วิทยานิพนธ์ปริญญาบริหารธุรกิจมหาบัณฑิต...

The Relationships between the Morals in Aspect of Having Human Relations, the Accounting Professional Ethics and the Work Efficiency of Accountants: The Case Study of Accountants in the Listed Companies in Stock Exchange

of Thailand in Bangkok Metropolis.

: 2557

385 1) ,

2.1) , , ,

0.05 2.2)

0.05 2.3) ,

, , / 0.05

3) 3.1)

THESIS

Title : The Relationships between the Morals in Aspect of Having Human Relations, the Accounting Professional Ethics and the Work Efficiency of Accountants: The Case Study of Accountants in the Listed Companies in Stock Exchange of Thailand in Bangkok Metropolis.

Researcher : Mr. Chatarmorn Yamcharoen Advisor : Dr. Prapatsorn Kittimanorom Program : Master of Business Administration Year : 2014

ABSTRACT This research aims to study the opinions, compare opinions and study

relationships between the morals in aspect of having human relations, the accounting professional ethics and the work efficiency of accountants. The research population and samples were accountants in the listed companies in Stock Exchange of Thailand in Bangkok Metropolis, numbering 478 companies. The tools used in the research were questionnaires. There were 385 responses returning. The research result found that:

1) The accountants had opinions related with the morals in aspect of havinghuman relations in the high level; the accounting professional ethics was in the most level and the work efficiency was in the high level.

2) From the compare opinions of accountants in the overview, it was foundthat:

2.1) The opinions of the morals in aspect of having human relations; the accountants with different age, education level, marriage status, industry of the organization and salary level had opined differently at significant level of 0.05.

2.2) The opinions of the accounting professional ethics; the accountants with different age and salary level had opined differently at significant level of 0.05.

2.3) The opinions of the work efficiency; the accountants with different age, industry of the organization, work experience, salary level and numbers of accountants in accounting department had opined differently at significant level of 0.05.

3) From the tests of relationships in the overview, it was found that:3.1) The morals in aspect of having human relations, in self-sacrifice and

apportionment, behave according with the rules and responsibilities that should be done, opinion and using of discretion; had relations and positive effects on the work efficiency at significant level of 0.05.

3.2) The accounting professional ethics, in independence, regarding knowledge and capability, work performance standard and responsibility towards shareholders, partners, individuals or juristic persons working for them; had relations and positive effects on the work efficiency at significant level of 0.05.

1 1 1.1 1 1.2 3 1.3 3 1.4 4 1.5 4 1.6 5 1.7 5 1.8 7 1.9 7 1.10 8

2 11 2.1 11 2.2 16 2.3 18 2.4 28 2.5 31 2.6 37 2.7 45 2.8 53

3 56 3.1 56 3.2 56 3.3 57 3.4 60 3.5 61

4.1 63 4.2 65 4.3 65 4.4 92 4.5 198 4.6 228 4.7 234

5 237 5.1 237 5.2 246 5.3 250

258 . .2547 259 ( 19)

. .2553 281 289

300 312

2.1 162.2

554.1 664.2 664.3 664.4 674.5 674.6 674.7 684.8 684.9 694.10 / 694.11

704.12

71 4.13

72 4.14

73 4.15

74 4.16

4.17 76

4.18 77

4.19 78

4.20 79

4.21 80

4.22 81

4.23 82

4.24 83

4.25 84

4.26 85

864.28

4.29 88

4.30 89

4.31 90

4.32 91

4.33 94

4.34 95

4.35 96

964.37

974.39

984.41

4.42 100

1014.44

1024.46

1034.48

4.49 104

4.50 105

1064.52

1074.54

1084.55

1104.57

1124.59

114 4.61

4.62 116

1174.64

1184.66

4.67 120

1214.69

1234.71

1254.73

1274.75

1284.76

4.78 134

4.79 135

4.80 136

4.81 136

4.82 137

4.83 138

4.84 138

4.85 139

1394.87

140 4.88

1414.90

4.91 143

1444.93

1454.95

1464.96

1474.97

4.98 149

1504.100

1524.102

154 4.104

4.105 156

1574.107

4.108 158

4.109 159

4.110 160

4.111 161

1624.113

1654.116

1674.118

4.119 169

4.120 170

1714.122

4.123 172

1734.125

4.126 177

4.127 178

4.128 178

4.129 179

4.130 180

4.131 180

4.132 181

4.133 182

4.134 183

184 4.136

4.137 186

4.138 187

4.140 188

4.141 189

4.142 190

4.143 191

4.144 192

4.145 193

4.146 194

194 4.148

1964.150

1994.151

2004.152

4.153 202

4.154 203

4.156 205

4.157 206

207 4.159

2084.160

2094.161

2104.162

2114.163

2134.164

4.166 216

4.167 217

2184.169

2194.170

2204.171

2224.172

2234.173

2244.174

226 4.175

1.1 62.1 5 Maslow 12 2.2 Alderfer Maslow 14 2.3 27

“ ” ( ( . . ), 2550 : 437 – 438)

( ) ( , 2548 : 62)

. .2547

( 19) . .2553

1.2 1.2.1

1.3 1.3.1

1.4 1.4.1

1.5.2 (1)

4 . .2556 478 (

( 2554 : 13 – 14) 5 % 95 % 385

1.5.4 . .2557

– . .2557

1.6.1 1)

2) 2.1) 2.2) 2.3)

( . . ) (2551 : 201) 2)

( 19) . .2553 3)

(2546 : 8 – 9)

(Concept Framework)

1.1 : (Concept Framework)

Independent Variables

Dependent Variables

- - - - -

- - - - - - - - -

- - - - - - - - - - /

(Questionnaires) 5

1.9 1.9.1

1) 2) 3) 4) 5) 6) 7) 8)

2.1.1 (Maslow’s Hierarchy of Needs) (Abraham Harold Maslow)

. .1943 (A Theory of Human Motivation) (Maslow, 1943 : 370 – 396)

(Motivation and Personality) . .1954 (Maslow, 1954)

( , 2542 : 51) ( . . . , 2548 : 49)

(1) (2)

( . . . , 2548 : 49)

2.1 : 5 Maslow

1) (Physiological needs)

( . . . , 2548 : 50) 2) (Safty needs)

( . . . ,

2548 : 51) 3) (Love and belonging needs)

( . . . , 2548 : 52) - - - - -

Self - actualization needs

Esteem needs

Love and belonging needs

Safty needs

Physiological needs

4) (Esteem needs) ( . . . , 2548 : 52)

- - - - - - -

5) (Self – actualization needs) ( . . . , 2548 : 52)

- - - - - - -

( . . . , 2548 : 53) 5

( . . . , 2548 : 53) 1 5

( , 2542 : 54)

2.1.2 (Alderfer’s ERG Theory) (Clayton Paul Alderfer) . .1969

An Empirical Test of a New Theory of Human Needs. (Alderfer, 1969 : 142 – 175) 5

Alderfer’s Modified Need Hierarchy Theory ( , 2542 : 54)

3 Existence – Relatedness – Growth ERG Theory

2.2 : Alderfer Maslow ( , 2542 : 55)

4. 2 3. 1 2.

5 3 ( , 2542 : 55)

1 (Existence) 1 2

2 (Relatedness) 3

3 (Growth) 4 5

3 ( , 2542 : 55)

1 3 (Frustration)

( , 2542 : 56)

2.1.3 (McClelland’s Socially Acquired Needs Theory) (David Clarence McClelland) 1962 Business Drive and National Achievements. (McClelland, 1962 :

99 – 112) 3 ( ,

2542 : 56) 3 1) (Need for Achievement)

2) (Need for Affiliation)

3) (Need for Power)

2.1.4 (Herzberg’s Two Factors Theory) Frederick Irving Herzberg . .1959 The Motivation to Work. (Herzberg, 1959)

( . . . , 2548 :

53 - 54) 1) (Motivational factors)

2) (Hygiene factors)

2.1 : Abraham H. Maslow Clayton P. Alderfer David C. McClelland Frederick I. Herzberg

(Physiological needs)

(Existence) -

(Hygiene factors)

(Safty needs)

(Love and belonging needs)

(Relatedness)

(Need for Affiliation)

(Esteem needs)

(Growth)

(Need for Power)

(Motivational factors)

(Self – actualization needs)

(Need for

Achievement)

2.2.1 . .2554 “ ”

, , ( , 2556 : 303) (2524)

(2540)

Kohlberg (1970)

Carroll (1993) (Moral Duty and

Obligation) (Morality) (Moral Conduct)

( , 2554 : 14)

1) (The Utilitarian View)

2) (The Individualism View)

3) (Moral – Rights View) (Basic Human

Rights)

4) (The Justice View)

2.3.1 . .2554 “ ”

( , 2556 : 879)

(2553 : 17)

(2538 : 2)

(2525 : 4)

(2541 : 2)

(2536 : 120)

(2542 : 134)

(2549 : 2)

(2535 : 1)

(2551 : 13)

(2540 : 4)

(2530 : 10)

(2542 : 25)

(2527 : 2)

(2535 : 17)

. . . (2548 : 3)

( . . . 2548 : 5) Benton (1998)

Dalton, Hoyle Watts (2000)

Davis (1957)

DeCenzo (1997)

Dubrin (1981 : 4)

Flippo (1966 : 15)

Gellerman (1966 : 12)

( , 2526 : 15 – 18) 4 (Keith Davis, 1952)

1) 2) 3) 4)

1) (Individual Difference)

(Socialization Process)

2) (whole person)

3) (Caused behaviour)

4) (Human dignity)

(2527 : 2 – 3)

(2550 : 19 – 20)

( 2550 : 22)

(2549 : 5)

(2542 : 95)

(2548 : )

( 2548 : 2)

(2530 : 42)

(2542 : 11)

(2543 : 15 – 16)

. . . (2542 : 16)

Kossen (1978 : 6)

( , 2548 : 2) 1) 2)

( , 2540 : 16) 1) 2) 3) 4) 5) 6)

( . . . , 2548 : 25) 1)

2) “

( , 2548 : 2) 1)

