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Article

Adoption of Electric Motorcycles in Pakistan: A Technology Acceptance Model Perspective

by
Sajan Shaikh
1,2,*,
Mir Aftab Hussain Talpur
3,*,
Farrukh Baig
4,5,*,
Fariha Tariq
5 and
Shabir Hussain Khahro
6
1
School of Transportation and Logistics, Dalian University of Technology, Dalian 116024, China
2
School of Transportation, Southeast University, Nanjing 211189, China
3
Department of City and Regional Planning, Mehran University of Engineering and Technology, Jamshoro 76062, Pakistan
4
School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
5
Department of City and Regional Planning, School of Architecture and Planning, University of Management and Technology, Lahore 54770, Pakistan
6
Department of Engineering Management, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi Arabia
*
Authors to whom correspondence should be addressed.
World Electr. Veh. J. 2023, 14(10), 278; https://doi.org/10.3390/wevj14100278
Submission received: 26 August 2023 / Revised: 19 September 2023 / Accepted: 28 September 2023 / Published: 3 October 2023
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Abstract

:
Electric motorcycles (EMs) are gaining popularity in densely populated Asian countries, offering environmentally friendly solutions to combat traffic-related pollution. Governments and authorities are eager to promote EMs to reduce reliance on traditional fuel-based motorcycles. While prior research has explored the potential impacts of EMs, limited attention has been given to the adoption intentions of the Pakistani public. This study investigates the factors influencing the behavioral intentions of adopting EMs in Pakistan, employing an extended technology acceptance model (TAM) framework. The extended model incorporates perceived values and environmental concerns, along with perceived usefulness and perceived ease of use, to assess their impact on EM adoption intentions. Based on data collected from 228 respondents in Karachi, Pakistan, structural equation models were estimated to identify significant factors affecting EM adoption. Findings highlight the substantial influence of perceived value and environmental concern on behavioral intentions, with perceived ease of use playing a mediated role through perceived usefulness. Results suggest that effective marketing and user-friendly EM designs, coupled with well-crafted policies and education, can substantially boost EM adoption by the public, facilitating a shift toward sustainable transportation alternatives.

