A complementor selection framework to nurture R&D ecosystems based on multidimensional patent data
by Fenfen Wei; Nanping Feng; Xinyu Liu; Furong Ruan; Shanlin Yang
International Journal of Technology Management (IJTM), Vol. 92, No. 3, 2023

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.

Online publication date: Tue, 07-Feb-2023

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