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A Multicriteria Model for the Evaluation of Intelligent Decision-making Support Systems (i-DMSS)

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Intelligent Decision-making Support Systems

Part of the book series: Decision Engineering ((DECENGIN))

Abstract

Although traditional decision-making support systems (DMSS) have been researched extensively, few, if any, studies have addressed a unifying architecture for the evaluation of intelligent DMSS (i-DMSS). Traditional systems have often been evaluated in the literature on the basis of single-outcome measures, such as decreased cost, increased profit, or improved forecasting, compared to decision making without a DMSS. In cases in which other metrics are used for evaluation, process measures are most often cited, such as increased efficiency, organizational learning, and increased speed. Previous research by the authors has shown that a multicriteria evaluation for DMSS can be provided, combining both outcome and process measures into a single metric using the analytic hierarchy process (AHP). However, the specific categories that should be utilized as evaluation measures have not been defined, and no studies have focused exclusively on categories for the evaluation of i-DMSS. This chapter explores the concept of intelligence in general, and artificial intelligence in particular, as it relates to aiding decision making. It then proposes an architecture for the evaluation of i-DMSS and applies the model to empirical systems. The results are: (1) recognition of the contribution of AI to i-DMSS; (2) identification of the criterion (or criteria) used to evaluate i-DMSS; (3) categorization of the evaluation measures; (4) an architecture for evaluation for i-DMSS; and (5) recommendation of a multicriteria model to assess i-DMSS.

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References

  • Adelman L (1992) Evaluating Decision Support and Expert Systems, John Wiley & Sons, Inc., New York, NY.

    Google Scholar 

  • Albus J, Meystel A (2001) Engineering of Mind, Wiley Series on Intelligent Systems, John Wiley and Sons, Inc., New York, NY.

    Google Scholar 

  • Boering E (1933) The Physical Dimensions of Consciousness. New York: Century.

    Google Scholar 

  • Borenstein D (1998) IDSSFLEX: an intelligent DSS for the design and evaluation of flexible manufacturing systems. Journal of the Operational Research Society 49(7): 734–744.

    Article  MATH  Google Scholar 

  • Brooks F (1996). The computer scientist as toolsmith II. Communications of the ACM, 19(3): 61–68.

    Article  Google Scholar 

  • Brown C, O’Leary D (1995) Introduction to Artificial Intelligence and expert systems. Accessed from http://accounting.rutgers.edu/raw/aies/www.bus.orst.edu/faculty/brownc/es_tutor/es_tutor.htm, on September 15, 2004.

    Google Scholar 

  • Cassaigne N, Singh MG (2001) Intelligent decision support for the pricing of products and services in competitive consumer markets. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 31(1): 96–106.

    Article  Google Scholar 

  • Chan FTS, Jiang B, Tang NKH (2000) The development of intelligent decision support tools to aid the design of flexible manufacturing systems. International Journal of Production Economics 65(1): 73–84.

    Article  Google Scholar 

  • Chan W, Naghd F (1997) An intelligent decision support system for body fluid balancing. In: IEEE International Conference on Intelligent Processing Systems, New York, NY, pp 1537–1541.

    Google Scholar 

  • Dhar V, Stein R (1998) Intelligent Decision Support Methods, Prentice-Hall, Upper Saddle River, pp 7–14.

    Google Scholar 

  • Elam J, Konsynski B (1987) Using artificial intelligence techniques to enhance the capabilities of model management systems. Decision Sciences, 18: 487–501.

    Google Scholar 

  • Eom S, Lee S, Kim E, Somarajan C (1998) A survey of decision support systems applications (1998–1994). Journal of Operational Research Society, 49: 109–120.

    Article  MATH  Google Scholar 

  • Eom S (1998) An overview of the contributions to the decision support systems area from artificial intelligence, Proceedings of the ICIS 1998 Conference, 149–151.

    Google Scholar 

  • Expert Choice (2004) Accessed from http://www.expertchoice.com/ on November 1.

