 ,934 ,800 ,080Pillai's Trace ,462 ,490 16,000 60,000 ,943 7,843 ,278Wilks' Lambda ,586 ,445 16,000 37,298 ,958 5,325 ,172Hotelling's Trace ,625 ,410 16,000 42,000 ,972 6,566 ,215
DEPARTMENT
Roy's Largest Root ,478 1,791(c) 4,000 15,000 ,183 7,163 ,419Pillai's Trace ,595 ,655 16,000 60,000 ,825 10,476 ,379Wilks' Lambda ,511 ,573 16,000 37,298 ,884 6,817 ,217Hotelling's Trace ,764 ,501 16,000 42,000 ,932 8,024 ,264
TITLE
Roy's Largest Root ,383 1,435(c) 4,000 15,000 ,271 5,742 ,340Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * EDUCATION
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050
144
Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * DEPARTMENT
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,202 ,761(b) 4,000 12,000 ,570 3,045 ,180Wilks' Lambda ,798 ,761(b) 4,000 12,000 ,570 3,045 ,180Hotelling's Trace ,254 ,761(b) 4,000 12,000 ,570 3,045 ,180
EDUCATION * DEPARTMENT
Roy's Largest Root ,254 ,761(b) 4,000 12,000 ,570 3,045 ,180Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * EDUCATION * DEPARTMENT
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,261 1,061(b) 4,000 12,000 ,417 4,244 ,240Wilks' Lambda ,739 1,061(b) 4,000 12,000 ,417 4,244 ,240Hotelling's Trace ,354 1,061(b) 4,000 12,000 ,417 4,244 ,240
MARITALSTATUS * TITLE
Roy's Largest Root ,354 1,061(b) 4,000 12,000 ,417 4,244 ,240Pillai's Trace ,344 1,571(b) 4,000 12,000 ,245 6,283 ,346Wilks' Lambda ,656 1,571(b) 4,000 12,000 ,245 6,283 ,346Hotelling's Trace ,524 1,571(b) 4,000 12,000 ,245 6,283 ,346
EDUCATION * TITLE
Roy's Largest Root ,524 1,571(b) 4,000 12,000 ,245 6,283 ,346Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * EDUCATION * TITLE
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,304 ,583 8,000 26,000 ,783 4,661 ,213Wilks' Lambda ,705 ,572(b) 8,000 24,000 ,790 4,574 ,205Hotelling's Trace ,404 ,556 8,000 22,000 ,802 4,445 ,196
DEPARTMENT * TITLE
Roy's Largest Root ,368 1,195(c) 4,000 13,000 ,359 4,778 ,274Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * DEPARTMENT * TITLE
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050
145
Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
EDUCATION * DEPARTMENT * TITLE
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
EDUCATION * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * EDUCATION * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
DEPARTMENT * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * DEPARTMENT * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
EDUCATION * DEPARTMENT * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050
146
Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * EDUCATION * DEPARTMENT * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
TITLE * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * TITLE * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
EDUCATION * TITLE * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * EDUCATION * TITLE * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
DEPARTMENT * TITLE * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * DEPARTMENT * TITLE * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
EDUCATION * DEPARTMENT * TITLE * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050
147
Pillai's Trace ,000 .(b) ,000 ,000 . . .Wilks' Lambda 1,000 .(b) ,000 13,500 . . .Hotelling's Trace ,000 .(b) ,000 2,000 . . .
MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE * GENDER
Roy's Largest Root ,000 ,000(b) 4,000 11,000 1,000 ,000 ,050a Computed using alpha = ,05 b Exact statistic c The statistic is an upper bound on F that yields a lower bound on the significance level. d Design: Intercept+C5+C6+C7+C8+AGE+TOTALYEAROFEMPLOYEED+TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY+MONTHLYSALARY+MARITALSTATUS+EDUCATION+DEPARTMENT+TITLE+GENDER+MARITALSTATUS * EDUCATION+MARITALSTATUS * DEPARTMENT+EDUCATION * DEPARTMENT+MARITALSTATUS * EDUCATION * DEPARTMENT+MARITALSTATUS * TITLE+EDUCATION * TITLE+MARITALSTATUS * EDUCATION * TITLE+DEPARTMENT * TITLE+MARITALSTATUS * DEPARTMENT * TITLE+EDUCATION * DEPARTMENT * TITLE+MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE+MARITALSTATUS * GENDER+EDUCATION * GENDER+MARITALSTATUS * EDUCATION * GENDER+DEPARTMENT * GENDER+MARITALSTATUS * DEPARTMENT * GENDER+EDUCATION * DEPARTMENT * GENDER+MARITALSTATUS * EDUCATION * DEPARTMENT * GENDER+TITLE * GENDER+MARITALSTATUS * TITLE * GENDER+EDUCATION * TITLE * GENDER+MARITALSTATUS * EDUCATION * TITLE * GENDER+DEPARTMENT * TITLE * GENDER+MARITALSTATUS * DEPARTMENT * TITLE * GENDER+EDUCATION * DEPARTMENT * TITLE * GENDER+MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE * GENDER
148
Levene's Test of Equality of Error Variances(a) F df1 df2 Sig. C1 2,148 17 23 ,044C2 1,154 17 23 ,368C3 2,115 17 23 ,047C4 1,076 17 23 ,428
Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a Design: Intercept+C5+C6+C7+C8+AGE+TOTALYEAROFEMPLOYEED+TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY+MONTHLYSALARY+MARITALSTATUS+EDUCATION+DEPARTMENT+TITLE+GENDER+MARITALSTATUS * EDUCATION+MARITALSTATUS * DEPARTMENT+EDUCATION * DEPARTMENT+MARITALSTATUS * EDUCATION * DEPARTMENT+MARITALSTATUS * TITLE+EDUCATION * TITLE+MARITALSTATUS * EDUCATION * TITLE+DEPARTMENT * TITLE+MARITALSTATUS * DEPARTMENT * TITLE+EDUCATION * DEPARTMENT * TITLE+MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE+MARITALSTATUS * GENDER+EDUCATION * GENDER+MARITALSTATUS * EDUCATION * GENDER+DEPARTMENT * GENDER+MARITALSTATUS * DEPARTMENT * GENDER+EDUCATION * DEPARTMENT * GENDER+MARITALSTATUS * EDUCATION * DEPARTMENT * GENDER+TITLE * GENDER+MARITALSTATUS * TITLE * GENDER+EDUCATION * TITLE * GENDER+MARITALSTATUS * EDUCATION * TITLE * GENDER+DEPARTMENT * TITLE * GENDER+MARITALSTATUS * DEPARTMENT * TITLE * GENDER+EDUCATION * DEPARTMENT * TITLE * GENDER+MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE * GENDER
149
Tests of Between-Subjects Effects
Source Dependent Variable Type III Sum of Squares df Mean Square F Sig.
Noncent. Parameter
Observed Power(a)
C1 945,558(b) 25 37,822 1,281 ,314 32,029 ,525C2 1458,331(c) 25 58,333 1,186 ,373 29,644 ,486C3 503,172(d) 25 20,127 1,443 ,232 36,067 ,589
Corrected Model
C4 1707,802(e) 25 68,312 ,617 ,861 15,430 ,245C1 229,553 1 229,553 7,776 ,014 7,776 ,741C2 157,737 1 157,737 3,206 ,094 3,206 ,388C3 4,731 1 4,731 ,339 ,569 ,339 ,085
Intercept
C4 70,471 1 70,471 ,637 ,437 ,637 ,116C1 6,844 1 6,844 ,232 ,637 ,232 ,074C2 4,967 1 4,967 ,101 ,755 ,101 ,060C3 ,771 1 ,771 ,055 ,817 ,055 ,056
C5
C4 16,313 1 16,313 ,147 ,706 ,147 ,065C1 25,554 1 25,554 ,866 ,367 ,866 ,141C2 ,129 1 ,129 ,003 ,960 ,003 ,050C3 ,182 1 ,182 ,013 ,911 ,013 ,051
C6
C4 ,014 1 ,014 ,000 ,991 ,000 ,050C1 145,524 1 145,524 4,929 ,042 4,929 ,547C2 596,390 1 596,390 12,123 ,003 12,123 ,902C3 122,136 1 122,136 8,755 ,010 8,755 ,790
C7
C4 219,038 1 219,038 1,979 ,180 1,979 ,261C1 35,893 1 35,893 1,216 ,288 1,216 ,178C2 ,106 1 ,106 ,002 ,964 ,002 ,050C3 6,748 1 6,748 ,484 ,497 ,484 ,100
C8
C4 6,364 1 6,364 ,057 ,814 ,057 ,056C1 11,075 1 11,075 ,375 ,549 ,375 ,089C2 2,879 1 2,879 ,059 ,812 ,059 ,056C3 4,407 1 4,407 ,316 ,582 ,316 ,082
AGE
C4 32,991 1 32,991 ,298 ,593 ,298 ,081
150
C1 26,323 1 26,323 ,892 ,360 ,892 ,143C2 41,327 1 41,327 ,840 ,374 ,840 ,138C3 15,945 1 15,945 1,143 ,302 1,143 ,170
TOTALYEAROFEMPLOYEED
C4 18,974 1 18,974 ,171 ,685 ,171 ,067C1 62,048 1 62,048 2,102 ,168 2,102 ,274C2 16,179 1 16,179 ,329 ,575 ,329 ,084C3 ,442 1 ,442 ,032 ,861 ,032 ,053
TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY
C4 7,698 1 7,698 ,070 ,796 ,070 ,057C1 68,185 1 68,185 2,310 ,149 2,310 ,296C2 115,292 1 115,292 2,344 ,147 2,344 ,300C3 ,242 1 ,242 ,017 ,897 ,017 ,052
MONTHLYSALARY
C4 7,765 1 7,765 ,070 ,795 ,070 ,057C1 2,641 1 2,641 ,089 ,769 ,089 ,059C2 16,682 1 16,682 ,339 ,569 ,339 ,085C3 19,772 1 19,772 1,417 ,252 1,417 ,200
MARITALSTATUS
C4 87,264 1 87,264 ,788 ,389 ,788 ,132C1 6,577 2 3,289 ,111 ,895 ,223 ,064C2 26,761 2 13,380 ,272 ,766 ,544 ,085C3 8,916 2 4,458 ,320 ,731 ,639 ,092
EDUCATION
C4 3,129 2 1,564 ,014 ,986 ,028 ,052C1 31,910 4 7,978 ,270 ,893 1,081 ,094C2 81,691 4 20,423 ,415 ,795 1,661 ,121C3 15,999 4 4,000 ,287 ,882 1,147 ,097
DEPARTMENT
C4 96,293 4 24,073 ,217 ,925 ,870 ,085C1 114,914 4 28,729 ,973 ,451 3,892 ,236C2 116,967 4 29,242 ,594 ,672 2,378 ,156C3 63,162 4 15,790 1,132 ,379 4,527 ,272
TITLE
C4 68,267 4 17,067 ,154 ,958 ,617 ,074C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
GENDER
C4 ,000 0 . . . ,000 .
151
C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * EDUCATION
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * DEPARTMENT
C4 ,000 0 . . . ,000 .C1 4,701 1 4,701 ,159 ,695 ,159 ,066C2 41,600 1 41,600 ,846 ,372 ,846 ,138C3 26,257 1 26,257 1,882 ,190 1,882 ,250
EDUCATION * DEPARTMENT
C4 1,419 1 1,419 ,013 ,911 ,013 ,051C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * EDUCATION * DEPARTMENT
C4 ,000 0 . . . ,000 .C1 111,484 1 111,484 3,776 ,071 3,776 ,444C2 34,791 1 34,791 ,707 ,414 ,707 ,124C3 12,922 1 12,922 ,926 ,351 ,926 ,147
MARITALSTATUS * TITLE
C4 107,247 1 107,247 ,969 ,341 ,969 ,152C1 186,669 1 186,669 6,323 ,024 6,323 ,652C2 97,001 1 97,001 1,972 ,181 1,972 ,260C3 41,331 1 41,331 2,963 ,106 2,963 ,364
EDUCATION * TITLE
C4 3,061 1 3,061 ,028 ,870 ,028 ,053C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * EDUCATION * TITLE
C4 ,000 0 . . . ,000 .C1 36,894 2 18,447 ,625 ,549 1,250 ,135C2 9,259 2 4,630 ,094 ,911 ,188 ,062C3 4,352 2 2,176 ,156 ,857 ,312 ,070
DEPARTMENT * TITLE
C4 27,897 2 13,948 ,126 ,883 ,252 ,066
152
C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * DEPARTMENT * TITLE
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
EDUCATION * DEPARTMENT * TITLE
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
EDUCATION * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * EDUCATION * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
DEPARTMENT * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * DEPARTMENT * GENDER
C4 ,000 0 . . . ,000 .
153
C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
EDUCATION * DEPARTMENT * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * EDUCATION * DEPARTMENT * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
TITLE * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * TITLE * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
EDUCATION * TITLE * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * EDUCATION * TITLE * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
DEPARTMENT * TITLE * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * DEPARTMENT * TITLE * GENDER
C4 ,000 0 . . . ,000 .
154
C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
EDUCATION * DEPARTMENT * TITLE * GENDER
C4 ,000 0 . . . ,000 .C1 ,000 0 . . . ,000 .C2 ,000 0 . . . ,000 .C3 ,000 0 . . . ,000 .
MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE * GENDER
C4 ,000 0 . . . ,000 .C1 442,832 15 29,522 C2 737,913 15 49,194 C3 209,267 15 13,951
Error
C4 1660,246 15 110,683 C1 66589,000 41 C2 83431,000 41 C3 23946,000 41
Total
C4 142571,000 41 C1 1388,390 40 C2 2196,244 40 C3 712,439 40
Corrected Total
C4 3368,049 40 a Computed using alpha = ,05 b R Squared = ,681 (Adjusted R Squared = ,149) c R Squared = ,664 (Adjusted R Squared = ,104) d R Squared = ,706 (Adjusted R Squared = ,217) e R Squared = ,507 (Adjusted R Squared = -,315)
155
Estimated Marginal Means 1. MARITALSTATUS Estimates Dependent Variable MARITALSTATUS Mean Std. Error 95% Confidence Interval
Lower Bound
Upper Bound Lower Bound Upper Bound
C1 1,00 40,145(a,b) 3,453 32,785 47,504
2,00 40,625(a,b) 1,341 37,768 43,483
C2 1,00 46,256(a,b) 4,457 36,756 55,756
2,00 44,238(a,b) 1,731 40,549 47,927
C3 1,00 26,517(a,b) 2,374 21,457 31,576
2,00 23,678(a,b) ,922 21,714 25,642
C4 1,00 64,860(a,b) 6,686 50,609 79,110
2,00 57,402(a,b) 2,596 51,869 62,935
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b Based on modified population marginal mean.
156
Pairwise Comparisons
Dependent Variable (I) MARITALSTATUS (J) MARITALSTATUSMean Difference
(I-J) Std. Error Sig.(a) 95% Confidence Interval for
Difference(a)
Lower Bound Upper Bound
Lower Bound Upper Bound Lower Bound
C1 1,00 2,00 -,481(b,c) 3,940 ,904 -8,878 7,916 2,00 1,00 ,481(b,c) 3,940 ,904 -7,916 8,878C2 1,00 2,00 2,018(b,c) 5,086 ,697 -8,822 12,857 2,00 1,00 -2,018(b,c) 5,086 ,697 -12,857 8,822C3 1,00 2,00 2,838(b,c) 2,708 ,311 -2,934 8,611 2,00 1,00 -2,838(b,c) 2,708 ,311 -8,611 2,934C4 1,00 2,00 7,458(b,c) 7,628 ,344 -8,802 23,717 2,00 1,00 -7,458(b,c) 7,628 ,344 -23,717 8,802
Based on estimated marginal means a Adjustment for multiple comparisons: Bonferroni. b An estimate of the modified population marginal mean (I). c An estimate of the modified population marginal mean (J). Multivariate Tests
Value F Hypothesis df Error df Sig. Noncent.
Parameter Observed Power(a)
Pillai's trace ,127 ,437(b) 4,000 12,000 ,780 1,747 ,119Wilks' lambda ,873 ,437(b) 4,000 12,000 ,780 1,747 ,119Hotelling's trace ,146 ,437(b) 4,000 12,000 ,780 1,747 ,119Roy's largest root ,146 ,437(b) 4,000 12,000 ,780 1,747 ,119
Each F tests the multivariate effect of MARITALSTATUS. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means. a Computed using alpha = ,05 b Exact statistic
157
Univariate Tests
Dependent Variable Sum of
Squares df Mean Square F Sig. Noncent.
Parameter Observed Power(a)
Contrast ,440 1 ,440 ,015 ,904 ,015 ,052C1 Error 442,832 15 29,522 Contrast 7,745 1 7,745 ,157 ,697 ,157 ,066C2 Error 737,913 15 49,194 Contrast 15,325 1 15,325 1,098 ,311 1,098 ,166C3 Error 209,267 15 13,951 Contrast 105,786 1 105,786 ,956 ,344 ,956 ,150C4 Error 1660,246 15 110,683
The F tests the effect of MARITALSTATUS. This test is based on the linearly independent pairwise comparisons among the estimated marginal means. a Computed using alpha = ,05
158
2. EDUCATION Estimates Dependent Variable EDUCATION Mean Std. Error 95% Confidence Interval
Lower Bound
Upper Bound Lower Bound Upper Bound
C1 1,00 40,168(a,b) 3,245 33,252 47,084
2,00 41,053(a,b) 1,306 38,269 43,837
3,00 35,929(a,b) 6,277 22,551 49,307
C2 1,00 44,891(a,b) 4,189 35,963 53,818
2,00 44,694(a,b) 1,686 41,100 48,288
3,00 39,734(a,b) 8,102 22,465 57,004
C3 1,00 23,081(a,b) 2,231 18,327 27,836
2,00 24,448(a,b) ,898 22,534 26,362
3,00 21,737(a,b) 4,315 12,540 30,933
C4 1,00 57,970(a,b) 6,283 44,578 71,361
2,00 58,682(a,b) 2,529 53,292 64,073
3,00 53,405(a,b) 12,153 27,501 79,308
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b Based on modified population marginal mean.
