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N E W R E S EA R CH

T he s ta te o f q ua li ty i n l og is ti cs :e vi de nc e f ro m a n e me rg in g

S ou th ea st A si an n at io nM. Sadiq Sohail

College of Industrial Management,Department of Management and Marketing,

King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

Amrik S. SohalDepartment of Management, Faculty of Business and Economics,

Monash University, Melbourne, Australia, andRobert Millen

College of Business Administration, Northeastern University, Boston,Massachusetts, USA

Keywords Logistics, Quality, Total quality management, Malaysia

AbstractThe importance of the logistics function has increased dramatically at many firms ascomparative priorities have shifted from production quality to delivery and flexibility. At the sametime, however, there have been few comprehensive studies on the implementation of TQM

practices in the logistics function. This paper examines the implementation of quality managementpractices in the logistics function based on a study of 113 Malaysian firms. Findings on the extent

to which logistics quality management programs had been implemented, the element of the logisticsstrategy, the impediments and the extent of quality programs are discussed. The paper concludeswith a discussion on the implications.

IntroductionA number of studies have shown that successfully implementing quality managementpractices leads to improved performance in terms of stock price (see, for example,George, 2002) and operating results (see, for example, Hendricks and Singhal, 1997).Hence, it is not surprising that the use of quality management practices bymanufacturers and service providers has become increasingly widespread.

Many organizations began their quality improvement programs within theproduction/operations area, focusing on improving the performance of various

processes within this function. These programs were then introduced to otherfunctions in an effort to obtain similar types of results.

Along with the increase in the implementation of quality management practices inrecent decades, the attention paid to the information and material flow processes of thesupply chain or logistics has increased as well. For leading edge firms, the focus hasshifted from only internal processes to include external processes also. By managingtheir supply chains, some firms have found they can achieve greater responsivenesswith increased efficiency (see, for example, Pazmany, 2000; Lee and Whang, 2001).

The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at

w w w .em eraldinsight.com/res earchregister w w w .emeraldinsight.com/0 2 6 5 -6 7 1 X .htm

Quality inlogistics

397

Received June 2002Revised May 2003

International Journal of Quality &Reliability Management

Vol. 21 No. 4, 2004pp. 397-411

q Emerald Group Publishing Limited0265-671X

DOI 10.1108/02656710410530091
http://www.emeraldinsight.com/researchregisterhttp://www.emeraldinsight.com/0265-671X.htmhttp://www.emeraldinsight.com/0265-671X.htmhttp://www.emeraldinsight.com/0265-671X.htmhttp://www.emeraldinsight.com/0265-671X.htmhttp://www.emeraldinsight.com/0265-671X.htmhttp://www.emeraldinsight.com/0265-671X.htmhttp://www.emeraldinsight.com/researchregisterhttp://www.emeraldinsight.com/researchregisterhttp://www.emeraldinsight.com/researchregister


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This requires, however, an ability to effectively integrate their firms activities withthose of their suppliers and customers (see, for example, Copacino and Byrnes, 2001;Shankar, 2001).

Not surprisingly, these two fields, total quality management and logistics, have

come together, and been examined through research. For example, a limited number ofstudies have been conducted regarding the use of quality management practices insupply chain management from the perspective of senior executives. The earliest studywas conducted by the Cleveland Consulting Group (Read and Miller, 1991) whosurveyed 2,200 American and European managers. Subsequently, Millen and Maggard(1997) and Millen et al. (1999) utilized a similar questionnaire to survey seniorexecutives about such practices in the 500 largest American and 500 largest Australianfirms, respectively. Surveys of non-senior managers have also been conducted ofvarious groups (Institute for Supply Management (Tan, 2002), American Society ofTransportation and Logistics (Tan and Wisner, 2001), and American Society forQuality (Tan et al., 1999)).

In total, these previous studies provide evidence of the application of qualitymanagement practices in logistics, and their positive impact when applied effectively.However, all of this research has been conducted in the context of highly developednations. Developing nations have not fully realized the importance of logistics, andactivities relating to cost and efficiency improvements have not been properly analyzedand co-coordinated (Ulengin and Uray, 1999). With developing nations becomingincreasingly important due to their geopolitical status, lower labor costs, and potentialfor growth, the utility of applying quality management practices would seemimportant for improving performance.

