DSpace at VNU: Relationship between quality management information and operational performance International perspective

Relationship between qualitymanagement information and operational performance International perspective Phan Chi Anh Faculty of Business Administration, University of Economics and Busi

Management Research Review

Relationship between quality management information and operational performance:

International perspective

Phan Chi Anh Yoshiki Matsui

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Phan Chi Anh Yoshiki Matsui, (2011),"Relationship between quality management information and

operational performance", Management Research Review, Vol 34 Iss 5 pp 519 - 540

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Relationship between quality

management information and

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 University,

Yokohama, Japan, and

Purpose – The purpose of this paper is to examine whether quality management information (QMI)

can be a source of competitive advantage and should be managed strategically.

Design/methodology/approach – 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

QMI practices across the countries This study highlights the important role 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

of a set of communication and information sharing practices in shop-floor and cross-functional levels

of manufacturing plants.

Originality/value – Although scholars considered information as one dimension of quality

management, existing quality management literature provides little empirical evidence on the

relationship of QMI and operational performance of manufacturing plants This paper fills 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

Introduction

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,

and generate solutions to the problems Effective implementation of QMI allows the

www.emeraldinsight.com/2040-8269.htm

QMI and operational performance

manufacturers to improve product and service quality and facilitate their supplierrelationship management (Flynn et al., 1994; Forza and Flipini, 1998; Kaynak, 2003;Morita et al., 2001; Schniederjans et al., 2006) Recently, greater attention has been paid toQMI by such international standards and awards as ISO 9000, Malcom BaldrigeNational Quality Award, and Japan Quality Award Although scholars consideredinformation as one dimension of quality management, existing quality managementliterature provides little empirical evidence on the relationship of QMI practices andoperational performance of manufacturing plants This study aims to fill this gap byresponding to the following questions:

. What are similarities and differences in the perception of QMI practices acrosscountries?

. Do QMI practices positively relate to various dimensions of operationalperformance of manufacturing plants such as quality, cost, delivery, flexibility, etc?

To be competitive in global market, many manufacturing companies have implemented aset of practices such as total quality management (TQM), just in time (JIT), and totalproductive maintenance (TPM) that hereafter broadly labeled as high-performancemanufacturing (HPM) initiatives HPM literature indicates that effective implementation

of such HPM practices highly depend on how the companies manage the communicationand information flow This study examines QMI by introducing a set of communicationand information sharing practices at shop-floor and cross-functional levels ofmanufacturing plants These practices reflect various types of communication andinteraction within shop floor and between functions/departments of manufacturing plantssuch as information feedback, suggestions, training, small group activities,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 countries during 2003-2004 in the framework of HPM project The statistical resultsindicate the significant difference in the perception of the QMI practices across thecountries Plants in the USA and Sweden show their stronger emphasis on QMI practicesthan other plants, particularly those in Japan and Italy All the countries except Japan andKorea place their higher attention on cross-functional practices than shop-floor practices.The significant difference among countries in the effect of QMI practices on performance isdetected The connection between the QMI practices and high performance in Japaneseplants appears tight, comparing with other countries These findings are consistent withthe institutional theory when the institutions are taken to be the countries Nationalculture, geographical specifics, and competitive environment may account for thedifferences we observe in communication and information sharing practices across thecountries The linkage between QMI and operational performance found in this studysuggests that HPM could be obtained by implementing a set of communication andinformation sharing practices The remaining of this paper presents the literature andresearch framework, which are followed by the descriptions of data collection,measurement test, and hypothesis testing The last three sections discuss on the importantfindings, the limitations of this research, and the final conclusions

Literature reviewThe impact of QMI on performance has been widely investigated by scholars (Flynn et al.,1994; Forza and Flipini, 1998; Morita et al., 2001; Kaynak, 2003; Schniederjans et al., 2006)

Flynn et al (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

To support 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 employees can identify and solve problems from materials

and parts supplied and provide the suppliers timely and important feedbacks to improve

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 to the 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 QMI directly depends on customer focus,

workforce management, and top management support Workforce management is

considered as infrastructure for quality management and it facilities the collection and

use of QMI by increasing employee’s continuous awareness of quality-related issues and

empowering employees in quality decision making Close contact with customers,

frequent visit to customers, and customer surveillance allow the firm to obtain product

and service quality information and use it for further quality improvements

For manufacturing organization, QMI is a critical issue influencing its long-term

viability However, little empirical research has been conducted with the international

perspective of QMI even in manufacturing sectors (Parast et al., 2006) Early studies

on international comparison of quality management mainly focused on comparing

the quality practices between the USA and Japan (Garvin, 1986; Flynn, 1992) Recently,

the scope of international comparison of quality management has been extended to

study the quality practices in other countries and regions around the world (Madu et al.,

