EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues Volume 58 / No 1 (January-February 2024) RAIRO-Oper. Res., 58 1 (2024) 909-932 References
Open Access
Issue
RAIRO-Oper. Res.
Volume 58, Number 1, January-February 2024
Page(s) 909 - 932
DOI https://doi.org/10.1051/ro/2024010
Published online 22 February 2024
  • Q. An, Y. Wen, T. Ding and Y. Li, Resource sharing and payoff allocation in a three-stage system: Integrating network DEA with the Shapley value method. Omega 85 (2019) 16–25. [Google Scholar]
  • M. Asrol, M. Machfud, M. Yani and E. Taira, Supply chain fair profit allocation based on risk and value added for sugarcane agro-industry. Oper. Supply Chain Manag. Int. J. 13 (2020) 150–165. [CrossRef] [Google Scholar]
  • W.E. Baker and J.M. Sinkula, The synergistic effect of market orientation and learning orientation on organizational performance. J. Acad. Mark. Sci. 27 (1999) 411–427. [CrossRef] [Google Scholar]
  • K. Bi, H. Hu and D. Zhang, Impact of incubator orchestration capacity on innovation performance of incubation network: The mediating role of network synergistic effect. Manag. Rev. 29 (2017) 36–46. [Google Scholar]
  • S. Borkotokey, S. Chakrabarti, R.P. Gilles, L. Gogoi and R. Kumar, Probabilistic network values. Math. Soc. Sci. 113 (2021) 169–180. [CrossRef] [Google Scholar]
  • P. Borm, G. Owen and S. Tijs, On the position value for communication situations. SIAM J. Discret. Math. 5 (1992) 305–320. [CrossRef] [Google Scholar]
  • F. Ciardiello, A. Genovese and A. Simpson, A unified cooperative model for environmental costs in supply chains: the Shapley value for the linear case. Ann. Oper. Res. 290 (2020) 421–437. [CrossRef] [MathSciNet] [Google Scholar]
  • J. Dai, Profit distribution model of collaborative R&D based on nash bargaining. R&D Manag. (2015). [Google Scholar]
  • C. D’Aspremont and A. Jacquemin, Cooperative and noncooperative R&D in duopoly with spillovers. Am. Econ. Rev. 78 (1988) 1133–1137. [Google Scholar]
  • O. Dedehayir, T. Nokelainen and S.J. M¨akinen, Disruptive innovations in complex product systems industries: A case study. J. Eng. Technol. Manage. 33 (2014) 174–192. [CrossRef] [Google Scholar]
  • E. Feess and J.-H. Thun, Surplus division and investment incentives in supply chains: A biform-game analysis. Eur. J. Oper. Res. 234 (2014) 763–773. [CrossRef] [Google Scholar]
  • J. Fernández, I. Gallego, A. Jiménez-Losada and M. Ordóñez, The cg-position value for games on fuzzy communication structures. Fuzzy Sets Syst. 341 (2018) 37–58. [CrossRef] [Google Scholar]
  • Q. Fu, C.-K. Sim and C.-P. Teo, Profit sharing agreements in decentralized supply chains: A distributionally robust approach. Oper. Res. 66 (2018) 500–513. [CrossRef] [MathSciNet] [Google Scholar]
  • J. Gao, X. Yang and D. Liu, Uncertain shapley value of coalitional game with application to supply chain alliance. Appl. Soft Comput. 56 (2017) 551–556. [CrossRef] [Google Scholar]
  • Q. Ge and M. Wang, The benefit assignment research on industry-university-research cooperative innovation strategy alliance based on modified asymmetric nash negotiation. J. Ind. Eng. Manag. 32 (2018) 79–83. [Google Scholar]
  • G. Hamel, Collaborate with your competitors and win. Harv. Bus. Rev. 67 (1989) 133–139. [Google Scholar]
  • S. Hu, How is a social cooperation in distribution?-“Clique solution” of cooperation game beyond Shapley value. Manag. World 34 (2018) 83–93. [Google Scholar]
  • X.-F. Hu, D.-F. Li and G.-J. Xu, Fair distribution of surplus and efficient extensions of the Myerson value. Econ. Lett. 165 (2018) 1–5. [CrossRef] [Google Scholar]
  • L. Jian, D. Wang, D. Wang and X. Du, A comparative study on the main manufacturer-core supplier collaborative development of large civil aircraft based on social networks. J. Nanjing Univ. Aeronaut. Astronaut. (Soc. Sci.) 21 (2019) 72–83. [Google Scholar]
