Electric Vehicle Adoption in Jordan: Analyzing Consumer Motivations and Barriers

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Alhamad, Hanan Taleb, Hanan Hashaykeh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7520351/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Dec, 2025 Read the published version in Discover Sustainability → Version 1 posted 13 You are reading this latest preprint version Abstract This study investigates the factors influencing electric vehicle (EV) adoption in Jordan, a small energy-importing country with a growing used EV market and strong renewable energy potential. A mixed-methods approach combined a quantitative survey (n = 135) with expert interviews to identify key drivers and barriers. Results show that technological factors, such as perceived reliability, driving range, and charging infrastructure, are the strongest predictors of adoption interest. Social influences, including peer opinions and widespread misconceptions, also shape consumer attitudes. Environmental benefits and cost savings matter but are often outweighed by practical technological and social considerations. Expert insights reinforced the need for stable incentives, reliable infrastructure, and public awareness campaigns to counter misinformation. Jordan’s newly approved gradual tax increases on EVs could challenge affordability if not balanced with clear policies, targeted incentives, and charging network improvements. The findings provide practical guidance for policymakers and industry stakeholders to design integrated strategies that address economic, technological, and social dimensions together, supporting sustainable transport growth in Jordan and similar emerging markets. Electric Vehicles EV Adoption EV Barriers Charging Infrastructure Sustainable Transport Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction The global adoption of electric vehicles (EVs) has grown rapidly in recent years, driven largely by strong market developments in China, the United States, and Europe. In 2023, global EV sales reached nearly 14 million units, representing around 18% of total car sales and marking a 35% increase from the previous year (IEA, 2024). This upward trend is projected to continue, with the global EV market expected to reach revenues of USD 786 billion in 2024 and exceed USD 1 trillion by 2029 (Statista, 2024). While established markets continue to lead, emerging economies are becoming increasingly important contributors to the worldwide transition towards low-emission road transport. Jordan, a small developing country in the Middle East, offers a unique context for examining EV adoption patterns. With a population of approximately 11.3 million and a heavy reliance on imported oil, the country faces persistent energy security challenges (Kiwan and Al-Gharibeh, 2020; World Bank, 2023). To address this, the Jordanian government has promoted EV uptake as part of its broader strategy to diversify the energy mix and reduce fuel import dependency (Mahadin, 2018; Abu-Rumman et al., 2020). The increasing installation of residential solar photovoltaic (PV) systems also provides opportunities for EV charging that power Jordan’s abundant solar resources (Al-Habaibeh et al., 2023). Unlike neighbouring oil-rich states, Jordan’s EV market is shaped by distinctive factors such as a thriving second-hand vehicle market, evolving charging infrastructure, and significant policy incentives including customs duty reductions and tax exemptions (Jordan Times, 2024; Shalamai, 2020). However, despite steady growth, with over 22,000 EVs cleared in the first half of 2024 (Jordan Times, 2024), barriers such as misconceptions about EV technology, limited public charging points, and social perceptions still affect adoption. While much of the existing literature has examined EV adoption in larger or more mature markets, there is limited empirical research that explores the unique drivers and barriers in smaller, energy-importing countries like Jordan. This case study therefore aims to fill this gap by integrating quantitative survey data with qualitative insights from expert interviews, providing a comprehensive understanding of the economic, environmental, technological, and social factors influencing consumer decisions. By highlighting Jordan’s specific challenges and opportunities, this study provides policy insights that may guide other emerging economies with comparable energy and transport contexts. 2. Literature Review Electric vehicle (EV) adoption has attracted considerable global attention in recent years, with multiple studies highlighting how socio-economic, environmental, technological, and psychological factors interact to shape consumer decisions. International research has shown that factors such as fuel prices, maintenance costs, environmental awareness, government incentives, home ownership, and the availability of public charging infrastructure all play a critical role (He et al., 2022; Chu et al., 2019; Jenn et al., 2013). Policies such as direct rebates, tax credits, toll exemptions, and access to bus or HOV lanes have been found to significantly boost adoption in countries like China (Lichtenthaeler and Kasperk, 2017), Norway, and the United States (Bjerkan et al., 2016; Cui et al., 2021; Anastasiadou and Gavanas, 2022). Despite these policy successes, studies have also shown mixed evidence regarding the long-term effectiveness of incentives, with local energy costs and charging infrastructure availability remaining persistent barriers in countries such as Brazil and India (Ruoso and Ribeiro, 2022; Goel et al., 2021). While much of the global literature focuses on mature markets, recent studies have increasingly examined EV adoption in emerging economies, including the Arab region. Research from Saudi Arabia, Lebanon, and the UAE identifies key drivers such as energy efficiency awareness, commute distance, and social or symbolic value attached to owning an EV (Bridi et al., 2022; Jreige et al., 2021). However, inadequate charging infrastructure, high upfront costs, and limited awareness continue to pose significant barriers in many MENA countries (Ramadan and Othman, 2023; Ottesen and Banna, 2021). Several studies group the factors influencing EV adoption into four broad categories: Economic Factors: Affordability, operating cost savings, fuel prices, and government financial incentives are consistently identified as major drivers (Fluchs and Kasperk, 2017; Mahadin, 2018). In Jordan, lower customs duties and tax exemptions make EVs more financially attractive than internal combustion engine (ICE) vehicles and hybrids. Environmental Factors: Growing awareness of climate change and air pollution, coupled with zero-emission benefits, enhances the appeal of EVs, particularly in urban areas (Salah et al., 2023; Klabi and Binzafrah, 2023). Technological and Infrastructure Factors: The availability of charging stations (Albatayneh, 2024), ease of home charging, and perceived technological performance are widely acknowledged as critical (Mpoi et al., 2023; He et al., 2022). Social and Cultural Factors: Social influence, symbolic values, and community trends can affect willingness to adopt EVs, as cars often represent more than just transportation in the region (Bhattacharyya and Thakre, 2021; Othman et al., 2022). In Jordan, the EV market presents distinctive features that set it apart from neighbouring oil-rich states. The country’s reliance on imported energy, limited local reserves, and high fuel prices have made the government’s push for EV adoption a strategic priority for energy security (Kiwan and Al-Gharibeh, 2020). The affordability of used EVs, mainly imported from China and Europe, combined with reduced customs duties, makes them accessible to a broader segment of consumers (Jordan Times, 2024). The widespread adoption of solar PV systems provides an additional incentive, allowing many EV owners to charge vehicles at home using renewable energy (Al-Habaibeh et al., 2023). However, challenges such as limited charging infrastructure, market volatility due to rumors and misinformation, and cultural perceptions tied to social status persist (Shalamai, 2020; Addustour, 2024). While existing studies provide valuable insights into global and regional EV adoption trends, there is limited empirical evidence examining how economic, technological, environmental, and cultural factors interact within Jordan’s unique context as an energy-importing country with a large used EV market and significant solar potential. This study addresses this gap by combining a quantitative consumer survey with qualitative expert interviews to identify which factors are most influential in the Jordanian context. The findings help clarify priorities for policymakers and stakeholders, supporting informed decisions on targeted incentives, tax policies, strategic planning, and infrastructure development that can accelerate sustainable transport adoption in Jordan and comparable markets. 3. Methodology Understanding the factors that influence electric vehicle (EV) adoption in Jordan requires an approach that captures both measurable consumer trends and the deeper market context. This section outlines the study’s mixed-methods design, the rationale behind it, the data collection processes for the survey and expert interviews, and the analytical techniques applied. 3.1 Research Design and Rationale This study employs a mixed-methods research design, combining quantitative and qualitative approaches to provide a comprehensive understanding of the drivers and barriers to EV adoption in Jordan. A mixed-methods approach was chosen to integrate measurable consumer responses with expert insights, offering a nuanced perspective that aligns with established technology adoption frameworks, such as the Technology Acceptance Model (TAM) to consider economic, environmental, technological, and social dimensions. The Technology Acceptance Model (TAM) provides a theoretical basis by explaining how consumers’ perceptions of usefulness and ease of use influence their attitudes and intentions to adopt new technologies, such as electric vehicles. 3.2 Survey Design and Data Collection A structured questionnaire was developed to investigate key determinants of EV adoption. The survey was organized into five sections: (1) personal and demographic information; (2) economic factors, including vehicle cost, operating expenses, and government incentives; (3) environmental factors, focusing on sustainability awareness and perceived air quality benefits; (4) technological and practicality factors, covering perceptions of vehicle performance, charging convenience, and reliability; and (5) social and cultural influences, such as peer opinions, social status, and the impact of rumors or misconceptions. Respondents were recruited through social media platforms, personal networks, and local EV owner groups to ensure diverse representation in age, gender, education, vehicle ownership, and commuting patterns. In total, 135 valid responses were collected. The study employed a non-probability convenience sampling method, which is common in exploratory case studies aiming to capture context-specific insights. The survey instrument and distribution procedures were reviewed and approved by the Research Ethics Committee at The British University in Dubai. This confirms that the survey met ethical standards for research involving human participants, including voluntary informed consent, confidentiality, and the right to withdraw. The survey was assessed as low risk, and no personally identifying information was collected to ensure participant anonymity. 3.3 Expert Interviews To complement the survey data, a semi-structured interview was conducted with an experienced EV consultant and sales professional in Jordan. The interview focused on market dynamics, consumer attitudes, pricing and maintenance perceptions, competitive positioning of EVs versus traditional vehicles, and the influence of government policies and incentives. Additional themes included the growth of charging infrastructure, technological advantages, environmental benefits, and social and cultural factors shaping adoption trends. Similarly, the semi-structured expert interviews were covered under the same ethical approval by the British University in Dubai. Experts participated voluntarily, with full informed consent for their names, affiliations, and professional insights to be cited in this study. Interview data were handled responsibly, securely stored, and used solely for the stated research purposes in accordance with the university’s research ethics guidelines. 