Journal of Industrial and Systems Engineering

Journal of Industrial and Systems Engineering

Identification of influencing factors on the informal advanced technology transfer using a qualitative approach in the industry LNG

Document Type : Research Paper

Authors
1 Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Faculty of Management and Industrial Engineering, Malik Ashtar University of Technology, Tehran, Iran
3 Department of Industrial Management, Karaj Branch, Islamic Azad University, Karaj, Iran
Abstract
The advanced technology transfer become importance because of the various countries and company’s requirement to technology transfer in recent years and is paid attention by many academics so that many companies aim to transfer advanced technology to increase their productivity and on the other hand to tackle their technologic weak and faults. The identification of influencing factors on the advanced technology transfer is very important highly. The aim of current research is to identify the factors influencing on advanced technology transfer. For achieving to this goal, several studies have been done and the gap is identified. For identification of factors influencing on the advanced technology transfer the content analysis and Delphi is used the using content analysis the factors are extracted. Then they are screened using Delphi. Finally, 18 influencing factors are identified.
Keywords
Subjects

Ardito, L., Natalicchio, A., Messeni Petruzzelli, A., & Garavelli, A. C. (2018). Organizing for continuous technology acquisition: The role of R&D geographic dispersion. R&D Management, 48(2), 165-176.
Ashari, P. A., Blind, K., & Koch, C. (2023). Knowledge and technology transfer via publications, patents, standards: Exploring the hydrogen technological innovation system. Technological Forecasting and Social Change, 187, 122201.
Ashoka, M. L., & Keihani, H. R. (2020). Factors Influencing the Investors to Invest in Stock Market. International Journal of Management (IJM), 11(1), 166-175.
Ashoka, M. L., & Keihani, H. R. (2021). The relationship between macroeconomic factors and Indian stock market. The journal of contemporary issues in business and government, 27(5), 1306-1312.
Akhlaghpour, A., Heidari, M. R., & Chobar, A. P. (2023). Applying Resiliency in Predicting Demand for the Automotive Supply Chain. International journal of industrial engineering and operational research, 5(3), 37-49.
Battistella, C., De Toni, A. F., & Pillon, R. (2016). Inter-organisational technology/knowledge transfer: a framework from critical literature review. The Journal of Technology Transfer, 41, 1195-1234.
Delshad, M. M., Chobar, A. P., Ghasemi, P., & Jafari, D. (2024). Efficient Humanitarian Logistics: Multi-Commodity Location–Inventory Model Incorporating Demand Probability and Consumption Coefficients. Logistics, 8(1), 9.
Fartash, K., Davoudi, S. M. M., Baklashova, T. A., Svechnikova, N. V., Nikolaeva, Y. V., Grimalskaya, S. A., & Beloborodova, A. V. (2018). The impact of technology acquisition & exploitation on organizational innovation and organizational performance in knowledge-intensive organizations. Eurasia Journal of Mathematics, Science and Technology Education, 14(4), 1497-1507.
Hafeez, A., Shamsuddin, A. B., & Saeed, B. (2023). An empirical investigation of absorptive capacity on technology transfer effectiveness through organizational innovation. International Journal of Professional Business Review: Int. J. Prof. Bus. Rev., 8(2), 2.
Huang, K. W., Guo, J. E., & Yuan, Y. (2019, December). The Multi-participant Perspective for Evaluating Technology Transfer by Using a Hybrid Multi-Attribute Decision Making Model. In Fourth International Conference on Economic and Business Management (FEBM 2019) (pp. 326-330). Atlantis Press.
Iraj, M., Chobar, A. P., Peivandizadeh, A., & Abolghasemian, M. (2024). Presenting a two-echelon multi-objective supply chain model considering the expiration date of products and solving it by applying MODM. Sustainable Manufacturing and Service Economics, 3, 100022.
