Decision support systems (DSS) is the part of the information systems (IS) discipline that is focused on supporting and improving managerial decision making. The field covers personal DSS, group support systems, negotiation support systems, intelligent DSS, knowledge management-based DSS, executive information systems/business intelligence, and data warehousing. Our long-term project on the intellectual foundations of DSS research has revealed a conservative field that needs to re-orient its research agendas to achieve greater quality and impact. This paper furthers this project and explores what we feel may be at the core of the field’s problems — its methodological and theoretical foundations. A number of recommendations for improving the quality and relevance of DSS research are made. As DSS is a significant proportion of IS research, the lessons and recommendations from this study may be of use to all IS researchers.
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Decision support systems (DSS) is the part of the information systems (IS) discipline that is focused on supporting and improving managerial decision making. Essentially, DSS is about developing and deploying IT-based systems to support decision processes. It is perhaps the most buoyant area of contemporary IS practice (Graham, 2005) and the decisions made using these systems can fundamentally change the nature of an organisation. To help define the field, Arnott and Pervan (2005) presented a history of DSS that focused on the evolution of a number of sub-groupings of research and practice. These DSS types are:
Personal DSS: usually small-scale systems that are normally developed for one manager, or a small number of independent managers, for one decision task;
Group Support Systems: the use of a combination of communication and DSS technologies to facilitate the effective working of groups;
Negotiation support systems: DSS where the primary focus of the group work is negotiation between opposing parties;
Intelligent DSS: the application of artificial intelligence techniques to DSS;
Knowledge Management-based DSS: systems that support decision making by aiding knowledge storage, retrieval, transfer and application by supporting individual and organisational memory and inter-group knowledge access;
Executive Information Systems/Business Intelligence: data-oriented and model-oriented DSS that provide reporting about the nature of an organisation to management; and
Data Warehousing: systems that provide the large-scale data infrastructure for decision support.
This paper arises from a long-term project investigating the intellectual foundations of the DSS field. The foundation of the project is the content analysis of 1,093 DSS articles published in 14 major journals from 1990 to 2004. The first, descriptive, results were presented in Arnott et al (2005b). Pervan et al (2005) presented a critical analysis of group support research from 1990 to 2003; Arnott et al (2005a) analysed the funding of all types of DSS research; Arnott and Pervan (2005) analysed published DSS research using a number of dimensions including journal publishing patterns, research paradigms and methods, decision support focuses, and professional relevance; Pervan and Arnott (2006) analysed data warehousing and business intelligence research; and Dodson et al (2006) investigated the role of the client and user in DSS research.
Our analysis of DSS research has revealed a conservative field that needs to re-orient its research agendas to achieve greater quality and impact. The practical relevance of DSS research is declining and it is underrepresented in ‘A’ journals (Arnott and Pervan, 2006). This means that it faces problems with both its key constituencies of industry and academe. Our paper addresses what we feel may be a major cause of these problems — the theoretical and methodological foundations of the field.
The paper is structured as follows: first, the project’s research method and design is outlined. This is followed by an analysis of the article sample and discussion in terms of research paradigms, research design and methods, judgement and decision-making foundations, and discipline coherence. As DSS is a significant proportion of IS research, the lessons and recommendations from this study may be of use to all IS researchers.