3.4 Data Analysis Quantitative survey data were analyzed using MATLAB to perform descriptive and inferential statistical analyses. This included correlation analysis to identify relationships between variables, Principal Component Analysis (PCA) to reduce dimensionality and highlight underlying factor structures, and ANOVA tests to assess differences across demographic groups. Qualitative interview responses were thematically coded and analyzed using MATLAB to identify patterns and provide context that enriches the interpretation of the quantitative results. The study adhered to ethical research standards, with participants fully informed of the study’s purpose and their confidentiality rights. 4. Results and Discussion This study presents findings from both a survey and expert interviews regarding EV adoption in Jordan. The survey targeted a diverse demographic sample of drivers across various vehicle categories, gathering responses from 135 participants through social media, personal outreach, and direct connections. Detailed statistical analyses were performed using MATLAB to process the survey data, employing techniques such as regression analysis and Pearson correlation to evaluate the impact of demographic and psychographic factors on EV adoption. Key metrics were visualized through graphs and correlation matrices to identify significant trends and relationships. Additionally, expert interviews provided qualitative insights, with thematic analysis used to distill key opinions and experiences from industry specialists. Using MATLAB, the interview responses were categorized according to demographics, adoption interests, and barriers to adoption; specific themes were identified using relevant keywords, then encoded into binary matrices to track the occurrence of each theme across responses, supporting structured analysis and clear visualizations. 4.1 Survey results The survey was distributed in Jordan among drivers of various car categories, including internal combustion engine (ICE) vehicles, hybrids, and electric vehicles (EVs). A total of 135 respondents participated in the survey, which was conducted using social media platforms, personal connections, and direct outreach methods. Analysis of personal demographics in the dataset reveals several key descriptive statistics. The mean age of respondents is 41.07 years, with a standard deviation of 7.34 years, indicating a relatively mature sample. The median age is 40 years, suggesting that half of the participants are younger than this age. The ages of respondents range from a minimum of 25 years to a maximum of 65 years, highlighting a diverse age distribution within the sample. In terms of gender representation, the mean value is 0.51, indicating a slight majority of male respondents in the dataset, where 0 represents Female and 1 represents Male. The standard deviation of 0.50 suggests a balanced distribution between the genders, with a median gender value of 1. This indicates that a significant portion of the participants identified as male. Regarding educational attainment, the mean educational level of respondents is 2.52, with a standard deviation of 0.76. This statistic implies that most participants have completed a bachelor's degree, which is coded as 2. The median educational level is also 2, with values ranging from a minimum of 1 (high school) to a maximum of 4 (PhD), showcasing a diverse educational background among respondents. The analysis of commute distance reveals a mean of 58.12 km, accompanied by a substantial standard deviation of 44.90 km. The median commute distance is reported at 30 km, indicating that while many respondents have shorter commutes, some commute distances are considerably longer. The range of commute distances extends from a minimum of 30 km to a maximum of 250 km, further illustrating the diversity of commuting patterns within the sample. Figure 1 shows the personal demographics of the survey sample. In this study, Principal Component Analysis (PCA) was employed to derive a composite score that defines EV adoption interest based on multiple influencing factors. PCA is a statistical technique used to reduce the dimensionality of a dataset while retaining as much variance as possible, allowing identification of the most significant factors that contribute to consumer attitudes toward EVs. The initial step involved standardizing the dataset, ensuring that each variable is on a similar scale to prevent any single variable from disproportionately influencing the results. The original Likert scale questions related to economic, environmental, technological, and social factors were then analyzed. The four key factors identified in the study are defined as follows: Economic Factors (EF): This includes questions related to financial incentives, operating costs, and the affordability of electric vehicles. Environmental Factors (EnF): This encompasses beliefs about EVs' impacts on air quality, carbon emissions, and overall sustainability. Technological Factors (TF): This refers to perceptions regarding the reliability of EV technology, charging infrastructure, and vehicle performance. Social Factors (SF): This includes the influence of social status, peer opinions, rumors and misconceptions, and community perceptions related to EV ownership. For each of these factors, a set of Likert scale questions was posed to the respondents. The scores from these questions were used to compute the principal components through PCA. Table 1 shows the Survey Questions Categorized by Economic, Environmental, Technological, and Social Factors. To define the EV adoption interest based on PCA, we formulated the following equation: $$\:\varvec{E}\varvec{V}\:\varvec{A}\varvec{d}\varvec{o}\varvec{p}\varvec{t}\varvec{i}\varvec{o}\varvec{n}\:\varvec{I}\varvec{n}\varvec{t}\varvec{e}\varvec{r}\varvec{e}\varvec{s}\varvec{t}=\varvec{P}{\varvec{C}}_{1}={\varvec{\omega\:}}_{\varvec{E}\varvec{F}}\varvec{E}\varvec{F}+{\varvec{\omega\:}}_{\varvec{E}\varvec{n}\varvec{F}}\varvec{E}\varvec{n}\varvec{F}+{\varvec{\omega\:}}_{\varvec{T}\varvec{F}}\varvec{T}\varvec{F}+{\varvec{\omega\:}}_{\varvec{S}\varvec{F}}\varvec{S}\varvec{F}$$ 1 Where: EV Adoption Interest is the composite score representing the overall inclination to adopt electric vehicles. PC 1 ​ is the first principal component derived from PCA, reflecting the most variance in the data. EF , EnF , TF , and SF represent the aggregated scores of economic, environmental, technological, and social factors, respectively. The weights \(\:{\omega\:}_{EF}\) ​, \(\:{\omega\:}_{EnF}\) ​, ​, \(\:{\omega\:}_{TF}\) ​, and \(\:{\omega\:}_{SF}\) ​, are the factor loadings assigned by PCA, indicating the relative contribution of each factor Table 1 Survey questions categorized by economic, environmental, technological, and social factors Factor Likert Scale Question Economic Factors (EF) 1. Electric vehicles have appealing prices compared to ICE and Hybrid vehicles. 2. Electric vehicles have lower operating costs compared to ICE and Hybrid vehicles. 3. Electric vehicles benefit from lower maintenance costs compared to ICE and Hybrid vehicles. 4. Government incentives make electric vehicles more affordable. 5. I believe the depreciation rate of electric vehicles is comparable to that of ICE and Hybrid vehicles. 6. I believe the cost of replacing an electric vehicle battery is manageable. Environmental Factors (EnF) 1. Electric vehicles help reduce air pollution in Jordan. 2. Using electric vehicles helps reduce the carbon footprint globally. 3. I believe electric vehicles are more energy-efficient compared to ICE and Hybrid vehicles. 4. I believe electric vehicles contribute more to environmental sustainability compared to ICE and Hybrid. Technological Factors (TF) 1. Electric vehicles offer better performance and technology compared to ICE and Hybrid vehicles. 2. There are enough charging stations available in Jordan. 3. Charging an electric vehicle is convenient, accessible, and fast. 4. I believe the technology of electric vehicles is reliable. 5. I am satisfied with the driving range that most electric vehicles currently offer. 6. I am confident in the safety of electric vehicle components, including batteries and motors. Social Factors (SF) 1. Owning an electric vehicle is seen as a positive social status symbol. 2. Owning an electric vehicle reflects a commitment to environmental responsibility. 3. My decision to purchase an electric vehicle is influenced by the opinions of my friends and family. 4. Seeing more electric vehicles in my community encourages me to consider purchasing one. 5. I am not influenced by rumors and misconceptions about electric vehicles. The analysis of factors influencing EV adoption interest revealed several significant correlations, as summarized in Table 2 . Each factor demonstrated a different level of association with consumers’ inclination to adopt EVs. Technological factors showed the strongest positive correlation (r = 0.760), indicating that perceptions of technology reliability, performance, and charging infrastructure play a critical role in adoption decisions. This highlights the importance of continued advancements and public trust in EV technology. Social factors also showed a strong positive correlation (r = 0.663), underscoring the influence of peer opinions, community norms, and societal attitudes on EV uptake. This suggests that visible social acceptance and word-of-mouth can meaningfully shape consumer behavior. Environmental factors exhibited a correlation coefficient of 0.622 (p = 0.000), showing that awareness of environmental benefits, such as reduced air pollution and lower greenhouse gas emissions, significantly enhances consumer interest in EVs. Economic factors had a correlation of 0.598 (p = 0.000), indicating that financial incentives, operating cost savings, and perceived affordability remain important motivators for potential buyers. All four factors were statistically significant at p < 0.05, providing strong evidence that they collectively influence EV adoption interest in Jordan. The low p-values (< 0.05) confirm that these relationships are unlikely to have occurred by chance, reinforcing the robustness of the findings. Table 2 Correlations of factors influencing EV adoption interest Factor Pearson Correlation P-Value (sig) Interpretation Economical 0.598 0.00 Significant positive correlation, indicating strong influence of economic factors on EV adoption. Environmental 0.622 0.00 Significant positive correlation, showing that environmental concerns significantly impact EV adoption. Technology 0.760 0.00 Strongest correlation, suggesting technological perceptions are crucial for consumer interest. Social 0.663 0.00 Strong correlation, highlighting the importance of social influences on EV adoption decisions. Correlation is significant at the 0.05 level The analysis of factors influencing EV adoption indicate that while each factor independently affects adoption interest, their combined influence illustrates how economic, environmental, technological, and social dimensions interact to shape the broader EV market landscape. This underlines the need for integrated strategies that address all four dimensions to build confidence and accelerate market growth. Additional analysis of individual traits is shown in Table 3 . The results revealed that age showed only a weak and statistically insignificant relationship with adoption interest (r = 0.119, p = 0.167). Gender was the only demographic factor with a significant effect (r = − 0.183, p = 0.033), suggesting that female respondents may show slightly more interest in EVs than males. Education level, commute distance, and primary vehicle use were not significantly correlated with EV adoption interest. These findings reinforce that broader economic, environmental, technological, and social factors are likely to be more influential than personal demographics alone in shaping EV adoption decisions in the Jordanian context. Table 3 Correlations between individual traits and EV adoption interest Factor Pearson Correlation p-Value (sig) * Interpretation Age 0.119 0.167 A weak positive correlation suggests older respondents may have slightly more interest in EVs, but it is not statistically significant at the 0.05 level. Gender -0.183 0.033 A negative correlation indicates that male respondents show less interest in EVs compared to females, with a statistically significant p-value. Education Level -0.056 0.518 No meaningful correlation; education level does not significantly influence interest in adopting EVs. Commute Distance 0.009 0.911 A weak positive correlation indicates commute distance does not significantly influence EV adoption interest. Primary Use of Vehicle 0.049 0.571 No significant correlation suggests that primary use of the vehicle does not impact interest in EV adoption. * Correlation is significant at the 0.05 level To further explore whether demographic and usage-related characteristics affect EV adoption interest, an Analysis of Variance (ANOVA) was conducted. This test compared group means across variables such as governorate, type of previous vehicle, gender, education level, age, and commute distance. Table 4 presents the ANOVA results. Among all variables tested, only gender showed a statistically significant difference (p = 0.033), suggesting that gender may influence adoption interest. Other demographic factors did not demonstrate significant effects, reinforcing the finding that broader economic, environmental, technological, and social factors are likely to play a more decisive role. These results highlight the importance of developing adoption strategies that focus less on personal demographics and more on addressing practical, economic, and societal influences that shape consumer attitudes toward EVs. Table 4 Analysis of Variance (ANOVA) results for factors Influencing electric vehicle adoption interest Source SS df MS F Prob > F Interpretation Governorate Groups 4.2319 6 0.7053 1.5811 0.1578 No significant difference in EV adoption interest across governorates. “Type of Previous Vehicle” Groups 0.9114 2 0.4557 1.0091 0.3675 The type of previous vehicle does not significantly influence EV adoption interest. Gender Groups 2.0586 1 2.0586 4.6191 0.0334 A significant difference exists in EV adoption interest based on gender, suggesting gender plays a role. Education Level Groups 1.7682 3 0.5894 1.2851 0.2823 Education level does not significantly affect EV adoption interest. Age Groups 1.4578 3 0.4859 1.0631 0.3671 Age groups do not show a significant impact on EV adoption interest. “Commute Distance” Groups 1.4399 3 0.4800 1.0426 0.3761 Commute distance groups do not significantly influence EV adoption interest. 