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Phan Chi Anh, Yoshiki Matsui (pp 519 - 540)
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Trang 3| ‘www emeraldinsigh(comv/2040-8269.hun ‘The current isu and ful text achive of his journals available at
Relationship between quality operational QMI and
management information and performance
operational performance
International perspective
Phan Chi Anh
Faculty of Business Administration,
University of Economics and Business ~ Vietnam National University, Hanoi, Vietnam and
Faculty of Business Administration, Yokohama National Univers Yokohama, Japan, and
Yoshiki Matsui
International Graduate School of Social Sciences,
Faculty of Business Administration, Yokohama National University Yokohama, Japan 519 Abstract
Purpose - The purpose ofthis paper is to examine whether quality management information (QM) can be 2 source of competitive advantage and should be managed strategicaly
Design/methodologyfapproach ~ Analysis of variance and regression techniques were applied to the database of the high-performance manufacturing (HPM) project to analyze the differences and Similarities existing across the countries on the degree of implementation of QMI practices and their contribution to operational performance of manufacturing plants
Findings ~ The results of statistical analysis indicate significant differences in the implementation of QM practices acrss the countries This study highlights the important roe of QMI in Japanese plants ‘where shop floor and cross-functional communication and information sharing practices significantly Impact on different dimensions of operational performance,
Practical implications ~ This study suggests that HPM could be achieved by the implementation ofa set of communication and information sharing practices in shopfloor and cross-functional levels, fof manufacturing plants
Originality/value - Although scholars considered information as one dimension of quality management, existing quality management literature provides litle empirical evidence on the relationship of QMI and operational performance of manufacturing plants This paper fill the gap by Introducing a comprehensive research framework to analyze the communication and information
sharing practices in the shop-floor and cross-functional levels ¢ ) Keywords Quality management, Management information systems,
Operations and production management
Paper type Research paper Emerald
Introduction Samana Une ree
Quality management information (QMI) refers to the systematic collection and analysis
of data in a problem-solving cycle to identify critical problems, find their root causes, € 23/0 and generate solutions to the problems Effective implementation of QMI allows the v4 osseous
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manufacturers to improve product and service quality and facilitate their suppli relationship management (Flynn ef af, 1994; Forza and Flipini, 1998; Kaynak, 2003; Morita etal, 2001; Schniederjans QMI by such international standards and awards as ISO 9000, Malcom Baldrige et al, 2006) Recently, greater attention has been paid to National Quality Award, and Japan Quality Award Although scholars considered information as one dimension of quality management, existing quality management literature provides little empirical evidence on the relationship of QMI practices and operational performance of manufacturing plants This study aims to fill this gap by responding to the following questions:
+ What are similarities and differences in the perception of QMI practices across, countries?
+ Do QMI practices positively relate to various dimensions of operational performance of manufacturing plants such as quality, cost, delivery, lexibility, etc?
‘Tobe competitive in global market, many manufacturing companies have implemented a set of practices such as total quality management (TQM), just in time UIT), and total productive maintenance (TPM) that hereafter broadly labeled as high-performance ‘manufacturing (HPM) initiatives HPM literature indicates that effective implementation of such HPM practices highly depend on how the companies manage and information flow This study examines QMI by introducing a set of communication the communication, and information sharing practices at shop-floor and cross-functional levels of manufacturing plants These practices reflect various types of communication and interaction within shop floor and between functions/departments of manufacturing plants, such as information feedback, suggestions, training, small group act ‘cross-functional product design, coordination of decision ‘between departments, etc This study utilizes survey data which have been gathered from 167 manufacturing plants in six counties during 2003-2004 in the framework of HPM project The statistical results indicate the significant difference in the perception of the QMI practices across the ‘countries Plants in the USA and Sweden show their stronger emphasis on QML practices: than other plants, particularly Korea place their higher attention on cross-functional practices than shop-fioor practic those in Japan and Italy All the countries except Japan and ‘The significant difference among countries n the effect of QMI practices on performance:
detected The connection between the QMI practices and high performance in Japanese plants appears tight, comparing with other countries These findings are consistent with the institutional theory when the institutions are taken to be the countries National culture, geographical specifics, and competitive environment may account for the differences we observe in communication and information sharing practices across the countries The linkage between QM and operational performance found in this study suggests that HPM could be obtained by implementing a set of communication and information sharing practices The remaining of this paper presents the literature and research framework, which are followed by the descriptions of data collection ‘measurement test, and hypothesis testing The last three sections discusson the important findings, the limitations of this research, and the final conclusions Literature review
