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Profit distribution in IPD projects based on weight fuzzy cooperative games

    Shuwen Guo Affiliation
    ; Junwu Wang Affiliation

Abstract

Integrated Project Delivery (IPD) is regarded as an effective project delivery method that can deal with the challenge of the rapid development of the architecture, engineering, and construction (AEC) industry. In the IPD team, the alliance profit is not distributed fairly and effectively due to uncertainty, preventing the achievement of the IPD project goals. This study focuses on optimizing the profit distribution among stakeholders in IPD projects and uses quadratic programming models to solve fuzzy cooperative games in the IPD. A payoff function is used in the fuzzy alliance to determine the characteristics of the interval-valued fuzzy numbers, and different weights of the alliance and the efficiency of the player’s participation in the IPD are considered in the profit distribution. A case study is conducted, and the results of the proposed method are compared with those of crisp cooperative games. The results show that the fuzzy cooperative game increases the profit of participants in IPD projects. It is more practical to use weight fuzzy cooperative games than crisp games to express imputation. Moreover, the quadratic programming models and methods result in a fair and efficient profit distribution scheme in IPD projects.


First published online 31 December 2021

Keyword : profit distribution, integrated project delivery, fuzzy cooperative game, weight of alliance, interval-valued fuzzy numbers, quadratic programming

How to Cite
Guo, S., & Wang, J. (2022). Profit distribution in IPD projects based on weight fuzzy cooperative games. Journal of Civil Engineering and Management, 28(1), 68–80. https://doi.org/10.3846/jcem.2021.16156
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Jan 11, 2022
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References

Abraham, S., & Punniyamoorthy, M. (2021). A fuzzy approach using asymmetrical triangular distribution in a two-person zero-sum game for a multi-criteria decision-making problem. Quantum Machine Intelligence, 3(1), 20. https://doi.org/10.1007/s42484-021-00044-y

American Institute of Architects. (2010). Integrated project delivery: Case studies. California Council.

Alparslan-Gök, S. Z., Miquel, S., & Tijs, S. (2009). Cooperation under interval uncertainty. Mathematical Methods of Operations Research, 69, 99–109. https://doi.org/10.1007/s00186-008-0211-3

Ashcraft, H. W. (2012). The IPD framework. Hanson Bridgett.

Babbar, N., Kumar, A., & Bansal, A. (2013). Solving fully fuzzy linear system with arbitrary triangular fuzzy numbers. Soft Computing, 17(4), 691–702. https://doi.org/10.1007/s00500-012-0941-2

Boodai, F. J. (2014). Achieving construction project success through integration in the project delivery system from an owner’s perspective [Doc-toral dissertation]. The University of Wisconsin, Madison.

Construction Management Association of America. (2010). Managing integrated project delivery. https://www.leanconstruction.org/wp-content/uploads/2016/02/CMAA_Managing_Integrated_Project_Delivery_1.pdf

United Kingdom’s Office of Government Commerce. (2007). Achieving excellence in construction Procurement Guide 05: The integrated project team: Team working and partnering.

Dubois, D., & Prade, H. (1980). Fuzzy sets and systems: Theory and applications. Academic Press.

Eissa, R., Eid, M. S., & Elbeltagi, E. (2021). Conceptual profit allocation framework for construction joint ventures: Shapley value approach. Jour-nal of Management in Engineering, 37(3), 04021016. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000911

Ernst and Young. (2014). Spotlight on oil and gas megaprojects (No. DW0426). EYGM Limited, EYG.

Han, T., & Li, D. (2016). Shapley value method of profit allocation for cooperative enterprises with intuitionistic fuzzy coalitions. Journal of Sys-tems Science and Mathematical Sciences, 36, 719–727.

Jene, S., & Zelewski, S. (2014). Practical application of cooperative solution concepts for distribution problems: an analysis of selected game theo-retic solution concepts from an economic point of view. International Journal of Mathematics, Game Theory, and Algebra, 23(1), 19–37.

