Title: Identifying R&D partners using SAO analysis: a case study of dye-sensitised solar cells

Authors: Xuefeng Wang; Yun Fu; Ying Huang; Yuqin Liu; Donghua Zhu

Addresses: School of Management and Economics, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China ' National Science Library, Chinese Academy of Sciences, 33 Beisihuan Xilu, Zhongguancun, Haidian District, Beijing, 100190, China ' Department of Public Administration, Hunan University, Lushan Road (S), Yuelu District, Changsha, 410082, China ' Beijing Academy of Printing and Packaging Industrial Technology, Beijing Institute of Graphic Communication, 25 Xinghua North Road, Daxing District, Beijing, 102600, China ' School of Management and Economics, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China

Abstract: This paper proposes a systematic process to identify potential research and development (R&D) partners from a technological perspective based on subject-action-object (SAO) semantic analysis. Improvements to traditional methods are made by combining the SAO structure map and the collaboration network analysis. The SAO structure map reveals the technological development trends, organisations' research contributions and their research experiences in the field, which are the factors that indicate an organisation's R&D capabilities. Furthermore, we explore the organisation's collaboration statuses through collaborative network analysis and their collaborative publications, which make it easier to identify the organisation's sense of cooperation. Potential R&D partners are identified by examining the organisation's R&D capabilities and sense of cooperation. An exploratory study is conducted on dye-sensitised solar cells (DSSCs). The proposed method provides useful information for organisations (firms, institutions, universities, etc.) to identify potential R&D partners or make cooperation related policies.

Keywords: subject-action-object; SAO; mapping science; semantic analysis; collaborative network analysis; partner identification; dye-sensitised solar cells; DSSCs.

DOI: 10.1504/IJTM.2019.101270

International Journal of Technology Management, 2019 Vol.81 No.1/2, pp.70 - 93

Received: 28 Jul 2017
Accepted: 04 Jul 2018
Published online: 30 Jul 2019 *

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