4.2 Expert Interviews results In addition to the survey, a series of semi-structured expert interviews was conducted to gain practical and strategic perspectives on EV adoption in Jordan and the wider Middle East. The expert panel included industry professionals and academics, each contributing unique insights into market trends, consumer behavior, policy issues, and adoption barriers (Table 5 ). Table 5 Expert interviewee panel for EV market insights Sr. Name Company Role Years of Experience 1 Eng. Abdel AlRahman AlQademat BYD-Jordan Sales Consultant 4 2 Professor Bassam Abu-Hijleh British University in Dubai Dean of Faculty of Engineering & IT + 25 3 Allen Bedrossian Mitsubishi Middle East General Manager Marketing and Sales 10 4 Alaa Tayeb Nissan, and Stellantis Middle East Brand Manager - Middle East 10 5 Bisher Khalil Khalil & Ali Car Trading Sales and Marketing Specialist 6 The panel included sales consultants, brand managers, and an academic dean specializing in sustainable transportation. Collectively, they emphasized four main themes shaping EV adoption: economic considerations, technological readiness, social factors, and environmental influences. From the sales perspective, affordable prices for used EVs, especially from China, and seasonal purchase patterns were highlighted as key drivers. However, misconceptions about battery life, driving range, and maintenance costs continue to limit consumer confidence. Marketing and brand managers underscored the importance of leveraging social networks and word-of-mouth, as peer influence and visible adoption trends encourage wider uptake. The academic perspective stressed the need for consistent government incentives, transparent tax structures, and large-scale investment in charging infrastructure to reduce range anxiety. Experts agreed that rumors and misinformation significantly distort market perceptions, driving price volatility and consumer hesitancy. This highlights the critical role of awareness campaigns and reliable information channels to counteract misconceptions. A structured thematic coding and correlation analysis was conducted on the interview transcripts to quantify the frequency and relationships among the key topics discussed. Figure 2 and Fig. 3 illustrate the frequency with which specific consumer traits and segments were discussed by the interviewed experts as critical for understanding EV adoption in Jordan. Rather than representing survey demographics, the frequencies reflect how often these themes appeared in qualitative interviews. For example, ‘Age’ was most frequently mentioned as a decisive factor, with experts highlighting younger buyers as tech-savvy adopters and older buyers as economically motivated adopters. ‘Commute distance’, ‘use of vehicle’, and ‘tech-enthusiasts’ were also emphasized as segments where tailored incentives and communication could enhance adoption rates. Figure 4 and Fig. 5 present the aggregated themes from the expert interviews regarding the primary motivators for EV adoption. Figure 4 and Fig. 5 , along with the thematic analysis confirmed that economic factors, vehicle price, operating costs, and financial incentives, are the strongest motivators driving EV purchases in Jordan. Technological reliability and accessible charging infrastructure also remain critical to building consumer confidence, while social and environmental motivations tend to overlap, indicating that buyers who care about sustainability are often influenced by positive peer perceptions and community norms. Interestingly, the correlation matrix shows that environmental concerns still have only a weak link to economic or technological priorities, suggesting that for many consumers, practical cost savings still outweigh purely environmental ideals. These insights are especially relevant given the Jordanian government’s newly announced EV tax policy (Addustour,2024). The updated measures include both temporary incentives and longer-term adjustments: The special tax rates for new EV imports will be restructured: vehicles with a customs value of 10,000–25,000 JD will see their special tax rate reduced from 40–20%, while higher-end vehicles above 25,000 JD will drop from 55–27.5%. The rate for lower-value EVs under 10,000 JD remains unchanged at 10%. This carefully phased approach aims to protect dealers, clear existing inventory, and keep EVs financially accessible, especially in the affordable segment that matters most for wider adoption. The experts highlighted that clear, predictable policies like these, combined with sustained investment in charging networks and public awareness campaigns, are critical to countering rumors and misconceptions that remain barriers to EV uptake. For policymakers and industry leaders, this study reinforces the need for an integrated approach: aligning fiscal measures, infrastructure readiness, and public trust to sustain growth in Jordan’s EV market without risking sudden drops in demand. Figure 6 and Fig. 7 highlight the main barriers to EV adoption as reported by experts. High taxes, insufficient charging infrastructure, and persistent rumors emerged as the top obstacles. Notably, misconceptions were strongly correlated with range anxiety, illustrating how misinformation can amplify practical concerns such as limited driving range. This connection suggests that addressing myths and rumors could directly reduce some of the practical anxieties that discourage potential buyers. Figure 8 presents the comprehensive correlation matrix combining the main themes identified across demographics, adoption motivators, and barriers. This holistic view shows how various factors interact to shape EV adoption dynamics in Jordan. One of the most notable findings is the strong positive correlation (0.70) between charging infrastructure and technological factors, suggesting that perceptions of EV technology reliability and performance are closely tied to the availability and convenience of charging networks. This reinforces the practical point that advancements in EV technology must go hand-in-hand with robust infrastructure to strengthen consumer confidence. Another clear relationship is between environmental factors and social factors (0.42), implying that sustainability concerns often align with social norms and peer influence. This highlights the potential of community-driven awareness campaigns to amplify environmental motivations through social channels. The matrix also reveals that misconceptions have significant links with limited range (0.62) and rumors (0.45). This indicates that misinformation and rumors tend to amplify range anxiety, creating a reinforcing cycle that can hinder adoption. Addressing these misconceptions through targeted education could therefore reduce both perceived and practical barriers. Interestingly, high taxes correlate moderately with the use of vehicle variable (0.47). This suggests that future tax policies could disproportionately impact consumers using vehicles for specific purposes, such as delivery or ride-sharing, which tend to have higher running costs. This points to the need for carefully designed fiscal policies that balance revenue with encouraging EV uptake in high-usage sectors. Demographic links are also evident: for instance, age shows a moderate positive correlation with tech enthusiasts (0.40), indicating that younger segments may be more willing to adopt new technologies like EVs, especially when combined with modern features and innovation. Finally, the low or negative correlations between environmental and economic factors (0.12) and technological factors (-0.23) underscore that while environmental consciousness is important, practical cost savings and technological readiness remain the dominant drivers for many consumers. Overall, the matrix illustrates that boosting EV adoption will require coordinated strategies: expanding charging infrastructure, addressing persistent misconceptions, designing effective tax incentives, and leveraging social and environmental messaging. This interconnected view emphasizes that barriers and motivators do not operate in isolation but interact in complex ways that must be addressed holistically. 5. Conclusions This study provides a comprehensive, mixed-methods assessment of the factors influencing electric vehicle (EV) adoption in Jordan, combining a quantitative consumer survey with qualitative expert interviews. By analyzing both perspectives, the research captures the multifaceted drivers and barriers shaping the country’s evolving EV market. The survey of 135 respondents, supported by thematic analysis and statistical techniques such as PCA, correlation, and ANOVA, revealed that while environmental sustainability and cost savings are important motivators, practical considerations, especially technological reliability, availability of charging infrastructure, and social perceptions, have a stronger influence on adoption decisions. Insights from five industry experts further emphasized the need for consistent government incentives, consumer education, and infrastructure expansion to address persistent misconceptions and build trust in EVs. This is particularly timely given Jordan’s recently approved phased increases in special taxes on EVs. Without balanced policies, such as targeted tax incentives for affordable models and investment in accessible charging networks, these tax changes could undermine progress by making EVs less financially attractive. Practically, the study offers evidence-based guidance for policymakers designing fiscal measures and infrastructure strategies to sustain adoption momentum. For industry stakeholders, understanding how local community norms and peer influence shape purchase behavior can inform tailored marketing, after-sales support, and public awareness campaigns. However, It is important to acknowledge that the study used a convenience-based, non-probability sample, which may limit its generalizability. Nonetheless, the combination of robust statistical methods and expert validation ensures that the findings are contextually relevant for Jordan and comparable emerging markets. Future research should build on this foundation by tracking the real-world impacts of the new tax regime and monitoring how improved infrastructure and public awareness influence adoption rates over time. Longitudinal studies and broader representative sampling would further enhance understanding and help refine incentives and outreach strategies to support Jordan’s transition to sustainable mobility. Declarations Ethics approval and consent to participate The survey instrument and distribution procedures were reviewed and approved by the Research Ethics Committee at The British University in Dubai; participation was voluntary with informed consent, confidentiality protections, and no collection of personally identifying information. Expert interviews were covered under the same approval, with informed consent for citing names and affiliations. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests, financial or non-financial, that could be perceived as influencing the content or conclusions of this paper Funding No funding was received for this study. Author Contribution I.M.H. visualized the study, developed the methodology, performed data analysis, and wrote both the original draft and the final manuscript. H.T. supervised the study, contributed to validation and methodology, critically reviewed the manuscript, and helped write the final manuscript. H.H. designed the survey, collected data, conducted interviews, critically reviewed the final manuscript, and helped write the final manuscript. All authors read and approved the final manuscript. Acknowledgement We gratefully acknowledge the experts who shared their time and insights during the interviews: Eng. Abdel AlRahman AlQademat (Sales Consultant, BYD-Jordan), Prof. Bassam Abu-Hijleh (Dean, Faculty of Engineering & IT, British University in Dubai), Allen Bedrossian (General Manager, Marketing & Sales, Mitsubishi Middle East), Alaa Tayeb (Brand Manager, Middle East, Nissan and Stellantis Middle East), and Bisher Khalil (Sales & Marketing Specialist, Khalil & Ali Car Trading). Their perspectives on market dynamics, consumer behavior, and policy conditions in Jordan substantially informed our analysis. 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(2023) ‘Solar energy in Jordan: Investigating challenges and opportunities of using domestic solar energy systems’, World Development Sustainability, 3, p. 100077. doi:10.1016/j.wds.2023.100077. Anastasiadou, K. and Gavanas, N. (2022) ‘State-of-the-art review of the key factors affecting electric vehicle adoption by consumers’, Energies, 15(24), p. 9409. doi:10.3390/en15249409. Bhattacharyya, S.S. and Thakre, S. (2021) ‘Exploring the factors influencing electric vehicle adoption: An empirical investigation in the emerging economy context of India’, Foresight, 23(3), pp. 311–326. doi:10.1108/FS-04-2020-0037. Bjerkan, K., Nørbech, T. and Nordtømme, M. (2016) ‘Incentives for promoting battery electric vehicle (BEV) adoption in Norway’, Transportation Research Part D: Transport and Environment, 43, pp. 169–180. doi:10.1016/j.trd.2015.12.002. Chu, W., Im, M., Song, M.R. and Park, J. (2019) ‘Psychological and behavioral factors affecting electric vehicle adoption and satisfaction: A comparative study of early adopters in China and Korea’, Transportation Research Part D: Transport and Environment, 76, pp. 1–18. doi:10.1016/j.trd.2019.09.009. Cui, L., Wang, Y., Chen, W., Wen, W. and Han, M.S. (2021) ‘Predicting determinants of consumers’ purchase motivation for electric vehicles: An application of Maslow’s hierarchy of needs model’, Energy Policy, 151, p. 112167. doi:10.1016/j.enpol.2021.112167. Fluchs, S. and Kasperk, G., 2017. The influence of government incentives on electric vehicle adoption: Cross-national comparison (No. 57-2017). MAGKS Joint Discussion Paper Series in Economics. He, S.Y., Sun, K.K. and Luo, S. (2022) ‘Factors affecting electric vehicle adoption intention: The impact of objective, perceived, and prospective charger accessibility’, Journal of Transport and Land Use, 15(1), pp. 779–801. International Energy Agency (IEA) (2024) Global EV Outlook 2024: Trends in electric cars. Available at: https://www.iea.org/reports/global-ev-outlook-2024/trends-in-electric-cars Jordan Times (2024) ‘Electric vehicles clearances up 12% in first half of 2024’. Jordan Times. Available at: https://jordantimes.com/news/local/electric-vehicles-clearances-12-first-half-2024 Kiwan, S. and Al-Gharibeh, E. (2020) ‘Jordan toward a 100% renewable electricity system’, Renewable Energy, 147, pp. 423–436. doi:10.1016/j.renene.2019.09.004. Lichtenthaeler, S. and Kasperk, G. (2017) ‘The influence of government incentives on electric vehicle adoption: Cross-national comparison’. Mahadin, B. (2018) ‘Factors affecting customer switching behavior towards hybrid electrical vehicles (HEVs) from a customer perspective in Jordan’, European Journal of Marketing and Economics, 1(3), pp. 53–65. doi:10.26417/ejme.v1i3.p53-65. Ruoso, A.C. and Ribeiro, J.L.D. (2022) ‘An assessment of barriers and solutions for the deployment of electric vehicles in the Brazilian market’, Transport Policy, 127, pp. 218–229. doi:10.1016/j.tranpol.2022.09.004. Salah, A.A., Shalby, M.M. and Ismail, F.B. (2023) ‘The status and potential of renewable energy development in Jordan: Exploring challenges and opportunities’, Sustainability: Science, Practice and Policy, 19(1), p. 2212517. doi:10.1080/15487733.2023.2212517. Shalamai, O. (2020) ‘Electric cars market development in Jordan and Ukraine (Comparative analysis of Ukrainian and Jordanian experiences)’, Business, Economics, Sustainability, Leadership and Innovation, pp. 8–16. doi:10.37659/2663-5070-2020-5-8-16. Shalalfeh, L., AlShalalfeh, A., Alkaradsheh, K., Alhamarneh, M. and Bashaireh, A. (2021) ‘Electric vehicles in Jordan: Challenges and limitations’, Sustainability, 13(6), p. 3199. doi:10.3390/su13063199. Statista (2024) Electric Vehicles: Worldwide Market Forecast. Available at: https://www.statista.com/outlook/mmo/electric-vehicles/worldwide Wilson Center (2023) Jordan’s government adopts women economic empowerment plan. Wilson Center. Available at: https://www.wilsoncenter.org/blog-post/jordans-government-adopts-women-economic-empowerment-plan Xinhua (2023) ‘Electric vehicles appeal to more Jordanians for lower driving costs’. Xinhua. Available at: https://english.news.cn/20230110/ Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Dec, 2025 Read the published version in Discover Sustainability → Version 1 posted Editorial decision: Revision requested 03 Nov, 2025 Reviews received at journal 24 Oct, 2025 Reviewers agreed at journal 08 Oct, 2025 Reviewers agreed at journal 07 Oct, 2025 Reviewers agreed at journal 06 Oct, 2025 Reviews received at journal 03 Oct, 2025 Reviewers agreed at journal 03 Oct, 2025 Reviewers agreed at journal 03 Oct, 2025 Reviewers invited by journal 03 Oct, 2025 Editor invited by journal 01 Oct, 2025 Editor assigned by journal 10 Sep, 2025 Submission checks completed at journal 10 Sep, 2025 First submitted to journal 02 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7520351","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":534293594,"identity":"44ec274c-b74a-47be-9f87-32654c240ad7","order_by":0,"name":"Issah M. 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2","display":"","copyAsset":false,"role":"figure","size":6114,"visible":true,"origin":"","legend":"\u003cp\u003eDemographics of potential buyers for EVs in Jordan\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7520351/v1/4a84c18f759192aa13754a25.png"},{"id":94462290,"identity":"60fb9f8d-cb8b-457c-89d6-eacd2f1c55d9","added_by":"auto","created_at":"2025-10-27 15:01:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":10748,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation matrix for demographics of potential buyers of EVs in Jordan\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7520351/v1/c0c269f282c7ed7fd351bda9.png"},{"id":94462273,"identity":"85e0c3e5-0e9e-4fa8-8400-82022cbf6ab9","added_by":"auto","created_at":"2025-10-27 15:01:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":6250,"visible":true,"origin":"","legend":"\u003cp\u003eAdoption factors for potential buyers of EVs in Jordan\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7520351/v1/d899076229974f841920014e.png"},{"id":94462169,"identity":"0ae62527-a117-4271-ba60-fb012ada1c0f","added_by":"auto","created_at":"2025-10-27 15:00:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":9513,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation matrix for adoption factors for Potential Buyers of EVs in Jordan\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7520351/v1/0ca8493aeb66aad01825641c.png"},{"id":94462170,"identity":"b30bbe30-3c93-4ead-9287-015ca90a9ffd","added_by":"auto","created_at":"2025-10-27 15:00:54","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":7836,"visible":true,"origin":"","legend":"\u003cp\u003eAdoption barriers for potential buyers of EVs in Jordan\u003c/p\u003e","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7520351/v1/5c2d00df6cb16ceec831e044.png"},{"id":94462317,"identity":"12165f45-1d75-4e51-bcd5-5d5d3b915bbc","added_by":"auto","created_at":"2025-10-27 15:01:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":12829,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation matrix for adoption barriers for potential buyers of EVs in Jordan\u003c/p\u003e","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7520351/v1/0d4cc2470711c8115a0f2187.png"},{"id":94462345,"identity":"f1d701ef-dd66-428e-acc7-a670e0d49e6a","added_by":"auto","created_at":"2025-10-27 15:01:43","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":37823,"visible":true,"origin":"","legend":"\u003cp\u003eComprehensive correlation matrix of EV adoption and barriers for potential buyers of EVs in Jordan\u003c/p\u003e","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7520351/v1/b3aa514a5627c36110d53c44.png"},{"id":99172396,"identity":"8a6a93d1-0790-439a-9cab-6e017771e66f","added_by":"auto","created_at":"2025-12-29 16:08:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":873647,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7520351/v1/e2d5e6af-8739-44a7-add6-4c4ae5b0e080.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Electric Vehicle Adoption in Jordan: Analyzing Consumer Motivations and Barriers","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe global adoption of electric vehicles (EVs) has grown rapidly in recent years, driven largely by strong market developments in China, the United States, and Europe. In 2023, global EV sales reached nearly 14\u0026nbsp;million units, representing around 18% of total car sales and marking a 35% increase from the previous year (IEA, 2024). This upward trend is projected to continue, with the global EV market expected to reach revenues of USD 786\u0026nbsp;billion in 2024 and exceed USD 1 trillion by 2029 (Statista, 2024). While established markets continue to lead, emerging economies are becoming increasingly important contributors to the worldwide transition towards low-emission road transport.\u003c/p\u003e\u003cp\u003eJordan, a small developing country in the Middle East, offers a unique context for examining EV adoption patterns. With a population of approximately 11.3\u0026nbsp;million and a heavy reliance on imported oil, the country faces persistent energy security challenges (Kiwan and Al-Gharibeh, 2020; World Bank, 2023). To address this, the Jordanian government has promoted EV uptake as part of its broader strategy to diversify the energy mix and reduce fuel import dependency (Mahadin, 2018; Abu-Rumman et al., 2020). The increasing installation of residential solar photovoltaic (PV) systems also provides opportunities for EV charging that power Jordan\u0026rsquo;s abundant solar resources (Al-Habaibeh et al., 2023). Unlike neighbouring oil-rich states, Jordan\u0026rsquo;s EV market is shaped by distinctive factors such as a thriving second-hand vehicle market, evolving charging infrastructure, and significant policy incentives including customs duty reductions and tax exemptions (Jordan Times, 2024; Shalamai, 2020). However, despite steady growth, with over 22,000 EVs cleared in the first half of 2024 (Jordan Times, 2024), barriers such as misconceptions about EV technology, limited public charging points, and social perceptions still affect adoption.\u003c/p\u003e\u003cp\u003eWhile much of the existing literature has examined EV adoption in larger or more mature markets, there is limited empirical research that explores the unique drivers and barriers in smaller, energy-importing countries like Jordan. This case study therefore aims to fill this gap by integrating quantitative survey data with qualitative insights from expert interviews, providing a comprehensive understanding of the economic, environmental, technological, and social factors influencing consumer decisions. By highlighting Jordan\u0026rsquo;s specific challenges and opportunities, this study provides policy insights that may guide other emerging economies with comparable energy and transport contexts.