1. Introduction

The transportation sector plays a vital role in boosting the country’s economy; it is responsible for 23% of global CO2 emissions from fuel combustion [1], and it is equally responsible for environmental pollution. Increasing vehicle ownership is investable as a result of rapid urbanization and the continuously growing world population [2]. Currently, one billion vehicles are reported to be on the roads, consuming approximately 70% of the total oil production, among which private vehicles only emit 14 million tons of carbon dioxide daily [3]. Technological innovations in the 20th century and environmental awareness make it easier for people to shift towards sustainable and economical transport solutions such as electric motorcycles (EMs) [4]. As known as ecofriendly vehicles, EMs have the benefits of reducing CO2 emissions and gasoline demand [5].
Since 2008, researchers have paid attention to discussing the penetration of EMs in the transport sector. China and the U.S.A., with their high environmental awareness, lead the world to promote the adoption of EMs [6]. The growing body of literature in the E-mobility research area has been discussing EVs’ adoption and purchase intentions [7,8,9]. However, only a handful of studies have been conducted to demonstrate the adoption of EMs in developing countries, as highlighted in a recent literature review [9]. Additionally, Eccarius and Lu [9] also argued that most of the prominent empirical studies stressing the adoption of EMs were from Taiwan, China, Laos, Vietnam, and Indonesia. Asian countries have an 80% share of the global motorcycle fleet, indicating high motorcycle dependency in this region [9,10].
For instance, Taiwan-China establishments sustained the examination and development of EMs and introduced subsidies for EMs purchases as early as 1998, pricing EMs comparably to conventional motorcycles. However, acceptance was low for many years due to riders’ concerns regarding EMs performance as substandard to conventional motorcycles, lack of convenience, and other complaints. In 2015, after tens of millions of Taiwan dollars were spent on subsidies, a notable increase in EMs consumption was observed [9]. Other Asian entities, such as Laos, Vietnam, and Indonesia, appear to be still growing their EMs usage. E-mobility uptake is continuously increasing and serving approximately 6.3 billion people living in low- and middle-income countries around the world [11]. Many countries have set targets and applied policies to deploy EMs, and EMs will likely take an impressive share in the future vehicle fleet. In 2015, worldwide sales crossed over 40 million, of which more than 90% were in China, 5% in Europe, and 0.7% in the USA [6].
EMs remained less popular in developing countries such as India, Pakistan, etc. [10]. The situation is changing now, and it is expected that EMs will achieve a significant market share in other Asian developing countries by 2050 [12]. Air pollution in Pakistan presents a pressing public health concern, demanding immediate attention and the adoption of sustainable solutions such as the acceleration of EV adoption. Major transportation consists of road transport and is responsible for adverse environmental effects, continuously increasing CO2 emissions, population increase, and urbanization [13,14]. It was estimated that 18% of the country’s total CO2 emissions were constituted by its transport sector because of its extensive use of nonrenewable energy resources (oil, fuel, etc.) [15]. According to estimates by the World Bank, Pakistan experiences a staggering disease burden due to outdoor air pollution, resulting in approximately 22,000 premature adult deaths annually [16]. Over the past two decades, the concentration of major air pollutants, such as NOx, O3, and SO2, has shown a concerning upward trend.
Furthermore, multiple studies have consistently reported air quality levels in major Pakistani cities that frequently exceed national guidelines [17,18]. A stark example is seen in Lahore, Pakistan, where, in 2019, PM2.5 concentrations regularly surpassed both WHO and national air quality standards [18]. In light of these alarming statistics and the detrimental impact on public health, adopting electric vehicles (EVs) emerges as a crucial and necessary step towards reducing air pollution, safeguarding lives, and promoting sustainable transportation alternatives in Pakistan [19].
Recently, Rasool et al. [15] investigated aspects of CO2 emissions caused by the transport sector of Pakistan and suggested EV adoption as a key priority for mitigating environmental pollution. The Pakistani government showed interest in adopting electric vehicles and has been set to introduce 100,000 electric vehicles into the market in 2020. The government has been looking for the conversion of 90% of the vehicle fleet to electric by 2040 [20]. A policy document was also prepared to enhance the understanding of electric vehicle adaptation and overcome the related issues and challenges, but less consideration was given to EMs [20,21]. In developing policy recommendations for E-mobility, the possibilities of EV penetration were discussed in the context of Pakistan [20,22]. EVs have the potential to solve critical challenges faced by Pakistan, including environmental degradation, climatic conditions, and socioeconomic imbalances. Pakistan is expected to contain more than half a million EMs in its major cities by the end of 2030 [22]. To achieve the national EV policy targets, the first few years require a carefully planned transformation of the auto industry in Pakistan. According to the policy, these initial years are divided into three aspects. The first aspect will focus on the market development strategy and public awareness of EVs for stockholders willing to invest in EV-related companies. The second aspect will cover fuel import billing barter along with targeted penetration of EMs by the local assembly and manufacturing industry. In the last aspect, the focus will be given to the local adoption and export of EVs and their related components. Thus, the need for understanding EM adoption arose in managing marketing strategies and developing policies to encourage the purchase of ecofriendly alternatives to fuel-based conventional motorcycles.
Pakistan’s transport sector has been predominantly concentrated on motorcycles [23]. Hence, the study suggests replacing conventional motorcycles with EMs may be much easier in Pakistan than in car-dominant cultures. EMs have already been introduced in 2019 in markets [24], but public acceptance still needs exploration to develop policy recommendations to enhance this modal shift. To the best knowledge of the authors, this paper is the first research contribution aimed at understanding the public acceptance of EMs in Pakistan through the technology acceptance model.
The present research aims to evaluate the effects of environmental concerns, perceived value, perceived usefulness, and perceived use in predicting the intentions to adopt EMs in the context of Pakistan. Hypothetical relations among the predictors of intentions to adopt EMs were postulated through the technology acceptance model (TAM), consistent with previous studies [25,26]. Agreeing with traditional TAM (Davis, 1989), perceived ease of use has a positive effect on perceived usefulness, while both perceived ease of use and perceived usefulness have a positive impact on consumer attitudes toward technology.
Firstly, this paper discusses a literature review to develop a hypothesized model for the present study. Secondly, a detailed description of the study materials and methods is given, followed by questionnaire design, data collection, respondent details, and the analytical instrument used to analyze the data. Thirdly, the study’s results are presented, which were determined by executing a conceptual model. Then, the discussion and policy recommendations are presented, and lastly, the conclusions, limitations, and future research directions are suggested to illuminate the significance of the present study.

