Learning from the Past: How Prior Experience Impacts the Value of Innovation After Scientist Relocation. (March 2022)

• Record Type: Journal Article
• Authors: Jain, Amit; Huang, Kenneth G.
• Is Part Of: Journal of management. Volume 48:Number 3(2022)
• Page Start: 571
• Page End: 604
• Publication Date: 2022-03
• Subjects: innovation -- management -- mobility -- organizational learning -- knowledge management; Management -- Periodicals; 658.005
• DOI: 10.1177/0149206320979658
• Languages: English
• ISSNs: 0149-2063

Abstract

There is growing interest in management and organizational research to study the relocation of knowledge workers, defined as a move by the knowledge worker to a different place of work. Relocation has been well studied as a potential source of losses or gains in human and social capital. However, our understanding of whether and how it disrupts a scientist's innovation activities is limited. Relocation could disrupt innovation activities in the new workplace by making it difficult for a scientist to coordinate work with prior collaborators with whom the scientist has relational experience and forcing the scientist to work with new collaborators. In this study, we develop a conceptual framework assessing the effectiveness of the scientists' research and development (R&D) experience to counter these disruptions arising from relocation and develop valuable patented innovations. We hypothesize that both the scientist's relational experience and working with new collaborators decrease the value of innovations the scientist creates after relocation. Scientist R&D experience, however, is double-edged in nature: It leads to less valuable innovations prior to relocation but facilitates the creation of more valuable innovations after it. Our theory suggests that this is because R&D experience facilitates the scientist's adaptation to the new context and helps coordinate her or his activities in new collaborations. Nevertheless, R&D experience is less effective in sustaining the efficacy of relational experience with prior collaborators after relocation. Using a longitudinal dataset from the knowledge-intensive genomics industry, we find support for our hypotheses. This study yields important managerial and policy implications.