The primary objective of this research is to extend the examination of theapplication of quality management practices to Malaysia, a developing nation.While studies of quality management practices in logistics are limited, studies of

quality or logistics in Southeast Asian countries are rare. Several studies (see, forexample, Poh and Hamid, 2001; Hazman, 2000) have i nvesti gated theimplementation of quality management practices in Malaysian organizations inan overall context. In the only study of logistics practice, Sohail and Sohal (2003)examined the extent and usage of third party logistics services in Malaysia.However, no study of which we are aware has examined the quality managementpractices in the logistics function by firms in Malaysia (or any other SoutheastAsian nation).

M a la y si a a n o v e rv i ewSince the early 1990s, Malaysia has been transforming from a commodity-basedproducing nation to being a manufacturer of industrial products that is geared

towards exports. Since the last quarter of the twentieth century, the country hasundergone a spectacular structural transformation. From a dependence onagriculture and primary commodities, it is now an export-driven economy, whichin turn is spurred by capital-intensive, knowledge-based, and high technologyindustries. In the 1990s, the economy achieved average annual growth rate of 7percent, the economic growth was broad based, driven by strong domestic demand,and reinforced by the favorable export performance. Exports and imports also wentup by four times since the beginning of the last decade to reach a total of almost

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US$150 billion by the turn of the century. The manufacturing sector has been theengine of growth of the economy. Exports of manufactured goods had made up 85percent of the total exports.

The remainder of the paper is divided into three sections. The next section describes

the research methodology and the profile of the survey respondents firms. Next thedetailed analysis of the data is presented. The paper concludes with a discussion andimplications of the findings.

R e s ea r c h m e t ho d o l o g y a n d s u r ve y r e s p on d e nt sTo determine the status of quality practices in Malaysian firms, a mail survey wasconducted. The questionnaire originally prepared by Read and Miller (1991) and Millenet al. (1999) served as a guideline in designing the survey instrument for this study.The resulting questionnaire contained a total of 24 structured questions. Responseswere measured using different scaling techniques as Likert-type scale (ten items),rank order (five), multiple choice question (four), dichotomous (three), and two

unstructured questions. The survey instrument reflected the framework presented inFigure 1 and focused on the following areas:

. existence of quality management program in the logistics function;

F i g u re 1 .The research framework

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. barriers, if any, in the reasons for not implementing quality initiatives inlogistics;

. important constructs in the definition of logistics quality management;

.

factors that contribute to the effectiveness of the logistic program;. decision making in implementation of the program;. major drivers of logistics quality management program;. the major impediments in its implementation;. organization of the program;. performance measures used to assess effectiveness;. benefits to the user firms; and. satisfaction to employees of user firm.

S a m p l e s e l e c t i on a n d a d m i n i s t ra t i o n o f s u r v ey

The target population included all Malaysian firms with significant logisticsrequirements. The database was compiled from two sources. One component of thedatabase was the 800 companies listed on the Kuala Lumpur Stock Exchange(KLSE). Financial, banking, real estate, and insurance organizations were eliminatedfrom this group as they were less likely to have significant logistics needs. Thesecond component of the database was the 2,200 member firms of the Federation ofMalaysian Manufacturers (FMM). This listing comprised 2,200 firms. While theKLSE listing comprised large firms, the database prepared from the FMM comprisedmainly medium and small sized firms. Weighted random samples were generatedfrom each of the two strata. A total of 600 firms were randomly selected in thismanner.

These firms were then contacted by telephone to obtain the name and address of thesenior personnel undertaking responsibilities for logistics operations of the company.Within one week of the telephone contact, a questionnaire with a cover letter andpre-paid reply envelope were mailed to the executives. A total of 113 questionnaireswere received in the following five-week period. This represented a response rate ofabout 19 percent, which compares favorably to response rates for other recent similarstudies (Read and Miller, 1991; Millen and Maggard, 1997; Millen et al., 1999). Analysisof the responses is presented in the next section.