3) (job role)

2.3.7 ( , 2551 : 44 – 45)

3 1) 2) 3) ( , 2549 : 128)

2.3 : ( , 2549 : 129)

3 ( , 2549 : 130)

2.4.1 3 ( ,

2550 : 53 – 54) 1)

( , 2539 : 44) - MAN IS POWER - MAN IS ASSETS - MAN IS MONEY - MAN IS TECHNOLOGY CREATOR - MAN IS DIGNITY -

“ ”

. .2554 “” ( , 2556 : 1224)

( . . ) (2550 : 437 – 438) “ ” “ ”

- - - - - ( ) - ( )

( . . ) (2551 : 201) 6

6 - ( ) - ( ) - ( ) - ( ) -

( ) - ( )

2552 : 55) 6 “ ” , “ - ” , “ ” , “ ”

, “ ”, “ ” “ ” ( ( . . ), 2551 : 201)

2 2.1) “ ” ,

“ ” “ ” 2.2) “ ”

, “ ”, “ ” “ ”

( , 2554 : 19)

( , 2554 : 20)

( , 2549 : 133)

4 . .2540 ( ,

2549 : 133) “

( 2549 : 133 – 134)

. .2554 “ ”

( , 2556 : 301)

( , 2549 : 54)

( , 2549 : 134)

( , 2549 : 134) (1)

2 ( , 2549 : 54)

( , 2549 : 55)

( , 2549 : 56) 4.3.1)

4.3.2)

4 ( , 2549 : 135)

2.5.2 (Accounting)

( , , 2550 : 4) (Book Keeping)

( , 2550 : 4 – 5)

2.5.3 . .2547 “ ”

2.5.4 (Information Technology)

( , 2550 : 4)

. .2547 47

( 19) . .2553

. . 2547

2.6.1 . .2554 “ ”

( , 2556 : 713) (2542 : 49) “ ” (Efficiency)

(Efficiency is Do Things Right) (2539 : 315)

(2542 : 7)

2.6.2 (2548 : 15 – 16)

(2546 : 6)

(2548 : 37)

(2548 : 16)

Input Output

(2549 : 22)

(2552 : 11)

(2545 : 3)

(2550 : 4) ,

(2523 : 246) (Job Efficiency)

(2552 : 30)

(2546 : 7)

Millett (1954 : 4)

(Human satisfaction and benefit produced) Ryan Smith (1954 : 276) (Human Efficiency)

( , 2523 : 246)

( , 2542 : 7 – 8)

3 ( , 2542 : 40 – 41) 1) (Cognitive Abilities)

1.3) 1.4) 1.5)

1.6) 1.7)

2) (Performance Abilities) 2.1)

2.2) (Information

Technology) 2.3) 2.4) 2.5) 2.6) 2.7)

3) (Affective Characteristics) 3.1) 3.2) 3.3) 3.4) 3.5)

( 2542 : 206-209) 1)

1.4) 1.5)

2) 2.1)

4.1) (Technical Skill)

4.2) (Human Skill)

4.3) (Conceptual Skill)

2.6.4 (2550 : 37 – 38) (Job

satisfaction) Herzberg (1957 : 103)

Pigors Meyer (1969 : 160 – 161) Becker Neuhauser (1975)

(Model of organizational efficiency)

(Open system) 1) (Low task –

environment complexity) (Certainty)

(High task –

environment complexity) (Uncertainty) 2) (Specification of procedure)

(Visibility of consequences)

(2521 : 30) 12

1) 2) 3) 4) 5) 6)

7) 8) 9) 10) 11) 12)

3 ( , 2546 : 8 – 9)

1) (Implementation Cost)

2) (Service Timing)

3) (Service Quality)

(2540 : 29)

(2546 : )

(2546 : ) “ ”

(2547 : ) “”

(2548 : ) “ SMEs

” SMEs

(2549 : ) “

(1) (2)

(3) (4)

(2549 : ) “”

1) 2) 3)

4) 5) 6)

(2550 : ) “

(2550 : ) “ ( . . .)

( 3)”

(2550 : ) “”

(2551 : ) “ ”

(2551 : ) “

SMEs ”

(2551 : ) “

(2552 : ) “ SMEs ”

SMEs SMEs

(2552 : ) “ ”

(2552 : ) “”

(2553 : ) “”

(2554 : ) “ ”

(2554 : ) “

” 21 – 35

/ 5,000

Atkinson, A.S. (2002 : 212 - 218) “”

Buchan (2009 : 1 – 7) “ :

1. ( ) 2. ( ) 3. ( ) 4. ( ) 5.

6. ( )

6 ( . . ) (2551 : 201)

2.3 . .2547 ( 19)

. .2553 . .2547

( 19) . .2553

( 19) . .2553 10

3. / /

2.4 (2546)

1) 2) 3) 4) 5)

: (Quantitative Research)

(Survey Research) (Questionnaires)

(Population)

4 . .2556

478 ( , ) (Representative Sample)

( 2554 : 13 – 14) 5% 95%

(Questionnaires)

1) 2) 3) 4)

5) (Validity) 3

5.1) 5.2) 5.3) / (CPA) 4976

6) (Index of Item-Objective Congruence : IOC)

IOC N +1 0 -1 0.50

8) (Try out) 30

9) Item – Total Correlation

(r) 0.385 – 0.799 (r) 0.474 – 0.906

(r) 0.394 – 0.921

10) (Reliability) Cronbach’s Alpha Coefficient

( – Coefficient) 0.759 – 0.858 ( – Coefficient) 0.771 – 0.918

( – Coefficient) 0.763 – 0.924 11)

(Closed – ended Question) (Check List) (Open – ended Question)

35 (Rating Scale) 5

Likert Scale

( 19) . .2553 10

44 (Rating Scale) 5

Likert Scale

2 3 (Rating Scale) Likert Scale 5

5 4 3 2 1

(2546 : 8 – 9) 3 18

(Rating Scale) 5 Likert Scale

4 (Rating Scale) Likert Scale 5

5 4 3 2 1

5 (Open – ended Question)

Internet http://goo.gl/tCh1q4 – . .2557

3) Internet 385

2) (Coding) 3)

4.1.1) (Frequency) 4.1.2) (Percentage)

4.2.1) (Frequency) 4.2.2) (Percentage)

4.2.3) (Mean or ) 4.2.4) (Standard Deviation : S.D.) 4.2.5)

(Range) = –

4.21 – 5.00 3.41 – 4.20 2.61 – 3.40 1.81 – 2.60 1.00 – 1.80

t – test 2 2 (One Way Analysis of Variance : ANOVA F – test)

(Least Signi cant Difference : LSD)

4.4.1) Variance Inflation Factors (VIFs) 4.4.2) (Correlation Analysis) 4.4.3)

(Multiple Regression Analysis) 4.5)

1) 2) 3) 4) 5) 6) 7)

n (Mean) S.D. (Standard Deviation) t t – distribution F F – distribution Sig. (Significance) VIF (Variance Inflation Factor)

R2 (R Square)

Adj. R2 (Adjusted R Square) SEest

(Standard Error of the estimate) MHR1

APE1 APE2 APE3 APE4 APE5 APE6 APE7 APE8 APE9

APE10 APET

WEA2 WEA3 WEAT

1) 2) 3) 4) 5)

4.1 – 4.10

4.1 ( ) (%)

125 260

32.47 67.53

385 100.00

4.1 385 260 67.53 125 32.47

( ) (%)

1. 21 – 28 2. 29 – 36 3. 37 – 44 4. 45 – 52 5. 53 – 60

75 122 95 61 32

19.48 31.69 24.68 15.84 8.31

385 100.00

4.2 385 29 – 36 122 31.69 37 –

44 95 24.68, 21 – 28 75 19.48, 45 – 52 61 15.84

53 – 60 32 8.31

4.3 ( ) (%)

1. 2. 3.

6 257 122

1.56 66.75 31.69

385 100.00

4.3 385 257 66.75

122 31.69 6 1.56

4.4 ( ) (%)

1. 2. 3.

381 2 2

98.96 0.52 0.52

385 100.00

4.4 385 381 98.96 2

0.52 2 0.52

4.5 ( ) (%)

1. 2. 3. 4.

218 162 3 2

56.62 42.08 0.78 0.52

385 100.00

4.5 385 218 56.62 162

42.08, 3 0.78 2 0.52

( ) (%)

1. 2. 3. 4. 5. 6. 7. 8. 9. (Holding Company)

6 47 86 34 48 21 108 32 3

1.56 12.21 22.34 8.83 12.47 5.45 28.05 8.31 0.78

385 100.00

4.6 385 108 28.05

86 22.34, 48 12.47, 47 12.21, 34 8.83, 32

8.31, 21 5.45, 6 1.56 (Holding

Company) 3 0.78

4.7 ( ) (%)

1. 6 2. 7 – 12 3. 13 – 18 4. 19 – 24 5. 25 – 30 6. 31 – 36

204 84 27 48 9 13

52.99 21.82 7.01 12.47 2.34 3.38

385 100.00

4.7 385 6 204 52.99

7 – 12 84 21.82, 19 – 24 48 12.47,

13 – 18 27 7.01, 31 – 36 13 3.38 25 – 30 9 2.34

( ) (%)

1. / 2.

89 296

23.12 76.88

385 100.00

4.8 385 296 76.88

/ 89 23.12

4.9 ( ) (%)

1. 10,000 2. 10,001 – 15,000 3. 15,001 – 20,000 4. 20,001 – 25,000 5. 25,001 – 30,000 6. 30,000

6 33 47 71 96 132

1.56 8.57 12.21 18.44 24.94 34.29

385 100.00

4.9 385 30,000 132 34.29

25,001 – 30,000 96 24.94, 20,001 – 25,000 71 18.44,

15,001 – 20,000 47 12.21, 10,001 – 15,000 33 8.57

10,000 6 1.56

4.10 / / ( ) (%)

1. 10 2. 11 – 40 3. 41 – 70 4. 71 – 100 5. 100

182 155 32 11 5

47.27 40.26 8.31 2.86 1.30

385 100.00

4.10 385 / 10 182 47.27

/ 11 – 40 155 40.26, / 41 – 70

32 8.31, / 71 – 100 11 2.86 / 100 5 1.30

4.3.2 6

(n = 385)

1. 4.11 .493 2. 3.94 .517 3. 3.92 .574 4. 4.06 .533 5. 4.19 .501 6. 4.03 .545

4.04 .427

385 ( = 4.04)

( =4.19) ( =4.11), ( =4.06), ( =4.03),

( =3.94) ( =3.92) 4.12 – 4.17

4.3.3 10

(n = 385)

1. 4.45 .554 2. 4.22 .617 3. 4.32 .578 4. 4.47 .552 5. 4.30 .566 6. 4.32 .628 7. 4.50 .589 8. 4.35 .574 9.

