Exploring Travelers’ Characteristics Affecting their Intention to Shift to Bike-Sharing Systems due to a Sophisticated Mobile App

Abstract

Many cities have already installed bike-sharing systems for several years now, but especially in recent years with the rise of micro-mobility, many efforts are being made worldwide to improve the operation of these systems. Technology has an essential role to play in the success of micro-mobility schemes, including bike-sharing systems. In this paper, it is examined if a state-of-the-art mobile application (app) can contribute to increasing the usage levels of such a system. It is also seeking to identify groups of travelers, who are more likely to be affected by the sophisticated app. With this aim, a questionnaire survey was designed and addressed to the users of the bike-sharing system of the city of Thessaloniki, Greece, as well as to other residents of the city. Through a descriptive analysis, the most useful services that an app can provide are identified. Most importantly, two different types of predictive models (i.e., classification tree and binary logit model) were applied in order to identify groups of users who are more likely to shift to or to use the bike-sharing system due to the sophisticated app. The results of the two predictive models confirm that people of younger ages and those who are not currently users of the system are those most likely to be attracted to the system due to such an app. Other factors, such as car usage frequency, education, and income also appeared to have slight impact on travelers’ intention to use the system more often due to the app.

Assessing the Impact of COVID-19 on Bike-Sharing Usage: The Case of Thessaloniki, Greece

“…A similar attitude towards bike-sharing usage has been also identified in other Greek cities, and it is attributed to the lack of cycling infrastructure and road safety issues [33,34]. The limited networks of bike-sharing stations and the underutilization of technology are two additional reasons for not succeeding in attracting a high number of users [35,36]. The low rates of COVID-19 cases and deaths in Greece are attributed to the timely imposition of movement restrictions.…”

Something for every one? - An investigation of people’s intention to use different types of shared electric vehicle

“…The intention to use commercial bike-sharing systems is positively affected by perceived usefulness of the system, attitude toward bike-sharing, and perceived behavioural control. Nikiforiadis et al (2019) Bike-sharing Users of the bike-sharing system of the city of Thessaloniki, Greece…”

Factors influencing user behaviour in micromobility sharing systems: A systematic literature review and research directions

“…Service quality is discussed in 21 articles (10.40%), that use the SERVQUAL dimensions of Parasuraman et al (1988), along with other service-related variables like MSS efficiency (e.g., Maioli et al, 2019) and Saibene, 2018), availability of relevant data (e.g., Patel and Patel, 2020), app completeness regarding the rental process (e.g., Nikiforiadis et al, 2019), and app user interface design (e.g., Jia et al, 2018). Studies investigating these application features usually find their presence and quality have a positive influence on the willingness to shift to MSS (e.g., Nikiforiadis et al, 2019), attitude towards uncivilized behaviour (e.g., Jia et al, 2018), and user satisfaction (e.g., Manzi and Saibene, 2018).…”