2. Literature Review

Weinert et al. [27] classified two-wheeler vehicles into electric two-wheelers, motorcycles, and bicycles for China, whereas in Europe, two-wheelers are categorized in terms of speed and power in line with legal regulations for e-mopeds, e-bikes, and e-motorcycles/scooters. Eccarius et al. [9] claimed that EMs differ from e-bikes in that EMs cannot be pedal-propelled by humans. Previous studies on e-mobility predominantly discuss the behavioral intentions to adopt EVs, where the larger focus was given to e-bikes and e-cars compared to electric motorcycles (EMs), as indicated in review studies [10,28].
An empirical study with 233 respondents from Taiwan, China, explained that the behavioral intentions to purchase EMs are positively influenced by various psychological factors, including product knowledge, perceived quality, perceived value, and perceived usefulness [8]. However, perceived risk was found to be negatively associated with perceived value towards purchase intentions for EMs. In an anecdotal study from Taiwan, China, consumers’ preference to adopt EMs was explored through a stated preference survey indicating the individual’s demographics, together with the price, speed, range, and charge of EMs as influential characteristics affecting the buying intentions [29]. Concurrently, Wu et al. [30] adopted an extension of the technology acceptance model (TAM) with the structural equation modeling (SEM) approach to verify the influencing factors (such as service image, risk, value, and perceived usefulness) affecting EMs purchase intentions in the context of Taiwan, China. Another study adopted the TAM model to highlight the effects of perceived risk, perceived value, and consumption attitude on behavioral intentions to buy EMs [31]. A study from Southeast Asia adopted a stated preference survey to explain the effects of speed, range, charge time, and price on EMs’ purchasing intentions perceived by people living in an urban area of Indonesia [32]. Additionally, a study from Macau, China, considered the influence of environmental awareness on EM adoption by measuring the relation of EM acceptance with an individual’s perception regarding environmental policy, pollution reduction, the saving of energy, and driving performance [33].
Thus, studies have discussed the individual’s purchase intentions to adopt EMs from various perspectives, including the perception of environmental policy, EMs’ actual characteristics, the individual’s perception of EMs’ characteristics, and individual demographics. Nevertheless, in many studies, the environmental concern comparison, which was found to be a significant predictor of behavioral intentions to adopt EVs, did not receive enough attention in the context of EM adoption in developing countries. In the present study, we aim to discuss environmental concerns comparable to perceived value in predicting behavioral intentions to adopt EMs.

2.1. Technology Acceptance Model (TAM)

The technology acceptance model (TAM) is a widely used theoretical framework that explains and predicts how users accept and adopt new technology [26]. TAM posits that users’ intention to use a technology is influenced by two primary factors, including perceived usefulness and ease of use. If users perceive a technology as both useful and easy to use, they are more likely to have a positive intention to adopt it. Several studies have adopted TAM to identify significant factors affecting the intention to adopt new technology [25,30,34]. Perceived usefulness refers to the degree to which a user assumes that using EM helps achieve his or her everyday commuting goals. Perceived ease of use is applied to the degree to which a person feels it is not too difficult to use an EM. The TAM also contends that variations in perceived usefulness are mostly explained by perceived ease of use. The TAM has been confirmed to be an accurate and efficient framework for analyzing users’ adoption of technology in an assortment of scenarios by earlier studies [34]. Applying it to EMs acceptance could help stakeholders predict adoption rates and usage patterns, thereby aiding in planning and decision-making. Thus, the present study considered the simplified TAM model positing the positive relation from perceived ease of use to perceived usefulness and the positive relation between perceived ease of use and perceived usefulness with behavioral intentions to adopt EMs (i.e., H1–H3).
H1. 
PU is positively linked with BIU towards using EMs.
H2. 
PEU is positively linked with BIU towards using EMs.
H3. 
PEU is positively linked with PU.
While TAM provides a basic structure, it is also flexible enough to be customized for specific contexts. Additional variables, such as environmental concern and perceived value, can be integrated into the model to make it more applicable to EM adoption. Subsequently, the study extended the TAM by adding environmental concerns (EC) and perceived value (PV), positing a positive influence on behavioral intentions to buy EMs. Relying on the TAM specifications [25,26], behavioral intentions to adopt the EMs led to the propensity of the participant to use the EMs.

2.2. Perceived Value (PV)

Perceived value is a trade-off between the received benefits and sacrifices. Where perceived benefits relate to positive consequences brought by a specific product (feelings of usefulness, ease-of-use, and entertainment), and perceived sacrifices relate to what is given up to enjoy that product (risk, effort) [35]. Previous Studies indicate these elements of perceived benefits and perceived sacrifices can be direct factors affecting users’ willingness to use products [36]. Consumers’ pursuit of marketing exchange is centered on PV. Although there are many different PV definitions, the following is the most common one: PV is a consumer’s estimation of the subjective value of a particular activity or item, taking into account all net benefits and consumption costs. The degree to which consumers value a product’s offering will determine how widely that product is used [30]. PV is the understanding by the customer of the perceived interest in any action or item, taking into account the net benefits and costs of consumption, consistent with previous studies [35,36]. Considering the facts, the present study proposes that perceived value is an influencing factor for the intentions to use EMs and postulates Hypothesis 4.
H4. 
PV is positively linked with BIU.

