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Abstract

This article presents a technical approach to acquiring quality, real-time decision-making information within organizations and illustrates this approach with an extended case study. Using relational model bases for real-time, operational decision making in organizations facilitates a transition to dynamic (vs. forecast-driven) resource allocation decisions. These and related systems offer development of a new generation of DSS applications which can be applied to extend preemptive decision making across many industries. This approach is illustrated through a description of a detailed conceptual case (scenario) pertaining to its application in agribusiness. This approach to decision making can be viewed as an extension of well-known techniques pertaining to DSS but also represents the opportunity to address problems not amenable to traditional post hoc analysis. Researchers can learn from the accumulated knowledge pertaining to DSS but can also examine innovations that push forward into new territories. The article presents and discusses a variety of emergent research questions prompted by the application of these technologies in the business environment.

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