Abstract
This paper reports an attempt to explore the relationships between logistics complexity and supply chain management (SCM) objectives and decision areas in large manufacturing companies operating in Brazil. Literature review is conducted, followed by survey research data (using a sample of 108 large companies operating in Brazil) analysis using cluster analysis, factor analysis and binary logistic regression. Results suggest that the level of logistics complexity of companies is a driver of management choices in supply chain objectives and decision areas, confirming our initial proposition that a contingency approach for supply chain management would be more appropriate than the "best practice" one. At the end of the article some further conclusions are drawn and opportunities for further research are discussed.
Highlights
The contingency approach to management basically argues that there is no one best way to manage
The variables considered during the cluster analysis were the company’s Gross revenue, Number of employees, Number of employees involved in supply chain management activities, Number of suppliers, Number of active clients, Number of active stock keeping units (SKUs), Number of product launchings per year, Number of distribution centers, and Number of orders per day
This study contributes to existing contingency research in operations management by unveiling the existence of significant relationships between logistic complexity and supply chain management decision areas and objectives
Summary
The contingency approach to management basically argues that there is no one best way to manage. Central to the contingency approach is the proposition that the structure and process of an organization must fit its context (Drazin and Van de Ven, 1985). This is in contrast with the “best practice” paradigm (Voss, 1995), which is reflected in the proliferation of many management practices such as total quality management, lean production, continuous replenishment, and six sigma, many times fueled by consulting firms, specialized in selling “best ” or “world class” practices that are often advocated as being universally applicable regardless of context and conditions. There are numerous reports in the literature showing a positive relationship between the adoption of best practice and performance After years of an emphasis on developing and demonstrating the value of practices such as collaborative forecasting (CF), collaborative
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