An integrated electric vehicle network planning with economic and ecological assessment: Application to the incipient middle Eastern market in transition towards sustainability
“…Comparable research examined the financial motivations associated with the adoption of EVs in the UAE (e.g., Anjam et al, 2020 [14]; Betancourt-Torcat et al, 2021 [15]; and Kiani, 2017 [16]). Betancourt-Torcat et al, 2021 [15] examined adoption rates in the Gulf Region including Saudi Arabia and the UAE. The authors underscore the significant role attributed to governmental policies in facilitating EV adoption rates.…”
Section: Economic Incentives Associated With Ev Adoptionmentioning
In 2022, the increased utilization of electric vehicles (EVs) curtailed global carbon dioxide emissions by 13 gigatons. While EV ownership has been on the rise in the United Arab Emirates (UAE), accounting for approximately 1.3% of passenger car vehicles in 2022, it has not yet attained a level of economic feasibility compared to petroleum vehicles. The authors examined consumers’ opinions in the UAE toward adopting EVs for light-duty transport from the economic and geographic perspectives. The main research question was the following: to what extent do economic and geographic factors affect consumers’ opinions toward adopting EVs in the UAE? The objectives were to determine if a relationship exists between economic factors, such as saving money on petroleum, the cost of car maintenance, the cost of purchase, and income level, and geographic factors, including 14 cities across the seven Emirates that affect consumers’ opinions toward adopting EVs. We designed a survey that was distributed to a sample of 5459 respondents to examine this relationship. Descriptive and inferential statistics as well as PyData analytical techniques complemented by the application of data visualization tools such as Seaborn, Plotly, and Matplotlib were employed to examine the dataset. The findings demonstrated that respondents across all income levels have a positive outlook regarding the appeal of EVs for saving money on petroleum, while their interest in saving money on car maintenance and the initial cost of purchase became more pronounced in the higher income levels. Moreover, there were variations in preferences in highly populated Emirates (e.g., Dubai and Abu Dhabi) compared to Emirates with lower populations (e.g., Ras Al Khaimah and Umm al Quwain), confirming that much more emphasis is required to promote EVs in rural areas. When comparing multiple income groups to determine the impact of different factors, the ANOVA confirmed the prevailing patterns evident in the associations.
“…Comparable research examined the financial motivations associated with the adoption of EVs in the UAE (e.g., Anjam et al, 2020 [14]; Betancourt-Torcat et al, 2021 [15]; and Kiani, 2017 [16]). Betancourt-Torcat et al, 2021 [15] examined adoption rates in the Gulf Region including Saudi Arabia and the UAE. The authors underscore the significant role attributed to governmental policies in facilitating EV adoption rates.…”
Section: Economic Incentives Associated With Ev Adoptionmentioning
In 2022, the increased utilization of electric vehicles (EVs) curtailed global carbon dioxide emissions by 13 gigatons. While EV ownership has been on the rise in the United Arab Emirates (UAE), accounting for approximately 1.3% of passenger car vehicles in 2022, it has not yet attained a level of economic feasibility compared to petroleum vehicles. The authors examined consumers’ opinions in the UAE toward adopting EVs for light-duty transport from the economic and geographic perspectives. The main research question was the following: to what extent do economic and geographic factors affect consumers’ opinions toward adopting EVs in the UAE? The objectives were to determine if a relationship exists between economic factors, such as saving money on petroleum, the cost of car maintenance, the cost of purchase, and income level, and geographic factors, including 14 cities across the seven Emirates that affect consumers’ opinions toward adopting EVs. We designed a survey that was distributed to a sample of 5459 respondents to examine this relationship. Descriptive and inferential statistics as well as PyData analytical techniques complemented by the application of data visualization tools such as Seaborn, Plotly, and Matplotlib were employed to examine the dataset. The findings demonstrated that respondents across all income levels have a positive outlook regarding the appeal of EVs for saving money on petroleum, while their interest in saving money on car maintenance and the initial cost of purchase became more pronounced in the higher income levels. Moreover, there were variations in preferences in highly populated Emirates (e.g., Dubai and Abu Dhabi) compared to Emirates with lower populations (e.g., Ras Al Khaimah and Umm al Quwain), confirming that much more emphasis is required to promote EVs in rural areas. When comparing multiple income groups to determine the impact of different factors, the ANOVA confirmed the prevailing patterns evident in the associations.
“…Peksen [20] reviewed the potential of new energy vehicles and hydrogen technology. Betancourt-Torcat et al [21] proposed a system of integrated electric vehicle network planning. Sinha-Brophy [22] applied the life-cycle assessment to renewable hydrogen for fuel cell passenger vehicles.…”
Alternative fuel vehicles (AFVs) offer opportunities to lower fuel costs as well as to reduce greenhouse gas emissions, and, therefore, they are a feasible option for customers in the market. Due to technological advancements, decisions about suitable alternative fuel vehicles are a challenging problem for fleet operators. This paper aims to introduce a multi-attribute decision-analysis framework to rank and select the “alternative fuel vehicles (AFVs)” for a private home healthcare service provider in Chandigarh, India. The selection of AFVs can be treated as a decision-making problem, because of the presence of various qualitative and quantitative attributes. Thus, the current work introduces an integrated decision-making framework based on intuitionistic fuzzy-“method based on the removal effects of criteria (MEREC)”, “ranking sum (RS)”, and the “double normalization-based multi-aggregation (DNMA)” framework for assessing the AFVs. The combination of MEREC and RS is applied to assess the objective and subjective weighting values of various parameters for AFV assessment. The DNMA approach is utilized to prioritize the different AFVs over various significant parameters. According to the outcomes, the most significant parameters for AFV assessment are social benefits, fueling/charging infrastructure, and financial incentives, respectively. In this context, globally existing AFVs for the sustainable transportation sector are identified, and then prioritized against fifteen different criteria relevant to the environmental, economic, technological, social, and political aspects of sustainability. It is distinguished that electric vehicles (G2), hybrid electric vehicles (G1), and hydrogen vehicles (G3) achieve higher overall performance compared to the other technologies available in India. The assessment outcomes prove that electric vehicles can serve as a valuable alternative for decreasing carbon emissions and negative effects on the environment. This technology contributes to transportation sector development and job creation in less developed areas of the country. Moreover, a comparison with existing studies and a sensitivity investigation are conferred to reveal the robustness and stability of the developed framework.
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