Quality management practices and competitive performance: Empirical evidence from Japanese manufacturing companies

1999) (6) Process management performance New Zealand – Multiple regression analysis Dow et al. Multidimensional construct Quality outcome – Questionnaire Employee commitment, shared vision, (1999) (1) Workforce commitment, (2) Shared (1) The percentage of defects at final – Data collected from and customer focus in combination has vision, (3) Customer focus, (4) Use of assembly (2) The cost of warranty 698 manufacturing a positive impact on quality outcomes. teams, (5) Personnel training, (6) Co- claims (3) The total cost of quality sites in Australia and operative supplier relations, (7) Use of (4) An assessment of the defect rate New Zealand benchmarking, (8) Use of advanced relative to competitors – Structural equation manufacturing systems, (9) Use of JIT modeling principle Das et al. Multidimensional construct: Financial performance: (1) Market share, – Questionnaire Quality practices are positively (2000) (2) ROA, (3) Market share increase – Data collected from correlated with customer satisfaction. (1) Supply chain management practices, Customer satisfaction 290 companies in US Customer satisfaction is positively (2) Quality resources and evaluation, – Structural equation correlated with firm performance. (3) Quality training, (4) Customer modeling commitment Cua et al. Multidimensional construct: Operating performance – Questionnaire The results of study indicate strong (2001) (1) Cross-functional product design, (1) Quality (2) Cost (3) Delivery – Data collected from link between quality management (2) Process management, (3) Supplier (4) Flexibility 163 manufacturing practices and operating performance. quality management, (4) Customer plants in US, UK, Italy, Integration of quality management, JIT, involvement Germany, and Japan and TPM should be adopted for better – Multiple discriminant performance analysis Matsui Multidimensional construct: Competitive performance: (1) Unit cost – Questionnaire Quality management is strongly (2002b) (1) Cleanliness and organization, of manufacturing, (2) Quality of product – Data collected from 46 influenced by certain organizational (2) Continuous improvement, conformance, (3) Delivery performance, manufacturing plants characteristics, human resource (3) Customer involvement, (4) Customer (4) Fast delivery, (5) Product mix in Japan management, information systems, satisfaction, (5) Feedback, flexibility, (6) Volume flexibility, – Canonical analysis and manufacturing strategy, and that 522 A.C. Phan et al. / Int. J. Production Economics 133 (2011) 518–529 Table 1. (continued ) (6) Maintenance, (7) Process control, (7) Inventory turnover, (8) Cycle time, it plays an important role in (7) Quality in new products, (8) Rewards (9) Speed of new product introduction, determining the competitive for quality (9) Supplier quality (10) Customer support and service, (11) performance of the manufacturing involvement, (10) Supplier quality Product capability and performance companies, partly through the impacts involvement, (11) Top management upon just-in-time production, leadership for quality, (12) TQM link information systems, and technology with customers development. Quality management depends on commitment, coordination of decision- making, task-related training for employees, small group problem solving, multi-functional employees, distinctive competence, and anticipation of new technology, among others. Kaynak Multidimensional construct (1) Financial & market performance, – Questionnaire Quality management gives positive (2003) (1) Management leadership, (2) Competitive performance, – Data collected from impact on financial and market (2) Training, (3) Employee relation, (3) Inventory performance 214 manufacturers in performance through operating (4) Quality data& report, (5) Supplier US performance. Process management quality management, (6) Process – Structural equation positively relates with quality management, (7) Product design modeling performance. Supply quality management and quality information positively relate with inventory performance Yeung Multidimensional construct: Operational Performance – Questionnaire Study indicated the chain effects on et al. (1) Top management leadership, (1) Time-based operational efficiency, – Data collected from organization performance of four (2005) (2) Cultural elements, (3) Operational (2) Customer satisfaction, (3) Cost- 225 electronics firms in quality management modules. Quality support systems, (4) Process control and related operational efficiency Hong Kong and China constructs are context dependent. In improvement Business results: (1) Financial mainland electronic industry, process performance, (2) Marketing – Path analysis management and customer focus are performance more important than other elements. Parast Multidimensional construct: Quality results – Questionnaire The study indicated the differences et al. (1) Quality leadership, (2) Quality Customer satisfaction – Data collected from between critical success factors of (2006) information analysis, (3) Strategic 250 companies in US quality management practices within planning, (4) Human resource, and 113 companies the United States and Mexico. In both (5) Quality assurance of product and in Mexico countries social responsibility and service, (6) Supplier quality (7) General – Analysis of variance supplier quality were found that matters Stepwise regression significantly explain variability of analysis quality results. Similarities on effect of quality management practices on customer focus and satisfaction were found Supplier quality involvement: This scale assesses the amount 3. Data collection and measurement analysis and type of interaction regarding quality concerns, which occurs with vendors. Data used for the subsequent analyses were gathered through the international joint research initiative called High Performance Competitiveness generally refers to the ability of a business Manufacturing Project (HPM) started in the 1980s by researchers organization to survive in