4.30 .568

10. 4.29 .565

4.35 .481

4.18 385

( =4.35)

( =4.50) ( =4.47), ( = 4.45), ( =4.35),

( =4.32), ( =4.30),

( =4.29) ( =4.22) 4.19 – 4.28

4.3.4 3

(n = 385)

1. 4.10 .574 2. 4.23 .534 3. 4.12 .537

4.14 .496

385 ( =4.14)

( =4.23)

( =4.12) ( =4.10) 4.30 – 4.32

( =4.12) ( =4.24)

( =4.23) ,

( =4.18) ( =4.17) ( =4.15)

( =4.13)

( =4.10) ( =4.03) ( =3.99)

( = 3.98)

/ t – test 2 2

(One Way Analysis of Variance : ANOVA F – test)

(Least Significant Difference : LSD)

/ 4.33 – 4.77

10 : /

(n = 385)

t Sig.

( n = 125 )

( n = 260 )

S.D. S.D.

1. 4.01 .450 4.16 .505 -2.983 .003** 2. 3.97 .475 3.93 .537 .812 .417 3. 3.91 .567 3.93 .578 -.324 .746 4. 4.04 .456 4.07 .567 -.543 .587 5.

4.04 .527 4.26 .473 -3.938 .000**

6. 4.02 .490 4.03 .571 -.205 .837

4.00 .410 4.06 .435 -1.364 .173 ** 0.01

0.01 1 1

21 –

37 –

53 –

ignifi

5 – 4

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.22 4.04 3.97 3.91 4.10

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.22 4.04 3.97 3.91 4.10

0.18**

0.26** 0.07

0.32** 0.13* 0.06

0.12 -0.06 -0.14 -0.19*

* 0.05 ** 0.01

4.35 21 – 28

29 – 36 , 37 – 44 45 – 52 0.01 29 – 36 45 – 52 53 – 60

45 – 52 0.05

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.28 4.19 4.02 3.90 4.11

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.28 4.19 4.02 3.90 4.11

0.26** 0.17**

0.38** 0.29** 0.12

0.17 0.08 -0.09 -0.21*

* 0.05 ** 0.01

4.36 21–28

37–44 45–52 0.01 29–36 37–44 45–52

0.01 53–60 45–52 0.05

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 3.92 3.93 3.92 3.88 4.23

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

3.92 3.93 3.92 3.88 4.23

0.00 0.01

0.04 0.05 0.04

-0.31** -0.30** -0.31** -0.35**

** 0.01

4.37 53 – 60

21 – 28 , 29 – 36 , 37 – 44 45 – 52 0.01

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.15 3.88 3.85 3.75 4.13

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.15 3.88 3.85 3.75 4.13

0.27**

0.30** 0.03

0.40** 0.12 0.09

0.02 -0.25* -0.28* -0.37**

* 0.05 ** 0.01

4.38 21 – 28

29 – 36 , 37 – 44 45 – 52 0.01 53 – 60 29 – 36 37 – 44

0.05 45 – 52 0.01

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.27 4.03 4.06 3.88 4.02

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.27 4.03 4.06 3.88 4.02

0.25**

0.21** -0.04

0.40** 0.15 0.19*

0.26* 0.01 0.04 -0.14

* 0.05 ** 0.01

4.39 21 – 28

29 – 36 , 37 – 44 45 – 52 0.01 53 – 60 0.05

37 – 44 45 – 52 0.05

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.38 4.20 4.01 4.22 4.18

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.38 4.20 4.01 4.22 4.18

0.37** 0.19**

0.16 -0.02

-0.21**

0.19 0.02 -0.17 0.04

* 0.05 ** 0.01

4.40 21 – 28

29 – 36 0.05 37 – 44 0.01

29 – 36 37 – 44 0.01 45 – 52 37 – 44

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.34 4.02 3.94 3.83 3.95

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.34 4.02 3.94 3.83 3.95

0.33**

0.40** 0.07

0.51** 0.19* 0.11

0.39** 0.07 -0.01 -0.12

* 0.05 ** 0.01

4.41 21 – 28

29 – 36 , 37 – 44 , 45 – 52 53 – 60

0.01 29 – 36 45 – 52 0.05

– 4.

3.74 4.09 3.96

-0.35* -0.22 0.13**

* 0.05 ** 0.01

3.92 3.99 3.84

-0.08 0.08 0.16**

** 0.01

3.73 3.99 3.79

-0.26 -0.06 0.20**

** 0.01

3.53 4.10 3.99

-0.57** -0.46* 0.11

* 0.05 ** 0.01

3.60 4.21 4.16

-0.61** -0.56** 0.05

** 0.01

3.67 4.08 3.94

-0.41 -0.27 0.14*

* 0.05

– 4.

4.00 4.11 4.25 3.65

-0.11* -0.25 -0.15

0.34 0.45 0.60

* 0.05

3.85 4.07 4.00 3.58

-0.21** -0.15 0.07

0.27 0.48 0.42

** 0.01

4.10 4.30 4.47 4.00

-0.20** -0.36 -0.17

0.10 0.30 0.47

** 0.01

ignifi

5 – 4

– 12

19 –

4.63 – 4.65

6 7 – 12 13 – 18 19 –24 25 –30 31 – 36 4.19 4.02 4.13 3.97 4.00 4.01

6 7 – 12 13 – 18 19 – 24 25 – 30 31 – 36

4.19 4.02 4.13 3.97 4.00 4.01

0.17** 0.06 -0.11

0.22** 0.05 0.16

0.19 0.02 0.13 -0.03

0.18 0.01 0.12 -0.04 -0.01

** 0.01

4.63 6

7 – 12 19 – 24 0.01

6 7 – 12 13 – 18 19 –24 25 –30 31 – 36 4.18 4.08 4.18 4.43 3.80 4.29 6

7 – 12 13 – 18 19 – 24 25 – 30 31 – 36

4.18 4.08 4.18 4.43 3.80 4.29

0.10 0.01 -0.09

-0.25** -0.35** -0.26*

0.38* 0.28 0.38* 0.63**

-0.11 -0.21 -0.11 0.14

-0.49*

* 0.05 ** 0.01

4.64 6

25 – 30 0.05, 13 – 18 25 – 30

0.05, 19 – 24 13 – 18

0.05 6 , 7 – 12 25 – 30 0.01

31 – 36 25 – 30 0.05

6 7 – 12 13 – 18 19 –24 25 –30 31 – 36 4.11 3.97 3.77 3.99 3.82 3.91 6

7 – 12 13 – 18 19 – 24 25 – 30 31 – 36

4.11 3.97 3.77 3.99 3.82 3.91

0.13 0.34** 0.20

0.12 -0.02 -0.22

0.29 0.15 -0.05 0.17

0.20 0.07 -0.14 0.08 -0.09

** 0.01

4.65 6

13 – 18 0.01

(n = 385)

t Sig.

( n = 89 )

( n = 296 )

S.D. S.D. 1. 4.05 .459 4.13 .501 -1.399 .162 2. 3.96 .504 3.94 .522 .352 .725 3. 3.93 .609 3.92 .564 .174 .862 4. 4.05 .511 4.06 .540 -.208 .835 5.

4.24 .480 4.17 .506 1.052 .293

6. 4.02 .551 4.03 .545 -.134 .894

4.04 .430 4.04 .427 -.025 .980

– 4.7

01 –

– 20

01 –

– 20

– 30

01 –

– 20

– 25

01 –

– 15

01 –

– 20

01 –

– 25

01 –

– 20

– 25

01 –

– 20

– 30

01 –

– 30

– 20

– 30

– 25

– 30

01 –

– 30

11 –

71 –

10 11 – 40 41 – 70 71 – 100 100 4.26 4.09 4.33 4.11 3.92

10 11 – 40 41 – 70 71 – 100

4.26 4.09 4.33 4.11 3.92

0.17**

-0.08 -0.24*

0.15 -0.02 0.22

0.34 0.17 0.41 0.19

* 0.05 ** 0.01

4.76 /

/ 11 – 40 0.01 / 41 – 70 / 11 – 40

0.05 /

4.33 – 4.76

- 0.01

0.05 2

- 0.01

0.05 0.01

- 0.05

0.01 5 5

0.05 6

0.01 6

7 0.05

0.01 7 7

- 0.01

9 0.01 9

10 0.01

/ 4.78 – 4.124

10 : /

(n = 385)

t Sig.

( n = 125 )

( n = 260 )

S.D. S.D.

1. 4.43 .576 4.45 .544 -.406 .685 2. 4.26 .623 4.20 .615 .895 .371 3. 4.33 .619 4.32 .558 .120 .905 4. 4.43 .600 4.49 .528 -.940 .348 5. 4.21 .599 4.34 .546 -2.025 .044* 6. 4.24 .653 4.36 .613 -1.668 .096 7. 4.36 .665 4.56 .538 -2.933 .004** 8. 4.35 .580 4.34 .573 .197 .844 9.

