Examining the causal factors of the electric vehicle adoption: a pathway to tackle climate change in resource-constrained environment

Abstract

Electric vehicles (EVs) serve an important role in lowering greenhouse gas emissions, which helps to mitigate global warming while also contributing to long-term growth. Thus, this research explores various criterions relevant to electric vehicle (EVs) adoption and causal relationships using the decision-making trial and evaluation laboratory (DEMATEL) method. From the comprehensive literature review, a set of criteria for EVs adoption were identified and are finalised through the Delphi method. The data was gathered from eleven experts and was analyzed using the DEMATEL method to develop the causal relationship between each criterion. The sensitivity analysis was performed to check the robustness of the model. The findings revealed that the key criteria for EV adoption include their causal relationships. It is observed that charging time, driving range and price are the most important criteria for an EV purchase. Battery capacities have a major and influential impact on other criteria like charging time, torque, driving range, and maximum power. Professionals and managers in the EV manufacturing industry can benefit from this prioritization of criteria by understanding the causal relationships between them. This study can also serve as guidance for EV engineers when it comes to implementing client preferences into vehicle design. It can also assist low-performing electric vehicles in determining their benchmarks. This work contributes to building an improved understanding of causal factors of electric vehicle adoption in resource-constrained environments for policy making.

Grey hybrid normalization with period based entropy weighting and relational analysis for cities rankings

“…Recently, Javanmardi et al 32 present the challenges of uncertainty in sustainability based on GST. Sonar et al 33 applied the decision making trial and evaluation laboratory approach to examine the factors for EV purchase and discovered charging time, driving range and price as the primary factors affecting EV adoption. Tavana et al 34 used the Internet of Things and big data to design a sustainable supply chain model for EV battery production-a fuzzy bi-objective mixed-integer linear programming model for manufacturing, remanufacturing, and distributing EV lithium-ion batteries.…”

Electric Vehicle Adoption Barriers in Thailand

“…When comparing DEMATEL with other techniques such as the AHP, Best Worst Method, VIKOR (VIekriterijumsko KOmpromisno Rangiranje), and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), it becomes clear that DEMATEL is superior because it not only identifies the connection between the components but also separates them into two groups: causes and effects. Meanwhile, the remaining techniques ignore the connection between variables [20]. To represent components in a hierarchical sequence, interpretive structural modeling (ISM) and DEMATEL approaches are useful tools for structural modeling.…”