A partner selection approach for strategic alliance in the global aerospace and defense industry

Wang, Chia–Nan; Nguyen, Xuan-Tho; Le, Thi-Dao; Hsueh, Ming-Hsien

doi:10.1016/j.jairtraman.2018.03.003

Cited by 21 publications

(9 citation statements)

References 32 publications

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“…However, strategic partnerships are relatively complex, especially in terms of managing the perspectives of each other to ensure macro and micro-level commitment is sustained for optimal mutual gains (Saraiva, 2017). This complexity has been documented in numerous qualitative and largely theoretical studies focusing on strategic partnerships, global and non-global (e.g., Hinds, Liu, & Lyon, 2011;Shakeri & Radfar, 2017;Wang, Nguyen, Le, & Hsueh, 2018). Despite this recognition and complexity, the role of individual-accomplish set goals but also to withstand opposition and setbacks (Bandura, 1995).…”

Section: Introductionmentioning

confidence: 99%

Affective organizational commitment in global strategic partnerships: The role of individual-level microfoundations and social change

Ghouri

Akhtar

Shahbaz³

et al. 2019

Technological Forecasting and Social Change

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Section: Introductionmentioning

confidence: 99%

Affective organizational commitment in global strategic partnerships: The role of individual-level microfoundations and social change

Ghouri

Akhtar

Shahbaz³

et al. 2019

Technological Forecasting and Social Change

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“…According to Wang et al (2018) alliance is a choice to increase market power, increase political power, i ncrease research, production and marketing or other functions, and provide good product and services. Alliances play a critical role in firm survival, providing the access to critical resources that allow gaining and maintaining competitive advantages in t oday turbulent economic environment (Cobeña et al, 2017).…”

Section: Empirical Reviewmentioning

confidence: 99%

Effect of Strategic Alliance Management On the Performance of Microfinance Institutions In Rwanda

Charles¹,

Kule²,

Kapaya³

2021

IJSRP

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One of the ways to improve performance of MFIs is to encourage them to form strategic alliance. The purpose of this study was to assess the effect of strategic alliance management on the performance of Microfinance Institutions in Rwanda. The target population was 491 MFIs, and a sample size of 220 was determined using Slovene's formula. Primary data for the study was collected by use of structured questionnaire. Structural Equation Modeling (SEM) was used to establish the relationship between strategic alliance management and performance of MFIs. The SEM results revealed that the model was significant (𝛘 𝟐 = 𝟐𝟑. 𝟓𝟔, 𝐩 = 𝟎. 𝟎𝟓𝟏𝟖) with the overall R2=0.588. This implied that 58.8% of the performance of MFIs is influenced by the changes in strategic alliance management. The results have both practical and theoretical implications. Since a positive relationship exists, it is recommended that policy makers as well as managers/CEO in MFIs should promote strategic alliance as a tool for improving the performance of these organizations.

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“…The green criteria developed in this study can be used to determine whether prospective partners value green development. Elia et al [15], Wang et al [25] and Büyüközkan et al [26] mentioned that strategic alliances in various industries must consider financial resources, organizational management and risks. Our evaluation framework includes their ideas and opinions.…”

Section: Literature Review For Strategic Alliance Partner Evaluation mentioning

confidence: 99%

“…Common methods for determining weights are the analytic hierarchy process (AHP) [17], analytic network process (ANP) [18], best-worst method (BWM) [19], decision making trial and evaluation laboratory (DEMATEL) [20], and entropy [21]. Methods for performance integration and evaluation include technique for order preference by similarity to an ideal solution (TOPSIS) [22], Visekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) [23], ELECTRE [18], preference ranking organization method for enrichment evaluation (PROMETHEE) [24], and data envelopment analysis (DEA) [25]. MCDM methods have been widely used in the assessment and selection of various industries.…”

Section: Introductionmentioning

confidence: 99%

“…The criteria for evaluation are mainly divided into the individual ability of the partner and the organizational cooperation ability of the alliance. Wang et al [25] proposed a selection framework for aerospace and defense alliance partners with the use of the DEA approach to predict the future operational performance of viable alliance partners. There are also some studies that use MCDM to evaluate strategic alliance partners, such as collaborative development of communities [27], cocreation strategies for telecom operators [28], and innovation and entrepreneurship of clean technologies [29].…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid MCDM Model for Evaluating Strategic Alliance Partners in the Green Biopharmaceutical Industry

Chang

Liou

2019

Sustainability

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Since the rise of strategic alliances which play such an important role in industry today, the biopharmaceutical industry worldwide has entered an era of rapid change and collaborative thinking. The strategic alliance is one of the most important strategies for the green biopharmaceutical industry. Member organizations in these alliances work together to create more advantageous biotechnologies based on environmental protection to achieve mutual benefits. In the past, there have been only a few studies discussing partner evaluations and the selection process for the green biopharmaceutical industry, so the criteria or indicators are still not complete. Therefore, this study proposes a novel multi-criteria decision-making (MCDM) framework for strategic alliance partner evaluation that combines the best-worst method (BWM) and the fuzzy TOPSIS technique based on the concept of aspiration level (called fuzzy TOPSIS-AL) to evaluate the performance and priority rankings of strategic alliance partners. The BWM overcomes the shortcomings of small sample sizes and streamlines the number of conventional pairwise comparisons needed. The fuzzy TOPSIS-AL technique introduces the concept of the aspiration level, thereby leading to more reasonable suggestions for improvement. In addition, data from a multinational green biopharmaceutical company survey are utilized to demonstrate the validity and applicability of the proposed model.

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A partner selection approach for strategic alliance in the global aerospace and defense industry

Cited by 21 publications

References 32 publications

Affective organizational commitment in global strategic partnerships: The role of individual-level microfoundations and social change

Affective organizational commitment in global strategic partnerships: The role of individual-level microfoundations and social change

Effect of Strategic Alliance Management On the Performance of Microfinance Institutions In Rwanda

A Hybrid MCDM Model for Evaluating Strategic Alliance Partners in the Green Biopharmaceutical Industry

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