Multi-Criteria Decision-Making Methodology for Ranking and Selecting Optimal Metaverse Platform
DOI:
https://doi.org/10.22105/74z15m70Keywords:
Multi-criteria decision making, Metaverse platform, Selection problem, MABAC methodAbstract
This study adopted a decision-making model for ranking and sectioning the best Metaverse platforms. This section has various criteria such as effectiveness, safety, user experience, etc. So, the Multi-Criteria Decision-Making (MCDM) methodology is used to deal with multiple criteria. The MABAC method is an MCDM methodology used to rank the alternatives. The proposed methodology is applied to nine criteria and fifteen alternatives. The criteria weights are computed. The sensitivity analysis is conducted to show the stability of the final rank. The ten cases in criteria weights are proposed, and ten ranks are shown. The results show the rank of alternatives under different cases is stable. The comparative analysis is conducted with other MCDM methods such as TOPSIS, VIKOR, EDAS, and COPRAS. The results show the proposed methodology is effective with other MCDM methods.
References
[1] Jeon, J. E. (2021). The effects of user experience-based design innovativeness on user-metaverse platform channel relationships in South Korea. Journal of distribution science, 19(11), 81–90.
[2] Kim, J. G. (2021). A study on metaverse culture contents matching platform. International journal of advanced culture technology, 9(3), 232–237.
[3] Periyasami, S., & Periyasamy, A. P. (2022). Metaverse as future promising platform business model: case study on fashion value chain. Businesses, 2(4), 527–545.
[4] Yoo, G. S., & Chun, K. (2021). A study on the development of a game-type language education service platform based on metaverse. Journal of digital contents society, 22(9), 1377–1386.
[5] Han, J., Heo, J., & You, E. (2021). Analysis of metaverse platform as a new play culture: focusing on roblox and zepeto [presentation]. International conference on human-centered artificial intelligence (pp. 1–10).
[6] Jovanović, A., & Milosavljević, A. (2022). VoRtex Metaverse platform for gamified collaborative learning. Electronics, 11(3), 317.
[7] Gwak, H. G., & Shin, D. H. (2023). The effect of Metaverse platform-based. Journal of korean elementary science education, 42(2), 385–397.
[8] Jeong, H., Yi, Y., & Kim, D. (2022). An innovative e-commerce platform incorporating metaverse to live commerce. International journal of innovative computing, information and control, 18(1), 221–229.
[9] Park, S., & Kang, Y. J. (2021). A study on the intentions of early users of metaverse platforms using the technology acceptance model. Journal of digital convergence, 19(10), 275–285.
[10] Ko, H., Jeon, J., & Yoo, I. (2022). Metaverse platform-based flipped learning framework development and application. Journal of the korean association of information education, 26(2), 129–140.
[11] Lukić, R. (2021). Application of MABAC method in evaluation of sector efficiency in Serbia. Revista de management comparat internațional, 22(3), 400–418.
[12] Jia, F., Liu, Y., & Wang, X. (2019). An extended MABAC method for multi-criteria group decision making based on intuitionistic fuzzy rough numbers. Expert systems with applications, 127, 241–255.
[13] Pamučar, D., Petrović, I., & Ćirović, G. (2018). Modification of the best–worst and MABAC methods: a novel approach based on interval-valued fuzzy-rough numbers. Expert systems with applications, 91, 89–106. https://www.sciencedirect.com/science/article/pii/S0957417417305882
[14] Torkayesh, A. E., Tirkolaee, E. B., Bahrini, A., Pamucar, D., & Khakbaz, A. (2023). A systematic literature review of MABAC method and applications: an outlook for sustainability and circularity. Informatica, 34(2), 415–448.
[15] Wei, G., Wei, C., Wu, J., & Wang, H. (2019). Supplier selection of medical consumption products with a probabilistic linguistic MABAC method. International journal of environmental research and public health, 16(24), 5082.
[16] Alinezhad, A., Khalili, J., Alinezhad, A., & Khalili, J. (2019). MABAC method. New methods and applications in multiple attribute decision making (MADM), 193–198.
[17] Wang, J., Wei, G., Wei, C., & Wei, Y. (2020). MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment. Defence technology, 16(1), 208–216.
[18] Sun, R., Hu, J., Zhou, J., & Chen, X. (2018). A hesitant fuzzy linguistic projection-based MABAC method for patients’ prioritization. International journal of fuzzy systems, 20, 2144–2160.
Metrics
