![]() ![]() Moreover, in traditional trading approaches, centralized parties are involved in energy trading, which leads to various issues such as increased computational cost, increased computational delay, data tempering and a single point of failure. EVs face two major problems: finding an optimal charging station and calculating the exact amount of energy required to reach the selected charging station. The proposed model deals with energy trading problems such as insecure energy trading and inefficient charging mechanisms for electric vehicles (EVs) in a vehicular energy network (VEN). These findings were discussed with policy recommendations and conclusion.In this paper, a secure energy trading mechanism based on blockchain technology is proposed. According to the results no factors tested negative, most of the factors were significant beneficial outcome on consumers' intents to buy electric vehicles (EVs). The factors affecting EV buying intent were examined by Structural equation modeling (SEM) using SPSS AMOS. ![]() A total 511 valid survey responses were collected. ![]() In Pakistan, a questionnaire was administered to potential customers. 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). 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). Pakistan is now considering switching from non-Electric vehicle to Electric vehicle (EVs) in spite of numerous cross-sectoral and multifaceted roadblocks. 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's government has been pushing for electric vehicles adoption to decrease energy consumption and pollution. ![]()
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