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Decision Support Systems: Present And Future Trends

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Author Info

  • MANOLE VELICANU

    ()
    (Informatics in Economy Department, Academy of Economic Studies, Bucharest, Romania)

  • GHEORGHE MATEI

    ()
    (Romanian Commercial Bank, Accounting Division, Bucharest, Romania,)

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    Abstract

    As competition gets tougher and tougher, companies have to implement new management systems to stay efficient. Along business performance monitoring application, executive information systems, business intelligence systems and decision support systems (DSS) help managers to lead their companies successfully and survive into the future. They are interactive, flexible and adjustable systems that offer support in solving unstructured or semistructured management problems, meant to improve the decision process. They are developed to assist the tactical and strategic level of management. The classic architecture of a DSS contains the database management system, the model base management system and the interface management system. The evolved DSS have also a knowledge component that provides the information needed for solving certain aspects of the problems. According to D. J. Power, at a conceptual level the DSS can be classified into the following categories: data-driven systems, model-driven systems, knowledgedriven systems, document-driven systems, communication-driven systems, intra and inter organizational systems, specialized systems and Web-based systems. At the end of the paper some opinions concerning the future of DSS are presented.

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    File URL: http://tbs.ubbcluj.ro/RePEc/bbn/journl/Negotia_2_2008.pdf
    File Function: Revised version, 2008
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    Bibliographic Info

    Article provided by Babes-Bolyai University, Faculty of Business in its journal JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA.

    Volume (Year): (2008)
    Issue (Month): ()
    Pages:

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    Handle: RePEc:bbn:journl:2008_2_6_velicanu

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    Related research

    Keywords: Decision support system; Structured; semistructured and unstructured problems; Database; Model base; Knowledge base; User interface;

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    References

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    1. Myers, Stewart C., 1984. "Capital structure puzzle," Working papers 1548-84., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Stewart C. Myers, 1984. "Capital Structure Puzzle," NBER Working Papers 1393, National Bureau of Economic Research, Inc.
    3. Myers, Stewart C, 1984. " The Capital Structure Puzzle," Journal of Finance, American Finance Association, vol. 39(3), pages 575-92, July.
    4. Shiqing Ling & Michael McAleer, 2001. "Asymptotic Theory for a Vector ARMA-GARCH Model," ISER Discussion Paper 0549, Institute of Social and Economic Research, Osaka University.
    5. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," NBER Working Papers 7933, National Bureau of Economic Research, Inc.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
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