How Flexibility Helps Rapid Production of Electric Vehicles in Azerbaijan

Electric vehicles have been developed as an alternative for the conventional drive system in which the internal combustion engine is converting the chemical energies in gasoline or diesel into the mechanical energies for power (Kim & Kum, 2016). In contrast to the conventional drive system, electric vehicles are empowered with batteries functioning as an energy source (Kim & Kum, 2016). There are four types of electric vehicles, such as battery, hybrid, plug-in, and fuel-cell electric vehicles (He et al., 2012).

The first firm of electric vehicles is regarded as battery run electric vehicles, in which batteries serve as an only source of energy (Fig. 1). When the battery electric vehicles are charged fully, they can cover between 100 and 250 km; however, the covering capacity of the respective vehicles is conditional to climate, road condition, and age of battery (He et al., 2012). In this regard, the capacity of batteries determines the capability of the vehicles. Once the battery of electric vehicles is completely depleted, it takes hours for the electric batteries to recharge, which is quite a long period of time as opposed to the time with conventional drive systems for fuel replenishment (He et al., 2012). Battery electric vehicles are characterized as environmentally friendly vehicles as they do not cause noise pollution or greenhouse gas emission (He et al., 2012).

In hybrid electric vehicles, the passenger cars are equipped with two engine systems, such as internal combustion engine system and electric propulsion system. The internal combustion engine is used in the passenger cars when the higher speed and energy is demanded (Yang et al., 2018). In such cases, the hybrid electric vehicles switch to the internal combustion engine. However, in the conditions requiring the lower speeds, the hybrid electric vehicles switch to the electric propulsion engine, such as, in case of traffic in urban areas (Hasan et al., 2022a, 2022b; Yang et al., 2018). The hybrid electric vehicles produce less greenhouse gas and noise pollution compared to the conventional vehicles (Yang et al., 2018). Besides, in the hybrid electric vehicles, the internal combustion engine functions as a charger of the electric batteries. In particular, the electric batteries in hybrid electric vehicles are recharged via a regenerative braking system during using the internal combustion engine (Fig. 2). Hybrid electric passenger vehicles can recharge the battery packs via means of internal combustion engine, which saves the time and cost for the customers compared to the battery electric vehicles. In this system, the internal combustion system is the principal driving force of the hybrid vehicles compared to the battery electric vehicles.

Another form of electric vehicles is regarded as plug-in electric vehicles, in which the internal combustion engine and electric power systems are combined for generating driving force. In this case, plug-in versions of hybrid electric vehicles utilize the internal combustion engine and energy propulsion systems for power-generation. In contrast to the hybrid vehicles, the principal driving force in the plug-in version is the electric motor (Ellingsen et al., 2016). In the plug-in electric vehicles, the electric power is used to start and run the vehicle and once the capacity of electric batteries is low, the system switches to the internal combustion engine for providing the boost and recharging the electric batteries (Fig. 3). However, in hybrid electric vehicles, the power generated from an internal combustion engine via gasoline or diesel is used for starting and running the vehicle, and switching to the electric motors once the condition, battery capacity and willingness of the driver are combined. Another principal difference between the plug-in and hybrid versions of electric vehicles is that ‘battery packs in the plug-in electric vehicles can be recharged via means of connecting the battery to the grid’ (Ellingsen et al., 2016). Furthermore, the plug-in electric vehicles produce less greenhouse gas and noise pollution compared to the hybrid electric vehicles as the plug-in version primarily uses electricity only.

The last version of electric vehicles is regarded as ‘fuel-cell electric vehicles’, in which the chemical reactions emerging in the fuel cell are used as a means for producing power for the vehicles (Camacho & Popa, 2016). In particular, the chemical reactions emerge via means of combining the hydrogen and air in the fuel cells, which generates power for electric motors (Fig. 4). The hydrogen in the fuel-cell electric vehicles is stored in a particular high-pressure tank and the oxygen is acquired from the environment air (Fig. 4). The surplus of energy generated in fuel-cell is stored in the battery pack of the passenger cars (Camacho & Popa, 2016). The principal competitive advantage of this vehicle is related to its capability of producing its own electricity via means of chemical reactions (Camacho & Popa, 2016). Accordingly, this vehicle is characterized by its zero-carbon emission in the process of generating power for motor vehicles, which reduces its carbon footprint (Camacho & Popa, 2016). Further competitive advantage of fuel-cell electric vehicles is associated with the time required for refilling the vehicles. In the case of conventional driving system, it takes few minutes to fill the hydrogen tank of the car at gas stations (Camacho & Popa, 2016).