159
Pairwise Comparisons
Dependent Variable (I) EDUCATION (J) EDUCATION
Mean Difference
(I-J) Std. Error Sig.(a) 95% Confidence Interval for
Difference(a)
Lower Bound Upper Bound
Lower Bound Upper Bound Lower Bound
C1 1,00 2,00 -,885(b,c) 3,560 1,000 -10,476 8,705 3,00 4,239(b,c) 7,554 1,000 -16,110 24,587 2,00 1,00 ,885(b,c) 3,560 1,000 -8,705 10,476 3,00 5,124(b,c) 6,378 1,000 -12,057 22,305 3,00 1,00 -4,239(b,c) 7,554 1,000 -24,587 16,110 2,00 -5,124(b,c) 6,378 1,000 -22,305 12,057C2 1,00 2,00 ,196(b,c) 4,596 1,000 -12,184 12,577 3,00 5,156(b,c) 9,751 1,000 -21,111 31,423 2,00 1,00 -,196(b,c) 4,596 1,000 -12,577 12,184 3,00 4,960(b,c) 8,233 1,000 -17,219 27,138 3,00 1,00 -5,156(b,c) 9,751 1,000 -31,423 21,111 2,00 -4,960(b,c) 8,233 1,000 -27,138 17,219C3 1,00 2,00 -1,366(b,c) 2,447 1,000 -7,959 5,226 3,00 1,345(b,c) 5,193 1,000 -12,644 15,333 2,00 1,00 1,366(b,c) 2,447 1,000 -5,226 7,959 3,00 2,711(b,c) 4,385 1,000 -9,100 14,522 3,00 1,00 -1,345(b,c) 5,193 1,000 -15,333 12,644 2,00 -2,711(b,c) 4,385 1,000 -14,522 9,100C4 1,00 2,00 -,713(b,c) 6,894 1,000 -19,283 17,857 3,00 4,565(b,c) 14,627 1,000 -34,836 43,965 2,00 1,00 ,713(b,c) 6,894 1,000 -17,857 19,283 3,00 5,278(b,c) 12,350 1,000 -27,990 38,545 3,00 1,00 -4,565(b,c) 14,627 1,000 -43,965 34,836 2,00 -5,278(b,c) 12,350 1,000 -38,545 27,990
Based on estimated marginal means a Adjustment for multiple comparisons: Bonferroni. b An estimate of the modified population marginal mean (I). c An estimate of the modified population marginal mean (J).
160
Multivariate Tests
Value F Hypothesis df Error df Sig. Noncent.
Parameter Observed Power(a)
Pillai's trace ,081 ,137 8,000 26,000 ,997 1,097 ,080Wilks' lambda ,920 ,127(b) 8,000 24,000 ,997 1,018 ,077Hotelling's trace ,085 ,117 8,000 22,000 ,998 ,938 ,074Roy's largest root ,064 ,209(c) 4,000 13,000 ,929 ,834 ,082
Each F tests the multivariate effect of EDUCATION. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means. a Computed using alpha = ,05 b Exact statistic c The statistic is an upper bound on F that yields a lower bound on the significance level. Univariate Tests
Dependent Variable Sum of
Squares df Mean Square F Sig. Noncent.
Parameter Observed Power(a)
Contrast 21,988 2 10,994 ,372 ,695 ,745 ,099C1 Error 442,832 15 29,522 Contrast 17,852 2 8,926 ,181 ,836 ,363 ,073C2 Error 737,913 15 49,194 Contrast 10,538 2 5,269 ,378 ,692 ,755 ,100C3 Error 209,267 15 13,951 Contrast 22,342 2 11,171 ,101 ,905 ,202 ,063C4 Error 1660,246 15 110,683
The F tests the effect of EDUCATION. This test is based on the linearly independent pairwise comparisons among the estimated marginal means. a Computed using alpha = ,05
161
3. DEPARTMENT Estimates Dependent Variable DEPARTMENT Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 2,00 36,790(a,b) 6,450 23,042 50,537 4,00 38,069(a,b) 4,460 28,563 47,574 5,00 41,246(a,b) 1,563 37,915 44,577 6,00 40,132(a,b) 6,122 27,083 53,180 8,00 40,121(a,b) 2,808 34,136 46,106 10,00 41,244(a,b) 3,924 32,881 49,607C2 2,00 31,321(a,b) 8,326 13,574 49,067 4,00 47,665(a,b) 5,757 35,395 59,935 5,00 44,515(a,b) 2,017 40,215 48,815 6,00 43,555(a,b) 7,903 26,710 60,399 8,00 44,176(a,b) 3,625 36,449 51,902 10,00 48,205(a,b) 5,065 37,410 59,001C3 2,00 25,296(a,b) 4,434 15,846 34,747 4,00 23,584(a,b) 3,066 17,050 30,119 5,00 24,118(a,b) 1,074 21,828 26,408 6,00 23,518(a,b) 4,208 14,548 32,488 8,00 24,213(a,b) 1,930 20,098 28,327 10,00 23,261(a,b) 2,697 17,512 29,010C4 2,00 70,121(a,b) 12,489 43,503 96,740 4,00 56,854(a,b) 8,635 38,449 75,259 5,00 59,475(a,b) 3,026 53,025 65,925 6,00 52,122(a,b) 11,854 26,856 77,388 8,00 57,815(a,b) 5,437 46,226 69,404 10,00 53,445(a,b) 7,597 37,252 69,638
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b Based on modified population marginal mean.
162
Pairwise Comparisons
Dependent Variable (I) DEPARTMENT (J) DEPARTMENT Mean
Difference (I-J) Std. Error Sig.(a) 95% Confidence Interval for Difference(a)
Lower Bound Upper Bound
Lower Bound Upper Bound Lower Bound
C1 2,00 4,00 -1,279(b,c) 7,972 1,000 -29,051 26,494 5,00 -4,456(b,c) 6,678 1,000 -27,720 18,808 6,00 -3,342(b,c) 9,378 1,000 -36,013 29,329 8,00 -3,331(b,c) 7,082 1,000 -28,002 21,339 10,00 -4,454(b,c) 7,596 1,000 -30,918 22,009 4,00 2,00 1,279(b,c) 7,972 1,000 -26,494 29,051 5,00 -3,177(b,c) 4,805 1,000 -19,915 13,561 6,00 -2,063(b,c) 7,881 1,000 -29,520 25,394 8,00 -2,052(b,c) 5,222 1,000 -20,243 16,138 10,00 -3,175(b,c) 6,001 1,000 -24,081 17,730 5,00 2,00 4,456(b,c) 6,678 1,000 -18,808 27,720 4,00 3,177(b,c) 4,805 1,000 -13,561 19,915 6,00 1,114(b,c) 6,107 1,000 -20,163 22,390 8,00 1,125(b,c) 3,227 1,000 -10,117 12,366 10,00 ,001(b,c) 4,286 1,000 -14,928 14,931 6,00 2,00 3,342(b,c) 9,378 1,000 -29,329 36,013 4,00 2,063(b,c) 7,881 1,000 -25,394 29,520 5,00 -1,114(b,c) 6,107 1,000 -22,390 20,163 8,00 ,011(b,c) 6,616 1,000 -23,037 23,059 10,00 -1,112(b,c) 7,262 1,000 -26,410 24,185 8,00 2,00 3,331(b,c) 7,082 1,000 -21,339 28,002 4,00 2,052(b,c) 5,222 1,000 -16,138 20,243 5,00 -1,125(b,c) 3,227 1,000 -12,366 10,117 6,00 -,011(b,c) 6,616 1,000 -23,059 23,037 10,00 -1,123(b,c) 5,224 1,000 -19,322 17,076
163
10,00 2,00 4,454(b,c) 7,596 1,000 -22,009 30,918 4,00 3,175(b,c) 6,001 1,000 -17,730 24,081 5,00 -,001(b,c) 4,286 1,000 -14,931 14,928 6,00 1,112(b,c) 7,262 1,000 -24,185 26,410 8,00 1,123(b,c) 5,224 1,000 -17,076 19,322C2 2,00 4,00 -16,344(b,c) 10,291 1,000 -52,195 19,507 5,00 -13,195(b,c) 8,620 1,000 -43,225 16,836 6,00 -12,234(b,c) 12,106 1,000 -54,408 29,940 8,00 -12,855(b,c) 9,142 1,000 -44,701 18,991 10,00 -16,885(b,c) 9,806 1,000 -51,045 17,276 4,00 2,00 16,344(b,c) 10,291 1,000 -19,507 52,195 5,00 3,150(b,c) 6,202 1,000 -18,457 24,756 6,00 4,110(b,c) 10,174 1,000 -31,333 39,553 8,00 3,489(b,c) 6,740 1,000 -19,992 26,971 10,00 -,541(b,c) 7,747 1,000 -27,527 26,446 5,00 2,00 13,195(b,c) 8,620 1,000 -16,836 43,225 4,00 -3,150(b,c) 6,202 1,000 -24,756 18,457 6,00 ,961(b,c) 7,884 1,000 -26,505 28,426 8,00 ,340(b,c) 4,165 1,000 -14,171 14,850 10,00 -3,690(b,c) 5,532 1,000 -22,963 15,582 6,00 2,00 12,234(b,c) 12,106 1,000 -29,940 54,408 4,00 -4,110(b,c) 10,174 1,000 -39,553 31,333 5,00 -,961(b,c) 7,884 1,000 -28,426 26,505 8,00 -,621(b,c) 8,540 1,000 -30,373 29,131 10,00 -4,651(b,c) 9,374 1,000 -37,307 28,005 8,00 2,00 12,855(b,c) 9,142 1,000 -18,991 44,701 4,00 -3,489(b,c) 6,740 1,000 -26,971 19,992 5,00 -,340(b,c) 4,165 1,000 -14,850 14,171 6,00 ,621(b,c) 8,540 1,000 -29,131 30,373 10,00 -4,030(b,c) 6,743 1,000 -27,522 19,462 10,00 2,00 16,885(b,c) 9,806 1,000 -17,276 51,045 4,00 ,541(b,c) 7,747 1,000 -26,446 27,527 5,00 3,690(b,c) 5,532 1,000 -15,582 22,963
164
6,00 4,651(b,c) 9,374 1,000 -28,005 37,307 8,00 4,030(b,c) 6,743 1,000 -19,462 27,522C3 2,00 4,00 1,712(b,c) 5,480 1,000 -17,380 20,803 5,00 1,178(b,c) 4,591 1,000 -14,814 17,171 6,00 1,778(b,c) 6,447 1,000 -20,681 24,237 8,00 1,083(b,c) 4,868 1,000 -15,876 18,042 10,00 2,035(b,c) 5,222 1,000 -16,157 20,226 4,00 2,00 -1,712(b,c) 5,480 1,000 -20,803 17,380 5,00 -,533(b,c) 3,303 1,000 -12,040 10,973 6,00 ,066(b,c) 5,418 1,000 -18,809 18,941 8,00 -,628(b,c) 3,590 1,000 -13,133 11,876 10,00 ,323(b,c) 4,125 1,000 -14,048 14,694 5,00 2,00 -1,178(b,c) 4,591 1,000 -17,171 14,814 4,00 ,533(b,c) 3,303 1,000 -10,973 12,040 6,00 ,600(b,c) 4,198 1,000 -14,027 15,226 8,00 -,095(b,c) 2,218 1,000 -7,822 7,633 10,00 ,857(b,c) 2,946 1,000 -9,407 11,120 6,00 2,00 -1,778(b,c) 6,447 1,000 -24,237 20,681 4,00 -,066(b,c) 5,418 1,000 -18,941 18,809 5,00 -,600(b,c) 4,198 1,000 -15,226 14,027 8,00 -,694(b,c) 4,548 1,000 -16,538 15,150 10,00 ,257(b,c) 4,992 1,000 -17,133 17,648 8,00 2,00 -1,083(b,c) 4,868 1,000 -18,042 15,876 4,00 ,628(b,c) 3,590 1,000 -11,876 13,133 5,00 ,095(b,c) 2,218 1,000 -7,633 7,822 6,00 ,694(b,c) 4,548 1,000 -15,150 16,538 10,00 ,952(b,c) 3,591 1,000 -11,559 13,462 10,00 2,00 -2,035(b,c) 5,222 1,000 -20,226 16,157 4,00 -,323(b,c) 4,125 1,000 -14,694 14,048 5,00 -,857(b,c) 2,946 1,000 -11,120 9,407 6,00 -,257(b,c) 4,992 1,000 -17,648 17,133 8,00 -,952(b,c) 3,591 1,000 -13,462 11,559C4 2,00 4,00 13,268(b,c) 15,436 1,000 -40,507 67,043
165
5,00 10,646(b,c) 12,930 1,000 -34,399 55,692 6,00 18,000(b,c) 18,159 1,000 -45,260 81,259 8,00 12,306(b,c) 13,712 1,000 -35,462 60,075 10,00 16,676(b,c) 14,709 1,000 -34,564 67,916 4,00 2,00 -13,268(b,c) 15,436 1,000 -67,043 40,507 5,00 -2,621(b,c) 9,303 1,000 -35,030 29,787 6,00 4,732(b,c) 15,261 1,000 -48,432 57,895 8,00 -,961(b,c) 10,110 1,000 -36,183 34,260 10,00 3,408(b,c) 11,620 1,000 -37,071 43,887 5,00 2,00 -10,646(b,c) 12,930 1,000 -55,692 34,399 4,00 2,621(b,c) 9,303 1,000 -29,787 35,030 6,00 7,353(b,c) 11,826 1,000 -33,844 48,550 8,00 1,660(b,c) 6,248 1,000 -20,106 23,426 10,00 6,030(b,c) 8,298 1,000 -22,879 34,938 6,00 2,00 -18,000(b,c) 18,159 1,000 -81,259 45,260 4,00 -4,732(b,c) 15,261 1,000 -57,895 48,432 5,00 -7,353(b,c) 11,826 1,000 -48,550 33,844 8,00 -5,693(b,c) 12,810 1,000 -50,321 38,934 10,00 -1,323(b,c) 14,061 1,000 -50,307 47,660 8,00 2,00 -12,306(b,c) 13,712 1,000 -60,075 35,462 4,00 ,961(b,c) 10,110 1,000 -34,260 36,183 5,00 -1,660(b,c) 6,248 1,000 -23,426 20,106 6,00 5,693(b,c) 12,810 1,000 -38,934 50,321 10,00 4,370(b,c) 10,115 1,000 -30,868 39,607 10,00 2,00 -16,676(b,c) 14,709 1,000 -67,916 34,564 4,00 -3,408(b,c) 11,620 1,000 -43,887 37,071 5,00 -6,030(b,c) 8,298 1,000 -34,938 22,879 6,00 1,323(b,c) 14,061 1,000 -47,660 50,307 8,00 -4,370(b,c) 10,115 1,000 -39,607 30,868
Based on estimated marginal means a Adjustment for multiple comparisons: Bonferroni. b An estimate of the modified population marginal mean (I). c An estimate of the modified population marginal mean (J).
166
Multivariate Tests
Value F Hypothesis df Error df Sig. Noncent.
Parameter Observed Power(a)
Pillai's trace ,608 ,538 20,000 60,000 ,937 10,765 ,338Wilks' lambda ,447 ,560 20,000 40,749 ,917 9,097 ,256Hotelling's trace 1,118 ,587 20,000 42,000 ,900 11,738 ,339Roy's largest root 1,002 3,006(b) 5,000 15,000 ,045 15,028 ,705
Each F tests the multivariate effect of DEPARTMENT. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means. a Computed using alpha = ,05 b The statistic is an upper bound on F that yields a lower bound on the significance level. Univariate Tests
Dependent Variable Sum of
Squares df Mean Square F Sig. Noncent.