a competitive marketplace by offering at the University of Minnesota and Iowa State University. The products or services that attract and satisfy customers (Fujimoto, overall target of this project is to study ‘‘best practices’’ in 2004). For manufacturing organizations, quality, cost, delivery, manufacturing plants and their impact on plant performance in flexibility, and time are recognized as the core of manufacturing the global competition. The first round of the survey was capabilities that leads to their competitiveness (Schroeder and conducted in 1989 gathering information from forty-six US Flynn, 2001). This study uses eleven competitive performance manufacturing plants. In 1992, the project was expanded to indicators to evaluate the competitiveness of each manufacturing include researchers from Germany, Italy, Japan, and the UK. The plant as: unit cost of manufacturing, conformance to product second round of the survey gathered data from one hundred and specifications, on-time delivery performance, fast delivery, flexibility forty-six manufacturing plants from those countries. In 2003, the to change product mix, flexibility to change volume, inventory project was further expanded to include other researchers from turnover, cycle time, speed of new product introduction, product Korea, Sweden, Finland, Austria, and Spain. The total number of capability and performance, and customer support and service. manufacturing plants participated in the third round of the These indicators have been widely use in HPM framework and survey is 266. Within each country, surveyed are plants with other quality management studies to measure whether imple- more than 100 employees belonging to one of three mentation of quality management practices can simultaneously industries—electrical & electronics, machinery, and automobile. improve different dimensions of competitive performance (Flynn Based on business and trade journals and financial information, et al., 1995; Cua et al., 2001; Matsui, 2002b; Kaynak, 2003). the researchers identified and selected manufacturers as having The first step of the analysis is to check the reliability and either a ‘‘World-Class Manufacturer (WCM)’’ or a ‘‘Non World- validity of each measurement scale. Hypotheses H1 and H2 are Class Manufacturer (NWCM)’’ reputation. Each manufacturing tested by using analysis of variance (ANOVA) techniques, correla- company selected one typical plant for participating in the tion analysis, and regression analysis. project. This selection criterion allowed for the construction of a A.C. Phan et al. / Int. J. Production Economics 133 (2011) 518–529 523 sample with sufficient variance to examine variables of interest acceptable alpha value of .60 for both samples collected in the for the research agenda. 1990s and the 2000s (Nunnally, 1967; Flynn et al., 1990). Most of Some of the significant results of studies conducted based on the scales have alpha value above .70 indicating that the scales this project are shown in Sakakibara et al. (1993), Flynn et al. are internally consistent. (1994) Flynn et al. (1995), Schroeder and Flynn (2001),(Matsui, Next, the validity of measurement scales is tested against 2002a,b, 2007); Phan and Matsui (2009). These results concern content and construct. with some important aspects of manufacturing plants: quality, JIT Content validity: An extensive review of the literature on the production, information systems, information technologies, and empirical study of quality management practices, production technology development, manufacturing strategy, improvement, management and organization performance is conducted to and performance. ensure content validity. This study continues the works of Flynn In this research, we acquire the data from twenty-seven et al. (1995), Schroeder and Flynn (2001), and Matsui (2002b) that Japanese manufacturing companies that are included in both developed and tested a set of measurement scales of quality two surveys in 1993–1994 and 2003–2004. Those data are management in the framework of HPM Project. extracted from the sample of forty-six companies participated Construct validity: Construct validity test is tested to ensure in the first survey during 1993–1994 and thirty-five companies that in a scale, all question items measure the same construct. participated in the second survey in 2003–2004 (in each com- Within scale factor analysis is conducted with the three criteria as pany, one typical manufacturing plant is selected to response to follows: (a) uni-dimensionality, (b) a minimum eigenvalue of 1, the survey). Twenty-seven plants belong to three industrial fields: (c) item factor loadings should be greater than .40. The results electrical & electronics (9 plants), machinery (11 plants), and show that all scales have good construct validity. Table 1 show automobile (7 plants). The first data gathered from survey in that the eigenvalue of the first factor is all more than 2.00 for each 1993–1994 reflects the degree of use of quality management in scale. The factor loading for each item (shown in the appendix) is Japanese plants during the 1990s. The second data gathered from more than .40, mostly ranged between .70 and .90 indicating the the latest survey in 2003–2004 illustrates the situation of quality high validity of the measurement scales. management in the 2000s. In both periods, the implementation of quality management practices is evaluated by fifteen and sixteen individuals in the same 4. Hypotheses testing nine positions from managers to direct labor for each period as summarized in Table 2. The measurement scales are constructed by In this section, we explore the time effect (the 2000s vs. the four to seven question items evaluated on a seven-point Likert scale 1990s) upon quality management practices and its relationship (1¼strongly disagree, 4¼neither agree nor disagree, 7¼strongly with competitive performance in Japanese manufacturing plants. agree). Individual question items are shown in the appendix. Finally, The description of each quality management practice in both eleven competitive performance indicators