ResultsProfile of respondents organizationsOf the 113 responses received, 86 firms had implemented quality programs in

logistics. Eight of the firms produce electronic products or components, 19manufactured products other than electronics, 45 provided services, and theremainder were categorized as others (primarily plantation and constructioncompanies). As for the employment characteristics of the firms, 59 of these hademployed a total of less than 200 employees, nine of them had between 200 and 400employees, and the remaining 18 firms had over 400 employees. The size of the firmsbased on number of employees is fairly representative of the population from whichthe samples were drawn.

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Implementation issuesOn the implementation of quality programs, about 70 percent of the managersreported that their firm had implemented a quality program in logistics. Amongthose firms that had not implemented a quality program in logistics, almost 40

percent planned to do so within the next three years. These results are consistentwith widely held beliefs and findings that TQM ideology has been gaining popularityin Malaysia (see, for example Agus and Hassan, 2001). Following this, the factorsthat prevented these firms from implementing a quality program in logistics wereinvestigated. The three most frequently selected reasons were lack of financialresources, no pressure to initiate, and lack of management support. These results aresimilar to those found in the Australian and US studies, which also reported thesethree as the most frequently selected reasons (Millen and Maggard, 1997; Millen et al.,1999). However, there were some variations in the ranking and percentage of firmsciting these reasons. Other reasons cited include lack of human resources, and lack oftraining.

Drivers for implementationThe firms that had implemented quality programs in logistics were asked to identifythe factors that had served as motivations for doing so. The major drivers forimplementing a quality program in logistics were initiative from top management,declining sales and competitors quality initiatives. Comparisons with industrybenchmarks and customer dissatisfaction or complaints were also factors thatinfluenced the implementation of quality practices in logistics. The mean scores ofresponses categorized into different industries are provided in Table I. The smallstandard deviation scores indicate that there is an agreement amongst the respondentson the relative extent to which these factors serve as drivers for logistics qualitymanagement.

The mean scores for each of the drivers of quality management programs foreach of the four industry types were compared using ANOVA procedures.Significant differences were found between the industry type and each of themeasures: customer dissatisfaction, declining sales, competitors quality initiatives,and lost customers. The industry effect was not significant in the case of top

Overall mean SDMean per industry

A B C D F

Top management initiative 3.98 1.02 3.63 4.13 4.25 3.79 1.48Customer dissatisfaction/complaints 3.51 1.03 3 3.87 3.875 2.86 5.45**Comparison with industry benchmarks 3.58 0.82 3.42 3.8 3.75 3 3.67*Internal pressures 3.14 0.81 2.95 3.29 3.13 2.93 1.18Lost customers 3.5 1.27 2.42 4.13 4 2.64 14.86**Declining sales 3.81 0.83 3.53 4.07 4.25 3.14 6.73**Competitors quality initiatives 3.73 0.85 3.63 3.93 3.88 3.14 4.075**Overall logistics strategy assessment 3.52 1.01 3.32 3.62 3.75 3.36 0.55

Notes: A manufacturing, B services, C electronics and D others. Mean scores based on afive-point scale ranging from 1 no impetus to 5 major impetus. F-values are the result of aone-way ANOVA test where * and ** represent statistical significance at 0.010 and 0.001 respectively

T a b l e I .Extent to which factors

served as drivers forlogistics quality

management programs

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management initiative, internal pressures, and a strategy assessment, while someeffect was in evidence when compared with industry benchmarks. Post hoccomparisons using the Duncan test further showed that major drive for theimplementation of quality logistic program was from the electronics industry due

to customer dissatisfaction, lost customers, competitors quality initiatives, andalso comparisons with industry benchmarks. The services industry wasconsistently rated as second.

Elements in the definition of logistics quality managementRespondents were asked to select those elements that define logistics qualitymanagement. Based on a review of the literature, nine measures were identified.Respondents were asked to rank three most important measures in their definition oflogistics quality management. Table II provides the results of the findings. Overall,total support of customer needs was rated as important by 64 percent of therespondents. On-time delivery and error free transaction were the next most oftenselected items, in that order of preference.