Khan, J., Haleem, A., & Husain, Z. (2017). Barriers to technology transfer: A total interpretative structural model approach. International Journal of Manufacturing Technology and Management, 31(6), 511-536.
Link, A. N., Siegel, D. S., & Bozeman, B. (2007). An empirical analysis of the propensity of academics to engage in informal university technology transfer. Industrial and corporate change, 16(4), 641-655.
Liu, X., & Meng, H. Consideration for the scale-up manufacture of nanotherapeutics—A critical step for technology transfer, VIEW. 2 (2021) 20200190.
Mahdavimanshadi, M., Anaraki, M. G., Mowlai, M., & Ahmadirad, Z. (2024, May). A Multistage Stochastic Optimization Model for Resilient Pharmaceutical Supply Chain in COVID-19 Pandemic Based on Patient Group Priority. In 2024 Systems and Information Engineering Design Symposium (SIEDS) (pp. 382-387). IEEE.
Mehrani, K., Mirshahvalad, A., & Abbasi, E. (2019). Comparison of the Accuracy of Black Hole Algorithms and Gravitational Research and the Hybrid Method in Portfolio Optimization. International Journal of Finance & Managerial Accounting, 4(14), 111-126.
Mehrani, K., Mirshahvalad, A., & Abbasi, E. (2019). Portfolio Optimization Using Black Hole Meta Heuristic Algorithm. Specialty Journal of Accounting and Economics, 5(2), 1-13.
Mikkonen, T., Lassenius, C., Männistö, T., Oivo, M., & Järvinen, J. (2018). Continuous and collaborative technology transfer: Software engineering research with real-time industry impact. Information and Software Technology, 95, 34-45.
Nasir, M. F. M., bin Abdul Rahim, A. R., bin Yusof, M. F., Ma’arof, M. I. N., & Chala, G. T. (2023). Transfer of Technology for Tactical Floating Bridge Local Fabrication. Journal of Innovation and Technology, 2023.
Noh, H., Kang, S., & Lee, S. (2019). Patterns of international technology acquisition in a post catch-up country: the case of Korean firms. Asian Journal of Technology Innovation, 27(1), 1-22.
Novickis, L., Mitasiunas, A., & Ponomarenko, V. (2017). Information technology transfer model as a bridge between science and business sector. Procedia Computer Science, 104, 120-126.
Pinto, M. M. A., Kovaleski, J. L., Yoshino, R. T., & Pagani, R. N. (2019). Knowledge and technology transfer influencing the process of innovation in green supply chain management: A multicriteria model based on the DEMATEL Method. Sustainability, 11(12), 3485.
Salahi, F., Daneshvar, A., Homayounfar, M., & Pourghader Chobar, A. (2023). Presenting an integrated model for production planning and preventive maintenance scheduling considering uncertainty of parameters and disruption of facilities. Journal of Industrial Management Perspective, 13(1), 105-39.
Schaeffer, V., Öcalan-Özel, S., & Pénin, J. (2020). The complementarities between formal and informal channels of university–industry knowledge transfer: a longitudinal approach. The Journal of Technology Transfer, 45, 31-55.
Secundo, G., De Beer, C., & Passiante, G. (2016). Measuring university technology transfer efficiency: a maturity level approach. Measuring Business Excellence, 20(3), 42-54.
Silva, S. S. D., Feldmann, P. R., Spers, R. G., & Bambini, M. D. (2019). Analysis of the process of technology transfer in public research institutions: The Embrapa agrobiology case. Innovation & Management Review, 16(4), 375-390.
Sutopo, W., Khofiyah, N. A., Hisjam, M., & Ma’aram, A. (2022). Performance Efficiency Measurement Model Development of a Technology Transfer Office (TTO) to Accelerate Technology Commercialization in Universities. Applied System Innovation, 5(1), 21.
Uusitalo, P., & Lavikka, R. (2021). Technology transfer in the construction industry. The Journal of Technology Transfer, 46(5), 1291-1320.

  • Receive Date 22 February 2024
  • Revise Date 28 April 2024
  • Accept Date 30 May 2024