University of Tabriz Applied Theories of Economics 2423-6586 8 3 2021 11 22 Application of Marshallian Cluster Model in Identifying and Creating Industrial Clusters in Bushehr Province Application of Marshallian Cluster Model in Identifying and Creating Industrial Clusters in Bushehr Province 55 84 13535 10.22034/ecoj.2021.42799.2770 FA Ebrahim Anvari Associate Professor of Economics, Shahid Chamran University of Ahvaz. 0000-0002-6050-8645 Hassan Farazmand Professor of Economics, Shahid Chamran University of Ahvaz Atefe Ahmadi Ph.D. student in Economics, Shahid Chamran University of Ahvaz. Journal Article 2020 11 12 Industrial clusters are representing a new way of thinking about place creating a business that improves industrial competitiveness through product specialization and increases overall returns through value chains of business and reduces transaction costs. In this study, formation of talented clusters in Bushehr province were identified by the Marshallian cluster model and by three quantitative approaches of cluster index, input-output table analysis and Getis-Ord’s Gi statistics. Thus, first, determine the concentration activities and calculated the cluster index. Then, by input-output table analysis and calculating the index of technical coefficients, strong links between activities were identified. In the following, Getis-Ord’s Gi statistics was calculated in ArcGIS10.2 software to determine the cities talented to formation of industrial cluster. Hence, the possibility of forming a cluster among the services and commerce activities of the hotel and restaurant category had the highest centralization of employment in Bushehr city. Then, the results of input-output table analysis showed that this category provides intermediate inputs for categorys of agricultural, electricity, water and gas and financial services, and in turn, these categorys provides intermediate inputs in the category of hotel and restaurants. As the categorys of food and beverage prouducts, wholesale and retail and building business activities plays a role in providing intermediate inputs in the hotel and restaurant category. In the end, the results of Getis-Ord’s Gi statistics showed that Bushehr city has the possibility of forming clusters with Genaveh and Deylam cities in the category of hotel and restaurant. Industrial clusters are representing a new way of thinking about place creating a business that improves industrial competitiveness through product specialization and increases overall returns through value chains of business and reduces transaction costs. In this study, formation of talented clusters in Bushehr province were identified by the Marshallian cluster model and by three quantitative approaches of cluster index, input-output table analysis and Getis-Ord’s Gi statistics. Thus, first, determine the concentration activities and calculated the cluster index. Then, by input-output table analysis and calculating the index of technical coefficients, strong links between activities were identified. In the following, Getis-Ord’s Gi statistics was calculated in ArcGIS10.2 software to determine the cities talented to formation of industrial cluster. Hence, the possibility of forming a cluster among the services and commerce activities of the hotel and restaurant category had the highest centralization of employment in Bushehr city. Then, the results of input-output table analysis showed that this category provides intermediate inputs for categorys of agricultural, electricity, water and gas and financial services, and in turn, these categorys provides intermediate inputs in the category of hotel and restaurants. As the categorys of food and beverage prouducts, wholesale and retail and building business activities plays a role in providing intermediate inputs in the hotel and restaurant category. In the end, the results of Getis-Ord’s Gi statistics showed that Bushehr city has the possibility of forming clusters with Genaveh and Deylam cities in the category of hotel and restaurant. https://ecoj.tabrizu.ac.ir/article_13535_651601c1f3ce618a317114e0208c6e3a.pdf