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ABSTRACTSupply chain management is a central and important area for academic research due to its impact on firms competing in today's global economy. Managing the flow of materials from supply sources to the ultimate customer represents a major challenge for today's managers. To assist managers, the concept of supply chain management has been adopted by many business leaders as an important way to assist in designing, planning, and controlling the network of facilities and tasks that comprise the many stages of the supply chain. In turn, the flow of academic research in the area has increased to provide a better set of guidelines for effective implementation and execution.This article sets the stage for recently completed research concentrating on supply chain management issues. First, a definition of supply chain management is provided and compared to recent usage in this area and logistics management. Also, a framework is provided that structures this dynamic and complex management task. Second, a review of past research is presented to illustrate the many paths supply chain management has traveled, and important contributions to supply management understanding and decision making. Third, recently completed research articles are introduced that have been selected to be part of this special issue of Decision Sciences. And fourth, future research directions for supply chain management that need to be pursued by interested investigators are discussed.

ABSTRACTThis teaching brief describes an engaging, in‐class exercise that introduces genetic algorithms as well as advanced Excel functions and capabilities by modeling the familiar Sudoku puzzle. Student groups are first asked to manually solve a given puzzle and then translate that solution methodology to a spreadsheet model. This exercise can be used to build classroom community and as a launching point for the content area of genetic algorithms and the use of Evolutionary Solver.

PurposeThe purpose of this paper is to develop a better understanding about drivers of enterprise systems complexity (ESC), as well as its multi‐faceted conceptualization.Design/methodology/approachCase studies were conducted among German Mittelstand companies by an international research team. A grounded theory approach was followed, with the first phase of the case studies being exploratory, and the second phase being more focused.FindingsCase study findings suggest that ESC is a multi‐dimensional construct consisting of the following dimensions: seamlessness, adoption date, number of integrated subsystems, system type/composition, number of functional areas linked, and number of users. Drivers of ESC identified via the case studies include the multi‐dimensional constructs of competition, complexity of processes, complexity of products, global operations, and the firm's customer base. Grounded theory development is used to conceptualize the measures of these drivers. Founded in these exploratory observations propositions for future research are developed.Originality/valueThe research reports on the experiences of companies with enterprise systems (ES), and explores organizational factors determining system complexity; as a sampling frame Mittelstand companies in Southwest Germany are chosen, making this study one of the few exploring ES within this context. The paper also places ESC within theoretical domains, especially the STS theory. The conceptualization of ESC and its antecedents presented provides a starting point for future academic research into this area.