Research on Strategic Alliance Conflict Issues Based on the GMCR Model
DOI:
https://doi.org/10.54097/q68bge13Keywords:
Strategic alliances, alliance conflict, GMCR model, conflict research.Abstract
With the rapid advancement of global economic integration and technology, strategic alliances have become an essential means for multinational enterprises to swiftly enter foreign markets and implement globalization strategies. Conflicts among alliance partners significantly impact the stability of alliances and the profitability of enterprises. This study examines the effects of conflict on alliance stability from the perspectives of the causes of conflict and the categorization of conflicts. Furthermore, it employs the Graph Model for Conflict Resolution (GMCR) to model alliance conflicts, paving the way for new approaches to investigating conflict issues within strategic alliances.
Downloads
References
[1] Yaodong Luo. Procedural fairness and interfirm cooperation in strategic alliance. Strategic Management Journal, 2008 (1):27
[2] Carmina Cavazos. Entering into strategic alliances: an empirical test of the direct and interaction effects of managers’attitudes, subjective norms and perceived behavioral control [J]. Journal of Strategic Marketing, 2013 (1):3
[3] Wang Lingyun, Su Xiaoying. Research on the Enterprise-Union Relationship in Cross-border M&A Based on the Graph Model for Conflict Resulation. Journal of WUT (Information & Management Engineering), 2021, 43 (06): 562-568.
[4] Yang Zhenning, Bai Chunye. Trust, conflict and stability of cross-national technological strategic alliances. Science Research Management, 2018, 39 (07): 34-42.
[5] Chen Zhenhong, Dong Junwu. Conflict Management Among Strategic Alliance Partners. Science of Science and Management of S&T, 2004 (03):106-109.
[6] Zhao Shinan, Xu Haiyan. Dynamic Interaction Model of Price Conflicts in Dual-Channel Supply Chains Based on GMCR. Operations Research and Management Science, 2017, 26 (10):94-100.
[7] Fang L, Hipel KW, Kilgour DM, et al. A decision support system for interactive decision making-Part I: model formulation. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2003, 33 (1): 42-55.
[8] Xu L, Zhang Q, Shi X, Stakeholders strategies in poverty alleviation and clean energy access: A case study of China's PV poverty alleviation program. Energy Policy, 2019, 135: 111011.
[9] Xu H, Hipel KW, Kilgour DM Multiple levels of preference in interactive strategic decisions. Discrete Applied Mathematics, 2009, 157 (15): 3300-3313.
[10] Yu J, Hipel KW, Kilgour DM, Fang L, Fuzzy levels of preference strength in a graph model with multiple decision makers. Fuzzy Sets and Systems, 2019, 377: 71-84.
[11] Yu J, Hipel KW, Kilgour DM, Fang L, Yin K, Graph model under unknown and fuzzy preferences. IEEE Transactions on Fuzzy Systems, 2020, 28 (2): 308-320.
[12] Yu J, Hipel KW, Kilgour DM, et al. Option prioritization for unknown preference. Journal of Systems Science and Systems Engineering, 2016, 25: 39-61.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Highlights in Business, Economics and Management
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