Parameter Observed Power(a)
Contrast 27,538 5 5,508 ,187 ,963 ,933 ,081C1 Error 442,832 15 29,522 Contrast 163,966 5 32,793 ,667 ,655 3,333 ,182C2 Error 737,913 15 49,194 Contrast 2,812 5 ,562 ,040 ,999 ,202 ,056C3 Error 209,267 15 13,951 Contrast 188,684 5 37,737 ,341 ,880 1,705 ,111C4 Error 1660,246 15 110,683
The F tests the effect of DEPARTMENT. This test is based on the linearly independent pairwise comparisons among the estimated marginal means. a Computed using alpha = ,05
167
4. TITLE Estimates Dependent Variable TITLE Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 3,00 46,680(a,b) 7,599 30,482 62,877 4,00 37,781(a,b) 4,436 28,326 47,237 5,00 44,079(a,b) 2,599 38,540 49,617 6,00 40,236(a,b) 2,784 34,302 46,169 7,00 39,359(a,b) 1,671 35,797 42,921C2 3,00 53,785(a,b) 9,810 32,876 74,695 4,00 35,097(a,b) 5,726 22,891 47,302 5,00 46,708(a,b) 3,354 39,558 53,857 6,00 42,584(a,b) 3,593 34,925 50,243 7,00 45,735(a,b) 2,157 41,137 50,333C3 3,00 24,831(a,b) 5,224 13,696 35,965 4,00 25,774(a,b) 3,050 19,275 32,274 5,00 25,798(a,b) 1,786 21,991 29,606 6,00 23,320(a,b) 1,914 19,241 27,399 7,00 23,104(a,b) 1,149 20,655 25,552C4 3,00 53,240(a,b) 14,715 21,877 84,603 4,00 65,420(a,b) 8,589 47,111 83,728 5,00 62,837(a,b) 5,031 52,112 73,561 6,00 54,903(a,b) 5,390 43,414 66,391 7,00 56,994(a,b) 3,236 50,097 63,892
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b Based on modified population marginal mean. Pairwise Comparisons
168
Dependent Variable (I) TITLE (J) TITLE Mean
Difference (I-J) Std. Error Sig.(a) 95% Confidence Interval for Difference(a)
Lower Bound Upper Bound
Lower Bound Upper Bound Lower Bound
C1 3,00 4,00 8,898(b,c) 8,904 1,000 -20,360 38,156 5,00 2,601(b,c) 8,142 1,000 -24,155 29,356 6,00 6,444(b,c) 7,750 1,000 -19,022 31,910 7,00 7,320(b,c) 7,830 1,000 -18,409 33,050 4,00 3,00 -8,898(b,c) 8,904 1,000 -38,156 20,360 5,00 -6,298(b,c) 5,360 1,000 -23,912 11,317 6,00 -2,454(b,c) 5,425 1,000 -20,282 15,373 7,00 -1,578(b,c) 4,613 1,000 -16,736 13,580 5,00 3,00 -2,601(b,c) 8,142 1,000 -29,356 24,155 4,00 6,298(b,c) 5,360 1,000 -11,317 23,912 6,00 3,843(b,c) 3,832 1,000 -8,749 16,436 7,00 4,720(b,c) 3,263 1,000 -6,003 15,442 6,00 3,00 -6,444(b,c) 7,750 1,000 -31,910 19,022 4,00 2,454(b,c) 5,425 1,000 -15,373 20,282 5,00 -3,843(b,c) 3,832 1,000 -16,436 8,749 7,00 ,876(b,c) 3,328 1,000 -10,059 11,811 7,00 3,00 -7,320(b,c) 7,830 1,000 -33,050 18,409 4,00 1,578(b,c) 4,613 1,000 -13,580 16,736 5,00 -4,720(b,c) 3,263 1,000 -15,442 6,003 6,00 -,876(b,c) 3,328 1,000 -11,811 10,059C2 3,00 4,00 18,688(b,c) 11,494 1,000 -19,080 56,457 5,00 7,077(b,c) 10,511 1,000 -27,461 41,615 6,00 11,201(b,c) 10,004 1,000 -21,672 44,074 7,00 8,050(b,c) 10,108 1,000 -25,163 41,264 4,00 3,00 -18,688(b,c) 11,494 1,000 -56,457 19,080 5,00 -11,611(b,c) 6,920 1,000 -34,349 11,127 6,00 -7,487(b,c) 7,003 1,000 -30,500 15,525 7,00 -10,638(b,c) 5,955 ,942 -30,206 8,929 5,00 3,00 -7,077(b,c) 10,511 1,000 -41,615 27,461
169
4,00 11,611(b,c) 6,920 1,000 -11,127 34,349 6,00 4,124(b,c) 4,947 1,000 -12,132 20,379 7,00 ,973(b,c) 4,212 1,000 -12,868 14,814 6,00 3,00 -11,201(b,c) 10,004 1,000 -44,074 21,672 4,00 7,487(b,c) 7,003 1,000 -15,525 30,500 5,00 -4,124(b,c) 4,947 1,000 -20,379 12,132 7,00 -3,151(b,c) 4,296 1,000 -17,267 10,965 7,00 3,00 -8,050(b,c) 10,108 1,000 -41,264 25,163 4,00 10,638(b,c) 5,955 ,942 -8,929 30,206 5,00 -,973(b,c) 4,212 1,000 -14,814 12,868 6,00 3,151(b,c) 4,296 1,000 -10,965 17,267C3 3,00 4,00 -,944(b,c) 6,121 1,000 -21,057 19,169 5,00 -,968(b,c) 5,597 1,000 -19,360 17,425 6,00 1,511(b,c) 5,327 1,000 -15,996 19,017 7,00 1,727(b,c) 5,383 1,000 -15,961 19,414 4,00 3,00 ,944(b,c) 6,121 1,000 -19,169 21,057 5,00 -,024(b,c) 3,685 1,000 -12,133 12,085 6,00 2,455(b,c) 3,729 1,000 -9,800 14,710 7,00 2,671(b,c) 3,171 1,000 -7,750 13,091 5,00 3,00 ,968(b,c) 5,597 1,000 -17,425 19,360 4,00 ,024(b,c) 3,685 1,000 -12,085 12,133 6,00 2,478(b,c) 2,634 1,000 -6,178 11,135 7,00 2,695(b,c) 2,243 1,000 -4,676 10,065 6,00 3,00 -1,511(b,c) 5,327 1,000 -19,017 15,996 4,00 -2,455(b,c) 3,729 1,000 -14,710 9,800 5,00 -2,478(b,c) 2,634 1,000 -11,135 6,178 7,00 ,216(b,c) 2,288 1,000 -7,301 7,733 7,00 3,00 -1,727(b,c) 5,383 1,000 -19,414 15,961 4,00 -2,671(b,c) 3,171 1,000 -13,091 7,750 5,00 -2,695(b,c) 2,243 1,000 -10,065 4,676 6,00 -,216(b,c) 2,288 1,000 -7,733 7,301C4 3,00 4,00 -12,179(b,c) 17,240 1,000 -68,831 44,472 5,00 -9,596(b,c) 15,766 1,000 -61,402 42,210 6,00 -1,662(b,c) 15,006 1,000 -50,972 47,647
170
7,00 -3,754(b,c) 15,161 1,000 -53,574 46,066 4,00 3,00 12,179(b,c) 17,240 1,000 -44,472 68,831 5,00 2,583(b,c) 10,379 1,000 -31,524 36,690 6,00 10,517(b,c) 10,505 1,000 -24,002 45,035 7,00 8,425(b,c) 8,932 1,000 -20,926 37,776 5,00 3,00 9,596(b,c) 15,766 1,000 -42,210 61,402 4,00 -2,583(b,c) 10,379 1,000 -36,690 31,524 6,00 7,934(b,c) 7,420 1,000 -16,449 32,317 7,00 5,842(b,c) 6,318 1,000 -14,919 26,603 6,00 3,00 1,662(b,c) 15,006 1,000 -47,647 50,972 4,00 -10,517(b,c) 10,505 1,000 -45,035 24,002 5,00 -7,934(b,c) 7,420 1,000 -32,317 16,449 7,00 -2,092(b,c) 6,443 1,000 -23,265 19,082 7,00 3,00 3,754(b,c) 15,161 1,000 -46,066 53,574 4,00 -8,425(b,c) 8,932 1,000 -37,776 20,926 5,00 -5,842(b,c) 6,318 1,000 -26,603 14,919 6,00 2,092(b,c) 6,443 1,000 -19,082 23,265
Based on estimated marginal means a Adjustment for multiple comparisons: Bonferroni. b An estimate of the modified population marginal mean (I). c An estimate of the modified population marginal mean (J).
171
Multivariate Tests
Value F Hypothesis df Error df Sig. Noncent.
Parameter Observed Power(a)
Pillai's trace ,754 ,870 16,000 60,000 ,604 13,926 ,511Wilks' lambda ,367 ,905 16,000 37,298 ,570 10,620 ,344Hotelling's trace 1,408 ,924 16,000 42,000 ,550 14,780 ,503Roy's largest root 1,152 4,320(b) 4,000 15,000 ,016 17,279 ,825
Each F tests the multivariate effect of TITLE. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means. a Computed using alpha = ,05 b The statistic is an upper bound on F that yields a lower bound on the significance level. Univariate Tests
Dependent Variable Sum of
Squares df Mean Square F Sig. Noncent.
Parameter Observed Power(a)
Contrast 91,724 4 22,931 ,777 ,557 3,107 ,194C1 Error 442,832 15 29,522 Contrast 243,629 4 60,907 1,238 ,337 4,952 ,295C2 Error 737,913 15 49,194 Contrast 29,981 4 7,495 ,537 ,711 2,149 ,144C3 Error 209,267 15 13,951 Contrast 237,521 4 59,380 ,536 ,711 2,146 ,144C4 Error 1660,246 15 110,683
The F tests the effect of TITLE. This test is based on the linearly independent pairwise comparisons among the estimated marginal means. a Computed using alpha = ,05
172
5. MARITALSTATUS * EDUCATION Dependent Variable MARITALSTATUS EDUCATION Mean Std. Error 95% Confidence Interval
Lower Bound
Upper Bound Lower Bound Upper Bound
C1 1,00 1,00 .(a,b) . . . 2,00 40,145(a,c
) 3,453 32,785 47,504
3,00 .(a,b) . . . 2,00 1,00 40,168(a,c
) 3,245 33,252 47,084
2,00 41,219(a,c) 1,471 38,084 44,354
3,00 35,929(a,c) 6,277 22,551 49,307
C2 1,00 1,00 .(a,b) . . . 2,00 46,256(a,c
) 4,457 36,756 55,756
3,00 .(a,b) . . . 2,00 1,00 44,891(a,c
) 4,189 35,963 53,818
2,00 44,410(a,c) 1,899 40,363 48,457
3,00 39,734(a,c) 8,102 22,465 57,004
C3 1,00 1,00 .(a,b) . . . 2,00 26,517(a,c
) 2,374 21,457 31,576
3,00 .(a,b) . . . 2,00 1,00 23,081(a,c
) 2,231 18,327 27,836
2,00 24,072(a,c) 1,011 21,917 26,227
3,00 21,737(a,c) 4,315 12,540 30,933
C4 1,00 1,00 .(a,b) . . . 2,00 64,860(a,c
) 6,686 50,609 79,110
3,00 .(a,b) . . .
173
2,00 1,00 57,970(a,c) 6,283 44,578 71,361
2,00 57,559(a,c) 2,848 51,489 63,629
3,00 53,405(a,c) 12,153 27,501 79,308
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean. 6. MARITALSTATUS * DEPARTMENT Dependent Variable MARITALSTATUS DEPARTMENT Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound
C1 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 40,145(a,c) 3,453 32,785 47,504 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 2,00 36,790(a,c) 6,450 23,042 50,537 4,00 38,069(a,c) 4,460 28,563 47,574 5,00 41,560(a,c) 1,940 37,425 45,695 6,00 40,132(a,c) 6,122 27,083 53,180 8,00 40,121(a,c) 2,808 34,136 46,106 10,00 41,244(a,c) 3,924 32,881 49,607C2 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 46,256(a,c) 4,457 36,756 55,756 6,00 .(a,b) . . .
174
8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 2,00 31,321(a,c) 8,326 13,574 49,067 4,00 47,665(a,c) 5,757 35,395 59,935 5,00 44,018(a,c) 2,504 38,680 49,356 6,00 43,555(a,c) 7,903 26,710 60,399 8,00 44,176(a,c) 3,625 36,449 51,902 10,00 48,205(a,c) 5,065 37,410 59,001C3 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 26,517(a,c) 2,374 21,457 31,576 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 2,00 25,296(a,c) 4,434 15,846 34,747 4,00 23,584(a,c) 3,066 17,050 30,119 5,00 23,433(a,c) 1,334 20,590 26,275 6,00 23,518(a,c) 4,208 14,548 32,488 8,00 24,213(a,c) 1,930 20,098 28,327 10,00 23,261(a,c) 2,697 17,512 29,010C4 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 64,860(a,c) 6,686 50,609 79,110 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 2,00 70,121(a,c) 12,489 43,503 96,740 4,00 56,854(a,c) 8,635 38,449 75,259 5,00 57,937(a,c) 3,757 49,930 65,944 6,00 52,122(a,c) 11,854 26,856 77,388 8,00 57,815(a,c) 5,437 46,226 69,404 10,00 53,445(a,c) 7,597 37,252 69,638
175
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean. 7. EDUCATION * DEPARTMENT Dependent Variable EDUCATION DEPARTMENT Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 40,293(a,c
) 3,120 33,644 46,943
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 39,793(a,c
) 7,081 24,701 54,885
2,00 2,00 36,790(a,c) 6,450 23,042 50,537
4,00 38,069(a,c) 4,460 28,563 47,574
5,00 41,722(a,c) 1,893 37,687 45,756
6,00 40,132(a,c) 6,122 27,083 53,180
8,00 42,217(a,c) 2,758 36,338 48,096
10,00 41,970(a,c) 4,479 32,423 51,517
3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 35,929(a,c
) 6,277 22,551 49,307
176
10,00 .(a,b) . . .C2 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 42,117(a,c
) 4,027 33,533 50,700
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 53,212(a,c
) 9,140 33,730 72,694
2,00 2,00 31,321(a,c) 8,326 13,574 49,067
4,00 47,665(a,c) 5,757 35,395 59,935
5,00 45,714(a,c) 2,443 40,506 50,922
6,00 43,555(a,c) 7,903 26,710 60,399
8,00 46,396(a,c) 3,560 38,808 53,985
10,00 45,702(a,c) 5,782 33,378 58,026
3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 39,734(a,c
) 8,102 22,465 57,004
10,00 .(a,b) . . .C3 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 22,354(a,c
) 2,145 17,783 26,925
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 25,264(a,c
) 4,867 14,889 35,639
2,00 2,00 25,296(a,c) 4,434 15,846 34,747
177
4,00 23,584(a,c) 3,066 17,050 30,119
5,00 25,000(a,c) 1,301 22,227 27,773
6,00 23,518(a,c) 4,208 14,548 32,488
8,00 25,451(a,c) 1,896 21,410 29,492
10,00 22,260(a,c) 3,079 15,697 28,823
3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 21,737(a,c
) 4,315 12,540 30,933
10,00 .(a,b) . . .C4 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 58,801(a,c
) 6,040 45,926 71,676
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 55,475(a,c
) 13,710 26,253 84,697
2,00 2,00 70,121(a,c) 12,489 43,503 96,740
4,00 56,854(a,c) 8,635 38,449 75,259
5,00 59,812(a,c) 3,665 52,000 67,624
6,00 52,122(a,c) 11,854 26,856 77,388
8,00 60,020(a,c) 5,340 48,638 71,403
10,00 52,431(a,c) 8,673 33,945 70,916
3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . .
178
5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 53,405(a,c
) 12,153 27,501 79,308
10,00 .(a,b) . . .a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean. 8. MARITALSTATUS * EDUCATION * DEPARTMENT Dependent Variable MARITALSTATUS EDUCATION DEPARTMENT Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 1,00 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 40,145(a,c
) 3,453 32,785 47,504
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . .
179
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 40,293(a,c
) 3,120 33,644 46,943
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 39,793(a,c
) 7,081 24,701 54,885
2,00 2,00 36,790(a,c) 6,450 23,042 50,537
4,00 38,069(a,c) 4,460 28,563 47,574
5,00 42,510(a,c) 2,434 37,322 47,699
6,00 40,132(a,c) 6,122 27,083 53,180
8,00 42,217(a,c) 2,758 36,338 48,096
10,00 41,970(a,c) 4,479 32,423 51,517
3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 35,929(a,c
) 6,277 22,551 49,307
10,00 .(a,b) . . .C2 1,00 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . .
180
2,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 46,256(a,c
) 4,457 36,756 55,756
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 42,117(a,c
) 4,027 33,533 50,700
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 53,212(a,c
) 9,140 33,730 72,694
2,00 2,00 31,321(a,c) 8,326 13,574 49,067
4,00 47,665(a,c) 5,757 35,395 59,935
5,00 45,444(a,c) 3,142 38,746 52,142
6,00 43,555(a,c) 7,903 26,710 60,399
8,00 46,396(a,c) 3,560 38,808 53,985
10,00 45,702(a,c) 5,782 33,378 58,026
3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . .
181
6,00 .(a,b) . . . 8,00 39,734(a,c
) 8,102 22,465 57,004
10,00 .(a,b) . . .C3 1,00 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 26,517(a,c
) 2,374 21,457 31,576
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 22,354(a,c
) 2,145 17,783 26,925
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 25,264(a,c
) 4,867 14,889 35,639
2,00 2,00 25,296(a,c) 4,434 15,846 34,747
4,00 23,584(a,c) 3,066 17,050 30,119
182
5,00 24,242(a,c) 1,673 20,675 27,809
6,00 23,518(a,c) 4,208 14,548 32,488
8,00 25,451(a,c) 1,896 21,410 29,492
10,00 22,260(a,c) 3,079 15,697 28,823
3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 21,737(a,c
) 4,315 12,540 30,933
10,00 .(a,b) . . .C4 1,00 1,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 64,860(a,c
) 6,686 50,609 79,110
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 .(a,b) . . . 2,00 1,00 2,00 .(a,b) . . .
183
4,00 .(a,b) . . . 5,00 58,801(a,c
) 6,040 45,926 71,676
6,00 .(a,b) . . . 8,00 .(a,b) . . . 10,00 55,475(a,c
) 13,710 26,253 84,697
2,00 2,00 70,121(a,c) 12,489 43,503 96,740
4,00 56,854(a,c) 8,635 38,449 75,259
5,00 57,288(a,c) 4,714 47,241 67,335
6,00 52,122(a,c) 11,854 26,856 77,388
8,00 60,020(a,c) 5,340 48,638 71,403
10,00 52,431(a,c) 8,673 33,945 70,916
3,00 2,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 8,00 53,405(a,c
) 12,153 27,501 79,308
10,00 .(a,b) . . .a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean.
184
9. MARITALSTATUS * TITLE
Dependent Variable MARITALSTATUS TITLE Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 1,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 45,585(a,c) 5,978 32,843 58,328 6,00 .(a,b) . . . 7,00 34,704(a,c) 3,062 28,176 41,231 2,00 3,00 46,680(a,c) 7,599 30,482 62,877 4,00 37,781(a,c) 4,436 28,326 47,237 5,00 43,326(a,c) 2,646 37,686 48,966 6,00 40,236(a,c) 2,784 34,302 46,169 7,00 40,024(a,c) 1,852 36,076 43,972C2 1,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 48,726(a,c) 7,717 32,277 65,175 6,00 .(a,b) . . . 7,00 43,786(a,c) 3,953 35,360 52,212 2,00 3,00 53,785(a,c) 9,810 32,876 74,695 4,00 35,097(a,c) 5,726 22,891 47,302 5,00 45,699(a,c) 3,416 38,418 52,979 6,00 42,584(a,c) 3,593 34,925 50,243 7,00 46,013(a,c) 2,391 40,917 51,110C3 1,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 28,880(a,c) 4,110 20,120 37,639 6,00 .(a,b) . . . 7,00 24,153(a,c) 2,105 19,666 28,641 2,00 3,00 24,831(a,c) 5,224 13,696 35,965 4,00 25,774(a,c) 3,050 19,275 32,274
185
5,00 24,258(a,c) 1,819 20,380 28,135 6,00 23,320(a,c) 1,914 19,241 27,399 7,00 22,954(a,c) 1,273 20,240 25,668C4 1,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 72,211(a,c) 11,576 47,538 96,884 6,00 .(a,b) . . . 7,00 57,508(a,c) 5,930 44,870 70,147 2,00 3,00 53,240(a,c) 14,715 21,877 84,603 4,00 65,420(a,c) 8,589 47,111 83,728 5,00 58,149(a,c) 5,124 47,229 69,070 6,00 54,903(a,c) 5,390 43,414 66,391 7,00 56,921(a,c) 3,586 49,277 64,565
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean.
10. EDUCATION * TITLE Dependent Variable EDUCATION TITLE Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 1,00 3,00 .(a,b) . . . 4,00 38,773(a,c
) 6,638 24,624 52,922
5,00 49,146(a,c) 5,142 38,185 60,107
6,00 .(a,b) . . . 7,00 36,377(a,c
) 4,387 27,025 45,728
2,00 3,00 46,680(a,c 7,599 30,482 62,877
186
) 4,00 36,790(a,c
) 6,450 23,042 50,537
5,00 41,545(a,c) 3,504 34,078 49,013
6,00 41,671(a,c) 3,097 35,071 48,271
7,00 40,353(a,c) 1,766 36,588 44,118
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 35,929(a,c
) 6,277 22,551 49,307
7,00 .(a,b) . . .C2 1,00 3,00 .(a,b) . . . 4,00 38,873(a,c
) 8,569 20,609 57,138
5,00 49,259(a,c) 6,638 35,110 63,408
6,00 .(a,b) . . . 7,00 45,715(a,c
) 5,664 33,643 57,786
2,00 3,00 53,785(a,c) 9,810 32,876 74,695
4,00 31,321(a,c) 8,326 13,574 49,067
5,00 45,432(a,c) 4,523 35,792 55,072
6,00 43,534(a,c) 3,997 35,014 52,054
7,00 45,742(a,c) 2,280 40,882 50,602
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 39,734(a,c
) 8,102 22,465 57,004
7,00 .(a,b) . . .