    Google Scholar 

  • Faye RM, Mora-Camino F, Sawadogo S, Niang (1998) An intelligent decision support system for irrigation system management. In: IEEE International Conference on Systems, Man, and Cybernetics; New York, NY, pp 3908–3913.

    Google Scholar 

  • Fazlollahi B, Parikh MA (1997) Adaptive decision support systems. Decision Support Systems 20(4): 297–315.

    Article  Google Scholar 

  • Forgionne G (1999) An AHP model of DSS effectiveness. European Journal of Information Systems 8: 95–106.

    Article  Google Scholar 

  • Forgionne G, Kohli R (2001) A multiple criteria assessment of decision technology system journal qualities. Information Management 38: 421–435.

    Article  Google Scholar 

  • Forgionne G, Mora M, Cervantes F, Gelman O (2002) I-DMSS: A conceptual architecture for the next generation of decision-making support systems in the internet age. In: Adam F, Brézillon P, Humphreys P, Pomerol J (eds), Decision-making and Decision Support in the Internet Age, Proceedings of the DSIage2002, IFIP WG 8.3, Cork, Ireland, July 4–7, pp 154–165.

    Google Scholar 

  • Goul M, Henderson J, Tonge F (1992) The emergence of artificial intelligence as a reference discipline for decision support systems research, Decision Sciences, 23, pp. 1263–1276.

    Google Scholar 

  • Gottinger HW, Weimann P (1992) Intelligent decision support systems. Decision Support Systems, 8(4): 317–332.

    Article  Google Scholar 

  • Grabowski M, Sanborn S (2001) Evaluation of embedded intelligent real-time systems. Decision Sciences (Winter) 32(1): 95–123.

    Google Scholar 

  • Gray P, Watson H (1996) The new DSS: data warehouses, OLAP, MDD and KDD. In: Proceedings of the AMCIS Conference 1996, Phoenix, AZ, USA.

    Google Scholar 

  • Guerlain S, Brown DE, Mastrangelo C (2000) Intelligent decision support systems. In: IEEE International Conference on Systems, Man and Cybernetics. ‘Cybernetics Evolving to Systems, Humans, Organizations, and their Complex Interactions’, Piscataway, NJ, pp 1934–1938.

    Google Scholar 

  • Harker P (1988) The Art and Science of Decision-making: The Analytic Hierarchy Process. Working Paper 88-06-03, Decision Science Department, The Wharton School, University of Pennsylvania, Philadelphia, PA.

    Google Scholar 

  • Holsapple CW, Whinston AB (1996) Decision Support Systems, West Publishing Company, St. Paul, MN.

    Google Scholar 

  • Ifeachor EC, Garibaldi, JM, Skinner J (1998) Intelligent decision support tools for the management of labour. In: IEE Colloquium on Intelligent Decision Support in Clinical Practice, pp 1–7.

    Google Scholar 

  • Jensen A (1998) Does IQ matter ? Comentary, pp. 20–21, November. Comments to F. Chabris, “IQ since the Bell Curve”, Commentary, August.

    Google Scholar 

  • Jensen A (1999) The G Factor: the Science of Mental Ability. Psycoloquy, 10, #23.

    Google Scholar 

  • Jensen A (2000) Artificial Intelligence and G Theory concern different Phenomena, Psycoloquy, 11, #86.

    Google Scholar 

  • Kobbacy KAH, Proudlove NC, Harper MA (1995) Towards an intelligent maintenance optimization system. Journal of the Operational Research Society 46(7): 831–853.

    Article  MATH  Google Scholar 

  • Kwok LF, Lau WT, Kong SC (1996) An intelligent decision support system for teaching duty assignments. In: Narasimhan VL, Jain LC (eds), Proceedings of the Australian New Zealand Conference on Intelligent Information Systems, pp 97–100.