1995; Rao et al., 1997; Flynn and Saladin, 2006; Phan and Matsui, 2009) Most of these

studies use different frameworks, instruments, and constructs for measuring and

comparing quality management practices across the countries As discussed in the

literature, the question regarding the “universal applicability” of quality management

has not been fully answered, and more empirical studies on international

comparison of quality management are needed (Sila and Ebrahimpour, 2003;

Rungtusanatham et al., 2005)

QMI and operational performance

521

Research frameworkQMI improves quality performance through collecting, storing, analyzing, and reportinginformation on quality to assist decision makers at all level This concept requires inputfrom a variety of functional areas and recognized that information consists of not onlydata but also other knowledge needed for decision making ( Juran and Gryna, 1980;Forza, 1995) Schroeder and Flynn (2001) argue that successful implementation ofvariety of manufacturing management practices such as TQM, JIT, and TPM depend onhow the manufacturing plants develop their horizontal linkage structure throughout thecommunication network The “communication and action” process is one of theunderlying forces that have made such practices as TQM and JIT so successful.While most of quality management literature have emphasized on the importance ofavailability, accuracy, and timeliness of QMI, this study focuses on how themanufacturing plants develop QMI through facilitating communication and informationsharing practices to achieve HPM The flow of communication and information sharing

is distinguished into two categories: shop-floor and cross-functional levels Shop-floorQMI concentrates on the collection, analysis, and feedback of quality information on theshop floor where products are created It relates with two-way communications betweenmanagers/engineers and workers and between workers themselves Conducting smallgroup activities is the means for employees to share their ideas and expertise for qualityimprovement In addition, along with the feedback of quality performance, employee’ssuggestions should be formally acknowledged to encourage the employee’sparticipation in quality improvement Cross-functional QMI, on the other hand, relateswith communication and information sharing between functions/departmentsconcerning with coordination, new product development efforts, and the interactionwith customers and suppliers Communication and information sharing betweendifferent functions are important for making quality decisions especially to solve criticalquality problems External communication with customers and suppliers is also crucialfor quality management Close contact with customers, frequent visit to customers, andregular customers’ survey are the best ways to capture customers’ needs andexpectations while sharing information with suppliers improves their mutual trustwithin the supply chain The framework of this study is simply shown in Figure 1.Prior to examining the linkage between QMI and operational performance, thisstudy empirically compares the degree of implementation of QMI practices across thecountries This is important as we can determine whether QMI depends on thecontextual factors such as national culture or geographical specifics Some scholars

Figure 1.

Research framework

Shop-floor quality management information practices

Cross-functional quality management information practices

Operational performance

argue 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 QMI 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:

H1 There is 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, 2009) Flynn and Flynn (1999) suggest that the use of

lateral relations would moderate the adverse impact of environmental complexity,

thereby improving manufacturing performance We assume that, shop-floor QMI is a

critical element for process control and improvement The application and results of

statistical process control need to be intensively discussed and shared on the shop floor

to solve the problems Process variation and quality problems should be detected,

analyzed, controlled, and eliminated through several activities such as shop-floor

information feedback, interaction between managers/engineers and workers, small

group activities, etc As cited in the existing literature, the reduction of defective

products leads to a reduction of time delay for rework, inspection, and time for machine

stop These allow the production run faster with shorter consuming time from material

receiving to customer delivery Thus, shop-floor QMI practices would relate with the

various dimensions of operational performance: product cost, on-time delivery, and

flexibility to change the production volume Cross-functional QMI, in other way, would

contribute to design quality and new product development lead time Fast identification

of customer’s expectations and translating those expectations into product

specifications requires intensive interaction with customers in various channels such

as web/fax/phone contacts, survey, or direct visits The reduction of time-to-market and

improvement of the design quality would be achieved though the cross-functional

products design effort This is an overlap design/engineering practice that includes

QMI and operational performance

523

all functions from the beginning of new product development project Suppliers can beregarded as an external process of the plants Collaboration with suppliers throughopening and sharing information concerning quality problems and design changeswould also allow the plants to improve product quality and save production cost.The hypothesis on the relationship between QMI practices and operational performance,therefore, is presented as follows:

H2 QMI practices positively relate to operational performance

To test the hypotheses, analysis of variance (ANOVA) and regression analysis areused to compare those practices across the countries and identify whether QMIsignificantly impact 13 operational performance indicators

Research variablesFrom literature reviewing, ten measurement scales are developed to examine QMIunder two perspectives: shop floor and cross-functional as mentioned early

Shop-floor QMI includes six measurement scales as follows:

(1) Feedback – measures whether the plant provides shop-floor personnel withinformation 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 betweenmanagement and workers is thought to promote problem solving and generalimprovement

(3) Employee suggestions – measures employees’ perception regardingmanagement’s implementation and feedback on employee suggestions.(4) Small group problem solving – evaluates how the plant uses teamworkactivities to solve quality problems

(5) Supervisory interaction facilitation – measures whether supervisorssuccessfully encourage workers works as team, including expressing theiropinions and cooperating with each other to improve production