In general, there are various forms of electric vehicles available in the current automobile industry, such as battery, hybrid, plug-in and fuel-cell electric vehicles.

Schuitema et al., (2013) analyzed the reasons leading the customers to purchase electric vehicles in the UK. The primary data of customer perspectives was gathered from the sample of 2728 electric vehicles’ users in the UK (Schuitema et al., 2013). The results of linear regression analysis ascertained that individual environmental awareness was a statistically significant predictor of the purchase decisions of electric vehicles by customers (Schuitema et al., 2013). In this context, the customers’ awareness about environmental concerns shapes their purchase behavior by leading them to purchase eco-friendly electric vehicles. Besides, the research findings presented that the financial incentives provided by the government are also detected as an important factor leading the customers to purchase electric vehicles (Ishak, et al., 2023; Schuitema et al., 2013). The government incentives via means of reductions in custom duties for electric cars and taxes imposed on oil and gasoline vehicles are statistically significant factors generating an incentive in consumers to purchase the electric vehicles (Schuitema et al., 2013). Besides, the research findings ascertained that the electric vehicles are not preferred by the certain customers, which is primarily due to their driving range which is significantly less than the conventional vehicles (Schuitema et al., 2013). According to Schuitema et al., (2013), the electric vehicles are purchased by the customers as the customers’ environmental awareness and financial incentives provided by the government. Schuitema et al., (2013) argued that if the driving range of electric cars increases compared to that of conventional cars, electric vehicles will dominate the automobile manufacturing industry across the world in the long run.

According to Carley et al. (2013), factors affecting the purchase decisions of customers regarding electric vehicles can be grouped into two clusters, namely internal and external factors. The research conducted by Carley et al. (2013) aimed to determine which internal and external factors affect the purchase decisions of electric vehicles in the USA. The research identified that the internal factors shaping the purchase decisions of customers in regard with electric vehicles include purchase price, battery cost, driving range, and electric vehicle’s charging times (Carley et al., 2013). A decline in the purchase prices, battery costs and charging times and an increase in the driving range of electric vehicles are primary determinants of the customers’ purchase of electric vehicles in the USA. Besides, there are external factors shaping the customers’ purchase decision of electric cars, which include fuel prices, environmental concerns, and networks of charging stations (Carley et al., 2013). An increase in the fuel prices, environmental concerns and networks of charging stations for electric vehicles motivate the customers to prefer electric vehicles over internal combustion engines in the USA (Carley et al., 2013). Additionally, the external factors are determinants of the purchase preferences of electric vehicles along with the internal factors.

Tu and Yang (2019) conducted a research project to identify and explain the determinants of the customers’ preferences of electric vehicles. The primary data about the customer perspectives on the performance, innovative nature and other core characteristics of electric vehicles was assembled from 300 customers of electric vehicles in China (Tu & Yang, 2019). The data found on electric vehicles was analyzed via structural equation model (SEM) (Tu & Yang, 2019). There are three key findings of the relevant research. Firstly, it was identified that the customers’ concern about the environmental impact of their purchase choices is a principal determinant of their purchase of electric vehicles (Tu & Yang, 2019). Since the electric vehicles are perceived as eco-friendly means of transportation, the customers’ concerns about environmental problems motivate them to purchase electric vehicles in China. Secondly, the research findings indicated that the acceptance of new technologies by customers is another determinant of the purchase of electric vehicles (Tu & Yang, 2019). In particular, electric vehicles are considered as new technologies on which customers lack experience and knowledge. Thus, electric vehicles’ acceptance by the customers determines the proliferation of the electric vehicles in a particular community. Finally, the recommendations of other consumers and legal regulations encouraging the use of electric vehicles are not empirical determinants of the purchase intentions of electric vehicles among the customers (Tu & Yang, 2019).