Trang 5Flynn et a (1994) indicate that process management strongly depends on how process's ‘owner collect and analyze data at the source to take immediate problem-solving action, Quality performance data such as defect rate, scrap, and rework must be collected, analyzed, shared, and used for quality improvement Design quality also depends on QMI because QMI provides a wide range of data from purchasing, marketing, manufacturing, design, customers, and suppliers in order to design quality into products ‘Tosupport suppliers for improving product quality, manufacturing plants need to create a database about the suppliers’ performance regarding quality, delivery, purchasing, cost, etc so that managers and parts supplied and provide and employees can identify and solve problems the suppliers timely and important feedbacks to improve from materials their performance (Kaynak, 2003) In summary, empirical studies on quality management emphasize importance of QMI as follows:
+ timely quality measurement;
*+ feedback of quality data to employees and managers for problem solving; + evaluation of managers and employees based on quality performance: and > availability of quality data
Recently, researchers find that systematic management of information and data resource is also important tothe use of advanced quality management methods such as Six Sigma, which is itself a data-driven approach to eliminate defects and wastes in business processes Researchers agree that the execution of Six Sigma relies on the availability and accuracy of QMI because quality metrics can only be used for quality improvement when they are calculated from reliable and valid data (Zu et al, 2008) To successfully implement QMI practices, many requirements need to be satisfied as indicated from empirical literature Effective QMII directly depends on customer focus
workforce management, and top management support Workforce management is
Trang 6MRR HS 522 Figure 1 Research framework Research framework
QM improves quality performance through collecting, storing, analyzing, and reporting, information on quality to assist decision makers at al level This concept requires input from a variety of functional areas and recognized that information consists of not only data but also other knowledge needed for decision making (Juran and Gryna, 1980; Forza, 1995) Schroeder and Flynn (2001) argue that successful implementation of variety of manufacturing management practices such as TQM, JIT.and TPM depend on how the manufacturing plants develop their horizontal linkage structure throughout the communication network The “communication and action” process is one of the underlying forces that have made such practices as TQM and JIT so successful While most of quality management literature have emphasized on the importance of availability, accuracy, and timeliness of QM, this study focuses on how the ‘manufacturing plants develop QMI through facilitaxing communication and information sharing practices toachieve HPM, The flow of communication and information sharing is distinguished into two categories: shop-floor and cross-functional levels Shop-floor QMI concentrates on the collection, analysis, and feedback of quality information on the shop floor where products are created It relates with two-way communications between managers/engineers and workers and between workers themselves Conducting small ‘group activities is the means improvement In addition, along with the feedback of quality performance employee's for employees to share their ideas and expertise for quality suggestions should be formally acknowledged to encourage the employee's participation in quality improvement Cross-functional QMI, on the other hand, rel with communication and information sharing between functions/departments concerning with coordination, new product development efforts, and the interaction with customers and suppliers Communication and information sharing between different functions are important for making quality decisions especially to solve critical ‘quality problems, External communication with customers and suppliers is also crucial for quality management Close contact with customers, frequent visit to customers, atid regular customers’ survey are the best ways to capture customers’ needs and expectations while sharing information with suppliers improves their mutual trust within the supply chain The framework of this study is simply shown in Figure 1
Trang 7argue that, with the evolvement and spreading of modern technologies, benchmarking, ‘organizations may design their operational structure in similar ways in order to be efficient and effective (Form, 1979) Other scholars, however, indicate the linkage between information and national specifics (Wacker and Sprague, 1998; Snell and Hui, 2000) More recently, Flynn and Saladin (2006) point out that such component of quality management as QM would be influenced by Hofstede national culture values ‘The power distance, individualism, masculinity, and uncertainty avoidance may affect the use of information to support decision making, For example, high power distance cultures may restrict learning opportunities to high-status members and discourage ‘open access to information and information sharing between different organizational levels Members of collectivist national cultures are more likely to rely on information provided though teamwork and cross-functional collaboration Because of a lack of development of valid instruments on QMI, the results of previous QMI studies cannot be generalized The question regarding the universality of QMI and its linkage with performance has not been answered More empirical and cross-country research is needed in QMI study Then, we establish comprehensive instruments on QMI and test ‘whether country location influences the implementation of QMI practices The first hypothesis is presented as follows:
