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A multi-agent based model for collective purchasing in electronic commerce

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Abstract

Several types of e-commerce (EC) including B2B, B2C, C2C are common on the internet. Collective purchasing in the EC is called customer-to-business EC. This type of EC offers unification of buyer’s common needs and priorities and the interaction between buyers and vendors to provide benefit for both. To achieve this goal, we consider requirements and preferences as two effective factors in the collective purchasing model. Requirements are qualitative or quantitative values which buyers assign to the issues of purchasing. Preferences are priorities assigned by the buyers and their values express the buyer’s measure of importance to the issues. To get buyer’s preferences of the issues, we use analytic hierarchy process. Additionally, a laptop computer buying example is used for illustration how the model calculates preferences of the issues.

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References

  1. Wang Y, Tan KL, Ran J (2004) PumaMart: a parallel and autonomous agent based internet marketplace. Electron Commer Res Appl 3:249–310

    Article  Google Scholar 

  2. Shah NH, Shukla KT (2010) Optimal production schedule in declining market for an imperfect production system. Int J Mach Learn Cybern 1(1–4):89–99

    Article  Google Scholar 

  3. Camarena-Ibarrola A, Chávez E (2011) Online music tracking with global alignment. Int J Mach Learn Cybern 2(3):147–156

    Article  Google Scholar 

  4. Friedrich T, Kroeger T, Neumann F (2012) Weighted preferences in evolutionary multi-objective optimization. Int J Mach Learn Cybern. doi:10.1007/s13042-012-0083-y

    Google Scholar 

  5. Chavez A, Maes P (1996) Kasbah: an agent marketplace for buying and selling goods. In: Proceedings of the international conference on the practical application of intelligent agents and multi-agent technology, London

  6. Huang CC, Liang WY, Lai YH, Lin YC (2010) The agent-based negotiation process for B2C e-commerce. Expert Syst Appl 37:348–359

    Article  Google Scholar 

  7. Yamamoto J, Sycara K (2001) A stable and efficient buyer coalition formation scheme for e-marketplaces. In: Proceedings of the international conference on autonomous agents, pp 576–583

  8. Tsvetovat M, Sycara K, Chen Y, Ying J (2000) Customer coalitions in the electronic marketplace. In: Proceedings of the workshop on agent mediated electronic commerce (AMEC-2000)

  9. Lerman K, Shehory O (2000) Coalition formation for large-scale electronic markets. In: Proceedings of the fourth international conference on multiagent systems (ICMAS-2000), pp 216–222

  10. Chen DN, Jeng B, Lee WP, Chuang CH (2008) An agent-based model for consumer-to-business electronic commerce. Expert Syst Appl 34:469–481

    Article  Google Scholar 

  11. He M, Jennings NR, Leung HF (2003) On agent-mediated electronic commerce. IEEE Trans Knowl Data Eng 15(4):985–1003

    Article  Google Scholar 

  12. Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York

    MATH  Google Scholar 

  13. Saaty TL (2008) Decision making with the analytic hierarchy process. Int J Serv Sci 1(1):83–98

    MathSciNet  Google Scholar 

  14. Bayazit O, Karpak B (2005) An AHP application in vendor selection. ISAHP, Honolulu

    Google Scholar 

  15. Saaty TL (1986) Axiomatic foundations of the AHP. Manag Sci 32(7):841–855

    Article  MathSciNet  MATH  Google Scholar 

  16. Cheng CB, Chan CCH, Lin KC (2006) Intelligent agents for e-marketplace: negotiation with issue trade-offs by fuzzy inference systems. Decis Support Syst 42:626–638

    Article  Google Scholar 

  17. Saaty TL, Aczél J (1983) Procedures for synthesizing ratio judgements. J Math Psychol 27:93–102

    Article  MATH  Google Scholar 

  18. Faratin P, Sierra C, Jennings NR (1998) Negotiation decision functions for autonomous agents. Robot Auton Syst 24:159–182

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Science and Research Branch, Islamic Azad University, Kerman, Iran

    Bahador Shojaiemehr

  2. Department of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran

    Marjan Kuchaki Rafsanjani

Authors
  1. Bahador Shojaiemehr
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  2. Marjan Kuchaki Rafsanjani
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Correspondence to Marjan Kuchaki Rafsanjani.

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Shojaiemehr, B., Kuchaki Rafsanjani, M. A multi-agent based model for collective purchasing in electronic commerce. Int. J. Mach. Learn. & Cyber. 4, 409–417 (2013). https://doi.org/10.1007/s13042-012-0098-4

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  • DOI: https://doi.org/10.1007/s13042-012-0098-4

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