Combining Behavioral Experiments and Agent-based Social Simulation to Support Trust-aware Decision-making in Supply Chains

Diego de Siqueira Braga, Marco Niemann, Bernd Hellingrath, Fernando Buarque de L. Neto

Abstract

Trust is seen as one of the most important dimensions in developing and maintaining fruitful business relationships and has deep impact on the decision-making process in the supply chain planning. Despite its importance, very limited research has been done in the trust-aware decision-making field. This paper aims to experimentally examine how trust can be assessed over different dimensions and then be used to support decision-making in order to reduce the Bullwhip Effect, which is one of the biggest efficiency problems shown by supply chains of highly interconnected organizations. As industry is generally reluctant to provide data due to privacy concerns and trade secret protection, the authors of this paper, designed and conducted a web-based trust behavioral experiment. The data collected was used to evaluate the proposed trust mechanism through an Agent-Based Social Simulation. The results revealed that it is possible to infer trust relationships from behavioral experiments and historical based data, and use these relationships to influence the procurement, ordering and information sharing process. Although additional research is still necessary, the preliminary results revealed that the use of computational trust mechanisms can be helpful to lower the Bullwhip Effect.

References

  1. Abdul-Rahman, A. and Hailes, S. (2000). Supporting trust in virtual communities. In System Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on, pages 9-pp. IEEE.
  2. Argonne National Laboratory (2015). Repast.
  3. Ba, S. and Pavlou, P. A. (2002). Evidence of the Effect of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior. MIS Quarterly, 26(3):243-268.
  4. Ba, S., Whinston, A. B., and Zhang, H. (2003). Building Trust in Online Auction Markets Through an Economic Incentive Mechanism. Decision Support Systems, 35(3):273-286.
  5. Bachmann, R. (2001). Trust, Power and Control in Trans-Organizational Relations. Organization Studies, 22(2):337-365.
  6. Braynov, S. and Sandholm, T. (2002a). Contracting With Uncertain Level Of Trust. Computational Intelligence, 18(4):501-514.
  7. Braynov, S. and Sandholm, T. (2002b). Incentive Compatible Mechanism for Trust Revelation. In Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems: Part 1, pages 310-311, Bologna, Italy. ACM Press.
  8. Burnett, C., Norman, T. J., Sycara, K., and Oren, N. (2014). Supporting trust assessment and decision making in coalitions. IEEE Intelligent Systems, 29(4):18-24.
  9. Castelfranchi, C. and Falcone, R. (1998). Principles of Trust for MAS: Cognitive Anatomy, Social Importance, and Quantification. In Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160), pages 72-79. IEEE Comput. Soc.
  10. Chaib-draa, B. and M üller, J. (2006). Multiagent based supply chain management, volume 28. Springer Science & Business Media.
  11. Chatfield, D. C., Kim, J. G., Harrison, T. P., and Hayya, J. C. (2004). The Bullwhip Effect-Impact of Stochastic Lead Time, Information Quality, and Information Sharing: A Simulation Study. Production and Operations Management, 13(4):340-353.
  12. Chatfield, D. C. and Pritchard, A. M. (2013). Returns and the bullwhip effect. Transportation Research Part E: Logistics and Transportation Review, 49(1):159-175.
  13. Christopher, M. (1999). Logistics and supply chain management: Strategies for reducing cost and improving service financial times: Pitman publishing. london, 1998 isbn 0 273 63049 0 (hardback) 294+ 1× pp.
  14. Clark, A. J. and Scarf, H. (1960). Optimal Policies for a Multi-Echelon Inventory Problem. Management Science, 6(4):475-490.
  15. De Bruijn, H. and Herder, P. M. (2009). System and actor perspectives on sociotechnical systems. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 39(5):981-992.
  16. Dejonckheere, J., Disney, S., Lambrecht, M., and Towill, D. (2003). Measuring and avoiding the bullwhip effect: A control theoretic approach. European Journal of Operational Research, 147(3):567-590.
  17. Dejonckheere, J., Disney, S., Lambrecht, M., and Towill, D. (2004). The impact of information enrichment on the Bullwhip effect in supply chains: A control engineering perspective. European Journal of Operational Research, 153(3):727-750.
  18. Donohue, K. and Siemsen, E. (2011). Behavioral operations: applications in supply chain management. Wiley Encyclopedia of Operations Research and Management Science.
  19. Forrester, J. W. (1958). Industrial dynamics: a major breakthrough for decision makers. Harvard business review, 36(4):37-66.
  20. Gould, S. (2011). OpenForecast.
  21. Greif, A., Milgrom, P., and Weingast, B. R. (1994). Coordination, Commitment, and Enforcement: The Case of the Merchant Guild. Journal of Political Economy, 102(4):745-776.
  22. Ha, B.-C., Park, Y.-K., and Cho, S. (2011). Suppliers' affective trust and trust in competency in buyers: Its effect on collaboration. International Journal of Operations & Production Management, 31(1-2):56-77.
  23. Haghpanah, Y. and DesJardins, M. (2010). Using a Trust Model in Decision Making for Supply Chain Management. In Proceedings of the 3rd AAAI Conference on Interactive Decision Theory and Game Theory, pages 25-29. AAAI Press.
