While the information technology (IT) literature is mixed regarding the direct benefits of eBusiness technologies on performance, the impact of such technologies on supply chain practices remains largely an unexplored area of research. We hypothesize that while there may be no direct benefit of eBusiness technologies on performance, these technologies might support customer integration and supplier integration in the supply chain, which in turn might impact operating performance.To examine our hypotheses, we collected data from respondents who focused their responses to a single major product the process that manufactures it, a significant customer, and an important supplier. Our analyses showed that there was no direct benefit of eBusiness technologies on performance; however these technologies supported customer integration and supplier integration. Further, supplier integration was found to positively impact cost, quality, flexibility, and delivery performance; however there was no relationship between customer integration and performance. Consequently, there is a relationship between eBusiness technologies and supplier integration that leads to better performance. Further, there is an interactive effect between customer integration and supplier integration that supports the notion that firms that have both forms of integration, supported by eBusiness technologies, significantly outperform the others. #

This research examines whether investments in advanced manufacturing technologies (AMTs) such as flexible manufacturing systems (FMS), computer aided design (CAD), computer aided manufacturing (CAM), robotics, etc., are more likely to lead to improved performance if they are supported by improvements in the manufacturing infrastructure of the company. This question is evaluated using data gathered from 202 manufacturing plants chosen from industries generally considered to have relatively high investments in technology. Multiple item scales are developed and adapted from sources in the literature to measure investments in technology, infrastructure, and the performance of the plant. Evidence supporting the reliability and validity of these scales is provided. Hierarchical regression is used to analyze the relationship between technology, infrastructure, and performance. The results suggest that there is an important interaction between the adoption of advanced manufacturing technologies and investments in infrastructure. Firms that invest in both AMTs and infrastructure perform better than firms which only invest in one or the other. Separate analyses on sub‐samples of firms with the highest and lowest investments in AMTs show that infrastructural investments have a stronger relationship with performance in the high investment group. Thus, the data indicate that infrastructural investments provide a key to unlocking the potential of advanced manufacturing technologies.

This multiple case study explores the reaction strategies suppliers use to respond to short-term dynamics of schedule changes in build-to-order supply chains. We examine the relationship and supply chain processes between a notebook computer manufacturer and five component suppliers. Two distinct reaction strategies emerge from these five buyer-supplier dyads. The ''reduce uncertainty'' strategy emphasizes supply contracts with a high degree of restrictiveness, relatively infrequent schedule revisions, and a high level of form postponement. The ''cope with uncertainty'' strategy emphasizes flexible supply contracts, relatively frequent schedule revisions, and low levels of form postponement. Eight propositions are formulated to understand the linkage between a supplier's power, its short-term process flexibility, and the elements of its reaction strategy. The paper concludes by proposing future research directions. #

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

In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg [1,2] is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.