Identification of Enablers and Barriers for Public Bike Share System Adoption using Social Media and Statistical Models

Ainhoa Serna, Tomas Ruiz, Jon Kepa Gerrikagoitia and Rosa Arroyo
Additional contact information
Ainhoa Serna: Computer Science and Artificial Intelligence Department, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastián, Spain
Tomas Ruiz: Transport Department, School of Civil Engineering, Universitat Politècnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain
Jon Kepa Gerrikagoitia: IDEKO, ICT and Automation Research Group, Arriaga 2, 20870 Elgoibar, Spain
Rosa Arroyo: Transport Department, School of Civil Engineering, Universitat Politècnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain

Sustainability, 2019, vol. 11, issue 22, 1-21

Abstract: Public bike share (PBS) systems are meant to be a sustainable urban mobility solution in areas where different travel options and the practice of active transport modes can diminish the need on the vehicle and decrease greenhouse gas emission. Although PBS systems have been included in transportation plans in the last decades experiencing an important development and growth, it is crucial to know the main enablers and barriers that PBS systems are facing to reach their goals. In this paper, first, sentiment analysis techniques are applied to user generated content (UGC) in social media comments (Facebook, Twitter and TripAdvisor) to identify these enablers and barriers. This analysis provides a set of explanatory variables that are combined with data from official statistics and the PBS observatory in Spain. As a result, a statistical model that assesses the connection between PBS use and certain characteristics of the PBS systems, utilizing sociodemographic, climate, and positive and negative opinion data extracted from social media is developed. The outcomes of the research work show that the identification of the main enablers and barriers of PBS systems can be effectively achieved following the research method and tools presented in the paper. The findings of the research can contribute to transportation planners to uncover the main factors related to the adoption and use of PBS systems, by taking advantage of publicly available data sources.

Keywords: sustainable transport; public bike share (PBS) systems; transportation; social media analysis; sentiment analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/22/6259/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/22/6259/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:22:p:6259-:d:284676

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().