The present study investigates commuters’ willingness-to-pay (WTP) for the attributes of plug-in hybrid electric vehicle (PHEV) in a typical Indian context. A stated preference discrete choice experiment was designed to collect choice responses from potential users of PHEV in Kolkata, India. The collected data were analyzed by developing multinomial logit (MNL) and mixed logit (ML) models to estimate overall commuters’ WTP for a set of key attributes of PHEV namely purchase price, fuel cost reduction, battery range, public charging station, battery recharging time, battery warranty and tailpipe emission. Additionally, in ML model, heterogeneity around the mean of random parameters with respect to sociodemographic characteristics such as age, monthly family income, car ownership, home-based parking facility and education, and trip characteristics such as average commuting trip length were examined, and WTP estimates were evaluated for different population sub-groups. The model estimation results indicate that ML models are overall statistically superior and represent the data better than MNL model. The results also highlight that the high purchase price of PHEV as compared to conventional vehicle (CV) could be one of the major deterrents towards the purchase of PHEV in Indian context. The WTP estimates indicate that commuters perceive battery warranty as the major determinant influencing the choice of PHEV followed by battery recharging time and tailpipe emission. The potential users’ income, availability of home-based parking facility, education, and average commuting trip length also substantially influenced their WTP for several attributes of PHEV in Indian context.


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    Titel :

    Commuters' Willingness-to-Pay for the Attributes of Plug-in Hybrid Electric Vehicle: A Case Study in Kolkata, India


    Weitere Titelangaben:

    Transp. in Dev. Econ.


    Beteiligte:
    Bera, Reema (Autor:in) / Maitra, Bhargab (Autor:in)


    Erscheinungsdatum :

    2022-04-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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