Conclusion- Employing hesitant fuzzy sets enable a better representation of decision makers’ inguistic evaluations and thus provide better results.
📌 3 Maddede Bu Makale
🎯
Amaç & Hipotez:Purpose- In recent decades, innovation and desearch and development (R&D) has been the key component for growth and economic competitiveness for companies and countries.Methodology- Since innovation Project require considerable funds and contain risk, it is important to evaluate their potantial performance and return on investment to make proper decision.Findings- The objective of this study is to develop a decision model for innovative Project selection using multicriteria decision making model (MCDM) and Hesitant Fuzzy sets.
📊
Temel Bulgular & Veri:By using MCDM approach, various perspectives on project evaluation can be integrated into decision making model.
💡
Sonuç & Katkı:Conclusion- Employing hesitant fuzzy sets enable a better representation of decision makers’ inguistic evaluations and thus provide better results.
Purpose- In recent decades, innovation and desearch and development (R&D) has been the key component for growth and economic competitiveness for companies and countries.Methodology- Since innovation Project require considerable funds and contain risk, it is important to evaluate their potantial performance and return on investment to make proper decision.Findings- The objective of this study is to develop a decision model for innovative Project selection using multicriteria decision making model (MCDM) and Hesitant Fuzzy sets. By using MCDM approach, various perspectives on project evaluation can be integrated into decision making model. Conclusion- Employing hesitant fuzzy sets enable a better representation of decision makers’ inguistic evaluations and thus provide better results.
Oztaysi, B., Onar, S. C., Kahraman, C. (2017). SELECTION AMONG INNOVATIVE PROJECT PROPOSALS USING A HESITANT FUZZY MULTIPLE CRITERIA DECISION MAKING METHOD. Journal of Economics Finance and Accounting, Cilt: 4 - Sayı: 2, 194–202. https://ajindex.com/articles/835450
Meuer, J., Rupietta, C., Backes-Gellner, U. 2015. “Layers of co-existing innovation systems”. Research Policy, 44(4), 888-910.
Gourville, J. 2006, “Eager seller and stony buyers: understanding the psychology of new-product adaptation”. Harvard Business Review, 84(6), 98-106.
Mohagheghi V., Mousavi S.M., Siadat A. 2015, "A new approach in considering vagueness and lack of knowledge for selecting sustainable portfolio of production projects" In: IEEE conference on industrial engineering and engineering management (IEEM), pp 1732–1736.
Heydari, T., Seyed Hosseini, S.-M., Makui, A. 2016, “Developing and solving an one-zero non-linear goal programming model to R and D portfolio project selection with interactions between projects”, International Business Management, 10(19), pp. 4516-4521. OECD, 2015. The OECD Innovation Strategy – 2015, http://www.oecd.org/innovation/innovation-imperative.htm, last accessed: 02.03.2017. Heidenberger K. Stummer C. 1999, “Research and development project selection and resource allocation: a review of quantitative modelling approaches”, International Jurnal of Management Reviews, Volume 1, Issue 2, Pages 197–224.
Oztaysi, B., Onar, S.C., Goztepe, K., Kahraman C. 2017 “Evaluation of research proposals for grant funding using interval-valued intuitionistic fuzzy sets”, Soft Computing, Volume 21, Issue 5, pp 1203–1218.
Morton A., Keiser J.M., Salo A. 2016. “Multicriteria Portfolio Decision Analysis for Project Selection, Multiple Criteria Decision Analysis”, Volume 233 of the series International Series in Operations Research & Management Science pp 1269-1298.
Read L., Madani K., Mokhtari S., Hanks C. 2017, “Stakeholder-driven multi-attribute analysis for energy project selection under uncertainty”, Energy, Volume 119, Pages 744-753. Rouhani S.2017 “A fuzzy superiority and inferiority ranking based approach for IT service management software selection”, Kybernetes, Vol. 46 Issue: 4, pp.728-746, (2017).
Oztaysi B., Cevik Onar B., Kahraman C. 2016 “Fuzzy multicriteria prioritization of Urban transformation projects for Istanbul”, Journal of Int. & Fuzzy Systems 30 (4), 2459-2474i Stojcetovic B., Nikolic D., Velinov V., Bogdanovic D. 2016, “Application of integrated strengths, weaknesses, opportunities, and threats and analytic hierarchy process methodology to renewable energy project selection in Serbia”, Journal of Renewable and Sustainable Energy, 8. Oztaysi, B. 2015. “A Group Decision Making Approach Using Interval Type-2 Fuzzy AHP