Formation of multiple local knowledge ties in an engineered-based cluster in developing regions

Safora Allahy (), Reza Naghizadeh (), Saeed Shavalpour () and João J. Ferreira ()
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Safora Allahy: Iran University of Science and Technology
Reza Naghizadeh: National Research Institute for Science Policy
Saeed Shavalpour: Iran University of Science and Technology
João J. Ferreira: Universidade da Beira Interior

Quality & Quantity: International Journal of Methodology, 2025, vol. 59, issue 6, No 31, 5623-5647

Abstract: Abstract In recent years, researchers have found that knowledge ties are effective channels for knowledge externalities in clusters, but few empirical studies have examined the dynamics of these mechanisms. This study aims to fill the gap by providing empirical evidence about the driving forces of local knowledge ties in an industrial cluster with an engineering-based knowledge. Using micro-level data from the cluster and relational data through the roster-recall methodology, we test and develop an exponential random graph model and empirically test nodal, dyadic, and structural characteristics patterns. We find that different types of knowledge ties between firms are formed and developed under the influence of various factors (firm, dyadic, structural level). Our findings not only contribute to a more complete understanding of knowledge flow in cluster contexts but also advance with some suggestions for firms, industrial clusters and regional policy.

Keywords: Knowledge ties; Local knowledge networks; Cluster; Exponential random graph model (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11135-025-02208-5

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