A Hybrid Fuzzy Approach of Similarity-Influence-Network and DEMATEL: Visualization and Analysis
DOI:
https://doi.org/10.11113/mjfas.v20n2.3343Keywords:
Similarity of preferences, Social Influence Network, DEMATEL, importance of criteria, criteria interdependencyAbstract
The Social Influence Group Decision Making (SIGDM) entails intricate intra- and interpersonal exchanges among a group of experts as they endeavor to persuade others toward reaching a mutually agreed-upon solution. However, prevailing SIGDM approaches often overlook the critical aspect of visualizing criteria interdependencies. This visual representation becomes crucial as it provides supplementary insights into analyzing the significance of criteria and their impacts within decision-making processes. In order to address the oversight of neglecting criteria interdependent relationships, we extend the similarity-influence-network algorithm by integrating a cause-effect visualization procedure inspired by the DEMATEL approach. Additionally, we introduce several supplementary steps to enhance the efficacy of existing methodologies. The proposed model not only fills a gap in the current methodology but also provides accuracy of influence representation by incorporating influence-based collective preferences. This hybrid approach stands as a valuable alternative decision-making tool, providing a comparative analysis of the related existing approaches.
References
Ahmad Shamudin, N. A. B. (2022). Visualisation of cause-effect criteria in preference similarity social influence network group decision making model. Master's Dissertation. Universiti Teknologi MARA.
Abdullah, L., Zulkifli, N., Liao, H., Herrera-Viedma, E., & Al-Barakati, A. (2019). An interval-valued intuitionistic fuzzy DEMATEL method combined with Choquet integral for sustainable solid waste management. Engineering Applications of Artificial Intelligence, 82, 207-215.
Sedek, A. N. S. A. B., Kamis, N. H., Kadir, N. A., Mohamad, D., & Chiclana, F. (2022, July). Social influence in fuzzy group decision making with applications. in intelligent and fuzzy systems: Digital acceleration and the new normal. Proceedings of the INFUS 2022 Conference, 2(505), 272.
Giri, B. C., Molla, M. U., & Biswas, P. (2022). Pythagorean fuzzy DEMATEL method for supplier selection in sustainable supply chain management. Expert Systems with Applications, 193, 116396.
Gong, K., Ma, W., Lei, W., & Goh, M. (2023). A dynamic trust network and influence measure-based consensus model for large-scale group decision-making with incomplete intuitionistic fuzzy preference relations. Journal of the Operational Research Society, 1-21.
González-Arteaga, T., de Andrés Calle, R., & Chiclana, F. (2016). A new measure of consensus with reciprocal preference relations: The correlation consensus degree. Knowledge-Based Systems, 107, 104-116.
Kamis, N. H., Chiclana, F., & Levesley, J. (2018). Preference similarity network structural equivalence clustering based consensus group decision making model. Applied Soft Computing, 67, 706-720.
Kamis, N. H., Chiclana, F., & Levesley, J. (2019). An influence-driven feedback system for preference similarity network clustering based consensus group decision making model. Information Fusion, 52, 257-267.
Kuzu, A. C. (2023). Application of fuzzy DEMATEL approach in maritime transportation: A risk analysis of anchor loss. Ocean Engineering, 273, 113786.
Lee, Y. C., Yen, T. M., & Tsai, C. H. (2008). Using importance performance analysis and decision making trial and evaluation laboratory to enhance order-winner criteria-A study of computer industry. Information Technology Journal, 7(3), 396-408.
Li, S., & Wei, C. (2019). Modeling the social influence in consensus reaching process with interval fuzzy preference relations. International Journal of Fuzzy Systems, 21, 1755-1770.
Liou, J. J., Tzeng, G. H., & Chang, H. C. (2007). Airline safety measurement using a hybrid model. Journal of Air Transport Management, 13(4), 243-249.
Seker, S., & Zavadskas, E. K. (2017). Application of fuzzy DEMATEL method for analyzing occupational risks on construction sites. Sustainability, 9(11), 2083.
Soner, O. (2021). Application of fuzzy DEMATEL method for analysing of accidents in enclosed spaces onboard ships. Ocean Engineering, 220, 108507.
Suzan, V., & Yavuzer, H. (2020). A Fuzzy Dematel Method to evaluate the most common diseases in internal medicine. International Journal of Fuzzy Systems, 22, 2385-2395.
Yager, R. R., & Filev, D. (1998, May). Operations for granular computing: mixing words and numbers. In 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No. 98CH36228) (Vol. 1, pp. 123-128). IEEE.
Yao, S., & Gu, M. (2022). An influence network-based consensus model for large-scale group decision making with linguistic information. International Journal of Computational Intelligence Systems, 15, 1-17.
Zhang, T., Tao, D., Qu, X., Zhang, X., Zeng, J., Zhu, H., & Zhu, H. (2020). Automated vehicle acceptance in China: Social influence and initial trust are key determinants. Transportation Research Part C: Emerging Technologies, 112, 220-233.
Zhang, J., Zhang, S., Liang, Z., Lang, X., Shi, M., Qiao, J., ... & Kang, J. (2024). A risk assessment method based on DEMATEL-STPA and its application in safety risk evaluation of hydrogen refueling stations. International Journal of Hydrogen Energy, 50, 889-902.
Zhou, Q., Huang, W., & Zhang, Y. (2011). Identifying critical success factors in emergency management using a fuzzy DEMATEL method. Safety Science, 49(2), 243-252.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Nor Hanimah Kamis, Nurul Atiqah Ahmad Shamudin, Adem Kilicman, Norhidayah A Kadir, Binyamin Yusoff
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