are judged by the periods is presented in Table 3. It is observed that top management plant manager. Each plant manager is asked to indicate his/her leadership and formal strategic planning are the most important opinion about how the plant compares to its competitors in the aspects in both periods. The less important aspects can be same industry on a global basis on a five-point Likert scale (1¼poor attributed to customer involvement (the 1990s) and process control or low end of the industry, 2¼below average, 3¼average, 4¼ (the 2000s). equivalent to competitor, 5¼superior or top of the industry). In order to identify the similarity and difference in Japanese The first step of analytical process is the analysis of reliability quality management practices between two periods (the 1990s and validity which is performed to evaluate the measurement vs. the 2000s), analysis of variance (ANOVA) technique is applied properties of the individual scales. Reliability is an estimate of and the results are shown in Table 4. If we set the significant level measurement consistency. In this study, Cronbach’s alpha coeffi- at 5% as suggested in cited literature, the results indicate that cient is calculated for each scale to evaluate the reliability. Table 2 significant differences between two periods existed in four shows the alpha values for all scales exceeded the minimum practices named as customer involvement, process control, supplier Table 2 Measurement analysis of individual scales for Japanese sample. Survey respondents 1990s Data 2000s Data DLa QM PE PS SP PD HR IM PM Alpha Eigenvalues Alpha Eigenvalues (Percentage (Percentage of variance) of variance) Top management leadership 1 1 1 .79 3.19 (46) .78 3.17 (53) Formal strategic planning 1 1 1 .87 3.41 (60) .72 2.25 (56) Training 1 4 1 .77 2.67 (53) .76 2.31 (58) Small group problem solving 5(4) 1 4 .69 2.28 (46) .75 2.48 (50) Employee suggestions 5(4) 1 4 .71 2.44 (45) .80 2.61 (26) Cross-functional product 1 4 1 .71 2.19 (55) .71 2.13 (53) design Housekeeping 5(4) 1 4 .80 2.89 (58) .84 3.10 (62) Process control 5(4) 1 1 .78 2.62 (52) .87 3.26 (62) Information feedback 5(4) 1 1 .77 2.85 (47) .76 2.62 (52) Customer involvement 5(4) 1 4 .66 2.11 (43) .69 2.17 (54) Supplier quality involvement 5(4) 1 1 .69 2.17 (45) .77 2.98 (43) DL, Direct Labor; QM, Quality Manager; PE, Process Engineer; PS, Plant Superintendent; SP, Supervisor; PD, Member of Product Development Team; HR, Human Resource Manager; IM, Inventory Manager; PM, Production Manager a The number of the direct labor answering the questionnaire is different between surveys in the 1990s and the 2000s. The figure in parentheses shows the number of the direct labor answering the questionnaire in the 2000s. 524 A.C. Phan et al. / Int. J. Production Economics 133 (2011) 518–529 Table 3 Quality management practices in Japanese manufacturing companies between 1990s and 2000s. Quality management practices 1990s 2000s Paired differences t Sig. (2-tailed) Mean Std. Mean Std. Mean Std. Std. error 95% Confidence difference mean interval of the difference Lower Upper Top management leadership 5.621 .551 5.562 .519 .059 .566 .109 .165 .283 .544 .591 Formal strategic planning 5.519 .873 5.297 .617 .222 .803 .154 .096 .539 1.436 .163 Training 4.877 .655 4.797 .564 .081 .693 .133 .194 .355 .604 .551 Small group problem solving 5.126 .467 4.797 .564 .330 .513 .099 .127 .533 3.337 .003 Employee suggestions 5.311 .530 5.189 .454 .122 .644 .124 .133 .377 .986 .333 Cross-functional design 4.950 .667 4.991 .652 .040 .700 .135 .317 .237 .299 .767 Housekeeping 5.232 .723 5.234 .551 .003 .687 .132 .275 .269 .022 .982 Process control 5.062 .546 4.570 .692 .492 .661 .127 .231 .754 3,869 .001 Information feedback 4.881 .671 4.764 .634 .117 .598 .115 .120 .353 1.015 .320 Customer involvement 4.687 .543 5.108 .393 .421 .619 .119 .666 .176 3.529 .002 Supplier quality involvement 5.218 .513 4.852 .372 .367 .610 .117 .125 .608 3.125 .004 Table 4 Competitive performance in Japanese manufacturing companies between 1990s and 2000s. Quality management practices 1990s 2000s Paired differences t Sig. (2-tailed) Mean Std. Mean Std. Mean Std. Std. error 95% Confidence mean interval of the difference Lower Upper Unit cost of manufacturing 3.407 1.047 3.192 .939 .269 .874 .171 .622 .084 1.570 .129 Conformance to product specifications 4.222 .751 4.115 .588 .115 .952 .187 .500 .269 .618 .542 On-time delivery performance 3.963 .706 3.769 .815 .231 1.142 .224 .692 .231 1.030 .313 Fast delivery 3.704 .993 3.692 .884 .077 1.230 .241 .574 .420 .319 .753 Flexibility to change product mix 3.778 .801 3.640 .995 .120 1.166 .233 .601 .361 .514 .612 Flexibility to change volume 3.704 .669 3.846 .881 .154 1.120 .220 .299 .606 .700 .490 Inventory turnover 3.185 .962 3.346 .936 .154 1.223 .240 .340 .648 .642 .527 Cycle time 3.444 .974 3.654 .797 .192 1.234 .242 .306 .691 .795 .434 Speed of new product introduction 3.481 1.087 3.577 1.137 .115 1.243 .244 .387 .618 .473 .640 Product capability and performance 4.333 .679 4.000 .800 .346 1.056 .207 .773 .080 1.671 .107 Customer support and service 3.778 .801 3.615 .941 .192 1.234 .242 .691 .306 .795 .434 quality involvement, and small group problem solving. Among them, We further test primary relations between individual quality only customer involvement shows higher score in the 2000s while management practices and performance indicator by conducting the last three exhibits lower scores in the 2000s comparing with simple correlation analysis for two samples. The binary correlation the 1990s. The largest difference between two periods occurs on coefficients between eleven practices and eleven performance indi- process control that becomes less important in the 2000s. Custo- cators are presented in Table 4. It appears that quality practices are mer involvement, which exhibits the lowest score in the 1990s, significantly associated with every performance measure in both becomes more important in the 2000s, just behind top manage- periods if we set the significant level at 5%. The number of significant ment leadership, formal strategic planning, and