2.3. Environment Concern (EC)

EC states consumers’ consideration of the environment, including their thoughts and concerns about the environment’s condition. Consumers who care about the environment consider how their actions affect the environment while making decisions [37]. Additionally, consumers concerned about environmental quality frequently assess how items affect the environment. They favor learning about and enhancing the environmental benefits of more ecologically friendly options [21]. EC is characterized as the degree to which people are aware of and promote attempts to solve environmental problems or can make a personal commitment to the solution of environmental problems [3]. EMs are much more ecofriendly than traditional motorcycles. Thus, the present study formulates the 5th hypothesis.
H5. 
EC is positively linked with behavioral intention toward using EMs.
After reviewing the literature and carrying out the in-depth interview, the present study postulated the following hypothesis, as indicated in (Figure 1).

3. Materials and Methods

3.1. Questionnaire and Measures

A questionnaire survey was designed to collect data to verify the conceptual model explained in (Figure 1). A brief introduction about the EMs’ characteristics with an ethical statement to use the respondent’s information only for academic research purposes was provided at the beginning of the questionnaire. The remaining parts of the questionnaire were related to the respondent’s demographic details and the items to measure latent factors involved in the present study.
The respondent’s demographic details include gender, age, education, income, motorcycle ownership, and occupation. The items to measure perceived usefulness (PU), perceived ease of use (PEU), perceived value (PV), environmental concerns (EC), and behavioral intention to use EMs (BIU) were adapted from previous studies as mentioned in Table 1 [26,34,38]. A five-point Likert scale varying from strongly disagree to strongly agree was used to measure the items for the latent constructs.
In connection with prior studies, the scale used to measure latent constructs involved in the present study was developed. A pilot survey was conducted in the beginning with 23 respondents for the selection of reliable and valid items associated with the latent constructs. In light of the pilot survey results and expert opinions, a carefully selected list of items explained in (Table 1) was finally exposed to the general audience to collect their responses.

3.2. Data Collection

The high motorcycle dependency of Asian cities [9] and the lack of research on EMs from countries such as Pakistan motivated researchers to consider Karachi metropolitan city as the study area. Karachi is the largest city in Pakistan, experiencing continuous population growth and industrial development, yielding excessive dependence on road transport and causing noise pollution [39]. The share of motorcycles in Karachi varies by 30–40% of the total vehicle fleet running on the roads. An online questionnaire survey was conducted in Karachi, Pakistan, by Google Forms. The early users of Internet facilities are educated people who are familiar with the online survey. Therefore, it is appropriate to treat them as the main targets of our survey, so the questionnaire was spread via the Facebook pages of colleges and universities. Following previous studies [40,41], this study used convenience sampling, and respondents were contacted through various online platforms, including LinkedIn, Facebook, emails, and WhatsApp. 260 respondents agreed to participate voluntarily in the survey. The collected data were further screened to remove incomplete and invalid questionnaires. The responses were considered invalid, if incomplete, or those where respondents had chosen the same choice for all the questions, constituting a zero standard deviation [21]. The data cleaning yielded 228 valid responses for further analysis. The sample size was sufficient for the analysis, as validated using Cochran’s formula with a 5% precision level and 95% confidence interval [42]. It is also analogous to the marginally varying sample sizes in previous studies [8] and other recent studies conducted in Pakistan using the UTAUT technique [43,44].

3.3. Descriptive Statistics of the Respondents

The distributions of the respondent’s age, gender, education, household income, and motorcycle ownership are described in Table 2. Descriptive statistics showed that 89.04% of the respondents were male and 10.96% were female. The lower ratio of female respondents is because it is a rare endeavor in conservative Pakistan, where women dare not ride a motorcycle [45]. A total of 43.8% earn a monthly income of more than 50,000 PKR (1 USD = 167.18 PKR), 29.82% earn between 20,000 and 50,000 PKR, and 26.32% earn less than 20,000 PKR. The classification of respondents who had two-wheeler motorcycles includes: 44.30% had one motorcycle, 30.70% had two motorcycles, 18.86% had three or more than three motorcycles, and only 6.14% had no motorcycle.

3.4. Analytical Approach

The study adopted the structural equation modeling (SEM) approach by considering its suitability to test the hypothesis positing a relationship among latent constructs [46] and is also consistent with previous studies [8,47,48]. A series of models were built to identify the contributions of standard and extended components, such as PV and EC, in TAM to predict the intentions to adopt EMs. The maximum likelihood (ML) was chosen to perform SEM in R using the Lavaan package [49,50,51]. All items in the data were normally distributed based on the skewness and kurtosis indexes, indicating the fulfillment of the assumption to perform ML-based SEM [51,52]. Confirmatory factor analysis was performed, followed by path analysis to generate structural models to verify the postulated hypothesis and explain the relationships among perceived ease of use, perceived usefulness, perceived value, and environmental concerns with behavioral intentions to adopt the EMs. The explanatory power of the structural models generated through SEM analysis was assessed by multiple indicators, including absolute fit measures, incremental fit indices, and parsimony fit indices [46].