Yan et al., (2019) also assessed the reasons leading the customers to buy electric vehicles in China. In the research, the impact of hedonic and symbolic attributes on the customers’ purchase intentions of electric vehicles was analyzed through primary data gathered from 537 customers of electric vehicles in China (Yan et al., 2019). The researchers analyzed primary data via structural equation model and multi-nominal logit model. The findings reflected that hedonic motivation referring to the pleasure of using electric vehicles has a statistically significant impact on the customers’ purchase intention of electric vehicles in China (Yan et al., 2019). Besides, symbolic motivation referring to the status obtained by the customers in their community via possessing and using electric vehicles has empirically significant impact on the customers buying decision of electric vehicles (Yan et al., 2019). According to Yan et al. (2019), hedonic and symbolic motivations are determinants of customers’ purchase decision of electric vehicles in China; thus, the customers mainly buy the electric vehicles for obtaining the pleasure of driving the respective vehicles and improving their position in the community via shaping the perceptions of community members about their awareness and commitment to the environmental problems.

The present study collects the primary data about the proliferation of the hybrid electric cars in Azerbaijan. Accordingly, the study is based upon the primary data gathered from the sample of the target population. The reasons for using primary data as a means for accomplishing the research objectives in the present study are related to its better reliability and accuracy compared to the secondary data (Saunders et al., 2009).

The research strategy utilized for gathering primary data about the factors leading to the proliferation of hybrid electric cars in Azerbaijan is survey because the survey method enables to gather data from the widely dispersed sample members in a less costly and more time-saving manners (Saunders et al., 2009) (See appendix-B). One of the widespread tools of survey method, questionnaire is formulated for obtaining the primary data from the target population in the present research (see Fig. 6). The questionnaire is composed of three sections and 11 questions. The first section of the questionnaire aims to gather data about the demographic information of the respondents, such as their gender, monthly income, duration of using hybrid electric cars, and brand name of their hybrid electric cars. The second section aims to identify the willingness of customers to purchase hybrid electric cars. The final section of questionnaire concentrates on determining the reasons leading the customers to purchase hybrid electric cars. The established questionnaire is distributed among the target population via means of social media platforms, such as Facebook, LinkedIn and WhatsApp.

The variables for assessing the relationship between the performance of hybrid electric cars and customer behaviors are divided into two clusters. The first one is labelled as independent variables, which included the indicators of the performance of hybrid electric cars in comparison with conventional cars (Table 1). The second one is regarded as dependent variables, which contained indicators of customer behavior toward the hybrid electric cars (Table 1). Thus, the regression analyses are undertaken to illustrate the impact of chosen independent variables on the dependent variables in this study.

The target population of the present study has two primary characteristics. The individuals who are currently possessing the hybrid electric cars is the first characteristics of the target population in the present study. The second one is that the individuals who are residing within the domestic environment in Azerbaijan. Thus, the target population of the research is the present users of hybrid electric cars in Azerbaijan. The absence of complete list of the target population makes it difficult to construct the sample of the target population via means of probability sampling method (Saunders et al., 2009). Accordingly, the sample of target population is formulated via means of non-probability sampling method. In particular, the snowball non-probability sampling technique is used to construct the sample for representing the target population in this study (Saunders et al., 2009). In particular, the sample members are asked to share the online questionnaires of the present study with others who are possessing and using hybrid electric vehicles in Azerbaijan. The sample in the study consisted of 121 possessors of hybrid electric cars in Azerbaijan.

This kind of qualitative research non-response bias a big issue. To eliminate or minimize the non-response bias, we used four different techniques, firstly, we thoroughly pretest our survey mediums, to do that we conduct a focus group, we first identify 5–10 participants from the target populations. Finding individuals as close to the target group as feasible allowed us to be a little more flexible. Once a focus group has been established, hold a fruitful discussion under the direction of a moderator to gain more insights regarding the survey's format. This includes the survey's objectives and concepts, the burden on respondents, and how sensitive the subject is to them. We make sure that each focus group participant completes the survey on their own, without watching others do it. They should complete this pre-test survey exactly as they would if they were doing the final version, which might take the shape of an online survey or live interviews with trained interviewers. Most crucial, encourage the participants to think aloud by asking them to describe their thoughts whenever they read or hear one of the questions. Secondly, we avoid rushing and provided our populations more time to complete the survey (3 months). Thirdly, we send reminder to our potential reminders, because we have collected a list of hybrid car users in Azerbaijan from the database and finally, we ensued that all the personal data will be confidential.

