DETERMINING FACTORS OF POST PURCHASE BEHAVIOUR OF ELECTRIC VEHICLE CONSUMERS

 

Dr. G. Kalpana ¹, J. Poovaraghavan ²

 

¹ Assistant Professor, Department of Corporate Secretaryship, Dhanraj Baid Jain College, Chennai, Tamil Nadu, India

² Assistant Professor, Department of Mathematics, Dhanraj Baid Jain College, Chennai, Tamil Nadu, India

 

1. INTRODUCTION

Electric vehicles (EVs) have become increasingly popular as environmentally sustainable alternatives to gasoline-powered automobiles Kumar and Sharma (2023). EVs operate on electricity, can be charged externally, and offer advantages such as reduced dependence on fossil fuels and lower maintenance costs Singh and Verma (2022). They represent a solution to environmental challenges, including pollution and climate change World Economic Forum (2023).

The increase in EV adoption is largely motivated by concerns over urban air pollution, as many major Indian cities rank among the most polluted globally Central Pollution Control Board (2022). Transportation emissions significantly contribute to environmental degradation, prompting manufacturers and governments to explore sustainable alternatives IEA (2023). Globally, governments are promoting electric mobility as a strategic response to climate concerns International Energy Agency (2022). For instance, China has actively encouraged hybrid and electric vehicles, while the UK offers incentives for EV purchases in urban areas like London OECD (2022).

In India, electric three-wheelers are widely used, but enhancements to the power distribution network remain necessary to support large-scale EV adoption NITI Aayog. (2023). There exists substantial growth potential for electric bikes and four-wheelers, provided there is greater government investment in charging infrastructure and purchase incentives FICCI (2023). India has set a target of achieving an all-electric vehicle fleet by 2030, with the Minister of Road Transport and Highways collaborating with the Society of Indian Automobile Manufacturers (SIAM) to facilitate this transition Ministry of Road Transport and Highways. (2023). This underscores the government’s commitment to sustainable transportation Times of India (2023).

 

2. Post purchase behaviour

The customer holds a paramount position, and consumer preferences significantly shape the identity and positioning of a firm Kotler and Keller (2022). The strength of an economy is largely attributed to the plentiful production of goods and services within a nation, creating a highly competitive market environment Solomon et al. (2021). Since most items are available from multiple alternative suppliers, consumers are required to choose products from a specific brand, often influenced by perceived quality, pricing, and brand reputation Schiffman and Wisenblit (2020).

Consumers generally engage in two types of purchases: trial purchases and regular (repeat) purchases. A product trial occurs when a consumer is persuaded to make an initial purchase at a reduced quantity and often with hesitation, typically to evaluate the performance and suitability of a product Peter and Olson (2019). Trial purchases thus serve as a fundamental basis for purchasing behaviour, where the primary goal is product evaluation. Conversely, repeat purchases indicate the consumer’s commitment to the product and the brand, reflecting both satisfaction and brand loyalty Hoyer et al. (2021).

The purchasing process outlines the actual buying environment and its influence on decision-making. At the point of purchase, a mental appraisal developed through information processing, expectations, and attitudes is translated into buying behaviour Blackwell et al. (2020). Numerous factors can affect purchase decisions, including time availability, consumer attitudes, shopping experiences, and salesperson effectiveness (Loudon and Della Bitta (2022).

Consumer satisfaction is evaluated based on an individual’s overall sentiment regarding the product post-purchase. Satisfaction is typically determined by the extent to which a product’s actual performance aligns with the consumer’s prior expectations Oliver (2015). In some cases, dissatisfied consumers may introduce products into secondary marketplaces, contributing to a lateral cycle within the consumption process Grewal and Levy (2022).

The purchase and post-purchase phases represent the final two stages in the consumer decision-making process. While the purchase stage is of greater importance for manufacturers and marketers, the post-purchase stage offers invaluable information about customer satisfaction, which is essential for influencing future purchasing decisions (Engel, Blackwell, and Miniard, 2020).