4.29 .564 4.30 .570 -.217 .828

4.19 .536 4.34 .573 -2.423 .016*

4.31 .503 4.37 .470 -1.147 .252 * 0.05 ** 0.01

1 0.05

0.01 1

29 –

45 –

4.80 – 4.90

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.50 4.41 4.18 4.29 4.40

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.50 4.41 4.18 4.29 4.40

0.32** 0.23**

0.21** 0.13 -0.10

0.10 0.02

-0.22* -0.11

* 0.05 ** 0.01

4.80 21 – 28 37 – 44

45 – 52 0.01, 29 – 36 37 – 44 0.01

53 – 60 37 – 44 0.05

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.59 4.52 4.26 4.38 4.52

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.59 4.52 4.26 4.38 4.52

0.33** 0.26**

0.20* 0.14 -0.13

0.07 -0.00 -0.26* -0.14

* 0.05 ** 0.01

4.81 21 – 28

37 – 44 0.01 45 – 52 0.05, 29 – 36

37 – 44 0.01 53 – 60 37 – 44 0.05

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.39 4.26 4.04 4.21 4.25

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.39 4.26 4.04 4.21 4.25

0.35** 0.22**

0.18 0.05 -0.17

0.14 0.01 -0.21 -0.04

** 0.01

4.82 21 – 28

37 – 44 0.01 29 – 36 37 – 44 0.01

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.42 4.37 4.17 4.27 4.48

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.42 4.37 4.17 4.27 4.48

0.24** 0.20*

0.15 0.10 -0.10

-0.07 -0.11

-0.31** -0.21

* 0.05 ** 0.01

4.83 21 – 28

37 – 44 0.01, 29 – 36 37 – 44 0.05

53 – 60 37 – 44 0.01

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.62 4.51 4.31 4.45 4.48

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.62 4.51 4.31 4.45 4.48

0.32** 0.21**

0.17 0.07 -0.14

0.14 0.03 -0.17 -0.03

** 0.01

4.84 21 – 28

37 – 44 0.01 29 – 36 37 – 44 0.01

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.40 4.41 4.15 4.17 4.27

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.40 4.41 4.15 4.17 4.27

0.25** 0.26**

0.22* 0.24** -0.02

0.13 0.14 -0.12 -0.10

* 0.05 ** 0.01

4.85 21 – 28

37 – 44 0.01 45 – 52 0.05, 29 – 36

37 – 44 45 – 52 0.01

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.37 4.42 4.13 4.32 4.38

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.37 4.42 4.13 4.32 4.38

0.24* 0.30**

0.05 0.10 -0.19

-0.01 0.04

-0.25* -0.06

* 0.05 ** 0.01

4.86 21 – 28

37 – 44 0.05, 29 – 36 37 – 44 0.01

53 – 60 37 – 44 0.05

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.64 4.59 4.27 4.45 4.59

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.64 4.59 4.27 4.45 4.59

0.38** 0.32**

0.20* 0.14 -0.18

0.05 -0.01

-0.33** -0.15

* 0.05 ** 0.01

4.87 21 – 28

37 – 44 0.01 45 – 52 0.05, 29 – 36

37 – 44 0.01 53 – 60 37 – 44 0.01

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.54 4.39 4.23 4.16 4.44

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.54 4.39 4.23 4.16 4.44

0.31** 0.15*

0.38** 0.23** 0.07

0.10 -0.05 -0.21 -0.28*

* 0.05 ** 0.01

4.88 21 – 28

37 – 44 45 – 52 0.01, 29 – 36 37 – 44

0.05 45 – 52 0.01 53 – 60 45 – 52

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.47 4.32 4.15 4.28 4.33

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.47 4.32 4.15 4.28 4.33

0.32** 0.18*

0.19 0.04 -0.13

0.14 -0.00 -0.18 -0.05

* 0.05 ** 0.01

4.89 21 – 28

37 – 44 0.01 29 – 36

37 – 44 0.05

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60 4.54 4.34 4.13 4.18 4.24

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.54 4.34 4.13 4.18 4.24

0.41** 0.21**

0.36** 0.16 -0.05

0.31** 0.10 -0.11 -0.06

* 0.05 ** 0.01

4.90 21 – 28

29 – 36 0.05 37 – 44 , 45 – 52 53 – 60

0.01 29 – 36 37 – 44 0.01

4.92 – 4.94

4.00 4.51 4.40

-0.51* -0.40 0.11

* 0.05

4.00 4.54 4.43

-0.54* -0.43 0.11

* 0.05

3.72 4.39 4.30

-0.66** -0.57* 0.09

* 0.05 ** 0.01

4.27 4.41 4.28 3.67

-0.15* -0.01 0.13

0.60 0.74 0.61

* 0.05

9 – 4

– 12

19 –

4.106 – 4.108

6 7 – 12 13 – 18 19 –24 25 –30 31 – 36 4.36 4.10 4.24 4.43 4.33 4.23

6 7 – 12 13 – 18 19 – 24 25 – 30 31 – 36

4.36 4.10 4.24 4.43 4.33 4.23

0.26** 0.12 -0.14

-0.08 -0.34** -0.20

0.02 -0.24 -0.10 0.10

0.12 -0.14 0.01 0.20 0.10

** 0.01

4.106 6

7 – 12 0.01 19 – 24

7 – 12 0.01

6 7 – 12 13 – 18 19 –24 25 –30 31 – 36 4.37 4.14 4.20 4.49 4.33 4.29

6 7 – 12 13 – 18 19 – 24 25 – 30 31 – 36

4.37 4.14 4.20 4.49 4.33 4.29

0.23** 0.17 -0.06

-0.12 -0.35** -0.29

0.04 -0.19 -0.13 0.16

0.08 -0.15 0.08 0.21 0.04

** 0.01

4.107 6

7 – 12 0.01 19 – 24

7 – 12 0.01

6 7 – 12 13 – 18 19 –24 25 –30 31 – 36 4.37 4.18 4.01 4.46 4.00 4.10

6 7 – 12 13 – 18 19 – 24 25 – 30 31 – 36

4.37 4.18 4.01 4.46 4.00 4.10

0.19** 0.36** 0.17

-0.09 -0.28** -0.45**

0.37 0.18 0.01 0.46*

0.27 0.08 -0.09 0.36* -0.10

* 0.05 ** 0.01

4.108 6

7 – 12 13 – 18 0.01,

19 – 24 7 – 12 13 – 18 0.01

25 – 30 31 – 36 0.05

(n = 385)

t Sig.

( n = 89 )

( n = 296 )

S.D. S.D.

1. 4.46 .567 4.44 .551 .287 .774 2. 4.22 .607 4.23 .621 -.107 .915 3. 4.36 .586 4.31 .576 .727 .468 4. 4.48 .566 4.47 .549 .180 .857 5. 4.31 .588 4.29 .560 .274 .784 6. 4.38 .600 4.30 .636 1.050 .294 7. 4.50 .601 4.50 .587 .074 .941 8. 4.32 .620 4.35 .561 -.453 .651 9.

4.33 .610 4.29 .555 .655 .513

4.28 .622 4.30 .548 -.294 .769

4.36 .506 4.35 .475 .294 .769

– 4.

01 –

– 20

01 –

– 25

01 –

– 20

01 –

– 25

– 20

– 30

01 –

– 30

– 25

01 –

– 30

01 –

– 30

– 20

– 30

01 –

– 30

– 20

01 –

– 30

01 –

– 30

11 –

71 –

4.121 – 4.123

10 11 – 40 41 – 70 71 – 100 100 4.51 4.35 4.64 4.18 4.27

10 11 – 40 41 – 70 71 – 100

4.51 4.35 4.64 4.18 4.27

0.16**

-0.12 -0.28**

0.33 0.17 0.45*

0.24 0.09 0.37 -0.08

* 0.05 ** 0.01

4.121 / 10

/ 11 – 40 0.01 /

41 – 70 / 11 – 40 0.01

/ 71 – 100 0.05 /

10 11 – 40 41 – 70 71 – 100 100 4.31 4.25 4.65 4.59 4.30

10 11 – 40 41 – 70 71 – 100

4.31 4.25 4.65 4.59 4.30

-0.34** -0.40**

-0.28 -0.34 0.06

0.01 -0.05 0.35 0.29

** 0.01

4.122 / 41 – 70

/ 10 11 – 40 0.01

10 11 – 40 41 – 70 71 – 100 100 4.34 4.18 4.50 4.53 4.00

10 11 – 40 41 – 70 71 – 100

4.34 4.18 4.50 4.53 4.00

0.16**

-0.16 -0.32**

-0.19 -0.35* -0.03

0.34 0.18 0.50 0.53

* 0.05 ** 0.01

4.123 / 10

/ 11 – 40 0.01,

/ 41 – 70 / 11 – 40

0.01 / 71 – 100 / 11 – 40

0.05 / 4.78 – 4.123

0.05 0.01

0.01 2

0.05 2 -

3 0.05 0.01 3 3

5 0.05

0.01 6 6

0.05 7 7

0.01 9

0.01 0.05

0.01 10 10

/ 4.125 – 4.149

10 : /

(n = 385)

t Sig.

( n = 125 )

( n = 260 )

S.D. S.D.

1. 4.05 .544 4.12 .587 -1.219 .223 2. 4.22 .518 4.23 .543 -.067 .947 3. 4.10 .556 4.13 .528 -.548 .584

4.11 .502 4.15 .495 -.614 .540

4.125 1

29 –

45 –

4.127 – 4.129

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.29 4.16 3.99 4.10 4.16

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.29 4.16 3.99 4.10 4.16

0.30** 0.17*

0.19* 0.06 -0.11

0.13 0.00 -0.17 -0.06

* 0.05 ** 0.01

4.127 21 – 28 37 – 44

0.01 45 – 52 0.05 29 – 36 37 – 44

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.30 4.13 4.00 3.91 4.17

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.30 4.13 4.00 3.91 4.17

0.30** 0.13

0.38** 0.21* 0.08

0.12 -0.05 -0.17 -0.26*

* 0.05 ** 0.01

4.128 21 – 28

29 – 36 0.05 37 – 44 45 – 52 0.01, 29 – 36

45 – 52 0.05 53 – 60 45 – 52 0.05

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.28 4.14 3.95 4.16 4.10

21 – 28 29 – 36 37 – 44 45 – 52 53 – 60

4.28 4.14 3.95 4.16 4.10

0.33** 0.19**

0.12 -0.02 -0.21*

0.18 0.04 -0.15 0.06

* 0.05 ** 0.01

4.129 21 – 28

37 – 44 0.01, 29 – 36 37 – 44 0.01

45 – 52 37 – 44 0.05

(n = 385)

F Sig.