These results are similar to the findings reported in the Australian study (Millenet al., 1999). In the Australian study, the top two elements selected by respondents wereidentical to those selected by the Malaysian managers. On the other hand, the nextmost frequently noted element by Malaysian firms was error free transactions, whichwas ranked fourth in the Australian study. There is a degree of consistency in theresponses from the Malaysian and Australian firms in choosing the elements thatdefine logistics strategy.

Areas of implementationThe logistics areas in which quality programs have been implemented were theninvestigated. The various areas were ranked on a five-point Likert-type scale ranging

from most implemented to least implemented. The mean rating of each area ispresented in Table III where higher numbers correspond to more extensiveimplementation.

As can be seen from Table III, quality practices had been most extensivelyimplemented in the area of customer service, followed by forecasting. The area thathad the least implementation of a quality program was warehousing. The standard

Elements that define logistics strategy Not important (%)Generally important (%)

1 2 3

Total support of customers needs 36.0 30.2 14.0 19.8On-time delivery 36.0 29.1 25.6 8.1Error free transaction 54.7 11.6 17.4 16.3No out of stocks 89.5 3.5 1.2 5.8No goods damaged in handing and shipping 68.6 8.1 15.1 8.1Consistency of order cycle 67.4 0.0 14.0 18.6Reliable suppliers 72.1 10.5 7.0 10.5Accurate inventory information 89.5 2.3 7.0 1.2Defined procedures and instruction 75.6 5.8 3.5 15.1

Note: 1 very important, 2 = important, 3 = quite important

T a b l e I I .Percentage ofrespondents thatidentified each alternativeas being one of the threemost important elementsthat define logisticsquality

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deviations of more than 1 indicate that there was some degree of disagreement in theimportance of its extent of implementation.

The mean scores in each of the areas for the four industry types were comparedusing ANOVA. Significant differences were found between the industry type andextent of implementation relating to the areas of inventory control, forecasting andwarehousing. Some effect of the industry type was also in evidence in the case ofproduction control and customer service. Post hoc comparisons using the Duncan testconfirmed that the most extensive implementation was mainly from the electronicsindustry. Overall, the manufacturing industry was rated as the next bestimplementer of quality programs, except in the area of warehousing, where it wasrated the highest.

Approach to administrationRespondent firms were asked to indicate the approach used to administer the logisticsprogram. Four alternatives were provided and respondents were asked to select thoseoptions that applied to their firm. The four alternatives were:

(1) All employees have quality project responsibilities.

(2) Specific employees have been dedicated to quality projects.

(3) Each manager has taken his/her own approach.

(4) Quality is managed through an external department.

The alternative that was selected the most was that of specific employees havingquality project responsibilities (65 percent), while all employees having quality project

was the next most selected (60 percent). Alternatives 3 and 4 from the above listfollowed with responses of 44 percent and 26 percent respectively. The administrativealternatives of specific employees having dedication to quality projects and thediffusion of quality project responsibilities amongst all employees were very positive.Other studies of quality practices have demonstrated the importance of moving theresponsibility for quality from a quality department (Terziovski et al., 1997). Theresults from the Australian study (Millen et al., 1999) are somewhat similar in terms ofthe percentage of firms reporting that specific employees have been dedicated to

Overall meanMean per industry

SD A B C D F

Purchasing 3.53 1.03 3.84 3.31 4.25 3.43 2.56

Forecasting 3.76 0.83 3.84 3.78 4.38 3.21 3.82**Production control 3.7 1.22 4.32 3.39 4 3.38 1.9*Inventory control 3.44 1.26 4.11 3.16 4 3.13 2.69***Warehousing 3.06 1.15 3.68 2.84 3.13 2.86 2.51**Transportation 3.08 1.16 3 2.98 3.25 3.43 1.4Customer service 3.92 0.92 3.47 4.2 3.63 3.79 2.12*

Notes: A manufacturing, B services, C electronics and D others. Mean scores based on afive-point scale ranging from 1 no implementation to 5 extensive implementation. F-values arethe result of a one-way ANOVA test where *, ** and *** represent statistical significance at 0.010, 0.05and 0.001 respectively

T a b l e I I I .Mean rating for each areawith respect to the extent

to which a qualityprogram had been

implemented

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quality projects as well as of all employees having some quality projectresponsibilities.

