IDEAS home Printed from https://ideas.repec.org/a/bas/econst/y2022i1p139-159.html
   My bibliography  Save this article

Fuzzy Logic Decision-Making Model for Technology Foresight

Author

Listed:
  • Vladyslav Sotnyk
  • Artem Kupchyn
  • Viktor Trynchuk
  • Vladimer Glonti
  • Larisa Belinskaja

Abstract

A new decision-making model in technology foresight based on fuzzy logic is proposed. The choice of technology as disruptive or critical doesn’t depend on the subjective expert’s opinion, but bases on the mathematically justified limits of technologies criticality. The basis of the model is the fuzzy inference system by Mamdani algorithm. Five of the most important criteria of criticality have been used as input linguistic variables. A new approach to defining membership functions based on equidistant derivative points is proposed and described in detail. The functioning of the model is considered by example. The influence of the application of different membership functions on the criticality assessment is shown. A comparison between the fuzzy model and classic expert model is also conducted.

Suggested Citation

  • Vladyslav Sotnyk & Artem Kupchyn & Viktor Trynchuk & Vladimer Glonti & Larisa Belinskaja, 2022. "Fuzzy Logic Decision-Making Model for Technology Foresight," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 139-159.
    • Handle: RePEc:bas:econst:y:2022:i:1:p:139-159
    as