( n = 6 )

( n = 257 )

( n = 122 ) S.D. S.D. S.D.

1. 3.88 .542 4.13 .557 4.05 .608 1.311 .271 2. 4.00 .418 4.23 .537 4.23 .534 .554 .575 3. 3.78 .531 4.13 .545 4.11 .518 1.307 .272

3.85 .466 4.15 .502 4.12 .485 1.177 .309

4.130 3

(n = 385)

F Sig.

( n = 381 )

( n = 2 )

S.D. S.D. S.D.

1. 4.09 .573 4.38 .884 4.50 .707 .732 .481 2. 4.23 .533 4.25 1.061 4.50 .707 .264 .768 3. 4.12 .536 4.25 .636 4.50 .707 .567 .568

4.13 .496 4.28 .786 4.50 .707 .620 .538

4.131 4

(n = 385)

F Sig.

( n = 218 )

( n = 162 )

( n = 3 )

( n = 2 ) S.D. S.D. S.D. S.D.

1. 4.11 .522 4.08 .632 4.33 1.155 3.88 .177 .331 .803 2. 4.24 .528 4.21 .535 4.33 1.155 3.88 .177 .414 .743 3. 4.11 .516 4.14 .552 4.33 1.155 3.50 .283 1.172 .320

4.13 .460 4.14 .532 4.33 1.155 3.67 .157 .758 .518

4.132 5

34 –

– 12

19 –

(Least Significant Difference : LSD) 4.138 – 4.139

6 7 – 12 13 – 18 19 –24 25 –30 31 – 36

4.15 4.03 4.12 4.29 4.26 3.95

6 7 – 12 13 – 18 19 – 24 25 – 30 31 – 36

4.15 4.03 4.12 4.29 4.26 3.95

0.12 0.03 -0.09

-0.14 -0.26** -0.17

-0.11 -0.23 -0.14 0.03

0.20 0.08 0.17 0.34* 0.31

* 0.05 ** 0.01

4.138 19 – 24

7 – 12 0.01 31 – 36 0.05

6 7 – 12 13 – 18 19 –24 25 –30 31 – 36 4.13 3.98 4.06 4.34 4.33 3.92

6 7 – 12 13 – 18 19 – 24 25 – 30 31 – 36

4.13 3.98 4.06 4.34 4.33 3.92

0.15* 0.07 -0.08

-0.21* -0.36** -0.28*

-0.20 -0.35 -0.27 0.01

0.21 0.07 0.15 0.42* 0.42

* 0.05 ** 0.01

4.139 6

7 – 12 0.05 19 – 24

6 , 13 – 18 31 – 36 0.05 7 – 12

(n = 385)

t Sig.

( n = 89 )

( n = 296 )

S.D. S.D. 1. 4.10 .648 4.10 .551 -.033 .974 2. 4.23 .527 4.23 .538 .075 .941 3. 4.14 .548 4.11 .534 .403 .687

4.15 .522 4.13 .490 .231 .818

4.140 8

01 –

– 25

11 –

71 –

– 4.

10 11 – 40 41 – 70 71 – 100 100 4.13 4.19 4.14 3.74 3.80

10 11 – 40 41 – 70 71 – 100

4.13 4.19 4.14 3.74 3.80

-0.01 0.05

0.39* 0.45** 0.40*

0.33 0.39 0.34 -0.06

* 0.05 ** 0.01

4.146 / 10

/ 71 – 100 0.05, / 11 – 40

/ 71 – 100 0.01 /

41 – 70 / 71 – 100 0.05 /

10 11 – 40 41 – 70 71 – 100 100 4.13 4.13 3.93 3.70 3.90

10 11 – 40 41 – 70 71 – 100

4.13 4.13 3.93 3.70 3.90

0.20 0.20

0.42* 0.43* 0.23

0.23 0.23 0.03 -0.20

* 0.05

4.147 / 10

/ 71 – 100 0.05 /

11 – 40 / 71 – 100 0.05 /

10 11 – 40 41 – 70 71 – 100 100 4.11 4.17 4.16 3.65 3.68

10 11 – 40 41 – 70 71 – 100

4.11 4.17 4.16 3.65 3.68

-0.05 0.02

0.45** 0.52** 0.50**

0.43 0.49* 0.48 -0.03

* 0.05 ** 0.01

4.148 / 10

/ 71 – 100 0.01, /

11 – 40 / 71 – 100 0.01 /

100 0.05 / 41 – 70 / 71 – 100

0.01 /

4.125 – 4.148

- 0.01 2

0.01 2

- 0.05

6 0.05

0.01 6 6

- 0.05

7 0.01 7

- 0.01 9

0.01 9

0.05 10

0.05 0.01 10

WEAT MHR1 MHR2 MHR3 MHR4 MHR5 MHR6

VIF 4.14 4.11 3.94 3.92 4.06 4.19 4.03 S.D. .497 .493 .517 .574 .533 .501 .545

WEAT 1.000 .382** .371** .472** .556** .484** .631** MHR1 1.000 .630** .573** .637** .390** .566** 2.106 MHR2 1.000 .700** .556** .423** .528** 2.324 MHR3 1.000 .655** .523** .680** 2.795 MHR4 1.000 .612** .735** 3.011 MHR5 1.000 .553** 1.707 MHR6 1.000 2.631

** 0.01

Multicollinearity

Multicollinearity VIF VIF 1.707 – 2.795 10

0.371 – 0.631

(WEAT) 4.151

t Sig.

1.391 0.198 7.026 0.000** -0.031 0.057 -0.030 -0.539 0.590 0.004 0.057 0.004 0.065 0.948 0.004 0.056 0.005 0.076 0.939

0.134 0.063 0.144 2.134 0.034*

0.152 0.050 0.154 3.032 0.003**

0.412 0.057 0.452 7.188 0.000**

R = 0.657 ; R2 = 0.432 ; Adj. R2 = 0.423 ; SEest = 0.37745 ; F = 47.836 ; Sig. F = 0.000

* 0.05 ** 0.01

4.151 (WEAT) 0.01 (Sig. F = 0.000)

WEAT = 1.391 – 0.031 MHR1 + 0.004 MHR2 + 0.004 MHR3 + 0.134 MHR4 + 0.152 MHR5 + 0.412 MHR6

(WEAT) (MHR6) (WEAT)

(MHR5) (MHR4)

(WEAT), (MHR1) (WEAT),

(MHR3) (MHR2) (WEAT)

(WEAT) (MHR4)

(WEAT)

0.05 (MHR5) (MHR6)

(WEAT) 0.01 4,5 6

(MHR1) (MHR2) (MHR3) (WEAT) 1, 2, 3 (MHR4) (MHR5)

(MHR6) (WEAT) 4.152

t Sig.

1.349 0.176 7.664 0.000** 0.122 0.057 0.131 2.143 0.033*

0.155 0.049 0.156 3.128 0.002**

0.408 0.053 0.448 7.718 0.000**

* 0.05 ** 0.01

4.152 (WEAT) 0.01 (Sig. F = 0.000)

WEAT = 1.349 + 0.122 MHR4 + 0.155 MHR5 + 0.408 MHR6

WEA1 MHR1 MHR2 MHR3 MHR4 MHR5 MHR6

VIF 4.10 4.11 3.94 3.92 4.06 4.19 4.03 S.D. .574 .493 .517 .574 .533 .501 .545

WEA1 1.000 .386** .330** .480** .488** .446** .550** MHR1 1.000 .630** .573** .637** .390** .566** 2.106 MHR2 1.000 .700** .556** .423** .528** 2.324 MHR3 1.000 .655** .523** .680** 2.795 MHR4 1.000 .612** .735** 3.011 MHR5 1.000 .553** 1.707 MHR6 1.000 2.631

** 0.01

Multicollinearity

0.330 – 0.550

(WEA1) 4.154

t Sig.

1.159 0.244 4.741 0.000** 0.090 0.070 0.077 1.284 0.200 -0.118 0.070 -0.107 -1.687 0.092 0.180 0.069 0.179 2.590 0.010**

0.053 0.077 0.049 0.688 0.492

0.187 0.062 0.163 3.005 0.003**

0.331 0.071 0.314 4.677 0.000**

** 0.01

4.154 (WEA1) 0.01

(Sig. F = 0.000)

WEA1 = 1.159 + 0.090 MHR1 – 0.118 MHR2 + 0.180 MHR3 + 0.053 MHR4 + 0.187 MHR5 + 0.331 MHR6

(WEA1) (MHR6) (WEA1)

(MHR3) (MHR5) (WEA1),

(MHR2) (WEA1), (MHR1)

(MHR4) (WEA1)

(WEA1)

(MHR3) (MHR5)

(MHR6) (WEA1)

0.01 3, 5 6 (MHR1) (MHR2)

(MHR4) (WEA1) 1, 2, 4

(MHR3) (MHR5)

(MHR6) (WEA1) 4.155

t Sig.

1.185 0.218 5.441 0.000** 0.151 0.058 0.151 2.582 0.010**

0.197 0.059 0.172 3.350 0.001**

0.371 0.063 0.353 5.914 0.000**

** 0.01

4.155 (WEA1) 0.01

(Sig. F = 0.000)

WEA1 = 1.185 + 0.151 MHR3 + 0.197 MHR5 + 0.371 MHR6

VIF 4.23 4.11 3.94 3.92 4.06 4.19 4.03 S.D. .534 .493 .517 .574 .533 .501 .545

** 0.01

Multicollinearity

0.297 – 0.514

(WEA2) 4.157

t Sig.