#1, There's difference in the implementation of QMI practices across the countries ‘The contribution of communication and information sharing to quality performance or supply chain performance has been identified in the existing literature (Forza, 1995; Carr and Kaynak, 2007) The use of bilateral relations, including lateral forms of ‘communication and joint decision-making processes increases information systems capacity This permits problems to be solved at the level where they occur, rather than, being referred upward in the hierarchy, increasing the capacity of the organization to, ‘process information and make decisions by increasing the discretion at lower levels of the organization (Phan and Matsui, 2000), Flynn and Flynn (1999) suggest that the use of
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all functions from the beginning of new product development project Suppliers can be regarded as an external process of the plants Collaboration with suppliers through opening and sharing information concerning quality problems and design changes would also allow the plants to improve product quality and save production cos ‘The hypothesis therefore, is presented as follows: on the relationship between QMI practices and operational performance,
H2, QMI practices positively relate to operational performance
To test the hypotheses analysis of variance (ANOVA) and regression analysis are used to compare those practices across the countries and identify whether QML significantly impact 13 operational performance indicators
Research variables
From literature reviewing, ten measurement scales are developed to examine QMI under two perspectives: shop floor and cross-functional as mentioned early Shop-floor QMT includes six measurement scales as follows:
(1) Feedback — measures whether the plant provides shop-floor personnel with information regarding their performance (including quality and productivity) in a timely and useful manner
2) Shop-floor contact - measures the level of interaction between managers, engineers, and workers, on the shop floor A high degree of interaction between management and workers is thought to promote problem solving and general improvement
@ Employee suggestions — measures employees’ perception regarding management's implementation and feedback on employee suggestions (4) Small group problem solving — evaluates how the plant uses teamwork
activities to solve quality problems,
(5) Supervisory interaction facilitation — measures whether supervisors successfully encourage workers works as team, including expressing thew ‘opinions and cooperating with each other to improve production,
(6 Multifunctional employees — determines if employees are trained in multiple tasldareas; that is, received cross-training so that they can perform multiple tasks or jobs
Cross-functional QMI includes four measurement scales as follows:
(1) Coordination of decision making ~ determines cross-functional cooperation and communication in the plants (2) Crossfunctional product design ~ measures the level about amount of input that the manufacturing function has in the new product introduction process
‘This includes cooperation and input into process across functional boundaries (8) Communication with customers assesses the level of customer contact, ‘customer orientation, and customer responsiveness (4) Communication with suppliers — assesses whether plants develop trust based relationship with suppliers by exchanging communication and sharing information
Trang 9A total of 13 measurement items are used to evaluate different dimensions of operational performance of the plants: unit cost of manufacturing, conformance to product specifications, on-time delivery performance, fast delivery, fexibility to change product mix, flexibility to change volume, inventory turnover, cycle time (from raw materials to delivery), new product development lead time, product capability and performance, on-time new product launch, product innovativeness, and customer support and service ‘Those items are summed up to form overall operational performance Because the objective of this study is to identify impacts of QMI practices on operational performance that can be generalized across countries and industries, the effects of country and industry need to be removed prior to evaluating the relationship between QMI practices and operational performance We, therefore, include the following control variables in the regression analyses Five country control variables:
USA (the USA compared to Japan), ITA (Italy compared to Japan), SWE (Sweden
compared to Japan), KOR (Korea compared to Japan), and AUT (Austria compared to, Japan) are used to represent the five countries Similarly, two industry control variables, MAC (machinery industry compared to automobile industry) and EE (electric and electronics industry compared to automobile industry), are used to represent the three
industries from which the data were collected
Data collection
