نقش تعدیل عوامل متنی بر شیوه های مدیریت کیفیت

This study investigates how contextual factors influence the relationship between Quality Management (QM) practices and manufacturing performance. It contributes to the contingency theory of QM effectiveness. Drawing on the management literature, we differentiate two different groups of QM practices: Quality Exploitation and Quality Exploration. The analysis empirically investigates the internal fit with organizational structure and the external fit with environmental uncertainty on the relationship between Quality Exploration, Quality Exploitation, and operational performance. The data comes from a survey of 238 manufacturing plants in three industries across eight countries. Regression analyses show that both internal fit with the organizational structure and external fit with the environment affect performance. The findings also provide insights for managers on how to customize QM programs to achieve optimal performance benefits. In stable environments Quality Exploitation practices provide the best performance outcomes, while in a dynamic environment Quality Exploration practices with an organic organizational structure give the best results.

Organizations continuously search for new ways to improve performance and gain a competitive advantage. Quality Management (QM) initiatives offer one approach that firms use to improve performance. For example, 3M implemented Six Sigma to help improve performance (Fiedler, 2004). However, 3M's implementation has been met with mixed success (Hindo, 2007). Prior research of the relationship between QM and performance also shows mixed results. Some studies show a positive relationship with performance (e.g. Prajogo and Sohal, 2003 and Ho et al., 2001), while other studies fail to find a relationship (e.g. Mohrman et al., 1995, Choi and Eboch, 1998 and Yeung et al., 2006). In a study by Mohrman et al. (1995) 83% of the surveyed companies indicated a positive or very positive experience with QM, while a study by Dooyoung et al. (1998) reports failure rates as high as 60–70%. Organizations need to understand how to implement QM to achieve the maximum benefit. Taking a one-size fits all approach to QM may not lead to optimal outcomes. Different organizations may need different approaches to QM. For instance, should a commodity based manufacturer use the same quality management system as a high tech manufacturer? Westphal et al. (1997) studied QM implementation in hospitals, and found that hospitals that customized the QM practices had higher performance than hospitals that adopted standardized approaches to QM. However, their study did not provide an explanation about how organizations can customize QM practices. This study draws on contingency theory and empirically shows that the contribution of different QM practices to performance depends on organizational structure and environmental contextual factors. Scholars have recognized the importance of contingency theory (Lawrence and Lorsch, 1967 and Thompson, 1967) in Operations Management (Sousa and Voss, 2001 and Sousa and Voss, 2008). As research in QM matures scholars need to move beyond simply justifying practices, they now need to better understand the effect of context on QM practices. Some scholars have started to develop a refined understanding of QM by drawing on contingency theory. For example, Foster (2006) notes the importance of taking a contingency theory perspective when implementing QM. Consistent with Foster (2006), Sousa and Voss (2008) also raise doubt about the “universal validity” of quality management practices. They suggest that the inconsistent performance in QM implementation may be due to contextual factors. Nair (2006) argues that future research in QM should consider contingency theory. Some empirical studies have considered contextual factors that influence QM effectiveness, such as country (e.g. Oliver et al., 1996, Rungtusanatham et al., 1998 and Rungtusanatham et al., 2005) and firm size (e.g. Ghobadian and Gallear, 1996, Ahire and Golhar, 1996 and Sila, 2007). Recently, Jayaram et al. (2010) investigate the effect of firm size, quality program duration, unionization, and industry context on QM implementation. These studies provide some support for the contingency theory perspective in quality management but treat QM as a single set of practices. Sitkin et al. (1994) note that scholars have treated QM practices as a single universal set of practices which does not allow for customization. However, studies have noted the importance of customization (Westphal et al., 1997). Sitkin et al. (1994) begin to theorize that quality practices have both a control and learning orientation, and that different QM practices are more suitable in different contextual settings. This research draws on Sitkin's et al. (1994) theoretical model as a starting point to empirically investigate contextual factors that influence the relationship between different types of quality practices and performance. Their work argues that different QM practices are more or less effective under different environmental uncertainty conditions. This paper builds on Sitkin et al. (1994) theoretical argument and empirically tests the influence of two different contextual factors. It contributes to the contingency perspective of QM, and empirically addresses the question “how can organizations fit QM practices to different contextual settings?” Drawing on the management literature (e.g. March, 1991 and Sitkin et al., 1994), this study differentiates two orientations or types of QM practices: Quality Exploitation and Quality Exploration2. Quality Exploitation practices aim at cybernetic control – “a process in which a feedback loop is represented by using standards of performance, measuring system performance, comparing that performance with standards, feeding back information about unwanted variances in the system, and modifying the system” (Green and Welsh, 1988, p. 289). Quality Exploration, on the other hand, highlights increasing an organization's ability to explore the unknown and to identify and pursue novel solutions (Garvin, 1993, p. 80). This research is the first empirical study that differentiates QM as two separate yet related practices bundles. The analysis examines the moderating effects of organizational structure and environmental uncertainty on the relationship between Quality Exploitation and Quality Exploration with operational performance. The findings provide implications for organizations in selecting the right mix of exploitation or exploration practices to customize QM, and to get better performance from their quality initiatives. The rest of the paper is arranged as follows. Section 2 reviews the theoretical foundation for the proposed model. Section 3 describes empirical data and measurement instruments. Section 4 presents the data analysis and results. Section 5 concludes the paper with a discussion of theoretical and practical implications as well as limitations and possible future research.

Increasingly organizations implement quality management practices to improve performance. However, research shows mixed results when examining the relationship between quality management practices and performance (Nair, 2006 and Kaynak, 2003). Some scholars have found that customizing quality management practices can lead to higher performance than implementing standardized or universal approaches (Westphal et al., 1997). But scholars have provided little explanation on how to customize quality practices. Contingency theory offers a theoretical lens (Amundson, 1998) to explain how organizations can customize quality practices (Sitkin et al., 1994). Drawing on contingency theory, this study empirically examines two different aspects of QM practices that have different objectives: Quality Exploitation and Quality Exploration. The analysis reveals that these two aspects of QM affect performance differently for different levels of organizational structure and environmental uncertainty. Consequently, the effectiveness of various quality management practices depends on the organizational structure and environmental uncertainty. This research contributes to the literature in three ways. First, it addresses the effectiveness of quality management practices by differentiating and measuring two separate bundles of practices, which provides insight into how to customize quality management practices. Second, it supports the contingency view of QM effectiveness and empirically validates the moderating effect of two contingency factors on the link between QM practices and performance. Finally, it establishes the importance of both internal and external fit which provides useful insight for practitioners on how to implement quality management practices. In a dynamic environment both internal and external fit affects performance (Siggelkow, 2001), which makes effective implementation of QM in this setting more complex (Rivkin and Siggelkow, 2007). This research supports the contingency view of the relationship between quality management practices and performance, instead of the traditional belief that all quality practices provide a “universal remedy.” 5.1. The moderating effect of organizational structure and environmental uncertainty The analysis shows that the impact of Quality Exploitation and Quality Exploration on manufacturing performance varies across the different levels of environmental uncertainty. Quality Exploitation influences performance to a greater degree than Quality Exploration with low environmental uncertainty. When environmental uncertainty is low, the internal structure does not significantly affect the relationship between QM and performance. In this situation, Quality Exploitation positively affects performance regardless of the organizational structure. In other words, in a low uncertainty environment external fit with the quality system and the environment affects performance, but internal fit with the structure and the quality system does not. But the story changes with high environmental uncertainty. In this setting, internal fit with the right type of quality practices and the organizational structure leads to higher performance. However, the fit with Quality Exploration and an organic structure has higher performance than the fit with Quality Exploitation and a mechanistic structure. As a result, in an uncertain environment an organic organizational structure with Quality Exploration has the highest performance. This research contributes to the discussion in the literature over the universal versus context-dependent approach to quality management. Only recently have scholars begin to investigate the context-dependent approach (Sila, 2007 and Sousa and Voss, 2008). In particular, Sousa and Voss (2008) raise doubts of the ‘universal validity’ of quality management and propose that more research should be done to check if quality management practices are