4. Results

4.1. Measurement Model

As a prerequisite to SEM, it is necessary to confirm the reliability and validity of factors to perform structural equation modeling [53]. Thus, conformity factor analysis (CFA) was performed by examining all items’ reliability and discriminant validity as factors to fix the measurement model [34]. The values of Cronbach’s alpha and composite reliability (CR) for all constructs were evaluated and found to be in an acceptable range (Cronbach alpha > 0.6) to confirm the reliability of the measurement model [54]. For further assurance, factor loading and average variance extracted (AVE) were calculated for each construct, which was also confirmed to be in an acceptable range of higher than 0.5 [44], as shown in (Table 3). To test possible common method bias, Harman’s single-factor method was used [55], in line with the previous studies [56,57,58]. Through unrotated exploratory factor analysis, it was examined that all the items in a single factor account for only 42.3% of the variance, which is less than the benchmark value of 50%. Thus, the results indicate that common method bias might not be a serious problem for this data.
The discriminant validity of the measurement model was measured through the Fornell–Lacker criterion [59]. According to the criterion, the measurement model can achieve discriminant validity when the correlations of all constructs arranged in matrix form are lower than the square root of AVE values arranged in a diagonal of the matrix, as indicated in (Table 4). In the literature, it has been discussed that the sample size and the number of variables can impact the values of statistical tests used to evaluate the fit indexes of the model [60]. Thus, absolute fitness can be measured by the ratio of χ2 to the degree of freedom (df), goodness-of-fit (GFI), adjusted goodness-of-fit (AGFI), standard root mean square residual (SRMR), and root mean square error of approximation (RMSEA), as shown in (Table 5). All of the fit indices were considered satisfactory to accept the measurement model.

4.2. Structural Models

To test the postulated hypothesis in the conceptual model, two structural models were developed by using a simplified TAM model referred to as Model 1, and its extension by adding environmental concerns and perceived value, referred to as Model 2. In other words, Model 1 contains only the first three hypotheses, H1, H2, and H3, describing the relationship between perceived usefulness, perceived use, and behavioral intentions to adopt EMs. Model 2 evaluates all hypotheses (H1–H5) involved in the present study by extending the simplified TAM with the addition of environmental concerns and perceived value to predict the behavioral intentions to adopt the EMs. All models’ goodness-of-fit indices satisfy the cutoff values indicated in (Table 5). However, Model 2, with all the latent factors, has shown more explanatory power as compared to the simplified TAM model (Model 1).
The path relationships estimated by performing SEM analysis through the Lavaan package for simplified TAM-based Model 1 are presented in (Figure 2) all the casual paths associated with Model 1 are in line with the hypothesis developed in the conceptual model. To be specific, perceived usefulness is positively related to the behavioral intentions to adopt EMs (β = 0.84, p < 0.001), in line with Hypothesis H1, as shown in (Figure 2). Likewise, Hypothesis H2 is also supported by empirical results indicating a positive relationship between perceived ease of use and behavioral intentions to adopt EMs (β = 0.44, p < 0.01). Hypothesis H3 was also confirmed in Model 1, indicating a positive effect generated by perceived ease of use towards perceived usefulness regarding EMs. The simplified model suggests that individuals who highly perceive EMs usefulness and ease of use tend to have higher intentions to adopt EMs in the future. Model 1 is a simplified TAM model and provides an insightful understanding of the behavioral intentions to adopt EMs. Still, the main focus of the research was to extend this model by adding EC and PV regarding EMs to predict behavioral intentions. Thus, Model 2 has been prepared to check all hypotheses combined in one structural model and is presented in (Figure 3).
The path relationships for the extended TAM with the addition of environmental concerns and perceived value are presented in (Figure 3). The results indicate support regarding the positive influence of all of the hypotheses developed in the conceptual model. However, Hypothesis H2 was not supported by the current dataset. The stronger effects generated by environmental concerns and perceived value on the behavioral intentions to adopt EMs may lead to vanishing the direct effects of perceived ease of use. In line with Hypothesis H1, perceived usefulness regarding EMs was found to have a positive influence on behavioral intentions to adopt EMs (β = 0.21, p < 0.1). Hypothesis H3 was also confirmed, as perceived ease of use was found to have a significant and positive effect on perceived usefulness (β = 0.85, p < 0.001). Similarly, the results confirmed Hypotheses H4 and H5, indicating the positive influence of perceived value (β = 0.52, p < 0.001) and environmental concerns (β = 0.35, p < 0.001) on the behavioral intentions to adopt EMs. Furthermore, the direct effects of environmental concerns and perceived value on behavioral intentions to adopt EMs were stronger compared to the direct effects generated by perceived usefulness. Empirically, results indicate that an individual with high perceived value and environmental concerns will have higher behavioral intentions to adopt EMs.

