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Pirasa: strategic protocol selection for e-commerce agents

Author

Listed:
  • Jack Hopkins

    (University of Cambridge)

  • Özgür Kafali

    (University of Kent)

  • Bedour Alrayes

    (King Saud University)

  • Kostas Stathis

    (University of London)

Abstract

We present Pirasa: an agent-based simulation environment for studying how autonomous agents can best interact with each other to exchange goods in e-commerce marketplaces. A marketplace in Pirasa enables agents to enact buyer or seller roles and select from sales, auction, and negotiation protocols to achieve the individual goals of their users. An agent’s strategy to maximize its utility in the marketplace is guided by its user’s preferences and constraints such as ‘maximum price’ and ‘deadline’, as well as an agent’s personality attributes, e.g., how ‘eager’ or ‘late’ the agent can be for exchanging goods and whether the agent is a ‘spender’ or ‘saver’ in an exchange. To guide the agent’s actions selected by a strategy, we use the notion of electronic contracts formulated as regulatory norms. In this context, we present how Pirasa is organized with regards to seller processes for goods submission, the inclusion of buyer preferences, and the management of transactions through specialized broker agents. Using randomized simulations, we demonstrate how a buyer agent can strategically select the most suitable protocol to satisfy its user’s preferences, goals and constraints in dynamically changing market settings. The generated simulation data can be leveraged by researchers to analyze agent behaviors, and develop additional strategies.

Suggested Citation

  • Jack Hopkins & Özgür Kafali & Bedour Alrayes & Kostas Stathis, 2019. "Pirasa: strategic protocol selection for e-commerce agents," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 239-252, June.
  • Handle: RePEc:spr:elmark:v:29:y:2019:i:2:d:10.1007_s12525-018-0307-4
    DOI: 10.1007/s12525-018-0307-4
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    References listed on IDEAS

    as
    1. Harris, Milton & Raviv, Artur, 1981. "Allocation Mechanisms and the Design of Auctions," Econometrica, Econometric Society, vol. 49(6), pages 1477-1499, November.
    2. Rainer Alt & Hans-Dieter Zimmermann, 2016. "Electronic Markets on electronic markets in education," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(4), pages 311-314, November.
    3. Houssein Ben-Ameur & Brahim Chaib-draa & Peter Kropf, 2002. "Multi-item Auctions for Automatic Negotiation," CIRANO Working Papers 2002s-68, CIRANO.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Ransome Epie Bawack & Samuel Fosso Wamba & Kevin Daniel André Carillo & Shahriar Akter, 2022. "Artificial intelligence in E-Commerce: a bibliometric study and literature review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 297-338, March.
    2. Yin Zhang & Haider Abbas & Yi Sun, 2019. "Smart e-commerce integration with recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 219-220, June.

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    More about this item

    Keywords

    Agent-based e-commerce; Protocol selection; Electronic contracts; Simulation;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • K12 - Law and Economics - - Basic Areas of Law - - - Contract Law
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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