Identifying and evaluating strategic partners for collaborative R&D: Index-based approach using patents and publications
- Authors
- Geum, Youngjung; Lee, Sungjoo; Yoon, Byungun; Park, Yongtae
- Issue Date
- Jun-2013
- Publisher
- ELSEVIER SCIENCE BV
- Keywords
- Collaborative R&D; Partner selection; Index-based; Patent; Publication; Technology intelligence
- Citation
- TECHNOVATION, v.33, no.6-7, pp 211 - 224
- Pages
- 14
- Indexed
- SCIE
SSCI
SCOPUS
- Journal Title
- TECHNOVATION
- Volume
- 33
- Number
- 6-7
- Start Page
- 211
- End Page
- 224
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/24895
- DOI
- 10.1016/j.technovation.2013.03.012
- ISSN
- 0166-4972
1879-2383
- Abstract
- Identifying and selecting appropriate strategic partners have been the subject of many previous studies: but most have dealt with partner selection that has relied heavily on experts' judgements: the value of a literature-based quantitative approach as a source of technology intelligence has seldom been addressed. This paper therefore aims to develop a systematic framework to guide strategic partner selection, taking a literature-based approach. Reviewing the factors that can lead to successful R&D partnerships to develop partner selection criteria, we designed 14 indexes - grouped into four major categories - to reflect desirable partner characteristics, and used the literature data to suggest a framework for prioritising potential partners. As data sources, the United States Patent and Trademark Office (USPTO) and the IS! Web of Science databases are adopted for patent analysis and publication analysis, respectively. This research applied the framework to identify strategic R&D partners for Korean firms and found that the use of literature data enabled a wide ranging search for potential partners and the quick analysis of their characteristics, with results that provided objective evidence for selection decisions. It also investigated the relative importance of literature databases and that of the four decision criteria by industry, and examined the relationships between the indexes to improve the application of the framework. The suggested framework is expected to be valuable as a complementary tool for decision-making about R&D collaboration. (C) 2013 Elsevier Ltd. All rights reserved.
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