2.039 0.239 8.526 0.000** -0.062 0.069 -0.058 -0.910 0.363 0.053 0.069 0.051 0.770 0.442 -0.080 0.068 -0.086 -1.180 0.239

0.215 0.076 0.214 2.836 0.005**

0.009 0.061 0.008 0.146 0.884

0.407 0.069 0.416 5.883 0.000**

** 0.01

4.157 (WEA2) 0.01

(Sig. F = 0.000)

WEA2 = 2.039 – 0.062 MHR1 + 0.053 MHR2 – 0.080 MHR3 + 0.215 MHR4 + 0.009 MHR5 + 0.407 MHR6

(WEA2) (MHR6)

(WEA2) (MHR4)

(WEA2), (MHR3) (MHR1)

(WEA2), (MHR2) (MHR5)

(WEA2)

(MHR4) (MHR6)

(WEA2) 0.01 4 6

(MHR1) (MHR2) (MHR3)

(MHR5) (WEA2) 1, 2, 3 5

(MHR4) (MHR6)

(WEA2) 4.158

t Sig.

1.988 0.189 10.542 0.000** 0.181 0.064 0.180 2.809 0.005**

0.374 0.063 0.381 5.950 0.000**

** 0.01

4.158 (WEA2) 0.01

(Sig. F = 0.000)

WEA2 = 1.988 + 0.181 MHR4 + 0.374 MHR6

VIF 4.12 4.11 3.94 3.92 4.06 4.19 4.03 S.D. .537 .493 .517 .574 .533 .501 .545

** 0.01

Multicollinearity Multicollinearity VIF VIF

1.707 – 2.795 10

0.349 – 0.609

(WEA3) 4.160

t Sig.

1.238 0.218 5.679 0.000** -0.071 0.062 -0.066 -1.144 0.253 0.036 0.063 0.035 0.581 0.561 -0.024 0.062 -0.026 -0.393 0.694

0.128 0.069 0.128 1.859 0.064

0.196 0.055 0.183 3.541 0.000**

0.443 0.063 0.451 7.026 0.000**

** 0.01

4.160 (WEA3) 0.01

(Sig. F = 0.000)

WEA3 = 1.238 – 0.071 MHR1 + 0.036 MHR2 – 0.024 MHR3 + 0.128 MHR4 + 0.196 MHR5 + 0.443 MHR6

(WEA3) (MHR6)

(WEA3) (MHR5) (MHR4)

(WEA3), (MHR1)

(WEA3), (MHR2)

(WEA3) (MHR3) (WEA3)

(WEA3)

(MHR5) (MHR6)

(WEA3) 0.01 5 6 (MHR1)

(MHR2) (MHR3) (MHR4)

(WEA3) 1, 2, 3 4

(MHR5) (MHR6)

(WEA3) 4.161

t Sig.

1.213 0.192 6.320 0.000**

0.230 0.051 0.214 4.520 0.000**

0.483 0.047 0.491 10.338 0.000**

** 0.01

4.161 (WEA3) 0.01

(Sig. F = 0.000)

WEA3 = 1.213 + 0.230 MHR5 + 0.483 MHR6

4.150 – 4.161

1. 2. 3. ** 4. ** * 5.

** ** **

6. ** ** ** **

* 0.05 ** 0.01

3, 5 6

0.01 4 6

0.01 5 6

4, 5 6

WEAT APE1 APE2 APE3 APE4 APE5 APE6 APE7 APE8 APE9 APE10

VIF 4.14 4.45 4.22 4.32 4.47 4.30 4.32 4.50 4.35 4.30 4.29 S.D. .497 .554 .617 .578 .552 .566 .628 .589 .574 .568 .565

WEAT 1.000 .571** .602** .655** .617** .736** .765** .679** .709** .695** .670**

APE1 1.000 .612** .653** .670** .608** .560** .601** .597** .537** .596** 2.274

APE2 1.000 .740** .616** .595** .640** .533** .590** .451** .598** 2.597

APE3 1.000 .752** .733** .706** .690** .679** .605** .752** 4.386

APE4 1.000 .681** .700** .720** .720** .522** .636** 3.726

APE5 1.000 .830** .691** .741** .627** .678** 4.230

APE6 1.000 .719** .706** .609** .664** 4.163

APE7 1.000 .684** .728** .668** 3.517

APE8 1.000 .718** .702** 3.646

APE9 1.000 .696** 3.181

APE10 1.000 3.102 ** 0.01

Multicollinearity Multicollinearity VIF VIF 2.274 – 4.386

0.571 – 0.765

(WEAT) 4.164

t Sig.

0.600 0.135 4.444 0.000** 0.031 0.039 0.034 0.796 0.427

0.100 0.037 0.125 2.718 0.007** -0.049 0.051 -0.057 -0.953 0.341

-0.018 0.049 -0.020 -0.356 0.722 0.123 0.051 0.140 2.392 0.017*

0.257 0.046 0.325 5.589 0.000** 0.024 0.045 0.029 0.541 0.589

0.081 0.047 0.093 1.716 0.087

0.217 0.044 0.248 4.883 0.000**

0.055 0.044 0.062 1.242 0.215

* 0.05 ** 0.01

4.164 (WEAT) 0.01 (Sig. F = 0.000)

WEAT = 0.600 + 0.031 APE1 + 0.100 APE2 – 0.049 APE3 – 0.018 APE4 + 0.123 APE5 + 0.257 APE6 + 0.024 APE7 + 0.081 APE8 + 0.217 APE9 + 0.055 APE10

(WEAT) (APE6) (WEAT)

(APE9) (APE5) (APE2)

(APE8) (APE10) (WEAT), (APE3)

(WEAT),

(APE1) (APE7) (WEAT) (APE4)

(WEAT)

(WEAT) (APE5)

(WEAT) 0.05 (APE2) (APE6)

(APE9) (WEAT)

0.01 2, 5, 6 9 (APE1) (APE3) (APE4)

(WEAT) 1, 3, 4, 7, 8 10 (APE2)

(WEAT) 4.165

t Sig.

0.658 0.125 5.264 0.000** 0.112 0.030 0.139 3.696 0.000**

0.152 0.047 0.173 3.240 0.001** 0.269 0.043 0.339 6.181 0.000**

0.277 0.033 0.317 8.457 0.000**

** 0.01

4.165 (WEAT) 0.01 (Sig. F = 0.000)

WEAT = 0.658 + 0.112 APE2 + 0.152 APE5 + 0.269 APE6 + 0.277 APE9

WEA1 APE1 APE2 APE3 APE4 APE5 APE6 APE7 APE8 APE9 APE10

VIF 4.10 4.45 4.22 4.32 4.47 4.30 4.32 4.50 4.35 4.30 4.29 S.D. .574 .554 .617 .578 .552 .566 .628 .589 .574 .568 .565

WEA1 1.000 .499** .383** .485** .456** .534** .487** .550** .555** .644** .558**

APE1 1.000 .612** .653** .670** .608** .560** .601** .597** .537** .596** 2.274

APE2 1.000 .740** .616** .595** .640** .533** .590** .451** .598** 2.597

APE3 1.000 .752** .733** .706** .690** .679** .605** .752** 4.386

APE4 1.000 .681** .700** .720** .720** .522** .636** 3.726

APE5 1.000 .830** .691** .741** .627** .678** 4.230

APE6 1.000 .719** .706** .609** .664** 4.163

APE7 1.000 .684** .728** .668** 3.517

APE8 1.000 .718** .702** 3.646

APE9 1.000 .696** 3.181

APE10 1.000 3.102 ** 0.01

Multicollinearity

0.383 – 0.644

(WEA1) 4.167

t Sig.

0.656 0.207 3.167 0.002** 0.159 0.059 0.153 2.689 0.007**

-0.020 0.057 -0.021 -0.346 0.730 -0.069 0.079 -0.070 -0.881 0.379

-.00004185 0.076 0.000 -0.001 1.000 0.145 0.079 0.143 1.842 0.066

-0.042 0.071 -0.046 -0.598 0.550 0.047 0.069 0.049 0.686 0.493

0.043 0.072 0.043 0.594 0.553

0.402 0.068 0.397 5.894 0.000**

0.128 0.068 0.126 1.891 0.059

** 0.01

4.167 (WEA1) 0.01

(Sig. F = 0.000) WEA1 = 0.656 + 0.159 APE1 – 0.020 APE2 – 0.069 APE3 – 0.00004185 APE4 + 0.145 APE5 – 0.042 APE6 + 0.047 APE7 + 0.043 APE8 + 0.402 APE9 + 0.128 APE10

(WEA1)

(APE9) (WEA1)

(WEA1), (APE3) (WEA1),

(APE7)

(WEA1), (APE6) (WEA1),

(APE8) (WEA1), (APE2)

(APE4) (WEA1)

(WEA1) (APE1)

(APE9)

(WEA1) 0.01 1 9 (APE2) (APE3)

(APE4) (APE5) (APE6) (APE7) (APE8)

(APE10) (WEA1)

2, 3, 4, 5, 6, 7, 8 10 (APE1)

(APE9)

(WEA1) 4.168

t Sig.

0.808 0.196 4.126 0.000** 0.224 0.047 0.216 4.796 0.000**

0.533 0.046 0.527 11.702 0.000**

** 0.01

4.168 (WEA1) 0.01

(Sig. F = 0.000)

WEA1 = 0.808 + 0.224 APE1 + 0.533 APE9

VIF 4.23 4.45 4.22 4.32 4.47 4.30 4.32 4.50 4.35 4.30 4.29 S.D. .534 .554 .617 .578 .552 .566 .628 .589 .574 .568 .565

WEA2 1.000 .461** .548** .517** .502** .583** .684** .562** .634** .556** .517**

APE1 1.000 .612** .653** .670** .608** .560** .601** .597** .537** .596** 2.274

APE2 1.000 .740** .616** .595** .640** .533** .590** .451** .598** 2.597

APE3 1.000 .752** .733** .706** .690** .679** .605** .752** 4.386

APE4 1.000 .681** .700** .720** .720** .522** .636** 3.726

APE5 1.000 .830** .691** .741** .627** .678** 4.230

APE6 1.000 .719** .706** .609** .664** 4.163

APE7 1.000 .684** .728** .668** 3.517

APE8 1.000 .718** .702** 3.646

APE9 1.000 .696** 3.181

APE10 1.000 3.102 ** 0.01

Multicollinearity

0.461 – 0.684

(WEA2) 4.170

t Sig.