housekeeping. Other pair could be used to evaluate the relationship between practices seven practices appear similarly between two periods: training, and performance indicators. In the 1990s sample; top management top management leadership, formal strategic planning, employee leadership, training, formal strategic planning, small problem group suggestions, cross-functional product design, housekeeping, and solving,andprocess control are the most influential factors to information feedback. This indicates that Hypothesis H1 could performance. In other side, speed of new product introduction, product not be rejected and we could state that our analysis could not capability and performance, cycle time, manufacturing unit cost, and prove any difference on practicing quality management in the conformance to product specifications are strongly connected to Japanese manufacturing plants. quality practices. In contrast, housekeeping, employee suggestions, Next, we examine the linkage between Japanese quality on-time delivery,andflexibility to change product mix have few management practices and competitive performance. As depicted significant pair with performance. In the 2000s sample; small in Table 4, the competitive performance of Japanese manufactur- problem group solving, employee suggestion, information feedback, ing companies is evaluated similar way between two periods. and training have strong connection to performance while flexibility Japanese managers highly evaluate their product quality in terms to change volume, manufacturing unit cost, speed of new product of both conformance to product specifications and product capability introduction,andcustomer support and service have strong connection and performance. In contrast, manufacturing unit cost and inventory to quality practices. In contrast, fast delivery, product capability and turnover lay in the bottom. Pair-sample t-test is conducted and we performance, and flexibility to change product mix have only few could not find out any significant difference between two periods significant pairs with performance. Comparing the correlation coeffi- (the significant level is 5%). cient between two periods, we can obtain mixed result. The number A.C. Phan et al. / Int. J. Production Economics 133 (2011) 518–529 525 of significant pair in the 2000s exhibits rather higher than the clearly exhibits higher mean value than the low performance number in the 1990s (75 vs. 67). Some practices like employee group for every quality practices. In detail, the results of F-test suggestion, housekeeping, small problem group solving, and information clearly indicate the significant difference existed in quality feedback become more correlated with performance indicators while practices of the 1990s sample excluding employee suggestion and other practices such as top management leadership, formal strategic information feedback which own marginal difference only. For the planning,andtraining slightly become less correlated with perfor- 2000s sample, the differences between two groups appear clearly mance indicators. We find the same phenomenon occurred with in five practices: small group problem solving, employee suggestion, performance where some indicators significantly become more cross-functional product design, housekeeping, and process control. correlated with quality practices such as on-time delivery, flexibility In addition, the marginal difference between two groups exhibit to change volume, and customer support and service while product in other four practices: top management leadership, training, capability and performance become no longer significantly correlated information feedback, and customer involvement. There is no with any quality practices. In summary, the correlation analysis significant difference between two groups for formal strategic indicates that quality practices significantly correlate with a large planning and supplier quality involvement even though the mean portion of competitive performance indicators Table 5. value of the high performance group is higher than the lower To test Hypothesis H2 formally, further ANOVA analysis is performance group. The results of correlation analysis and conducted. Japanese companies are spitted into two sub-groups ANOVA analysis indicate Hypothesis H2 could not be rejected depending on their competitive performance, which is delivered and we could state that our analysis could not prove any by summing-up the individual performance indicators for each difference in the relationship of quality management practices period: the high performance group (above average score) and and competitive performance in Japanese manufacturing plants. low performance group (under average score). The numbers of companies classified into high performance group are 14 and 13 in the 1990s and the 2000s, respectively, while the numbers of 5. Implications and discussions companies in the low performance group are 13 and 14. Table 6 presents the mean value of each quality practices by two groups The previous sections presented the results of an empirical and the results of F-test. In general, the high performance group analysis on relationship between quality management and Table 5 Correlation analysis of quality management and competitive performance in Japanese manufacturing companies. Constructs 1990s 2000s (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) Top management .242 .488 .224 .339 .443 .370 .335 .337 .433 .490 .437 .394 .360 .159 .070 .169 .428 .594 .410 .637 .229 .299 leadership Formal strategic .323 .204 .323 .501 .171 .038 .482 .505 .516 .357 .149 .273 .098 .311 .134 .479 .464 .338 .246 .285 .071 .405 planning Training .444 .441 .334 .146 .322 .209 .504 .595 .719 .552 .353 .593 .381 .182 .045 .213 .504 .365 .404 .589 .140 .399 Small group problem .592 .346 .283 .211 .237 .354 .480 .684 .583 .327 .150 .508 .415 .360 .243 .464 .616 .573 .601 .653 .277 .574 solving Employee suggestions .287 .142 .012 .054 .217 .116 .216 .393 .497 .283 .033 .456 .371 .457 .418 .235 .599 .192 .339 .419 .113 .513 Cross-functional .375 .340 .214 .278 .015 .083 .372 .395 .507 .434 .235 .441 .216 .093 .008 .360 .470 .340 .391 .623 .163 .381 product design Housekeeping .236 .206 .161 .059 .007 .123 .146 .304 .653 .483 .378 .445 .452 .381 .265 .390 .589 .157 .133 .525 .012 .510 Process control .438 .401 .284 .268 .257 .451 .201 .468 .719 .526 .411 .538 .551 .439 .293 .210 .587 .376 .299 .490 .075 .467 Information feedback .467 .136 .138 .371 .034 .260 .283 .438 .457 .334 .023 .494 .483 .479 .206 .108 .600 .447 .308 .576 .008 .382 Customer involvement .373 .486 .106 .153 .258 .429 .120 .176 .720 .514 .531 .346 .360 .363 .235 .085 .610 .237 .195 .454 .197 .474 Supplier quality .390 .652 .288 .162 .259 .291 .287 .293 .756 .621 .377 .429 .254 .350 .117 .065 .619 .298 .176 .333 .084 .298 involvement (1) Unit cost of manufacturing; (2) conformance to product specifications; (3) on-time delivery performance; (4) fast delivery; (5) flexibility to change product mix (6) Flexibility to change volume; (7) inventory turnover; (8) cycle time; (9) speed of new product introduction; (10) product capability and performance; (11) customer support and service. Table 6 Japanese quality management practices classified by high and low performance. 1990s 2000s High Low F Sig. High Low F Sig. Top management leadership 5.949 5.267 16.479 .000 5.789 5.471 3.818 .062 Formal strategic planning 5.994 5.008 12.349 .002 5.479 5.234 1.202 .284 Training 5.255 4.470 14.792 .001 5.326 4.963 3.361 .079 Small group problem solving 5.367 4.867 10.539 .003 5.169 4.516 12.704 .002 Employee suggestions 5.474 5.136 2.947 .098 5.413 4.995 6.435 .018 Cross-functional product design 5.209 4.672 5.070 .033 5.340 4.775 6.552 .017 Housekeeping 5.364 5.088 .981 .331 5.533 5.015 7.088 .014 Process control 5.319 4.785 8.295 .008 4.886 4.369 4.280 .050 Information feedback 5.105 4.639 3.573 .070 5.054 4.605 4.158 .053 Customer involvement 4.921 4.435 4.995 .017 5.265 4.947 3.891 .060 Supplier quality involvement 5.425 4.995 5.563 .026 4.947 4.793 1.109 .303 526 A.C. Phan et al. / Int. J. Production Economics 133 (2011) 518–529 competitive performance in Japanese manufacturing plants. The 2000s to produce extreme high-quality product with consumer- main findings and implications derived from a series of statistical friendly features. analyses are summarized as below. We further find the evidence of the shift in how the Japanese During the 1990s and the 2000s Japanese manufacturing com- manufacturing companies specifically utilize quality management panies explore quality management as a strategic weapon for practices to improve specific performance indicators. It is identi- improving their competitive advance. Along with other factors such fied that the determinants for high performance is moderately as information technology and manufacturing technology, quality changed in the 2000s. The influence of small group problem management can considerably explain the high performance in solving, employee suggestion, information feedback, and training is terms of conformance quality, manufacturing cost, dependability, significantly increased. This indicates that quality management flexibility, time, and customer service. During the 1990s and the information became more critical for achieving high competitive 2000s Japanese manufacturers maintain a consistent structure of performance during 2000s than before. Other important finding is quality management system which characterized by top manage- the change of determinants for design quality. By the time, ment leadership for quality, close customer relationship; sharp focus product capability and performance become less dependent on on process management, employees’ training and participation, and quality management practices at plant level. It indicates that information feedback. This allows the Japanese manufacturing Japanese high design quality may be defined by other factors than maintain the competitive position in the global market as illustrated common quality management practices used in this study. They in Fig. 2, where we can observe that the level of competitive might be high technology, advanced manufacturing methods, or performance appears in similar pattern in both periods. Quality Six Sigma-oriented techniques. performance (both conformance and design quality), delivery, The relationship between quality practices and performance is flexibility are rated in high in both periods while the bottoms are illustrated in more detail in Fig. 3 that shows the level of eleven two indicators concerning with manufacturing cost and inventory quality management practices for two groups based on their which can be evaluated internally only. These indicate the confident overall competitive performance. As shown in this figure, a of Japanese managers about their quality performance while man- similar pattern occurs in both groups in each period with parallel ufacturing cost and inventory remain as serious concerns for distance between the groups in term of implementation level of them. The stability of Japanese quality management practices and the practices. This indicates the positive inter-relationship quality performance over the time can be explained by the fact between quality management practices where the higher level that quality management concepts are deeply instilled into people of implementation of one practice is achieved through mutual in most Japanese manufacturing companies regardless of their supportive relationship among practices. Naming this as ‘‘levered products and processes. The superior performance is achieved linkage’’, Morita et al. (2001) discusses that one of the most by long-term efforts involving several strategic and human factors: important characteristics of successful Japanese manufactures is company-wide participation, emphasis on employees training, their ability to create a ‘‘levered linkage structure’’ through the quality circles, quality diagnoses, statistical methods, and national- communication network. The ‘‘communication and action’’ pro- wide campaign which could not be easily graded down in a cess is viewed as an underlying force that made Japanese quality decade. management