Construction of a model for evaluating the efficiency of technology transfer process based on a fuzzy logic approach

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.300796

Keywords:

technology transfer projects, MATLAB environment, fuzzy logic, Mamdani method

Abstract

The object of research is technology transfer, which covers the mechanism of transfer of technological knowledge and innovations from developers to end users or manufacturers. The problem to be solved is to provide a relevant assessment of the effectiveness of technology transfer by applying modern economic and mathematical models (based on the method of fuzzy logic) to assess the effectiveness of technology transfer under conditions of uncertainty.

The main results obtained: a fuzzy-logical model for evaluating the level of the technology transfer efficiency indicator was built; it is performed according to the following algorithm:

1) the involvement of three components of technology transfer – technological, financial, and marketing as input variables of the model, which are calculated on the basis of statistical and financial reporting data, expert surveys;

2) selection of parameters and type of membership function for three input variables and one output variable (integral indicator) and construction of a system of 27 logical rules;

3) determining the efficiency of technology transfer using Mamdani's fuzzy derivation and checking the adequacy of the model.

A visualization of the "input-output" surface was performed, which determines the maximum value of the TTPE (TechnologyTransferProjectsEfficiency) indicator, which serves as a summary indicator for the success of technology transfer projects and is observed at high levels of model input variables. The indicator T (technical component of technology transfer efficiency), F (financial component of technology transfer efficiency), and M (marketing component of technology transfer efficiency) was introduced.

The scientific results could be applied to determine the optimal ways of technology transfer to industry, to plan strategies for introducing new technological products to the market, taking into account the effectiveness of licensing, partnership, and cooperation processes

