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Electric vehicle development in Pakistan

Predicting consumer purchase intention

Bibliographic Data

ID22355488
AuthorsUsamah Shakeel (0000-0002-8019-6095, Tianjin University, corresponding author)
Year2022
Volume5
Pages100065
Publication date2022-06-01
Open AccessYes
TypeARTICLE
VenueCleaner and Responsible Consumption (JOURNAL)
Journal identifiersISSN: 2666-7843
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.clrc.2022.100065
OpenAlexW4224999482
LanguageEN
Citations received7
References cited47

Pakistan's government has been pushing for electric vehicles adoption to decrease energy consumption and pollution. Acceptance of large numbers of electric vehicles will undoubtedly help to ease important issues such as carbon pollution and fuel reliance and to improve economic success. Pakistan is now considering switching from non-Electric vehicle to Electric vehicle (EVs) in spite of numerous cross-sectoral and multifaceted roadblocks. The theory of planned behavior (TPB) model was utilized in this study to construct a model of purchase intention impact mechanism for electric vehicles (EVs). It considered consumer attitude (AT) and subjective norms (SN), cognitive states (CS), product perception (PA), perceived behavioral control (PBC), non-monetary incentive policy (NMIP), as well as monetary policy (MIP). In Pakistan, a questionnaire was administered to potential customers. A total 511 valid survey responses were collected. The factors affecting EV buying intent were examined by Structural equation modeling (SEM) using SPSS AMOS. According to the results no factors tested negative, most of the factors were significant beneficial outcome on consumers' intents to buy electric vehicles (EVs). These findings were discussed with policy recommendations and conclusion

Automotive industry · Business · Consumer behaviour · Economics · Electric vehicle · Incentive · Microeconomics · Perception · Risk perception · Structural equation modeling · Theory of planned behavior · Computer Science · Electric Vehicles and Infrastructure · Energy, Environment, and Transportation Policies · Engineering · Innovation Diffusion and Forecasting · Psychology · Marketing

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Citations per year3.5
Citation span2024 - 2026 (3)
Highly citedNo

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