A new model to optimize the knowledge exchange in industrial cluster: A case study of Semnan plaster production industrial cluster

Abstract

Industrial clusters bring member firms the opportunities and advantages to save resources and increase competitiveness through cooperation and joint activities. One of these opportunities is knowledge exchange, using shared resources. If cluster firms want to create knowledge directly or acquire it from out of cluster, it is necessary to spend much money and time. The aim is to maximize knowledge transfer between firms of a cluster regarding the limitation of budget and time, using existing knowledge flow networks. This problem is formulated with a new model of mixed integer programming and solved by the CPLEX solver for Semnan plaster production industrial clusters. The results of sensitivity analysis show that knowledge transfer is much more influenced by budget than time constraints. The results help cluster managers to have a better understanding, regarding the available resources and business conditions, to maximize the results obtained from knowledge transfer process in industrial cluster members.