اثر ضعیف حمل و نقل در تولید ناب و خوشه بندی صنعتی: شواهد از صنعت خودرو هند
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|12136||2001||21 صفحه PDF||سفارش دهید||12030 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : World Development, Volume 29, Issue 7, July 2001, Pages 1157–1177
Conventional wisdom suggests that poor transportation systems adversely affect industrial competitiveness by raising the unit cost of freight. This study finds that freight is neither the only nor the most significant cost that poor transportation creates for auto firms in India. Poor transportation also raises the damages incurred in transit, total inventories, and ordering and overhead costs. Worse, it creates external diseconomies by introducing inefficiencies and unreliability in the supply chain, making it difficult for assemblers to implement lean production. These external diseconomies—rather than excessive freight prices or other direct costs—may be the more debilitating impact of poor transportation infrastructure on industrial performance. In India, transportation constraints and the imperatives of lean production are driving assemblers to create auto clusters.
Industrial firms in developing countries have to contend with highly ineffective freight transportation systems. The physical infrastructure—the ports, airports, and road and rail networks—is capacity constrained and poorly maintained, and the freight services provided by private and public sector operators tend to be limited in range, poor in quality, and often technologically obsolete. Consequently, industrial firms in these countries operate under a handicap relative to their competitors in advanced industrialized countries. But, neither the extent of this handicap nor the mechanisms through which inadequate infrastructure harms competitiveness are well understood (see, e.g., Diamond & Spence, 1989; World Bank, 1994; Anas & Lee, 1996).1 To bridge this gap in our understanding, this paper empirically examines the impact of poor transport infrastructure on industrial performance in a developing country. The illustrative case in this study is the automobile industry in India. The literature on transportation in developing countries tends to focus on the more obvious and easy to quantify linkages between transport infrastructure and industrial performance. This literature, primarily generated by development practitioners and institutions such as the World Bank, notes that poor transportation systems result in slow movement of goods and in high unit cost of freight (see, e.g., India Infrastructure Report, 1996; World Bank, 1995 and World Bank, 1996b). Perhaps because it is hard to estimate the value of time, this literature relies on indicators such as “unit freight cost” and “vehicle operating cost” to estimate the relative costs or benefits of different transportation systems.2 From this perspective, the key problem with badly maintained and inadequate road networks is that they directly raise the cost of freight by (a) increasing the cost of operations and maintenance (due to greater wear and tear and higher fuel consumption); and (b) increasing transit time, which, in turn, means that both labor (driver) and capital (the truck) are deployed for a longer period of time to complete a given delivery. The literature thus suggests that improvements in the transportation system would result in lower freight costs and greater competitiveness.3 This paper quantifies the logistics costs borne by India's largest auto assembler, Maruti, and analyzes the transport solutions devised by Maruti, Ford, and some other assemblers.4 It shows that the analytic approach discussed above is inadequate for understanding how transport infrastructure affects competitiveness and suggests a broader analytical framework within which to consider the issue. In contrast to much of the existing development literature, this study finds that—for the example of auto assemblers in India—freight costs are neither the only nor the most significant cost that poor transportation systems create. An inadequate transportation system also increases the damages incurred in transit, the total inventories that firms have to maintain, and the ordering and overhead costs associated with managing material flows. Taken together, these variables constitute the “total logistics cost” borne by a firm. This total logistics cost equation offers a more comprehensive approach for calculating the direct costs that poor transportation imposes on a firm. Specifically, View the MathML source This equation allows for better estimation of quantifiable firm-specific costs, but it does not capture those transportation-created costs that go beyond a particular firm and affect the supply chain as a whole (i.e., the external diseconomies).5 Moreover, the quantification alone does not shed light on how individual firms (in this case, the car assemblers) perceive the transportation problem and the relative importance they attach to various components of the logistics equation. To capture such information, this study examines not just the direct logistics cost borne by a particular firm but also the transportation costs over its supply chain. The quantitative supply chain analysis is supported by semi-structured interviews with firm managers and an inductive analysis of the coping strategies firms have devised to limit the adverse impacts of poor transportation. This analysis reveals that auto assemblers are highly concerned about the inefficiency and unreliability that poor transportation systems introduce into their supply chains. This is because, as the literature on industrial competitiveness emphasizes, efficient and well-managed supply chains are critical for competitive success in global industry (Gereffi & Korzeniewicz, 1994; Porter, 1990). Assemblers find that poor transportation is a major obstacle to their efforts to implement lean production and supply chain management strategies. Poor transport systems thus hurt their competitiveness not only by raising direct costs but also by creating external diseconomies that adversely affect the efficiency of supply chains and, indeed, entire networks of firms. Further, these external diseconomies—rather than excessive freight prices or other direct costs—may be the more debilitating impact of poor transportation infrastructure on industrial development and competitiveness. Although this paper takes the literature on transportation and industrial performance in developing countries as its point of entry, it also draws upon and contributes to two additional and traditionally separate bodies of literature. First, it contributes to the literature on industrial districts by showing how clustering in the Indian auto industry is being driven by a relatively straightforward and mechanistic logic—lack of infrastructure. Second, it contributes to the lean production literature by questioning the argument that the only significant difference between lean and nonlean firms is management attitude (not variables such as infrastructure) and that lean production can be fully implemented anywhere in the world (Womack, Jones, & Roos, 1990). Third, this paper suggests connections between these two separate models of industrial performance and competitiveness—it shows how auto firms in India are combining the geography of the industrial districts model with the hierarchy of the lean production model to enhance industrial performance. This study leads to a different understanding of the links between transportation and industrial performance because it modifies and augments the standard methodological approaches used in the transportation and infrastructure development literature. First, the unit of analysis is the firm and its supply chain. This analytical approach lies in between the usual micro and macro approaches, and tries to capture both direct firm-specific benefits and some of the external economies associated with infrastructure. Second, unlike most studies that have tended to take a supply-side perspective on the transportation problem and its potential solutions, this study examines these issues from a user's perspective. Third, it combines quantitative cost data with qualitative data from in-depth, semi-structured interviews with firm managers. The paper is structured as follows. Section 2 presents a brief overview of the Indian auto industry and of the lean production system that assemblers are trying to implement. Section 3 presents a case study of Maruti, India's largest and most successful car assembler, and assesses the magnitude of various components of its total logistics cost. It also discusses the “localization” solution that Maruti has devised to cope with transportation problems over its supply chain. Section 4 further analyzes supply chain management issues by examining the transport solutions Ford Motor Company is devising for its new plant in India. Section 5 suggests that firm responses to transportation constraints are affecting the geography of production in the Indian auto industry. Section 6 summarizes the study's findings and conclusions.
