Purpose – This paper aims to provide a contribution on the diffusion of Industry 4 (I4.0)-related knowledge in industrial districts (IDs). The main goal is to examine the dissemination of I4.0 knowledge, exploring the main mechanisms for its spreading and highlighting the main factors shaping such processes. Focus is on dissemination processes in IDs active in traditional industries, which could represent the “periphery” of I4.0 application context. Design/methodology/approach – The methodology is qualitative. Notably, this paper presents a case study of the Pesaro ID specialized in furniture/woodworking machinery sector. A total of 18 in-depth one-to- one interviews have been conducted with relevant informants from a variety of organizations within the cluster: companies, institutions and universities. Findings – The complexity of I4.0 requires a combination of traditional mechanisms with innovative ones within IDs characterized by the emergence of new players, activities and resources. These changes led to three main evolving patterns: the horizon of I4.0 upgrading shows blurred boundaries in terms of sectors and geographic location, the I4.0 diffusion appears fragmented in terms of initiatives and projects by both firms and institutions and the dissemination of I4.0 knowledge pushes ID firms and institutions to pursue deliberate initiatives leading to innovative forms of “collective” cooperation. Originality/value – This paper contributes to both theory and practice. From the theoretical point of view, this paper contributes to the literature on innovation in IDs and clusters on two interrelated grounds. First, it provides further research on I4.0 and IDs and clusters. Second, it contributes to the stream of research on knowledge creation and diffusion in IDs and clusters, providing empirically based insights over emerging local learning processes in IDs. Moreover, relevant managerial and policy implications stem from the analysis.

The dissemination mechanisms of Industry 4.0 knowledge in traditional industrial districts: evidence from Italy

Alessandro Pagano;Elisa Carloni;Serena Galvani;Roberta Bocconcelli
2021

Abstract

Purpose – This paper aims to provide a contribution on the diffusion of Industry 4 (I4.0)-related knowledge in industrial districts (IDs). The main goal is to examine the dissemination of I4.0 knowledge, exploring the main mechanisms for its spreading and highlighting the main factors shaping such processes. Focus is on dissemination processes in IDs active in traditional industries, which could represent the “periphery” of I4.0 application context. Design/methodology/approach – The methodology is qualitative. Notably, this paper presents a case study of the Pesaro ID specialized in furniture/woodworking machinery sector. A total of 18 in-depth one-to- one interviews have been conducted with relevant informants from a variety of organizations within the cluster: companies, institutions and universities. Findings – The complexity of I4.0 requires a combination of traditional mechanisms with innovative ones within IDs characterized by the emergence of new players, activities and resources. These changes led to three main evolving patterns: the horizon of I4.0 upgrading shows blurred boundaries in terms of sectors and geographic location, the I4.0 diffusion appears fragmented in terms of initiatives and projects by both firms and institutions and the dissemination of I4.0 knowledge pushes ID firms and institutions to pursue deliberate initiatives leading to innovative forms of “collective” cooperation. Originality/value – This paper contributes to both theory and practice. From the theoretical point of view, this paper contributes to the literature on innovation in IDs and clusters on two interrelated grounds. First, it provides further research on I4.0 and IDs and clusters. Second, it contributes to the stream of research on knowledge creation and diffusion in IDs and clusters, providing empirically based insights over emerging local learning processes in IDs. Moreover, relevant managerial and policy implications stem from the analysis.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2676016
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