5. Discussion

The dominant presence of conventional vehicles in developing countries propelled researchers to search for ways to help the penetration of environment-friendly alternatives, such as EMs [6]. This study attempted to uncover the psychological determinants of adopting EMs for guiding policy interventions to accelerate the penetration of EMs in Pakistan. Moreover, it seeks to verify the application of the technology acceptance model (TAM) extended with the addition of environmental concerns and perceived value to predict the behavioral intentions to adopt EMs. Thus, the findings of the study provide an insightful vision for the players interested in the development of marketing strategies for EM sales in developing countries. Moreover, the study also reveals the importance of environmental concerns and the perceived value of adopting EMs compared to their perceived usefulness.
The study provided evidence supporting the positive effects of perceived ease of use, perceived usefulness, environmental concerns, and perceived value on behavioral intentions to adopt EMs, consistent with previous studies [7]. However, the extended TAM model only supports the indirect effect of perceived ease of use on EMs. The findings suggest that an individual with significant environmental concerns and a high perceived value for EMs is more likely to purchase EMs. Similarly, an individual who perceives EM usefulness as high will be more likely to be involved in EM adoption. Nevertheless, perceived ease of use was not found to be significantly related to behavioral intentions to adopt EMs in extended models due to the stronger effects generated by environmental concerns and perceived value.
The significant and positive effects generated by environmental concerns toward behavioral intentions to buy EMs indicate the importance of increasing environmental awareness. Countries may have varying adoptions of EMs, which may contribute to promotional or containment policies. For example, authorities in Asia’s large motorcycle markets could anticipate significant environmental benefits (less air and noise pollution) by shifting from traditional motorcycles to EMs [9,11].
The empirical results suggested that the increase in perceived usefulness has direct positive effects on behavioral intentions to adopt EMs [12]. The initiatives to teach the EMs’ functions and strengthen the knowledge regarding EMs may help in increasing the perceived usefulness of EMs. Individuals with more knowledge regarding the functionality of EMs may be more likely to adopt EMs, as suggested by the study findings. The perceived ease of use significantly increases the perceived usefulness of EMs. The positive awareness about speed, range, and electricity consumption of EMs may likely increase the perceived usefulness and then the behavioral intentions to adopt them. Thus, social media campaigning, promotional messages, advertisements, and educational interventions may need to spread awareness regarding the EMs’ features to help individuals adopt EMs by increasing perceived usefulness and ease of use.

6. Conclusions

This study verified the application of the TAM model with the addition of environmental concerns and perceived value to explain the effects of psychological determinants on behavioral intentions to adopt EMs. The study contributes to the existing literature through a comparative discussion on PV and EC in predicting the behavioral intentions to adopt EMs and enhances the current understanding of EM adoption in the context of Pakistan, which was not highlighted in previous research. Pakistan’s National Electric Vehicle Policy targets shifting 50% of two-wheeler sales to the EMs [22]. This study aims to suggest implications and marketing strategies for enhancing the EMs’ market penetrations to achieve EV policy goals. To achieve the aims, a questionnaire survey method was adopted to collect data to test hypotheses. The structural equation modeling (SEM) approach was employed to identify the influence of perceived ease of use, perceived usefulness, PV, and EC on people’s behavioral intentions to adopt the EMs. In this way, the study uncovers an essential issue of EM adoption in developing countries with little e-mobility, such as Karachi, Pakistan. Relying on the questionnaire survey data from Karachi, Pakistan, the study provides a brief insight into the factors that have the potential to bring about behavioral change in the locals to adopt EMs. The present study highlights the importance of environmental concerns and perceived value in increasing consumers’ intentions to adopt EMs. It may help market companies and transport agencies target the promotion of EMs with special attention to perceived usefulness, perceived ease of use, environmental benefits, and perceived value of EMs.

6.1. Theoretical Implications

This study delves into the critical issue of enhancing the adoption of electric motorcycles (EMs) in developing countries, particularly Pakistan. The theoretical framework, based on the extended technology acceptance model (TAM), incorporates the elements of environmental concerns and perceived value alongside perceived usefulness and perceived ease of use to predict behavioral intentions to adopt EMs. The findings of this research carry significant theoretical weight, offering valuable insights for stakeholders interested in developing marketing strategies for EMs in developing nations. Furthermore, it underscores the primacy of environmental concerns and perceived value over perceived usefulness in driving EM adoption, providing a nuanced perspective on technology acceptance theories.
The study’s empirical evidence supports the positive influence of perceived ease of use, perceived usefulness, environmental concerns, and perceived value on behavioral intentions to adopt EMs, however, this extended TAM model unveils that perceived ease of use indirectly impacts EM adoption. The pronounced effects of environmental concerns and perceived value overshadow the influence of perceived ease of use, emphasizing the role of psychological factors in vehicle technology adoption decisions. This theoretical insight highlights the need for heightened environmental awareness and tailored policies for regions with varying EM adoption potential, especially in large motorcycle markets in Asia.
Empirical findings further emphasize the direct positive relationship between perceived usefulness and behavioral intentions to adopt EMs. Initiatives aimed at educating individuals about EM functionality and enhancing knowledge regarding EMs can significantly boost the perceived usefulness of EMs, fostering greater adoption rates. Importantly, perceived ease of use positively affects perceived usefulness, and raising awareness about EM features, such as speed, range, and electricity consumption, through channels, such as social media campaigns, promotional messages, advertisements, and educational interventions can further enhance the perceived usefulness and ease of use, ultimately encouraging EM adoption.

