Roger G. Schroeder

A FRAMEWORK FOR QUALITY MANAGEMENT RESEARCH AND AN ASSOCIATED MEASUREMENT INSTRUMENT

Abstract Research on quality incorporates a range of concerns, including quality definition and management, and such specific mechanisms as statistical quality control (SQC). However, though research in statistical quality control has evolved in a scientific and rigorous fashion, based on the early works of Shewhart, Juran, Deming and others, the study of other aspects of quality, particularly quality management, has not evolved in a similarly rigorous fashion. Theory development and measurement issues related to reliability and validity are particularly weak in the quality management literature. Starting from a strategic perspective of the organization, this paper identifies and substantiates the key dimensions of quality management, then tests the measurement of those dimensions for reliability and validity. In doing so, it establishes a clear framework for subsequent research and for evaluation of quality management programs by practitioners. In order to specify the important dimensions of quality management, a thorough search of the relevant literature was undertaken. Quality management is defined as an approach to achieving and sustaining high quality output; thus, we employ a process definition, emphasizing inputs (management practices) rather than outputs (quality performance) in our analysis. Quality management is first viewed as an element of the integrated approach known as World Class Manufacturing; quality management supports and is supported by JIT, human resources management, top management support, technology management and strategic management. The key dimensions of quality management are then articulated. Top management support creates an environment in which quality management activities are rewarded. These activities are related to quality information systems, process management, product design, work force management, supplier involvement and customer involvement. They are used in concert to support the continuous improvement of manufacturing capability. As manufacturing capability and quality performance improve, a plant achieves and sustains a competitive advantage. This, in turn, provides feedback, reinforcement and resources to top management, which stimulates continuous improvement. Based on the seven dimensions of quality management identified in this paper, a set of 14 perceptual scales was developed. The scales were assessed for reliability and validity with a sample of 716 respondents at 42 plants in the U.S. in the transportation components, electronics and machinery industries. Reliability is broadly defined as the degree to which scales are free from error and, therefore, consistent. The use of reliable scales provides assurance that the obtained results will be stable. Application of Cronbachs alpha both across the board and by industry and nationality subsamples refined the original group of 14 scales to 11 internally consistent scales. Validity refers to the degree to which scales truly measure the constructs which they are intended to measure. This provides academic and industry users with confidence that the scales measure important constructs which are related to independent measures of the same constructs, and that each scale measures a single construct. It was concluded that the scales, and the instrument as a whole, are valid measures of quality management practices. Thus, the scales may be used with confidence by both researchers and industry users to measure quality management practices, with the ability to generalize beyond the immediate sample. This paper makes several important contributions to the area of quality management. It proposes an emergent theory of quality management and links it to the literature. Because the proposed scales are reliable and valid, they may be used by other researchers for hypothesis testing and by practitioners for assessing quality management practices in their plants and for internal and external benchmarking. Finally, the paper provides a step-by-step approach and criteria for conducting reliability and validity analysis of a measurement instrument.

Empirical research methods in operations management

Abstract This paper discusses the need for more research in operations management which is based on data from the real world. Tying operations management theory in with practice has been called for over a long period of time, however, many P/OM researchers do not have a strong foundation in gathering and using empirical data. This paper provides a starting point that encourages operations management researchers to use empirical data and provides a systematic approach for conducting empirical studies. Empirical research can be used to document the state of the art in operations management, as well as to provide a baseline for longitudinal studies. It can also be invaluable in the development of parameters and distributions for mathematical and simulation modeling studies. A very important use for empirical data is in theory building and verification, topics which are virtually ignored in most P/OM research. Operations management researchers may be reluctant to undertake empirical research, due to its cost, both in dollars and time and the relative risk involved. Because empirical research may be considered “soft,” compared with mathematical modeling, it may be perceived as risky. This paper attempts to provide a foundation of knowledge about empirical research, in order to minimize the risks to researchers. It also provides a discussion of analytical techniques and examples of extremely rigorous empirical P/OM research. Although operations management researchers may not recognize it, all research is based on theory. The initial step in conducting empirical research deals with articulating the theoretical foundation for the study. It also includes determining whether the problem under investigation involves theory building or theory verification. In the second step, a research design should be selected. Although surveys are fairly common in empirical P/OM research, a number of other designs, including single and multiple case studies, panel studies and focus groups, may also be used, depending on the problem being studied. Third, a data collection method should be selected. One method, or a combination of several data collection methods, should be used in conjunction with the research design. These include historical archive analysis, participant observation, outside observation, interviews, questionnaires and content analysis. The implementation stage involves actually gathering the data. This section of the paper focuses on using questionnaires as the method of data analysis, although some of the concepts discussed may be applicable to other data collection methods, as well. A brief overview of data analysis methods is given, along with documentation of the types of data analysis which have been used in various types of empirical research conducted by operations management researchers over the past ten years. Potential outlets for publication of empirical P/OM research are discussed and their history of publishing such research is documented. Underlying every step of the process are considerations of reliability and validity. Conducting empirical research without considering its reliability and validity is pointless, because the researcher will not be able to generalize from the results. This should be considered in each of the four stages listed in the approach described above. A number of conclusions are discussed. These include the need for more empirical research and the need for P/OM researchers to become more critical readers of the empirical research done by others. Colleagues in the social sciences can be a valuable source of information about conducting empirical research. Industry contacts can be useful, as well, in pilot testing, finding industry sites and determining consensus on the definition of terms. Finally, researchers in operations management need to be more aware of the theory which underlies their work. Empirical research can be highly useful in both theory building and theory verification.

