Decision Support in Virtual Organizations: The Case for Multi-Agent Support

The new economy, which is being formed by the Internet-based e-commerce and the now emerging mobile commerce, may become what Martin calls a cyber economy. This will combine traditional business with the new e- and mobile business, and will be driven by a new breed of online customers, who operate both wired and wireless networks, who will expect fast delivery, easier transactions and more fact-based information. The cyber economy requires that business is operated with virtual organisations and that decision making in this context – virtual organisations and the cyber economy – will require new and advanced forms of decision support. We have found that a useful decision platform can be built around hyperknowledge and the use of multiple software agents, if the core of these agents is built on fuzzy logic and approximate reasoning.

[1]  Christer Carlsson,et al.  Reducing the bullwhip effect by means of intelligent, soft computing methods , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[2]  Chuck Martin Net Future , 1998 .

[3]  Dennis A. Gioia,et al.  Sensemaking and sensegiving in strategic change initiation , 1991 .

[4]  Lance Self INTRODUCTION TO SOFTWARE AGENTS , 1999 .

[5]  Christer Carlsson,et al.  Industry Foresight with Intelligent Agents , 1999 .

[6]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[7]  R. Daft,et al.  Toward a Model of Organizations as Interpretation Systems , 1984 .

[8]  Bert Bredeweg,et al.  An overview of approaches to qualitative model construction , 1996, The Knowledge Engineering Review.

[9]  Nicholas R. Jennings,et al.  A Roadmap of Agent Research and Development , 2004, Autonomous Agents and Multi-Agent Systems.

[10]  Judy Bayer,et al.  “Miner”, “Manager”, and “Researcher”: Three modes of analysis of scanner data , 1991 .

[11]  L. Zadeh The role of fuzzy logic in the management of uncertainty in expert systems , 1983 .

[12]  Hyacinth S. Nwana,et al.  Software agents: an overview , 1996, The Knowledge Engineering Review.

[13]  Jeffrey M. Bradshaw,et al.  An introduction to software agents , 1997 .

[14]  Pádraig Cunningham,et al.  Software agents: A review , 1997 .

[15]  Hyacinth S. Nwana,et al.  An Introduction to Agent Technology , 1997, Software Agents and Soft Computing.

[16]  Arthur B. Markman,et al.  Knowledge Representation , 1998 .

[17]  Robert Fullér,et al.  Problem Solving with Multiple Interdependent Criteria , 1997 .

[18]  Arthur C. Graesser,et al.  Is it an Agent, or Just a Program?: A Taxonomy for Autonomous Agents , 1996, ATAL.

[19]  Michael Wooldridge,et al.  Applications of intelligent agents , 1998 .

[20]  Pattie Maes,et al.  Agents that reduce work and information overload , 1994, CACM.

[21]  Shuhua Liu Data warehousing agent: in seeking of improved support for environmental scanning and strategic management , 1998, ECIS.

[22]  Christer Carlsson,et al.  Fuzzy logic and hyperknowledge: a new, effective paradigm for active DSS , 1997, Proceedings of the Thirtieth Hawaii International Conference on System Sciences.

[23]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[24]  H. Van Dyke Parunak Practical and Industrial Applications of Agent-Based Systems , 1998 .

[25]  Greg Elofson,et al.  An intelligent agent community approach to knowledge sharing , 1997, Decis. Support Syst..

[26]  Pattie Maes,et al.  Agent-mediated Electronic Commerce : A Survey , 1998 .

[27]  Daniel E. O'Leary,et al.  Intelligent Executive Information Systems , 1996, IEEE Expert.

[28]  Franklin Neubauer,et al.  A managerial approach to environmental assessment , 1977 .

[29]  C. Carlsson,et al.  Soft computing and the bullwhip effect , 1999 .

[30]  Oren Etzioni,et al.  A softbot-based interface to the Internet , 1994, CACM.

[31]  L. A. Zedeh Knowledge representation in fuzzy logic , 1989 .

[32]  Ralph L. Keeney,et al.  Decisions with multiple objectives: preferences and value tradeoffs , 1976 .

[33]  J. Dutton,et al.  Categorizing Strategic Issues: Links to Organizational Action , 1987 .

[34]  A. Tversky Intransitivity of preferences. , 1969 .

[35]  Hans W. Gottinger,et al.  Intelligent decision support systems , 1992, Decis. Support Syst..

[36]  Marcos Fernández,et al.  Virtual reality for driving simulation , 1996, CACM.

[37]  M. Malone The Virtual Corporation , 1993 .

[38]  J. Dutton,et al.  Discerning threats and opportunities. , 1988 .

[39]  Peter G. W. Keen,et al.  Decision support systems: The next decade , 1987, Decis. Support Syst..

[40]  Fah-Chun Cheong Internet Agents: Spiders, Wanderers, Brokers, and 'Bots , 1996 .

[41]  N. Negroponte Agents: from direct manipulation to delegation , 1997 .

[42]  Benn R. Konsynski,et al.  Delegation Technologies: Environmental Scanning with Intelligent Agents , 1991, J. Manag. Inf. Syst..

[43]  S. Schneider,et al.  Interpreting and responding to strategic issues: The impact of national culture , 1991 .

[44]  Daniel S. Weld,et al.  Intelligent Agents on the Internet: Fact, Fiction, and Forecast , 1995, IEEE Expert.

[45]  Sergei Ovchinnikov,et al.  Fuzzy sets and applications , 1987 .

[46]  Hugh J. Watson,et al.  Building Executive Information Systems and Other Decision Support Applications , 1996 .

[47]  Hau L. Lee,et al.  Information distortion in a supply chain: the bullwhip effect , 1997 .

[48]  Lotfi A. Zadeh,et al.  Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic , 1997, Fuzzy Sets Syst..

[49]  James J. Buckley,et al.  L∞ fuzzy logic , 1999, Fuzzy Sets Syst..

[50]  Michael Wooldridge,et al.  Agent technology: foundations, applications, and markets , 1998 .

[51]  Efraim Turban,et al.  Decision support systems and intelligent systems , 1997 .

[52]  P. Drucker Management Challenges for the 21st Century , 1992 .

[53]  A. Tversky,et al.  Judgment under Uncertainty , 1982 .