  24. Handfield, R. (2003). Trust in Supply Chain Relationships: What Does It Mean to Trust? - Part I.
  25. Houser, D. and Wooders, J. (2006). Reputation in Auctions: Theory, and Evidence from eBay. Journal of Economics & Management Strategy Management Strategy, 15(2):353-369.
  26. Kim, P. H., Dirks, K. T., Cooper, C. D., and Ferrin, D. L. (2006). When more blame is better than less: The implications of internal vs. external attributions for the repair of trust after a competence-vs. integrity-based trust violation. Organizational Behavior and Human Decision Processes, 99(1):49-65.
  27. Kim, W.-S. (2009). Effects of a trust mechanism on complex adaptive supply networks: An agent-based social simulation study. Journal of Artificial Societies and Social Simulation, 12(3):4.
  28. Kwon, I.-W. G. and Suh, T. (2005). Trust, commitment and relationships in supply chain management: a path analysis. Supply chain management: an international journal, 10(1):26-33.
  29. La Londe, B. J. and Masters, J. M. (1994). Emerging Logistics Strategies: Blueprints for the Next Century. International Journal of Physical Distribution & Logistics Management, 24(7):35-47.
  30. Laeequddin, M., Sahay, B. S., Sahay, V., and Waheed, K. A. (2010). Measuring trust in supply chain partners' relationships. Measuring Business Excellence, 14(3):53- 69.
  31. Lin, A. F.-r., Sung, Y.-w., and Lo, Y.-p. (2005). Effects of Trust Mechanisms on Supply-Chain Performance: A Multi-Agent Simulation Study. International Journal of Electronic Commerce, 9(4):91-112.
  32. Marsh, S. P. (1994). Formalising Trust as a Computational Concept. Disseration, University of Stirling.
  33. Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., and Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2):1-25.
  34. Morgan, R. M. and Hunt, S. D. (1994). The CommitmentTrust Theory of Relationship Marketing. Journal of Marketing, 58(3):20-38.
  35. Moyaux, T., Chaib-draa, B., and D'Amours, S. (2007). Information sharing as a coordination mechanism for reducing the bullwhip effect in a supply chain. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 37(3):396-409.
  36. Ottens, M., Franssen, M., Kroes, P., and Van De Poel, I. (2006). Modelling infrastructures as socio-technical systems. International Journal of Critical Infrastructures, 2(2-3):133-145.
  37. Ozer, O., Zheng, Y., and Chen, K.-Y. (2011). Trust in Forecast Information Sharing. Management Science, 57(6):1111-1137.
  38. Pinyol, I. and Sabater-Mir, J. (2013). Computational trust and reputation models for open multi-agent systems: a review. Artificial Intelligence Review , 40(1):1-25.
  39. Raimondo, M. A. (2000). The measurement of trust in marketing studies: a review of models and methodologies. In 16th IMP-conference, Bath, UK. Citeseer.
  40. Resnick, P. and Zeckhauser, R. (2002). Trust Among Strangers in Internet Transactions: Empirical Analysis of eBay's Reputation System. In Baye, M. R., editor, Advances in Applied Microeconomics, number 11, pages 127-157. Emerald Group Publishing Limited.
  41. Ring, P. S. and Van de Ven, A. H. (1994). Developmental processes of cooperative interorganizational relationships. Academy of management review, 19(1):90-118.
  42. Rousseau, D. M., Sitkin, S. B., Burt, R. S., and Camerer, C. (1998). Not so different after all: A crossdiscipline view of trust. Academy of management review, 23(3):393-404.
  43. Sabater, J. and Sierra, C. (2005). Review on computational trust and reputation models. Artificial Intelligence Review, 24(1):33-60.
  44. ServiceNow (2016). % of undamaged goods after shipping/transportation.
  45. Tykhonov, D., Jonker, C., Meijer, S., and Verwaart, T. (2008). Agent-based simulation of the trust and tracing game for supply chains and networks. Journal of Artificial Societies and Social Simulation , 11(3):1.
  46. Yu, B. and Singh, M. P. (2002). An Evidential Model of Distributed Reputation Management. In Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems: Part 1 - AAMAS 7802, pages 294-301, Bologna, Italy. ACM Press.
  47. Yu, H., Shen, Z., Leung, C., Miao, C., and Lesser, V. R. (2013). A survey of multi-agent trust management systems. IEEE Access, 1:35-50.
  48. Zacharia, G., Moukas, A., and Maes, P. (2000). Collaborative reputation mechanisms for electronic marketplaces. Decision Support Systems, 29(4):371-388.
Download


Paper Citation


in Harvard Style

de Siqueira Braga D., Niemann M., Hellingrath B. and de L. Neto F. (2017). Combining Behavioral Experiments and Agent-based Social Simulation to Support Trust-aware Decision-making in Supply Chains . In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-219-6, pages 260-267. DOI: 10.5220/0006200802600267


in Bibtex Style

@conference{icaart17,
author={Diego de Siqueira Braga and Marco Niemann and Bernd Hellingrath and Fernando Buarque de L. Neto},
title={Combining Behavioral Experiments and Agent-based Social Simulation to Support Trust-aware Decision-making in Supply Chains},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2017},
pages={260-267},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006200802600267},
isbn={978-989-758-219-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Combining Behavioral Experiments and Agent-based Social Simulation to Support Trust-aware Decision-making in Supply Chains
SN - 978-989-758-219-6
AU - de Siqueira Braga D.
AU - Niemann M.
AU - Hellingrath B.
AU - de L. Neto F.
PY - 2017
SP - 260
EP - 267
DO - 10.5220/0006200802600267