187
C3 1,00 3,00 .(a,b) . . . 4,00 26,253(a,c
) 4,563 16,526 35,979
5,00 24,928(a,c) 3,535 17,394 32,463
6,00 .(a,b) . . . 7,00 20,572(a,c
) 3,016 14,143 27,001
2,00 3,00 24,831(a,c) 5,224 13,696 35,965
4,00 25,296(a,c) 4,434 15,846 34,747
5,00 26,233(a,c) 2,408 21,100 31,367
6,00 23,848(a,c) 2,129 19,310 28,385
7,00 23,948(a,c) 1,214 21,359 26,536
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 21,737(a,c
) 4,315 12,540 30,933
7,00 .(a,b) . . .C4 1,00 3,00 .(a,b) . . . 4,00 60,718(a,c
) 12,853 33,321 88,114
5,00 57,071(a,c) 9,957 35,848 78,295
6,00 .(a,b) . . . 7,00 57,045(a,c
) 8,495 38,938 75,152
2,00 3,00 53,240(a,c) 14,715 21,877 84,603
4,00 70,121(a,c) 12,489 43,503 96,740
5,00 65,719(a,c) 6,784 51,260 80,179
6,00 55,402(a,c) 5,996 42,622 68,182
188
7,00 56,978(a,c) 3,420 49,687 64,268
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 53,405(a,c
) 12,153 27,501 79,308
7,00 .(a,b) . . .a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean.
11. MARITALSTATUS * EDUCATION * TITLE Dependent Variable MARITALSTATUS EDUCATION TITLE Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 1,00 1,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 45,585(a,c
) 5,978 32,843 58,328
6,00 .(a,b) . . . 7,00 34,704(a,c
) 3,062 28,176 41,231
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
189
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 1,00 3,00 .(a,b) . . . 4,00 38,773(a,c
) 6,638 24,624 52,922
5,00 49,146(a,c) 5,142 38,185 60,107
6,00 .(a,b) . . . 7,00 36,377(a,c
) 4,387 27,025 45,728
2,00 3,00 46,680(a,c) 7,599 30,482 62,877
4,00 36,790(a,c) 6,450 23,042 50,537
5,00 37,505(a,c) 2,860 31,409 43,601
6,00 41,671(a,c) 3,097 35,071 48,271
7,00 41,483(a,c) 2,005 37,209 45,757
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 35,929(a,c
) 6,277 22,551 49,307
7,00 .(a,b) . . .C2 1,00 1,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 48,726(a,c
) 7,717 32,277 65,175
6,00 .(a,b) . . .
190
7,00 43,786(a,c) 3,953 35,360 52,212
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 1,00 3,00 .(a,b) . . . 4,00 38,873(a,c
) 8,569 20,609 57,138
5,00 49,259(a,c) 6,638 35,110 63,408
6,00 .(a,b) . . . 7,00 45,715(a,c
) 5,664 33,643 57,786
2,00 3,00 53,785(a,c) 9,810 32,876 74,695
4,00 31,321(a,c) 8,326 13,574 49,067
5,00 42,138(a,c) 3,692 34,269 50,007
6,00 43,534(a,c) 3,997 35,014 52,054
7,00 46,133(a,c) 2,588 40,616 51,650
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 39,734(a,c
) 8,102 22,465 57,004
7,00 .(a,b) . . .C3 1,00 1,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 3,00 .(a,b) . . .
191
4,00 .(a,b) . . . 5,00 28,880(a,c
) 4,110 20,120 37,639
6,00 .(a,b) . . . 7,00 24,153(a,c
) 2,105 19,666 28,641
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 1,00 3,00 .(a,b) . . . 4,00 26,253(a,c
) 4,563 16,526 35,979
5,00 24,928(a,c) 3,535 17,394 32,463
6,00 .(a,b) . . . 7,00 20,572(a,c
) 3,016 14,143 27,001
2,00 3,00 24,831(a,c) 5,224 13,696 35,965
4,00 25,296(a,c) 4,434 15,846 34,747
5,00 23,587(a,c) 1,966 19,396 27,777
6,00 23,848(a,c) 2,129 19,310 28,385
7,00 23,906(a,c) 1,378 20,968 26,844
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 21,737(a,c
) 4,315 12,540 30,933
7,00 .(a,b) . . .C4 1,00 1,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
192
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 72,211(a,c
) 11,576 47,538 96,884
6,00 .(a,b) . . . 7,00 57,508(a,c
) 5,930 44,870 70,147
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 1,00 3,00 .(a,b) . . . 4,00 60,718(a,c
) 12,853 33,321 88,114
5,00 57,071(a,c) 9,957 35,848 78,295
6,00 .(a,b) . . . 7,00 57,045(a,c
) 8,495 38,938 75,152
2,00 3,00 53,240(a,c) 14,715 21,877 84,603
4,00 70,121(a,c) 12,489 43,503 96,740
5,00 59,227(a,c) 5,538 47,424 71,031
6,00 55,402(a,c) 5,996 42,622 68,182
7,00 56,871(a,c) 3,882 48,596 65,147
3,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 53,405(a,c 12,153 27,501 79,308
193
) 7,00 .(a,b) . . .
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean. 12. DEPARTMENT * TITLE Dependent Variable DEPARTMENT TITLE Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 2,00 3,00 .(a,b) . . . 4,00 36,790(a,c
) 6,450 23,042 50,537
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 38,069(a,c
) 4,460 28,563 47,574
5,00 3,00 46,680(a,c) 7,599 30,482 62,877
4,00 38,773(a,c) 6,638 24,624 52,922
5,00 44,079(a,c) 2,599 38,540 49,617
6,00 45,194(a,c) 6,222 31,933 58,455
7,00 36,109(a,c) 1,839 32,188 40,029
194
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 40,132(a,c
) 6,122 27,083 53,180
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 37,637(a,c
) 3,752 29,640 45,634
7,00 45,089(a,c) 4,328 35,865 54,313
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 40,474(a,c
) 5,757 28,202 52,745
7,00 41,629(a,c) 4,712 31,586 51,673
C2 2,00 3,00 .(a,b) . . . 4,00 31,321(a,c
) 8,326 13,574 49,067
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 47,665(a,c
) 5,757 35,395 59,935
5,00 3,00 53,785(a,c) 9,810 32,876 74,695
4,00 38,873(a,c) 8,569 20,609 57,138
195
5,00 46,708(a,c) 3,354 39,558 53,857
6,00 40,811(a,c) 8,031 23,693 57,929
7,00 42,348(a,c) 2,374 37,287 47,409
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 43,555(a,c
) 7,903 26,710 60,399
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 43,085(a,c
) 4,843 32,762 53,409
7,00 46,356(a,c) 5,586 34,449 58,263
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 43,356(a,c
) 7,432 27,515 59,196
7,00 50,630(a,c) 6,083 37,666 63,595
C3 2,00 3,00 .(a,b) . . . 4,00 25,296(a,c
) 4,434 15,846 34,747
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . .
196
7,00 23,584(a,c) 3,066 17,050 30,119
5,00 3,00 24,831(a,c) 5,224 13,696 35,965
4,00 26,253(a,c) 4,563 16,526 35,979
5,00 25,798(a,c) 1,786 21,991 29,606
6,00 24,910(a,c) 4,277 15,794 34,026
7,00 21,225(a,c) 1,264 18,529 23,920
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 23,518(a,c
) 4,208 14,548 32,488
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 23,676(a,c
) 2,579 18,178 29,173
7,00 25,287(a,c) 2,975 18,946 31,628
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 21,018(a,c
) 3,958 12,583 29,454
7,00 24,383(a,c) 3,239 17,479 31,287
C4 2,00 3,00 .(a,b) . . . 4,00 70,121(a,c
) 12,489 43,503 96,740
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .
197
4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 56,854(a,c
) 8,635 38,449 75,259
5,00 3,00 53,240(a,c) 14,715 21,877 84,603
4,00 60,718(a,c) 12,853 33,321 88,114
5,00 62,837(a,c) 5,031 52,112 73,561
6,00 58,392(a,c) 12,047 32,715 84,069
7,00 58,139(a,c) 3,562 50,548 65,730
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 52,122(a,c
) 11,854 26,856 77,388
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 54,649(a,c
) 7,265 39,164 70,134
7,00 64,147(a,c) 8,380 46,286 82,007
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 51,921(a,c
) 11,148 28,160 75,681
7,00 54,208(a,c) 9,124 34,761 73,654
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902.
198
b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean. 13. MARITALSTATUS * DEPARTMENT * TITLE Dependent Variable MARITALSTATUS DEPARTMENT TITLE Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 45,585(a,c
) 5,978 32,843 58,328
6,00 .(a,b) . . . 7,00 34,704(a,c
) 3,062 28,176 41,231
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . .
199
7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 2,00 3,00 .(a,b) . . . 4,00 36,790(a,c
) 6,450 23,042 50,537
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 38,069(a,c
) 4,460 28,563 47,574
5,00 3,00 46,680(a,c) 7,599 30,482 62,877
4,00 38,773(a,c) 6,638 24,624 52,922
5,00 43,326(a,c) 2,646 37,686 48,966
6,00 45,194(a,c) 6,222 31,933 58,455
7,00 36,811(a,c) 2,319 31,867 41,755
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
200
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 40,132(a,c
) 6,122 27,083 53,180
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 37,637(a,c
) 3,752 29,640 45,634
7,00 45,089(a,c) 4,328 35,865 54,313
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 40,474(a,c
) 5,757 28,202 52,745
7,00 41,629(a,c) 4,712 31,586 51,673
C2 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 48,726(a,c
) 7,717 32,277 65,175
6,00 .(a,b) . . . 7,00 43,786(a,c
) 3,953 35,360 52,212
201
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 2,00 3,00 .(a,b) . . . 4,00 31,321(a,c
) 8,326 13,574 49,067
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 47,665(a,c
) 5,757 35,395 59,935
5,00 3,00 53,785(a,c) 9,810 32,876 74,695
4,00 38,873(a,c) 8,569 20,609 57,138
5,00 45,699(a,c) 3,416 38,418 52,979
6,00 40,811(a,c) 8,031 23,693 57,929
202
7,00 41,629(a,c) 2,994 35,247 48,011
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 43,555(a,c
) 7,903 26,710 60,399
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 43,085(a,c
) 4,843 32,762 53,409
7,00 46,356(a,c) 5,586 34,449 58,263
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 43,356(a,c
) 7,432 27,515 59,196
7,00 50,630(a,c) 6,083 37,666 63,595
C3 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 28,880(a,c 4,110 20,120 37,639
203
) 6,00 .(a,b) . . . 7,00 24,153(a,c
) 2,105 19,666 28,641
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 2,00 3,00 .(a,b) . . . 4,00 25,296(a,c
) 4,434 15,846 34,747
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 23,584(a,c
) 3,066 17,050 30,119
5,00 3,00 24,831(a,c) 5,224 13,696 35,965
4,00 26,253(a,c 4,563 16,526 35,979
204
) 5,00 24,258(a,c
) 1,819 20,380 28,135
6,00 24,910(a,c) 4,277 15,794 34,026
7,00 19,760(a,c) 1,594 16,362 23,159
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 23,518(a,c
) 4,208 14,548 32,488
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 23,676(a,c
) 2,579 18,178 29,173
7,00 25,287(a,c) 2,975 18,946 31,628
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 21,018(a,c
) 3,958 12,583 29,454
7,00 24,383(a,c) 3,239 17,479 31,287
C4 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . .
205
7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 72,211(a,c
) 11,576 47,538 96,884
6,00 .(a,b) . . . 7,00 57,508(a,c
) 5,930 44,870 70,147
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 2,00 3,00 .(a,b) . . . 4,00 70,121(a,c
) 12,489 43,503 96,740
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . .
206
7,00 56,854(a,c) 8,635 38,449 75,259
5,00 3,00 53,240(a,c) 14,715 21,877 84,603
4,00 60,718(a,c) 12,853 33,321 88,114
5,00 58,149(a,c) 5,124 47,229 69,070
6,00 58,392(a,c) 12,047 32,715 84,069
7,00 58,454(a,c) 4,491 48,882 68,026
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 52,122(a,c
) 11,854 26,856 77,388
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 54,649(a,c
) 7,265 39,164 70,134
7,00 64,147(a,c) 8,380 46,286 82,007
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 51,921(a,c
) 11,148 28,160 75,681
7,00 54,208(a,c) 9,124 34,761 73,654
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean.
207
14. EDUCATION * DEPARTMENT * TITLE Dependent Variable EDUCATION DEPARTMENT TITLE Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 38,773(a,c
) 6,638 24,624 52,922
5,00 49,146(a,c) 5,142 38,185 60,107
6,00 .(a,b) . . . 7,00 32,961(a,c
) 4,364 23,660 42,261
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .
208
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 39,793(a,c
) 7,081 24,701 54,885
2,00 2,00 3,00 .(a,b) . . . 4,00 36,790(a,c
) 6,450 23,042 50,537
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 38,069(a,c
) 4,460 28,563 47,574
5,00 3,00 46,680(a,c) 7,599 30,482 62,877
4,00 .(a,b) . . . 5,00 41,545(a) 3,504 34,078 49,013 6,00 45,194(a,c
) 6,222 31,933 58,455
7,00 37,683(a) 1,807 33,832 41,533 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 40,132(a,c
) 6,122 27,083 53,180
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 39,345(a,c 4,396 29,975 48,715
209
) 7,00 45,089(a,c
) 4,328 35,865 54,313
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 40,474(a,c
) 5,757 28,202 52,745
7,00 43,465(a,c) 6,328 29,977 56,953
3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . .
210
6,00 35,929(a,c) 6,277 22,551 49,307
7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .C2 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 38,873(a,c
) 8,569 20,609 57,138
5,00 49,259(a,c) 6,638 35,110 63,408
6,00 .(a,b) . . . 7,00 38,218(a,c
) 5,633 26,212 50,224
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . .
211
6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 53,212(a,c
) 9,140 33,730 72,694
2,00 2,00 3,00 .(a,b) . . . 4,00 31,321(a,c
) 8,326 13,574 49,067
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 47,665(a,c
) 5,757 35,395 59,935
5,00 3,00 53,785(a,c) 9,810 32,876 74,695
4,00 .(a,b) . . . 5,00 45,432(a) 4,523 35,792 55,072 6,00 40,811(a,c
) 8,031 23,693 57,929
7,00 44,413(a) 2,332 39,442 49,383 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 43,555(a,c
) 7,903 26,710 60,399
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
212
5,00 .(a,b) . . . 6,00 46,436(a,c
) 5,675 34,341 58,531
7,00 46,356(a,c) 5,586 34,449 58,263
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 43,356(a,c
) 7,432 27,515 59,196
7,00 48,049(a,c) 8,169 30,637 65,460
3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
213
5,00 .(a,b) . . . 6,00 39,734(a,c
) 8,102 22,465 57,004
7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .C3 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 26,253(a,c
) 4,563 16,526 35,979
5,00 24,928(a,c) 3,535 17,394 32,463
6,00 .(a,b) . . . 7,00 15,880(a,c
) 3,000 9,487 22,274
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
214
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 25,264(a,c
) 4,867 14,889 35,639
2,00 2,00 3,00 .(a,b) . . . 4,00 25,296(a,c
) 4,434 15,846 34,747
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 23,584(a,c
) 3,066 17,050 30,119
5,00 3,00 24,831(a,c) 5,224 13,696 35,965
4,00 .(a,b) . . . 5,00 26,233(a) 2,408 21,100 31,367 6,00 24,910(a,c
) 4,277 15,794 34,026
7,00 23,897(a) 1,242 21,250 26,544 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 23,518(a,c
) 4,208 14,548 32,488
8,00 3,00 .(a,b) . . .
215
4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 25,615(a,c
) 3,022 19,174 32,056
7,00 25,287(a,c) 2,975 18,946 31,628
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 21,018(a,c
) 3,958 12,583 29,454
7,00 23,502(a,c) 4,350 14,230 32,774
3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . .
216
4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 21,737(a,c
) 4,315 12,540 30,933
7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .C4 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 60,718(a,c
) 12,853 33,321 88,114
5,00 57,071(a,c) 9,957 35,848 78,295
6,00 .(a,b) . . . 7,00 58,614(a,c
) 8,449 40,606 76,623
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . .
217
4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 55,475(a,c
) 13,710 26,253 84,697
2,00 2,00 3,00 .(a,b) . . . 4,00 70,121(a,c
) 12,489 43,503 96,740
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 56,854(a,c
) 8,635 38,449 75,259
5,00 3,00 53,240(a,c) 14,715 21,877 84,603
4,00 .(a,b) . . . 5,00 65,719(a) 6,784 51,260 80,179 6,00 58,392(a,c
) 12,047 32,715 84,069
7,00 57,901(a) 3,498 50,446 65,357 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 52,122(a,c
) 11,854 26,856 77,388
218
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 55,893(a,c
) 8,512 37,751 74,036
7,00 64,147(a,c) 8,380 46,286 82,007
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 51,921(a,c
) 11,148 28,160 75,681
7,00 52,940(a,c) 12,253 26,824 79,057
3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .
219
8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 53,405(a,c
) 12,153 27,501 79,308
7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable. c Based on modified population marginal mean. 15. MARITALSTATUS * EDUCATION * DEPARTMENT * TITLE Dependent Variable MARITALSTATUS EDUCATION DEPARTMENT TITLE Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound C1 1,00 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . .
220
4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 45,585(a) 5,978 32,843 58,328
221
6,00 .(a,b) . . . 7,00 34,704(a) 3,062 28,176 41,231 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .
222
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 38,773(a) 6,638 24,624 52,922 5,00 49,146(a) 5,142 38,185 60,107 6,00 .(a,b) . . . 7,00 32,961(a) 4,364 23,660 42,261 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
223
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 39,793(a) 7,081 24,701 54,885 2,00 2,00 3,00 .(a,b) . . . 4,00 36,790(a) 6,450 23,042 50,537 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 38,069(a) 4,460 28,563 47,574 5,00 3,00 46,680(a) 7,599 30,482 62,877 4,00 .(a,b) . . . 5,00 37,505(a) 2,860 31,409 43,601 6,00 45,194(a) 6,222 31,933 58,455 7,00 40,662(a) 1,847 36,726 44,598 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . .
224
7,00 40,132(a) 6,122 27,083 53,180 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 39,345(a) 4,396 29,975 48,715 7,00 45,089(a) 4,328 35,865 54,313 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 40,474(a) 5,757 28,202 52,745 7,00 43,465(a) 6,328 29,977 56,953 3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . .
225
4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 35,929(a) 6,277 22,551 49,307 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .C2 1,00 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . .
226
6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 48,726(a) 7,717 32,277 65,175 6,00 .(a,b) . . . 7,00 43,786(a) 3,953 35,360 52,212 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .
227
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
228
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 38,873(a) 8,569 20,609 57,138 5,00 49,259(a) 6,638 35,110 63,408 6,00 .(a,b) . . . 7,00 38,218(a) 5,633 26,212 50,224 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . .
229
7,00 53,212(a) 9,140 33,730 72,694 2,00 2,00 3,00 .(a,b) . . . 4,00 31,321(a) 8,326 13,574 49,067 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 47,665(a) 5,757 35,395 59,935 5,00 3,00 53,785(a) 9,810 32,876 74,695 4,00 .(a,b) . . . 5,00 42,138(a) 3,692 34,269 50,007 6,00 40,811(a) 8,031 23,693 57,929 7,00 45,040(a) 2,384 39,959 50,121 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 43,555(a) 7,903 26,710 60,399 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 46,436(a) 5,675 34,341 58,531 7,00 46,356(a) 5,586 34,449 58,263 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 43,356(a) 7,432 27,515 59,196 7,00 48,049(a) 8,169 30,637 65,460 3,00 2,00 3,00 .(a,b) . . .
230
4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 39,734(a) 8,102 22,465 57,004 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .C3 1,00 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . .
231
6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .
232
4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 28,880(a) 4,110 20,120 37,639 6,00 .(a,b) . . . 7,00 24,153(a) 2,105 19,666 28,641 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
233
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . .
234
7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 26,253(a) 4,563 16,526 35,979 5,00 24,928(a) 3,535 17,394 32,463 6,00 .(a,b) . . . 7,00 15,880(a) 3,000 9,487 22,274 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 25,264(a) 4,867 14,889 35,639 2,00 2,00 3,00 .(a,b) . . . 4,00 25,296(a) 4,434 15,846 34,747 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 23,584(a) 3,066 17,050 30,119 5,00 3,00 24,831(a) 5,224 13,696 35,965
235
4,00 .(a,b) . . . 5,00 23,587(a) 1,966 19,396 27,777 6,00 24,910(a) 4,277 15,794 34,026 7,00 23,640(a) 1,269 20,934 26,346 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 23,518(a) 4,208 14,548 32,488 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 25,615(a) 3,022 19,174 32,056 7,00 25,287(a) 2,975 18,946 31,628 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 21,018(a) 3,958 12,583 29,454 7,00 23,502(a) 4,350 14,230 32,774 3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . .
236
6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 21,737(a) 4,315 12,540 30,933 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .C4 1,00 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .
237
6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 72,211(a) 11,576 47,538 96,884 6,00 .(a,b) . . . 7,00 57,508(a) 5,930 44,870 70,147 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . .
238
5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . .
239
7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 2,00 1,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 60,718(a) 12,853 33,321 88,114 5,00 57,071(a) 9,957 35,848 78,295 6,00 .(a,b) . . . 7,00 58,614(a) 8,449 40,606 76,623 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . .
240
4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 55,475(a) 13,710 26,253 84,697 2,00 2,00 3,00 .(a,b) . . . 4,00 70,121(a) 12,489 43,503 96,740 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 56,854(a) 8,635 38,449 75,259 5,00 3,00 53,240(a) 14,715 21,877 84,603 4,00 .(a,b) . . . 5,00 59,227(a) 5,538 47,424 71,031 6,00 58,392(a) 12,047 32,715 84,069 7,00 58,294(a) 3,575 50,673 65,915 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 52,122(a) 11,854 26,856 77,388 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . .
241
6,00 55,893(a) 8,512 37,751 74,036 7,00 64,147(a) 8,380 46,286 82,007 10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 51,921(a) 11,148 28,160 75,681 7,00 52,940(a) 12,253 26,824 79,057 3,00 2,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 4,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 5,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 6,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . . 8,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 53,405(a) 12,153 27,501 79,308 7,00 .(a,b) . . .
242
10,00 3,00 .(a,b) . . . 4,00 .(a,b) . . . 5,00 .(a,b) . . . 6,00 .(a,b) . . . 7,00 .(a,b) . . .
a Covariates appearing in the model are evaluated at the following values: C5 = 39,5854, C6 = 22,2927, C7 = 8,5610, C8 = 13,4878, AGE = 33,4146, TOTALYEAROFEMPLOYEED = 11,8293, TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY = 8,8171, MONTHLYSALARY = 1154,3902. b This level combination of factors is not observed, thus the corresponding population marginal mean is not estimable.
243
7.3. ANOVA
7.3.1. ANOVA for CC and Marital Status
Warnings Post hoc tests are not performed for CC because there are fewer than three groups.
Descriptives CC
N Mean Std. Deviation Std. Error 95% Confidence Interval for
Mean Minimum Maximu
m
Lower Bound
Upper Bound Lower Bound
Upper Bound Lower Bound Upper Bound
Lower Bound
Upper Bound
1,00 11 170,0909 35,30001 10,64335 146,3760 193,8058 84,00 201,002,00 78 168,1538 22,60334 2,55932 163,0576 173,2501 80,00 208,00Total 89 168,3933 24,27055 2,57267 163,2806 173,5059 80,00 208,00
Test of Homogeneity of Variances CC
Levene Statistic df1 df2 Sig.
1,801 1 87 ,183 ANOVA CC
Sum of
Squares df Mean Square F Sig. Between Groups 36,173 1 36,173 ,061 ,806 Within Groups 51801,063 87 595,415 Total 51837,236 88
244
7.3.2. ANOVA for CC and Education
Descriptives CC
N Mean Std. Deviation Std. Error 95% Confidence Interval for
Mean Minimum Maxim
um
Lower Bound
Upper Bound Lower Bound
Upper Bound Lower Bound
Upper Bound
Lower Bound
Upper Bound
1,00 14 171,7857 30,09262 8,04259 154,4108 189,1607 80,00 198,00
2,00 71 168,9577 23,10315 2,74184 163,4893 174,4262 84,00 208,00
3,00 6 157,8333 21,94007 8,95700 134,8086 180,8580 127,00 194,00
Total 91 168,6593 24,12662 2,52916 163,6347 173,6840 80,00 208,00
Test of Homogeneity of Variances
CC
Levene Statistic df1 df2 Sig.
,185 2 88 ,832
ANOVA CC
Sum of
Squares df Mean Square F Sig. Between Groups 846,376 2 423,188 ,723 ,488 Within Groups 51542,064 88 585,705
Total 52388,440 90
Homogeneous Subsets
CC Scheffe
EDUCATION N Subset for alpha = .05
1 1 3,00 6 157,83332,00 71 168,95771,00 14 171,7857Sig. ,376
Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 11,896. b The group sizes are unequal. The harmonic mean of the
group sizes is used. Type I error levels are not guaranteed.
245
7.3.3. ANOVA for CC and Department
Warnings Post hoc tests are not performed for CC because at least one group has fewer than two cases.
Descriptives CC
N Mean Std. Deviation Std. Error 95% Confidence Interval for
Mean Minimum Maximu
m
Lower Bound
Upper Bound Lower Bound
Upper Bound Lower Bound Upper Bound
Lower Bound
Upper Bound
1,00 1 170,0000 . . . . 170,00 170,002,00 2 187,0000 11,31371 8,00000 85,3504 288,6496 179,00 195,004,00 2 166,5000 31,81981 22,50000 -119,3896 452,3896 144,00 189,005,00 61 166,7049 25,82011 3,30593 160,0921 173,3178 80,00 201,006,00 1 151,0000 . . . . 151,00 151,008,00 11 166,2727 23,87924 7,19986 150,2304 182,3150 127,00 197,0010,00 11 178,6364 14,28477 4,30702 169,0397 188,2330 160,00 208,00Total 89 168,4382 24,13643 2,55846 163,3538 173,5226 80,00 208,00
Test of Homogeneity of Variances CC
Levene Statistic df1 df2 Sig. 1,214(a) 4 82 ,311a Groups with only one case are ignored in computing the test of homogeneity of variance for CC.
ANOVA CC
Sum of
Squares df Mean Square F Sig. Between Groups 2381,994 6 396,999 ,666 ,677 Within Groups 48883,916 82 596,145 Total 51265,910 88
246
7.3.4. ANOVA for CC and Title
Descriptives CC
N Mean Std. Deviation Std. Error 95% Confidence Interval for
Mean Minimum Maximum
Lower Bound
Upper Bound Lower Bound
Upper Bound Lower Bound
Upper Bound
Lower Bound
Upper Bound
3,00 2 180,0000 21,21320 15,00000 -10,5931 370,5931 165,00 195,004,00 3 186,6667 10,01665 5,78312 161,7839 211,5494 179,00 198,005,00 21 173,9524 25,35050 5,53193 162,4130 185,4918 109,00 199,006,00 9 155,2222 16,82095 5,60698 142,2925 168,1520 127,00 178,007,00 51 166,5098 25,12319 3,51795 159,4438 173,5758 80,00 208,00Total 86 168,1628 24,49099 2,64093 162,9119 173,4137 80,00 208,00
Test of Homogeneity of Variances CC
Levene Statistic df1 df2 Sig.
,782 4 81 ,540
ANOVA CC
Sum of
Squares df Mean Square F Sig. Between Groups 3657,801 4 914,450 1,565 ,192 Within Groups 47325,920 81 584,271 Total 50983,721 85
247
Post Hoc Tests Multiple Comparisons Dependent Variable: CC Scheffe
(I) TITLE (J) TITLE
Mean Difference
(I-J) Std. Error Sig. 95% Confidence Interval
Lower Bound Upper Bound Lower Bound Upper Bound Lower Bound 3,00 4,00 -6,66667 22,06563 ,999 -76,2269 62,8935 5,00 6,04762 17,88736 ,998 -50,3409 62,4361 6,00 24,77778 18,89588 ,787 -34,7900 84,3456 7,00 13,49020 17,42388 ,963 -41,4372 68,41764,00 3,00 6,66667 22,06563 ,999 -62,8935 76,2269 5,00 12,71429 14,91909 ,947 -34,3170 59,7456 6,00 31,44444 16,11446 ,439 -19,3551 82,2440 7,00 20,15686 14,36012 ,741 -25,1123 65,42605,00 3,00 -6,04762 17,88736 ,998 -62,4361 50,3409 4,00 -12,71429 14,91909 ,947 -59,7456 34,3170 6,00 18,73016 9,63023 ,442 -11,6284 49,0887 7,00 7,44258 6,26727 ,842 -12,3145 27,19976,00 3,00 -24,77778 18,89588 ,787 -84,3456 34,7900 4,00 -31,44444 16,11446 ,439 -82,2440 19,3551 5,00 -18,73016 9,63023 ,442 -49,0887 11,6284 7,00 -11,28758 8,73929 ,796 -38,8375 16,26247,00 3,00 -13,49020 17,42388 ,963 -68,4176 41,4372 4,00 -20,15686 14,36012 ,741 -65,4260 25,1123 5,00 -7,44258 6,26727 ,842 -27,1997 12,3145 6,00 11,28758 8,73929 ,796 -16,2624 38,8375
Homogeneous Subsets CC Scheffe TITLE N Subset for alpha = .05 1 1 6,00 9 155,22227,00 51 166,50985,00 21 173,95243,00 2 180,00004,00 3 186,6667Sig. ,389
Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 4,942. b The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed.
248
7.4. MAC
7.4.1. MAC for CCC and Gender
Crosstabs Case Processing Summary
Cases
Valid Missing Total N Percent N Percent N Percent GENDER * CCC 120 96,0% 5 4,0% 125 100,0%
GENDER * CCC Crosstabulation Count
CCC Total
,00 1,00 ,00 2,00 45 74 119GENDER 5,00 0 1 1
Total 45 75 120 Chi-Square Tests
Value df Asymp. Sig.
(2-sided) Exact Sig. (2-sided)
Exact Sig. (1-sided)
Pearson Chi-Square ,605(b) 1 ,437 Continuity Correction(a) ,000 1 1,000
Likelihood Ratio ,945 1 ,331 Fisher's Exact Test 1,000 ,625 Linear-by-Linear Association ,600 1 ,439
N of Valid Cases 120 a Computed only for a 2x2 table b 2 cells (50,0%) have expected count less than 5. The minimum expected count is ,38. Symmetric Measures
Value Approx. Sig. Phi ,071 ,437Nominal by
Nominal Cramer's V ,071 ,437N of Valid Cases 120
a Not assuming the null hypothesis. b Using the asymptotic standard error assuming the null hypothesis.
249
7.4.2. MAC for CCC and Marital Status
Case Processing Summary
Cases
Valid Missing Total N Percent N Percent N Percent MARITALSTATUS * CCC 120 96,0% 5 4,0% 125 100,0%
MARITALSTATUS * CCC Crosstabulation Count
CCC Total
,00 1,00 ,00 1,00 4 9 132,00 40 66 106
MARITALSTATUS
5,00 0 1 1Total 44 76 120
Chi-Square Tests
Value df Asymp. Sig.
(2-sided) Pearson Chi-Square ,826(a) 2 ,662Likelihood Ratio 1,165 2 ,558Linear-by-Linear Association ,022 1 ,881
N of Valid Cases 120
a 3 cells (50,0%) have expected count less than 5. The minimum expected count is ,37. Symmetric Measures
Value Approx. Sig. Phi ,083 ,662Nominal by
Nominal Cramer's V ,083 ,662N of Valid Cases 120
a Not assuming the null hypothesis.b Using the asymptotic standard error assuming the null hypothesis.
250
7.4.3. MAC for CCC and Education
Case Processing Summary
Cases
Valid Missing Total N Percent N Percent N Percent EDUCATION * CCC 123 98,4% 2 1,6% 125 100,0%
EDUCATION * CCC Crosstabulation Count
CCC Total
,00 1,00 ,00 1,00 4 21 252,00 36 55 913,00 5 1 6
EDUCATION
5,00 0 1 1Total 45 78 123
Chi-Square Tests
Value df Asymp. Sig.
(2-sided) Pearson Chi-Square 11,142(a) 3 ,011Likelihood Ratio 12,005 3 ,007Linear-by-Linear Association 5,296 1 ,021
N of Valid Cases 123
a 4 cells (50,0%) have expected count less than 5. The minimum expected count is ,37. Symmetric Measures
Value Approx. Sig. Phi ,301 ,011Nominal by
Nominal Cramer's V ,301 ,011N of Valid Cases 123
a Not assuming the null hypothesis. b Using the asymptotic standard error assuming the null hypothesis.
251
7.4.4. MAC for CCC and Department
Case Processing Summary
Cases
Valid Missing Total N Percent N Percent N Percent DEPARTMENT * CCC 120 96,0% 5 4,0% 125 100,0%
DEPARTMENT * CCC Crosstabulation Count
CCC Total
,00 1,00 ,00 1,00 1 0 12,00 0 2 24,00 1 1 25,00 31 54 856,00 1 0 18,00 6 6 12
DEPARTMENT
10,00 4 13 17Total 44 76 120
Chi-Square Tests
Value df Asymp. Sig.
(2-sided) Pearson Chi-Square 6,949(a) 6 ,326Likelihood Ratio 8,226 6 ,222Linear-by-Linear Association ,365 1 ,546
N of Valid Cases 120
a 9 cells (64,3%) have expected count less than 5. The minimum expected count is ,37. Symmetric Measures
Value Approx. Sig. Phi ,241 ,326Nominal by
Nominal Cramer's V ,241 ,326N of Valid Cases 120
a Not assuming the null hypothesis. b Using the asymptotic standard error assuming the null hypothesis.
252
7.4.5. MAC for CCC and Title
Case Processing Summary
Cases
Valid Missing Total N Percent N Percent N Percent TITLE * CCC 114 91,2% 11 8,8% 125 100,0%
TITLE * CCC Crosstabulation Count
CCC Total
,00 1,00 ,00 3,00 1 1 24,00 0 3 35,00 6 24 306,00 8 4 12
TITLE
7,00 29 38 67Total 44 70 114
Chi-Square Tests
Value df Asymp. Sig.
(2-sided) Pearson Chi-Square 10,984(a) 4 ,027Likelihood Ratio 12,313 4 ,015Linear-by-Linear Association 3,688 1 ,055
N of Valid Cases 114
a 5 cells (50,0%) have expected count less than 5. The minimum expected count is ,77. Symmetric Measures
Value Approx. Sig. Phi ,310 ,027Nominal by
Nominal Cramer's V ,310 ,027N of Valid Cases 114
a Not assuming the null hypothesis. b Using the asymptotic standard error assuming the null hypothesis.
253
7.4.6. MAC for CC and Age
Correlations CC AGE
Correlation Coefficient 1,000 ,002Sig. (2-tailed) . ,985
CC
N 93 60Correlation Coefficient ,002 1,000Sig. (2-tailed) ,985 .
Kendall's tau_b
AGE
N 60 78Correlation Coefficient 1,000 ,001Sig. (2-tailed) . ,995
CC
N 93 60Correlation Coefficient ,001 1,000Sig. (2-tailed) ,995 .
Spearman's rho
AGE
N 60 78
7.4.7. MAC for CC and Total Years of Emplooyed
Correlations
CC
TOTALYEAROFEMPL
OYEED Correlation Coefficient 1,000 -,001 Sig. (2-tailed) . ,994
CC
N 93 87 Correlation Coefficient -,001 1,000 Sig. (2-tailed) ,994 .
Kendall's tau_b
TOTALYEAROFEMPLOYEED
N 87 114 Correlation Coefficient 1,000 -,007 Sig. (2-tailed) . ,945
CC
N 93 87 Correlation Coefficient -,007 1,000 Sig. (2-tailed) ,945 .
Spearman's rho
TOTALYEAROFEMPLOYEED
N 87 114
254
7.4.8. MAC for CC and Total Years of Emplooyement in Existing Company
Correlations
CC
TOTALYEARSEMPLYEEMENTINEXISTING
COMPANY Correlation Coefficient 1,000 ,038 Sig. (2-tailed) . ,608
CC
N 93 89 Correlation Coefficient ,038 1,000 Sig. (2-tailed) ,608 .
Kendall's tau_b
TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY
N 89 118 Correlation Coefficient 1,000 ,058 Sig. (2-tailed) . ,590
CC
N 93 89 Correlation Coefficient ,058 1,000 Sig. (2-tailed) ,590 .
Spearman's rho
TOTALYEARSEMPLYEEMENTINEXISTINGCOMPANY
N 89 118
7.4.9. MAC for CC and Monthly Salary
Correlations
CC MONTHLYSALARY
Correlation Coefficient 1,000 ,003 Sig. (2-tailed) . ,971
CC
N 93 78 Correlation Coefficient ,003 1,000 Sig. (2-tailed) ,971 .
