Advertisement

The Strategy of Third-Party Mediation Based on the Option Prioritization in the Graph Model

  • Zhenggao Wu
  • Haiyan Xu
  • Ginger Y. KeEmail author
Article
  • 11 Downloads

Abstract

The resolution of real-world conflicts is often supported by third-party intervention (i.e., mediation). This paper proposes a possible mediation support in the form of a reverse optimization procedure under the framework of theGraph Model for Conflict Resolution (GMCR). The approach computes minimal priority adjustments of preference statements that are necessary to achieve a desired agreement. A mathematical model, based on the matrix form of GMCR, is developed to analyze this third-party mediation problem. Thereby, this study makes a first attempt to obtain option-based mediation strategies, which add comprehensiveness to the traditional state-based strategies, yet are easier to understand and hence more acceptable to the conflict participants. To illustrate the practicality, the proposed procedure is applied to a medical dispute between a patient and a hospital, with the aim to suggest changes in the ordering of preference statements that lead to a desired outcome.

Keywords

Graph Model for Conflict Resolution third party mediation option prioritization minimal adjustment 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgments

The authors appreciate financial support from the National Natural Science Foundation of China under Grant Nos. 71471087, 71071076 and 61673209.

References

  1. Balas E, Jeroslow R (1972). Canonical cuts on the unit hypercube. SIAM Journal on Applied Mathematics 23(1):61–69MathSciNetCrossRefzbMATHGoogle Scholar
  2. Bove V, Gleditsch KS, Sekeris PG (2016). “Oil above water”: Economic interdependence and third-party intervention. Journal of Conflict Resolution 60(7):1251–1277.CrossRefGoogle Scholar
  3. Chang YM, Luo Z, Zhang Y (2018). The timing of third-party intervention in social conflict. Defence and Peace Economics 29(2):91–110.CrossRefGoogle Scholar
  4. Channel PO (2016). 42 cases of typical meidical disputes since 2016. http://yuqing.people.com.cn/n1/2016/1118/c405625-28880100.html Google Scholar
  5. Fang L, Hipel KW, Kilgour DM (1989). Conflict models in graph form: Solution concepts and their interrelationships. European Journal of Operational Research 41(1):86–100.MathSciNetCrossRefzbMATHGoogle Scholar
  6. Fang L, Hipel KW, Kilgour DM (1993). Interactive Decision Making: The Graph Model for Conflict Resolution. Wiley, New York, USA.Google Scholar
  7. Fang L, Hipel KW, Kilgour DM, Peng X (2003a). A decision support system for interactive decision making - part I: Model formulation. Systems Man & Cybernetics Part C Applications & Reviews IEEE Transactions on 33(1):42–55.CrossRefGoogle Scholar
  8. Fang L, Hipel KW, Kilgour DM, Peng X (2003b). A decision support system for interactive decision making-part II: Analysis and output interpretation. Systems Man & Cybernetics Part C Applications & Reviews IEEE Transactions on 33(1):56–66.CrossRefGoogle Scholar
  9. Fenn P, Lowe D, Speck C (1997). Conflict and dispute in construction. Construction Management and Economics 15(6):513–518.CrossRefGoogle Scholar
  10. Findley MG, Marineau JF (2015). Lootable resources and third-party intervention into civil wars. Conflict Management and Peace Science 32(5):465–486.CrossRefGoogle Scholar
  11. Fisher R (2001). Methods of Third-party Intervention. Berghof Research Center for Constructive Conflict Management, Berlin, Germany.Google Scholar
  12. Fraser NM, Hipel KW (1979). Solving complex conflicts. IEEE Transactions on Systems Man & Cybernetics 9(12):805–816.CrossRefGoogle Scholar
  13. Fraser NM, Hipel KW (1984). Conflict Analysis: Models and Resolutions. North-Holland, Amsterdam, Netherlands.zbMATHGoogle Scholar
  14. Garcia A, Obeidi A, Hipel KW (2018).Strategic advice for decision-making under conflict based on observed behaviour. Applied Mathematics and Computation 332:96–104.Google Scholar
  15. Greig JM, Diehl PF (2006). Softening up: Making conflicts more amenable to diplomacy. International Interactions 32(4):355–384.CrossRefGoogle Scholar
  16. Han Q, Zhu Y, Ke GY, Lin H (2019). A two-stage decision framework for resolving brownfield conflicts. International Journal of Environmental Research and Public Health 16(6):1039.CrossRefGoogle Scholar
  17. Hou Y, Jiang Y, Xu H (2015). Option prioritization for three-level preference in the graph model for conflict resolution. International Conference on Group Decision and Negotiation, Warsaw, Poland, June 22–26, 2015.Google Scholar
  18. Howard N (1971). Paradoxes of Rationality: Theory of Metagames and Political Behavior. MA: MIT Press, Cambridge, USA.Google Scholar
  19. Kilgour D, Hipel KW, Fang L (1987). The graph model for conflicts. Automatica 23(1):41–55.MathSciNetCrossRefzbMATHGoogle Scholar
