Support Systems Research Research Articles

Ranking institutional contributions to decision support systems research

This research investigates the types and contributions of DSS research conducted by major MIS doctoral institutions in the U.S. and Canada. The primary data for this study were gathered from a total of 692 citing articles in the DSS area over the past 20 years (1971-1990) and the database file of cited references that consists of a total of 15,030 records taken from the 692 citing articles.This research ranks 85 MIS doctoral institutions in the U.S. and Canada in terms of their contributions to decision support systems research during the period of 1971 through 1990 using a citation analysis. Among those doctoral institutions, three universities are identified as leading DSS research schools: MIT, the University of Minnesota, and the University of Texas-Austin.

Editorial Notes

Free AccessAboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked InEmail Go to SectionFree Access HomeInformation Systems ResearchVol. 4, No. 4 Editorial NotesJohn Leslie KingJohn Leslie KingPublished Online:1 Dec 1993https://doi.org/10.1287/isre.4.4.291 Back to Top Next FiguresReferencesRelatedInformationCited ByThe Philosopher's CornerACM SIGMIS Database: the DATABASE for Advances in Information Systems, Vol. 52, No. 2Knowledge Management and the Creation of Business Value10 December 2015 | Journal of Computer Information Systems, Vol. 55, No. 4Design and Behavioral Science Research in Premier IS Journals: Evidence from Database Management ResearchThe Early Years of ISR: Recollections of the EditorsE. Burton Swanson, John Leslie King, Izak Benbasat, Chris F. Kemerer, 1 December 2010 | Information Systems Research, Vol. 21, No. 4Reconstituting knowledge managementJournal of Knowledge Management, Vol. 12, No. 3An Analysis of Diversity in Electronic Commerce Research8 December 2014 | International Journal of Electronic Commerce, Vol. 12, No. 1Analyzing e-government research: Perspectives, philosophies, theories, methods, and practiceGovernment Information Quarterly, Vol. 24, No. 2A metaphor for knowledge management: explicit islands in a tacit seaJournal of Knowledge Management, Vol. 11, No. 1The subject of information systemsThe five‐tier knowledge management hierarchyJournal of Knowledge Management, Vol. 10, No. 1A work system view of DSS in its fourth decadeDecision Support Systems, Vol. 38, No. 3Research Commentary: The Next Wave of Nomadic ComputingKalle Lyytinen, Youngjin Yoo, 1 December 2002 | Information Systems Research, Vol. 13, No. 4Information systems as technological innovationInformation Technology & People, Vol. 13, No. 3The paradigm is dead, the paradigm is dead…long live the paradigm: the legacy of Burrell and MorganOmega, Vol. 28, No. 3Is information system a science? an inquiry into the nature of the information systems disciplineACM SIGMIS Database: the DATABASE for Advances in Information Systems, Vol. 31, No. 3Is information systems a science? an inquiry into the nature of the information systems disciplineACM SIGMIS Database: the DATABASE for Advances in Information Systems, Vol. 31, No. 2Ethnic diversity in ISACM SIGCPR Computer Personnel, Vol. 20, No. 3Colonial SystemsJaana Porra, 1 March 1999 | Information Systems Research, Vol. 10, No. 1The subject of information systemsDecision support systems research: Reference disciplines and a cumulative traditionOmega, Vol. 23, No. 5Limitations of information systems theory and practice: a case for pluralismKnowledge management systems: emerging views and practices from the fieldThe Identity, Dynamics, and Diffusion of MIS Volume 4, Issue 4December 1993Pages 291-382 Article Information Metrics Information Published Online:December 01, 1993 © 1993 INFORMSCite asJohn Leslie King, (1993) Editorial Notes. Information Systems Research 4(4):291-297. https://doi.org/10.1287/isre.4.4.291 PDF download

Leading U.S. universities and most influential contributors in decision support systems research (1971–1989) a citation analysis

This paper identifies the most influential contributors in the DSS area in the U.S., examines their contributions, and reviews the institutional publishing records at the leading U.S. universities, which are actively publishing DSS research. To measure the influence/contributions of leading universities and contributors, we used the bibliographic citations of the publications on the specific DSS applications. The critical assumption of this study is that “bibliographic citations are an acceptable surrogate for the actual influence of various information sources.” (M.J. Culnan, Management Science 32, 2, feb 1986, 156–172) This paper identifies thirty-two leading U.S. universities with eighty-one of their affiliated members and twenty three most influential researchers. Among the leading U.S. universities identified, two universities are truly outstanding: The University of Texas-Austin and MIT. Regardless of any types of yardsticks which may be applied to measure their contributions, these two universities may be recognized as centers of excellent DSS research in the U.S.A. in terms of the number of research publications, the number of total citation frequencies, and the number of active researchers in the DSS related areas.