so successful. An empirical evidence to support this So, what have been considerably changed between the 1990s argument is found in our study. Our finding is that competitive and the 2000s? A few practices become more or less important performance becomes more dependent on the shop-floor com- over the time. For example, Japanese plants turn to more focused munication and information sharing (employee suggestion, small on how to satisfy the customer by managing closed relationship group problem solving, and information feedback) in the 2000s, with customers and improving the responsiveness to customer’s while Japanese manufacturing companies maintain their focus on requirements. Japanese market is uniquely characterized by the the cross-functional communication and information sharing strong demand of Japanese consumers on quality and refinement. (cross-functional design, customer involvement, and supplier quality The concept of ‘‘economical defective rate’’ is not allowed in involvement). The effective communication and information shar- Japanese plants. This explains the reason why the Japanese ing improve the effectiveness of statistical process control, allow manufacturers have increased their attention on involving the people to share and capture necessary information, and lead to customers in their product quality improvement programs in the the behaviors that continuously improve the competitiveness of 5 4.5 4 3.5 3 2.5 Competitive Performance in 1990's 2 Competitive Performance in 2000's 1.5 1 0.5 0 1 234567891011 Fig. 2. Competitive performance in Japanese manufacturing companies between the 1990s and 2000s. 1: Unit cost of manufacturing 2: Conformance to product specifications 3: On time delivery performance 4: Fast delivery 5: Flexibility to change product mix 6: Flexibility to change volume 7: Inventory turnover 8: Cycle time 9: Speed of new product introduction 10: Product capability and performance 11: Customer support and service Note: Vertical axis shows the level of competitive performance on a five-point Likert scale (1¼Poor or low end of the industry, 2¼Below average, 3¼Average, 4¼Equivalent to competitor, 5¼Superior or top of the industry). A.C. Phan et al. / Int. J. Production Economics 133 (2011) 518–529 527 7 6 5 4 High Performance in 1990's 3 Low Performance in 1990's 2 1 0 1 234 567891011 7 6 5 4 High Performance in 2000's 3 Low Performance in 2000's 2 1 0 1 234567891011 Fig. 3. Quality management practices in Japanese manufacturing companies between the 1990s and 2000s classified by high and low performance. 1: Top management leadership 2: Formal strategic planning 3: Training 4: Small group problem solving 5: Employee’s suggestions 6: Cross-functional product design 7: Housekeeping 8: Process control 9: Information feedback 10: Customer involvement 11: Supplier quality involvement Note: Vertical axis shows the degree of implementation of quality management practices on a seven-point Likert scale (1¼Strongly disagree, 4¼Neither agree nor disagree, 7¼Strongly agree). manufacturing companies. From this analysis, researchers and and cost performance? What are determinants for Japanese high practitioners can recognize the toughness of competition in design quality? Future study should develop new measurement Japanese market where the manufacturing organizations must construct to capture current situations and new trends of Japanese compete in every aspect of manufacturing management in order quality management beside the existing eleven scales used in to survive competitively. Beside the long term emphasizing on this study. process management, Japanese manager also seek for other breakthrough solutions (to achieve superior design quality, for 7. Conclusions example) and sometime to return to the basic techniques (good housekeeping, for example). The Japanese economy has encountered several crises during the 1990s and the 2000s. Japanese companies still face with the problems caused by the burst of the bubble economy and the fierce 6. Limitations and further research competition from other developed countries or emergent econo- mies. But it is believed that they overcome these problems success- It is important to view this study in the context of its limitations. fully because the manufacturing sector still remains competitive. As Methodologically, this study is based on the cross-sectional survey a core of Japanese production system, quality management is now data gathered via self-reported questionnaires, and individual bias in almost half-of-century old and seems built to endure. This study reporting may exist. Although we addressed the issue of common suggests the stability of most quality management practices, which method bias through the use of multiple respondents in the same have been still utilized to maintain the competitive advantage positions at the companies in both surveys, the study still heavily of Japanese manufacturing companies. Focusing on a set of eleven relies on the use of perceptual data. The other issue is small sample quality management practices, this study reveals their general size. Because of time and resources constraints, it is impossible to contribution to competitive performance in Japanese manufacturing involve more manufacturing companies into the survey. In addition, companies in both periods. In addition, the evidence of evolution on the sample is limited to three industries. These restricted the scope Japanese quality management is detected. By the time, the Japanese of the studies and the utilization of some data analysis techniques. manufacturing plants become more focused on the interaction with For example, we could not use the path analysis technique to customers and involving customers in quality improvement activ- examine interrelations among quality management and competitive ities. The influence of shop floor communication and information performance with industry effect. sharing on the competitive performance of the plants has been also To overcome these limitations, a future research should be increased. We observe that the high performance manufacturing conducted with