context dependent and under what contextual factors. This research provides strong empirical evidence to support a context-dependent approach and identifies contextual factors that affect different types of quality practices. This study also has implications for further research on how organizations may need to adapt their quality systems over time. For instance, organizations may need to change their focus between Quality Exploitation and Quality Exploration with changes in the environmental contingencies. The quality system that made an organization successful today may not be the same system that will make it successful in the future. A longitudinal study using the framework proposed in this research could reveal the challenges in reorienting the organization's quality system as the context changes. Investigating these results in a longitudinal setting has some interesting implications. For example, if an organization's environment changes from stable to dynamic, they could improve performance by increasing the level of Quality Exploitation with a mechanistic structure (see Fig. 4), but the best performance improvement would be to change both the quality systems to an Exploration orientation along with changing to an organic structure. The research could possibly provide insight into how organizations may need to adapt their quality system over time to sustain high levels of quality performance. 5.2. Managerial implications Despite the increasing popularity of QM practices, practitioners still experience mixed results. By distinguishing two different fundamental orientations of quality management practices (Quality Exploitation from Quality Exploration), this study provides a basis of guidance for practitioners to customize QM practices under different situational factors. For example, commodity based manufacturer might benefit more from a Quality Exploitation orientation, whereas a high technology manufacturer may benefit more from a Quality Exploration orientation. Fig. 5 summarizes the implications of this research for managers. When the environmental uncertainty is low, firms need to choose the right focus of quality practices to achieve better performance. However, when the environmental uncertainty is high, the internal fit between quality practices and the structure becomes critical. Furthermore, to achieve higher performance, the internal fit between quality practices and organizational structure needs to fit the external environment. This means when operating in a highly uncertain environment, choosing the right focus of quality practices is not enough to achieve the best performance. The best solution includes an organic structure with a focus on Quality Exploration. Achieving high performance in an uncertain environment involves more complex decision variables. In an increasingly competitive business environment where scarce resources have to be allocated for many different purposes, this research helps organizations choose the right focus of the quality management practices and allocate their resources wisely based on their organizational structure and the external environment.5.3. Limitations and future research This study has several limitations. For example, the data used in this study comes from manufacturing plants. Therefore the results cannot be generalized to other settings such as the service industry. However, manufacturing plants have a long history of implementing QM practices and provide a more mature setting for this research. Therefore the manufacturing industry provides a good starting point for examining the context-dependent perspective of quality management practices. Another limitation is that although HPM provides a comprehensive dataset with quality management as its major component, the measurement scales were developed after the survey was done. Therefore, some measurement scales are limited by the existing items. Future research could further refine the measurement scales. Future research can make several extensions to this study. First, the research could be extended to other settings such as service and health care. Would the Exploitation/Exploration context-dependent perspective hold in these situations? Second, the study could be expanded to include the supply chain. Now most studies on quality management initiatives are within the scope of one link of the supply chain. A holistic view of the supply chain that investigates the cooperation between suppliers, producers, and customers should bring further insights into the research on quality management effectiveness. Are different orientations to quality practices more important at different stages of the supply chain? Third, as Sousa and Voss (2008) point out, more key contingency variables need to be identified in the Operations Management discipline. This paper investigates the moderating role of two contingency factors. Future research could consider other contingencies. Finally, the antecedents to implementing quality practices should be investigated to help understand why organizations adopt a particular orientation to quality management practices. For example, institutional theory could help explain why organizations implement a particular orientation to quality management practices? Nevertheless, this paper points to important contingencies that should be considered when implementing QM practices. It is hoped that future research will continue to expand our understanding of the contingent effects of QM methods.