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eElectric vehicle (EV) adoption has attracted considerable global attention in recent years, with multiple studies highlighting how socio-economic, environmental, technological, and psychological factors interact to shape consumer decisions. International research has shown that factors such as fuel prices, maintenance costs, environmental awareness, government incentives, home ownership, and the availability of public charging infrastructure all play a critical role (He et al., 2022; Chu et al., 2019; Jenn et al., 2013). Policies such as direct rebates, tax credits, toll exemptions, and access to bus or HOV lanes have been found to significantly boost adoption in countries like China (Lichtenthaeler and Kasperk, 2017), Norway, and the United States (Bjerkan et al., 2016; Cui et al., 2021; Anastasiadou and Gavanas, 2022). Despite these policy successes, studies have also shown mixed evidence regarding the long-term effectiveness of incentives, with local energy costs and charging infrastructure availability remaining persistent barriers in countries such as Brazil and India (Ruoso and Ribeiro, 2022; Goel et al., 2021).\u003c/p\u003e\u003cp\u003eWhile much of the global literature focuses on mature markets, recent studies have increasingly examined EV adoption in emerging economies, including the Arab region. Research from Saudi Arabia, Lebanon, and the UAE identifies key drivers such as energy efficiency awareness, commute distance, and social or symbolic value attached to owning an EV (Bridi et al., 2022; Jreige et al., 2021). However, inadequate charging infrastructure, high upfront costs, and limited awareness continue to pose significant barriers in many MENA countries (Ramadan and Othman, 2023; Ottesen and Banna, 2021). Several studies group the factors influencing EV adoption into four broad categories:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEconomic Factors: Affordability, operating cost savings, fuel prices, and government financial incentives are consistently identified as major drivers (Fluchs and Kasperk, 2017; Mahadin, 2018). In Jordan, lower customs duties and tax exemptions make EVs more financially attractive than internal combustion engine (ICE) vehicles and hybrids.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEnvironmental Factors: Growing awareness of climate change and air pollution, coupled with zero-emission benefits, enhances the appeal of EVs, particularly in urban areas (Salah et al., 2023; Klabi and Binzafrah, 2023).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTechnological and Infrastructure Factors: The availability of charging stations (Albatayneh, 2024), ease of home charging, and perceived technological performance are widely acknowledged as critical (Mpoi et al., 2023; He et al., 2022).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eSocial and Cultural Factors: Social influence, symbolic values, and community trends can affect willingness to adopt EVs, as cars often represent more than just transportation in the region (Bhattacharyya and Thakre, 2021; Othman et al., 2022).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eIn Jordan, the EV market presents distinctive features that set it apart from neighbouring oil-rich states. The country\u0026rsquo;s reliance on imported energy, limited local reserves, and high fuel prices have made the government\u0026rsquo;s push for EV adoption a strategic priority for energy security (Kiwan and Al-Gharibeh, 2020). The affordability of used EVs, mainly imported from China and Europe, combined with reduced customs duties, makes them accessible to a broader segment of consumers (Jordan Times, 2024). The widespread adoption of solar PV systems provides an additional incentive, allowing many EV owners to charge vehicles at home using renewable energy (Al-Habaibeh et al., 2023). However, challenges such as limited charging infrastructure, market volatility due to rumors and misinformation, and cultural perceptions tied to social status persist (Shalamai, 2020; Addustour, 2024). While existing studies provide valuable insights into global and regional EV adoption trends, there is limited empirical evidence examining how economic, technological, environmental, and cultural factors interact within Jordan\u0026rsquo;s unique context as an energy-importing country with a large used EV market and significant solar potential. This study addresses this gap by combining a quantitative consumer survey with qualitative expert interviews to identify which factors are most influential in the Jordanian context. The findings help clarify priorities for policymakers and stakeholders, supporting informed decisions on targeted incentives, tax policies, strategic planning, and infrastructure development that can accelerate sustainable transport adoption in Jordan and comparable markets.\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eUnderstanding the factors that influence electric vehicle (EV) adoption in Jordan requires an approach that captures both measurable consumer trends and the deeper market context. This section outlines the study\u0026rsquo;s mixed-methods design, the rationale behind it, the data collection processes for the survey and expert interviews, and the analytical techniques applied.\u003c/p\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Research Design and Rationale\u003c/h2\u003e\u003cp\u003eThis study employs a mixed-methods research design, combining quantitative and qualitative approaches to provide a comprehensive understanding of the drivers and barriers to EV adoption in Jordan. A mixed-methods approach was chosen to integrate measurable consumer responses with expert insights, offering a nuanced perspective that aligns with established technology adoption frameworks, such as the Technology Acceptance Model (TAM) to consider economic, environmental, technological, and social dimensions. The Technology Acceptance Model (TAM) provides a theoretical basis by explaining how consumers\u0026rsquo; perceptions of usefulness and ease of use influence their attitudes and intentions to adopt new technologies, such as electric vehicles.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Survey Design and Data Collection\u003c/h2\u003e\u003cp\u003eA structured questionnaire was developed to investigate key determinants of EV adoption. The survey was organized into five sections: (1) personal and demographic information; (2) economic factors, including vehicle cost, operating expenses, and government incentives; (3) environmental factors, focusing on sustainability awareness and perceived air quality benefits; (4) technological and practicality factors, covering perceptions of vehicle performance, charging convenience, and reliability; and (5) social and cultural influences, such as peer opinions, social status, and the impact of rumors or misconceptions. Respondents were recruited through social media platforms, personal networks, and local EV owner groups to ensure diverse representation in age, gender, education, vehicle ownership, and commuting patterns. In total, 135 valid responses were collected. The study employed a non-probability convenience sampling method, which is common in exploratory case studies aiming to capture context-specific insights. The survey instrument and distribution procedures were reviewed and approved by the Research Ethics Committee at The British University in Dubai. This confirms that the survey met ethical standards for research involving human participants, including voluntary informed consent, confidentiality, and the right to withdraw. The survey was assessed as low risk, and no personally identifying information was collected to ensure participant anonymity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Expert Interviews\u003c/h2\u003e\u003cp\u003eTo complement the survey data, a semi-structured interview was conducted with an experienced EV consultant and sales professional in Jordan. The interview focused on market dynamics, consumer attitudes, pricing and maintenance perceptions, competitive positioning of EVs versus traditional vehicles, and the influence of government policies and incentives. Additional themes included the growth of charging infrastructure, technological advantages, environmental benefits, and social and cultural factors shaping adoption trends. Similarly, the semi-structured expert interviews were covered under the same ethical approval by the British University in Dubai. Experts participated voluntarily, with full informed consent for their names, affiliations, and professional insights to be cited in this study. Interview data were handled responsibly, securely stored, and used solely for the stated research purposes in accordance with the university\u0026rsquo;s research ethics guidelines.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Data Analysis\u003c/h2\u003e\u003cp\u003eQuantitative survey data were analyzed using MATLAB to perform descriptive and inferential statistical analyses. This included correlation analysis to identify relationships between variables, Principal Component Analysis (PCA) to reduce dimensionality and highlight underlying factor structures, and ANOVA tests to assess differences across demographic groups. Qualitative interview responses were thematically coded and analyzed using MATLAB to identify patterns and provide context that enriches the interpretation of the quantitative results. The study adhered to ethical research standards, with participants fully informed of the study\u0026rsquo;s purpose and their confidentiality rights.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Results and Discussion","content":"\u003cp\u003eThis study presents findings from both a survey and expert interviews regarding EV adoption in Jordan. The survey targeted a diverse demographic sample of drivers across various vehicle categories, gathering responses from 135 participants through social media, personal outreach, and direct connections. Detailed statistical analyses were performed using MATLAB to process the survey data, employing techniques such as regression analysis and Pearson correlation to evaluate the impact of demographic and psychographic factors on EV adoption. Key metrics were visualized through graphs and correlation matrices to identify significant trends and relationships. Additionally, expert interviews provided qualitative insights, with thematic analysis used to distill key opinions and experiences from industry specialists. Using MATLAB, the interview responses were categorized according to demographics, adoption interests, and barriers to adoption; specific themes were identified using relevant keywords, then encoded into binary matrices to track the occurrence of each theme across responses, supporting structured analysis and clear visualizations.\u003c/p\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Survey results\u003c/h2\u003e\u003cp\u003eThe survey was distributed in Jordan among drivers of various car categories, including internal combustion engine (ICE) vehicles, hybrids, and electric vehicles (EVs). A total of 135 respondents participated in the survey, which was conducted using social media platforms, personal connections, and direct outreach methods. Analysis of personal demographics in the dataset reveals several key descriptive statistics. The mean age of respondents is 41.07 years, with a standard deviation of 7.34 years, indicating a relatively mature sample. The median age is 40 years, suggesting that half of the participants are younger than this age. The ages of respondents range from a minimum of 25 years to a maximum of 65 years, highlighting a diverse age distribution within the sample. In terms of gender representation, the mean value is 0.51, indicating a slight majority of male respondents in the dataset, where 0 represents Female and 1 represents Male. The standard deviation of 0.50 suggests a balanced distribution between the genders, with a median gender value of 1. This indicates that a significant portion of the participants identified as male. Regarding educational attainment, the mean educational level of respondents is 2.52, with a standard deviation of 0.76. This statistic implies that most participants have completed a bachelor's degree, which is coded as 2. The median educational level is also 2, with values ranging from a minimum of 1 (high school) to a maximum of 4 (PhD), showcasing a diverse educational background among respondents. The analysis of commute distance reveals a mean of 58.12 km, accompanied by a substantial standard deviation of 44.90 km. The median commute distance is reported at 30 km, indicating that while many respondents have shorter commutes, some commute distances are considerably longer. The range of commute distances extends from a minimum of 30 km to a maximum of 250 km, further illustrating the diversity of commuting patterns within the sample. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the personal demographics of the survey sample.