The example of the Unicorn: A knowledge-based approach to scientific creativity and the growth of knowledge

In the course of researching the question ‘What does it mean for knowledge to grow?’, the author has developed a large and unique compendium of components, some of which are knowledge systems that serve as research and creativity support systems. The self-modifying, self-effecting creative process and the results of developing and working with these systems, using novel methods and drawing on eclectic sources, is discussed.

A decision support system for aquaculture research and management

A decision support system was developed to facilitate the collection, manipulation and analysis of physico-chemical and biological data generated in aquaculture research. The Aquaculture Research and Monitoring System (ARMS) consists of integrated hardware and software packages that facilitate the operational decision making process in aquaculture research via a user-friendly, visual interactive-modelling interface. ARMS provides a management system for the capture and manipulation of real, online environmental data sampled by a data logger and a modelling system allowing the user to input their own judgements in the analytical decision-making process. These judgements may be qualitative as well as quantitative. The user is able to assign importance values to the various environmental parameters and management practices that constitute variables in experiments and ARMS determines the probability of specific experimental outcomes. Thus, ARMS may be used to examine the validity of the assumptions used in past experiments and, more importantly, to simulate new experiments before actual implementation. ARMS also has a demonstration capacity that may be used to train other managers or students. The software is implemented on an IBM AT using routines written in Turbo Pascal and macros written for Minitab and Microsoft Excel. The design of ARMS stresses modular independence and thus the decision process and data collection and management are not necessarily coupled to specific experimental data and may be modified to suit the requirements of other uses such as day-to-day management of commercial aquaculture operations.

The Emergence of Artificial Intelligence as a Reference Discipline for Decision Support Systems Research

ABSTRACTIt is timely and appropriate to examine both philosophical and pragmatical issues associated with formalizing the adoption of artificial intelligence as a reference discipline for decision support systems research. This paper reflects on where we were when the first special issue of Decision Sciences on expert systems and decision support systems was published, addresses the dynamics of what has taken place subsequent to the publication of that first special issue, sets forth a proposition to stimulate ongoing dialog with respect to synergies between the decision support system research agenda and the research agenda of the artificial intelligence discipline, and demonstrates how the papers appearing in this follow‐up special issue of Decision Sciences are representative of an emerging, challenging, and exciting new decision support systems era.

The role of quantitative models in management accounting education

The management accounting curriculum in undergraduate and professional level courses consists largely of explanations and discussions of a variety of quantitative models. This unanimity as to the appropriate content of the curriculum is not easy to reconcile with an apparent absence of theory closure in management accounting. However, this paper does not attempt to deductively derive a proposed new curriculum from any particular theory; such an exercise might be considered premature while disagreement over theory still prevails. Instead, the paper acknowledges that quantitative modelling is the preferred approach to management accounting education, and from this starting point two related questions are addressed. First, can management accounting education learn anything about the effective use of models in the curriculum from the experience of other related disciplines such as economics, operations research, and decision support systems? Second, what are the possible justifications for accepting the use of quantitative modelling as an approach to management accounting education, and what are the implications for the discipline of accepting each of these justifications?.

Negotiation support systems: roots, progress and needs

Abstract. This paper identifies game theories and social behavior science as important roots for negotiation support systems (NSS) research. As these are not typically cited in the NSS literature, summary reviews of them are provided with indications of their relevance to NSS study. On the other hand, neither offers a sufficiently general-purpose formal model of negotiation that could serve as a backbone for NSS research. A survey of that research is provided, indicating that prugress to date has been somewhat eclectic and devoid of such a model. Our central contention is that a theoretical foundation for NSS study is much needed. Desirable characteristics of a suitable negotiation model are identified as guidance for future research that will aim to devise (and subsequently apply and test) such a model.

The space exploration initiative: A challenge to advanced life support technologies: Keynote presentation

President Bush has enunciated an unparalleled, open-ended commitment to human exploration of space called the Space Exploration Initiative (SEI). At the heart of the SEI is permanent human presence beyond Earth orbit, which implies a new emphasis on life science research and life support system technology. Proposed bioregenerative systems for planetary surface bases will require carefully designed waste processing elements whose development will lead to streamlined and efficient systems for applications on Earth.

