Decision support systems evolution: framework, case study and research agenda
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Decision support systems evolution: framework, case study and research agenda David Arnott1 1
Monash University, Victoria 3800, Australia
Correspondence: Professor David Arnott, Decision Support Systems Laboratory, Monash University, PO Box 197, Caulfield East VIC 3145, Australia Tel: þ 61 3 9903 2693; Fax: þ 61 3 9903 1204; E-mail: [email protected]
Abstract Evolutionary development has been central to the theory and practice of decision support systems (DSS) since the inception of the field. Terms such as ‘adaptive’ and ‘evolutionary’ capture the organic nature of the development of a decision support system. However, the terms are rarely defined and their meaning varies widely in the research literature. The aim of this paper is to contribute to decision support systems theory by investigating and clearly specifying the nature of the evolutionary process of a DSS. Using insights from other disciplines and prior DSS research, a framework for understanding DSS evolution is developed based on the aetiology, lineage, and tempo of evolution. The descriptive validity of the framework is demonstrated by applying it to published DSS studies and to an intensive case study of DSS development. The framework and the case study findings are used to define a research agenda that is important for evolutionary DSS development. European Journal of Information Systems (2004) 13, 247–259. doi:10.1057/palgrave.ejis.3000509 Keywords: decision support systems; evolutionary development; case study
Introduction
Received: 4 October 2002 Revised: 15 April 2003 2nd Revision: 15 June 2004 Accepted: 10 August 2004 Online publication date: 28 September 2004
Decision support systems (DSS) are computer-based information systems that are designed with the purpose of improving the process and outcome of decision-making. Evolutionary development has been central to the theory of decision support systems since the inception of the field. The functionality of DSS is thought to evolve over a series of development cycles where both the client and the systems analyst are active contributors to the shape, nature, and logic of the system. Terms such as ‘adaptive’ and ‘evolutionary’ capture the organic nature of the development of a decision support system. However, the terms are rarely defined in DSS research and their meaning varies widely in the research literature. Because of the centrality of evolution to DSS theory and practice, the relative lack of research on this core concept is a major academic omission. The aim of this paper is to contribute to decision support systems theory by investigating the nature of the process of evolution of a DSS. This paper is structured as follows: first, the current theories of DSS evolution are reviewed. Theories of evolution from other disciplines that are relevant to DSS are then discussed and a framework for understanding DSS evolution that extends current theories is proposed. Case studies of DSS development from the research literature are fitted to the framework to demonstrate its desc
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