The dual moderating roles of organizational unlearning in knowledge transfer within an industry network

Purpose This study aims to propose dual moderating roles of organizational unlearning in shaping the network drivers and the performance outcomes of interfirm knowledge transfer. First, the authors examine the moderating effect of unlearning on two key network drivers, structural network (measured as centrality) and relational network (measured as tie strength), on knowledge transfer. Second, the authors examine the moderating effect of unlearning on the relationship between knowledge transfer and firm performance. Design/methodology/approach To test the two proposed moderating models, the authors collected a unique data set comprising the entire sociometric network of 42 petroleum wholesalers in Tanzania and analyzed the survey data using moderated regression analyses. Findings The results support the authors’ hypotheses. Specifically, organizational unlearning weakens the effect of tie strength but strengthens the effect of centrality on knowledge transfer. Moreover, organizational unlearning amplifies the positive effect of knowledge transfer on firm performance. Originality/value By theorizing unlearning as a critical boundary condition, the authors show that it shapes when and how network drivers influence knowledge transfer and its performance consequences. In doing so, this study deepens our understanding of the network mechanisms underlying knowledge transfer and reveals the opposing moderating effects of unlearning on network drivers and knowledge transfer, which prior research has largely overlooked.

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Publication Details

Journal
Journal of Knowledge Management
Published
2026-08-27
DOI
https://doi.org/10.1108/jkm-09-2025-1278
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
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article

The dual moderating roles of organizational unlearning in knowledge transfer within an industry network

Steven S. Lui, Carolyn Yesse Ngowi, Salih Zeki Ozdemir
Journal of Knowledge Management
Innovation and Knowledge Management
article

The dual moderating roles of organizational unlearning in knowledge transfer within an industry network

Steven S. Lui, Carolyn Yesse Ngowi, Salih Zeki Ozdemir
article en

Abstract

Purpose This study aims to propose dual moderating roles of organizational unlearning in shaping the network drivers and the performance outcomes of interfirm knowledge transfer. First, the authors examine the moderating effect of unlearning on two key network drivers, structural network (measured as centrality) and relational network (measured as tie strength), on knowledge transfer. Second, the authors examine the moderating effect of unlearning on the relationship between knowledge transfer and firm performance. Design/methodology/approach To test the two proposed moderating models, the authors collected a unique data set comprising the entire sociometric network of 42 petroleum wholesalers in Tanzania and analyzed the survey data using moderated regression analyses. Findings The results support the authors’ hypotheses. Specifically, organizational unlearning weakens the effect of tie strength but strengthens the effect of centrality on knowledge transfer. Moreover, organizational unlearning amplifies the positive effect of knowledge transfer on firm performance. Originality/value By theorizing unlearning as a critical boundary condition, the authors show that it shapes when and how network drivers influence knowledge transfer and its performance consequences. In doing so, this study deepens our understanding of the network mechanisms underlying knowledge transfer and reveals the opposing moderating effects of unlearning on network drivers and knowledge transfer, which prior research has largely overlooked.

Journal of Knowledge ManagementVol. 30(11)
Institute on Governance (CA)
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Innovation and Knowledge Management
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