By taking a number of preventative actions during the research design phase, it may be possible to rule out ex-ante the likelihood of common method bias appearing in an internet commerce survey. The optimal approach is to collect information about the model's structures from two or more sources. To minimize the common method bias we used three different social media platforms to collect out data.

The primary data for determining the reasons leading to the proliferation of hybrid electric cars in Azerbaijan was analyzed and the interpretations of the results of analyses from the descriptive statistics and regression analysis were presented in this chapter.

Figure 7 demonstrates the results for the percentage of the sample members belonging to one of two gender groups. The results of descriptive statistics indicate that the highest percent of sample members belonged to the cluster of male respondents, as 78.5% of the users of hybrid electric cars that participated in the survey of this study highlighted their gender as being male (Fig. 7). Besides, the remaining percentage of sample members belonged to female cluster in the current study. The main reason for such a high disparity between female and male respondents in the sample was related to increasing popularity of driving a car among the female portion of population in Azerbaijan in recent years. There is a gender bias in the drivers in the current domestic community of Azerbaijan, which is primarily due to the cultural norms and perceptions associating driving a car with male portion of population. However, the sample had enough percentage of female drivers who could channel the perceptions of the female customers about the reasons for proliferation of hybrid electric cars in Azerbaijan (Fig. 7).

Figure 8 shows the allocation of customers of hybrid electric cars in Azerbaijan who participated in the survey of this study based on their monthly income. The outcome of descriptive statistics shows that the highest percent of sample members belonged to the second cluster of monthly income, as 38.5% of customers of hybrid electric cars in Azerbaijan who participated in this survey earned the income level between AZN 700 and AZN 1000 (Fig. 8). The sample also included customers of hybrid electric cars in Azerbaijan, who belonged to various income clusters, including low-, middle-, and high-income levels. Thus, the generated primary data represented the perspectives of individuals from the group of each income level about the reasons leading to the proliferation of hybrid electric cars in Azerbaijan.

Figure 9 displays the allocation of the customers of hybrid electric cars in Azerbaijan who participated in the study based on their duration of using the respective vehicles. The findings indicate that the highest percent of customers responded to the survey belonged to the third cluster of customers because 44.7% of customers highlighted that their usage of hybrid electric cars ranged between 13 and 18 months at the time of assembling data for this study (Fig. 9). Furthermore, only 6.6% of customers of hybrid electric cars in Azerbaijan that participated in the survey of this study were less experienced about performance indicators of hybrid electric cars due to their current purchase of hybrid electric cars (Fig. 9). As more than 97% of participants in the survey have been using hybrid electric cars over 6 months at the time of assembling primary data for this study, it could be assumed that the sample of customers possessing hybrid electric cars in Azerbaijan was experienced enough to represent the target population via indicating their extent of satisfaction with the performance of hybrid electric cars.

Figure 10 illustrates the results of allocating the sample into clusters based on the type of hybrid electric cars possessed by the relevant customers. The outcome of descriptive statistics illustrates that 47.9% of sample members possessed Toyota branded hybrid electric cars at the time of assembling primary data for this study (Fig. 10). There were also the significant percent of the customers of Ford branded hybrid electric cars in the sample of this study, as 21.5% of sample members possessed Ford labelled hybrid electric cars in the process of assembling primary data for this study (Fig. 10). The main reason that led to the disparity between the clusters of customers of Toyota and Ford branded hybrid electric cars and other brand hybrid electric cars could be due to the popularity of Toyota and Ford brands among the customers in Azerbaijan. The customers in Azerbaijan could prefer the Toyota and Ford branded hybrid electric cars over others because of their brand value, as Toyota and Ford corporations have the brand reputation of high quality and performance in the global automobile industry in regard with hybrid electric cars compared to other hybrid electric cars manufacturing brand companies. Thus, the research findings in the study primarily represent the perspectives of customers of Toyota or Ford branded hybrid electric cars in Azerbaijan.

