Published In
Technological Forecasting and Social Change
Document Type
Article
Publication Date
6-2023
Subjects
Transportation monitoring, Real-time information, Traffic safety -- Metaverse
Abstract
As the Metaverse’s popularity grows, its effect on everyday problems is beginning to be discussed. The upcoming Metaverse world will influence the transportation system as cross-border lines blur due to rapid globalization. The purpose of this paper is to investigate the capabilities of the Metaverse and its alternatives to traffic safety, as well as to prioritize its advantages. The case study is based on a densely populated metropolis with an extensive education system. The city’s decision-makers will have to weigh the pros and cons of the Metaverse’s effect on traffic safety. To illustrate the complex forces that drive the decision-making process in traffic safety, we create a case study with four alternatives to Metaverse’s integration into the traffic system. Alternatives are evaluated using twelve criteria that reflect the decision problem’s rules and regulations, technology, socioeconomic, and traffic aspects. In this study, fuzzy Einstein based logarithmic methodology of additive weights (LMAW) is applied to calculate the weights of the criteria. We present a new framework that combines Einstein norms and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the alternatives. The findings of this study show that public transportation is the most appropriate area for implementing the Metaverse into traffic safety because of its practical opportunities and broad usage area.
Rights
Copyright (c) 2023 The Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
Locate the Document
DOI
10.1016/j.techfore.2023.122681
Persistent Identifier
https://archives.pdx.edu/ds/psu/40616
Citation Details
Deveci, M., Pamucar, D., Gokasar, I., Köppen, M., Gupta, B. B., & Daim, T. (2023). Evaluation of Metaverse traffic safety implementations using fuzzy Einstein based logarithmic methodology of additive weights and TOPSIS method. Technological Forecasting and Social Change, 194, 122681.