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn this study, Principal Component Analysis (PCA) was employed to derive a composite score that defines EV adoption interest based on multiple influencing factors. PCA is a statistical technique used to reduce the dimensionality of a dataset while retaining as much variance as possible, allowing identification of the most significant factors that contribute to consumer attitudes toward EVs. The initial step involved standardizing the dataset, ensuring that each variable is on a similar scale to prevent any single variable from disproportionately influencing the results. The original Likert scale questions related to economic, environmental, technological, and social factors were then analyzed. The four key factors identified in the study are defined as follows:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEconomic Factors (EF): This includes questions related to financial incentives, operating costs, and the affordability of electric vehicles.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEnvironmental Factors (EnF): This encompasses beliefs about EVs' impacts on air quality, carbon emissions, and overall sustainability.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTechnological Factors (TF): This refers to perceptions regarding the reliability of EV technology, charging infrastructure, and vehicle performance.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eSocial Factors (SF): This includes the influence of social status, peer opinions, rumors and misconceptions, and community perceptions related to EV ownership.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eFor each of these factors, a set of Likert scale questions was posed to the respondents. The scores from these questions were used to compute the principal components through PCA. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the Survey Questions Categorized by Economic, Environmental, Technological, and Social Factors. To define the EV adoption interest based on PCA, we formulated the following equation:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{E}\\varvec{V}\\:\\varvec{A}\\varvec{d}\\varvec{o}\\varvec{p}\\varvec{t}\\varvec{i}\\varvec{o}\\varvec{n}\\:\\varvec{I}\\varvec{n}\\varvec{t}\\varvec{e}\\varvec{r}\\varvec{e}\\varvec{s}\\varvec{t}=\\varvec{P}{\\varvec{C}}_{1}={\\varvec{\\omega\\:}}_{\\varvec{E}\\varvec{F}}\\varvec{E}\\varvec{F}+{\\varvec{\\omega\\:}}_{\\varvec{E}\\varvec{n}\\varvec{F}}\\varvec{E}\\varvec{n}\\varvec{F}+{\\varvec{\\omega\\:}}_{\\varvec{T}\\varvec{F}}\\varvec{T}\\varvec{F}+{\\varvec{\\omega\\:}}_{\\varvec{S}\\varvec{F}}\\varvec{S}\\varvec{F}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhere: EV Adoption Interest is the composite score representing the overall inclination to adopt electric vehicles. \u003cem\u003ePC\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e​ is the first principal component derived from PCA, reflecting the most variance in the data. \u003cem\u003eEF\u003c/em\u003e, \u003cem\u003eEnF\u003c/em\u003e, \u003cem\u003eTF\u003c/em\u003e, and \u003cem\u003eSF\u003c/em\u003e represent the aggregated scores of economic, environmental, technological, and social factors, respectively. The weights \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\omega\\:}_{EF}\\)\u003c/span\u003e\u003c/span\u003e​, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\omega\\:}_{EnF}\\)\u003c/span\u003e\u003c/span\u003e​, ​, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\omega\\:}_{TF}\\)\u003c/span\u003e\u003c/span\u003e​, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\omega\\:}_{SF}\\)\u003c/span\u003e\u003c/span\u003e​, are the factor loadings assigned by PCA, indicating the relative contribution of each factor\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSurvey questions categorized by economic, environmental, technological, and social factors\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFactor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLikert Scale Question\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eEconomic Factors (EF)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1. Electric vehicles have appealing prices compared to ICE and Hybrid vehicles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2. Electric vehicles have lower operating costs compared to ICE and Hybrid vehicles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3. Electric vehicles benefit from lower maintenance costs compared to ICE and Hybrid vehicles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4. Government incentives make electric vehicles more affordable.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5. I believe the depreciation rate of electric vehicles is comparable to that of ICE and Hybrid vehicles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6. I believe the cost of replacing an electric vehicle battery is manageable.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eEnvironmental Factors (EnF)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1. Electric vehicles help reduce air pollution in Jordan.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2. Using electric vehicles helps reduce the carbon footprint globally.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3. I believe electric vehicles are more energy-efficient compared to ICE and Hybrid vehicles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4. I believe electric vehicles contribute more to environmental sustainability compared to ICE and Hybrid.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eTechnological Factors (TF)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1. Electric vehicles offer better performance and technology compared to ICE and Hybrid vehicles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2. There are enough charging stations available in Jordan.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3. Charging an electric vehicle is convenient, accessible, and fast.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4. I believe the technology of electric vehicles is reliable.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5. I am satisfied with the driving range that most electric vehicles currently offer.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6. I am confident in the safety of electric vehicle components, including batteries and motors.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eSocial Factors (SF)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1. Owning an electric vehicle is seen as a positive social status symbol.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2. Owning an electric vehicle reflects a commitment to environmental responsibility.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3. My decision to purchase an electric vehicle is influenced by the opinions of my friends and family.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4. Seeing more electric vehicles in my community encourages me to consider purchasing one.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5. I am not influenced by rumors and misconceptions about electric vehicles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe analysis of factors influencing EV adoption interest revealed several significant correlations, as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Each factor demonstrated a different level of association with consumers\u0026rsquo; inclination to adopt EVs. Technological factors showed the strongest positive correlation (r\u0026thinsp;=\u0026thinsp;0.760), indicating that perceptions of technology reliability, performance, and charging infrastructure play a critical role in adoption decisions. This highlights the importance of continued advancements and public trust in EV technology. Social factors also showed a strong positive correlation (r\u0026thinsp;=\u0026thinsp;0.663), underscoring the influence of peer opinions, community norms, and societal attitudes on EV uptake. This suggests that visible social acceptance and word-of-mouth can meaningfully shape consumer behavior. Environmental factors exhibited a correlation coefficient of 0.622 (p\u0026thinsp;=\u0026thinsp;0.000), showing that awareness of environmental benefits, such as reduced air pollution and lower greenhouse gas emissions, significantly enhances consumer interest in EVs. Economic factors had a correlation of 0.598 (p\u0026thinsp;=\u0026thinsp;0.000), indicating that financial incentives, operating cost savings, and perceived affordability remain important motivators for potential buyers. All four factors were statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, providing strong evidence that they collectively influence EV adoption interest in Jordan. The low p-values (\u0026lt;\u0026thinsp;0.05) confirm that these relationships are unlikely to have occurred by chance, reinforcing the robustness of the findings.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelations of factors influencing EV adoption interest\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFactor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP-Value\u003c/p\u003e\u003cp\u003e(sig)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEconomical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.598\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSignificant positive correlation, indicating strong influence of economic factors on EV adoption.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnvironmental\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.622\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSignificant positive correlation, showing that environmental concerns significantly impact EV adoption.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTechnology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.760\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStrongest correlation, suggesting technological perceptions are crucial for consumer interest.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.663\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStrong correlation, highlighting the importance of social influences on EV adoption decisions.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eCorrelation is significant at the 0.05 level\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe analysis of factors influencing EV adoption indicate that while each factor independently affects adoption interest, their combined influence illustrates how economic, environmental, technological, and social dimensions interact to shape the broader EV market landscape. This underlines the need for integrated strategies that address all four dimensions to build confidence and accelerate market growth. Additional analysis of individual traits is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The results revealed that age showed only a weak and statistically insignificant relationship with adoption interest (r\u0026thinsp;=\u0026thinsp;0.119, p\u0026thinsp;=\u0026thinsp;0.167). Gender was the only demographic factor with a significant effect (r = \u0026minus;\u0026thinsp;0.183, p\u0026thinsp;=\u0026thinsp;0.033), suggesting that female respondents may show slightly more interest in EVs than males. Education level, commute distance, and primary vehicle use were not significantly correlated with EV adoption interest. These findings reinforce that broader economic, environmental, technological, and social factors are likely to be more influential than personal demographics alone in shaping EV adoption decisions in the Jordanian context.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelations between individual traits and EV adoption interest\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFactor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003cp\u003e(sig) *\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA weak positive correlation suggests older respondents may have slightly more interest in EVs, but it is not statistically significant at the 0.05 level.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA negative correlation indicates that male respondents show less interest in EVs compared to females, with a statistically significant p-value.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation Level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.518\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo meaningful correlation; education level does not significantly influence interest in adopting EVs.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCommute Distance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.911\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA weak positive correlation indicates commute distance does not significantly influence EV adoption interest.