The Complexity and Simulation of Revenue Sharing Negotiation Based on Construction Stakeholders

This paper focuses on the complexity characteristics of a stakeholder’s revenue sharing for time compression in construction projects, such as adopting a life cycle perspective, the preferences of stakeholders, and the adaptability behaviors in the negotiation process. We build an agent-based model on revenue sharing negotiation. Considering that the agents who are in a weak position not only care about their own benefits but also compare their benefits to others, we design an experimental scenario where a contractor has fairness preference based on China’s reality. According to different sympathy and envy coefficients, we can divide the inequity aversion preference into three typical types, and we research how a contractor’s different types of inequity aversion preferences impact revenue sharing coefficient of agreements, results of successful negotiations, and efficiency in negotiations. Results are as follows: it is advantageous for a contractor to maintain a modest inequity aversion for their own earnings and the degree of sympathy preference in inequity aversion has an important impact on the time to reach consensus while the degree of jealousy preference has no obvious effect. If contractors’ sympathy preference is maintained within a moderate range, it will achieve a higher success rate of negotiations in the negotiation process; the success rate of negotiation is affected largely by the agents’ sympathy preference, though it is also influenced by the jealousy preference, but it is not very sensitive.

[1]  Sai On Cheung,et al.  A cusp catastrophe model of withdrawal in construction project dispute negotiation , 2012 .

[2]  Keith W. Hipel,et al.  Facilitating risky project negotiation: An integrated approach using fuzzy real options, multicriteria analysis, and conflict analysis , 2015, Inf. Sci..

[3]  Ehsan Eshtehardian,et al.  Multi-mode resource-constrained discrete time–cost-resource optimization in project scheduling using non-dominated sorting genetic algorithm , 2013 .

[4]  Tony Haitao Cui,et al.  Fairness and Channel Coordination , 2007, Manag. Sci..

[5]  Gary E. Bolton,et al.  Estimating the Influence of Fairness on Bargaining Behavior , 2008, Manag. Sci..

[6]  Michael J. Fry,et al.  Supply-chain performance anomalies: Fairness concerns under private cost information , 2016, Eur. J. Oper. Res..

[7]  Yaozhong Wu,et al.  Social Preferences and Supply Chain Performance: An Experimental Study , 2008, Manag. Sci..

[8]  Jingjing Du,et al.  Solution to the Time-Cost-Quality Trade-off Problem in Construction Projects Based on Immune Genetic Particle Swarm Optimization , 2014 .

[9]  Do Ba Khang,et al.  Time, cost and quality trade-off in project management: a case study , 1999 .

[10]  Kaj U. Koskinen,et al.  Role of boundary objects in negotiations of project contracts , 2009 .

[11]  Elena Katok,et al.  Wholesale Pricing under Mild and Privately Known Concerns for Fairness , 2014 .

[12]  Nalina Suresh,et al.  Project management with time, cost, and quality considerations , 1996 .

[13]  M. Rabin Published by: American , 2022 .

[14]  E. Fehr A Theory of Fairness, Competition and Cooperation , 1998 .

[15]  Wei Tong Chen,et al.  A method to determine minimum contract bids for incentive highway projects , 2003 .

[16]  Xiaole Wu,et al.  Fairness in Selling to the Newsvendor , 2013 .

[17]  Humberto González,et al.  Numerical synthesis of pontryagin optimal control minimizers using sampling-based methods , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

[18]  Sai On Cheung,et al.  Withdrawal in Construction Project Dispute Negotiation , 2011 .

[19]  Xianbo Zhao,et al.  Agent-Based Debt Terms' Bargaining Model to Improve Negotiation Inefficiency in PPP Projects , 2016, J. Comput. Civ. Eng..

[20]  Keith W. Hipel,et al.  Attitude-Based Strategic Negotiation for Conflict Management in Construction Projects , 2010 .

[21]  Jinming Liu,et al.  PROJECT TIME-COST TRADE-OFF OPTIMIZATION BY MAXIMAL FLOW THEORY , 2004 .

[22]  Cheng-Min Feng,et al.  A royalty negotiation model for BOT (build-operate-transfer) projects: The operational revenue-based model , 2011, Math. Comput. Model..

[23]  M. Rabin,et al.  Understanding Social Preference with Simple Tests , 2001 .

[24]  Jian Liu,et al.  Research into the moderating effects of progress and quality performance in project dispute negotiation , 2014 .

[25]  Baabak Ashuri,et al.  Shuffled Frog-Leaping Model for Solving Time-Cost-Resource Optimization Problems in Construction Project Planning , 2015 .

[26]  Jiujun Cheng,et al.  Time Performance Optimization and Resource Conflicts Resolution for Multiple Project Management , 2016, IEICE Trans. Inf. Syst..

[27]  Jing Yang,et al.  Cooperative advertising in a distribution channel with fairness concerns , 2013, Eur. J. Oper. Res..

[28]  Guangdong Wu,et al.  Robust Optimization for Time-Cost Tradeoff Problem in Construction Projects , 2014 .

[29]  Angus Jeang,et al.  Project management for uncertainty with multiple objectives optimisation of time, cost and reliability , 2015 .

[30]  Fen-May Liou,et al.  Automated Approach to Negotiations of BOT Contracts with the Consideration of Project Risk , 2008 .

[31]  Sanjay Jain,et al.  Behavior-Based Pricing: An Analysis of the Impact of Peer-Induced Fairness , 2015, Manag. Sci..

[32]  Chengbin Chu,et al.  Newsvendor model for a dyadic supply chain with Nash bargaining fairness concerns , 2014 .

[33]  Teck-Hua Ho,et al.  Self-tuning experience weighted attraction learning in games , 2007, J. Econ. Theory.

[34]  Paul R. Messinger,et al.  Production , Manufacturing and Logistics The role of fairness in competitive supply chain relationships : An experimental study , 2016 .