Delivering in Urban Areas: A Probabilistic-Behavioral Approach for Forecasting the Use of Electric Micromobility

Marisdea Castiglione, Antonio Comi, Rosita De Vincentis, Andreea Dumitru and Marialisa Nigro
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Marisdea Castiglione: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Antonio Comi: Department of Enterprise Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy
Rosita De Vincentis: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Andreea Dumitru: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Marialisa Nigro: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy

Sustainability, 2022, vol. 14, issue 15, 1-13

Abstract: Urban delivering is facing some significant changes that are heading towards unsustainable scenarios. At the same time, local administrations as well as city planners are involved in promoting new solutions that can help to improve city sustainability and livability. In this context, electric micromobility could offer a valuable contribution. In fact, electric micromobility systems such as e-bikes and e-scooters, both at an individual level or as a shared service, could represent sustainable mobility options for city logistics, especially for specific classes of parcel delivery, users’ characteristics and travelled distances. Considering both the growth of e-commerce and the spreading of new options for delivering parcels (e.g., crowdshipping), electric micromobility (e-bikes and e-scooters) could support the penetration and acceptability of such new options, limiting the impacts of delivery operations. After analysis of the current e-commerce background and a review of the current delivery options to satisfy delivery demand, crowdshipping stands out. Thus, the potential shift from private transport to e-micromobility for crowdshipping is investigated, assuming that potential crowdshippers may, mainly, be commuters. The methodology is based on using probabilistic-behavioral models developed within random utility theory, which allow the potential shift towards e-micromobility for commuting to be forecasted. The models were calibrated in Rome, where more than 200 interviews with commuters were available.

Keywords: electric micromobility; e-scooters; e-bikes; floating car data; random utility models; city logistics; crowdshipping (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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