This study explores data gathered through the international joint research initiative called High Performance Manufacturing (HPM) Project started in 1980s by researchers at the University of Minnesota and Iowa State University The overall target of this project is to study “best practices” in manufacturing plants and their impact on plant performance in the global competition The first round of the survey was conducted in 1989 gathering information from 46 US manufacturing plants In 1992, the project was expanded to include researchers from Germany, Italy, Japan, and the UK The second round of the survey gathered data from 146 manufacturing plants from the above countries In 2003, the project was expanded to include other researchers from Korea, Sweden, Finland, Austria, and Spain The total number of manufacturing plants participated in the third round of the survey is 210 except Spanish plants Within each country, surveyed are plants with more than 100 employees belonging to one of three
industrial fields — electrical and electronics, machinery, and transportation
‘The researchers, based on business and trade journals and financial information, identified manufacturers as having either a “worldlass manufacturer (WCM)" or “non-WCM” reputation Each manufacturer selected one typical plant for participating in the project This selection criterion allowed for the construction of a sample with sufficient variance to examine Variables of interest for the research agenda
In this research, the authors can acquire data from 167 manufacturing plants in six countries: the USA, Japan, Ttalia, Sweden, Austria, and Korea during 2003-2004, ‘The key characteristics of these plants are summarized in Table L
In each plant, the degree of implementation of QMI practices and continuous improvement and learning is evaluated by nine positions such as direct workers, supervisors, process engineer, quality manager, production control manager, inventory manager, human resource manager, plant superintendent, and a member of new product development team as summarized in Table I Ten QMI measurement scalesare constructed
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MRR 4 ~ neither agree nor disagree, and 7 ~ strongly agree) The individual question items are 345 shown in the Appendix Finally, 13 operational measures of manufacturing plants are
= judged by the plant manager Each plant manager is asked to indicate his/her opinion about
how the plant compares to its competitors in the same industry on a global basis on five-point Likert scale (1 — poor or low end of the industry,3 — average, and 5 ~ superior or
top ofthe industry)
526
Measurement analysis
‘The first step of analytical process is the analy and validity of ten ‘measurement scales and two super scales In this study, Cronbach's alpha enefficent i calculated to evaluate the reliability of each measurement scale Table Il] shows the alpha values forall of ten scales exceeded the minimum acceptable alpha value of 0.60 for pooled sample and country-wise Most of the scales have the alpha value above 0:75, indicating that the scales were internally consistent:
+ Content validity An extensive review of literature and empirical studies is undertaken about quality management and organization performance to ensure content validity,
USA Japan HA Sweden Austria Korea Toval
Electrical and electronic ° wo wo 7 W 10
Machinery no oR wb wm 7 lô
Automobile 8 Bb 7 7 4 ụ
Total Plant characteristics B BS uw a A a
Awerage market sare(%) 2550 34B 2348 HED MY Table 1 Average sale (SK) 284181 THAM 71209 58471 BEAT 228600 Demographic of Average of number of
survey respondent employee (slaried person) 1587} A6 88 12
Positions to answer questionnaire
Measurement scales PD WR DĨ IM PE QM PS PM
Feedback Shop-floor contact 1 6 11 41
Supervisory interaction facilitation 6 so
Enployee suggestions 6 aot
Multifunctional employees 1 a1
Small group problem solving 6 14
Coordination of decision making 6 mm
Cross functional product design 1 1 4
Communication with suppliers 61 144
Communication with customers 6 A -
“Table II,
Sarvey respondents
Operational performance 1
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ity is conducted to ensure thac atl question items in a scale all measure the same construct, Within-scale factor analysis is tested with the three criteria: uni-dimensionality, a minimum eigenvalue of 1, and item factor loadings in excess of 0.40, The results of measurement testing for the ‘pooled sample and country-wise show that all scales had well construct validity ‘The eigenvalue of the first factor for each scale is more than two Factor loading, for each items are more than 0.40, mostly range between 0.70 and 0.90 for the pooled sample as shown in the Appendix
Hypothesis testing
‘This section starts with the analysis of country effect existed in QMI practices, One-way ANOVA is used to identify the similarities and differences in QMI practices across the countries The last two columns of Table IV show the values of the Fstatistic and their ificant levels If we set the set significant level at 5 percent, the ANOVA test results suggest that all of QMI practices are signiticantly different across the countries except employee suggestions Next, Tukey pairwise comparison tests of mean differences are conducted to identify how QMI practice differed between cach pair of countries ‘We observe that the largest differences exist in such practices as supervisory interaction, facilitation, cross-functional product design, coordination of decision-making, communication with suppliers, and communication with customers The Japanese and US plants are quite similar in almost of the practices except multifunctional employees and communication with customers In addition, QMII practices are evaluated in similar \way in two Asian countries In general, shop-floor QMI practices are lov highest in Austriaand Korea, while cross-functional QM practicesare lowest in Japan and highest in Austria and the USA In the USA, an Italian plants, the focus of cross-functionst ‘QMI practices are appeared higher than shop-floor QMI while both of them are similar in Japanese and Korean plants It is found that the most focused practices (top practices) of (QMI practices are different between the countries: communication with customer (in the USA), multifunctional employees (in Sweden), coordination of decision malking (én Austria), shop-foor contact (in Korea), and employee suggestions (m Japan) In summary, the results of ANOVA test suggest that QMI practices vary widely by country