The role of artificial intelligence in understanding the strategic decision-making process

A survey is given which focuses on research issues involving strategic planning and artificial intelligence (AI), including the nature of the formulation task, cognitive studies of strategic planners and computer-based support for strategic planning. The author reviews the research to date, and argues that, like traditional decision support systems (DSS) research, much of the potential for future research in this area lies in modeling the ill-structured, early stages of the strategic decision making process namely, the strategic intelligence analysis and the issue diagnosis. Therefore, he discusses a specific model-based approach to the study of these early stages. Research in artificial intelligence-including investigations into diagnosis and situation assessment, analogical reasoning, plan recognition, nonmonotonic reasoning and distributed intelligence, among others-can be used to build models of strategic decision making that help researchers in better understanding this traditionally unstructured activity.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The use of assessments of British university teaching, and especially research, for the allocation of resources: A personal view

The paper is in three parts: 1. Background; demography of student numbers and age distribution of faculty in the 80s and 90s; the dual support system for academic research by the University Grants (Funding) Committee (Council) and Research Councils, the funding formula; Economic and Social Research Council sanctions on departments too few of whose doctoral students submit on time. 2. UGC/UFC subject reviews and research rating exercises. Criticisms of correlation of assessed quality with departmental scale; difficulties of mixing input and output indices; bibliometrics and the apparent weighting of prestige journals; the role of consultation with learned societies such as the Royal Economic Society. 3. Incentive issues and their transmission to individuals. The balance between pure and applied research.

The Space Exploration Initiative: a challenge to advanced life support technologies: keynote presentation.

President Bush has enunciated an unparalleled, open-ended commitment to human exploration of space called the Space Exploration Initiative (SEI). At the heart of the SEI is permanent human presence beyond Earth orbit, which implies a new emphasis on life science research and life support system technology. Proposed bioregenerative systems for planetary surface bases will require carefully designed waste processing elements whose development will lead to streamlined and efficient and efficient systems for applications on Earth.

A Longitudinal Study of the Impact of Group Decision Support Systems on Group Development

Abstract:This paper reports on a study aimed at integrating an important but neglected behavioral issue-group development-into group decision support systems (gdss) research. Group development is based on the fact that most groups have a past and a future, and this affects group outcomes. However, most gdss studies have investigated only a single group session. This study examined the behavior of groups using a gdss over multiple sessions.The study reported in this paper specifically examined the following two questions: (1) does computer support affect the development of decision-making groups? and (2) do the patterns of development differ over time between computer-supported and manual groups? These two questions were studied using a two-factorial repeated measures research design. Results showed significant differences in development patterns between computer-supported groups and manual groups in terms of conflict management and degree of cohesiveness. Mter adapting to gdss, computer-supported groups d...

Special Issue: Decision Support and Knowledge-Based Systems

Robert W. Blanning is Professor of Management Information Systems at the Owen Graduate School of Management at Vanderbilt University. He holds a B.S. in Physics from the Pennsylvania State University, an M.S. in Operations Research from the Case Institute of Technology, and a Ph.D. from the University of Pennsylvania, specializing in operations research and management information systems. He has been a member of the faculties of the School of Business at New York University and the Wharton School at the University of Pennsylvania. His teaching and research interests are in model management systems, information economics, and the management applications of artificial intelligence. He has published in Management Science, Decision Sciences, Communications of the ACM, Naval Research Logistics Quarterly, Decision Support Systems, Information and Management, Omega, Policy Analysis and Information Systems, International Journal of Policy and Information, Human Systems Management, Journal of Information Science, Long Range Planning, and Technological Forecasting and Social Change. He has presented papers at the National Computer Conference, the International Conference on Decision Support Systems, the Hawaii International Conference on Systems Sciences, the International Workshop on Expert Database Systems , and the International Workshop on Artificial Intelligence in Economics and Management. He is a member of the Board of Editors of JMIS, a member of the Editorial Boards of Decision Support Systems and Information Systems Research, and Associate Editor of Information and Decision Technologies and in the Decision Support Systems Department of Management Science.