نتیجه گیری انگلیسی
The literature on transportation in developing countries suggests that the major problem associated with inadequate road networks (and poor transportation systems, in general) is that they raise transportation costs and thereby hurt competitiveness. Analyses of Maruti's expenditures—summarized in Table 4—show that the assembler does indeed incur significant freight costs. In 1996–97, Maruti's freight bill including damages accounted for 4.35% of total sales revenue. These freight costs represent a highly significant expense, given that the assembler's entire wage bill accounted for only 2.0% of total sales revenues in the year. But, as the table indicates, freight is not the largest cost variable in the total logistics cost equation: the estimated inventory carrying costs were more than double the total freight costs. The carrying cost of supply-chain inventories was 8.0% of which buffer stock accounted for 5.0% and inbound in-transit inventories for 3.0%; the latter alone exceeded the expenditures on inbound freight (1.5%) and those on outbound freight (2.5%).As compared to the traditional approach of examining freight expenditures and vehicle operating costs, the total logistics cost equation offers a more comprehensive insight into the direct costs—especially the financial costs—imposed by poor transport systems on firms. It also suggests reasons why distance between firms tends to affect competitiveness—with increasing distance, not only do freight costs increase, but so do in-transit inventories, buffer stock, and damages. As an analytical framework, however, the equation offers only a limited understanding of the transportation problem. It appears to suggest that the key problem with poor transportation is that it raises freight costs and increases the financial cost of holding inventories—that is, the problem is that assemblers have to spend more. From the assemblers' perspective, however, the more difficult problem is that poor transport systems introduce or aggravate unreliability and inefficiency in the nonlocal supply chain. They find, for example, that distant suppliers deliver far less frequently as compared to local suppliers, that only local suppliers are able to deliver just-in-time, and that the feedback and response loops tend to be slower among firms located a significant distance apart. Taken individually, just-in-time delivery, low inventories, and quick-response feedback loops are important competitive strategies; taken together, they are key drivers of the lean production system and can create dynamic gains in quality and competitiveness. Thus, poor transportation systems serve as a major obstacle in firms' efforts at implementing—and realizing dynamic gains from—competitive strategies such as lean production and supply chain management. This finding stands in contrast to much of the literature on lean production in the auto industry. These studies have found that distance from—or, conversely, proximity to—suppliers does not help explain differences in inventory levels and “leanness” at different assembly plants (Lieberman et al., 1995; Womack et al., 1990). The emerging geography of production in countries such as the United States appears to support such an argument and suggests that distance is not a primary concern for auto firms. In the United States, newer assembly and supplier plants (i.e., those built after 1980) have been located outside the traditional auto center in southeast Michigan and in communities that were not traditionally associated with the auto industry (Rubenstein, 1992). These investments have been dispersed in communities along the I-65 and I-75 corridor. Ohio is the only state that has been able to attract two assembly plants, and many suppliers have chosen to locate outside an “ideal” JIT distance of 150 km from the assembly plants they serve (Rubenstein, 1992). The difference between the above findings—based largely on research in advanced industrialized economies—and my observations can be explained as follows. Within India, the poor road infrastructure means that the transit time for road freight is both longer and more unpredictable as compared to, say, the United States and Europe. The excellent road and rail infrastructure for freight in the United States and Europe reduce the importance of proximity in their auto industries, while the terrible infrastructure in India makes proximity crucial to implementing just-in-time production in the Indian auto industry. This is also the reason why assemblers in India, unlike those in the United States, are selecting locations with a significant existing supplier base, clustering with other assemblers, and pushing suppliers to relocate in close proximity to their own assembly plants. Poor transportation, combined with the logic of lean production, is determining the geography of production in the Indian auto industry. What are the wider implications of this analysis of a particular industry (automobiles) in a particular developing country (India)? First, it argues for the reintroduction of the infrastructure variable into the debates on economic geography, industrial districts, globalization, and industrial competitiveness. It highlights how physical infrastructure can influence firm level competitive strategies, the nature of interfirm networks, and the geography of production. These effects combined with its more intuitively obvious impacts on production costs and efficiency make infrastructure a critical variable influencing industrial performance. Second, this study suggests that there is a need to resurrect the old concept of external economies in transport and infrastructure analysis, and to broaden the set of direct cost variables with which we work. Recent literature and practice takes far too narrow a view of the benefits and costs that infrastructure creates. By relying on easily quantifiable and narrowly defined proxy indicators such as freight costs and vehicle operating costs we may be making significant errors in identifying and selecting transportation investments and projects. Indeed, we may be underinvesting in precisely those types of infrastructure projects that are worthy of public investment—those that create large external economies and contribute more significantly toward enhancing industrial development and performance.