Each country evaluated the degree of implementation of QMI practices in different ways
National culture, geographical specifics, and competition environment and other factors
may account for the differences we observed among QMI practices adopted in different
Trang 15‘exbility to change volume, new product develop lead time, and on-time new product
launch Ín case of Japanese and pooled samples, QMI practices significantly correlate
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‘pooled sample with the corresponding model applied for six sub-samples In estimating the regression models for the sub-samples, no restrictions regression coefficients so that every coefficient can take different values for different are imposed on the val countries We can evaluate the improvement in explanatory power by dividing the pooled sample into six sub-samples and enabling regression coefficients to rake different
values by an F-test (Chow, 1960): (RSSR ~ SSSR)/k F~ aatste = eo ! where:
'RSSRis the sum of squared residuals from a linear regression of the pooled sample SSR, is the sum of squared residuals from a linear regression of sub sample ¿ i is the number of subgroup
kis number of independent variable, 2 is mumber of total observations
Table VII shows regression analysis on relationship between QMI practices and operational performance taking on pooled and country-wise sample using SQMI and CQMI as two independent variables We obtain value of F'statistic is 3654 with p-value is 0.008 If we setting significant level at 5 percent, the results of Chow test indicate the difference on determinant of operational performance across the countries, In summary, we can accept H2 and state that QMI practices significantly impact operational performance In addition, statistical results reveal that this impact widely varies the countries and the linkage between QMI and performance in Japanese
closer than others,
Discussions
Results of the present study show that the differences on QMI practices existed in manufacturing plants operating each QMI practices and their linkage with specific operational performance indicators, in different countries The degree of implementation of appear differently across the countries Although this has been previously implied in the ‘quality management literature, comparison of a comprehensive list of QMI practices, ‘among countries was lacking, We obtained the mixed results when the QMI practices, ‘were compared across six countries First, we find that all the QMI practices are significantly different across the ‘countries (except employee suggestion), The USA and three other European countries place their higher focus on cross-functional QMI practices rather than on shop-floor ‘QMI practices Plants in the USA, Austria, and Sweden show their stronger emphasis ‘on every QMI practice than other plants in Italy and Japan, Second, we find the linkage between QMI practices with different dimensions of operational performance rather than with quality performance only For example, statistical analysis reveals that QMI practices closely linked with time-based performance indicators of manufacturing plants, for example: on-time delivery (in Austria the USA, and Italy), on-time new product launch (in Korea), and new product development lead time (in Japan) Cross-functional product design is found as the most
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critical factor for these performances In general, employee suggestions, coordination of decision making, and cross-functional product are found highly associated with ‘operational performance of plants in the six countries,
“Third, the significant difference between countries in the linkage of individual QM practices on specific performance indicators is detected We observed that the ‘connection between the QMI practices and high performance in Japanese plants ‘appears tight, comparing with other countries Japanese plants with high performance highly focus on shop-floor contact, small group problem solving, and feedback The findings on significant differences across the countries are consistent with the institutional theory when the institutions are taken to be the countries, National culture, geographical specifics, and competitive environment may account for the differences that we observed in communication and information sharing practices across the countries In addition, the finding of our study highlights the Japanese quality ‘management The prosperity and survival of Japanese manufacturers are archived by their Japanese way of management such as TQM, JIT production, TPM, concurrent engineering, and their ability to create horizontal linkage structure throughout the communication network Those are the real strengths of Japanese manufacturers, besides of their technological advantages The “communication and action” process is ‘one of underlying forces that have made such practices as TQM and JIT so successful (Morita et al, 2001) For the researchers and practitioners, this study provides the evidence on how performance is associated with communication and information sharing in the plants “Managers who want to improve selected operational performance
some Valuable suggestions from the statistical analysis results
