 Understanding “reverse” knowledge flows following inventor exit in the semiconductor industryMayank Varshney and Amit Jain Technovation, 2023, vol. 121, issue C Abstract: Organizational learning research suggests that employee exit lowers firm performance by eroding its human and social capital. We have a rather limited understanding of the conditions under which exit from a focal firm, defined as the firm from which exit takes place, may stimulate learning and reverse knowledge flows from the hiring firm. We developed a model of learning-by-exit to address this gap and tested it using a long panel of data (1985–2012) from the semiconductor industry. Our model suggests that the focal firm is likely to benefit more from reverse knowledge flows from the hiring firm when it is less aware of the latter. A focal firm is less aware of the hiring firm when there have been no prior inter-firm interactions between them, and when they are separated by a larger geographic and technological distance. Econometric analysis of our data using zero-inflated Poisson regressions provides empirical support for our model. This research contributes to our understanding of knowledge spillovers by highlighting the criticality of firm heterogeneity in the relationship between employee exit and reverse knowledge flows. Keywords: Inventor exit; Reverse knowledge flow; Learning-by-exit; Semiconductor industry (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:121:y:2023:i:c:s0166497222001882 DOI: 10.1016/j.technovation.2022.102638 Access Statistics for this article Technovation is currently edited by Jonathan Linton More articles in Technovation from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.