Introduction
High performing firms are working in business networks with advanced decision making capabilities. Decision making in business networks is a new research area that provides knowledge and insight about how decision rights are allocated and how decision processes are designed and implemented in evolving business networks [22]. In this article we focus on a particular type of support: software agents. Software agents are software programs that act on behalf of users or other programs. Software agents can be autonomous (capable of modifying the way in which they achieve their objectives), intelligent (capable of learning and reasoning), and distributed (capable to being executed on physically distinct computers). Software agents can act in multi-agent systems (e.g. distributed agents that do not have the capabilities to achieve an objective alone and thus must be able to communicate) and as mobile agents (e.g. these relocate their execution onto different processors). Recent research shows that software agents are able to act as a decision support tool or a training tool for negotiations with people. For example, [16] Lin and Kraus (2010) identified several types of agents in several variations of negotiation settings. These agents differ in the number of negotiators, encounters, and attributes they can handle. The identified agents are: Diplomat, AutONA, Cliff-Edge, Colored-Trails, Guessing Heuristic, QOAgent, and Virtual Human. Although software agents are popular in scientific research programs, the use of software agents in real life business situations is limited. We will explore the use of software agents in the flower industry with its complex logistics, commercial, and financial processes on a global scale.
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References
Adomavicius, G., Tuzhilin, A.: Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005)
Carare, O., Rothkopf, M.H.: Slow Dutch Auctions. Management Science 51(3), 365–373 (2005)
Collins, J., Ketter, W., Gini, M.: A Multi-Agent Negotiation Testbed for Contracting Tasks with Temporal and Precedence Constraints. International Journal of Electronic Commerce 7(1), 35–57 (2002)
Collins, J., Ketter, W., Gini, M.: Flexible decision support in a dynamic business network. In: Vervest, P., van Liere, D., Zheng, L. (eds.) The Network Experience – New Value from Smart Business Networks, pp. 233–246. Springer, Heidelberg (2008)
Collins, J., Ketter, W., Gini, M.: Flexible decision support in dynamic interorganizational networks. European Journal of Information Systems 19(4) (September 2010a)
Collins, J., Ketter, W., Gini, M.: Flexible decision control in an autonomous trading agent. Electronic Commerce Research and Applications 8(2), 91–105 (2009)
Collins, J., Ketter, W., Sadeh, N.: Pushing the limits of rational agents: the trading agent competition for supply chain management. AI Magazine 31(2), 63–80 (2010b)
Economist, The, A Life of Slime: Railways and Slime Moulds, p. 71 (January 23, 2010)
Goldberg, D., et al.: Using collaborative filtering to weave an information tapestry. Communications of the ACM, 61–70 (1992)
Haeubl, G., Trifts, V.: Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids. Marketing Science 19(1), 4–21 (2000)
Kambil, A., Van Heck, E.: Reengineering the Dutch Flower Auctions: A Framework for Analyzing Exchange Organizations. Information Systems Research 9(1), 1–19 (1998)
Kambil, A., van Heck, E.: Making Markets: How firms can design and profit from online auctions and exchanges. Harvard Business School Press (June 2002)
Ketter, W., Collins, J., Gini, M., Gupta, A., Schrater, P.: Detecting and Forecasting Economic Regimes in Multi-Agent Automated Exchanges. Decision Support Systems 47(4), 307–318 (2009)
Koppius, O.R.: Information Architecture and Electronic Market Performance. 2002: Erasmus Research Institute of Management (ERIM, PhD Dissertation), Erasmus University Rotterdam
Koppius, O., van Heck, E., Wolters, M.: The importance of product representation online: Empirical results and implications for electronic markets. Decision Support Systems 38, 161–169 (2004)
Lin, R., Kraus, S.: Can automated agents proficiently negotiate with humans? Communications of the ACM 53(1), 78–88 (2010)
Maes, P.: Agents that reduce work and information overload. Communications of the ACM 37(7), 30–40 (1994)
Myers, K., et al.: An Intelligent Personal Assistant for Task and Time Management. AI Magazine, 47 (2007)
Rich, C., Sidner, C.L.: COLLAGEN: A Collaboration Manager for Software Interface Agents. User Modeling and User-Adapted Interaction 8(3), 315–350 (1998)
Sandholm, T., et al.: CABOB: A Fast Optimal Algorithm for Winner Determination in Combinatorial Auctions. Management Science 51(3), 374–390 (2005)
Tero, A., Takagi, S., Saigusa, T., Ito, K., Bebber, D.P., Fricker, M.D., Yumiki, K., Kobayashi, R., Nakagaki, T.: Rules for Biologically Inspired Adaptive Network Design. Science 327(5964), 439–442 (2010)
Van Heck, E., Vervest, P.: Smart business networks: how the network wins. Communications of the ACM 50(6), 29–37 (2007)
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van Heck, E., Ketter, W. (2012). Challenges for Software Agents Supporting Decision-Makers in Trading Flowers Worldwide. In: Filipe, J., Cordeiro, J. (eds) Web Information Systems and Technologies. WEBIST 2011. Lecture Notes in Business Information Processing, vol 101. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28082-5_3
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