A Multi Psychology Accounts CSD Model for ISC Bi-Level Distribution Network

  • Quan Lu
  • Jing Chen
  • Junping Qiu
Conference paper
Part of the IFIP — The International Federation for Information Processing book series (IFIPAICT, volume 251)


The researches on Supply Chain are mainly about the conjunction mechanism and efficiency in Integrated Supply Chain to enhance its competitiveness and the cooperation between its members. But most of those belong to the standard finance field, and few about the factors of human mental or psychology. We studied the satisfaction degree models of customer with mental account based on the customer satisfaction degree (CSD) model and found they are too simplified, not reasonable and inaccurate. This paper suggests a CSD model based on multi artificial psychology accounts, which quantify exact customer psychology using cognition and artificial psychology methods, and then describes an ISC bi-level distribution network model based on this CSD model.


Supply Chain Management Mental Account Integrate Supply Psychology Account Adjective Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    T. Davis, Effective supply chain management, Sloan Management Review, Summer, 34(4), 5–46 (1993).Google Scholar
  2. 2.
    J.T. Douglas and M.G. Paul, Coordinated supply chain management, European Journal of Operational Research, 94(1), 1–15 (1996).MATHCrossRefGoogle Scholar
  3. 3.
    S. Bylka, A dynamic model for the single-vendor, multi-buyer problem, International Journal of Production Economics, 59(3), 297–304 (1999).CrossRefGoogle Scholar
  4. 4.
    P. H. Zipkin, Supply chain management: reflections, interpretations and predictions, Global SCM Conference, Berlin: Springer-Verlage Press (2002).Google Scholar
  5. 5.
    F. Cheng, M. Ettl and G. Lin, Inventory-service optimization in configure-to-order systems, Manufacturing and Service Operations Management, 4(2), 114–132 (2002).CrossRefGoogle Scholar
  6. 6.
    M. Friedman and L.J. Savage, The utility analysis of choices involving risk, Journal of Political Economy, 56(4), 279–304 (1948).CrossRefGoogle Scholar
  7. 7.
    Y.K. Ma and X.W. Tang, Decision-making methods for behavioral portfolio choice, Journal of systems engineering, 18(1), 71–76 (2003).MathSciNetGoogle Scholar
  8. 8.
    S. Hersh and S. Meir, Behavioral Portfolio Theory, The Journal of Financial and Quantitative Analysis, 35(2), 127–151 (2000).CrossRefGoogle Scholar
  9. 9.
    J.J. Jiang etc. Optimization of the ISC Bi-Level Distribution Network with Multiple Mental Accounts, Industrial Engineering Journal, 8(3), 12–17 (2005).Google Scholar
  10. 10.
    Q. Lu, J. Chen and B. Meng, Web Personalization based on Artificial Psychology, WISE Workshop on Web Information Access and Digital Library, LNCS4256, 223–229 (2006).Google Scholar
  11. 11.
    R. Cooley, B. Mobasher and J. Srivastava, Data preparation for mining World Wide Web browsing patterns, Journal of Knowledge and Information Systems, 1(1) (1999).Google Scholar
  12. 12.
    X.y. Zhao etc, An Optimization Model for Distribution Network Design with Uncertain Customer Demands and Production Capacity,0-7803-8971-9/05 IEEE (2005).Google Scholar

Copyright information

© International Federation for Information Processing 2007

Authors and Affiliations

  • Quan Lu
    • 1
  • Jing Chen
    • 2
  • Junping Qiu
    • 1
  1. 1.Research Center for China Science EvaluationWuhan UniversityWuhanP.R.China
  2. 2.Department Of Computer ScienceCentral China Normal UniversityWuhanP.R.China

Personalised recommendations