Implementation activities with external suppliers

A number of previous studies have indicated that quality management practices areoften more fully implemented in purchasing than in other logistics areas (exampleMillen and Maggard, 1997; Read and Miller, 1991). As the logistics activities interfacewith external suppliers, a question was included in this study to determine the types ofactivities and their level of implementation that firms had conducted together withtheir suppliers.

Responses from this question, which are provided in Table IV, reveal that manyfirms had identified their key suppliers and had increased co-operation with themleading to the development of a long-term relationship. Reduced new productdevelopment time and teamwork involving suppliers to improve each others workprocesses had resulted from this co-operation for many firms. The small standarddeviation scores indicate that there is consensus in the importance of the measuresbeing used to determine the extent of implementation of quality programs with thesuppliers.

ANOVA results reveal significant differences between the industry type and theactivities relating to goal of zero defects, reduced new production time, cross-functionalteams with key suppliers, and teaming with suppliers to improve work processes. Posthoc comparisons further showed that, comparatively, the electronics industry has mostextensively sought to increase co-operation and long-term relationships with keysuppliers. The goal of zero defects in implementation of quality measures has beenmost extensive in the electronics industry.

Full integration of the program

Respondents were asked to estimate the extent to which the quality managementprogram will be integrated into their logistics operations over the next five-yearperiod. A five-point scale was utilized, in which 5 represents full integration. Themean response was 4.00, an above average score, indicating a good number of therespondents expect to achieve full integration by the year 2006. Industry wise, the

Overall mean SDMean per industryA B C D F

Identified key suppliers 3.66 0.66 3.63 3.76 3.75 3.36 0.88Goal of zero defects 2.95 1 3.21 2.84 4.13 2.29 5.59**Increase co-operation and long-term relationship

with key suppliers 3.87 0.65 3.89 3.76 4.38 3.93 1.54Reduced new product development time 3.29 0.76 3 3.49 3.88 2.71 5.07**Cross-functional teams with key suppliers 3.07 0.86 3 3.09 4 2.57 03.49**Teamed with key suppliers 3.15 0.99 3.21 3.16 4 2.57 2.94*

Notes: A manufacturing, B services, C electronics and D others. Mean scores based on afive-point scale ranging from 1 no implementation to 5 extensive implementation. F-values arethe result of a one-way ANOVA test where * and ** represent statistical significance at 0.05 and 0.001respectively

T a b l e I V .Percentage ofrespondents whoindicated the extent ofimplementation withsuppliers

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electronics industry recorded a higher tendency towards full integration, with a meanof 4.88, followed by the services industry (m 3:82), and lastly manufacturing(m 3:68). The other categories recorded a mean of 4.5.

Impediments in implementationFactors that impeded the logistics program are presented in Table V. The greatestobstruction to implementing a quality program was funding availability. Lack ofavailable data and considering quality in long-term planning were ranked secondand third as impediments to implementation. This is in contrast to the findings fromthe Australian study, which reported that the two greatest obstructions to a qualityprogram in logistics were changing the corporate culture and establishing employeeownership of the quality process (Millen et al., 1999). ANOVA results indicatesignificant differences between the industry and the factors training and educatingemployees, considering quality in long-term planning and establishing a commonvision across logistics. Post hoc comparisons showed that major impediments werefaced by the electronics industry particularly in establishing a common vision acrosslogistics, as well as due to lack of availability of data. Firms in the services industryfaced major impediments in funding availability and in considering quality inlong-term planning, while being placed second in the remaining six of the eightfactors.