Relationships between implementation of TQM, JIT, and TPM and manufacturing performance

Research on Total Quality Management (TQM), Just-in-Time (JIT) and Total Productive Maintenance (TPM) generally investigates the implementation and impact of these manufacturing programs in isolation. However, many researchers believe and argue conceptually the value of understanding the joint implementation and effect of manufacturing programs. This study investigates the practices of the three programs simultaneously. We find that there is evidence supporting the compatibility of the practices in these programs and that manufacturing performance is associated with the level of implementation of both socially- and technically-oriented practices of the three programs.

Six Sigma: a goal-theoretic perspective

Abstract Six Sigma is a phenomenon that is gaining wide acceptance in industry, but lacks a theoretical underpinning and a basis for research other than “best practice” studies. Rigorous academic research of Six Sigma requires the formulation and identification of useful theories related to the phenomenon. Accordingly, this paper develops an understanding of the Six Sigma phenomena from a goal theoretic perspective. After reviewing the goal theory literature, these concepts, when applied to Six Sigma, suggest some propositions for future research. This paper can help serve as a foundation for developing scientific knowledge about Six Sigma.

The impact of human resource management practices on operational performance: recognizing country and industry differences

The interest in strategic human resource management (HRM) has spawned a number of empirical research studies that investigated the impact of HRM practices on organizational performance. However, very little attention has been paid to address the impact of HRM practices on operations management and to generalize the findings across countries and industries. Success of some business decisions (e.g. globalization and merger and acquisition) necessitates recognition and reconciliation of the differences among HRM practices in different countries and industries. This study attempts to generalize the efficacy of seven HRM practices proposed by Pfeffer in the context of country and industry, focusing primarily on the effects of these practices on operations. The findings provide overall support for Pfeffer’s seven HRM practices and empirically validate an ideal-type HRM system for manufacturing plants.

Relationship Between JIT and TQM: Practices and Performance

We propose that the use of total quality management (TQM) practices wilt improve just-in-time (JIT) performance through process variance reduction and reduced rework time and that JIT practices wil...

Operations strategy: A literature review

Abstract Competitive pressures on American business have created the need for improved understanding and practice of operations strategy. Over the past 20 years some 80 articles and several books have been written on the subject. These writings, while diverse in nature and placement, serve to shape what we know about operations strategy and the opportunities for improved practice and meaningful research. This paper examines an underlying argument that exists within the literature that proper strategic positioning or aligning of operations capabilities can significantly impact competitive strength and business performance of an organization. The discussion is organized around four related premises: (1) that there exists a strategic, as opposed to a tactical, view of operations, (2) that there must be some synergistic process of integrating business and operations strategic issues, (3) that there are operations decision or policy areas which demonstrate strategic opportunities, and (4) that conceptual structures exist by which to target and focus operations strategy. The paper concludes that the literature and emerging research support each of these premises to varying degrees. The authors believe that further understanding of these premises could be benefited by more careful and consistent definition of operations strategy concepts and terminology, by more attention being placed on the content and process of operations strategy, by more empirical study, and finally by more emphasis being placed on service operations strategy.

The impact of total productive maintenance practices on manufacturing performance

In this paper we investigate the relationship between Total Productive Maintenance (TPM) and manufacturing performance (MP) through Structural Equation Modeling (SEM). We find that TPM has a positive and significant relationship with low cost (as measured by higher inventory turns), high levels of quality (as measured by higher levels of conformance to specifications), and strong delivery performance (as measured by higher percentage of on-time deliveries and by faster speeds of delivery). We also find that the relationship between TPM and MP can be explained by both direct and indirect relationships. In particular, there is a significant and positive indirect relationship between TPM and MP through Just-In-Time (JIT) practices.

Impact of Work Teams on Manufacturing Performance: A Longitudinal Field Study

We report the results of a longitudinal field study examining the impact of work teams on manufacturing performance. An electromechanical assembly plant was our research site from April 1992 throug...

Manufacturing practices, strategic fit and performance: A routine-based view

This article challenges and advances the extant manufacturing practice‐performance research in three ways. First and most fundamentally, the article offers a sound theoretical foundation for the proposition that manufacturing practices have competitive value. Second, typical studies do not pay enough attention to the multidimensional nature of performance and often collapse strategic position (performance) into a one‐dimensional index. The article will show that this does not do justice to the multidimensional nature of operational performance. Third, extant research, aside from a few exceptions, pays little attention to the strategic contingencies involved in adopting and implementing specific practices. The overarching goal of this article is to move us toward better‐informed empirical inquiry of the strategic contingency argument in operations strategy research. The article builds a theoretical argument of manufacturing practices, strategic contingency and performance and tests it in a sample of 164 manufacturing plants using a series of regression analyses. Results show that both the best practice and strategic contingency arguments have merit in explaining operational performance; however, the contingency argument has stronger support.