    Download full text from publisher

    File URL: https://www.iki.bas.bg/Journals/EconomicStudies/2022/2022-1/08_Britchenko-2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ezgi Erturk & Ebru Akcapinar Sezer, 2016. "Software fault prediction using Mamdani type fuzzy inference system," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 8(1), pages 14-28.
    2. Bota, Constantin & Căruntu, Bogdan, 2017. "Analytical approximate solutions for quadratic Riccati differential equation of fractional order using the Polynomial Least Squares Method," Chaos, Solitons & Fractals, Elsevier, vol. 102(C), pages 339-345.
    3. Khrystyna Danylkiv & Khrystyna Gorbova & Nataliia Hembarska & Viktor Trynchuk & Yurii Paida & Volodymyr Havran, 2020. "Methods of Economic Evaluation of Concession Project Effectiveness," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 16(4), pages 67-84.
    4. Hafezali Iqbal Hussain & Beata Slusarczyk & Fakarudin Kamarudin & Hassanudin Mohd Thas Thaker & Katarzyna Szczepańska-Woszczyna, 2020. "An Investigation of an Adaptive Neuro-Fuzzy Inference System to Predict the Relationship among Energy Intensity, Globalization, and Financial Development in Major ASEAN Economies," Energies, MDPI, vol. 13(4), pages 1-17, February.
    5. Alexander Baranovsky & Nataliia Tkachenko & Vladimer Glonti & Valentyna Levchenko & Kateryna Bogatyrova & Zaza Beridze & Larisa Belinskaja & Iryna Zelenitsa, 2020. "Non-Price Criteria for the Evaluation of the Tender Offers in Public Procurement of Ukraine," IJFS, MDPI, vol. 8(3), pages 1-15, July.
    6. Keshtkar, Azim & Arzanpour, Siamak, 2017. "An adaptive fuzzy logic system for residential energy management in smart grid environments," Applied Energy, Elsevier, vol. 186(P1), pages 68-81.
    7. Jin-Biao Lu & Zhi-Jiang Liu & Dmitry Tulenty & Liudmila Tsvetkova & Sebastian Kot, 2021. "RETRACTED: Implementation of Stochastic Analysis in Corporate Decision-Making Models," Mathematics, MDPI, vol. 9(9), pages 1-16, May.
    8. Prasert Aengchuan & Busaba Phruksaphanrat, 2018. "Comparison of fuzzy inference system (FIS), FIS with artificial neural networks (FIS + ANN) and FIS with adaptive neuro-fuzzy inference system (FIS + ANFIS) for inventory control," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 905-923, April.
    9. Elizabeth Gibson & Tugrul Daim & Edwin Garces & Marina Dabic, 2018. "Technology Foresight: A Bibliometric Analysis to Identify Leading and Emerging Methods," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 12(1), pages 6-24.
    10. Igor Britchenko & Anna Kniazevych, 2015. "The Bases of Functioning and Development of Innovative Infrastructure of Ukraine," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 43-66.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Igor Britchenko & Oksana Polinkevych & Viktor Trynchuk & Inna Khovrak, 2023. "The Impact of COVID-19 on the Philosophy of Doing Business in a Sustainable Environment," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 100-116.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Panagiotis Michailidis & Iakovos Michailidis & Dimitrios Vamvakas & Elias Kosmatopoulos, 2023. "Model-Free HVAC Control in Buildings: A Review," Energies, MDPI, vol. 16(20), pages 1-45, October.
    2. Chen, Liudong & Liu, Nian & Li, Chenchen & Wu, Lei & Chen, Yubing, 2021. "Multi-party stochastic energy scheduling for industrial integrated energy systems considering thermal delay and thermoelectric coupling," Applied Energy, Elsevier, vol. 304(C).
    3. Hannan, M.A. & Lipu, M.S. Hossain & Ker, Pin Jern & Begum, R.A. & Agelidis, Vasilios G. & Blaabjerg, F., 2019. "Power electronics contribution to renewable energy conversion addressing emission reduction: Applications, issues, and recommendations," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    4. Nazim Hajiyev & Klaudia Smoląg & Ali Abbasov & Valeriy Prasolov, 2020. "Energy War Strategies: The 21st Century Experience," Energies, MDPI, vol. 13(21), pages 1-15, November.
    5. Rafal Nagaj & Jaroslaw Korpysa, 2020. "Impact of COVID-19 on the Level of Energy Poverty in Poland," Energies, MDPI, vol. 13(18), pages 1-18, September.
    6. Dawid Stadniczenko, 2020. "Development and Challenges for the Functioning of the Renewable Energy Prosumer in Poland: A Legal Perspective," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 623-630.
    7. Beata Poteralska, 2021. "Support for the Development of Technological Innovations at an R&D Organisation," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    8. Fotio, Hervé Kaffo & Adams, Samuel & Nkengfack, Hilaire & Poumie, Boker, 2023. "Achieving sustainable development goal 7 in Africa: Does globalization matter for electricity access, renewable energy consumption, and energy efficiency?," Utilities Policy, Elsevier, vol. 82(C).
    9. Ferahtia, Seydali & Houari, Azeddine & Cioara, Tudor & Bouznit, Mohammed & Rezk, Hegazy & Djerioui, Ali, 2024. "Recent advances on energy management and control of direct current microgrid for smart cities and industry: A Survey," Applied Energy, Elsevier, vol. 368(C).
    10. Shahin Bayramov & Iurii Prokazov & Sergey Kondrashev & Jan Kowalik, 2021. "Household Electricity Generation as a Way of Energy Independence of States—Social Context of Energy Management," Energies, MDPI, vol. 14(12), pages 1-19, June.
    11. Mufutau Opeyemi, Bello, 2021. "Path to sustainable energy consumption: The possibility of substituting renewable energy for non-renewable energy," Energy, Elsevier, vol. 228(C).
    12. Jia, Kunqi & Guo, Ge & Xiao, Jucheng & Zhou, Huan & Wang, Zhihua & He, Guangyu, 2019. "Data compression approach for the home energy management system," Applied Energy, Elsevier, vol. 247(C), pages 643-656.
    13. Octavian Dospinescu, 2022. "Business and Economics Mathematics," Mathematics, MDPI, vol. 10(20), pages 1-3, October.
    14. Bożena Gajdzik & Włodzimierz Sroka & Jolita Vveinhardt, 2021. "Energy Intensity of Steel Manufactured Utilising EAF Technology as a Function of Investments Made: The Case of the Steel Industry in Poland," Energies, MDPI, vol. 14(16), pages 1-17, August.
    15. Germán González Rodríguez & Jose M. Gonzalez-Cava & Juan Albino Méndez Pérez, 2020. "An intelligent decision support system for production planning based on machine learning," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1257-1273, June.
    16. Seyed Mahmoud Zanjirchi & Mina Rezaeian Abrishami & Negar Jalilian, 2019. "Four decades of fuzzy sets theory in operations management: application of life-cycle, bibliometrics and content analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1289-1309, June.
    17. Jasleen Kaur & Khushdeep Dharni, 2022. "Application and performance of data mining techniques in stock market: A review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(4), pages 219-241, October.
    18. Aleksandra Pavlović & Milica Njegovan & Andrea Ivanišević & Mladen Radišić & Aleksandar Takači & Alpar Lošonc & Sebastian Kot, 2021. "The Impact of Foreign Direct Investments and Economic Growth on Environmental Degradation: The Case of the Balkans," Energies, MDPI, vol. 14(3), pages 1-21, January.
    19. Clarke, Will Challis & Brear, Michael John & Manzie, Chris, 2020. "Control of an isolated microgrid using hierarchical economic model predictive control," Applied Energy, Elsevier, vol. 280(C).
    20. Janusz Grabara & Arsen Tleppayev & Malika Dabylova & Leonardus W. W. Mihardjo & Zdzisława Dacko-Pikiewicz, 2021. "Empirical Research on the Relationship amongst Renewable Energy Consumption, Economic Growth and Foreign Direct Investment in Kazakhstan and Uzbekistan," Energies, MDPI, vol. 14(2), pages 1-18, January.

    More about this item

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • O20 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bas:econst:y:2022:i:1:p:139-159. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Diana Dimitrova (email available below). General contact details of provider: https://edirc.repec.org/data/ikbasbg.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.