Optimization of Knowledge Exchange in Industrial Cluster by Goal Programming Case Study: Golestan Animal Feed Industrial Cluster
Subject Areas :Hamidreza Dezfoolian 1 , Parvaneh Samouei 2
1 - Assistant Professor, Department of Industrial Engineering, Faculty of Engineering, Bo Ali Sina University, Hamadan, Iran
2 - Assistant Professor, Department of Industrial Engineering, Faculty of Engineering, Bo Ali Sina University, Hamadan, Iran
Keywords: Industrial cluster, knowledge exchange, ideal planning, case study,
Abstract :
Knowledge as a strategic resource in organizations is a major and effective factor in creating and sustaining competitive advantage. In industrial clusters, which include a set of organizations with similar field of activities, there is a joint effort among members to save resources and enhance their competitive ability. One of these joint activities is the exchange of knowledge among the members, which reduces the cost of knowledge acquisition, increasing collaboration between companies, the ability to innovate and strengthen their competitive ability. In this paper, a goal programming model for the process of knowledge exchange in industrial clusters has been presented based on the data of industrial cluster of animal feed, poultry and aquaculture in Golestan and its results have been analyzed. Achieving the ideal degree of knowledge in the cluster and the amount of budget assigned are considered as two model ideals. In this model, for the process of knowledge exchange, there are two types of presence and non-attendance methods that have significant differences in terms of cost and duration of the transfer. Analyzing the model parameters and examining the results shows that the use of both face-to-face and non- attendance methods for the exchange of knowledge enables companies to flexibly participate in the process according to their working conditions and resources. It also provides better understanding to cluster managers in order to be able to make better decisions and planning in order to achieve greater returns from the knowledge transfer process, based on existing resources and goals.
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