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Vehicle scrappage incentives to accelerate the replacement decision of heterogeneous consumers

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  • Zaman, Hosain
  • Zaccour, Georges

Abstract

Vehicle scrappage subsidy programs have been widely applied by governments to replace old cars by newer, more fuel-efficient ones. While these programs have been implemented to provide motivation for replacing vehicles earlier, they may not be as effective as expected. From a cost-benefit perspective, the consumers who would have replaced anyway, even without the program, must be considered when evaluating the net benefits of the program. This requires accounting for variations in consumers’ willingness to replace. Considering consumer heterogeneity in net trade-in valuation, this study investigates a dynamic vehicle-replacement problem based on a life cycle optimization (LCO) approach. We theoretically demonstrate that although increasing the subsidy level does motivate low-value consumers to replace earlier, it also induces consumers with a high net trade-in valuation to replace later in order to become eligible for the subsidy program. We have also developed a simulation program based on real data, to demonstrate the application of our general model. According to the simulation results, ignoring consumer heterogeneity could result in an overestimation of the net benefits of the scrappage program.

Suggested Citation

  • Zaman, Hosain & Zaccour, Georges, 2020. "Vehicle scrappage incentives to accelerate the replacement decision of heterogeneous consumers," Omega, Elsevier, vol. 91(C).
  • Handle: RePEc:eee:jomega:v:91:y:2020:i:c:s0305048318302639
    DOI: 10.1016/j.omega.2018.12.005
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    Cited by:

    1. Zaman, Hosain & Zaccour, Georges, 2021. "Optimal government scrappage subsidies in the presence of strategic consumers," European Journal of Operational Research, Elsevier, vol. 288(3), pages 829-838.
    2. Nie, Qingyun & Zhang, Lihui & Tong, Zihao & Hubacek, Klaus, 2022. "Strategies for applying carbon trading to the new energy vehicle market in China: An improved evolutionary game analysis for the bus industry," Energy, Elsevier, vol. 259(C).

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