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary Use of Vehicle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo significant correlation suggests that primary use of the vehicle does not impact interest in EV adoption.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e* Correlation is significant at the 0.05 level\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo further explore whether demographic and usage-related characteristics affect EV adoption interest, an Analysis of Variance (ANOVA) was conducted. This test compared group means across variables such as governorate, type of previous vehicle, gender, education level, age, and commute distance. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the ANOVA results. Among all variables tested, only gender showed a statistically significant difference (p\u0026thinsp;=\u0026thinsp;0.033), suggesting that gender may influence adoption interest. Other demographic factors did not demonstrate significant effects, reinforcing the finding that broader economic, environmental, technological, and social factors are likely to play a more decisive role. These results highlight the importance of developing adoption strategies that focus less on personal demographics and more on addressing practical, economic, and societal influences that shape consumer attitudes toward EVs.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnalysis of Variance (ANOVA) results for factors Influencing electric vehicle adoption interest\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;F\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGovernorate Groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.2319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.7053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5811\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1578\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo significant difference in EV adoption interest across governorates.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ldquo;Type of Previous Vehicle\u0026rdquo; Groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.9114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.4557\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.0091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.3675\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eThe type of previous vehicle does not significantly influence EV adoption interest.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender Groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.0586\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.0586\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.6191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eA significant difference exists in EV adoption interest based on gender, suggesting gender plays a role.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation Level Groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.7682\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.5894\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.2851\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.2823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eEducation level does not significantly affect EV adoption interest.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.4578\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.4859\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.0631\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.3671\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAge groups do not show a significant impact on EV adoption interest.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ldquo;Commute Distance\u0026rdquo; Groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.4399\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.4800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.0426\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.3761\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCommute distance groups do not significantly influence EV adoption interest.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Expert Interviews results\u003c/h2\u003e\u003cp\u003eIn addition to the survey, a series of semi-structured expert interviews was conducted to gain practical and strategic perspectives on EV adoption in Jordan and the wider Middle East. The expert panel included industry professionals and academics, each contributing unique insights into market trends, consumer behavior, policy issues, and adoption barriers (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExpert interviewee panel for EV market insights\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSr.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eName\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCompany\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRole\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYears of Experience\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEng. Abdel AlRahman AlQademat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBYD-Jordan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSales Consultant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProfessor Bassam Abu-Hijleh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBritish University in Dubai\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDean of Faculty of Engineering \u0026amp; IT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u0026thinsp;25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAllen Bedrossian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMitsubishi Middle East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGeneral Manager Marketing and Sales\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAlaa Tayeb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNissan, and Stellantis Middle East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBrand Manager - Middle East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBisher Khalil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKhalil \u0026amp; Ali Car Trading\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSales and Marketing Specialist\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe panel included sales consultants, brand managers, and an academic dean specializing in sustainable transportation. Collectively, they emphasized four main themes shaping EV adoption: economic considerations, technological readiness, social factors, and environmental influences. From the sales perspective, affordable prices for used EVs, especially from China, and seasonal purchase patterns were highlighted as key drivers. However, misconceptions about battery life, driving range, and maintenance costs continue to limit consumer confidence. Marketing and brand managers underscored the importance of leveraging social networks and word-of-mouth, as peer influence and visible adoption trends encourage wider uptake. The academic perspective stressed the need for consistent government incentives, transparent tax structures, and large-scale investment in charging infrastructure to reduce range anxiety. Experts agreed that rumors and misinformation significantly distort market perceptions, driving price volatility and consumer hesitancy. This highlights the critical role of awareness campaigns and reliable information channels to counteract misconceptions. A structured thematic coding and correlation analysis was conducted on the interview transcripts to quantify the frequency and relationships among the key topics discussed. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrate the frequency with which specific consumer traits and segments were discussed by the interviewed experts as critical for understanding EV adoption in Jordan. Rather than representing survey demographics, the frequencies reflect how often these themes appeared in qualitative interviews. For example, \u0026lsquo;Age\u0026rsquo; was most frequently mentioned as a decisive factor, with experts highlighting younger buyers as tech-savvy adopters and older buyers as economically motivated adopters. \u0026lsquo;Commute distance\u0026rsquo;, \u0026lsquo;use of vehicle\u0026rsquo;, and \u0026lsquo;tech-enthusiasts\u0026rsquo; were also emphasized as segments where tailored incentives and communication could enhance adoption rates.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e present the aggregated themes from the expert interviews regarding the primary motivators for EV adoption.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, along with the thematic analysis confirmed that economic factors, vehicle price, operating costs, and financial incentives, are the strongest motivators driving EV purchases in Jordan. Technological reliability and accessible charging infrastructure also remain critical to building consumer confidence, while social and environmental motivations tend to overlap, indicating that buyers who care about sustainability are often influenced by positive peer perceptions and community norms. Interestingly, the correlation matrix shows that environmental concerns still have only a weak link to economic or technological priorities, suggesting that for many consumers, practical cost savings still outweigh purely environmental ideals.\u003c/p\u003e\u003cp\u003eThese insights are especially relevant given the Jordanian government\u0026rsquo;s newly announced EV tax policy (Addustour,2024). The updated measures include both temporary incentives and longer-term adjustments: The special tax rates for new EV imports will be restructured: vehicles with a customs value of 10,000\u0026ndash;25,000 JD will see their special tax rate reduced from 40\u0026ndash;20%, while higher-end vehicles above 25,000 JD will drop from 55\u0026ndash;27.5%. The rate for lower-value EVs under 10,000 JD remains unchanged at 10%. This carefully phased approach aims to protect dealers, clear existing inventory, and keep EVs financially accessible, especially in the affordable segment that matters most for wider adoption. The experts highlighted that clear, predictable policies like these, combined with sustained investment in charging networks and public awareness campaigns, are critical to countering rumors and misconceptions that remain barriers to EV uptake. For policymakers and industry leaders, this study reinforces the need for an integrated approach: aligning fiscal measures, infrastructure readiness, and public trust to sustain growth in Jordan\u0026rsquo;s EV market without risking sudden drops in demand.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e highlight the main barriers to EV adoption as reported by experts. High taxes, insufficient charging infrastructure, and persistent rumors emerged as the top obstacles. Notably, misconceptions were strongly correlated with range anxiety, illustrating how misinformation can amplify practical concerns such as limited driving range. This connection suggests that addressing myths and rumors could directly reduce some of the practical anxieties that discourage potential buyers.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e presents the comprehensive correlation matrix combining the main themes identified across demographics, adoption motivators, and barriers. This holistic view shows how various factors interact to shape EV adoption dynamics in Jordan. One of the most notable findings is the strong positive correlation (0.70) between charging infrastructure and technological factors, suggesting that perceptions of EV technology reliability and performance are closely tied to the availability and convenience of charging networks. This reinforces the practical point that advancements in EV technology must go hand-in-hand with robust infrastructure to strengthen consumer confidence. Another clear relationship is between environmental factors and social factors (0.42), implying that sustainability concerns often align with social norms and peer influence. This highlights the potential of community-driven awareness campaigns to amplify environmental motivations through social channels. The matrix also reveals that misconceptions have significant links with limited range (0.62) and rumors (0.45). This indicates that misinformation and rumors tend to amplify range anxiety, creating a reinforcing cycle that can hinder adoption. Addressing these misconceptions through targeted education could therefore reduce both perceived and practical barriers.