plants, high performance in term of manufacturing cost and volume flexibility relates with the implementation of such shop-floor QMI practices as feedback, shop-floor contact supervisory interaction facilitation, and employee suggestions Improvement of inventory turnover and reduction of new product development lead time would be achieved by {implementation of such cross-functional QMI practices as cross-functional product design, and communication to suppliers and communication to customers Because the quality, cost, delivery, and flexibility performances are closely correlated, benefits of QM practices sometimes have multiple effects on operational performance Regression analysis on the pooled sample shows that cross-functional QML is significant predictor fr operational performance This suggests that the emphasis on communication and information crossing the borders of functions would explain the difference on competitive
position of manufacturing plants
This study contributes to quality management literature as it refines our understanding of the nature of relationship between QMI practices and plant performance Continuing to use HPM perspective to study QMI, we provide further insight on the achievement of high performance through communication and information sharing This study introduces a comprehensive research framework to study QMI and uses the latest database to test the hypotheses Out findings are inline with previous studies on QMI using HPM perspectives such as Forza and Salvador (2001), Schroeder and Flynn (2001) and Flynn and Saladin (2006) In addition, we find that operational performance would be influenced by such QMI components as shop-floor contact or supervisory interaction facilitation, which have not been fully studied in previous works
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Limitation and future research Itis important to view this research in the context of its limitations, Methodologically, this study is based on cross-sectional survey research data It utilizes database gathered from self-reported questionnaires, and individual bias in reporting may exist Although, ‘we address the issue of common method bias through the use of multiple respondents, the study heavily relies on the use of perceptual data The other issue is sample size ‘Because time and resources constrains, the sample consist of only 167 plants belonging to three industries These restrict the scope of the studies and utilization of some data analysis techniques For example, the relative small sample size not allows the authors to use path analysis technique to examine interrelations among specific QMI practices and operational performance with industry and country effects Next the issuerelates with evaluation of operational performance The HPM collected both objective and subjective data on operational performance of manufacturing plants in all of member countries, The objective measures of operational performance on quality cost, and delivery have been collected such as “percentage of scrap and rework”, “manufacturing cost”, “percentage of onctime delivery”, etc However, because of industrial difference; these objective data on performance cannot be fully used in this, study Therefore the subjective measures are used to evaluate operational performance in this study Other studies in framework of HPM projects also encountered this issue (Fiynn et al, 1995; Ahmad et al, 2003; Matsui and Sato, 2002: Phan and Matsui, 2009) ‘Toovercome abovementioned limitations, a future research should be conducted with larger and comprehensive sample size This will allow the researchers to use comprehensive techniques for investigating relationship between management practices and performance for specific countries or specific industries, such as path analysis or structural equation modeling Researchers should explore both objective measures and subjective measures in their studies, particularly when focusing on a specific industry
Conclusions
In the previous sections, we presented the results of the empirical study on the relationship between QMI and operational performance in manufacturing plants A simple analytical framework and two hypotheses were proposed Then, based on the literature, we introduced ten measurement scales and two super scales and all of those ‘measurement scales are satisfactory in terms of reliability and validity for the dataset of 167 manufacturing plants in six countries Using these scales, we examined the country effect on QMI to explore the critical success factors of operational performance The results indicate the similarities and differences of the implementation of QMI and its impact on operational performance across countries This study suggests that manufacturing plants should develop the process and network of shop-floor and cross-functional communication and information sharing which is an underlying force that have made manufacturing management practices became successful and contribute to their competitive performance It also highlights the unique and distinguished position of Japanese manufacturers in the impact of QMI on operational performance
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Purther reading
Ahice, SL, Golkar, DY and Waller, MA (1996), ‘Development and validation of TQM implementation constructs", Decision Sciences, Vol 27 No, 1, pp 2356 Benson, P.G, Saraph,V-and Schroeder, RG, (199), "The effects of organizational ‘manajgement: an empirical investigation”, Management Science, Vol 3? No.9, context on quality pp 1107-24, Das, A., Handied, RB, Calantone, RJ and Ghosh, S 2000), “A contingent view of quality management ~ the impact of international competition on quality", Dedbion Sciences,
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Trang 22Appendix
