Why established collaborative networks fail to drive organizational innovation efficiency – from an internal knowledge network perspective

Purpose Interorganizational research and development (R&D) networking encounters obstructions, due mainly to inefficient resource utilization and necessary breakthroughs are not achieved. We aim to explore the interplay between a firm’s internal knowledge network and subsequent resource consumption efficiency. Design/methodology/approach We build collaborative and knowledge networks through screening patent data for 2007–2019 in the aerospace industry. By integrating social network analysis (SNA) with data envelopment analysis (DEA), we measure organizations’ resource transformation efficiency in collaborative networks (RTECN). Through regression analysis, we further investigate the impact of internal knowledge network invulnerability, agility and knowledge positions on RTECN. Findings The results show that organizations’ internal knowledge network invulnerability has a positive effect on their RTECN. Agility has an inverted U-shaped effect, whereas organizational knowledge element position has no obvious effect on RTECN. Practical implications Managers must rework their internal knowledge infrastructure by encouraging deep cooperation among interdisciplinary research talent. Organizations must establish a more comprehensive and scientific evaluation system for new R&D projects through collective intelligence and data support. Organizations can achieve learning efficiency comparable to that of organizations in other fields and should not blindly pursue crowded technology fields without careful examination. Managers must avoid massive networks rather than opt for networks with fewer occupants to achieve learning efficiency. Originality/value First, we propose a new indicator to measure organizational efficiency when studying networked partners. Second, we advance social network theory to multilayered network examination through incorporating knowledge and collaborative networks into a conceptual model from a new perspective. Third, our research enables us to understand the efficiency gap and explore means of filling it from a knowledge standpoint. Fourth, our findings highlight limitations in SNA in terms of the position of knowledge (elements) such that it does not contribute to a firm’s efficiency in collaborative resource transformation.