Identifying manufacturers' competitive priorities has long been considered a key element in manufacturing strategy research. However, relatively little effort has been devoted to measurement of these constructs in published research. In this study we develop scales for commonly accepted competitive priorities, cost importance, quality importance, delivery-time importance, and flexibility importance. We assess how well the scales capture the constructs that they represent using data collected from 114 manufacturing plants in the United States. The findings suggest that the instrument developed can provide reliable data and that the constructs measured are valid. In addition, comparisons between pairs of informants representing the same business indicate that the perceptual measures of competitive priorities are as reliable as point estimates of routine, seemingly objective information.

Process choice, a major part of operations strategy, is a key decision that links operations to business strategy. Hayes and Wheelwright, among others, argue that the emphasis given to product customization and other competitive priorities should agree with process choice. Our empirical study investigates whether firms actually link their process choice to product customization and other competitive priorities as hypothesized, and whether compatible decision patterns lead to better performance. Analysis of data collected from managers at 144 U.S. manufacturing plants shows a strong correlation between process choice, product customization, and competitive priorities. Process choice is highly related with the degree of product customization, and also with the emphasis placed on the quality and cost competitive priorities. Job shops and batch shops tend to have more product customization, higher costs, and higher quality. Some continuous flow shops use part commonality and flexible automation to achieve more customization than would otherwise be expected. Without these initiatives, customization in continuous flow shops results in weak performance.operations management, process choice, operations strategy, manufacturing strategy

Testing and cross‐validation of theories and paradigms are necessary to advance the field of manufacturing strategy. When the findings of one study are also obtained in other studies, using entirely different databases, we become more confident in the results. Replication alleviates concerns about spurious results and is one motivation for this study. We examine aspects of the tradeoffs concept, production competence paradigm, and a manufacturing strategy taxonomy framework. In regard to the tradeoffs concept, we found evidence of tradeoffs between some, but certainly not all, manufacturing capabilities of quality, cost, delivery, and customization. The relationships get sharper when controlling for process choice. For example, the tradeoff between cost and customization is particularly strong between plants that have different process choices. We find that such tradeoffs can change, or even disappear, however, once the process choice is in place. With respect to the production competence paradigm, our analysis shows a statistically significant correlation between production competence and operations performance in batch shops, but not in plants with other process choices. Finally, using variables similar to those of Miller and Roth, our data produced three similar clusters even though their unit of analysis was much more macro than ours. Controlling for process choice is consistent with the current manufacturing strategy literature that emphasizes dynamic development of capabilities within the context of path dependencies. A major argument of this strand of research is that operations decisions not only affect current capabilities, but also set the framework for development of capabilities in the future. That being the case, controlling for process choice (or other factors such as industry or markets) should contribute to the understanding of capability‐development paths adopted by different manufacturing plants. In short, we found at least partial support for each of the theories examined here, even though the theories seem on the surface to be contradictory and mutually exclusive. Controlling for process choice or other measures of dependency goes a long way in uncovering consistency across different theories and empirical studies in operations management.

There has been a great deal of interest recently in the Japanese approach to manufacturing, growing out of a concern for finding ways to reduce inventories and increase productivity. At this project's inception, its objective was to assess whether the kanban system could perform well in the manufacturing environments found in this country. Based on observations from managers visiting Japan, the project was enlarged to also assess which factors in a production environment have the biggest impact on performance---regardless of the system in use. Guided by a panel of production and inventory managers from diverse plant environments, a comprehensive list of factors thought most important to manufacturing effectiveness was constructed. The panel established low and high values for each one. These settings were considered representative of the range experienced in U.S. plant environments. The factor settings allowed a variety of representative plants to be tested with a large scale simulator. Results show that kanban, when implemented in certain environmental settings, does indeed perform exceptionally well. However, so do the more traditional systems used in the United States. Conversely, there are other plant environments in which all systems perform much worse. This suggests that the factors themselves are the keys to major improvement. Simultaneously reducing setup times and lot sizes is found to be the single most effective way to cut inventory levels and improve customer service. Shop factors of particular importance are yield rates and worker flexibility. Degree of product standardization and the product structure are also high impact factors. Less crucial than earlier believed, at least over the factor settings simulated, are inventory record inaccuracy, equipment failures, and vendor reliability. Such results suggest that the selection of a production/inventory system can be of less importance than the improvement of the manufacturing environment itself.inventory/production: operating characteristics, inventory/production: simulation, production/scheduling

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In a departure from most other empirical studies of service organizations, this study employs a lower-level unit of analysis and explores service processes with front-office or back-office orientations. Moreover, unlike past studies, no front-office process has a corresponding back-office process in our sample. The analysis of unrelated front-office and back-office processes offers a more rigorous examination of the customer contact model. The findings by and large support the premise of this model for breaking up the activities involved in a service delivery process. Our most surprising finding relates to the levers for achieving outstanding performance. The best performers among the processes with a front-office orientation emphasize capital investment, while the best performers among those with a back-office orientation embrace higher degrees of labor intensity. It appears that in order to achieve its superior performance, each process type adopts an additional design characteristic commonly attributed to the opposite process type.

This study investigates how process choice relates to production planning and inventory control decisions. We empirically examine the validity of deductively derived patterns about these types of decisions. More importantly, we look for normative insights by exploring how production planning and inventory control decisions affect operations performance. Our findings show that production line and continuous flow plants use more of a level production strategy, and carry less raw material and work‐in‐process inventory. The performance drivers for these plants, through which the operations function excels, are effective utilization of equipment, reduced finished goods inventory, and reduced setup down time. To gain forward demand visibility and batching economies, job and batch shops rely much more on backlogs in their planning process. These plants use more of a production chase strategy and position inventory lower in the bills of materials. Four performance drivers for top‐performing job and batch shops are to find ways that better anticipate customers' orders, have a more responsive chase strategy, carry less raw material or purchased inventory, and shorten production planning horizon, partly through less reliance on backlogs. It is intriguing that top‐performing plants not only do the expected things, given their choice of process, but also excel in selected dimensions—some of which fit the profile normally associated with a different process choice. To monitor and continuously improve operations, evaluation ‘scorecards’ should pay particular attention to performance drivers, which change depending on the plant's process choice.

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