Measurement Issues in Decision Support Systems

View Sample PDF

Author(s): William K. Holstein (University at Albany, State University of New York, USA)and Jakov Crnkovic (University at Albany, State University of New York, USA)
Copyright: 2009
Pages: 7
Source title: Encyclopedia of Information Science and Technology, Second Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-60566-026-4.ch402

Keywords: Information Resources Management / Information Science Reference / Library & Information Science

Purchase

View Measurement Issues in Decision Support Systems on the publisher's website for pricing and purchasing information.

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 decision support systems (DSS), now often called business intelligence (BI) systems, incorporate diverse data drawn from many different internal and external sources. Increasingly, these sources include sophisticated enterprise resource planning (ERP) systems, customer relationship management (CRM) 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, DSS and BI 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.

The IRMA Community

Research IRM

Measurement Issues in Decision Support Systems

Purchase

Abstract

Related Content

IRMA Sponsors