  • X. Jiang, L. Wang, B. Cao and X. Fan, Benefit distribution and stability analysis of enterprises’ technological innovation cooperation alliance. Comput. Ind. Eng. 161 (2021) 107637. [CrossRef] [Google Scholar]
  • A. Jiménez-Losada, J. Fernández and M. Ordóñez, Myerson values for games with fuzzy communication structure. Fuzzy Sets Syst. 213 (2013) 74–90. [CrossRef] [Google Scholar]
  • E. Kemahlıoğlu-Ziya and J.J. Bartholdi, Centralizing inventory in supply chains by using shapley value to allocate the profits. Manuf. Serv. Oper. Manag. 13 (2011) 146–162. [CrossRef] [Google Scholar]
  • J.J. Lee and H. Yoon, A comparative study of technological learning and organizational capability development in complex products systems: Distinctive paths of three latecomers in military aircraft industry. Res. Policy 44 (2015) 1296–1313. [CrossRef] [Google Scholar]
  • D.L. Li and E.-F. Shan, The Myerson value on local structures of coalitions. J. Oper. Res. Soc. China 7 (2019) 461–473. [CrossRef] [MathSciNet] [Google Scholar]
  • D.L. Li and E. Shan, The position value and the structures of graphs. Appl. Math. Comput. 356 (2019) 190–197. [MathSciNet] [Google Scholar]
  • T. Li and J. Chen, Alliance formation in assembly systems with quality-improvement incentives. Eur. J. Oper. Res. 285 (2020) 931–940. [CrossRef] [Google Scholar]
  • X. Li, H. Sun and D. Hou, On the position value for communication situations with fuzzy coalition. J. Intell. Fuzzy Syst. 33 (2017) 113–124. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Li, J. Zhao and E. Shan, A characterization of the position value for hypernetwork situations. Oper. Res. Trans. 23 (2019) 165–174. [MathSciNet] [Google Scholar]
  • R. Li, N. Yang, Y. Zhang and H. Liu, Risk propagation and mitigation of design change for complex product development (CPD) projects based on multilayer network theory. Comput. Ind. Eng. 142 (2020). [Google Scholar]
  • S. Liu and L.G. Papageorgiou, Fair profit distribution in multi-echelon supply chains via transfer prices. Omega 80 (2018) 77–94. [CrossRef] [Google Scholar]
  • G. Liu, L. Wei, J. Gu, T. Zhou and Y. Liu, Benefit distribution in urban renewal from the perspectives of efficiency and fairness: A game theoretical model and the government’s role in China. Cities 96 (2020) 102422. [CrossRef] [Google Scholar]
  • J.-C. Liu, J.-B. Sheu, D.-F. Li and Y.-W. Dai, Collaborative profit allocation schemes for logistics enterprise coalitions with incomplete information. Omega 101 (2021) 102237. [CrossRef] [Google Scholar]
  • R. Lotfi, B. Kargar, M. Rajabzadeh, F. Hesabi and E. Özceylan, Hybrid fuzzy and data-driven robust optimization for resilience and sustainable health care supply chain with vendor-managed inventory approach. Int. J. Fuzzy Syst. 24 (2022) 1216–1231. [CrossRef] [MathSciNet] [Google Scholar]
  • R. Lotfi, H. Nazarpour, A. Gharehbaghi, S.M.H. Sarkhosh and A. Khanbaba, Viable closed-loop supply chain network by considering robustness and risk as a circular economy. Environ. Sci. Pollut. Res. 29 (2022) 70285–70304. [CrossRef] [PubMed] [Google Scholar]
  • R. Lotfi, M. Rajabzadeh, A. Zamani and M.S. Rajabi, Viable supply chain with vendor-managed inventory approach by considering blockchain, risk and robustness. Ann. Oper. Res. (2022) 1–20. [Google Scholar]
  • R. Lotfi, M.S. Mehrjardi, P. Mohajer Ansari, F. Zolfaqari and M. Afshar, Antifragile, sustainable, and agile supply chain network design by considering resiliency, robustness, risk, and environmental requirements. Environ. Sci. Pollut. Res. (2023). [Google Scholar]
  • R. Lotfi, H. Hazrati, S.S. Ali, S.M. Sharifmousavi, A. Khanbaba and M. Amra, Antifragile, sustainable and agile healthcare waste chain network design by considering blockchain, resiliency, robustness and risk. Cent. Eur. J. Oper. Res. (2023). [Google Scholar]
  • P. Lv, X. Hu and B. Lu, Cooperative game model for HSR express based on relationship networks between participants. Syst. Eng. Theory Pract. 37 (2017) 1536–1547. [Google Scholar]