6.2. Practical Implications

In practical terms, this study offers actionable insights for public and private agencies tasked with promoting e-mobility in developing countries, particularly those with low EM penetration, such as Pakistan. Crafting a targeted marketing strategy aimed at shifting individual behaviors towards EM adoption becomes essential. Financial incentives alone may not suffice, and therefore, additional support mechanisms for EMs must be considered. These measures encompass entry restrictions for conventional vehicles, tax breaks, preferential parking, road toll exemptions, driving license requirements, preferential license plate issuance, reduced electricity rates, and service incentives. Highlighting the environmental benefits of EMs in promotional efforts and implementing educational interventions to raise awareness of environmental degradation caused by fuel-based motorcycles are recommended strategies to strengthen individuals’ environmental concerns and drive EM adoption.
Moreover, practical stakeholders should focus on enhancing the perceived value of EMs over ease of use, as the study findings underscore the greater influence of environmental concerns and perceived value on behavioral intentions. Tailoring marketing messages to accentuate these aspects is likely to yield more effective results. Policymakers should acknowledge regional disparities in EM adoption potential and adapt promotional and regulatory policies to cater to the specific preferences of diverse areas within the country. Initiatives that educate the public about EM functionality and benefits hold promise for enhancing the perceived usefulness of EMs, ultimately increasing adoption rates. Employing social media campaigns, promotional messages, advertisements, and educational interventions to disseminate information about EM features can be instrumental in this regard. Additionally, simplifying the use of EMs through user-friendly design and clear instructions can enhance their perceived usefulness and appeal to potential adopters, ultimately fostering greater EM adoption.
A developing country, such as Pakistan, has extensive domination of males to ride motorcycles [20]. However, most of the females have been seen as pillion riders on motorcycles. This unique demographic representation was accumulated in this study by over-representing the male respondents in the sample. However, we acknowledge this limitation of the study to generalize the results at a broader level. A large sample with a more generalizable representation of gender may enhance the applicability of the results and is thus suggested for future studies. In line with the scope of this study, Karachi City, with its large number of two-wheelers causing traffic and environmental issues, was given focus to discuss the case of EM adoption. Future studies can include other metropolitan cities, such as Lahore, Islamabad, and Peshawar, to confirm and compare the trends of EV adoption. Furthermore, future studies should explore the effects of BIU on EMs under different scenarios with the addition of more latent factors. Though EM adoption will provide an environment-friendly alternative for travelers, EMs still have limited potential for commute trips. Therefore, EM’s potential to be used in combination with public transportation should be explored in future studies.

Author Contributions

Conceptualization, methodology, software, validation, formal analysis, investigation, data curation, and writing—original draft preparation, S.S. and F.B.; resources, writing—review and editing, visualization, supervision, project administration, and funding acquisition, S.H.K., M.A.H.T. and F.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The datasets generated during and/or analyzed during the current study are not publicly available due to data privacy reasons.

