A Risk Assessment Model for Exploitation of New Technologies

Document Type : Original Research Article


Department of Industrial Management, Karaj Branch, Islamic Azad University, Karaj, Iran


Considering the importance of risk assessment for exploitation projects of new technologies in the manufacturing power plant equipment industry in MAPNA Group, a suitable model for assessing the related risks was extracted, along with identifying and ranking the factors affecting it. This study was carried out using the library-field method, and data collection tools were questionnaires and interviews. It should be noted that with the review of the literature and study of the related research along with the expert viewpoints, a number of 78 measured variables affecting the risk assessment model for the exploitation of technologies in the power generation industry were extracted. Finally, 43 measured variables that affect the mentioned model were determined after screening by expert judgment and university professors in the form of 8 latent variables. Then, a questionnaire was developed and distributed among 89 experts in the field of power plant equipment, and the completed questionnaires were collected. To test the research model's validation and goodness of fit (GOF), the variables and their effects, confirmatory factor analysis using structural equation modeling and Smart PLS software were used, and 24 measured variables were accepted. In addition, paired comparisons with the analysis of the network process and Super Decision software were used to prioritize the variables affecting the risk assessment model for the exploitation of new technologies in power plant equipment industry. The results show that the risk assessment model for exploiting new technologies in the power plant manufacturing industry includes 7 latent variables: 1- Operational and Processes 2-Human 3- Technical and Technological, 4- Environmental and Industrial, 5- Strategic, 6- Financial, and 7- Managerial. Also, ranking showed that variables such as Technical and technological, Operational and Processes, and Human ranked first to third, and financial variables ranked last.


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