The Intellectual Structure of Decision Support Systems Research (1991–2004)

2010 ◽  
pp. 49-68 ◽  
Author(s):  
Sean Eom
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Intellectual Structure ◽  
Systems Research

The Changing Structure of Decision Support Systems Research

2010 ◽  
pp. 318-342
Author(s):  
Sean Eom
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Group Support Systems ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Model Management ◽  
Intellectual Structure ◽  
Research Areas ◽  
Systems Research

This chapter extends an earlier benchmark study (Sean B. Eom, 1995) which examined the intellectual structure, major themes, and reference disciplines of decision support systems (DSS) over the last two decades (1960-1990). Factor analysis of an author cocitation matrix over the period of 1990 through 1999 extracted 10 factors, representing 6 major areas of DSS research: group support systems, DSS design, model management, implementation, and multiple criteria decision support systems and five contributing disciplines: cognitive science, computer supported cooperative work, multiple criteria decision making, organizational science, and social psychology. We have highlighted several notable trends and developments in the DSS research areas over the 1990s.

The Intellectual Structure of Decision Support Systems Research (1969-1989)

2010 ◽  
pp. 284-317
Author(s):  
Sean Eom
Keyword(s):  
Cluster Analysis ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Optimal Number ◽  
Intellectual Structure ◽  
Dimensional Scaling ◽  
And Cluster Analysis ◽  
Author Cocitation ◽  
Multi Dimensional Scaling

This is the capstone chapter that shows how the concepts, tools, and techniques discussed in each of the previous chapters can be applied in conducting author cocitation analysis using a real data in the DSS area. The step-by-step procedures are shown in detail from the preparation of data file in Excel format and importing the file to the SAS system for multivariate statistical analysis. This chapter also guides the readers through the process of analyzing the results of principal components analysis, cluster analysis, and multi-dimensional scaling. The chapter also shows how to apply different criteria to select the optimal number of factor solutions, cluster solutions, and evaluating the acceptability of multi-dimensional scaling outputs. This chapter reports part of the intellectual structure of the DSS field by means of an empirical assessment of the DSS literature over the period 1969 through 1989. Three multivariate data analysis tools (factor analysis, multidimensional scaling, and cluster analysis) are applied to an author cocitation frequency matrix derived from a large database file of comprehensive DSS literature over the same period. Four informal clusters of decision support systems (DSS) research subspecialties and a reference discipline were uncovered. Four of these represent DSS research subspecialties—foundations, model/data management, user-interface/individual differences, and group support systems. One other conceptual grouping defines a reference discipline of DS—organizational science.

A Critical Analysis of Decision Support Systems Research Revisited: The Rise of Design Science

2014 ◽  
Vol 29 (4) ◽  
pp. 269-293 ◽  
Author(s):  
David Arnott ◽  
Graham Pervan
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Critical Analysis ◽  
Support Systems ◽  
Design Science ◽  
Statistical Hypothesis ◽  
Business Analytics ◽  
Statistical Hypothesis Testing ◽  
Systems Research

In 2005 the Journal of Information Technology article ‘A critical analysis of decision support systems research’ analyzed 1020 decision support systems (DSS) articles from 1990 to 2003. Since 2003 business intelligence (BI) and business analytics have gained popularity in practice. In theory and research the period since 2003 has seen a change in the decision-making theory orthodoxy and the codification and acceptance of design science. To investigate the changes in the DSS field, a number of expectations were derived from previous literature analyses. These expectations were assessed using bibliometric content analysis. The article sample to 2010 now includes 1466 articles from 16 journals. The analysis of the expectations yields mixed results for the DSS field. On the negative side, there has been an overall decline in DSS publishing, the relevance of DSS research published in journals to IT professionals has declined, and the rigor of DSS research designs has not improved. On the positive side, there has been improvement in relevance to managers, grant funding of DSS research has increased, there has been a positive shift in judgment and decision-making foundations, BI publishing has increased, and group support systems publishing has reduced to a more balanced level. An important result from the analysis of the last 7 years of DSS research is the significant increase in DSS design-science research (DSR) to almost half of published articles. It is clear from the analysis that DSS is undergoing a transition from a field based on statistical hypothesis testing and conceptual studies to one where DSR is the most popular method.

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