Acknowledgments

The authors acknowledge the kind support of Dong Zhang and Hong-feng Xu in designing this study. The authors are also thankful to the Dalian University of Technology, China for providing technical resources to conduct this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Wevj 14 00278 g001
Figure 1. Conceptual model.
Figure 1. Conceptual model.
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Figure 2. Path diagram for Model 1, Note: *** p < 0.001; ** p < 0.01; * p < 0.05.
Figure 2. Path diagram for Model 1, Note: *** p < 0.001; ** p < 0.01; * p < 0.05.
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Figure 3. Path diagram for Model 2, Note: *** p < 0.001; * p < 0.05.
Figure 3. Path diagram for Model 2, Note: *** p < 0.001; * p < 0.05.
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Table 1. Construct with their respective items.
Table 1. Construct with their respective items.
Construct with ItemsSource
BIU
BIU-1Assuming I had access to EMs I intend to use it.[26]
BIU-2If I had access to Ems, I predict that I would use them.
BIU-3Overall, I intend Ems to be a reliable mode of transport.
PU
PU-1I think using EMs would allow me to be more productive.[38]
PU-2I believe that I would find EMs useful for riding.
PU-3I feel using EMs would be easier to ride than a car.
PU-4I think I will continue to use a motorcycle despite the high fuel prices.
PEU
PEU-1I think learning to operate EMs would be easy for me.[34,38]
PEU-2I believe my interaction with EMs would be clear and understandable.
PEU-3I think it would be easy for me to become skillful at using EMs.
PEU-4I believe I would find EMs easy to use.
PV
PV-1EMs will make me feel good.[34]
PV-2EMs will provide me pleasure.
PV-3EMs will make me want to use them.
PV-4I will feel comfortable using EMs.
EC
EC-1I have the responsibility to adopt a low-carbon mode of transportation.[34]
EC-2I want to preserve the environment.
EC-3I want to buy EMs because of the air pollution crises.
EC-4EMs contribute to saving the environment for the next generation.
Table 2. Social demographic characteristics.
Table 2. Social demographic characteristics.
Demographic VariableObservationsPercentage
(%)		Demographic
Variable		ObservationsPercentage (%)
GenderIncome
Male20389.04Less than 20 K-PKR6026.32
Female2510.9620–50 K-PKR6829.82
More than 50 K PKR 10043.86
Age Motorcycles owned by the family
18–3014560.600146.14
31–405825.440110144.30
41–50159.58027030.70
51 and over31.3203 or more4318.86
EducationOccupation
Junior college187.89Student3515.35
Bachelor7030.70Govt. Employee5423.68
Masters7934.65Private employee7633.33
Ph.D.6126.75Businessman3013.17
Other3314.47
Table 3. Reliability and validity of the measurement model.
Table 3. Reliability and validity of the measurement model.
ConstructsItemsFactor LoadingsCronbach’s AlphaCRAVE
BIUBIU-10.7340.7670.7750.526
BIU-20.770
BIU-30.671
PUPU-10.8080.8040.8160.604
PU-20.827
PU-30.695
PU-4Removed
PEUPEU-10.7820.9050.9060.711
PEU-20.824
PEU-30.892
PEU-40.869
PVPV-10.7380.8700.8720.628
PV-20.759
PV-30.832
PV-40.842
ECEC-10.7910.8540.8560.604
EC-20.668
EC-30.848
EC-40.784
Note: Model fits: χ2 = 271.639, df = 142, p < 0.001; χ2/df = 1.91; CFI = 0.950; TLI = 0.939; RMSEA = 0.063; SRMR = 0.046, CR = composite reliability, AVE = average variance extracted.
Table 4. Discriminant validity.
Table 4. Discriminant validity.
PEPEUPVIUEE
PU0.777
PEU0.7650.843
PV0.6030.6400.793
IU0.7110.7070.7680.725
EC0.5500.5070.4230.6970.777
Note: For discriminant validity, the diagonal elements should be larger than the off-diagonal elements. Diagonal elements are the square root of variance (AVE). Off-diagonal elements are the correlations among constructs.
Table 5. Goodness-of-fit indices for all constructed models.
Table 5. Goodness-of-fit indices for all constructed models.
Fit IndexModel 1Model 2Critical Value
Absolute fit measures
X2/DF2.081.971<3.00
RMSEA0.0690.065<0.08
SRMR0.0420.050<0.08
GFI0.9460.904>0.90
AGFI0.9070.907>0.90
Incremental fit measures
NFI0.9520.906>0.90
CFI0.9740.951>0.90
TLI0.9640.941>0.90
Parsimony fit measure
PGFI0.5500.664>0.50
PNFI0.6770.752>0.50
Note: Chi-square/degree of freedom (X2/DF), root mean square error of approximation (RMSEA), goodness-of-fit statistic (GFI), adjusted goodness-of-fit (AGFI), standard root mean square residual (SRMR). Normal-fit index (NFI) and comparative fit index (CFI). Parsimony fit indices: Parsimony goodness-of-fit (PGFI), parsimonious normed fit index (PNFI).
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MDPI and ACS Style

Shaikh, S.; Talpur, M.A.H.; Baig, F.; Tariq, F.; Khahro, S.H. Adoption of Electric Motorcycles in Pakistan: A Technology Acceptance Model Perspective. World Electr. Veh. J. 2023, 14, 278. https://doi.org/10.3390/wevj14100278

AMA Style

Shaikh S, Talpur MAH, Baig F, Tariq F, Khahro SH. Adoption of Electric Motorcycles in Pakistan: A Technology Acceptance Model Perspective. World Electric Vehicle Journal. 2023; 14(10):278. https://doi.org/10.3390/wevj14100278

Chicago/Turabian Style

Shaikh, Sajan, Mir Aftab Hussain Talpur, Farrukh Baig, Fariha Tariq, and Shabir Hussain Khahro. 2023. "Adoption of Electric Motorcycles in Pakistan: A Technology Acceptance Model Perspective" World Electric Vehicle Journal 14, no. 10: 278. https://doi.org/10.3390/wevj14100278

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