Selecting Partners in Strategic Alliances: An Application of the SBM DEA Model in the Vietnamese Logistics Industry
Nguyen-Nhu-Y Ho (),
Phuong Mai Nguyen,
Thi-Minh-Ngoc Luu and
Thi-Thuy-Anh Tran
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Nguyen-Nhu-Y Ho: International School, Vietnam National University, Hanoi 10000, Vietnam
Thi-Minh-Ngoc Luu: University of Economics and Business, Vietnam National University, Hanoi 10000, Vietnam
Thi-Thuy-Anh Tran: International School, Vietnam National University, Hanoi 10000, Vietnam
Logistics, 2022, vol. 6, issue 3, 1-15
Abstract:
Background: Strategic alliance is a popular strategic option for business entities to strengthen the competitive advantages of all partners in a partnership. The global logistics industry has witnessed the formulation of several successful strategic alliances. However, the Vietnamese logistics industry seems to grow slowly and lacks long-term inter-firm partnerships. In such a context, it is critical to have a more effective approach to selecting partners in strategic alliances to increase long-term relationships and firm performance. Method: Thus, this study proposes using the SBM-I-C DEA model to examine and suggest partners for Vietnamese logistics firms to form strategic alliances. Results: Our findings show that integrating technology in managing strategic alliances will foster companies in the alliance to formulate a better strategy with up-to-date information on policies. Conclusion: Using the SBM-I-C DEA model, companies can minimize operating costs and optimize delivery time. Thus, companies can better satisfy customers. From the research findings, some implications are proposed for Vietnamese logistics companies.
Keywords: super-SBM-I-C DEA model; strategic alliance; Vietnam domestic logistics companies (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlogis:v:6:y:2022:i:3:p:64-:d:915648
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