Fuzzy Cognitive Map Design for Evaluation Performance of Research Projects in Area of Quantum Computing
Subject Areas : FuturologyAbolqasem Sharayei 1 , Mahmood Alborzi 2 * , Ali Jabbar Rashidi 3
1 - IT Management department, Islamic Azad University, Science and Research branch, Tehran,Iran
2 - Associate professor. Information Technology Management Department. Economy and Management Faculty. Islamic Azad University. Science and research branch.
3 - ِElectrical Engineering Department.complex of electrical and Information technology.Malek ashtar university of technology
Keywords: Performance Evaluation, Research Projects, BSC, Fuzzy-Cognitive Map, Quantum Technology, Quantum Computing,
Abstract :
Field: Evaluation performance of research projects in area of quantum technology help organizations to recognize the best projects and so, they can use their sources in better way to achieve their goals. Goals: The main goal of this article is to design a fuzzy-cognitive strategic map to evaluate research projects based on BSC in area of emerging quantum technology specially quantum computing. Methods: In this research, we have used both library and field study methods to collect information. Also, 18 factors have been identified and validated to evaluate performance of research projects according to literature reviews. In section of data analysis, we first have defined vision, mission and fundamental values and then, performance factors in different layers of BSC by using fuzzy Delphi methods. Finally, fuzzy-cognitive strategic map have been designed to evaluate performance of research projects based on BSC. Findings: We have found that “Liquidity conditions to cover current expenses” in financial layer, “customer acquisition rate” in customer layer, “ratio of successful projects to total projects’ in internal processes layer and "Acquired technical knowledge" in growth and learning layer has been identified as the most influence factors. Also, “growth and learning” layer and “financial” layer have been respectively recognized as the most influence layer and the most affected layer and output of the model.