Performance and improvement measuresRespondents were also asked about the procedures utilized to measure qualityperformance and target setting. A quality audit by internal auditors was the mostfrequently utilized measure for quality performance. The next most popularimprovement measure was through surveys of customer expectations. Competitivebenchmarking, quality audit by customers and process-specific measures were the

other procedures used to measure quality performances.The techniques that firms use to gauge customer expectations were also

examined. The percentage of respondents that employed the various techniques ispresented in Table VI. Customer surveys and market research data were employed


Funding availability 3.64 1.18 3.78 3.76 3.5 3.14 2.40*

Changing the corporate culture 3.06 1.29 2.37 3.13 3.75 3.36 2.54*

Gaining senior executive commitment 2.85 1.43 2.63 2.82 3.13 3.07 0.289

Training and educating employees 3.17 1.29 2.42 3.16 3.38 4.14 4.49**Considering quality in long-term planning 3.27 1.2 2.26 3.62 3.38 3.43 6.13**

Lack of data availability 3.39 1.05 2.95 3.59 3.86 3.14 1.79

Establishing employee ownership of the process 2.76 1.04 2.11 2.91 3.43 2.85 2.66*

Establishing a common vision across logistics 3.19 1.18 2.68 3.11 4.14 3.64 3.68**

Notes: A = manufacturing, B = services, C = electronics and D = others. Mean scores based on afive-point scale ranging from 1 = no impediment to 5 = major impediment. F-values are the result of aone-way ANOVA test where * and ** represent statistical significance at 0.05 and 0.001 respectively

T a bl e V .Mean rating of each

factor that obstructed thequality program in

logistics

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most frequently. Published information in trade and business journals was used leastfrequently. The technique of using customer surveys has also been widely used asreported in the Australian study (Millen et al., 1999). This indicates that managers areseeking more information directly from customers rather than relying on external

sources.In addition, the methods that firms employ to measure improvements in processes

were investigated. The results of the analysis relating to the utilization of varioustechniques are provided in Table VII. Apart from the scatter diagrams and Paretocharts, at least one-third of the respondents used each of the other methods to measureimprovements. Statistical process control and flow charts were employed mostfrequently. Check sheets and cause/effect diagrams seemed to be equally important.The first three items most often utilized by Australian firms were flow charts,statistical process control, and check sheets.

Measures of effectivenessFrom a list comprising seven items, respondents were asked to indicate the importanceof each towards an effective logistics quality management program. Table VIIIprovides a list of the variables and the responses. As is evident from this table, theimportant variables for an effective logistics quality program were commitment fromtop management, an emphasis on total customer satisfaction and continuousimprovement in product and process. ANOVA analysis revealed that significantdifferences exist between the nature of the industry and three of the seven variablesexamined (see Table VIII).

Not important (%)Generally important (%)

Method 1 2 3

Flow charts 34.9 20.9 26.7 17.4Statistical process control 32.6 39.5 9.3 18.6Histograms 64.0 7.0 10.5 18.6Pareto charts 75.6 17.4 0.0 7.0Cause/effect diagrams 53.5 10.5 26.7 9.3Check sheets 53.5 5.8 26.7 14.0Scatter diagram 84.9 0.0 0.0 15.1

Note: 1 = very important; 2 = important; 3 = quite important

T a b l e V I I .Percentage ofrespondents that utilizevarious methods tomeasure improvements

Not important (%)

Generally important(%)

Techniques 1 2 3

Customer surveys 23.3 44.2 16.3 16.3Line management visits to customer sites 44.2 12.8 31.4 11.6Internal measures of repeat business 39.5 10.5 24.4 25.6Market research data 32.6 20.9 17.4 29.1Published information in trade and business journals 82.6 2.3 3.5 11.6

Note: 1 = very important, 2 = important, 3 = quite important

T a b l e V I .Percentage ofrespondents that utilizedvarious techniques toascertain customerexpectations

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Supplier-related programThe impact of supplier-related programs on performance was also examined. Thefigures presented in Table IX show that supplier-related programs in aggregate hada moderate impact (overall average mean 3.62). Customer satisfaction andproductivity were the areas where noticeable improvements were reported fromsupplier-related programs. The low standard deviation scores indicate that there isconsensus in the degree of improvement due to the implementation of qualityprograms. From the ANOVA analysis and post hoc comparisons, it is evident thatactivities with external suppliers have made a comparatively higher impact on thelogistics quality management practices of the electronics industry. This is moresignificant in the areas of improvement in new product time, increasing customersatisfaction, improving productivity performance and improving finished product

defect rates.