Kendall's tau_b
MONTHLYSALARY
N 78 104 Correlation Coefficient 1,000 ,006 Sig. (2-tailed) . ,955
CC
N 93 78 Correlation Coefficient ,006 1,000 Sig. (2-tailed) ,955 .
Spearman's rho
MONTHLYSALARY
N 78 104
255
7.5. Multiple Regression
Descriptive Statistics Mean Std. Deviation N CC 166,9529 24,90119 85C5 40,3059 9,78826 85C6 23,3882 8,63836 85C7 8,5294 1,93088 85C8 13,7412 3,95255 85
Correlations
CC C5 C6 C7 C8
CC 1,000 ,362 ,220 ,538 ,410 C5 ,362 1,000 ,791 ,428 ,836 C6 ,220 ,791 1,000 ,290 ,792 C7 ,538 ,428 ,290 1,000 ,497
Pearson Correlation
C8 ,410 ,836 ,792 ,497 1,000 CC . ,000 ,022 ,000 ,000 C5 ,000 . ,000 ,000 ,000 C6 ,022 ,000 . ,004 ,000 C7 ,000 ,000 ,004 . ,000
Sig. (1-tailed)
C8 ,000 ,000 ,000 ,000 . CC 85 85 85 85 85 C5 85 85 85 85 85 C6 85 85 85 85 85 C7 85 85 85 85 85
N
C8 85 85 85 85 85 Variables Entered/Removed(b)
Model Variables Entered
Variables Removed Method
1 C8, C7, C6, C5(a) . Enter
a All requested variables entered. b Dependent Variable: CC
256
Model Summary(b)
Model R R Square
Adjusted R
Square Std. Error of the Estimate Change Statistics Durbin-Watson
R Square Change F Change df1 df2
Sig. F Change
R Square Change F Change df1 df2 Sig. F Change
1 ,575(a) ,331 ,298 20,87069 ,331 9,894 4 80 ,000 2,049a Predictors: (Constant), C8, C7, C6, C5 b Dependent Variable: CC ANOVA(b)
Model Sum of
Squares df Mean Square F Sig. Regression 17238,940 4 4309,735 9,894 ,000(a) Residual 34846,872 80 435,586
1
Total 52085,812 84 a Predictors: (Constant), C8, C7, C6, C5 b Dependent Variable: CC
257
Coefficients(a)
Unstandardized Coefficients
Standardized Coefficients t Sig. Correlations Collinearity Statistics
Model B Std. Error Beta Zero-order Partial Part Tolerance VIF B Std. Error (Constant) 99,458 11,902 8,357 ,000 C5 ,351 ,462 ,138 ,760 ,449 ,362 ,085 ,070 ,254 3,941 C6 -,621 ,480 -,216 -1,293 ,200 ,220 -,143 -,118 ,301 3,320 C7 5,306 1,395 ,411 3,805 ,000 ,538 ,391 ,348 ,715 1,399
1
C8 1,645 1,213 ,261 1,356 ,179 ,410 ,150 ,124 ,225 4,436 a Dependent Variable: CC Collinearity Diagnostics(a)
Model Dimension Eigenvalue Condition
Index Variance Proportions
(Constant) C5 C6 C7 C8 (Constant
) C5 1 1 4,867 1,000 ,00 ,00 ,00 ,00 ,00 2 ,081 7,749 ,12 ,00 ,19 ,10 ,01 3 ,026 13,626 ,67 ,00 ,04 ,50 ,07 4 ,016 17,404 ,00 ,18 ,76 ,35 ,31 5 ,010 22,271 ,21 ,82 ,00 ,04 ,62
a Dependent Variable: CC
258
Casewise Diagnostics(b)
Case Number Std. Residual CC Predicted
Value Residual Status 1 ,270 180,00 174,3733 5,62671 2 -1,691 144,00 179,2840 -35,28398 3 . . 179,8949 . M(a) 4 ,614 184,00 171,1905 12,80950 5 . 193,00 . . M(a) 6 . . 184,7022 . M(a) 7 . . . . M(a) 8 1,850 201,00 162,3895 38,61052 9 . . 181,4339 . M(a) 10 . . 161,0276 . M(a) 11 . . 166,5329 . M(a) 12 -,471 150,00 159,8206 -9,82060 13 ,580 189,00 176,9054 12,09462 14 ,367 183,00 175,3369 7,66313 15 -1,476 144,00 174,7949 -30,79488 16 -,193 157,00 161,0364 -4,03643 17 -2,203 84,00 129,9877 -45,98769 18 . . 173,1659 . M(a) 19 -2,508 80,00 132,3353 -52,33531 20 -,077 181,00 182,6069 -1,60688 21 . . . . M(a) 22 . . . . M(a) 23 ,904 200,00 181,1373 18,86270 24 ,670 193,00 179,0124 13,98755 25 ,694 195,00 180,5161 14,48391 26 -,760 157,00 172,8608 -15,86084 27 . . . . M(a) 28 -,951 149,00 168,8484 -19,84843 29 ,450 190,00 180,6016 9,39836 30 -1,006 134,00 155,0010 -21,00101 31 -1,073 156,00 178,3912 -22,39124 32 -,334 169,00 175,9803 -6,98026 33 -1,545 130,00 162,2435 -32,24346 34 ,456 184,00 174,4839 9,51608 35 . 186,00 . . M(a) 36 -,082 176,00 177,7155 -1,71547 37 . 195,00 . . M(a) 38 1,002 152,00 131,0807 20,91934 39 -,553 168,00 179,5437 -11,54371 40 . . 175,2406 . M(a)
259
41 ,492 190,00 179,7326 10,26741 42 1,072 197,00 174,6182 22,38177 43 -,496 142,00 152,3516 -10,35159 44 ,254 179,00 173,7016 5,29844 45 1,069 192,00 169,6880 22,31199 46 ,716 179,00 164,0613 14,93868 47 -2,564 119,00 172,5152 -53,51521 48 1,089 193,00 170,2669 22,73312 49 ,120 184,00 181,4973 2,50272 50 -,278 159,00 164,8109 -5,81094 51 . . 166,7499 . M(a) 52 -,536 170,00 181,1934 -11,19337 53 -,545 142,00 153,3668 -11,36683 54 ,743 192,00 176,4981 15,50186 55 . 168,00 . . M(a) 56 . . . . M(a) 57 -,327 173,00 179,8181 -6,81814 58 -,661 144,00 157,7961 -13,79608 59 -,098 148,00 150,0372 -2,03725 60 ,484 178,00 167,9011 10,09887 61 . 198,00 . . M(a) 62 . . . . M(a) 63 ,508 189,00 178,3971 10,60286 64 1,857 191,00 152,2354 38,76459 65 1,823 208,00 169,9595 38,04047 66 . . . . M(a) 67 ,141 179,00 176,0673 2,93269 68 . . 157,3092 . M(a) 69 ,061 183,00 181,7334 1,26658 70 . . . . M(a) 71 . . 136,6162 . M(a) 72 . 150,00 . . M(a) 73 . . . . M(a) 74 ,102 175,00 172,8708 2,12921 75 . . 172,4901 . M(a) 76 -,406 170,00 178,4739 -8,47389 77 -,119 157,00 159,4823 -2,48227 78 -,331 165,00 171,8984 -6,89840 79 -,194 161,00 165,0544 -4,05439 80 -,378 172,00 179,8949 -7,89488 81 ,974 143,00 122,6748 20,32518 82 -,921 152,00 171,2244 -19,22439 83 ,520 194,00 183,1425 10,85746 84 ,544 181,00 169,6375 11,36251
260
85 -,526 156,00 166,9837 -10,98366 86 1,783 164,00 126,7850 37,21498 87 . 170,00 . . M(a) 88 1,583 186,00 152,9585 33,04155 89 . . 172,9992 . M(a) 90 ,482 184,00 173,9483 10,05174 91 -1,635 109,00 143,1305 -34,13048 92 . . . . M(a) 93 1,558 199,00 166,4801 32,51986 94 -1,286 160,00 186,8359 -26,83590 95 . . . . M(a) 96 -,233 160,00 164,8611 -4,86111 97 1,176 178,00 153,4491 24,55087 98 -1,976 136,00 177,2359 -41,23588 99 . . 139,2620 . M(a) 100 . . 114,6544 . M(a) 101 . . 176,7431 . M(a) 102 . 168,00 . . M(a) 103 ,317 163,00 156,3806 6,61936 104 ,542 188,00 176,6885 11,31148 105 . . 181,1373 . M(a) 106 ,489 189,00 178,7912 10,20882 107 ,830 192,00 174,6854 17,31461 108 . . 164,9939 . M(a) 109 -,407 151,00 159,4930 -8,49300 110 ,596 191,00 178,5506 12,44936 111 -,857 140,00 157,8887 -17,88868 112 -,422 139,00 147,8169 -8,81690 113 1,243 194,00 168,0678 25,93217 114 -,697 165,00 179,5437 -14,54371 115 ,081 176,00 174,3120 1,68796 116 -,993 127,00 147,7203 -20,72026 117 . . 159,7336 . M(a) 118 -,645 159,00 172,4595 -13,45950 119 . . . . M(a) 120 -,212 163,00 167,4330 -4,43299 121 1,254 178,00 151,8197 26,18028 122 -,301 165,00 171,2728 -6,27280 123 ,607 148,00 135,3292 12,67079 124 . . 164,5453 . M(a) 125 . . 168,4261 . M(a)
a Missing Case b Dependent Variable: CC
261
Residuals Statistics(a) Minimum Maximum Mean Std. Deviation N Predicted Value 122,6748 186,8359 166,9529 14,32569 85 Std. Predicted Value -3,091 1,388 ,000 1,000 85 Standard Error of Predicted Value 2,486 10,135 4,845 1,475 85
Adjusted Predicted Value 115,2999 188,9189 166,8498 14,73353 85 Residual -53,51521 38,76459 ,00000 20,36771 85 Std. Residual -2,564 1,857 ,000 ,976 85 Stud. Residual -2,626 2,040 ,002 1,012 85 Deleted Residual -57,40438 48,70013 ,10315 21,94279 85 Stud. Deleted Residual -2,730 2,082 ,000 1,026 85 Mahal. Distance ,204 18,822 3,953 3,197 85 Cook's Distance ,000 ,257 ,016 ,035 85 Centered Leverage Value ,002 ,224 ,047 ,038 85
a Dependent Variable: CC
262
Regression Standardized Predicted Value
210-1-2-3-4
Regression Studentized Residual 3
2
1
0
-1
-2
-3
Scatterplot
Dependent Variable: CC
263
8. CONCLUSION
The result of this study confirms that the variables considered in the theoretical
framework are important individually.
As a result of reliability analysis the variable list of the proposed model modified.
In initial model there were 64 dependent and 30 indenependent variables in the model.
After consistency analysis 20 dependent variables and 5 independent variables are
exluded from the model. Specifically quality awareness, agreeable, influencing, friendly,
evaluate of alternative solution, evaluate of difficulties, problem solving, balance between
work&private life problems, risk taker, creative, conventional, innovative approach, action
oriented, result oriented, adaptable, situantional, adaptable to change are deleted from
dependent variable list. In addition to this economic crisis, stability, globalization,
techonological development and market competition is deleted from independent variable
list. In the revised model there are 44 dependent variables and 25 independent variables.
After consistency analysis total score of each items related with main components
gathered. As a result of total score of management competency item, specialties
competency item, entreperanuership competency item and personal competency item
core concept item gathered. The total score of individual compotencies gathered into 4
main component as company core competency, human resource management,
environmental management and work competencies. In the MANOVA analysis general
linear model designed including the core concept item, 4 individual competencies as
covariate and demographic variables as covariate and factors. In the MANOVA analysis
the interaction between groups and correlation between variables gathered.
After MANOVA analysis Multiple Regression Analysis performed. The result of
regression analysis showed that there is insignificant relationship between dependent and
independent variables. The total explanation of the core concept by independent variables
is 25%. Due to the very low adjusted R square value the residuals statistics are examined.
The scores for each respondent are checked by the statics.
264
9. LIMITATIONS
During the research study the main difficulties were that there was no
uniform concept and definition about core concept. Therefore searching the various
concepts and gathering different literature sources took several monlong period of
time to achieve a model.
In addition to this field survey for the reaserch study has some obstacles
as well. Some unhomogenous data in the source causes the limitation in the study.
265
10. APPENDICES
10.1. Description of The Competency List
No Competency Definition
1 Motivate others Understands how to get involved others into work to be able to
achieve successful business outcome by keeping their
contribution continuously. Motivation is the set of reason to
perform a specific action or certain behavior. Motivation is
present in every life function.
2 Taking Responsibility Focuses efforts and energy on successfully attaining
organizational goals and objectives. This includes making
difficult decisions and persisting even when confronted by
obstacles or adversity and may involve questioning status quo
assumptions. Assuming accountability for decisions, actions
and results follow through on issues to completion, point out
problems and ask questions others may have overlooked or
been reluctant to acknowledge.
3 Decision Making Independently takes action and responsibility for solving
problems. Makes decisions designed to achieve desired
outcomes. Challenges the status quo by taking calculated
actions in complex, ambiguous, contentious or hazardous
situations to force an issue or set a direction.
4 Flexibility The ability to adapt to and work effectively with a variety of
situations, individuals or groups to understand and appreciate
different and opposing perspectives on an issue, to adapt
one’s own approach as the requirements of a situation change
and to change or easily accept changes as the requirements
of a situation change, and to change or easily accept changes
in one’s own organization or job requirements. Accepts
changes as a healthy and normal part of growth. Receptive to
new information and recognizes the validity of various
266
viewpoints, sees situations objectively. Responds positively to
changes in direction and priorities, responsibilities and
assignments. Adjusts to multiple demands, priorities,
responsibilities or assignments. Adjusts to multiple demands,
priorities, ambiguity and change positively. Works effectively
within a variety of situations, individuals or groups.
5 Delegation Delegation is the assignment of authority and responsibility to
another person to carry out specific activities. The person who
delegated the work remains accountable for the outcome of the
delegate work. It allows a subordinate to make decisions; it is a
shift of decision-making authority from one organizational level
to a lower one. Delegation, if properly done, is not abdication.
The opposite of effective delegation is micromanagement,
where a manager provides too much input, direction, and
review of delegated work.
6 Independent A preference for proactive and anticipatory action based upon
taking calculated risks and making difficult decisions despite
ambiguity or adversity. Accepting responsibility for decisions,
actions, risks and results and being willing to ask difficult
questions and point out problems or issues others may have
overlooked or been reluctant to acknowledge.
7 Long Term View An individual who creates a clear and inspiring broad picture.
One, who moves, acts and communicates at the appropriate
time. Thinks openly about new possibilities. Keeps a long-term
and broad perspective. Displays a spontaneous and wide-
ranging imagination. Stays focused on the mission and goals
while considering future impact and opportunities.
8 Focus on Details Awareness of the each of particular for a job or a subject.
Carefully consider the details and evaluates.
9 Evaluative To examine and judge carefully. Evaluation is systematic
determination of merit, worth, and significance of something or
267
someone using criteria against a set of standards.
10 Committed - Precise Having determinate limitations. Realize the works on time and
required quality.
11 Time Management Recognizes or establishes the relative importance of multiple
issues, tasks and opportunities to maximize the productivity of
the organization. Plans the work, task and other
responsibilities effectively
30 Planning Define and create the activities steps by step for a process or
work carefully
31 Organizing Arranging people, source and things related with a subject in
order to achieve a specific target
12 Quality Orientating -
Awareness
Achieve excellent work result by attending to details,
standards and procurers. Demonstrates an appropriate level
of precision to complete projects successfully and to execute
job responsibilities in a timely manner.
13 Agreeable Having a manner tries to understand others opinions and
achieve common decisions.
14 Influencing Negotiates with convinces or influences others to take a
course of action which might not otherwise be taken in order to
achieve a specific result. Uses appropriate interpersonal styles
and communication methods to gain acceptance of an idea,
plan, activity or product. Bring conflicts and disagreements into
the open, when appropriate and attempts resolution
collaboratively through building consensus.
15 Strategic Conscious behavior arising among a small number of
competitors or players, in a situation where all are aware of
their conflicting interests and interdependence of their
decisions.
268
16 Friendly Being sympathetic and behaving warmly to the others
17 Conceptual - Theoretician Likes to study on the concept of an idea, formulation and theory
of a subject. Tries to understand the background of a subject
and make evaluation on the basis of theoretical data
18 Following Technical
Development
Follows all latest development on the expertise area. Makes
interpretation, apply and suggest the new technologies.
19 Evaluate by numerical data Uses reason and logic to identify and solve problems.
Understands cause and effect relationships, recognizes
similarities and differences in situations and applies numerical
data to help make effective decisions or to come up with new
ways to accomplish a task.
20 Open to development Likes to learn new things and improve the knowledge
continuously. Open to implement new ideas into work.
21 Self confidence Includes confidence in one’s own ability expressed in
increasingly challenging circumstances, confidence in one’s
own decisions or opinions and ability to handle failures
constructively. Believes in own capabilities and convictions.
Projects a positive self-image in the workplace. Addresses
challenges or other issues clearly and appropriately.
22 Evaluate of alternative
solutions
Ability to think in broader aspect and seek for the new ways to
find the most appropriate solutions to solve a problem and
make a plan including all possible alternatives
23 Evaluate of difficulties Defines and cares all obstacles with a realistic point of view at
the stage of planning
24 Problem Solving Finding potential problem and ability to analyze cause effects
of the problems and taking corrective action for the complex
situations
269
25 Verbal communication Express and presents thoughts and ideas clearly, succinctly
and in an understandable manner individually and in a group.
Adjusts language, delivery or terminology to meet the needs of
the audience. This competency includes any type of verbal
communication, such as giving presentations, providing
training, giving testimony, speaking in person or by telephone.
26 Speaking Thoughtfully Cares others opinions and feelings when emphasizing own
thoughts and acts strategic and empathetic
27 Outspoken Directly express thoughts when arguing a subject. Feels
confident about own thoughts and ideas and doesn’t hesitate
to express to others
28 Examine writing mistakes Cares writing rules and mistakes when reading or editing a
text and being more careful the meaning, appearance and
grammar of a text
29 Effective Writing Express and presents information and ideas in writing that is
clear, succinct and understandable. Adjusts the language,
writing style and terminology used to meet the need and level
of understanding of the reader. Utilize knowledge of the
structure and content of the language, including meaning and
spelling of words, rules of compositions, and grammar.
32 Presenting Communicate ideas to others effectively by using effective
presentation skills. Explain the concepts, methods and
contents clearly in a way to emphasis the strengths of that
subject
33 Competitive Ability to compete with others to achieve the targets. Likes to
achieve success by overwhelming the difficult situations and
never give up when facing any obstacles
34 Decisive Capable of making a swift and choice about an ambiguous
situation. Making fast decisions and reaches conclusions
270
quickly.
