A Methodology of Partner Selection for Sustainable Industry-University Cooperation Based on LDA Topic Model

Jiho Kang, Junseok Lee, Dongsik Jang and Sangsung Park
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Jiho Kang: Department of Industrial Management Engineering, Korea University, Seoul 02841, Korea
Junseok Lee: Department of Industrial Management Engineering, Korea University, Seoul 02841, Korea
Dongsik Jang: Department of Industrial Management Engineering, Korea University, Seoul 02841, Korea
Sangsung Park: Division of Software Convergence, Cheongju University, Chungbuk 28503, Korea

Sustainability, 2019, vol. 11, issue 12, 1-16

Abstract: In today’s knowledge-based society, industry-university cooperation (IUC) is recognized as an effective tool for technological innovation. Many studies have shown that selecting the right partner is essential to the success of the IUC. Although there have been a lot of studies on the criteria for selecting a suitable partner for IUC or strategic alliances, there has been a problem of making decisions depending on the qualitative judgment of experts or staff. While related works using patent analysis enabled the quantitative analysis and comparison of potential research partners, they overlooked the fact that there are several sub-technologies in one specific technology domain and that the applicant’s research concentration and competency are not the same for every sub-technology. This study suggests a systematic methodology that combines the Latent Dirichlet Allocation (LDA) topic model and the clustering algorithm in order to classify the sub-technology categories of a particular technology domain, and identifies the best college partners in each category. In addition, a similar-patent density (SPD) index was proposed and utilized for an objective comparison of potential university partners. In order to investigate the practical applicability of the proposed methodology, we conducted experiments using real patent data on the electric vehicle domain obtained from the Korean Intellectual Property Office. As a result, we identified 10 research and development sectors wherein Hyundai Motor Company (HMC) focuses using LDA and clustering. The universities with the highest values of SPD for each sector were chosen to be the most suitable partners of HMC for collaborative research.

Keywords: Industry–university cooperation; topic model; Latent Dirichlet Allocation; patent analysis; collaborative research planning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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