Abstract Once automatic vehicles (AV) are available, working from self-driving cars (WFC) will be an option. It allows firms to socialize office land costs to road infrastructure used by AV’s mobile offices. Employees, in turn, can switch wasted commuting time into working and substitute office hours. We model employers’ offers and employees’ discrete choice of WFC contracts and decisions on WFC hours, considering heterogeneous preferences for WFC. We further perform Monte Carlo studies for the U.S. and Germany to quantify these decisions, assess consequences on distances traveled and traffic-related externalities, and evaluate whether transport pricing can reduce the latter. Our findings suggest that WFC is a likely feature of tomorrow’s world, but it comes at the cost of induced traffic and traffic-related externalities. Eventually, we see that standard transport-policy instruments on car use, traveling, and parking affect the number of mobile employees, i.e., those with WFC contracts, but do not lower distances traveled per mobile employee. Given these tentative findings, a policy to lower traffic and emissions shall primarily focus on avoiding WFC contracts. Once WFC contracts exist, standard policy instruments to reduce travel may need to be revised.

    Highlights How will autonomous driving affect society/daily life/transport? Here: Working from self-driving cars (WFC). Model: Heterogeneous employees and employers decide on WFC contracts and the intensity of WFC use. Monte Carlo simulations for U.S. and German data. Outcome: WFC is a likely feature of tomorrow’s world, but it comes at the cost of induced traffic and traffic-related externalities. Policy outcome: Standard transport-policy instruments to mitigate externalities affect the number of WFC contracts. But, once WFC contracts exist, these policies are ineffective.


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    Title :

    Working from self-driving cars


    Contributors:


    Publication date :

    2023-07-18




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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