The reasons leading to the proliferation of hybrid electric cars among the customers in Azerbaijan were identified through linear regression analysis in the study. Hence, the regression model is generated for each customer behavior in the current study to analyze how the performance indicators of hybrid electric cars affect the customer behavior in Azerbaijan. The first framework of regression model is assumed to identify the impact of performance-related characteristics of hybrid electric cars on the customer behavior in Azerbaijan. The respective framework is shown in Table 2:

Table 3 illustrates the outcomes of the data analysis for first regression framework.

Table 3 illustrates the results of data analysis for the initial regression model, including r-square, coefficients and significance levels of dependent variables. R-Square of model is estimated at 0.956, implying that the independent variable in the constructed model predicts 95.6% of alterations in the chosen dependent variable, which is more than sufficient level of R-square, like 0.7 (Table 3). Thus, it could be assumed that our first regression model in the study predicts the changes in the consumer behavior because the selected independent variables predict the alterations in repurchasing behavior of customers of hybrid electric cars. In the constructed model, two independent variables, such as perceived usefulness and perceived ease of use have significance levels less than 0.05, meaning that the perceived usefulness and perceived ease of use as two indicators of performance of hybrid electric cars have empirically significant connection with repurchasing behavior of customers (Table 3). The coefficients of those predictors, such as perceived usefulness and perceived ease of use of hybrid electric cars are 0.927 and 0.064, implying the positive correlation between the respective predictors and repurchasing behavior of customers (Table 3). In this regard, a growth in the level of either perceived usefulness or perceived ease of use of hybrid electric cars are also accompanied by a growth in the repurchasing behavior of customers of the respective cars. Therefore, H₁ of study emphasizing the existence of statistically positive connection between perceived usefulness and purchase intention of customers of hybrid electric cars and H₂ of study highlighting the existence of empirically positive nexus between perceived ease of use and purchase intention of customers of the respective cars in Azerbaijan are verified in the present study. Accordingly, it can be assumed that the consumers’ intention of repurchasing hybrid electric cars in Azerbaijan is shaped by the perceived usefulness and perceived ease of use of the respective vehicles.

The second regression model is developed to appraise the influence of performance-indicators of hybrid electric cars on another characteristics of consumer behavior, such as purchase of new versions of the respective cars. The framework of the relevant regression model is illustrated in Table 4:

The outcomes of the second regression framework are presented in Table 5. The R-Square of the framework is 0.748, implying that the chosen performance-indicators of hybrid electric cars, such as perceived usefulness and ease of use, compatibility and complexity predict 74.8% of the modifications in the purchase intention of consumers in case of availability of new and innovative versions of hybrid electric cars (Table 5). Thus, it can be assumed that the developed framework is suitable to demonstrate the connection between performance of hybrid electric cars and customers’ willingness to purchase the corresponding cars. There are three predictors that have statistically significant connection with the purchase intention of customers in case of availability of new and innovative versions of hybrid electric cars in the marketplace, which are perceived usefulness and ease of use and compatibility of the respective cars because their significance levels are less than 0.05 (Table 5). In addition, the coefficients of relevant predictors are 0.311, 0.221 and 0.443, respectively, meaning the positive correlation between them and the customers’ purchase intention of new and innovative versions of hybrid electric cars. Therefore, the positive growth in the level of perceived usefulness, perceived ease of use or compatibility of hybrid electric cars is accompanied by a positive improvement in the customers’ purchase intentions of hybrid electric cars. Accordingly, in addition to H₁ and H₂, H₃ of the study, which highlights the positive nexus between customers’ purchase intentions and compatibility of hybrid electric cars are verified in the study. Thus, it can be assumed that the customers’ purchase intentions of new and innovative hybrid electric cars are positively affected by the perceived usefulness, perceived ease of use and extent of match between actual and expected performance (compatibility) of the respective vehicles.