1.206 0.178 6.786 0.000** 0.028 0.051 0.029 0.555 0.580

0.173 0.049 0.200 3.557 0.000** -0.101 0.068 -0.109 -1.491 0.137

-0.116 0.065 -0.120 -1.787 0.075 -0.097 0.068 -0.103 -1.439 0.151

0.423 0.061 0.497 6.989 0.000** 0.053 0.059 0.059 0.897 0.370

0.271 0.062 0.292 4.383 0.000**

0.117 0.059 0.125 2.005 0.046*

-0.049 0.058 -0.052 -0.852 0.395

* 0.05 ** 0.01

4.170 (WEA2) 0.01

(Sig. F = 0.000)

WEA2 = 1.206 + 0.028 APE1 + 0.173 APE2 – 0.101 APE3 – 0.116 APE4 – 0.097 APE5 + 0.423 APE6 + 0.053 APE7 + 0.271 APE8 + 0.117 APE9 – 0.049 APE10

(WEA2) (APE6)

(WEA2) (APE8)

(APE2)

(APE9) (WEA2), (APE4) (APE3)

(APE5) (WEA2), (APE7)

(WEA2), (APE10)

(WEA2) (APE1)

(WEA2)

(APE9) (WEA2)

0.05, (APE2) (APE6) (APE8)

(WEA2) 0.01 2, 6, 8 9 (APE1) (APE3) (APE4) (APE5) (APE7)

(APE10) (WEA2) 1, 3, 4, 5, 7 10

(APE9)

(WEA2) 4.171

t Sig.

1.045 0.164 6.369 0.000** 0.111 0.041 0.128 2.704 0.007**

0.332 0.047 0.390 7.060 0.000** 0.184 0.055 0.198 3.326 0.001**

0.111 0.049 0.118 2.273 0.024*

** 0.01

4.171 (WEA2) 0.01

(Sig. F = 0.000)

WEA2 = 1.045 + 0.111 APE2 + 0.332 APE6 + 0.184 APE8 + 0.111 APE9

VIF 4.12 4.45 4.22 4.32 4.47 4.30 4.32 4.50 4.35 4.30 4.29 S.D. .537 .554 .617 .578 .552 .566 .628 .589 .574 .568 .565

WEA3 1.000 .548** .622** .678** .635** .767** .791** .666** .693** .656** .668**

APE1 1.000 .612** .653** .670** .608** .560** .601** .597** .537** .596** 2.274

APE2 1.000 .740** .616** .595** .640** .533** .590** .451** .598** 2.597

APE3 1.000 .752** .733** .706** .690** .679** .605** .752** 4.386

APE4 1.000 .681** .700** .720** .720** .522** .636** 3.726

APE5 1.000 .830** .691** .741** .627** .678** 4.230

APE6 1.000 .719** .706** .609** .664** 4.163

APE7 1.000 .684** .728** .668** 3.517

APE8 1.000 .718** .702** 3.646

APE9 1.000 .696** 3.181

APE10 1.000 3.102 ** 0.01

Multicollinearity

0.548 – 0.791

(WEA3) 4.173

t Sig.

0.354 0.143 2.478 0.014* -0.032 0.041 -0.033 -0.776 0.438

0.123 0.039 0.141 3.146 0.002** -0.017 0.054 -0.018 -0.310 0.757

0.024 0.052 0.025 0.466 0.642 0.214 0.054 0.226 3.941 0.000**

0.298 0.049 0.349 6.133 0.000** -0.004 0.048 -0.004 -0.081 0.936

0.031 0.050 0.033 0.626 0.531

0.176 0.047 0.187 3.752 0.000**

0.062 0.047 0.065 1.319 0.188

* 0.05 ** 0.01

4.173 (WEA3) 0.01

(Sig. F = 0.000)

WEA3 = 0.354 – 0.032 APE1 + 0.123 APE2 – 0.017 APE3 + 0.024 APE4 + 0.214 APE5 + 0.298 APE6 – 0.004 APE7 + 0.031 APE8 + 0.176 APE9 + 0.062 APE10

(WEA3) (APE6)

(WEA3) (APE5)

(WEA3), (APE1)

(WEA3), (APE8) (APE4)

(WEA3), (APE3) (APE7) (WEA3)

(WEA3) (APE2)

(WEA3) 0.01 2, 5, 6 9

(APE1) (APE3) (APE4) (APE7) (APE8)

(APE10) (WEA3)

1, 3, 4, 7, 8 10 (APE2)

(WEA3) 4.174

t Sig.

0.373 0.132 2.833 0.005** 0.128 0.032 0.147 4.024 0.000**

0.227 0.049 0.240 4.595 0.000** 0.313 0.046 0.366 6.844 0.000**

0.204 0.035 0.215 5.897 0.000**

** 0.01

4.174 (WEA3) 0.01

(Sig. F = 0.000)

WEA3 = 0.373 + 0.128 APE2 + 0.227 APE5 + 0.313 APE6 + 0.204 APE9

4.163 – 4.174

1. ** 2. ** ** ** 3. 4. 5. ** * 6. ** ** ** 7. 8. ** 9.

** * ** **

* 0.05 ** 0.01

0.01 1 9

0.01 2, 6, 8 9

0.01 2, 5, 6 9

4.6 10

4.6.1 1)

4.6.2 1)

4.6.3 1)

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¡“μ√“ ˜ı „π√–À«à“ß∑’Ë ¿“«‘™“™’æ∫—≠™’¬—ß¡’ ¡“™‘°‰¡à∂÷ßÀâ“√âÕ¬§π „Àâ§≥–°√√¡°“√°”°—∫¥Ÿ·≈°“√ª√–°Õ∫«‘™“™’æ∫—≠™’∑”Àπâ“∑’Ë ¿“«‘™“™’æ∫—≠™’‡æ◊ËÕÕπÿ¡—μ‘À√◊Õ„Àâ§«“¡‡ÀÁπ™Õ∫¢âÕ∫—ß§—∫¢Õß ¿“«‘™“™’æ∫—≠™’

¡“μ√“ ˜ˆ „Àâ∫√√¥“°Æ°√–∑√«ß ¢âÕ∫—ß§—∫ À√◊Õª√–°“»∑’ËÕÕ°μ“¡æ√–√“™∫—≠≠—μ‘ºŸâ Õ∫∫—≠™’æ.». Úıı ¡’º≈„™â∫—ß§—∫μàÕ‰ª®π°«à“®–¡’°Æ°√–∑√«ß ¢âÕ∫—ß§—∫ À√◊Õª√–°“»μ“¡æ√–√“™∫—≠≠—μ‘π’È„π‡√◊ËÕß‡¥’¬«°—πÕÕ°„™â∫—ß§—∫

„π°√≥’∑’Ë¡’ªí≠À“‰¡àÕ“®ªØ‘∫—μ‘μ“¡°Æ°√–∑√«ß ¢âÕ∫—ß§—∫ À√◊Õª√–°“»∑’ËÕÕ°μ“¡æ√–√“™∫—≠≠—μ‘ºŸâ Õ∫∫—≠™’ æ.». Úıı ‰¥â„π‡√◊ËÕß„¥ „Àâ§≥–°√√¡°“√°”°—∫¥Ÿ·≈°“√ª√–°Õ∫«‘™“™’æ∫—≠™’°”Àπ¥«‘∏’ªØ‘∫—μ‘À√◊Õ¬°‡«âπ°“√ªØ‘∫—μ‘„π‡√◊ËÕßπ—Èπ¢÷Èπ‡ªìπ°“√‡©æ“–À√◊Õ‡ªìπ°“√∑—Ë«‰ª‰¥â

¡“μ√“ ˜˜ „π«“√–‡√‘Ë¡·√°∑’Ë¬—ß¡‘‰¥â¡’°“√°”Àπ¥¡“μ√∞“π°“√∫—≠™’μ“¡æ√–√“™∫—≠≠—μ‘π’È§≥–°√√¡°“√°”°—∫¥Ÿ·≈°“√ª√–°Õ∫«‘™“™’æ∫—≠™’®–°”Àπ¥„Àâ„™â¡“μ√∞“π°“√∫—≠™’∑’Ë ¡“§¡π—°∫—≠™’·≈–ºŸâ Õ∫∫—≠™’√—∫Õπÿ≠“μ·Ààßª√–‡∑»‰∑¬‰¥â°”Àπ¥¢÷Èπ·≈–„™â°—π·æ√àÀ≈“¬Õ¬Ÿà·≈â«°àÕπ«—π∑’Ëæ√–√“™∫—≠≠—μ‘π’È„™â∫—ß§—∫‡ªìπ¡“μ√∞“π°“√∫—≠™’μ“¡æ√–√“™∫—≠≠—μ‘π’È‰ªæ≈“ß°àÕπ°Á‰¥â

¡“μ√“ ˜¯ π‘μ‘∫ÿ§§≈„¥„Àâ∫√‘°“√°“√ Õ∫∫—≠™’À√◊Õ°“√∑”∫—≠™’Õ¬Ÿà·≈â«°àÕπ«—π∑’Ëæ√–√“™∫—≠≠—μ‘π’È„™â∫—ß§—∫ „Àâ¬◊Ëπ¢Õ®¥∑–‡∫’¬πμàÕ ¿“«‘™“™’æ∫—≠™’¿“¬„πÀπ÷Ëßªïπ—∫·μà«—π∑’Ëæ√–√“™∫—≠≠—μ‘π’È„™â∫—ß§—∫μ“¡‡ß◊ËÕπ‰¢ ¥—ßμàÕ‰ªπ’È

(Ò) π‘μ‘∫ÿ§§≈π—ÈπμâÕß®—¥„Àâ¡’À≈—°ª√–°—πμ“¡¡“μ√“ ÒÒ (Ò) „Àâ§√∫∂â«π¿“¬„π√–¬–‡«≈“μ“¡∑’Ë°”Àπ¥„π°Æ°√–∑√«ß´÷ËßμâÕß‰¡à‡°‘π°«à“ “¡ªï