35
Customer Orientation Creates an atmosphere in which timely and high quality
information flows smoothly between self and customer.
Encourages open, honest and constructive expression of
ideas and opinions. Demonstrates active listening skills. And
uses appropriate body language when meeting with customer.
Seeks to understand others’ point of view. Analyzes the
customer needs and adjusts to the perspective of the
customer when appropriate.
36 Balance between work and
social life
Ability to balance workload and effectively manage social and
work life together. Try to eliminate the pressure effect of work
life on family life and opposite.
37
Creative Generates fresh, original or unconventional perspectives and
original approaches. Reexamines established ways of doing
things.
38 Conventional Generally accept the standards and public norms. Hesitate to
try new ways for a situation and feel comfortable to use valid
methods and thoughts
39 Risk Taker Ability to take the risk to achieve the goal and complete a task
on time. Being encourage to invest in a
40 Innovative Invent and thinks new ways and methods with an
unconventional point of view. Suggest add on values to the
existing services and products
41 Action oriented Ability to being proactive, acting on time, always keeping busy
and never giving up to achieve the goals. Prefer to the stage
as taking action instead of thinking and planning deeply
42 Goal and Result Orientated Achieve goals and brings projects to completion. Investigates,
calculates and proceeds through a project or task to bring
about a conclusion. Persists and stays focused when faced
271
with a series of challenging or uncertain situations.
Demonstrates a concern for working well or for competing
against a standard of excellence.
43 Team Worker Ability to contribute in the group effectively. Satisfying the roles
and functions as a team member and work in harmonious way
in the group. Produce successful performance output by
managing the conflicts and obstacle occurring during the team
work.
44 Loyalty Ability and willingness to align behavior with the needs and
goals of the organization and provide a visible role model for
others. Holds self accountable for organizational activities,
services, successes and failures. An employee with
commitment demonstrates an understanding of the link
between his/her own job responsibilities and overall
organizational goals and needs and subsequently performs
the job with broader goals in mind.
45 Optimistic Ability to sustain positive point of view when facing with
difficulties and obstacles. Believes in the things goes well and
manages the things lean way
46 Ambitious Eagerly desire to achieve goals and gather success in the life,
work and every situation. Focus always on target and results
47 Confident Having strong assurance and belief of self. Believe own
sources, knowledge and skills.
48 Visionary Having specific and clear targets and dreams about future,
belonging to this vision strongly
49 Strategic Acting Acting tactically and behaving according to a plan and
mission. Try every possibilities in a strategic way to achieve
own target
272
50 Supportive Ability to encourage others to execute their responsibilities.
Coaching others to aware of their potential and relapse these
potential for appropriate use.
51 Responsive Quick to react to people or events and to show emotions such
as pleasure and affection. Interact openly and honestly.
Encourages others to express viewpoint. Listens and respects
different view points. Addresses misunderstandings directly
with those involved. Maintain confidences. Demonstrate an
awareness of nonverbal as well as verbal communication.
Elicit from others by showing honesty, reliability and integrity.
52 Trust to Others Believe in others commitment, their promises and loyalty.
Behave transparent and trustworthy to the others.
53 Behavioral Analysis Try to understand the reasons of others behavior, carefully
analyze the people and situations. Observe the responses and
situational behaviors.
54 Adaptable Ability to have common understanding with others. Agree on
decisions by flexible and harmonious attitudes Having a
manner as win-win.
55 Situational Behaving Ability to act depending on the situation and people’s
competency level. Adjust own behaviors according to the
others to understand their expectation
56 Adapt to change Being flexible when it is necessary to change an attitude,
behavior and thought. Accepting the change as an
improvement and adjusting own abilities according to new
situation
57 Follow common decision Ability to accept common decisions even having different
opinions and thought. Align and act based on shared targets
58 Vigorous - Like various Likes to have various hobbies, tasks, responsibilities and
roles. Always interest in new actions to learn new things and
273
activities attend different events
59 Calm Ability to stay positive manner, peaceful and quite under the
high pressure and in the stressful environment. Don’t loose the
control and being always emotionally controlled.
60 Patient Ability to wait the people decisions and output of the
performance until it’s finalized. Being less stressful, stay calm
and having high moral under the conflict situation, difficulties
and obstacles.
61 Open to Critics Ability to accept the others feedback about own self and open
to get the opinions and comments on own behaviors and
performance.
62 Emotionally Stable Ability to control the emotions and feelings as behaving
professional under the different conditions.
63 Anxious Emotionally uncontrolled and being quickly panic at
unexpected and undesired situation
64 Energy Level Having full of energy to do activities. Not becoming tried or
loosing motivation in short period of time
65 Leadership in the Company Effective management in the organization. Defining, planning
and adjusting the company strategies and employees targets
based on the vision and mission with the realistic point of view.
Sustaining loyalty and commitment in the company under the
difficult situation
66 Company Flexibility Executing according to existing market conditions and taking
necessary corrective action and adjusting targets, plans,
products and services
67 Company Responsibility
Being responsible for each of the outcome in the organization.
Taking the responsibility of the unsuccessful and successful
274
actions.
68 Company Vision&Mission
Developing a clear, realistic and traceable mission and vision.
Create common purpose and culture in the organization
69 Company Profitability
Controlling very kind of cost at each of the stages of the
business process and caring appropriate profitability to sustain
business continuity
70 Product&Service
Produce high quality product and service
71 Company Innovation
Create innovative product and service
72 Customer Relationship
Management
Achieve high customer satisfaction, understand and define the
customer request correctly and provide high quality service
73 Quality Orientation Meet and exceed the quality expectation of the customer and
provide high quality product and services at any conditions
with a standard level of quality
74 Equality Provide equal right and benefits to the each of the employees
in the company based on their contribution, positions and roles
75 Transparency Establish a open standards, procedures and rule into the
company that everybody understand the policies in the
organization
76 HR Strategy
Align HR strategies with company core activities, targets and
strategies.
77 Crisis Management
Create a crisis management strategy and announce it in the
company
78 Employee Support Program
Provide employee assistance program in case to support
employees under the high stressful and conflict situations.
79 Recruitment
Establish clear and easy to excite standards for search and
selection process and tie it with business plans and
275
requirements.
80 Performance Management
Assess the employees performance with the objective
techniques and implement a trustful and measurable
performance management process
81 Individual Development Analyze and plan the training needs of employees and define
the gap between today competencies and future targets
82 Career Planning Plan a career map for the positions and share it with the
employees. Create a talent pool for each positions succession
planning
83 Firing Explain the reason for the downsizing and give adequate
support to manage the transition period for the employees
84 Economic Crisis
Downturn in the economy and its negative effects to business
world and social life
85 Stability Sustaining economic, socio politic and business stability
86 Globalization
Globalization is the process by which the people of the world
are unified into a single society and function together.
Globalization is often used to refer to economic globalization
87 Follow –up Technological development
Follow up new technology and implement new applications
into work
88 Social Life Balance Having a social and network, good rand supportive
relationship within
89 Family Life Balance Having good relationship with family members and supporting
each other
90 Market Competition Compete with other solution providers and provide added
value to the customers with key advantages in the product and
services
276
91 Work Content
The general tasks, functions, and responsibilities of a work
and position. Includes the specifications, the qualifications and
the roles needed by the person
92 Business Process
Business method collection of related, structured activities or
tasks that produce a specific service or product (serve a
particular goal) for a particular customer or customers. It often
can be visualized with a flowchart as a sequence of activities.
93 Work Load
The amount of work assigned to or expected from an
employee in a specified time period. It can be consisted of
several tasks, projects and roles as assigned to a person
94 Work Responsibility Area
Including the control function of projects, tasks, decisions,
teams and deliverables needs to completed the tasks and
works successfully
277
10.2. Questionnaire
10.2.1. Questionnaire in Turkish
Bölüm I – Kişisel Yetkinlikler
Mevcut Durum: Lütfen aşağıdaki aşağıda yer alan durumlarla ilgili normal
koşullarda sergilendiğiniz kişisel davranışlarınızı ve yetkinliklerinizi düşünerek
değerlendirme yapın
Kriz Durumu: Lütfen aşağıda yer alan durumlarla ilgili kriz dönemlerinde
sergileyeceğiniz kişisel davranışlarınızı ve yetkinliklerinizi düşünerek değerlendirme yapın
278
BÖLÜM I
279
No Etiket No Durumlar
Katılmıy
orum
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
1 Motive Etme Ortak hedeflere ulaşmak için başkalarını motive ederim
KRİZ DURUMU
NORMAL DURUM
2 Sorumluluk Alma
Bir işi sonuçlandırana kadar üzerinde durur ve takip ederim KRİZ
DURUMU
NORMAL DURUM
3 Karar Alma Bir konu hakkında hızlı değerlendirme yapar ve en doğru kararı veririm KRİZ
DURUMU
NORMAL DURUM
4 Esnek Davranma
Karar verdiğim bir konuda gerekiyorsa fikrimi değiştiririm KRİZ
DURUMU
NORMAL DURUM
5 Delegasyon
İşleri gerektiğinde başkalarına devrederim KRİZ
DURUMU
NORMAL DURUM
6 Bağımsız Hareket Etme
İşle ilgili konularda çoğunlukla kendi başıma hareket ederim
KRİZ DURUMU
NORMAL DURUM
7 Uzun vadeli bakış açısı benimseme
Uzun vadeli bir bakış açısı benimserim
KRİZ DURUMU
NORMAL DURUM
8 Detaylara odaklanma
Bir işle ilgili detayları gözden kaçırmam
KRİZ DURUMU
NORMAL DURUM
9 Eleştirel bakış açısı
Bir işi, olumlu ve olumsuz bütün koşulları göz önüne alarak planlarım KRİZ
DURUMU
280
No Etiket No Durumlar
Katılmıy
orum
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
10 Teslim tarihlerine uyma
İşlerin söz verilen zamanda bitmesini sağlarım
KRİZ DURUMU
NORMAL DURUM
11 Zaman Planlaması
Acil işler nedeniyle önemli işlerimi aksatmam
KRİZ DURUMU
NORMAL DURUM
12 Organize Etme
İşleri en ince ayrıntısına kadar organize ederim
KRİZ DURUMU
NORMAL DURUM
13 Etkili Planlama
Planladığım işler çoğu zaman eksiksiz olur
KRİZ DURUMU
NORMAL DURUM
14 Kalite kurallarına uyma
İşleri yaparken bütün kalite standartlarına uyarım
KRİZ DURUMU
NORMAL DURUM
15 Uzlaşmacı Çoğunluğun kararlarına uyarım
KRİZ DURUMU
NORMAL DURUM
16
Kendi görüşlerini kabul ettirme
Fikirlerimin başkaları tarafından benimsemesini çok önemserim KRİZ
DURUMU
NORMAL DURUM
17 Anlayışlı ve Arkadaşça Davranma
Sempatik ve arkadaşça davranışların işleri kolaylaştırdığına inanırım KRİZ
DURUMU
NORMAL DURUM
18 Teorik bilgilere ilgi duyma
İşimle ilgili teorik bilgilere ilgi duyarım
KRİZ DURUMU
281
No Etiket No Durumlar
Katılmıy
orum
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
19 Teknik gelişmeleri takip etme
Uzmanlık alanımla ilgili teknik gelişmeleri yakından takip ederim KRİZ
DURUMU
NORMAL DURUM
20
Sayısal verilerle değerlendirme
Sayısal verilere göre değerlendirme yaparım
KRİZ DURUMU
NORMAL DURUM
21 Gelişmeye açık olma
Öğrendiğim yeni yöntem ve teknikleri iş yerinde uygularım
KRİZ DURUMU
NORMAL DURUM
22 Bilgisine Güvenen
Yaptığım bütün işlerde başarı elde ederim
KRİZ DURUMU
NORMAL DURUM
23
Çözümleri değerlendirme
Bir sorunu gidermek için aklıma gelen ilk çözüm yerine alternatif çözümleri değerlendiririm KRİZ
DURUMU
NORMAL DURUM
24
Potansiyel zorlukları değerlendirme
Bir işi yapmadan önce olası zorlukları belirlerim
KRİZ DURUMU
NORMAL DURUM
25
Sayısal verilerle problem çözme
İşle ilgili bir problemin nedenini detaylı olarak araştırırım
KRİZ DURUMU
NORMAL DURUM
26 Etkili konuşma
Bir grup içinde konuşma yapmam gerektiğinde fikirlerimi etkili bir şekilde açıklarım KRİZ
DURUMU
NORMAL DURUM
27 Nazikçe ifade etme
Fikirlerimi belirtirken başkalarını incitmemeye dikkat ederim KRİZ
DURUMU
282
No Etiket No Durumlar
Katılmıy
orum
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
28 Düşündüğünü açıkça ifade eden
Herhangi bir olay hakkındaki görüşümü açıkça belirtmekten hoşlanırım KRİZ
DURUMU
NORMAL DURUM
29 Etikili Sunum
Bir konuyu sunarken kendimi rahat hissederim
KRİZ DURUMU
NORMAL DURUM
30 Yazım hatalarına dikkat etme
Okuduğum bir metinde yazım hatalarına dikkat ederim
KRİZ DURUMU
NORMAL DURUM
31 Yazılı olarak etkili ifade etme
Yazılı iletişimde açık ve anlaşılması kolay ifadeler kullanırım KRİZ
DURUMU
NORMAL DURUM
32 Rekabet etme
Başarıya ulaşmak için gerektiğinde rekabet ederim
KRİZ DURUMU
NORMAL DURUM
33 Kararlı davranma
Çoğunlukla başladığım işten en son ben vazgeçerim
KRİZ DURUMU
NORMAL DURUM
34 Müşteri Odaklılık
Müşteri ihtiyaçlarına yönelik satış aktivitelerinden hoşlanırım KRİZ
DURUMU
NORMAL DURUM
35
Ticari sorunlarla kişisel sorunları dengeleme
Profesyonelce davranmaya dikkat eder özel hayattaki sorunları iş hayatına yansıtmam KRİZ
DURUMU
NORMAL DURUM
36 Risk Alma İşimi yaparken gerektiğinde risk alırım
KRİZ DURUMU
283
No Etiket No Durumlar
Katılmıy
orum
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
37 Yaratıcı Olma
Normalin dışında değişik fikirler öne sürerim
KRİZ DURUMU
NORMAL DURUM
38 Geleneksel davranma
Bir işi yaparken daha önce denenmiş yöntemleri tercih ederim KRİZ
DURUMU
NORMAL DURUM
39 Yenilikçi bakış açısı
Yenilikçi yaklaşımların işe farklılık ve değer kattığını düşünürüm KRİZ
DURUMU
NORMAL DURUM
40 Harekete Geçme
Başkalarından yardım beklemektense bir işe kendi başıma başlamayı tercih ederim KRİZ
DURUMU
NORMAL DURUM
41 Hedef odaklı davranan
Zorlayıcı hedeflerden hoşlanırım
KRİZ DURUMU
NORMAL DURUM
42 Bağlılık İşyerinde işler beklediğim gibi gitmediğinde umudumu yitirmem KRİZ
DURUMU
NORMAL DURUM
43 Vizyoner Bir işe başlarken o günün gereklerinden çok geleceği düşünerek hareket ederim KRİZ
DURUMU
NORMAL DURUM
44 Stratejik
Kendi düşüncelerimi belirtmeden önce diğer insanların ne düşündüğünü bilmek isterim KRİZ
DURUMU
NORMAL DURUM
45 Takım çalışması
Ortak bir hedefe ulaşmak için başkalarıyla çalışmayı severim
KRİZ DURUMU
284
No Etiket No Durumlar
Katılmıy
orum
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
46 Destekleyen İhtiyacı olduğunda başkalarının başarısı için onları desteklerim KRİZ
DURUMU
NORMAL DURUM
47 Teşvik eden Ortak çalışmalara katılımı artırmak için diğerlerini teşvik ederim KRİZ
DURUMU
NORMAL DURUM
48 Duyarlı Başkalarının endişelerini anlar ve onlara karşı duyarlı davranırım KRİZ
DURUMU
NORMAL DURUM
49 Başkalarına güvenen
Biri işi kontrol etmeme gerek kalmadan başkaları tarafından başarıyla yapılacağına inanırım KRİZ
DURUMU
NORMAL DURUM
50 Davranışları sorgulayan
Başkalarının davranışlarının nedenlerini merak eder ve sorgularım KRİZ
DURUMU
NORMAL DURUM
51 Uyumlu Çalıştığım insanlarla arkadaşça ve sıcak ilişkiler sürdürmeyi tercih ederim KRİZ
DURUMU
NORMAL DURUM
52 Durumsal davranan
Davranışlarımı çoğunlukla başkalarına göre ayarlarım
KRİZ DURUMU
NORMAL DURUM
53 Değişime uyum sağlayan
İşimle ilgili herhangi bir konuda değişiklik yapmam
KRİZ DURUMU
NORMAL DURUM
54 Çeşitlilikten hoşlanan
İş yerinde yeni sorumluluklar almaktan ve yeni insanlarla çalışmaktan çok hoşlanırım KRİZ
DURUMU
285
No Etiket No Durumlar
Katılmıy
orum
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
55 Sakin
Önemli bir iş üzerinde çalışırken başkalarının işimi yarıda kesmesine nadiren sinirlenirim KRİZ
DURUMU
NORMAL DURUM
56 Sabırlı Kısa sürede sonuç alamadığım bir konuda ilgimi uzun süre canlı tutabilirim KRİZ
