DEVELOPING AND IMPLEMENTING DECISION SUPPORT SYSTEMS: A CRITIQUE AND A CHALLENGE¹

Abstract

Computer‐based models together with their interactive interfaces are typically called decision support systems. DSSs are interactive computer‐based information providers. The common objective of all DSSs, regardless of the frameworks, methodologies, or techniques used, is to provide timely information that supports human decision makers ‐ at whatever level of decision making. The informational needs of the decision making process are the key considerations that motivate the development of DSSs. The growth of DSS development and use has been substantial. In spite of this impressive growth, computer‐aided decision support systems can still be improved and made more useful to those they are intended to support. Researchers and practitioners, and indeed the computer industry, continue to identify ways of doing this. This paper reviews some of these needs and opportunities by focusing on the process of successful DDS development and implementation. The paper outlines an approach and some guidelines for developing DSSs. The approach emphasizes and requires considerable interaction between the DSS developers (analysts) and the DSS users (decision makers). This interaction and feedback is required throughout the entire DSS building, testing and evaluation (debugging), and implementation processes. The paper concludes by identifying some research needs and opportunities affecting DSS development and effective use.

A DSS generator for multiobjective optimisation of spreadsheet-based models

“…Decision Support Systems (DSS), and model-driven DSS in particular (Power and Sharda, 2007), that could be defined simply as "computer-based models together with their interactive interfaces" (Loucks, 1995), aim to support the user in addressing and solving particular unstructured problems in a timely manner (Scott Morton, 1971). Although there is no widely accepted definition of DSS, these systems can integrate a number of technologies (tools), including optimisation and simulation models, geographic information systems, artificial intelligence algorithms, data-mining tools, expert or knowledge-based systems, statistical and graphing tools, etc.…”

“…Although there is no widely accepted definition of DSS, these systems can integrate a number of technologies (tools), including optimisation and simulation models, geographic information systems, artificial intelligence algorithms, data-mining tools, expert or knowledge-based systems, statistical and graphing tools, etc. From the early beginnings when computers were utilised as mere calculators to the so-called 'fourth generation models', which are widely used commercial software that includes databases, models and policy analysis instruments (Abbott, 1991), water management practice has benefited from the development of DSS (Loucks, 1995).…”

From Design to Application of a Decision-support System for Integrated River-basin Management

“…This task is clearly different from comprehensive analysis of a management strategy by a person who is to provide a river manager with detailed information. In the past DSS have been defined as computer-based tools that assist managers with solving ill-structured problems (Morton 1971;Sprague and Carlson 1982;Loucks 1995). Although the analysis of different solutions to a problem is an obvious purpose, various other uses for a DSS have been identified as well (Loucks 1995;Walker 2002;Janssen et al 2006):…”

“…It can be used to support the planning and implementation of measures (Giupponi 2007;Volk et al 2007) and the communication between the stakeholders and between the researchers involved. The different purposes of a DSS for IRBM include: analysis of different management alternatives, communication, education, and knowledge management (Loucks 1995;Hahn and Engelen 2000;Zhu and Dale 2000;Westmacott 2001;De Kok and Wind 2003;Legris et al 2003;Maurel et al 2007;Giupponi 2007). During the last decades a variety of tools were developed to assist water managers with strategic planning tasks (Berlekamp et al 2005;Giupponi 2007).…”

Multi-indicator assessment of water environment in government environmental auditing

“…Bain et al (2000) reviewed the assessment and evaluation methods for aquatic ecosystem protection and restoration. These methods include the EPT index (Bode and Novak, 1995;Novak and Bode, 1992), the index of biotic integrity (Karr, 1991;Karr and Dudley, 1981), the watershed habitat evaluation and biotic integrity protocol (Goforth, 1999) and the integrated river aquifer simulation model (Loucks, 1995;Loucks et al, 1996). It should be emphasized that most of the above mentioned indicators focused on state evaluation and quality description.…”