The last regression framework is built to bring out the impact of performance-indicators of hybrid electric cars on another aspect of consumer behavior, such as their likelihood of recommending the hybrid electric cars to others. The third regression model is illustrated in Table 6:

The results of the third regression framework are demonstrated at Table 7. The developed regression model is capable of forecasting the modifications in the dependent variable, such as the willingness of customers to recommend hybrid electric cars to other customers because R-Square of model is 0.895 (Table 7). Therefore, 89.5% of alterations in the level of customers’ willingness to suggest the hybrid electric cars to other customers can be predicted by the chosen indicators of performance of the respective cars (Table 7). Besides, there are three predictors that are empirically related to the customers’ likelihood of recommending hybrid electric cars, which are perceived usefulness, perceived ease of use and compatibility of the corresponding cars, as their significance levels are less than 0.05 (Table 7). Also, their coefficients are 0.023, 0.880, 0.092, meaning the positive nexus between them and customers’ willingness to suggest hybrid electric cars to others (Table 7). The positive coefficients of three predictors denote that a growth in the level of one of the relevant predictors is accompanied by a growth in the level of customers’ intention to recommend the hybrid electric cars to others. Therefore, the first three hypotheses of research, H₁ H₂, and H₃ are verified because of the statistically positive and empirically significant connection between perceived usefulness, perceived ease of use, and compatibility of hybrid electric cars and the customers’ willingness to suggest the respective cars to others. In this regard, it can be claimed that the customers’ likelihood of offering hybrid electric cars to other drivers is determined by their perceptions about usefulness and ease of use of the respective cars and the match between expected and actual performance of the corresponding cars.

The research outcomes indicated that the customers’ perceptions about the usefulness of hybrid electric cars in Azerbaijan were a critical determinant of the consumers’ purchase intentions of the respective vehicles. In particular, the thoughts of consumers about the hybrid electric cars as being a useful means of transporting them to their destinations affect their intention of repurchasing exactly the same vehicles or replacing them with their new and innovative types, this finding is in line with the previous literature (see, Albatayneh et al., 2020; Hasan & Islam, 2022). Besides, the research findings displayed that the customers’ perceptions about ease of use of hybrid electric cars were also a critical determinant of customers’ purchase intentions. In this regard, once customers perceive that using hybrid electric cars can be easily learned by its users, the customers’ willingness to repurchase the respective cars, to buy their new versions or recommending them to other customers increase relatively. There are lots of reason could be involved for this decision and recommendation, one of them is the change of the weight. Lower passenger safety and design durability were the results of a weight reduction of automobiles that was excessively drastic. Vehicles started to come with various safety systems, such as stability control systems, automatic braking systems (ABS), and safety airbags, in the 1980s and 1990s in an effort to increase passenger safety. Additionally, a number of passive safety devices were created. The end of the twentieth century saw an increase in vehicle weight as a result of the development of new safety systems and their installation on vehicles.

Internal combustion engine vehicles of the same model typically see minimal weight changes. If cars are fitted with engines of varied sizes, modifications, and devices, there will typically be slight weight adjustments. Due to the varied sizes of their goods compartments, commercial vehicles' weights might fluctuate.

The average fuel consumption of an automobile might fluctuate if its weight changes. Such a pattern is typically seen while driving in urban environments, where the car is frequently accelerated and halted. According to an analysis of annual variations in fuel consumption for cars, the average fuel consumption for cars significantly dropped in the middle of the 1980s, although this tendency was less pronounced subsequently (Heavenrich, 2008). The historical development of automobiles has shown a similar tendency in terms of weight loss; the vehicles produced between 1981 and 1987 experienced the smallest weight loss. The typical weight of later-produced cars tended to rise once more. Because of the introduction of contemporary engine designs, the weight growth tendency does not significantly affect the acceleration dynamics of automobiles of new designs (Heavenrich, 2008).

Electric vehicle (EV) batteries have very high energy density per unit weight, ranging from 60 to 96 Whkg^-1. Lithium batteries with a 20 kWh capacity might weigh up to 200 kg in a vehicle. Batteries can be very expensive, costing up to 1000 EUR per kWh^-1 (Huh et al., 2011). As it is economically unproductive to carry the extra weight of the batteries, it is advisable to choose a custom-made pack of electric vehicle batteries in order to lower the cost of automobiles.

In this case, the research demonstrated that the theory of Technology Acceptance can explain the nexus between the performance indicators of hybrid electric cars and customers’ purchase intentions of the respective vehicles due to the relationship between perceived usefulness and ease of use and consumer behavior in regard with purchasing hybrid electric vehicles in Azerbaijan.