Author Biographies

Viacheslav Makedon, Oles Honchar Dnipro National University

Doctor of Economic Sciences, Professor

Department of International Economics and World Finances

Valentin Myachin, Dnipropetrovsk State University of Internal Affairs

Doctor of Economic Sciences, PhD

Department of Analytical Economics and Management

Olena Plakhotnik, Dniprovsky State Technical University

Doctor of Economic Scinces

Department of Management

Nadiia Fisunenko, Dnipropetrovsk State University of Internal Affairs

PhD

Department of Analytical Economics and Management

Olha Mykhailenko, Oles Honchar Dnipro National University

PhD, Associate Professor

Department of International Economics and World Finances

References

  1. Makedon, V., Krasnikova, N., Krupskyi, O., Stasiuk, Y. (2022). Arrangement of Digital Leadership Strategy by Corporate Structures: A Review. Ikonomicheski Izsledvania, 31, 19–40. Available at: https://www.academia.edu/92269253/Arrangement_of_Digital_Leadership_Strategy_by_Corporate_Structures_A_Review
  2. Siler, W., Buckley, J. J. (2005). Fuzzy Expert Systems and Fuzzy Reasoning. John Wiley & Sons, Inc. https://doi.org/10.1002/0471698504
  3. Sarfaraz, A. H., Yazdi, A. K., Hanne, T., Hosseini, R. S. (2023). Decision support for technology transfer using fuzzy quality function deployment and a fuzzy inference system. Journal of Intelligent & Fuzzy Systems, 44 (5), 7995–8014. https://doi.org/10.3233/jifs-222232
  4. Sabounchi, M., Wei-Kocsis, J. (2021). FLTRL: A Fuzzy-Logic Transfer Learning Powered Reinforcement Learning Method for Intelligent Online Control in Power Systems. Lecture Notes in Networks and Systems, 368–379. https://doi.org/10.1007/978-3-030-82099-2_33
  5. Makedon, V., Zaikina, H., Slusareva, L., Shumkova, O., Zhmaylova, O. (2020). Use of rebranding in marketing sphere of international entrepreneurship. International Journal of Entrepreneurship, 24 (1S). Available at: https://www.abacademies.org/articles/use-of-rebranding-in-marketing-sphere-of-international-entrepreneurship-9325.html
  6. Makedon, V., Dzeveluk, A., Khaustova, Y., Bieliakova, O., Nazarenko, I. (2021). Enterprise multi-level energy efficiency management system development. International Journal of Energy, Environment, and Economics, 29 (1), 73–91. Available at: https://novapublishers.com/shop/enterprise-multi-level-energy-efficiency-management-system-development/
  7. Mohammadi, N., Heidary Dahooie, J., Khajevand, M. (2021). A hybrid approach for identifying and prioritizing critical success factors in technology transfer projects (case study: diesel locomotive manufacturing). Journal of Engineering, Design and Technology, 21 (5), 1389–1413. https://doi.org/10.1108/jedt-07-2021-0345
  8. Estep, J., Daim, T. (2016). A framework for technology transfer potential assessment. 2016 Portland International Conference on Management of Engineering and Technology (PICMET). https://doi.org/10.1109/picmet.2016.7806626
  9. Dandoussou, A., Kenfack, P. (2023). Fuzzy Logic Control of an Automatic Changeover for the Management of a Grid-Connected Photovoltaic System. International Transactions on Electrical Energy Systems, 2023, 1–13. https://doi.org/10.1155/2023/9960296
  10. Hong, J., Cha, J., G., B., Park, K. (2023). Evaluation framework for facilitating the technology transfers of universities: Focusing on the perspective of technology donors. PLOS ONE, 18 (12), e0293951. https://doi.org/10.1371/journal.pone.0293951
  11. Sardak, S., Britchenko, I., Vazov, R., Krupskyi, O. P. (2021). Life cycle: formation, structure, management. Economic Studies (Ikonomicheski Izsledvania), 30 (6), 126–142. Available at: https://www.iki.bas.bg/Journals/EconomicStudies/2021/2021-6/7_Krupskyi_f_f.pdf
  12. Iroegbu, U. F., Ushie, M. A., Otiala, B. P. (2021). A Fuzzy AHP Approach for Technology Transfer Problems: A Case Study of Africa and China Partnerships. American Journal of Industrial and Business Management, 11 (06), 646–663. https://doi.org/10.4236/ajibm.2021.116042
  13. Yazdi Moghaddam, J., Owlia, M. S., Bandarian, R. (2018). Developing a fuzzy expert system to predict technology commercialization success. Journal of Industrial and Systems Engineering, 11 (2), 228–250. Available at: https://www.jise.ir/article_74015_094b4a1e30d23cd5ea4fefb5c0707ba3.pdf
  14. Makedon, V., Mykhailenko, O., Dzyad, O. (2023). Modification of the Value Management of International Corporate Structures in the Conditions of the Digital Economy. European Journal of Management Issues, 31 (1), 50–62. https://doi.org/10.15421/192305
  15. Battistella, C., De Toni, A. F., Pillon, R. (2015). Inter-organisational technology/knowledge transfer: a framework from critical literature review. The Journal of Technology Transfer, 41 (5), 1195–1234. https://doi.org/10.1007/s10961-015-9418-7
  16. Cho, J., Lee, J. (2013). Development of a new technology product evaluation model for assessing commercialization opportunities using Delphi method and fuzzy AHP approach. Expert Systems with Applications, 40 (13), 5314–5330. https://doi.org/10.1016/j.eswa.2013.03.038
  17. Akkaya, G., Turanoğlu, B., Öztaş, S. (2015). An integrated fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing. Expert Systems with Applications, 42 (24), 9565–9573. https://doi.org/10.1016/j.eswa.2015.07.061
  18. Peckol, J. K. (2021). Introduction to Fuzzy Logic. John Wiley & Sons Ltd. https://doi.org/10.1002/9781119772644
  19. Hernández-Hernández, M., Alfonso Bonilla Cruz, L., Cobián-Romero, L. (2024). Improvement of Validated Manufacturing Processes with Fuzzy Logic. Supply Chain - Perspectives and Applications. https://doi.org/10.5772/intechopen.113302
  20. Servin, C., Becker, B. A., Eaton, E., Kumar, A. (2023). Fuzzy Logic++: Towards Developing Fuzzy Education Curricula Using ACM/IEEE/AAAI CS2023. Lecture Notes in Networks and Systems, 184–193. https://doi.org/10.1007/978-3-031-46778-3_17
  21. Kibira, D., Brundage, M. P., Feng, S., Morris, K. C. (2017). Procedure for Selecting Key Performance Indicators for Sustainable Manufacturing. Journal of Manufacturing Science and Engineering, 140 (1). https://doi.org/10.1115/1.4037439
  22. Krupskyi, O. P., Kuzmytska, Y. (2020). Organizational Culture and Business Strategy: Connection and Role for A Company Survival. Central European Business Review, 9 (4), 1–26. https://doi.org/10.18267/j.cebr.241
  23. Kumar, S., Luthra, S., Haleem, A. (2015). Benchmarking supply chains by analyzing technology transfer critical barriers using AHP approach. Benchmarking: An International Journal, 22 (4), 538–558. https://doi.org/10.1108/bij-05-2014-0040
  24. Makedon, V., Mykhailenko, O., Vazov, R. (2021). Dominants and Features of Growth of the World Market of Robotics. European Journal of Management Issues, 29 (3), 133–141. https://doi.org/10.15421/192113
  25. Azagra-Caro, J. M., Barberá-Tomás, D., Edwards-Schachter, M., Tur, E. M. (2017). Dynamic interactions between university-industry knowledge transfer channels: A case study of the most highly cited academic patent. Research Policy, 46 (2), 463–474. https://doi.org/10.1016/j.respol.2016.11.011
  26. Mendez, G. M., Lopez-Juarez, I., Montes-Dorantes, P. N., Garcia, M. A. (2023). A New Method for the Design of Interval Type-3 Fuzzy Logic Systems With Uncertain Type-2 Non-Singleton Inputs (IT3 NSFLS-2): A Case Study in a Hot Strip Mill. IEEE Access, 11, 44065–44081. https://doi.org/10.1109/access.2023.3272531
  27. Rostek, K. (2014). Modeling Commercial Potential of Innovative Projects. International Review of Management and Business Research, 3 (1), 78–95. Available at: https://irmbrjournal.com/papers/1389633477.pdf
Construction of a model for evaluating the efficiency of technology transfer process based on a fuzzy logic approach

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Published

2024-04-30

How to Cite

Makedon, V., Myachin, V., Plakhotnik, O., Fisunenko, N., & Mykhailenko, O. (2024). Construction of a model for evaluating the efficiency of technology transfer process based on a fuzzy logic approach. Eastern-European Journal of Enterprise Technologies, 2(13 (128), 47–57. https://doi.org/10.15587/1729-4061.2024.300796

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Section

Transfer of technologies: industry, energy, nanotechnology