مدل تصمیم‌گیری گراف برای تخصیص ریسک در قراردادهای طرح و ساخت، با استفاده از تئوری بازی‌ها

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشکده هنر و معماری، دانشگاه آزاد اسلامی، واحد تهران غرب، تهران، ایران

2 دانشکده فنی و مهندسی، دانشگاه آزاد اسلامی، واحد تهران جنوب، تهران، ایران .

چکیده

توافق بر نحوه تخصیص ریسک‌ها شرط موفقیت پروژه شناخته می­شود. به دلیل برداشت­های متفاوت و منافع متضاد عوامل پروژه، مذاکرات تخصیص ریسک به منظور انتخاب تخصیص بهینه ریسک‌ها، فرآیندی دشوار و پر هزینه است. در این مقاله با مدل‌سازی مذاکرات تخصیص ریسک در چهارچوب تحلیل حل اختلاف بر مبنای تئوری بازی‌ها، یک رویکرد تصمیم‌گیری بر مبنای مدل گراف برای حل مذاکرات قراردادی و انتخاب تخصیص ریسک بهینه توسعه داده شده است. در این رویکرد، با تحلیل رفتار بازیگران و تصمیم‌ گیرندگان فرآیند تخصیص ریسک، اولویت‌های تصمیم­گیری ذی‌نفعان در قالب تحلیل هزینه-فایده هر تخصیص ریسک محاسبه شده و با پیش‌بینی حرکت‌های متقابل هر طرف برای کسب بیش‌ترین منافع یا فرار بیش‌ترین زیان، مدلی خاص برای دستیابی به تفاهم بین تصمیم‌ گیرندگان به منظور توافق بر انتخاب تخصیص بهینه ارائه می‌شود. مدل پیشنهادی در قالب یک برنامه نرم افزاری در محیط متلب پیاده‌سازی شده است و نتایج آن در یک پروژه موردی حوزه آب و نیرو مورد بررسی و مقایسه قرار گرفته است. مقایسه نتایج مدل پیشنهادی با دیگر مدل‌های کمی تخصیص ریسک نشان می‌دهد که استفاده از تئوری بازی‌ها می‌تواند الگوی متعادل‌تری برای تخصیص ریسک‌ها ارائه دهد. مدل پیشنهادی این مزیت حیاتی را دارد که برخلاف مطالعات مشابه، صرفا عامل مسئول مدیریت ریسک را تعیین نمی‌کند بلکه اقدامات لازم برای رسیدن به تخصیص ریسک متعادل را بیان کرده و تبعات تصمیم را برای تصمیم‌ گیرنده روشن می‌نماید.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

The Graph Decision Model for Risk Allocation in Design-Build Contracts; Game Theory approach

نویسندگان [English]

  • garshasb khazaeni 1
  • Ali khazaeni 2
1 Assistant Professor, Islamic Azad University West Tehran branch
2 Islamic Azad University, South Tehran
چکیده [English]

Risk allocation, the definition and division of responsibility associated with a possible ‎future loss or gain, seeks to assign responsibility for a variety of hypothetical circumstances ‎should a project not proceed as planned. The result of improper risk allocation is increased ‎costs, project delays and services, which cause loss of value-for-money for the public interest. This paper introduced a decision support system based on the graph model for systematically resolving construction risk allocation. In this model mainly assumed success of a contract needs to ‎agreement on how risks are allocated by parties. The graph analysis process considers ‎the decision-makers, their decision options, and their relative preferences when modeling ‎risk allocation negotiation as a game theory problem. Owners could also use the model to perform an in-depth stability analysis in order to ‎ascertain the ‎possible compromise resolutions or equilibrium. The model predicts the sequence ‎of decisions that took place in the dispute and furnishes an array of useful strategic insights ‎about the risk allocation renegotiation. Moreover, the model to determine how ‎changes in preferences can affect the equilibrium results executes a sensitivity analysis. This risk allocation procedure is ‎useful for both researchers and practitioners to better deal with the dispute-prone nature of ‎ construction contracts.‎

کلیدواژه‌ها [English]

  • Risk Management
  • Risk Allocation
  • Project management
  • Graph
  • Game Theory