Jia, N. X., & Yokoyama, I. L. (2003). Profit allocation of independent power producers based on cooperative game theory. Electrical Power and Energy Systems, 25, 633–641. https://doi.org/10.1016/S0142-0615(02)00180-1

Khalfan, M. M. A., & McDermott, P. (2006). Innovating for supply chain integration within construction. Construction Innovation, 6, 143–157. https://doi.org/10.1108/14714170610710695

Li, D.-F. (2012). A fast approach to compute fuzzy values of matrix games with payoffs of triangular fuzzy numbers. European Journal of Opera-tional Research, 223(2), 421–429. https://doi.org/10.1016/j.ejor.2012.06.020

Lin, L., & Wang, H. (2019). Dynamic incentive model of knowledge sharing in construction project team based on differential game. Journal of the Operational Research Society, 70, 2084–2096. https://doi.org/10.1080/01605682.2018.1516177

Liu, Q., & Cheng, Z. (2020). Research on profit distribution of construction project dynamic alliance under integrated project delivery mode. Value Engineering, 39, 58–61.

Long, Y., Peng, J., & Iwamura, K. (2009). Uncertain equilibrium analysis on profits distribution between partner firms in competitive strategic alliances. Soft Computing, 13(2), 203–208. https://doi.org/10.1007/s00500-008-0302-3

Meade, L. M., & Lilesa, D. H. (1997). Justifying strategic alliances and partnering: a prerequisite for virtual enterprising. Omega, 25(1), 29–42. https://doi.org/10.1016/S0305-0483(96)00034-5

Moore, R. E. (1979). Methods and applications of interval analysis. DBLP. https://doi.org/10.1137/1.9781611970906

Myerson, R. B. (1997). Game theory: Analysis of conflict. Harvard University Press.

Pishdad-Bozorgi, P., & Srivastava, D. (2018). Assessment of integrated project delivery (IPD) risk and reward sharing strategies from the stand-point of collaboration: A game theory approach. In Proceedings of Construction Research Congress 2018: Construction Project Management (pp. 196–206). ASCE. https://doi.org/10.1061/9780784481271.020

Shapley, L. S. (1953). A value for n-persons games. Annals of Mathematics Studies, 28(7), 307–318. https://doi.org/10.1515/9781400881970-018

Su, D., & Yang, J. (2018). Distribution model of fuzzy graph cooperative games with restricted alliance and its application. Journal of FuZhou University (Natural Science Edition), 46, 458–465.

Su, S. (2020). Research on triangular fuzzy number type entrepreneurial team many persons income distribution cooperation game based on satis-factory degree. Mathematics in Practice and Theory, 50(1), 1–8.

Teng, Y., Li, X., Wu, P., & Wang, X. (2017). Using Cooperative game theory to determine profit distribution in IPD projects. International Jour-nal of Construction Management, 19, 32–45. https://doi.org/10.1018/15623599.2017.1358075

Wang, R., & Yuan, Z. (2019). Dynamic distribution of cooperative profit mechanism in EPC projects considering satisfaction of all parties. Journal of Engineering Management, 33, 13–18. https://doi.org/10.13991/j.cnki.jem.2019.02.003

Ye, Y., Li, D., & Yu, G. (2019). A joint replenishment model with demands represented by triangular fuzzy numbers and its cost allocation meth-od. Journal of Systems Science and Complexity, 39, 1142–1158.

Yu, X., & Zhang, Q. (2019). Core for game with fuzzy generalized triangular payoff value. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 27(5), 789–813. https://doi.org/10.1142/S0218488519500351

Zhao, W. J., & Liu, J. C. (2018). Triangular fuzzy number-typed fuzzy cooperative games and their application to rural e-commerce regional coop-eration and profit sharing. Symmetry, 10(12), 699. https://doi.org/10.3390/sym10120699