 

3. Review of literature

Rajarajan and Priyanga (2013) conducted a study on "Consumer Pre- and Post-Purchase Behavior—An Overview." The study concludes that customer satisfaction and value ratio indicate that customers are satisfied when their perceived value aligns with their expected value, and delight is achieved when the actual gain significantly surpasses expectations. Globisch et al. (2019) studied consumers' economic and psychological perspectives regarding public charging infrastructure, highlighting that a major barrier to electric vehicle deployment is the insufficient proliferation of public charging stations. The authors found that numerous potential users are unwilling to pay for infrastructure deployment due to high costs, which prevent them from realizing the associated benefits. Ukesh et al. (2022). This study aimed to analyse consumer post-purchase satisfaction regarding electric two-wheelers in Coimbatore city. Post satisfaction is assessed through straightforward percentage analysis. To perform the simple percentage analysis, five statements are formulated based on various articles. The results indicated that five statements were identified: Better Customer Service, Promotional Offers, Credit and Loan Facility, After Sales Service, and Post-Satisfactory Response to Customer Complaints. Therefore, the electric two-wheeler dealer should strive to enhance services anticipated by respondents to improve performance and sustainability. This study, as stated by Silvana (2022), conducts a bibliometric and thematic analysis of 254 studies pertaining to consumer behaviour in the electric car market. This study identifies the main co-citation network among international journals and authors, defines the prominent research centres in the field, and outlines the dimensions addressed by scholars. The analysis further develops the theory of planned behaviour by providing a useful consumer profile for practitioners. The study presents several research questions that contribute to the academic discourse. Susheela and Devaru (2023). This paper analyses consumer buying behaviour regarding electric vehicles, specifically investigating the various factors that influence consumers' decisions during the purchasing process. The study identifies a gender disparity in electric vehicle interest, highlighting the necessity for targeted marketing strategies to engage a larger female consumer base. Age groups, specifically those between 25-30 and 30-40, demonstrate a significant preference for electric vehicles, influenced by young professionals pursuing a luxury lifestyle. Income level does not significantly influence electric vehicle preference, although the $25,000 to $40,000 income range exhibits notable interest. Graduates and postgraduates possess knowledge of branded electric vehicle outlets and demonstrate an understanding of brand differentiation. Narendiran and Vetrivel (2024) conducted research on essential factors including purchase price, charging features, maintenance expenses, battery life and durability, performance and safety features, warranty, and after-sales service. A comprehensive literature review from multiple authors recently indicates that consumers take these factors into account when purchasing an electric vehicle. Research indicates that the purchase price significantly influences consumer behaviour regarding electric vehicles. The availability and accessibility of charging features are essential for improving convenience and alleviating range anxiety. Maintenance costs are a critical factor for potential buyers when assessing long-term affordability. Battery life and durability are essential determinants of overall satisfaction with electric vehicles, as batteries substantially influence their cost-effectiveness. Performance and safety features were critical factors influencing consumer perceptions of reliability and the driving experience. Warranty coverage provides assurance to customers regarding potential technical issues or defects that may arise over time. After-sales service has become a critical factor in influencing post-purchase behaviour. The prompt support provided by manufacturers during servicing or repairs can greatly affect the overall ownership experience. Our findings led to several recommendations for stakeholders in the electric vehicle sector.

 

4. Objectives of the study

1)     To find the factors that determines the post purchase behaviour of consumers using electric vehicle.

2)     To study the influence of demographic and e-vehicle related variables on Post purchase behaviour.

 

4.1. Hypotheses of the study

·        H₀1: Significant influence of demographic variables on Post purchase behaviour is not observed

·        H₀2: Significant influence of e-vehicle related variables on Post purchase behaviour is not observed

 

5. Research Methodology

The study explores the determinants affecting the post-purchase behaviour of consumers who use electric vehicles in Chennai. A sample of 114 respondents using electric vehicles in Chennai was selected for the study, which is classified as descriptive in nature. The questionnaire serves as the study instrument for data collection. The convenience sampling method is employed to select respondents for the study. The questionnaire consists of two segments: the first addresses the demographic characteristics of the respondents, while the second includes scales for post-purchase behaviour. Exploratory Factor Analysis identifies the factors influencing the post-purchase behaviour of electric vehicles. A one-way ANOVA is employed to assess the impact of demographic variables and e-vehicle-related factors on post-purchase behaviour. Cronbach's alpha is utilised to assess the reliability of the study. Data analysis is conducted using SPSS v25.

