تأثیر پیچیدگی زنجیره تامین بر عملکرد کارخانه
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|10752||2009||16 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Operations Management, Volume 27, Issue 1, January 2009, Pages 78–93
This paper puts forth a model of supply chain complexity and empirically tests it using plant-level data from 209 plants across seven countries. The results show that upstream complexity, internal manufacturing complexity, and downstream complexity all have a negative impact on manufacturing plant performance. Furthermore, supply chain characteristics that drive dynamic complexity are shown to have a greater impact on performance than those that drive only detail complexity. In addition to providing a definition and empirical test of supply chain complexity, the study serves to link the systems complexity literature to the prescriptions found in the flexibility and lean production literatures. Finally, this research establishes a base from which to extend previous work linking operations strategy to organization design [Flynn, B.B., Flynn, E.J., 1999. Information-processing alternatives for coping with manufacturing environment complexity. Decision Sciences 30 (4), 1021–1052].
The last twenty years have seen a steady convergence of the traditionally distinct areas of operations management (OM), sourcing, and logistics into a single area commonly known as supply chain management (SCM). According to the SCM perspective, it is no longer adequate for businesses to run these areas as loosely linked pockets of excellence. They must also develop and manage the information flows, physical flows and relationships that link these areas together, and link these areas with upstream and downstream partners. At the same time, the SCM perspective requires businesses to broaden the scope of business activities that must be designed and managed, and the nature of these activities has become more challenging as product life cycles shorten, product variety and customization levels increase and supply chain partners become more geographically dispersed. Managing the supply chain, therefore, is clearly a challenging mission, and most observers would agree that a supply chain is a complicated system. In this paper, however, we employ some of the concepts and terminology of the systems science literature to formally define supply chain complexity, clarifying the aspects of supply chains that make them truly complex systems. While much attention has been paid to why it is necessary for companies to expand the scope and depth of their supply chain activities (e.g., Swafford et al., 2006), only recently have researchers and practitioners begun to consider the downside of this added complexity (Hoole, 2006). In addition to defining supply chain complexity, we also empirically explore the impact of various sources of complexity—upstream in the supply chain, internal to the manufacturing plant, and downstream from the plant—on manufacturing plant performance. Our results allow us to identify the sources of complexity that have a statistically significant impact on plant performance across a large data set of manufacturing plants from various industries and geographic regions of the globe. Moreover, our results resonate with the existing lean production literature in terms of the importance of certain sources of complexity in explaining poor manufacturing performance. Our research also helps to illuminate important priorities for supply chain managers in focusing on certain lean principles over others. The remainder of this paper is organized as follows. We first review the systems complexity literature, paying particular attention to the concepts of detail complexity and dynamic complexity. Out of this, we develop a definition of supply chain complexity, and discuss its three component parts: internal manufacturing complexity, downstream complexity, and upstream complexity. In the third part of the paper, we put forth a conceptual model of supply chain complexity, which we then test using data gathered from 209 manufacturing plants in seven countries. We end the paper by discussing the parallels and differences between our results and the prescriptions found in the lean production literature, implications for managers, and directions for future research.
نتیجه گیری انگلیسی
6.1. Parallels to the lean production literature Practitioners and academics are starting to recognize how supply chain complexity affects plant performance (Deloitte and Touche, 2003). More formally, our research presents a conceptual model that divides plant-level supply chain complexity into three distinct parts (downstream complexity, internal manufacturing complexity, and upstream complexity), and distinguishes between drivers of detail complexity and dynamic complexity. levels of upstream, internal manufacturing, and downstream complexity will have a negative impact on plant performance. The empirical analysis, based on a sample of 209 plants from seven countries, supports these hypotheses. Three supply chain complexity drivers stand out in terms of their impact on plant performance: long supplier lead times, instability in the master production schedule, and variability in demand. Note that these findings parallel the prescriptions commonly advocated in the lean production literature, as captured in the comprehensive definition put forth by Shah and Ward (2007): “Lean production is a socio-technical system whose main objective is to eliminate waste by concurrently reducing or minimizing supplier, customer and internal variability” (p. 791—our italics). Our research does more than provide empirical support for lean prescriptions, though. It establishes a link between the lean production literature and the systems science literature that formally defines the characteristics of higher-order complexity systems. In doing so, our study provides an alternative view into why variability and unpredictability in supplier, customer, and internal inputs to the manufacturing process can be so detrimental to plant performance. In at least one important way, our findings differ from traditional lean prescriptions. Controlling for industry and country effects, we did not see a significant relationship between plant performance and the supply chain characteristics that addressed numerousness in the system—number of suppliers, number of parts and products, and number of customers. One possible explanation is that manufacturers have become adept at managing such sources of detail complexity, either through product design efforts that limit true variability in product design, through marketing efforts that grow the number of customers without increasing heterogeneity, through the use of information technology, or through lean-based simplifications to the production system that allow it to accommodate more environmental uncertainty (an excellent example of the latter is the Aisin Mattress Factory described in Spear and Bowen, 1999, p. 102). It remains to be seen whether our findings represent an anomaly or an early indication that manufacturers have learned to effectively manage detail complexity. 