Skip to main content

Industrial clusters in the developing economies: insights from the Iranian carpet industry

Saadatyar, Fahime, Al-Tabbaa, Omar, Dagnino, Giovanni, Vazife, Zahra (2020) Industrial clusters in the developing economies: insights from the Iranian carpet industry. Strategic Change, 29 (2). pp. 227-239. ISSN 1086-1718. E-ISSN 1099-1697. (doi:10.1002/jsc.2324) (KAR id:74344)

PDF Author's Accepted Manuscript
Language: English
Download (875kB)
[thumbnail of Full 11-6-19.pdf]
This file may not be suitable for users of assistive technology.
Request an accessible format
Official URL:


Industrial clusters are perceived as potential drivers of SMEs development and efficient policy instruments to lead national and regional innovation and growth. However, these clusters in developing economies are typically placed in complex environments that impose a mix of serious challenges which adversely affect their overall performance. Therefore, this study aims to analyze the nature of these challenges and understand their dynamics using a case study of a carpet industry cluster in Iran. Using multiple sources of evidence, the study reveals two distinct, yet interrelated, levels of challenges: micro and macro. Under each level, a number of key dimensions were identified and theoretically linked which helped to conceptualize the structure of these challenges and model their dynamics.

Item Type: Article
DOI/Identification number: 10.1002/jsc.2324
Uncontrolled keywords: Industrial cluster; Carpet industry; Geographical agglomeration, Beneficiaries, Obstacles-Constraints, Sistan and Baluchestan province
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Divisions > Kent Business School - Division > Department of Marketing, Entrepreneurship and International Business
Depositing User: Omar Altabbaa
Date Deposited: 11 Jun 2019 09:25 UTC
Last Modified: 09 Dec 2022 05:40 UTC
Resource URI: (The current URI for this page, for reference purposes)
Al-Tabbaa, Omar:
  • Depositors only (login required):


Downloads per month over past year