 

6. Results and Discussion

The reliability of this study is measured at 0.829 (82.9%). A total of 114 respondents participated in this survey. Of the respondents, 77.2% are male, 38.7% fall within the 30-40 age range, 55.1% are married, and 47.6% hold an undergraduate or postgraduate degree. 41.1% of respondents are employed in private services, while 67.9% report an income exceeding 50,000 per month. This section identifies the factors influencing post-purchase behaviour in electric vehicles.

 

7. Factors that determine the Post purchase behavior of e-vehicle users 

This section examines the elements that affect the post-purchase behaviors of electric vehicle users in Chennai. The evaluation of post-purchase behavior among electric vehicle users is conducted through the analysis of twenty-three variables. A factor analysis was performed using the principal component method with varimax rotation to classify the variables into factors according to the responses from the chosen customers. The KMO measure of 0.841 suggests that the sample size is sufficient, and the Bartlett’s test of sphericity produces a Chi-square value of 401.625 (p = .000), indicating statistical significance. The eigenvalues and the corresponding variance they account for are detailed in Table 1.

Table 1  

Table 1 Eigen values for Post Purchase Behavior of E-Vehicle Users
S. No	Eigen Value	Variance (%)	Cumulative Variance (%)
1	10.145	26.143	26.143
2	5.328	14.245	40.388
3	3.116	8.218	48.606
4	2.012	7.215	55.821
5	1.354	6.059	61.88
6	1.113	5.513	67.393
7	1.049	4.362	71.755

 

Twenty-three variables are reduced into seven factors by analyzing the correlation between variables. Since the eigenvalues of 10.145, 5.328, 3.116, 2.012, 1.354, 1.113, and 1.049 are greater than one (1), the twenty-three variables are successfully reduced into seven significant factors that explain much of the respondents’ post-purchase behaviour towards electric vehicles. It is noted that the cumulative percentage of variance explained by these seven factors is 71.755%, which indicates that these extracted factors effectively represent the majority of the variability in the data. The seven factors extracted, along with their respective components and factor loadings, are presented in Table 2.

Table 2

Table 2 Factor Loadings for Post Purchase Behavior
Factor	Components	Factor Scores
Factor 1: Comfort	Driving is comfortable	0.801
	Seating space/design is good	0.764
	Storage space provided is enough	0.651
	Driver Assistance System is present in the vehicle	0.587
	Steering/Handle bar is flexible	0.54
Factor 2: Driving	Vehicle running performance in Straight roads is good	0.776
	Curve running performance	0.713
	Braking system is good and suitable for all type of road conditions	0.684
	Accelerated performance is good	0.623
	Start/stop functions are working perfectly	0.55
Factor 3: Energy consumption	Driven distance is calculated accurately	0.713
	Power consumption is less	0.581
Factor 4: Design	Exterior/Interior look is good	0.626
	Physical appearance of the vehicle is good	0.51
Factor 5: Safety	Vision and lighting functions are good	0.723
	Felt safety while driving the vehicle	0.688
	Battery performance is good	0.543
	Anti-theft indicator installed is good	0.531
Factor 6: Charging convenience	Time consumption for re-charging is normal	0.646
	Charging Interface/plug provided is comfortable while charging	0.583
Factor 7: Information exchange	Navigation System provided in the system is working properly	0.771
	Communication System indications are fine	0.616
	Vehicle information display system is working properly	0.532

 

Table 2 shows that factor 1 consists of five variables: “Driving is comfortable,” “Seating space/design is good,” “Storage space provided is sufficient,” “Driver Assistance System is included in the vehicle,” and “Steering/Handlebar is flexible.” This factor is referred to as "Comfort."

