Manufacturing strategy and competitive performance – An ACE analysis

In this study, we investigate the relationships between competitive dimensions of manufacturing strategy and competitive performance in two clusters. One consists of plants in countries known for their manufacturing excellence (i.e., "JUG" referring to Japan, the United States and Germany); and the other of plants in emerging manufacturing countries (i.e., "BC" referring to Brazil and China). Data from the third round of the High Performance Manufacturing (HPM) project, which is a worldwide plant-level questionnaire survey project, were used in this study. The Alternating Conditional Expectations (ACE) algorithm, which is a nonlinear statistical tool, was applied to capture nonlinear relationships among the factors. Specifically, the possession of proprietary resources and the use of manufacturing as a competitive resource exhibit negative relationships with competitive performance for BC, but positive relationships for JUG. The achievement of functional integration varies negatively with competitive performance for JUG, but positively for BC. These relationships plateau over the mid-ranges. A proactive IT posture demonstrates the most statistically significant positive relationship with competitive performance for both JUG and BC. Based on our findings in an exploratory approach, managerial implications are also discussed.

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