Reviewer
005-114-226
| Name: | Hooman Shababi |
| Designation: | Assistant Professor |
| Department: | Management |
| Research Area: | Science and technology policy |
| Organization: | Rahedanesh Institute of Higher Education |
| Contact: | Contact Reviewer |
| Qualification: | PhD |
| About: | Dr. Hooman Shababi** is an Assistant Professor of Management and a researcher in the fields of **Science, Technology, and Innovation (STI) Policy, strategic management, innovation governance, and technology management**. His academic work focuses on understanding how science, technology, innovation, institutions, and public policy interact to shape economic and societal development, particularly in the context of Iran and other emerging economies. Dr. Shababi holds a **Ph.D. in Science and Technology Policy**, with an interdisciplinary academic background that connects management sciences with science and technology studies, innovation policy, institutional analysis, and strategic management. His research interests include **STI policy evaluation, innovation systems, technology governance, AI policy, emerging technologies, strategic management, science and technology indicators, and the application of computational and quantitative methods to policy research**. He is an **Assistant Professor at Rahedanesh Institute of Higher Education**, where he is involved in teaching, research, academic development, and institutional activities. In his academic and administrative roles, he has contributed to the development of educational programs, curriculum planning, academic affairs, and the advancement of research-oriented activities within higher education. His teaching portfolio includes subjects related to **strategic management, advanced strategic management, management, entrepreneurship, innovation, technology management, and business strategy**. His approach to teaching emphasizes connecting theoretical concepts with contemporary organizational, technological, and policy challenges. Dr. Shababi's research methodology is strongly interdisciplinary. His work incorporates both conventional quantitative and qualitative approaches and computational methods, including **machine learning, system dynamics, scientometrics, bibliometric analysis, network analysis |
| Status: |
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