  20. Kilgour DM, Hipel KW (2005). The graph model for conflict resolution: Past, present, and future. Group Decision & Negotiation 14(6):441–460.CrossRefGoogle Scholar
  21. Kinsara RA, Hipel KW, Kilgour DM (2013). Inverse approach in third party intervention. 2013 IEEE International Conference on Systems, Man, and Cybernetics, Manchester, UK, October 13–16, 2013.Google Scholar
  22. Lee DW, Lai PB (2015). The practice of mediation to resolve clinical, bioethical, and medical malpractice disputes. Hong Kong Medical Journal 21(6):560–564.CrossRefGoogle Scholar
  23. Liebman BL (2013). Malpractice mobs: Medical dispute resolution in China. Columbia Law Review 113(1):181–264.Google Scholar
  24. Moore CW (2014).The Mediation Process: Practical Strategies for Resolving Conflict(4ed). Jossey-Bass, San Francisco, USA.Google Scholar
  25. Nash JF (1950). Equilibrium points in n-person games. Proceedings of the National Academy of Sciences of the United States of America 36(1): 48–49.MathSciNetCrossRefzbMATHGoogle Scholar
  26. Nash J (1951).Non-cooperative games. Annals of Mathematics 54(2):286–295.MathSciNetCrossRefzbMATHGoogle Scholar
  27. NHFPC (2017). National health and family planning commission 2016 annual report on the work of the construction of legal government. http://www.nhfpc.gov.cn/fzs/s3578/201709/713971c7f03d4e94bdc31109754c4c2b.shtml Google Scholar
  28. Peng X, Hipel KW, Kilgour DM, Fang L (1997). Representing ordinal preferences in the decision support system gmcr II. IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, Orlando, USA, October 12–15, 1997.Google Scholar
  29. Prein H (1987). Strategies for third party intervention. Human Relations 40(11):699–719.CrossRefGoogle Scholar
  30. Regan PM (1996). Conditions of successful third-party intervention in intrastate conflicts. The Journal of Conflict Resolution 40(2):336–359.CrossRefGoogle Scholar
  31. Rubin JZ (1980). Experimental research on third-party intervention in conflict: Toward some generalizations. Psychological Bulletin 87(2):379–91.CrossRefGoogle Scholar
  32. Sakakibara H, Okada N, Nakase D (2002). The application of robustness analysis to the conflict with incomplete information. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 32(1):14–23.CrossRefGoogle Scholar
  33. Sakamoto M, Hagihara Y, Hipel KW (2005). Coordination process by a third party in the conflict between Bangladesh and India over regulation of the Ganges River. IEEE International Conference on Systems, Man and Cybernetics, Waikoloa, USA, October 10–10, 2005.Google Scholar
  34. Tsai JF, Lin MH, Hu YC (2008). Finding multiple solutions to general integer linear programs. European Journal of Operational Research 184(2):802–809.MathSciNetCrossRefzbMATHGoogle Scholar
  35. Wang J, Hipel KW, Fang L, Dang Y (2018). Matrix representations of the inverse problem in the graph model for conflict resolution. European Journal of Operational Research 270(1):282–293.MathSciNetCrossRefzbMATHGoogle Scholar
  36. Xu H, Hipel KW, Kilgour DM (2007). Matrix representation of conflicts with two decision-makers. IEEE International Conference on Systems, Man and Cybernetics, Montreal. Canada, October 7–10, 2007.Google Scholar
  37. Xu H, Hipel KW, Kilgour DM (2008). Matrix representation of solution concepts in multiple-decision-maker graph models. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 39(1):96–108.CrossRefGoogle Scholar
  38. Xu H, Hipel KW, Kilgour DM, Fang L (2018). Conflict Resolution Using the Graph Model: Strategic Interactions in Competition and Cooperation. Springer.CrossRefzbMATHGoogle Scholar
  39. Young OR (2015). The Intermediaries: Third Parties in International Crises. Princeton University Press, Princeton, USA.Google Scholar
  40. Yu J, Hipel KW, Kilgour DM, Zhao M (2016). Option prioritization for unknown preference. Journal of Systems Science and Systems Engineering 25(1):39–61.CrossRefGoogle Scholar
  41. Zanjanian H, Abdolabadi H, Niksokhan MH, Sarang A (2018). Influential third party on water right conflict: A game theory approach to achieve the desired equilibrium (case study: Ilam dam, Iran). Journal of Environmental Management 214:283–294.CrossRefGoogle Scholar
  42. Zhao M (2011). Evaluation of the third-party mediation mechanism for medical disputes in China. Medicine and Law 30(3):401–415.Google Scholar
  43. Zhong Y (2015). People’s Mediation Skills in Doctor-patient Disputes and Typical Case Analysis. Jindun, Beijing, China, in Chinese.Google Scholar

Copyright information

© Systems Engineering Society of China and Springer-Verlag GmbH Germany 2019

Authors and Affiliations

  1. 1.College of Economics and ManagementNanjing University of Aeronautics and AstronauticsNanjingChina
  2. 2.Faculty of Business AdministrationMemorial University of NewfoundlandSt. John’s, Newfoundland and LabradorCanada

Personalised recommendations