Performance improvement and satisfaction levelhe final area addressed was the impact of a logistics quality program on theorganizations performance and the organizations satisfaction with such a program.Respondents reported an overall degree of moderate improvements in customer


A B C D F

Improved new product time 3.17 1.09 3.63 3.04 3.38 2.57 3.03***

Improved productivity performance 3.78 0.87 4 .05 3 .8 4 3.21 2 .24**

Increased customer satisfaction 3.79 0.84 4.21 3.69 4.38 3.21 4.64***

Improved technological competitiveness 3.66 1 3.95 3.67 4 3.07 1.86*

Lower total cost per unit of product 3.6 1.02 4.21 3.71 4.13 3.21 3.33*

Improved finished product detect rate 3.3 1.05 3.95 2.98 4 3.07 3.80**

Notes: A manufacturing, B services, C electronics and D others. Mean scores based on afive-point scale ranging from 1 none to 5 extensive. F-values are the result of a one-way ANOVAtests where *, ** and *** represent statistical significance at 0.010, 0.05 and 0.001 respectively

T a b l e I X .Impact of external

suppliers


Management commitment 4.69 0.6 4.68 4.62 4.75 4.86 1.02

Emphasis on total customer satisfaction 4.49 0.86 4.79 4.36 4.25 4.64 0.93

Total employee involvement 4.31 0.92 4.53 4.4 3.75 4.07 1.4

Continuous improvement in product and process 4.49 0.72 4.74 4.58 4 4.14 2.63*

Employee accountability 4.33 0.68 4.42 4.51 3.75 3.93 3.52**

Quality teams/circles 4.16 0.87 4.21 4.24 4.25 3.71 0.94Synergy of all business components 3.87 0.92 3.89 4.01 3 3.64 2.48**

Notes: A manufacturing, B services, C electronics and D others. Mean scores based on afive-point scale ranging from 1 = no important to 5 very important. F-values are the result of aone-way ANOVA test where * and ** represent statistical significance at 0.05 and 0.001 respectively

T a b l e V I I I .Importance of variables

as composition of aneffective logistics quality

program

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satisfaction, internal communication/co-ordination, productivity, delivery quality andreliability, and information accuracy. The degree of improvements was comparativelyhigher in the case of the manufacturing industry. Table X provides an overview of thefindings.

The extent to which respondents were satisfied with various aspects of the logisticsprogram was also sought. These results are presented in Table XI. The greatest degreeof satisfaction reported was in relation to the management commitment, followed bymanagement involvement. Education and training had been the area in which therewas least satisfaction reported. Responses from Australian managers differed fromthose noted above with the order of the level of satisfaction (from most satisfied toleast) being management commitment, goals, results to date, managementinvolvement, and education and training (Millen et al., 1999). The standard deviationscores, which were consistently very low, indicate that there is consensus in thesatisfaction levels due to the implementation of quality programs. The mean scores foreach of the aspects of the program and the four industry types were compared usingANOVA. Some differences were found between the industry type and managementinvolvement, ability to meet program objectives, and education and training (seeTable XI).

D i s c us s i o n a n d i m p l i ca t i o nsFindings from this study indicate that many Malaysian firms have implementedquality programs in their logistics functions. Over 70 percent of the respondentsindicated that their firms had done so. Of those whose firms had not done so, 40 percentwere planning to implement such programs in the next three years. Besides lack offinancial resources, other reasons for not having initiated quality programs in logisticswere that there is no pressure to initiate, and a lack of management support. It appears

that firms need to focus on bringing about a change. One approach to facilitating thischange would be through the provision of training and development opportunities forsenior management in order to learn about the enhanced performance possibilities inlogistics.