  • M. Majidpour, Technological catch-up in complex product systems. J. Eng. Technol. Manage. 41 (2016) 92–105. [CrossRef] [Google Scholar]
  • R. Meessen, Communication games in dutch. Depart. Math. (1988). [Google Scholar]
  • R.B. Myerson, Graphs and cooperation in games. Math. Oper. Res. 2 (1977) 225–229. [CrossRef] [MathSciNet] [Google Scholar]
  • T.-Y. Park and I. Ji, From mass production to complex production: case of the Korean telecom equipment sector. Asia-Pac. J. Account. Econ. 22 (2015) 78–102. [Google Scholar]
  • K. Prince, M. Barrett and E. Oborn, Dialogical strategies for orchestrating strategic innovation networks: The case of the internet of things. Inf. Organ. 24 (2014) 106–127. [CrossRef] [Google Scholar]
  • L. Quanlin, Z. Yu and E. Chengguo, Network game between multiple agricultural communes and multiple supermarkets. J. Syst. Eng. 34 (2019) 29–45. [Google Scholar]
  • E. Shan, L. Cai, H. Zeng and C. Peng, The v-position value measure on centrality of hypernetworks. Oper. Res. Manag. Sci. 29 (2020) 135–142. [Google Scholar]
  • O. Skibski and M. Yokoo, An algorithm for the Myerson value in probabilistic graphs with an application to weighted voting. IEEE Intell. Syst. 32 (2017) 32–39. [CrossRef] [Google Scholar]
  • M. Slikker, A characterization of the position value. Int. J. Game Theory 33 (2005) 505–514. [CrossRef] [Google Scholar]
  • J. Suh and S.-G. Yoon, Profit-sharing rule for networked microgrids based on Myerson value in cooperative game. IEEE Access 9 (2021) 5585–5597. [CrossRef] [Google Scholar]
  • H. Ting and L. Dengfeng, Shapley value method of profit allocation for cooperative enterprises with intuitionstic fuzzy coalitions. J. Syst. Sci. Math. Sci. 36 (2016) 719. [MathSciNet] [Google Scholar]
  • D. Wang, Q. Gong and F. Fang, Benefit distribution of the modular R&D network of high-tech enterprises. China Soft Sci. (2012) 177–184. [Google Scholar]
  • W. Xiaoyan and Y. Hui, Improvement and application of interval Shapley value method in fuzzy cooperative games. Comput. Eng. Appl. 49 (2013) 60–64. [Google Scholar]
  • X.-M. Xie and S. Liu, Impact mechanism of collaborative innovation modes on collaborative effect and innovation performance. J. Manag. Sci. 28 (2015) 27–39. [Google Scholar]
  • J. Xu and Y. Xu, Enterprise’s collaborative competence, network location and technology innovation performance-empirical analysis of manufacturing enterprises in the bohai coastal region. Manag. Rev. 27 (2015) 114–125. [Google Scholar]
  • Y. Zhang, L. Jian and Y. Zhang, University-industry cooperation network evaluation based on weighted scale-free network. Syst. Eng. 33 (2015) 68–73. [Google Scholar]
  • Y. Zhang, L. Jian, S. Liu, H. Zhao and Y. Liu, Interests coordination mechanism of university-industry network cooperation based on optimized shapley value-A case study in industrial technology innovation strategy alliance. Chin. Manag. Stud. 24 (2016) 36–44. [Google Scholar]
  • M. Zhang, N. Yang, X. Zhu and Y. Wang, The evolution of cooperation in public goods games on the scale-free community network under multiple strategy-updating rules. Phys. A Stat. Mech. Appl. 608 (2022) 128220. [CrossRef] [Google Scholar]
  • X.-X. Zheng, Z. Liu, K.W. Li, J. Huang and J. Chen, Cooperative game approaches to coordinating a three-echelon closed-loop supply chain with fairness concerns. Int. J. Prod. Econ. 212 (2019) 92–110. [CrossRef] [Google Scholar]
  • Y. Zhong, F. Guo, Z. Wang and H. Tang, Coordination analysis of revenue sharing in E-commerce logistics service supply chain with cooperative distribution. SAGE Open 9 (2019) 215824401987053. [CrossRef] [Google Scholar]
  • W. Zhu, H. Yuan, X. Zhang and J. Zhang, Study on benefit distribution of multimodal transport dynamic alliance based on the shapely value method. J. Coast. Res. 110 (2020) 104–107. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.