Application and Research Areas for Hypertext in Decision Support Systems

:Review of decision support system (DSS) research and applications frameworks and literature review of hypertext research reveals many areas where further work may make a valuable contribution in the application of hypertext technology to DSS. These areas are discussed as they relate to user characteristics, decision and problem characteristics, situational and organizational factors, and technological factors. Some research topics that appear to be worthy of further investigation include hypertext’s support of the human brain’s hemispheric specialization, its isomorphism with generalized problem-solving paradigms such as the state-space approach, its potential to support collaborative work and group DSS, and many technological issues related to the appropriate content, structure, and representation of hypertext networks. In addition, hypertext may be used as a DSS research vehicle to simulate and study various user interface techniques and as a process tracing laboratory. Hypertext offers a great deal of promise as a powerful component of future DSS environments.

Decision support system research at Leicester Polytechnic

Leicester Polytechnic Library has recently completed a research programme for the British Library Research and Development Department into the application of office automation and decision support systems in particular to the library environment. Decision support systems (DSS) can seen as an extension of the idea of management information systems by providing a broader range of information in a more flexible and interactive way. There is a wide range of computer software claiming to offer decision support ranging from spread‐sheets at one end of the spectrum to knowledge based, or expert DSS programs, with proportional variations in cost. For this reason a definition of a DSS is difficult to establish but the major components of a system are generally considered to be:

Computer-Assisted Staffing Systems: The Use of Computers in Implementing Meta-Analysis and Utility Research in Personnel Selection

Recent advances in methods of cumulating research results across studies (i.e., meta-analysis) and related advances in utility research have rapidly increased our knowledge about the usefulness of personnel selection procedures in identifying capable job applicants. This paper describes two computer-based systems, one designed to disseminate the existing knowledge base on personnel selection, and the second to expand this knowledge base. The dissemination system, called the Staffing Decision Support System (SDSS), is a computer-based information system designed to assist staffing decision makers in answering two questions: 1) What is the best personnel selection procedure for identifying capable applicants for a job 2) What is the economic value of a personnel selection procedure? This paper will summarize the research which forms the basis of the SDSS, and explain the capabilities of the system. This paper will conclude with a description of the research support system designed to update and expand the SDSS system.

Computer-Aided Deliberation: Model Management and Group Decision Support

The paper highlights principles of group process as an important component of group activities in planning and policy making. The management of a variety of models utilized in organizational planning is discussed. Descriptions of the features and functions of the hardware and software environment, along with scenarios for use of the environment, illustrate critical issues in group deliberation. A particular model, stakeholder identification and assumption surfacing, is used to illustrate aspects of model management and planning process implementation. Findings of the group decision support system (GDSS) research are discussed in terms of anonymity of participation, facility design, need for multiple public screens, use of knowledge and data bases, communication network speed, methodological approach, software design, mixing of manual and electronic sessions, group size, composition, satisfaction of the users and model management systems. In general, the research results from experiments and case studies reflect our findings from observation of 40 groups.

On-Line Research-Support Systems

This article provides an overview of trends in electronic communication among research scientists, with particular attention to the Experimental Research in Electronic Submission (EXPRES) initiative at the National Science Foundation (NSF). NSF is an independent agency of the federal government authorized to initiate and support basic scientific research and to strengthen the nation's scientific research potential and education in the sciences. EXPRES is a conceptual and technological project attempting to facilitate the exchange of compound scientific documents between research sites possessing different kinds of computer hardware and software. In its most fundamental aspect, EXPRES is about scientific collaboration as well as communication. This dual process is exemplified in the development of basic research proposals by scientists at universities, and the subsequent procedures by which such proposals are submitted, evaluated for scientific merit by the scientists' peers, and ultimately funded or declined. EXPRES holds the promise of not just streamlining but also enhancing the support systems by which today's scientific research is carried out.

Process Tracing Methods in Decision Support Systems Research: Exploring the Black Box

An overview is provided of the appficability to DSS research of process tracing methodologies in general and verbal protocol analysis in particular. Rationale is developed for why process tracing methods are an important addition to the inventory of methodologies available to researchers, stressing the need to explore the black box of decision processes. A variety of process tracing methods are presented, along with their relative strengths and weaknesses. Verbal protocol analysis is discussed as a particularly promising method for use in DSS research. The nature of verbal protocols is outlined and methods for analysis are reviewed. The criticisms of this method and the controversy surrounding its use are discussed, and an assessment of the validity of these criticisms is provided. Finally, areas of DSS research in which protocols may prove valuable are identified and relevant studies are examined.