A B C D F

Improved delivery quality and reliability 3.72 0.88 4.16 3.64 4 3.21 3.57**Increased customer satisfaction 4 0.74 4.42 3 .89 4.125 3.71 2.15**Reduced logistics costs 3.01 0.76 3.26 2.64 3.75 3.43 6.90***Reduced transactions costs 3.22 0.88 3.26 3.11 4 3.07 1.80*

Improved productivity 3.89 0.79 3.89 4.07 4.125 3.21 3.04***Reduced order cycle time 3.59 0.66 3.63 3.61 3.75 3.36 0.76Improved information accuracy 3.68 0.68 3.42 3.64 4.125 3.93 2.82**Improved internal communication/co-ordination 3.88 0.85 4.158 3.8 4.5 3.43 2.72**

Notes: A manufacturing, B services, C electronics and D others. Mean scores based on afive-point scale ranging from 1 no improvement to 5 extensive improvement. F-values are theresult of a one-way ANOVA test where *, ** and *** represent statistical significance at 0.010, 0.05and 0.001 respectively

T a bl e X .Percentage ofrespondents whoindicated the differentlevels of improvementsfrom the total qualitymanagement program inlogistics

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As for the elements of logistics quality, the study observed that total support of

customers needs, on-time delivery and error free transactions have been the majoritems in their definition. This is certainly a good approach, in the face of challengesbrought about in the wake of an increasing competitive environment. In addition, over80 percent of the respondents believed that it is important to have their qualityprograms fully integrated into their logistics programs in about five years time. Thisshows that the Malaysian firms see quality integration into functional areas as acrucial factor in gaining competitive advantage.

Nearly 60 percent of the executives indicated that specific employees werededicated to quality projects. More than 50 percent of the responding firms indicatedall employees had some quality project responsibilities. Given the importance ofreliable suppliers in terms of logistics quality, it is not surprising that firms had morefully implemented their quality programs in customer service versus other areas inlogistics. Customer service has been the area where the logistics program had beenextensively implemented followed by production control. Forecasting and inventorycontrol were the areas where the next greatest level of implementation had beenachieved.

Availability of funds was the greatest obstacle faced by managers. Related tothis were considering quality in long-term planning, and training and educatingemployees. Senior executive commitment and establishing employee ownership ofthe process were perceived as much lesser obstacles. Many of the firms employmultiple measures for evaluating their level of performance internally andexternally. Similarly, many firms utilize multiple means for ascertaining customerexpectations. Many of the findings are similar to those reported in the study of

Australian firms. The tools employed, the process for measuring performance, thetypes of obstacles faced, and other responses were generally similar across the twostudies. This could indicate that the level of diffusion of knowledge in this field iswidespread.

While these firms have much to be proud of in terms of their accomplishments todate, it is important that these organizations do not cease their quality efforts. Thosethat are best practice today will be less than satisfactory in the future. The onlyresponse that has proven effective over time is to improve and to do so continuously.

Aspects of logistics quality program Overall mean SDMean per industry

A B C D F

Goals 3.44 0.61 3.42 3.47 3.75 3.21 1.6

Education and training 3.14 0.84 2.74 2.6 2.88 3.29 2.13**

Management commitment 3.52 0.7 3.16 3.73 3.38 3.43 2.37**

Management involvement 3.5 0.65 3.16 3.67 3.38 3.5 2.25**

Results to date 3.34 0.52 3.53 3.18 3.88 3.14 1.90*

Ability of program to meet objectives 3.28 0.71 3.37 3.18 3.88 3.14 2.05**

Notes: A manufacturing, B services, C electronics and D others. Mean scores based on afive-point scale ranging from 1 very dissatisfied to 5 very satisfied. F-values are the result of aone-way ANOVA test where * and ** represent statistical significance at 0.010 and 0.05 respectively

T a b l e X I .Satisfaction with the

different aspects ofquality improvement

efforts

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While the study itself reveals interesting results and broadly applicable findings, wewould like to highlight a major limitation of the study. The sample size is an apparentlimitation. Further study with the larger and more representative Malaysian samplesize is suggested to increase generalizibility.

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