Measurement Issues in Decision Support Systems

Measurement Issues in Decision Support Systems

William K. Holstein (The College of William and Mary, USA and The Graduate School of Business Administration-Zurich, Switzerland) and Jakov Crnkovic (University at Albany, State University of New York, USA)
DOI: 10.4018/978-1-59140-553-5.ch336
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Abstract

The past decade has seen tremendous progress in systems for information support-flexible and adaptable systems to support decision makers and to accommodate individual needs and preferences. These model- or data-driven or hybrid systems incorporate diverse data drawn from many different internal and external sources. Increasingly, these sources include sophisticated enterprise resource planning systems, data warehouses, and other enterprise-wide systems that contain vast amounts of data and permit relatively easy access to that data by a wide variety of users at many different levels of the organization. Decision support and decision support systems (DSS) have entered our lexicon and are now common topics of discussion and development in large, and even in medium-sized, enterprises. Now that DSS is well established, attention is turning to measurement and the metrics that populate such systems.

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