\u003c/p\u003e\u003cp\u003eInterestingly, high taxes correlate moderately with the use of vehicle variable (0.47). This suggests that future tax policies could disproportionately impact consumers using vehicles for specific purposes, such as delivery or ride-sharing, which tend to have higher running costs. This points to the need for carefully designed fiscal policies that balance revenue with encouraging EV uptake in high-usage sectors. Demographic links are also evident: for instance, age shows a moderate positive correlation with tech enthusiasts (0.40), indicating that younger segments may be more willing to adopt new technologies like EVs, especially when combined with modern features and innovation. Finally, the low or negative correlations between environmental and economic factors (0.12) and technological factors (-0.23) underscore that while environmental consciousness is important, practical cost savings and technological readiness remain the dominant drivers for many consumers. Overall, the matrix illustrates that boosting EV adoption will require coordinated strategies: expanding charging infrastructure, addressing persistent misconceptions, designing effective tax incentives, and leveraging social and environmental messaging. This interconnected view emphasizes that barriers and motivators do not operate in isolation but interact in complex ways that must be addressed holistically.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study provides a comprehensive, mixed-methods assessment of the factors influencing electric vehicle (EV) adoption in Jordan, combining a quantitative consumer survey with qualitative expert interviews. By analyzing both perspectives, the research captures the multifaceted drivers and barriers shaping the country\u0026rsquo;s evolving EV market. The survey of 135 respondents, supported by thematic analysis and statistical techniques such as PCA, correlation, and ANOVA, revealed that while environmental sustainability and cost savings are important motivators, practical considerations, especially technological reliability, availability of charging infrastructure, and social perceptions, have a stronger influence on adoption decisions. Insights from five industry experts further emphasized the need for consistent government incentives, consumer education, and infrastructure expansion to address persistent misconceptions and build trust in EVs. This is particularly timely given Jordan\u0026rsquo;s recently approved phased increases in special taxes on EVs. Without balanced policies, such as targeted tax incentives for affordable models and investment in accessible charging networks, these tax changes could undermine progress by making EVs less financially attractive.\u003c/p\u003e\u003cp\u003ePractically, the study offers evidence-based guidance for policymakers designing fiscal measures and infrastructure strategies to sustain adoption momentum. For industry stakeholders, understanding how local community norms and peer influence shape purchase behavior can inform tailored marketing, after-sales support, and public awareness campaigns. However, It is important to acknowledge that the study used a convenience-based, non-probability sample, which may limit its generalizability. Nonetheless, the combination of robust statistical methods and expert validation ensures that the findings are contextually relevant for Jordan and comparable emerging markets. Future research should build on this foundation by tracking the real-world impacts of the new tax regime and monitoring how improved infrastructure and public awareness influence adoption rates over time. Longitudinal studies and broader representative sampling would further enhance understanding and help refine incentives and outreach strategies to support Jordan\u0026rsquo;s transition to sustainable mobility.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003eThe survey instrument and distribution procedures were reviewed and approved by the Research Ethics Committee at The British University in Dubai; participation was voluntary with informed consent, confidentiality protections, and no collection of personally identifying information. Expert interviews were covered under the same approval, with informed consent for citing names and affiliations.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests, financial or non-financial, that could be perceived as influencing the content or conclusions of this paper\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eNo funding was received for this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eI.M.H. visualized the study, developed the methodology, performed data analysis, and wrote both the original draft and the final manuscript. H.T. supervised the study, contributed to validation and methodology, critically reviewed the manuscript, and helped write the final manuscript. H.H. designed the survey, collected data, conducted interviews, critically reviewed the final manuscript, and helped write the final manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe gratefully acknowledge the experts who shared their time and insights during the interviews: Eng. Abdel AlRahman AlQademat (Sales Consultant, BYD-Jordan), Prof. Bassam Abu-Hijleh (Dean, Faculty of Engineering \u0026amp; IT, British University in Dubai), Allen Bedrossian (General Manager, Marketing \u0026amp; Sales, Mitsubishi Middle East), Alaa Tayeb (Brand Manager, Middle East, Nissan and Stellantis Middle East), and Bisher Khalil (Sales \u0026amp; Marketing Specialist, Khalil \u0026amp; Ali Car Trading). Their perspectives on market dynamics, consumer behavior, and policy conditions in Jordan substantially informed our analysis.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAddustour (2024) \u0026lsquo;Electric vehicles exempted from special tax by 50%\u0026rsquo;, Addustour, 6 May. Available at: https://www.addustour.com/articles/1455774\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAddustour (2024) \u0026lsquo;Free-zone investors condemn rumors surrounding electric vehicles\u0026rsquo;. Addustour. [In Arabic] Available at: https://www.addustour.com/articles/1409285\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbu-Rumman, G., Khdair, A., Khdair, S., 2020. Current status and future investment potential in renewable energy in Jordan: An overview. Heliyon 6, 1\u0026ndash;8. https://doi.org/10.1016/j.heliyon.2020.e03346\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlbatayneh, A. (2024) \u0026lsquo;Electric cars in Jordan: Opportunities and challenges\u0026rsquo;, International Journal of Electrical and Computer Engineering Research, 4, pp. 8\u0026ndash;12. doi:10.53375/ijecer.2024.414.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAl-Habaibeh, A., Al-haj Moh\u0026rsquo;d, B., Massoud, H., Nweke, O.B., Al Takrouri, M. and Badr, B.E.A. (2023) \u0026lsquo;Solar energy in Jordan: Investigating challenges and opportunities of using domestic solar energy systems\u0026rsquo;, World Development Sustainability, 3, p. 100077. doi:10.1016/j.wds.2023.100077.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnastasiadou, K. and Gavanas, N. (2022) \u0026lsquo;State-of-the-art review of the key factors affecting electric vehicle adoption by consumers\u0026rsquo;, Energies, 15(24), p. 9409. doi:10.3390/en15249409.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBhattacharyya, S.S. and Thakre, S. (2021) \u0026lsquo;Exploring the factors influencing electric vehicle adoption: An empirical investigation in the emerging economy context of India\u0026rsquo;, Foresight, 23(3), pp. 311\u0026ndash;326. doi:10.1108/FS-04-2020-0037.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBjerkan, K., N\u0026oslash;rbech, T. and Nordt\u0026oslash;mme, M. (2016) \u0026lsquo;Incentives for promoting battery electric vehicle (BEV) adoption in Norway\u0026rsquo;, Transportation Research Part D: Transport and Environment, 43, pp. 169\u0026ndash;180. doi:10.1016/j.trd.2015.12.002.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChu, W., Im, M., Song, M.R. and Park, J. 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(2020) \u0026lsquo;Electric cars market development in Jordan and Ukraine (Comparative analysis of Ukrainian and Jordanian experiences)\u0026rsquo;, Business, Economics, Sustainability, Leadership and Innovation, pp. 8\u0026ndash;16. doi:10.37659/2663-5070-2020-5-8-16.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShalalfeh, L., AlShalalfeh, A., Alkaradsheh, K., Alhamarneh, M. and Bashaireh, A. (2021) \u0026lsquo;Electric vehicles in Jordan: Challenges and limitations\u0026rsquo;, Sustainability, 13(6), p. 3199. doi:10.3390/su13063199.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStatista (2024) Electric Vehicles: Worldwide Market Forecast. Available at: https://www.statista.com/outlook/mmo/electric-vehicles/worldwide\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilson Center (2023) Jordan\u0026rsquo;s government adopts women economic empowerment plan. Wilson Center. Available at: https://www.wilsoncenter.org/blog-post/jordans-government-adopts-women-economic-empowerment-plan\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXinhua (2023) \u0026lsquo;Electric vehicles appeal to more Jordanians for lower driving costs\u0026rsquo;. Xinhua. Available at: https://english.news.cn/20230110/\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Electric Vehicles, EV Adoption, EV Barriers, Charging Infrastructure, Sustainable Transport","lastPublishedDoi":"10.21203/rs.3.rs-7520351/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7520351/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the factors influencing electric vehicle (EV) adoption in Jordan, a small energy-importing country with a growing used EV market and strong renewable energy potential. A mixed-methods approach combined a quantitative survey (n\u0026thinsp;=\u0026thinsp;135) with expert interviews to identify key drivers and barriers. Results show that technological factors, such as perceived reliability, driving range, and charging infrastructure, are the strongest predictors of adoption interest. Social influences, including peer opinions and widespread misconceptions, also shape consumer attitudes. Environmental benefits and cost savings matter but are often outweighed by practical technological and social considerations. Expert insights reinforced the need for stable incentives, reliable infrastructure, and public awareness campaigns to counter misinformation. Jordan\u0026rsquo;s newly approved gradual tax increases on EVs could challenge affordability if not balanced with clear policies, targeted incentives, and charging network improvements. The findings provide practical guidance for policymakers and industry stakeholders to design integrated strategies that address economic, technological, and social dimensions together, supporting sustainable transport growth in Jordan and similar emerging markets.\u003c/p\u003e","manuscriptTitle":"Electric Vehicle Adoption in Jordan: Analyzing Consumer Motivations and Barriers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-27 12:32:07","doi":"10.21203/rs.3.rs-7520351/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-03T08:10:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-24T05:39:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3933416516290838311446708342468079450","date":"2025-10-08T18:23:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"178314794242380260261308634581887922728","date":"2025-10-07T10:21:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90848127831770525015129307846167125212","date":"2025-10-06T05:47:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-03T18:46:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315121079229827893468554664727829979006","date":"2025-10-03T08:20:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187888970321213779360068027791054598235","date":"2025-10-03T06:18:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-03T04:40:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-01T12:26:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-10T04:46:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-10T04:46:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2025-09-02T18:03:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"882d0eb1-f46e-4839-b27e-77e17906a9a3","owner":[],"postedDate":"October 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T16:02:53+00:00","versionOfRecord":{"articleIdentity":"rs-7520351","link":"https://doi.org/10.1007/s43621-025-02446-5","journal":{"identity":"discover-sustainability","isVorOnly":false,"title":"Discover Sustainability"},"publishedOn":"2025-12-24 15:58:18","publishedOnDateReadable":"December 24th, 2025"},"versionCreatedAt":"2025-10-27 12:32:07","video":"","vorDoi":"10.1007/s43621-025-02446-5","vorDoiUrl":"https://doi.org/10.1007/s43621-025-02446-5","workflowStages":[]},"version":"v1","identity":"rs-7520351","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7520351","identity":"rs-7520351","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}