Finally, the thoughts of customers about compatibility of hybrid electric cars also affect their purchase intentions as the congruence between actual and expected performance of hybrid electric cars increase their willingness to repurchase the same hybrid electric cars, to replace their current hybrid electric cars with their new and innovative versions or to suggest the respective cars to other customers. However, the research could not identify the empirically significant nexus between complexity and customers’ purchase intentions. Thus, the last hypothesis of the study was rejected due to the absence of a relationship between the respective predictor and three aspects of consumer behavior, such as repurchase of hybrid electric cars, purchase of new versions of hybrid electric cars and recommending the respective cars to other customers. Therefore, the theory of Innovation Diffusion provides the partial explanation for the relationship between performance of hybrid electric cars and customers’ purchase intentions as information spread about the balance between actual and expected performance of hybrid cars is determined as a critical factor leading the customers to repurchase hybrid electric cars, to buy their new and innovative versions and to suggest them to other customers. In general, the research identified that the customer perceptions about three performance indicators of hybrid electric cars, such as their usefulness, ease of use and compatibility were detected as primary reasons leading to the proliferation of the corresponding cars in Azerbaijan. To mitigate the ‘common method bias-ness problem’, we use Harman's single factor score.¹

The main implications of electric vehicle are as follows-

The study has certain limitations that should be addressed in future research for further elaboration of the reasons for the proliferation of electric cars. The first one is that the research findings of the study lack the expert views, especially the perceptions of qualified persons in the field of hybrid electric vehicles and internal combustion engines. Gathering primary data from engineers, designers, and other persons working in the production process of hybrid electric vehicles and internal combustion engines could enable them to determine performance differences between the respective vehicles and to identify reasons leading the customers to prefer hybrid electric cars in recent years. The second limitation of study is the sample size which could be increased for including more members of the target population into the data collecting process for reliably and accurately. The current study had the sample size of 121 customers, which was enough to generate certain conclusions about the nexus between hybrid electric vehicles and customers’ purchase intentions. However, its findings could be improved via gathering data from a large sample base, grouping the sample based on their demographic characteristics with subsequent comparison between the responses regarding the performance of hybrid electric vehicles and their purchase intentions of hybrid electric cars.

In the current automobile market, electric cars have gained popularity among the customers. In particular, the customer preferences of electric cars have increased over the recent years in contrast to the conventional cars equipped with internal combustion engines. The increasing popularity of electric vehicles among the consumers has been an unexpected outcome in the automobile manufacturing industry because of their performance constraints. In this regard, the customers disregarded electric vehicles as a means of transportation in the past due to its restricted driving range, limited speed, time-consuming charging process and expensive maintenance costs. Therefore, the increasing popularity of electric vehicles has been an unexpected change in the customer preferences due to the constraints in its performance and functionality compared to the internal combustion engines. Hence, the primary aim of the research was to determine the reasons directing the customers to buy and use electric vehicles despite their performance and function related limitations in comparison with the conventional vehicles.

The primary focus of study is to identify the factors motivating the consumers to purchase one of the commonly used types of electric vehicles, hybrid electric cars. In this study, the hypotheses of research were constructed via two theories. The first theory of study was Technology Acceptance Theory which was used for identifying the relationship between perceived usefulness and ease of use of hybrid electric cars and customers’ purchase intention of the respective cars in Azerbaijan. The second theory of study was Innovation Diffusion Theory, which was used for identifying the relationship between compatibility and complexity of hybrid electric cars and the customers’ purchase intention of the respective cars in Azerbaijan.

In this study, the primary data of customers’ perspectives on performance of hybrid electric vehicles was collected through questionnaires. Besides, the sample included 121 customers of hybrid electric vehicles, whose responses were analyzed through descriptive and regression analyses. While independent variables of study included indicators of the performance of hybrid electric cars, the dependent variables included the forms of consumer behavior.

The findings of study highlighted that the customer perceptions about the usefulness, ease of use and compatibility of hybrid electric cars are determinants of the customers’ purchase intentions of the respective cars in Azerbaijan. Besides, the research findings presented that the customer perceptions about usefulness, ease of use and compatibility of hybrid electric vehicles are primary reasons leading the customers to purchase the respective cars in Azerbaijan. In case of complexity of hybrid electric vehicles, the research findings identified the absence of empirically significant nexus between the complexity of using hybrid electric vehicles and customers’ intention to purchase the respective cars in Azerbaijan.