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

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.