‘The values that follow the names of scales and super-scales report the results of factor analyss (the eigenvalue and percentage of variance of the first factor) talking on the pooled sample ta ‘evaluate the validity of these scales “The values follow each question item show factor loading for this que
1 Shop floor quality information practices (3488 and 64 percent) L1 Feedback @.792 and 56 percent):
1 Charts showing defect rates are posted on the shop floor (076) 2 Charts showing schedule compliance are pasted on the shop floor (0.78) 5 Glare oti en mai baows af tel ob he se A
n item,
4 Information on quality performance is readily available to employees (078) 5 Information on productivity is readily available to employees (07 L2 Shop floor contact 220 and 44 percent)
| Managers in this plant believe in using alot of facetoface contact with shop floor exmployees (070), 2 Engineers are located near the shop floor, to provide quick
production stops (073
3 Our plant manager is seen on the shop fluor almost every day (075) 44 Managers are readily available on the shop floor when they are needed (079) 5 Manufacturing engineers are often on the shop floor to assist with production
problems (0.70),
13 Supervisory interaction facilitation (257 and 64 percent)
1 Our supervisors encourage the people who work for them to work as 2 team (077), 2 Our supervisors encourage the people who work for them to exchange opinions and, ideas (078) $3 Our supervisors frequently hold group meetings where the people who work for them can really discuss things together (0.79) 4 Our supervisors rarely encourage us to get together to solve problems (0.76) A Employee suggestions (03 and 61 percent)
1 Management es prot and rice Ingres: gros ity 2 We ae encouraged to make sugges for improving performance this ant
078
‘3 Management tells us why our suggestions are implemented or not used (81), 4 Many useful suggestions are implemented at this plant
5 My suggestions are never taken seriously around here (removed) 15 Small group problem solving 264 and 53 percent
1 During problem solving sessions, we make an effort to get all team members ‘opinions and ideas before making a decision (080),
2 Our plant forms teams to solve problems (0.78)
3 In the past three years, many problems have been solved through small group sessions (0387)
Trang 234, Problem solving teams have helped improve manufacturing processes at this plant QMI and
i encouraged to try to solve thei lems h apeationat
5 Employee Abe 78) teams are ie own i 6 as much as performance Tư 6 We do not use problem-solving teams much, inthis plant (removed)
16 Multifunctional employees (2026 and 61 percent) 539
1 Our employees receive training to perform multiple tasks (0.77) 2, Employees at this plant leam how to perform a variety of tasks (076)
3 The longer an employee has been at this plant, the more tasks they lear to perform 07n
4 Employees arecrusstrained at this pÏant, so that they can fill in for others if necessary 078) 5, At this plant, each employee only learns how t0 do one job (075)
IL Cross-functional quality information practices (2:220 and 58 percent) 11 Coordination of decision making (228 and 57 percent)
1, Generally speaking, everyone in the plant works well together (0.79) 2 Departments in the plant communicate frequently with each other (079) 3 Departments within the plant seem to be in constant conflict (070) 4 Management works together well on all important decisions (0.75) 112 Cross-functional product design (228 and 86 percent)
1 Direct labor employees ‘or making product changes (0.76) are involved toa great extent before introducing new products 2, Manufacturing engineers are involved to a great extent before the introduction of
new products (077)
3 There is litle involvement of manufacturing or products, before they reach the plant (0.78) and quality people in the early desism 4 We work in teams, with members froma variety of arcas (marketing, manufacturing, etc) to introduce new products (0.77) 113 Communication with customer (2.11 and 63 percent)
1 We frequently are in close contact with our customers (0.70)
2, Our customers give us feedback on our quality and delivery performance (0.65) 3, We strive to be highly responsive to our customers’ needs (0:76)
4 We regularly survey our customers’ needs (0.0) 114 Communication with supplier (218 and 54 percent)
1, We are comfortable sharing problems with our suppliers (0.76)
2 In dealing with our suppliers, we are willing (o change assumptions, in order to find more effective solutions (0.7) 3 We believe that cooperating with our suppliers is beneficial (0.76)
4 We emphasize openness of communications in collaborating with our suppliers 072)
5 We maintain close communications with suppliers about quality considerations and design changes (removed)
Trang 24MRR 345 Phan Chi An is a Lecturer in the Faculty of Business Administration, Univer About the authors
‘and Business ~ Vietnam National Univesity Hanoi His research 1 nes telate to quality y of Economics management, lean production, and high-performance manufacturing, His articles canbe four in Intemational Journal of Productivity and Quadty, Operation Research Revtes, and dnternatonal Journal of Production Economics Phan Chi Anh is the corresponding author and can be
‘contacted at: annpe@yahoo com
540 School of Social Sciences and Faculty of Business Administration, Yokohama National University in Japan His research and teaching topics cover issies of manufacturing Yoshiki Matsui is a Professor of Operations Management at the International Graduate ‘management, supply chain management, quality management, JIT production, and new product evelopment He has published papers in International Journal of Production Íšomamne, International Journal of Operations and Quantitative Management, buernational Journal of Global Logistics ond Supply Chain Management, and 30 on