UNCORRECTED PROOF ARTICLE IN PRESS 1 Past, present, and f uture of decision support technology 2 J.P. Shim a, * , Merrill Warkentin a , James F. Courtney b , Daniel J. Power c , 3 Ramesh Sharda d , Christer Carlsson e 4 a Mississippi State University, Mississippi State, MS 39762 USA 5 b University of Central Florida, Orlando, FL 32816-1400 USA 6 c University of Northern Iowa, Cedar Falls, IA 50614 USA 7 d Oklahoma State University, Stillwater, OK 74078 USA 8 e IAMSR/Abo Akademi University, DataCity B 6734, 20520 Abo, Finland 9 10 Abstract 11 Since the early 1970s, decision support systems (DSS) technology and applications have evolved significantly. Many 12 technological and organizational developments have exerted an impact on this evolution. DSS once utilized more limited 13 database, modeling, and user interface functionality, but technological innovations have enabled far more powerful DSS 14 functionality. DSS once supported individual decision-makers, but later DSS technologies were applied to workgroups or 15 teams, especially virtual teams. The advent of the Web has enabled inter-organizational decision support systems, and has given 16 rise to numerous new applications of existing technology as well as many new decision support technologies themselves. It 17 seems likely that mobile tools, mobile e-services, and wireless Internet protocols will mark the next major set of developments 18 in DSS. This paper discusses the evolution of DSS technologies and issues related to DSS definition, application, and impact. It 19 then presents four powerful decision support tools, including data warehouses, OLAP, data mining, and Web-based DSS. Issues 20 in the field of collaborative support systems and virtual teams are presented. This paper also describes the state of the art of 21 optimization-based decision support and active decision support for the next millennium. Finally, some implications for the 22 future of the field are discussed. D 2002 Published by Elsevier Science B.V. 23 24 Keywords: Decision support technology; DSS development; Collaborative support systems; Virtual teams; Optimization-based decision support 25 26 27 1. Introduction 28 Decision support systems (DSS) are computer tech- 29 nology solutions that can be used to support complex 30 decision making and problem solving. DSS have 31 evolved from two main areas of research—the theore- 32 tical studies of organizational decision making (Simon, 33 Cyert, March, and others) conducted at the Carnegie 34 Institute of Technology during the late 1950s and early 35 1960s and the technical work (Gerrity, Ness, and 36 others) carried out at MIT in the 1960s [32]. Classic 37 DSS tool design is comprised of components for (i) 38 sophisticated database management capabilities with 39 access to internal and external data, information, and 40 knowledge, (ii) powerful modeling functions accessed 41 by a model management system, and (iii) powerful, 42 yet simple user interface designs that enable interac- 0167-9236/02/$ - see front matter D 2002 Published by Elsevier Science B.V. PII:S0167-9236(01)00139-7 $ This paper is based on a panel discussion at the 30th Decision Sciences Institute Annual Meeting in New Orleans, LA. The authors were invited panelists for the Decision Support Tools session. * Corresponding authors. E-mail addresses: jshim@cobilan.msstate.edu (J.P. Shim), mwarkentin@acm.org (M. Warkentin), Jim.Courtney@bus.ucf.edu (J.F. Courtney), Daniel.Power@uni.edu (D.J. Power), sharda@okstate.edu (R. Sharda), christer.carlsson@abo.fi www.elsevier.com/locate/dsw $ Decision Support Systems 931 (2002) xxx – xxx