    Google Scholar 

  • Lin R, Wang Q, Hu J (1996) An intelligent decision support system applied to the investment of real estate. In: Proceedings of the IEEE International Conference on Industrial Technology, New York, NY, 801–805.

    Google Scholar 

  • Macintosh A (2004) The optimization of What?. Proceedings of the DSS2004 Conference, Prato, Italy. Keynote Address.

    Google Scholar 

  • Maynard S, Burstein F, Arnott, D (2001) A multi-faceted decision support system evaluation approach. Journal of Decision Systems, special issue “DSS in the New Millennium”, 10(3–4): 395–428.

    Google Scholar 

  • McCarthy J (2003) What is artificial intelligence?. Technical Report. Computer Science Department, Stanford University. Accessed from http://www-formal.standord.edu/jmc on September 9.

    Google Scholar 

  • Mora M, Forgionne G, Gupta J, Cervantes F, Gelman O (2003) A framework to assess intelligent decision-making support systems. In: Proceedings of the 7th International Conference KES 2003, Oxford, UK, September (Lecture Notes on Artificial Intelligence 2774, Springer-Verlag), 59–65.

    Google Scholar 

  • Nemati HR, Iyer LS (1999) An intelligent decision support system prototype for asset allocation. In: Haseman WD, Nazareth DL (eds), Proceedings of the Fifth Americas Conference on Information Systems; Atlanta, GA, 70–72.

    Google Scholar 

  • Newell A, Simon H (1976) Computer science as empirical inquiry: Symbols and Search (1975 ACM Turing Award Lecture), Communications of the ACM, 19(3): 113–126

    Article  MathSciNet  Google Scholar 

  • Palaniappan C, Srinivasan R, Halim I (2002) A material-centric methodology for developing inherently safer environmentally benign processes. Computers & Chemical Engineering 26(4–5): 757–774.

    Article  Google Scholar 

  • Parnas D (1985) Software aspects of strategic defense systems, ACM SIGSOFT Software Engineering Notes, 10(5): 15–23.

    Article  Google Scholar 

  • Pflughoeft KA, Hutchinson GK, Nazareth DL (1996) Intelligent decision support for flexible manufacturing: Design and implementation of a knowledge-based simulator. Omega 24(3): 347–360.

    Article  Google Scholar 

  • Phillips-Wren G, Forgionne G (2002) Evaluating web-based and real-time decision support systems. In: Adam F, Brézillon P, Humphreys P, Pomerol J (eds), Decision-making and Decision Support in the Internet Age, Proceedings of the DSIage2002, IFIP WG 8.3, Cork, Ireland, July 4–7, 166–175.

    Google Scholar 

  • Phillips-Wren G, Hahn E, Forgionne G (2004) A multiple criteria framework for the evaluation of decision support systems. Omega 32(4): 323–332.

    Article  Google Scholar 

  • Pohl J (2005) Intelligent software systems in historical context. In: Phillips-Wren G, Jain LC (eds), Intelligent Decision Support Systems in Agent-Mediated Environments, IOS Press: The Netherlands, 3–34.

    Google Scholar 

  • Potter W, Ramyaa LJ, Ghent TT (2002) STP: an aerial spray treatment planning system. In: Proceedings of the IEEE Southeast Conference, pp 300–305.

    Google Scholar 

  • Proudlove NC, Vedera S, Kobbacy KAH (1998), Intelligent management systems in operations: a review. Journal of the Operations Research Society, 49: 682–699.

    MATH  Google Scholar 

  • Renton MW, Wallace AR (1996) Expert system scheduling of cascade hydro-electric plants. Proceedings of the International Conference on Opportunities and Advances in International Power Generation, IEE, London, UK, pp. 69–72.

    Chapter  Google Scholar 

  • Saaty TL (1977) A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology 15: 234–281.

    Article  MATH  MathSciNet  Google Scholar 

  • Silverman BG (1992) Evaluating and refining expert critiquing systems: A methodology. Decision Sciences 23(1): 86–110.

