A scientometric analysis of knowledge transfer partnerships in digital transformation
Year: 2024
Type: article
Abstract: In an era where digital transformation (DT) reshapes industries, the role of Knowledge Transfer Partnerships (KTP) in bridging academic insights with industrial innovation becomes crucial. This study conducts a comprehensive scientometric analysis of 360 academic papers spanning from 2013 to 2023 to map the evolving landscape of KTP in the context of DT. By employing advanced visualization tools including generative visual networks and keyword co-occurrence analysis through CiteSpace, critical research gaps and trends, particularly addressing how KTP can mitigate technological obsolescence and enhance innovation management within enterprises are identified. The findings reveal a significant escalation in research output related to KTP, with a pronounced focus on integrating cutting-edge technologies of Artificial Intelligence, machine learning and virtual reality and fostering market adaptability. This study charts the exponential growth of literature and highlights strategic areas of research entities, global geographical coverage, and advanced digital trends where KTPs are pivotal in enhancing organizational resilience and competitive advantage in a rapidly digitizing world. This paper contributes to the existing knowledge of KTP by identifying the patterns and trends of on-going research and offering an evolutionary model to guide theoretical development and practical business operations and policy making.
Authors: Lihong Zhang, Saeed Banihashemi, Liting Zhu, Homa Molavi, Eyyub Odacioglu, Miyuan Shan
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,000
OpenAlex ID: W4400078091