Factor 2 includes five variables: “Vehicle running performance on straight roads is good,” “Curve running performance,” “Braking system is effective and suitable for all types of road conditions,” “Accelerated performance is satisfactory,” and “Start/stop functions operate effectively.” This group is designated as the "Driving".

Factor 3 includes two variables: "Driven distance is calculated accurately" and "Power consumption is less," collectively termed as "Energy."

Factor 4 includes two variables: "Exterior/Interior look is good" and "Physical appearance of the vehicle is good," collectively termed as "Design."

Factor 5 includes four variables: “Vision and lighting functions are adequate,” “Felt secure while operating the vehicle,” “Battery performance is satisfactory,” and “Anti-theft indicator installed is effective.” This group is designated as the "Safety".

Factor 6 includes two variables: "Time consumption for recharging is normal" and "Charging interface/plug provided is comfortable while charging," collectively termed as Charging "Convenience."

Factor 7 consists of three components: the proper functioning of the navigation system, the accuracy of communication system indications, and the effective operation of the vehicle information display system. This collective is referred to as the “Information exchange”.

Post-purchase behaviour towards electric vehicles is influenced by factors such as comfort, driving experience, energy efficiency, design, safety, charging convenience, and information exchange.

Key aspects influencing post-purchase behavior towards electric vehicles include comfortable driving, vehicle performance on straight roads, accurate distance calculation, appealing exterior and interior design, effective vision and lighting functions, reasonable recharging time, and proper functioning of the navigation system.

 

8. Demographic variables influence on Post purchase behavior

This section looks at the impact of demographic variables on post-purchase behaviours regarding electric vehicles. To assess the significant impact of demographic variables on post-purchase behaviour regarding electric vehicles, a one-way ANOVA and Duncan's post hoc test are employed to analyse this relationship.

H01: Significant influence of demographic variables on Post purchase behaviour is not observed

Table 3

Table 3 Influence of Demographic Variables on Post Purchase Behaviour
Demographic variable	Classification	Mean	SD	F-value
Gender	Male	3.21	0.885	1.596 (p=.098)
	Female	3.34	0.916
Age	Up to 30 years	3.39	0.869	7.928** (p=.000)
	31-40 years	3.27	0.948
	41-50 years	2.95	0.844
	50 and above	2.72	0.835
Marital status	Married	3.19	0.886	1.394 (p=.238)
	Unmarried	3.08	0.969
Occupation	Private Service	3.26	0.911	3.148* (p=.045)
	Government service	3.23	0.982
	Self-employed / Business	2.99	0.901
	Others	3	0.816
Education qualification	Up to School	3.14	0.907	1.297 (p=.275)
	Graduate/Diploma	3.22	0.937
	Post-graduation	3.04	0.893
	Others	2.88	0.786
Income per month	Below 25,000	3.26	0.855	4.993** (p=.002)
	Rs.25,000 to 50, 000	2.98	0.908
	Rs.50,000 to 1,00,000	3.11	0.919
	1,00,000 and above	3.46	0.906
*p <.05    **p< .01

 

Age (F=7.928, p=.000), occupation (F=3.148, p=.045), and monthly income (F=4.993, p=.002) significantly influence post-purchase behaviour, leading to the rejection of H05 at the 1% level. Conversely, the influences of gender (F=1.596, p=.098), marital status (F=1.394, p=.238), and educational qualification (F=1.297, p=.275) on post-purchase behaviour regarding electric vehicles are not significant, resulting in the acceptance of H05 at the 5% level. Respondents under 30 years of age achieved the highest mean score of 3.39, whereas those over 50 years recorded the lowest mean score of 2.72. Respondents under 30 years exhibit higher satisfaction levels, while those over 50 years demonstrate comparatively lower satisfaction with electric vehicles. Respondents employed in the private sector recorded the highest mean score of 3.26, while those engaged in self-employment or business reported the lowest mean score of 2.99. Respondents in the private sector exhibit greater satisfaction with electric vehicles, while those who are self-employed or in business demonstrate lower satisfaction levels. Respondents with monthly earnings exceeding Rs.1,00,000 achieved the highest mean score of 3.46, while those earning between Rs.25,000 and Rs.50,000 recorded the lowest mean value of 2.98. Respondents with monthly earnings exceeding Rs.1,00,000 demonstrate higher satisfaction with electric vehicles, whereas those earning between Rs.25,000 and Rs.50,000 exhibit lower satisfaction levels.