(Ú) ¥”‡π‘π°“√„Àâ∂Ÿ°μâÕßμ“¡¡“μ√“ ÒÒ (Ú) „Àâ§√∫∂â«π¿“¬„π “¡ªïπ—∫·μà«—π∑’Ëæ√–√“™∫—≠≠—μ‘π’È„™â∫—ß§—∫

ºŸâ√—∫ πÕßæ√–∫√¡√“™‚Õß°“√æ—πμ”√«®‚∑ ∑—°…‘≥ ™‘π«—μ√

π“¬°√—∞¡πμ√’

À¡“¬‡Àμÿ :- ‡Àμÿº≈„π°“√ª√–°“»„™âæ√–√“™∫—≠≠—μ‘©∫—∫π’È §◊Õ ‡π◊ËÕß®“°„πªí®®ÿ∫—ππ’È°“√ª√–°Õ∫«‘™“™’æ∫—≠™’‰¥â¢¬“¬§√Õ∫§≈ÿ¡ÕÕ°‰ªÀ≈“¬¥â“π‰¡à«à“°“√∑”∫—≠™’ °“√ Õ∫∫—≠™’ °“√∫—≠™’∫√‘À“√ °“√«“ß√–∫∫∫—≠™’ °“√∫—≠™’¿“…’Õ“°√°“√»÷°…“·≈–‡∑§‚π‚≈¬’°“√∫—≠™’ À√◊Õ∫√‘°“√¥â“πÕ◊Ëπ ÷Ëß¡’§«“¡‡°’Ë¬«¢âÕß —¡æ—π∏å°—∫°‘®°√√¡„π∑“ß∏ÿ√°‘®μà“ßÊÕ¬à“ß°«â“ß¢«“ß ¡§«√ àß‡ √‘¡„ÀâºŸâª√–°Õ∫«‘™“™’æ∫—≠™’Õ¬Ÿà¿“¬„μâ°“√¥Ÿ·≈¢Õß ¿“«‘™“™’æ‡¥’¬«°—π‡æ◊ËÕ‡ªìπ»Ÿπ¬å√«¡·≈– àß‡ √‘¡§«“¡‡ªìπªñ°·ºàπ√«¡∑—Èß„Àâ§«“¡√Ÿâ·≈–æ—≤π“ àß‡ √‘¡¡“μ√∞“π°“√ª√–°Õ∫«‘™“™’æ ‡æ◊ËÕ„ÀâºŸâª√–°Õ∫«‘™“™’æ¡’§ÿ≥¿“æ·≈–¡“μ√∞“π·≈–¡’§«“¡°â“«Àπâ“„π«‘™“™’æ μ≈Õ¥®π‡æ◊ËÕ„Àâ¡’°“√§«∫§ÿ¡®√√¬“∫√√≥°“√ª√–°Õ∫«‘™“™’æ®÷ß®”‡ªìπμâÕßμ√“æ√–√“™∫—≠≠—μ‘π’È

( 19) . .2553

( ) ( ) ( ) . .

“ ( )

. . ”

“ ”

“ ” ( ) ( ) / ( )

“ ” ( ) “ ”

“ ”

“ ” “ ”

“ ”

“ ” ( )

( ) ( )

. 08-1E - Mail :

1 2 3 4 5

1485-2292 chatarmorn@

://goo.gl/tCh1

@hotmail.com

http://goo.gl/tC

1.2 .....................

( )...................................................................

1.4 ( )..........................

( ).....................................................................................

1.7 ....................

1.9 10,000 10,000 15,000

15,000 20,000 20,000 25,000

25,000 30,000 30,000

1.10 / .....................

5 4 3 2 1

2.1 5 4 3 2 1

2.1.1 2.1.2 2.1.3 2.1.4 2.1.5 2.1.6

2.2 5 4 3 2 1

2.2.1 2.2.2 2.2.3 2.2.4 2.2.5 2.2.6

2.3 5 4 3 2 1

2.3.1 2.3.2 2.3.3 2.3.4 2.3.5 2.3.6 2.3.7 2.3.8

2.4 5 4 3 2 1

2.4.1 2.4.2 2.4.3 2.4.4 2.4.5

2.5 5 4 3 2 1

2.5.1 2.5.2 2.5.3 2.5.4 2.5.5

2.6 5 4 3 2 1

2.6.1 2.6.2 2.6.3 2.6.4 2.6.5

5 4 3 2 1

3.1 5 4 3 2 1

3.1.1 3.1.2 3.1.3

3.2 5 4 3 2 1

3.2.1 3.2.2 3.2.3

3.3 5 4 3 2 1

3.3.1 3.3.2 3.3.3 3.3.4 3.3.5 3.3.6

3.4 5 4 3 2 1

3.4.2 3.4.3

3.5 5 4 3 2 1

3.5.1 3.5.2 3.5.3 3.5.4 3.5.5 3.5.6 3.5.7

3.6 5 4 3 2 1

3.6.3 3.6.4

3.7 5 4 3 2 1

3.8 5 4 3 2 1

3.8.2 3.8.3

5 4 3 2 1

3.9.1 3.9.2 3.9.3 3.9.4 3.9.5

3.10 5 4 3 2 1

3.10.1 3.10.2 3.10.3 3.10.4 3.10.5

3.10.6

3.10.7

5 4 3 2 1

4.1 5 4 3 2 1

4.1.2 4.1.3 4.1.4

4.2 5 4 3 2 1

4.2.1 4.2.2 4.2.3

4.3 5 4 3 2 1

4.3.2 4.3.3

4.3.4 4.3.5 4.3.6

4.3.9 4.3.10

......................................................................................................................................................................... ......................................................................................................................................................................... ......................................................................................................................................................................... ......................................................................................................................................................................... ......................................................................................................................................................................... 5.2

......................................................................................................................................................................... ......................................................................................................................................................................... ......................................................................................................................................................................... ......................................................................................................................................................................... ......................................................................................................................................................................... 5.3

......................................................................................................................................................................... ......................................................................................................................................................................... ......................................................................................................................................................................... ......................................................................................................................................................................... .........................................................................................................................................................................

(Index of Item-Objective Congruence : IOC)

1.1 1 1 1 3 1.00

1.2 1 1 1 3 1.00

1.3 1 1 1 3 1.00

1.4 1 1 1 3 1.00

1.5 1 1 1 3 1.00

0 1 1 2 0.67

1 1 1 3 1.00

1.8 1 1 1 3 1.00

1.9 1 1 1 3 1.00

1.10 /

1 1 0 2 0.67

0 1 1 2 0.67

1 1 1 3 1.00

0 1 1 2 0.67

1 1 1 3 1.00

0 1 1 2 0.67

1 1 1 3 1.00

2.3.2 1 1 1 3 1.00

1 1 1 3 1.00

1 0 1 2 0.67

1 1 1 3 1.00

0 1 1 2 0.67

1 0 1 2 0.67

1 1 1 3 1.00

1 0 1 2 0.67

1 1 1 3 1.00

0 1 1 2 0.67

1 0 1 2 0.67

1 1 1 3 1.00

1 0 1 2 0.67

1 1 1 3 1.00

1 1 0 2 0.67

1 1 1 3 1.00

0 1 1 2 0.67

3.1.3 /

1 1 1 3 1.00

3.2.2 /

1 1 1 3 1.00

0 1 1 2 0.67

1 1 1 3 1.00

1 1 0 2 0.67

0 1 1 2 0.67

1 1 1 3 1.00

0 1 1 2 0.67

1 1 1 3 1.00

3.9.2 1 1 1 3 1.00

1 1 1 3 1.00

3.10.1

1 1 1 3 1.00

3.10.2

0 1 1 2 0.67

3.10.3

1 1 0 2 0.67

3.10.4

0 1 1 2 0.67

3.10.5

1 1 1 3 1.00

3.10.6

1 1 1 3 1.00

3.10.7

1 1 1 3 1.00

1 0 1 2 0.67

1 1 1 3 1.00

1 1 0 2 0.67

1 1 1 3 1.00

4.3.10

1 1 1 3 1.00

0 1 1 2 0.67

1 2 3 4 5 6

0.742 0.643 0.618 0.677 0.645 0.551

2. 1 2 3 4 5 6

0.409 0.757 0.752 0.728 0.600 0.651

3. 1 2 3 4 5 6 7 8

0.571 0.786 0.678 0.429 0.649 0.673 0.418 0.653

1 2 3 4 5

0.412 0.385 0.517 0.664 0.671

1 2 3 4 5

0.451 0.799 0.615 0.731 0.703

6. 1 2 3 4 5

0.495 0.749 0.775 0.748 0.638

1. 1 2 3

0.841 0.649 0.491

2. 1 2 3

0.820 0.869 0.782

3. 1 2 3 4 5 6

0.729 0.767 0.843 0.737 0.866 0.734

4. 1 2 3

0.823 0.906 0.702

5. 1 2 3 4 5 6 7

0.577 0.622 0.744 0.634 0.640 0.845 0.658

1 2 3 4

0.676 0.719 0.745 0.691

7. 1 2 3

0.713 0.633 0.488

8. 1 2 3

0.835 0.835 0.639

1 2 3 4 5

0.685 0.736 0.755 0.603 0.593

1 2 3 4 5 6 7

0.617 0.605 0.721 0.658 0.631 0.778 0.776

1. 1 2 3 4

0.394 0.602 0.602 0.663

2. 1 2 3 4

0.800 0.720 0.921 0.871

3. 1 2 3 4 5 6 7 8 9 10

0.679 0.581 0.489 0.704 0.761 0.772 0.809 0.775 0.811 0.610

17 . . 2531

. . 2547 – 2550 ( .)

. . 2550 – 2553 ( . .) ( )

. . 2554 – 2558 ( . .)

. . 2547 ( . . ) . . 2548 ( . . ) . . 2549 ( . . )

. . 2547 – 2550 .

. . 2550 – 2553 . ( . .)

. . 2554 – 2557 .

( . .)

. . 2549

. . 2553 ( ) 2

. . 2554

. . 2555 . . .

. . 2554 –

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