    Google Scholar 

  • Simon H (1996) Models of My Life. MIT Press.

    Google Scholar 

  • Simon H (1997) Administrative Behavior, Fourth edition (Original publication date 1945), The Free Press, New York, NY.

    Google Scholar 

  • Singh R, Reif HL (1999) Intelligent decision aids for electronic commerce. In: Haseman WD, Nazareth DL (eds), Proceedings of the Fifth Americas Conference on Information Systems (AMCIS), Atlanta, GA, 85–87.

    Google Scholar 

  • Smith A, Nugent C, McClean S (2001) Intelligent decision support systems for medicine: inherent performance evaluation. In: Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Piscataway, NJ, vol. 4, 3746–3749.

    Google Scholar 

  • Sprague RH (1980) A framework for the development of decision support systems. MIS Quarterly, 4(4): 1–26.

    Article  Google Scholar 

  • Strachan SM, West GM, McDonald JR (2001) Knowledge management and intelligent decision support for protection scheme design and application in electrical power systems. In: Seventh International Conference on Developments in Power System Protection, London, UK, 559–562.

    Google Scholar 

  • Tsumoto S (2003) Web based medical decision support system: application of Internet to telemedicine. In: Proceedings of the Symposium on Applications and the Internet Workshops, Los Alamitos, CA, 288–93.

    Google Scholar 

  • Turban E, Aronson J (1998) Decision Support Systems and Intelligent Systems. A. Simon and Schuster Company, Upper Saddle River, NJ

    Google Scholar 

  • Turing A (1950) Computing machinery and intelligence. Mind 59, 433–460.

    Article  MathSciNet  Google Scholar 

  • Vraneš S, Stanojević M, Stevanović VL (1996) INVEX: investment advisory expert system. Expert Systems 13(2): 105–120.

    Google Scholar 

  • Wong AKC, Yang W (2003) Pattern discovery: a data driven approach to decision support. IEEE Transactions on Systems, Man and Cybernetics, Part C 33(1): 114–124.

    MathSciNet  Google Scholar 

  • Yang H, Huang Y (1996) Intelligent decision support for diagnosis of incipient transformer faults using self-organizing polynomial networks. In: Proceedings of the 20th International Conference on Power Industry Computer Applications, New York, NY, pp 60–66.

    Google Scholar 

  • Zeleznikow J, Nolan JR (2001) Using soft computing to build real world intelligent decision support systems in uncertain domains. Decision Support Systems 31(2): 263–285.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Information Systems, Loyola College in Maryland, Baltimore, MD, 21210, USA

    Gloria Phillips-Wren

  2. Department of Information Systems, Autonomous University of Aguascalientes, Aguascalientes, Mexico, 20000

    Manuel Mora

  3. Department of Information Systems, University of Maryland Baltimore County, Catonsville, MD, 21250, USA

    Guisseppi A. Forgionne

  4. Center for Intelligent Systems, Monterrey Tech, Monterrey, N.L., Mexico, 64800

    Leonardo Garrido

  5. College of Administrative Science, The University of Alabama in Huntsville, Huntsville, AL, 35899, USA

    Jatinder N. D. Gupta

Authors
  1. Gloria Phillips-Wren
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  2. Manuel Mora
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  3. Guisseppi A. Forgionne
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  4. Leonardo Garrido
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  5. Jatinder N. D. Gupta
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© 2006 Springer-Verlag London Limited

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Phillips-Wren, G., Mora, M., Forgionne, G.A., Garrido, L., Gupta, J.N.D. (2006). A Multicriteria Model for the Evaluation of Intelligent Decision-making Support Systems (i-DMSS). In: Intelligent Decision-making Support Systems. Decision Engineering. Springer, London. https://doi.org/10.1007/1-84628-231-4_1

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  • DOI: https://doi.org/10.1007/1-84628-231-4_1

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84628-228-7

  • Online ISBN: 978-1-84628-231-7

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