larger size which allows the researchers to use plants give strong focuses on implementation of small group more comprehensive techniques for investigating the relationship problem solving, employee suggestions, and information feedback. among quality management practices and competitive perfor- The results of analysis indicate the linkage between quality manage- mance for specific industries, such as path analysis or structural ment practices and competitive performance in terms of on-time equation modeling. The researchers should explore both objective delivery and volume flexibility in the 2000s. The findings of this and subjective performance measures in their studies, particularly study suggest that such components of quality management as when studying a specific industry. This study indicates several leadership commitment, process management, and communication questions for future research on Japanese quality management. and information sharing should be explored to achieve high com- For example, is there any trade-off between quality performance petitive performance. 528 A.C. Phan et al. / Int. J. Production Economics 133 (2011) 518–529 Acknowledgments Employees at this plant have skills that .771 .658 are above average, in this industry The authors gratefully thank the anonymous reviewers for Our employees regularly receive training – .841 making constructive comments and suggestions for improving to improve their skills the original draft. The remaining errors must be attributed to Our employees are highly skilled, in this – Removed the authors only, nevertheless. The authors also appreciate the plant financial support for this research from the Japan Society for the Small group problem solving Promotion of Science by Grant-in-Aids for Scientific Research, During problem solving sessions, we .513 Removed Nos. 19330082 and 2008317. make an effort to get all team members’ opinions and ideas before making a decision Appendix. Question items of quality management scales Our plant forms teams to solve problems .748 .772 In the past three years, many problems .755 .627 Values show factor loading of each question item in the 1990s have been solved through small group and the 2000s samples. sessions Problem solving teams have helped .773 .783 Measurement scales 1990s 2000s improve manufacturing processes at this plant Top management leadership Employee teams are encouraged to try to .536 Removed All major department heads within the .638 .836 solve their own problems, as much as plant accept their responsibility for possible quality We don’t use problem solving teams – .846 Plant management provides personal .823 .851 much, in this plant leadership for quality products and Employee suggestion quality improvement Management takes all product and .640 .827 The top priority in evaluating plant .580 .432 process improvement suggestions management is quality performance seriously. Our top management strongly .477 .544 We are encouraged to make suggestions .783 .657 encourages employee involvement in for improving performance at this the production process plant. Our plant management creates and .692 .759 Management tells us why our .684 .705 communicates a vision focused on suggestions are implemented or not quality improvement used. Our plant management is personally .720 .831 Many useful suggestions are .596 .788 involved in quality improvement implemented at this plant projects My suggestions are never taken seriously .770 .761 Formal strategic planning around here Our plant has a formal strategic planning .783 .797 Cross-functional product design process, which results in a written Direct labor employees are involved to a .819 .652 mission, long-range goals and strategies great extent before introducing new for implementation products or making product changes Plants management is not included in the .748 - Manufacturing engineers are involved to .828 .777 formal strategic planning process. It is a great extent before the introduction concluded at higher levels in the of new products corporation There is little involvement of .535 .753 This plant has a strategic plan, which is .848 .845 manufacturing and quality people in put in writing the early design or products, before Plant management routinely reviews and .771 .589 they reach the plant updates a long-range strategic plan We work in teams, with members from a .738 .732 The plant has an informal strategy, which .822 .747 variety of areas (marketing, is not very well defined manufacturing, etc.) to introduce new The plant manager is part of the business .668 - products strategy planning process for business Housekeeping unit(s) at the plant Our plant emphasizes putting all tools .645 .669 Training and fixtures in their place Our plant has a low skill level, compare .829 - We take pride in keeping our plant neat .857 .839 with our industry and clean At this plant, some employees lack .592 - Our plant is kept clean at all times .764 .871 important skill Employees often have trouble finding the .660 .685 Our plant employees receive training and .759 .821 tools they need development in work place skills, on a Our plant is disorganized and dirty .850 .840 regular basis Process control Management at this plant believes that .677 .715 Customer requirements are thoroughly .654 - continual training and upgrading of analyzed in the new product design employee skills is important process A.C. Phan et al. / Int. J. Production Economics 133 (2011) 518–529 529 Processes in our plant are designed to be .675 .761 Management Method: preliminary empirical findings. Decision Sciences 26 ‘‘foolproof’’ (5), 637–658. Choi, T.Y., Liker, J.K., 1995. Bringing Japanese continuous improvement approaches A large percent of the processes on the Removed .840 to US manufacturing: the roles of process orientation and communications. shop floor are currently under Decision Sciences 26 (5), 589–616. statistical quality control Cua, K.O., McKone, K.E., Schroeder, R.G., 2001. Relationship between implementa- tion of TQM, JIT, and TPM and manufacturing performance. Journal of We make extensive use of statistical .739 .823 Operations Management 9 (6), 675–694. techniques to reduce variance in Das, A., Handfield, R.B., Calantone, R.J., Ghosh, S., 2000. A contingent view of processes quality management—the impact of international competition on quality. We use charts to determine whether our .654 .713 Decision Sciences 31 (3), 649–690. Dow, D., Samson, D., Ford, S., 1999. Exploding the myth: do all quality manage- manufacturing processes are in control ment practices contribute to superior quality performance? Production and We monitor our processes using .675 .884 Operations Management 8 (1), 1–27. statistical process control Flynn, B.B., Sakakibara, S., Schroeder, R.G., Bates, K.A., Flynn, E.J., 1990. Empirical research methods in operations management. Journal of Operations Manage- Information feedback ment 9 (2), 250–284. Charts showing defect rates are posted .714 .664 Flynn, B.B., Schroeder, R.G., Sakakibara, S., 1994. A framework for quality manage- on the shop floor ment research and an associated measurement instrument. Journal of Opera- tions Management 11 (4), 339–366. Charts showing schedule compliance are .752 .706 Flynn, B.B., Schroeder, R.G., Sakakibara, S., 1995. The impact of quality manage- posted on the shop floor ment practices on performance and competitive advantage. Decision Sciences Charts plotting the frequency of machine .660 .673 26 (5), 659–691. Forza, C., Flippini, R., 1998. TQM impact on quality conformance and customer breakdowns are posted on the shop satisfaction: a causal model. International Journal of Production Economics 55 floor (1), 1–20. Information on quality performance is .724 .813 Fujimoto, T., 2004. A twenty-first-century strategy for Japanese manufacturing. Japan Echo 31 (1), 20–25. readily available to employees Hayes, R.H., Wheelwright, S.C., 1984. Restoring our Competitive Edge: Competing Information on productivity is readily .529 .748 through Manufacturing. Wiley, New York. available to employees Imai, M., 1986. Kaizen: The Key to Japanese Competitive Success. Random House, My manager never comments about the .729 - New York. Kaynak, H., 2003. The relationship between total quality management practices quality of my work and their effects on firm performance. Journal of Operations Management 21 Customer involvement (4), 405–435. We frequently are in close contact with .684 .628 Kono, T., Clegg, S.R., 2001. Trends in Japanese Management. Palgrave, London. Matsui, Y., 2002a. Contribution of manufacturing departments to technology our customers development: an empirical analysis for machinery, electrical and electronics, Our customers seldom visit our plant Removed Removed and automobile plants in Japan. International Journal of Production Economics Our customers give us feedback on our .617 .720 80 (2), 185–197. Matsui, Y., 2002b. An empirical analysis of quality management in Japanese quality and delivery performance manufacturing companies. In: Proceedings of the Seventh Annual Meeting of Our customers are actively involved in .590 Removed the Asia-Pacific Decision Sciences Institute, APDSI, pp.1–18. our product design process Matsui, Y., 2007. An empirical analysis of just-in-time production in Japanese manufacturing companies. International Journal of Production Economics 108 We strive to be highly responsive to our .602 .793 (1-2), 153–164. customers’ needs Morita, M., Sakikabara, S., Matsui, Y., Sato, O., 2001. Japanese manufacturing We regularly survey our customers’ .757 .797 organization: are they still competitive. In: Schroeder, R.G., Flynn, B.B. (Eds.), High Performance Manufacturing: Global Perspectives. John Wiley & Sons, needs New York. Supplier quality involvement Nunnally, J., 1967. Psychometric Theory. McGraw Hill, New York. We strive to establish long-term .632 .609 Ohno, T., 1988. Toyota Production System: Beyond Large-Scale Production. relationships with suppliers Productivity Press, Cambridge. Parast, M.M., Adam, S.G., Jones, E.C., Rao, S.S., Raghu-Nathan, T.S., 2006. Comparing Our suppliers are actively involved in our .594 .671 quality management practices between the United States and Mexico. Quality new product development process Management Journal 13 (4), 36–49. Quality is our number one criterion in .645 .448 Phan, C.A., Matsui, Y., 2009. Effect of quality management on competitive performance in manufacturing companies: international perspective. Interna- selecting suppliers tional Journal of Productivity and Quality Management 4 (2), 153–177. We use mostly suppliers that we have Removed .683 Sakakibara, S., Flynn, B.B., Schroeder, R.G., 1993. A framework and measurement certified instrument for Just-in-Time manufacturing. Production and Operations Man- agement 2 (3), 177–194. We maintain close communication with .699 .766 Sako, M., 1999. From individual skills to organizational capability in Japan. Oxford suppliers about quality considerations Review of Economic Policy 15 (1), 114–126. and design changes Samson, D., Terziovski, M., 1999. The relationship between total quality manage- ment practices and operational performance. Journal of Operations Manage- We actively engage suppliers in our – .783 ment 17 (4), 393–409. quality improvement efforts Schroeder, R.G., Flynn, B.B., 2001. High Performance Manufacturing: Global We would select a quality supplier over – .549 Perspectives. John Wiley & Sons, New York. Schonberger, R.J., 1986. World Class Manufacturing: The Lessons of Simplicity one with a lower price Applied. Free Press, New York. Schonberger, R.J., 2007. Japanese production management: an evolution-with mixed success. Journal of Operations Management 25 (2), 403–419. Takeishi, A., 2001. Bridging inter- and intra-firm boundaries: management of References supplier involvement in automobile product development. Strategic Manage- ment Journal 22 (5), 403–433. Yeung, A.C.L., Cheng, T.C.E., Lai, K.H., 2005. An empirical model for managing Anderson, J.C., Rungtusanatham, M., Schroeder, R.G., Devaraj, S., 1995. A path quality in the electronic industry. Production and Operations Management 14 analytic model of a theory of quality management underlying the Deming (2), 189–204.