 

9. Influence of e-vehicle related variables on Post purchase behaviour 

This section examines how variables related to e-vehicles influence post-purchase behavior. A one-way ANOVA is employed to evaluate the substantial effects of e-vehicle-related variables on post-purchase behaviour.

H02: Significant influence of e-vehicle related variables on Post purchase behaviour is not observed

Table 4

Table 4 Influence of E-Vehicle Related Variables on Post Purchase Behaviour
e-vehicle related variable	Classification	Mean	SD	F-value
Type of e-vehicle usage	2-wheeler	3.18	0.93	0.568 (p=.567)
	4-wheeler (car)	3.14	0.823
	Both	3.02	0.995
Experience in	Up to 1 year	2.91	0.862	12.747**( p=.000)
e-vehicle driving	1 to 3 years	3.64	0.756
	3 to 5 years	3.06	0.912
	Above 5 years	3.5	0.945
Annual driving distance	Below 2,000 Km	3.23	0.979	0.748 (p=.524)
	2,000 to 5,000 Km	3.13	0.906
	5,000 to 10,000 Km	3.17	0.863
	Above 10,000 Km	2.94	0.9
Frequency of using electric vehicles	Only once	3.06	0.846	1.746 (p=.157)
per day	2 to 3 times	3.29	0.986
	3 to 5 times	3.12	0.938
	More than 5 times	3.27	1.01
** p<.01

              

The experience in e-vehicle driving significantly influences post-purchase behaviour towards electric vehicles (F=12.747, p=.000), leading to the rejection of H02 at the 1% level. The analysis reveals no significant influence of e-vehicle usage type (F=0.568, p=.567), annual driving distance (F=0.748, p=.524), or daily frequency of e-vehicle use (F=1.746, p=.157) on post-purchase behaviour. Thus, H02 is accepted at the 5% significance level. Respondents who have driven electric vehicles for a duration of 1 to 3 years achieved the highest mean score of 3.64, while those driving for less than 1 year recorded the lowest mean score of 2.91. Respondents who have driven electric vehicles for 1 to 3 years exhibit higher satisfaction levels compared to those who have driven them for less than 1 year.

 

 

 

 

10. Conclusion

The findings indicate that comfort, driving experience, energy efficiency, design, safety, charging convenience, and information exchange are significant factors influencing post-purchase behaviour regarding electric vehicles Singh and Sharma (2023). Comfortable driving, vehicle performance on straight roads, accurate distance calculation, appealing exterior and interior design, effective vision and lighting functions, reasonable recharging time, and proper navigation system functionality are key aspects influencing consumer satisfaction Kumar et al. (2022). Respondents under 30 years of age exhibit higher satisfaction levels, while those over 50 years demonstrate comparatively lower satisfaction with electric vehicles Patel and Ramesh (2021). Similarly, respondents employed in the private sector report higher satisfaction with electric vehicles, whereas self-employed individuals or those engaged in business demonstrate lower satisfaction levels Gupta (2022). Furthermore, respondents with monthly earnings exceeding ₹1,00,000 exhibit greater satisfaction levels regarding electric vehicles, while those earning between ₹25,000 and ₹50,000 demonstrate lower satisfaction Chatterjee and Nair (2023). Age, occupation, monthly income, and experience in driving electric vehicles significantly influence post-purchase behaviour Mishra and Verma (2022). Respondents who have driven electric vehicles for one to three years exhibit higher satisfaction levels compared to those who have driven electric vehicles for less than one year Rao and Iyer (2021).

 

CONFLICT OF INTERESTS

None. 

 

ACKNOWLEDGMENTS

None.

 

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