| This research focuses on the supply chain management (SCM) integration software decision that enables an enterprise to distribute information so that planners, forecasters, and other supply chain managers in various locations can collaborate to build a unified, integrated system. Collaboration among these groups at various organizational levels and tiers is cited as the most complicated and important part of a successful SCM implementation. Consequently, the decision to choose one form of integration software over another is very critical. Until now, there is no well-documented, structured approach to this specific decision making problem. The research here is to adapt and test the Choice Modeling technique to this very important problem in information systems and supply chain management.; The research purpose is to address the integration planning issues by using the help of industry experts to develop and test a choice decision model to predict the behavior of members within the integration chain.; First, a decision model was developed utilizing Choice Modeling and decision criteria identified through research and interviews with experts, and validated through subject matter experts in the supply chain areas. Using these experts, a set of relevant attributes was identified for incorporation into a case example for an actual decision model for investing in a discrete choice for SCM software. This method enables decision makers to structure and articulate their requirements for SCM solutions in a way that allowed them to integrate and align their decisions for supply chain information technology with their upstream and downstream partners.; The choice model and case were administered to a separate group of working professionals with MBAs and recent coursework in SCM. These participants made decisions based on seven attributes offered at two levels for sixteen different options, resulting from a fractional factorial designed experiment. The resulting data were analyzed to determine which predictors could be used in the form of attributes for decision makers in SCM integration. The results were valid and we are able to predict which attributes are significant, and at what levels. One can also accurately predict the resulting odds ratios of making one choice over another for any given attribute. |
