Drivers and barriers to integrating shared micromobility with public transport A latent class clustering analysis of adoption attitudes in the Netherlands
Nejc Geržinič (TU Delft - Transport, Mobility and Logistics)
Mark van Hagen (Nederlandse Spoorwegen)
Hussein Al-Tamimi (Nederlandse Spoorwegen)
Niels Van Oort (TU Delft - Transport, Mobility and Logistics)
Dorine Duives (TU Delft - Transport, Mobility and Logistics)
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Abstract
Shared micromobility (SMM), including bicycles, e-bikes, scooters, etc., is often cited as a solution to the first and especially the last mile problem of public transport (PT), yet when implemented, they often do not get adopted by a broader travelling public. As behavioural adaption is largely related to peoples’ attitudes and perceptions, we develop a behavioural framework based on the UTAUT2 framework to gain better understanding why individuals may (not) be willing to use SMM. Through an exploratory factor analysis (EFA) and a latent class cluster analysis (LCCA), we study the adoption potential of SMM and assess drivers and barriers as perceived by different user groups. Our findings uncover six user groups; Shared mobility positives, Car-oriented sharing neutrals, Older apprehensive sharers, Young eager adopters, (Shared) Mobility avoiders and Skilled sharing sceptics. The Young eager adopters and Shared mobility positives tend to be the most open to adopting SMM and able to do so. Older apprehensive sharers would like to, but find it difficult or dangerous to use, while Skilled sharing sceptics are capable and confident, but have limited intention of using it. Car-oriented sharing neutrals and (Shared) Mobility avoiders are most negative about SMM, finding it difficult to use and dangerous. Factors relating to technological savviness, ease-of-use, physical safety and societal perception seem to be the strongest adoption predictors. Younger, high-educated males are the group most likely and open to using SMM, while older individuals with lower incomes and a lower level of education tend to be the least likely.