مراجع

[1] C.M. Gordon, Choosing appropriate construction contracting method, Journal of construction engineering and management, 120(1) (1994) 196-210.
[2] A. Nagendra, A. Sharan, Risk Analysis for Project Management, Journal of Applied Management-Jidnyasa, 9(2) (2018) 22-31.
[3] H. Wang, Y. Liu, W. Xiong, J. Song, The moderating role of governance environment on the relationship between risk allocation and private investment in PPP markets: Evidence from developing countries, International Journal of Project Management, 37(1) (2019) 117-130.
[4] G. Khazaeni, M. Khanzadi, A. Afshar, Fuzzy adaptive decision making model for selection balanced risk allocation, International Journal of Project Management, 30(4) (2012) 511-522.
[5] G. Khazaeni, M. Khanzadi, A. Afshar, Optimum risk allocation model for construction contracts: fuzzy TOPSIS approach, Canadian Journal of Civil Engineering, 39(7) (2012) 789-800.
[6] E.I. Ezulike, J.G. Perry, K. Hawwash, The barriers to entry into the PFI market, Engineering Construction and Architectural Management, 4(3) (1997) 179-193.
[7] D. Perez, J. Gray, M. Skitmore, Perceptions of risk allocation methods and equitable risk distribution: a study of medium to large Southeast Queensland commercial construction projects, International Journal of Construction Management, 17(2) (2017) 132-141.
[8] C.K. Tembo-Silungwe, N. Khatleli, Development of risk misallocation causal networks using interpretive judgement in the construction industry, International Journal of Construction Management,  (2020) 1-15.
[9] W. Bank, Global Development Finance 2002 Vol 1: Financing the Poorest Countries. ANALYSIS AND SUMMARY TABLES, The World Bank, 2002.
[10] F. Medda, A game theory approach for the allocation of risks in transport public private partnerships, International journal of project management, 25(3) (2007) 213-218.
[11] L. Bing, A. Akintoye, P.J. Edwards, C. Hardcastle, The allocation of risk in PPP/PFI construction projects in the UK, International Journal of project management, 23(1) (2005) 25-35.
[12] E. Fisk, Construction Project Administration Prentice Hall, New Jersey, USA,  (1997).
[13] F. Nasirzadeh, M. Khanzadi, M. Rezaie, Dynamic modeling of the quantitative risk allocation in construction projects, International Journal of Project Management, 32(3) (2014) 442-451.
[14] K.C. Lam, D. Wang, P.T. Lee, Y.T. Tsang, Modelling risk allocation decision in construction contracts, International journal of project management, 25(5) (2007) 485-493.
[15] K. Almarri, S. Alzahrani, H. Boussabaine, An evaluation of the impact of risk cost on risk allocation in public private partnership projects, Engineering, Construction and Architectural Management,  (2019).
[16] R. Rafaat, H. Osman, M. Georgy, M. Elsaid, Preferred risk allocation in Egypt’s water sector PPPs, International Journal of Construction Management, 20(6) (2020) 585-597.
[17] K. Ashmawi, L.A. Hadidi, S. Assaf, F.M. Tuffaha, K. Al-Ofi, Risk assessment and allocation in the contract for public works used in Saudi Arabia construction industry, Cogent Engineering, 5(1) (2018) 1490148.
[18] C.K. Tembo-Silungwe, N. Khatleli, Identification of enablers and constraints of risk allocation using structuration theory in the construction industry, Journal of Construction Engineering and Management, 144(5) (2018) 04018021.
[19] A. Shrestha, J. Tamošaitienė, I. Martek, M.R. Hosseini, D.J. Edwards, A principal-agent theory perspective on PPP risk allocation, Sustainability, 11(22) (2019) 6455.
[20] M. Parchami, E. Tghizadeh, B. Saghi, ‎, Examining the contractual allocation of risks in the general terms of the three-factor contract‎, Journal of Fine Arts - Architecture and Urban Planning, 3(46) (2011) 39-50. (In Persian)
[21] G. Khazaeni, M. Fatahi, E. Zeighami, E. Abasian, Optimal risk allocation multi-objective decision model; Multi-objective optimization algorithm of ‎ant community‎, ASAS Scientific and Research Journal, 21(55)  44-54. (In Persian)
[22] B. Rasouli, S. kheradiar, B. Banimohamad, ‎, Ranking and allocation of critical risks of public-private partnership stages with Delphi technique in ‎the context of resistance economy (Case study: water and sewage industry of Guilan province)‎, Journal of Investment Knowledge, 7(27) (2018) 125-140. (In Persian)
[23] G. Khazaeni, M. Khanzadi, A. Afshar, Optimizing risk allocation in construction ‎projects; the ant community optimization algorithm, Sharif Scientific and Research Journal, 229(3) (2013) 61-69. (In Persian)
[24] M. Kassab, K. Hipel, T. Hegazy, Conflict resolution in construction disputes using the graph model, Journal of construction engineering and management, 132(10) (2006) 1043-1052.
[25] F. Orrego Vicuña, Arbitration in a New International Alternative Dispute Resolution System, ICSID News, 18(2) (2001).
[26] H. Mann, A. Cosbey, L. Peterson, K. von Moltke, Possible improvement of the framework for ICSID arbitration, Comments on ICSID Discussion Paper,  (2004).
[27] A. Johnston, S. Iwasaki, Effective Use of Alternative Dispute Resolution (ADR) Provisions, in, Morrison and Foerster Legal Updates and News, March, 2003.
[28] K.W. Hipel, L. Fang, D.M. Kilgour, The graph model for conflict resolution: Reflections on three decades of development, Group Decision and Negotiation, 29(1) (2020) 11-60.
[29] R.Z. Norman, Structural models: An introduction to the theory of directed graphs,  (1965).
[30] L. Fang, K.W. Hipel, D.M. Kilgour, Interactive decision making: the graph model for conflict resolution, John Wiley & Sons, 1993.
[31] O. Morgenstern, J. Von Neumann, Theory of games and economic behavior, Princeton university press, 1953.
[32] N. Howard, Paradoxes of rationality: Theory of metagames and political behaviour, MIT press, 1971.
[33] J.F. Nash, Equilibrium points in n-person games, Proceedings of the national academy of sciences, 36(1) (1950) 48-49.
نشریه مهندسی عمران امیرکبیر
دوره 54، شماره 1
فروردین 1401
صفحه 323-342

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