6.2. Determining the appropriate level of supply chain complexity Another interesting issue highlighted by the results is one that, in our view, is not discussed enough in the operations and supply chain management literature—the extent to which the firm should reduce or eliminate certain sources of supply chain complexity. Indeed, a firm might consciously decide to take on customers who, although their demands are less predictable, might nevertheless purchase higher-margin products and services. Moreover, a firm might decide for strategic reasons to use suppliers whose piece prices are substantially lower, but whose delivery capabilities are deficient, or perhaps to hedge its bets between fast and expensive suppliers and slow and inexpensive suppliers by employing both, thereby injecting additional complexity in its supply management and internal planning systems. Our argument, then, is not that all sources of supply chain complexity are bad things and therefore must be eliminated or reduced to the lowest possible levels. Rather, it is our contention that if manufacturers engage in activities and relationships that increase the complexity of their supply chains—something they might indeed need to do for competitive reasons—they need to understand the potential performance impacts of these choices, and, where necessary, take actions to offset or accommodate the higher levels of complexity that strategic imperatives might entail. 6.3. Accommodating supply chain complexity Most of the trade and academic literature on lean production has focused predominantly on how to reduce supply chain complexity—see, e.g., the excellent literature reviews in Shah and Ward, 2003 and Shah and Ward, 2007. Yet the literature on flexibility (e.g., Swink et al., 2005 and Sethi and Sethi, 1990 and Swafford et al., 2006) and operations strategy (from, e.g., Hayes and Wheelwright, 1979, to recent work like that of Closs et al., 2008) indicates that manufacturers must understand how to accommodate high levels of supply chain complexity when the business strategy requires it. Galbraith, 1973, Galbraith, 1974 and Galbraith, 1977, in his information processing view of the firm, posited that organizations have two basic strategies for accommodating environmental uncertainty: (1) put in place mechanisms that absorb the effects of uncertainty or (2) enhance the organization's ability to manage uncertainty. Flynn and Flynn (1999) studied the impacts of such strategies within the manufacturing plant, but to our knowledge, no one has examined how effective these strategies are at moderating the impacts of upstream and downstream complexity. While Flynn and Flynn focused on complexity in manufacturing, we extend the scope of analysis to study sources of complexity upstream and downstream from the plant. The nature of the study carried out by Flynn and Flynn, however, is broader in that it also studies the moderating effects of applying Galbraith's prescriptions for managing uncertainty. It would be useful, then, to extend our research to explore whether Galbraith's prescriptions are being employed in managing complex supply chains, and to the extent that they are, whether they moderate the negative effects of supply chain complexity on plant performance. 6.4. Study limitations and directions for future research While this research makes a significant contribution to the academic literature and provides the potential to positively influence managerial practice, there are nonetheless limitations that provide opportunities for further research. First, we did not explicitly explore the impact of industry and country differences on the complexity–performance relationships we found in our analysis. In some industries or countries, these relationships may differ due to differences in customer requirements and preferences, or differences in manufacturing or supply chain management practices. Moreover, the set of significant supply chain complexity drivers might vary across industries or countries. Second, our study has not explored the source of the differences in the complexity–performance relationships among firms, just that those relationships exist. A deeper question, then, is whether plant-level decision makers actually recognize these relationships and account for them in managing the supply chain. Finally, we have proposed what we believe would be an interesting study to extend previous work (Flynn and Flynn, 1999) regarding the moderating impact of organizational prescriptions for managing in an uncertain environment ( Galbraith, 1973, Galbraith, 1974 and Galbraith, 1977). The research presented in this paper serves as a natural base from which to explore similar effects in the broader supply chain. Thus, we close the paper with a series of specific questions regarding those directions for future research: • To the extent that the relationships posited in the conceptual model might differ across geographic regions or industries, how do these differences affect our more general findings regarding the effects of specific sources of complexity on plant performance? • Are there other important sources of complexity in the supply chain not addressed in this study that might also explain performance differences among manufacturers? Moreover, do manufacturing industries that differ from those considered in this study exhibit different complexity drivers and performance effects? For example, do these complexity issues present themselves differently in “lighter” manufacturing industries (e.g., consumer electronics or medical devices) or in non-manufacturing portions of physical goods supply chains (e.g., retailing or distribution)? Could a study parallel to ours be undertaken on service supply chains? • How well do plant-level decision makers understand supply chain complexity and its impacts? Do the better performers in our data set reflect proactive management or good instincts on the part of some plants, lack of awareness on the part of other plants, or something else? • Building on the work of Galbraith, 1973, Galbraith, 1974 and Galbraith, 1977 and Flynn and Flynn (1999), what strategies are plants using to moderate the impacts of supply chain complexity? How effective are these strategies? • Last, what frameworks can manufacturers use to identify and balance the positive, revenue-generating aspects of increased supply chain complexity versus their performance impacts? How can these frameworks be integrated into the supply chain strategy debate?