African Journal of
Business Management

  • Abbreviation: Afr. J. Bus. Manage.
  • Language: English
  • ISSN: 1993-8233
  • DOI: 10.5897/AJBM
  • Start Year: 2007
  • Published Articles: 4193

Full Length Research Paper

A (data envelopment analysis) DEA-based systematic approach for selection of strategic alliance candidates: Case by the biotechnology industry

Chia-Nan Wang1* and Chih-Hong Wang2
1National Kaohsiung University of Applied Sciences, Taiwan. 2National Chengchi University, Taiwan.  
Email: [email protected]

  •  Accepted: 28 February 2011
  •  Published: 04 September 2011

Abstract

Enterprises become more and more difficult to maintain success in the highly competitive environment. This is the reason why many enterprises start searching for strategic alliance partners to strengthen their competitive advantage. However, facing a future of uncertainty, choosing the suitable partner of strategic alliance has become a difficult task. Based on data envelopment analysis and heuristic techniques, this study proposes a new systematic approach, which calls alliance candidate selection. The objective of alliance candidate selection is to assist biotech companies to evaluate the operation efficiency and find the best candidate of strategic alliance. Realistic data are collected from biotechnology businesses of Taiwan published stock market. Target company and 19 biotechnology companies for decision making units were collected. This research tries to help target company to find the right alliance partners for future integration. By analysis of alliance candidate selection, the results show that, the predicted benefits of 3 candidates as first priority 4 ones suggested and 10 of the ones not recommended. The results are sound for enterprises to find the future candidates of strategic alliance by many industry peoples. Alliance candidate selection can effectively provide all the essential analysis and recommendations to enterprises, for finding the right candidate of strategic alliance.

 

Key words: Strategic alliance, data envelopment analysis, biotechnology, efficiency.