Title: A complementor selection framework to nurture R&D ecosystems based on multidimensional patent data
Authors: Fenfen Wei; Nanping Feng; Xinyu Liu; Furong Ruan; Shanlin Yang
Addresses: School of Management, Hefei University of Technology, Hefei 230009, China; School of Management, Nanjing University of Posts and Telecommunications, Nanjing 21003, China ' School of Management, Hefei University of Technology, Hefei 230009, China; Key Laboratory of Process Optimisation and Intelligent Decision-Making in Ministry of Education, Hefei 230009, China ' School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China ' School of Management, Hefei University of Technology, Hefei 230009, China ' School of Management, Hefei University of Technology, Hefei 230009, China; Key Laboratory of Process Optimisation and Intelligent Decision-Making in Ministry of Education, Hefei 230009, China
Abstract: Complementor selection is a crucial factor that impacts collaborative innovation performance in platform-based innovation ecosystems (PIEs). However, the existing literature pays little attention to their selection and relevant criteria, and supplier selection methods cannot meet the selection requirements of PIEs. Therefore, this study offers platform leaders a framework for complementor selection to nurture research and development (R&D) ecosystems using multidimensional patent data. In this framework: 1) the search for complementors is worldwide, thereby expanding the search scope and improving the acquisition of resources for customer-oriented solutions; 2) the evaluation of potential complementors is based on multidimensional patent data, thus reducing dependence on experts and enhancing the reliability of evaluation results; 3) cluster analysis identifies general, developmental, and core potential complementors, enabling platform leaders to conduct classified selection and management of them. Finally, an empirical case study is performed by applying the proposed framework to verify its feasibility and effectiveness.
Keywords: complementor selection; complementor ecosystem; R&D collaboration; patent data; cluster; platform-based innovation ecosystems; PIEs.
International Journal of Technology Management, 2023 Vol.92 No.3, pp.159 - 183
Accepted: 23 Feb 2022
Published online: 07 Feb 2023 *