Automobile Industry Strategic Alliance Partner Selection: The Application of a Hybrid DEA and Grey Theory Model

• Main Authors: Chia-Nan Wang, Xuan-Tho Nguyen, Yen-Hui Wang
• Format: Article
• Language: English
• Published: MDPI AG 2016-02-01
• Series: Sustainability
• Subjects: strategic alliance; data envelopment analysis; grey prediction; automobile industry
• Online Access: http://www.mdpi.com/2071-1050/8/2/173

Finding the right strategic alliance partner is a critical success factor for many enterprises. Therefore, the purpose of this study is to propose an effective approach based on grey theory and data envelopment analysis (DEA) for selecting better partners for alliance. This study used grey forecasting to predict future business performances and used DEA for the partner selection of alliances. This research was implemented with realistic public data in four consecutive financial years (2009–2012) of the world’s 20 biggest automobile enterprises. Nissan Motor Co., Ltd was set to be the target decision making unit (DMU). The empirical results showed that, among 19 candidate DMUs, Renault (DMU10) and Daimler (DMU11) were the two feasible beneficial alliance partners for Nissan. Although this research is specifically applied to the automobile industry, the proposed method could also be applied to other manufacturing industries.