Causal analysis of knowledge synergy in knowledge-based companies with the integrated approach of interpretive structural modeling and structural equations (Study case: Yazd Science and Technology Park)

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Article Type:
Case Study (دارای رتبه معتبر)
Abstract:

Nowadays, knowledge-based companies can create and strengthen dynamic capabilities by synergizing knowledge in the stages of integration and knowledge acquisition. Therefore, the aim of this study is to analyze and investigate the factors affecting knowledge synergies in the science and technology park of Yazd's knowledge-based companies. To conduct this research, the influential factors in the formation of knowledge synergies within knowledge-based companies were initially examined. Then, using the interpretive structural modeling approach, the identified factors were structured. To validate the conceptual model of the research, the structural equation modeling approach and SmartPls3 software were used, and the statistical population of this research consisted of experts, specialists, and employees of knowledge-based companies in the Yazd Science and Technology Park. The sampling method in the structural equation section of this research was an available sampling method. In this study, 186 questionnaires were completed and analyzed at the sixth and initial level of the model, the environmental background factor was placed, at the fifth level, the management leadership factor, and at the fourth level, the organizational culture factor. At the third level, the factors of resources, vision and strategy, and social capital were considered. At the second level, the factors of training and employee commitment, and finally, at the final level, the information technology factor were placed. Among the other findings of this research, it can be mentioned that the training and employee commitment of knowledge-based companies in the Yazd Science and Technology Park have an impact on information technology.

Language:
Persian
Published:
Scientific Journal of Organizational Knowledge Management, Volume:6 Issue: 22, 2023
Pages:
49 to 80
https://magiran.com/p2641829  
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