DURUMU
NORMAL DURUM
57 Eleştirilere karşı açık
Yaptığım işle ilgili eleştirilmek moralimi bozmaz
KRİZ DURUMU
NORMAL DURUM
58 Duygularını kontrol eden
Beklemediğim bir durum karşısında nadiren tepki gösteririm KRİZ
DURUMU
NORMAL DURUM
59 Endişeli Önemli bir toplantı öncesinde çoğunlukla sakin olurum
KRİZ DURUMU
NORMAL DURUM
60 Enerji düzeyi
Yaptığım işte başarısız olsam dahi moralimi bozmam
KRİZ DURUMU
NORMAL DURUM
61 İyimserliğini koruyan
Çoğu kimseyi kaygılandıran durumlarda bile genellikle her şeyin iyi gideceğine inanırım KRİZ
DURUMU
NORMAL DURUM
62 Başarma azmi olan
Karşıma çıkacak güçlükler yaptığım işten vazgeçmeme neden olmaz KRİZ
DURUMU
NORMAL DURUM
63 Kendine Güvenen
Her türlü koşulda kendime güvenim çok yüksektir
KRİZ DURUMU
286
No Etiket No Durumlar
Katılmıy
orum
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
64 Hırslı Kariyerimde başarılı olmayı hedeflerim
KRİZ DURUMU
287
BÖLÜM II
288
No Etiket No Durumlar
Katılmıy
oru
m
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
1 Liderlik Yönetimin alacağı kararlara güvenirim ve onları sonuna kadar takip ederim KRİZ
DURUMU
NORMAL DURUM
2 Esneklik
Yönetim kurum hedeflerini, stratejilerini ve organizasyon yapısını günün şartlarına uygun olacak şekilde değiştirir KRİZ
DURUMU
NORMAL DURUM
3 Sorumluluk
Yönetim elde edilen başarılı veya başarısız her türlü sonucu üstlenir KRİZ
DURUMU
NORMAL DURUM
4 Vizyon ve Misyon
Kurum olarak amacımız ve hedeflerimiz açıktır
KRİZ DURUMU
NORMAL DURUM
5 Karlılık Kurumumuzda maliyetler her zaman kontrol edilerek karlılık ön planda tutulur KRİZ
DURUMU
NORMAL DURUM
6 Ürün ve Hizmet
Sunulan ürün ve hizmeti herekese tavsiye ederim
KRİZ DURUMU
NORMAL DURUM
7 Yenilkçilik Kurum olarak yeni teknolojiler geliştirmede öncüyüz
KRİZ DURUMU
NORMAL DURUM
8 Müşteri ilişkileri Yönetimi
Müşteri memnuniyeti her zaman en yüksek seviyede tutulur KRİZ
DURUMU
NORMAL DURUM
9 Kalite Odaklılık
Ürün ve hizmet kalitesinin artırılmasına her zaman önem verilir KRİZ
DURUMU
289
No Etiket No Durumlar
Katılmıy
orum
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
10 Eşitlik Çalışanlar eşit haklara sahiptir KRİZ
DURUMU
NORMAL DURUM
11 Şeffaflık Kurum içinde bütün prosedürler açık ve şeffaftır
KRİZ DURUMU
NORMAL DURUM
12 İK Stratejisi İnsan kaynakları uygulamaları kurum hedef ve statejileriyle uyumludur KRİZ
DURUMU
NORMAL DURUM
13 Çalışan Destek Programı
Çalışma ortamında stres, çatışma ve yaşadığımız diğer problemlerle ilgili danışabileceğimiz bir birim vardır
KRİZ DURUMU
NORMAL DURUM
14 İşe Alım İşe alımlar iş ihtiyaçlarına göre objektif ve adil olarak yapılır
KRİZ DURUMU
NORMAL DURUM
15 İşten Çıkartma
İşten çıkarmalarda çalışanlara önceden haber verilir
KRİZ DURUMU
NORMAL DURUM
16 Performans Değerlendirme
Performansım objektif, şeffaf ve düzenli olarak değerlendirilir KRİZ
DURUMU
NORMAL DURUM
17 Bireysel Gelişim
İşimle ilgili gerekli eğitimleri alırım
KRİZ DURUMU
NORMAL DURUM
18 Kariyer Planlama
Kariyer hedeflerim açık ve objektif olarak planlanır
KRİZ DURUMU
290
No Etiket No Durumlar
Katılmıy
oru
m
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
19 Kriz Yönetimi
Kriz durumlarında yapılacak uygulamalar ve alınacak tedbirleri bilirim KRİZ
DURUMU
NORMAL DURUM
20 Ekonomik Kriz
Ekonomik belirsizliklerin olumsuz etkilerini azaltmak için en etkin ve uygun tedbirler alınır KRİZ
DURUMU
NORMAL DURUM
21 İstikrar İşlerin gidişatı nadiren değişir KRİZ
DURUMU
NORMAL DURUM
22 Küreselleşme
Küreselleşme işlerin daha kolay ve hızlı yapılmasını sağlar KRİZ
DURUMU
NORMAL DURUM
23 Teknolojik Gelişmeler
Yeni teknolojiler takip edilir ve uygulanır
KRİZ DURUMU
NORMAL DURUM
24 Sosyal Hayat Dengesi
Sosyal çevrem oldukça hareketlidir
KRİZ DURUMU
NORMAL DURUM
25 Aile İlişkileri Dengesi
Aile ilişkilerim olumlu ve destekleyicidir
KRİZ DURUMU
NORMAL DURUM
26 Rekabet Çalıştığım sektörde rekabet çok yüksektir
KRİZ DURUMU
NORMAL DURUM
27 İşin İçeriği İşim açık ve net bir şekilde tanımlanmıştır
KRİZ DURUMU
291
No Etiket No Durumlar
Katılmıy
oru
m
Çok
Az
Katılı
yoru
m
Az
Katılı
yoru
m
Old
ukça
K
atılı
yoru
m
Çok
K
atılı
yoru
m
Kes
inlik
le
Katılı
yoru
m
NORMAL DURUM
28 İş Süreçleri İş akışları işin hızlı ve rahat bir şekilde yapılmasını sağlar
KRİZ DURUMU
NORMAL DURUM
29 İş Yükü İş yükü adil olarak dağıtılmıştır KRİZ
DURUMU
NORMAL DURUM
30 İşin Sorumluluk Alanı
Yaptığım işin sorumluluk alanı çok kapsamlıdır
KRİZ DURUMU
292
BÖLÜM III
293
No Sorular
1 Yaşınız
2 Cinsiyet Kadın Erkek
3 Medeni Durumunuz Bekar Evli
İlk Öğretim Üniversite Doktora 4 Öğrenim Dururmunuz
Lise Yüksek Lisans
5 Mesleğiniz
6 Toplam Çalışma Yılınız
7 Çalıştığınız Kurum Özel Sektör Kamu
Genel Müdürlük Operasyon
İnsan Kaynakları Lojistik
Muhasebe Teknik Hizmetler
Satış ve Pazarlama Servis
8 Bölümünüz
Üretim Diğer
Müdür
Uzman
Formen
İdari Personel
Tekniker /Teknisyen
Takım Üyesi
9 Ünavnınız
Diğer
10 Kaç Yıldır Bu Kurumda Çalışıyorsunuz
11 Kuruluşunuzda Kaç Kişi Çalışıyor
12 Aylık Gelir Düzeyiniz
294
10.2.2. Questionnaire in English
Section I – Individual Competencies
Current Situation: Please evaluate the below situations as considering your
individual behaviorus and competencies at normal conditions
Crisis Situation: Please evaluate the below situations as considering your
individual behaviorus and competencies at crisis conditions
295
SECTION I
296
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
1 Motivate others
I motivate others to achieve common goals
CRISIS CONDITIONS
NORMAL CONDITIONS
2 Taking Responsibility
I follow-up and control a work until finalizing it
CRISIS CONDITIONS
NORMAL CONDITIONS
3 Decision Making
I evaluate an issue quickly and take right decision
CRISIS CONDITIONS
NORMAL CONDITIONS
4 Flexibility
I change my decision on a topic if it’s necessary CRISIS
CONDITIONS
NORMAL CONDITIONS
5 Delegation I delagte the tasks if it’s necessary CRISIS
CONDITIONS
NORMAL CONDITIONS
6 Independent I do the things by myself CRISIS
CONDITIONS
NORMAL CONDITIONS
7 Long Term View I prefer long term view
CRISIS CONDITIONS
NORMAL CONDITIONS
8 Detailed Focus
I don’t miss the details of a work
CRISIS CONDITIONS
NORMAL CONDITIONS
9 Evaluative I plan a work with the all advantages and disadvantages CRISIS
CONDITIONS
297
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
10 Committed I finalize the works on time that I committed
CRISIS CONDITIONS
NORMAL CONDITIONS
11 Effective Time Planning
I don’t postpone the important works because of urgent works CRISIS
CONDITIONS
NORMAL CONDITIONS
12 Organizing I prefer to know other’s opinions before I explain my thoughts CRISIS
CONDITIONS
NORMAL CONDITIONS
13 Effective Planning
I make the plans step by step
CRISIS CONDITIONS
NORMAL CONDITIONS
14 Quality work Follow-up
I obey the quality standards and rules when I’m working
CRISIS CONDITIONS
NORMAL CONDITIONS
15 Agreeable I follow-up common decisions CRISIS
CONDITIONS
NORMAL CONDITIONS
16 Influencing others
I care to influence others with my opinions
CRISIS CONDITIONS
NORMAL CONDITIONS
17 Friendly I believe that friendly and sympathetic behaviors makes the works easy CRISIS
CONDITIONS
NORMAL CONDITIONS
18 Conceptual I interest in conceptual knowledge about my work
CRISIS CONDITIONS
298
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
19 Follows Technology
I follow-up the latest technology about my work
CRISIS CONDITIONS
NORMAL CONDITIONS
20 Numerical Evaluation
I prefer to evaluate based on numerical data
CRISIS CONDITIONS
NORMAL CONDITIONS
21 Open to Learn
I implement the new methods and techniques that I learned
CRISIS CONDITIONS
NORMAL CONDITIONS
22
Confident About Knowledge
I achieve success on every work that I do
CRISIS CONDITIONS
NORMAL CONDITIONS
23
Evaluate Alternative Solutions
I evaluate the alternative solutions instead of using first idea that appeared in my mind CRISIS
CONDITIONS
NORMAL CONDITIONS
24 Evaluate Difficulties
I consider all obstacles and difficulties before starting a work CRISIS
CONDITIONS
NORMAL CONDITIONS
25 Problem Solving
I search the cause effect of a problem in detailed
CRISIS CONDITIONS
NORMAL CONDITIONS
26 Effective Speaking
I explain my thoughts effectively in a group when it’s need to talk about a topic CRISIS
CONDITIONS
NORMAL CONDITIONS
27 Speaking Thoughtfully
I care others opinions while I’m expressing my thoughts
CRISIS CONDITIONS
299
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
28 Outspoken I loose my attention on a text if there is writing mistakes
CRISIS CONDITIONS
NORMAL CONDITIONS
29 Presenting I feel comfortable when I’m making presentation
CRISIS CONDITIONS
NORMAL CONDITIONS
30 Cares Writing Rules
I care writing mistakes CRISIS
CONDITIONS
NORMAL CONDITIONS
31 Effective Writing
I prefer to use clear and lean sentences when I’m writing
CRISIS CONDITIONS
NORMAL CONDITIONS
32 Competitive I compete to achieve success if it’s necessary
CRISIS CONDITIONS
NORMAL CONDITIONS
33 Decisive I loose my attention on a text if there is writing mistakes
CRISIS CONDITIONS
NORMAL CONDITIONS
34 Customer Orientation
I like to sales activities to cover the customer requirements CRISIS
CONDITIONS
NORMAL CONDITIONS
35
Balance Between Work&Private Life
Problem in private life doesn’t reflects the work life even I care to act professionally CRISIS
CONDITIONS
NORMAL CONDITIONS
36 Risk Taker I take the risk if it’s necessary CRISIS
CONDITIONS
300
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
37 Creative
I like to present unconventional ideas
CRISIS CONDITIONS
NORMAL CONDITIONS
38 Conventional
I prefer to use valid methods when I’m working
CRISIS CONDITIONS
NORMAL CONDITIONS
39 Innovative
I believe that innovative approaches add diversity and value to the work CRISIS
CONDITIONS
NORMAL CONDITIONS
40 Action Oriented
I prefer to start a work by myself instead of waiting a support from others CRISIS
CONDITIONS
NORMAL CONDITIONS
41 Result Oriented
I like compelling targets CRISIS
CONDITIONS
NORMAL CONDITIONS
42 Loyalty
I don’t loose my belief when the works going to the way that I’m not expected CRISIS
CONDITIONS
NORMAL CONDITIONS
43 Visionary I act for the future
CRISIS CONDITIONS
NORMAL CONDITIONS
44 Strategic
I prefer to know other’s opinions before I explain my thoughts CRISIS
CONDITIONS
NORMAL CONDITIONS
45 Team Work I like to work with others to achieve a common goals
CRISIS CONDITIONS
301
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
46 Supportive I support others for their success when it’s necessary
CRISIS CONDITIONS
NORMAL CONDITIONS
47 Encouraging I encourage others to increase their contribution into co-operation CRISIS
CONDITIONS
NORMAL CONDITIONS
48 Responsive I understand others concern and act responsive to them
CRISIS CONDITIONS
NORMAL CONDITIONS
49 Trust to Others
I rarely trust to others when a work finalized without a mistake CRISIS
CONDITIONS
NORMAL CONDITIONS
50 Behavioral I wonder the reasons of others behaviours
CRISIS CONDITIONS
NORMAL CONDITIONS
51 Adaptable I prefer to have warm and friendly relationship with my colleague CRISIS
CONDITIONS
NORMAL CONDITIONS
52 Situational I adjust my behavior according to others behavior
CRISIS CONDITIONS
NORMAL CONDITIONS
53 Adapt to Change
I don’t change any subject in my work
CRISIS CONDITIONS
NORMAL CONDITIONS
54 Vigorous I like to take new responsibilibilites and know new people CRISIS
CONDITIONS
302
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
55 Calm
It put out my patience if somebody disturb me when I’m working on an important subject CRISIS
CONDITIONS
NORMAL CONDITIONS
56 Patient I need to get quick result to keep my interest
CRISIS CONDITIONS
NORMAL CONDITIONS
57 Open to Critics
I don’t feel unhappy when somebody give negeative feedback about my work CRISIS
CONDITIONS
NORMAL CONDITIONS
58 Emotionally Controlled
I don’t loose my control at unexpected sitiuations
CRISIS CONDITIONS
NORMAL CONDITIONS
59 Anxious I don’t feel anxious before an important meeting
CRISIS CONDITIONS
NORMAL CONDITIONS
60 Energetic
I don’t loose my moral and takes long time to recover after an unsuccessful sitiaution CRISIS
CONDITIONS
NORMAL CONDITIONS
61 Optimistic I believe the things goes well even everybody worries
CRISIS CONDITIONS
NORMAL CONDITIONS
62 Achieving I don’t quit when I facing with any obstacles
CRISIS CONDITIONS
NORMAL CONDITIONS
63 Confident I am very confident at every situation
CRISIS CONDITIONS
303
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
64 Ambitious I target to be successful in my career
CRISIS CONDITIONS
304
SECTION II
305
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
1 Leadership
I trust management decisions and follow them
CRISIS CONDITIONS
NORMAL CONDITIONS
2 Flexibility
Management adjust the targets, strategies and organization strutures according to existing conditions
CRISIS CONDITIONS
NORMAL CONDITIONS
3 Responsibility
Management takes responsibility abut successful and unsuccesfull results. CRISIS
CONDITIONS
NORMAL CONDITIONS
4 Vission and Mission
Our corporate mission and vision is clear
CRISIS CONDITIONS
NORMAL CONDITIONS
5 Profitability
In our cooperation there is always cost control to be profitable CRISIS
CONDITIONS
NORMAL CONDITIONS
6 Product and Service
I suggest product and sevice that our corporate provide
CRISIS CONDITIONS
NORMAL CONDITIONS
7 Innovative
Our cooperation is leader to develop new technologies
CRISIS CONDITIONS
NORMAL CONDITIONS
8
Customer Relationship Management
Our coperation always care high level of customer satisfaction CRISIS
CONDITIONS
NORMAL CONDITIONS
9 Quality Focus
Our coperation always cars to increase product and service quality CRISIS
CONDITIONS
306
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
10 Equality Employees have equal rights CRISIS
CONDITIONS
NORMAL CONDITIONS
11 Transparency
All procedures are clear and transparent in the corporation
CRISIS CONDITIONS
NORMAL CONDITIONS
12 HR Strategy HR application is compatible with corporation strategy and targets CRISIS
CONDITIONS
NORMAL CONDITIONS
13 Employee Support Program
There is a department to get advise when a conflict, stress situation or other problems are occurred CRISIS
CONDITIONS
NORMAL CONDITIONS
14 Recruitment Hiring is done with objective and equal criteria based on the work plans CRISIS
CONDITIONS
NORMAL CONDITIONS
15 Firing Employees are informed about downsizing before firing
CRISIS CONDITIONS
NORMAL CONDITIONS
16 Performance Evaluation
My performance are assesses regularly with objective and transparent criteria’s CRISIS
CONDITIONS
NORMAL CONDITIONS
17 Individual Development
I gather the trainings related with my job and position
CRISIS CONDITIONS
NORMAL CONDITIONS
18 Career Planning
My career targets are open and planning objectively
CRISIS CONDITIONS
307
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
19
Crisis Management
All procedures and precaution are clear when a crisis situation occurred CRISIS
CONDITIONS
NORMAL CONDITIONS
20 Economic Crisis
To reduce the negative effects of economic uncertainty most effective cautions are planned CRISIS
CONDITIONS
NORMAL CONDITIONS
21 Stability
The way of work changes rarely
CRISIS CONDITIONS
NORMAL CONDITIONS
22 Globalisation
Effects of the globalisation is positive in business life
CRISIS CONDITIONS
NORMAL CONDITIONS
23 Technology
Our corporation follows new technology and implement it
CRISIS CONDITIONS
NORMAL CONDITIONS
24 Social Life Balance
My social life and environment are very vigorous
CRISIS CONDITIONS
NORMAL CONDITIONS
25 Family Life Balance
My family life is very positive and supportive
CRISIS CONDITIONS
NORMAL CONDITIONS
26 Competition
The competitionb is very high in the sector that I work
CRISIS CONDITIONS
NORMAL CONDITIONS
27 Job Description My job is defined very clearly
CRISIS CONDITIONS
308
No Label Name Situations
Dis
agre
e
Rar
ely
A
gree
Slig
htly
A
gree
Som
ewha
t A
gree
Stro
ngly
Agr
ee
Def
inet
ly
Agr
ee
NORMAL CONDITIONS
28 Work Flow
Work flows in our corporation helps the works done fast and easy CRISIS
CONDITIONS
NORMAL CONDITIONS
29 Work Load Work load is equally organized
CRISIS CONDITIONS
NORMAL CONDITIONS
30 Work Responsibility
My work responsibility area is very wide
CRISIS CONDITIONS
309
SECTION III
310
No Questions
1 Your Age
2 Your Gender Female Male
3 Your Marital Status Single Married
Primary School University Doctorate 4
Your Highest Completed Level of Education High School Master
5 Your Occupation
6 Total Years of Employed
7 Your Company Private Public
General Management Operation
Human Resouces Logistic
Finance Technical Services
Sales and Marketing Services
8 Your Department
Manufacturing Other
Manager
Specialist
Formen
Adminisrative Personel
Tecnihian
Team Member
9 Your Position
Other
10 Years of Employement in Existing Company
11 Total Number of Employee in Existing Company
12 Monthly Salary
311
10.3. Outputs of Findings
Outputs of findings are listed in finding section.
312
11. REFERENCES
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April 1998
2. David McClelland, (1973). Testing for competence rather than for intelligence,
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313
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m
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2008
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