(6) Multi-functional employees – determines if employees are trained in multipletask/areas; that is, received cross-training so that they can perform multipletasks or jobs

Cross-functional QMI includes four measurement scales as follows:

(1) Coordination of decision making – determines cross-functional cooperation andcommunication in the plants

(2) Cross-functional product design – measures the level about amount of inputthat the manufacturing function has in the new product introduction process.This includes cooperation and input into process across functional boundaries.(3) Communication with customers – assesses the level of customer contact,customer orientation, and customer responsiveness

(4) Communication with suppliers – assesses whether plants develop trust-basedrelationship with suppliers by exchanging communication and sharinginformation

A 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, flexibility 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 “world-class manufacturer (WCM)” or a

“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, Italia, Sweden, Austria, and Korea during 2003-2004

The key characteristics of these plants are summarized in Table I

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 II Ten QMI measurement scales are constructed

by four to six question items evaluated on a seven-point Likert scale (1 – strongly disagree,

QMI and operational performance

525

4 – neither agree nor disagree, and 7 – strongly agree) The individual question items areshown in the Appendix Finally, 13 operational measures of manufacturing plants arejudged by the plant manager Each plant manager is asked to indicate his/her opinion abouthow the plant compares to its competitors in the same industry on a global basis on afive-point Likert scale (1 – poor or low end of the industry, 3 – average, and 5 – superior ortop of the industry).

Measurement analysisThe first step of analytical process is the analysis of reliability and validity of tenmeasurement scales and two super-scales In this study, Cronbach’s alpha coefficient iscalculated to evaluate the reliability of each measurement scale Table III shows thealpha values for all of ten scales exceeded the minimum acceptable alpha value of 0.60for pooled sample and country-wise Most of the scales have the alpha value above 0.75indicating that the scales were internally consistent:

. Content validity An extensive review of literature and empirical studies isundertaken about quality management and organization performance to ensurecontent validity

USA Japan Italy Sweden Austria Korea Total

Plant characteristics Average market share (%) 25.50 33.05 23.38 34.80 20.00 31.54 Average sale ($000) 284,181 1,118,492 71,209 584,371 64,470 2,266,962 Average of number of

employee (salaried person) 153 474 296 348 122 2,556

Notes: DL, Direct labor; PM, plant manager; PD, member of new product development team; HR, human resource manager; QM, quality manager; PS, plant superintendent; IM, inventory manager; SP, supervisor; PE, process engineer

QMI and operational performance

527

Construct validity Construct validity is conducted to ensure that all questionitems in a scale all measure the same construct Within-scale factor analysis istested with the three criteria: uni-dimensionality, a minimum eigenvalue of 1, anditem factor loadings in excess of 0.40 The results of measurement testing for thepooled 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 loadingfor each items are more than 0.40, mostly range between 0.70 and 0.90 for thepooled sample as shown in the Appendix.

Hypothesis testingThis section starts with the analysis of country effect existed in QMI practices One-wayANOVA is used to identify the similarities and differences in QMI practices across thecountries The last two columns of Table IV show the values of the F-statistic and theirsignificant levels If we set the set significant level at 5 percent, the ANOVA test resultssuggest that all of QMI practices are significantly different across the countries exceptemployee suggestions Next, Tukey pairwise comparison tests of mean differences areconducted to identify how QMI practice differed between each pair of countries

We observe that the largest differences exist in such practices as supervisory interactionfacilitation, 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 multi-functional employeesand communication with customers In addition, QMI practices are evaluated in similarway in two Asian countries In general, shop-floor QMI practices are lowest in Italy andhighest in Austria and Korea, while cross-functional QMI practices are lowest in Japan andhighest in Austria and the USA In the USA, an Italian plants, the focus of cross-functionalQMI practices are appeared higher than shop-floor QMI while both of them are similar inJapanese and Korean plants It is found that the most focused practices (top practices) ofQMI practices are different between the countries: communication with customer (in theUSA), multi-functional employees (in Sweden), coordination of decision making(in Austria), shop-floor contact (in Korea), and employee suggestions (in Japan) Insummary, 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 factorsmay account for the differences we observed among QMI practices adopted in differentcountries As the result, we would like to accept H1 and state that there is significantdifference in QMI practices across the countries

Primary relationship between ten QMI practices and 13 operational performancemeasures is identified by the binary correlation analysis that conducted in pooled andcountries-wise samples as show in Table V It has 130 cells, each corresponding to apair of one QMI practices and one operational indicator The cells include initials ofthe countries for which significant correlations are found between the practices and theperformance indicators We observe that linkage between QMI practices andperformance in Japanese plants exhibits closer than the one in other countries if weset the significant level at 0.5 percent as suggested in literature Out of 130, the number ofpair of significant correlation in Japanese case is 43 This number is 14, 13, 10, 8, 7, and 82

in Korea, Austria, Italy, Korea, US, Sweden, and pooled samples, respectively

It is observed that QMI practices are highly associated with on-time delivery,

QMI and operational performance

529