To Share or not to Share? Determinants of Sharing Mobility in Italy

Pierpaolo D’Urso (), Alessio Guandalini (), Francesca Romana Mallamaci (), Vincenzina Vitale () and Laura Bocci ()
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Pierpaolo D’Urso: University of Rome “La Sapienza”
Alessio Guandalini: Italian National Institute of Statistics (ISTAT)
Francesca Romana Mallamaci: LUISS
Vincenzina Vitale: University of Rome “La Sapienza”
Laura Bocci: University of Rome “La Sapienza”

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2021, vol. 154, issue 2, No 12, 647-692

Abstract: Abstract In the last years, there has been a growing interest in the sharing mobility transport thanks to its potentialities in terms of service accessibility and versatility being a valid alternative to the use of private vehicles. Its role could become central to promote environmental sustinability as well as to fill the gap of public transport being the integrated transport system the new future challenge. The aim of this study is to investigate the main factors promoting sharing mobility in Italy, with reference to cars and bikes, in particular. The representative sample coming from the 2017 Aspects of Daily Life survey has been used in the analysis developed on two research directives: the former based on the use of the logistic regression technique to identify the significant factors predicting the carsharing and bikesharing propensity; the latter based on the use of the Bayesian Networks framework to explore the complex dependence structure of all involved variables. The application results are in line with the sharing mobility literature noting that this is one of the few works based on a representative sample. In this study, many predisponent aspects promoting the sharing service have been emphasized and analysed suggesting new possible intervention policies for managers and stakeholders.

Keywords: Carsharing; Bikesharing; Logistic regression model; Bayesian networks model averaging; Aspects of Daily Life survey; ROSE algorithm (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11205-020-02574-7

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