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Mobility is one of the most important and challenging aspects that influence climate change, air quality, and especially the quality of citizens’ lives. Therefore, creating sustainable transport solutions makes way for different modes of transport such as the bicycle, which is continuously gaining more supporters, due to the health, economic, and environmental benefits that it provides. However, cyclists are facing several barriers (e.g., lack of infrastructure), a fact that keeps away commuters from using a bicycle for their daily trips. Investigating the factors that reflect on the commuters’ intention to use a bicycle is a sine qua non for the promotion of sustainable mobility. Therefore, the objective of this paper is the investigation of the factors that prevent residents with low experience or with no cultural/lifestyle background in regards to cycling from cycling. The case study of the city of Larnaca (Cyprus) is deployed by exploring the socio-demographic and trip characteristics of the city’s residents and their relation with the intention to cycle. A two-step approach is developed, namely Explanatory Factor Analysis (EFA) and Structural Equation Modeling (SEM). Despite the promotion of cycling that education is attempting to do (successfully), other factors (such as age, distance, and time) appear to prevent Larnaca’s residents from cycling. Among the actions that local authorities should undertake is that of safety prevention of the vulnerable users of the road network. This group includes elderly people, who need major encouraging interventions by local policymakers and stakeholders.
Bicycle sharing systems (BSSs) have been implemented in cities worldwide in an attempt to promote cycling. Despite exhibiting characteristics considered to be barriers to cycling, such as hot summers, hilliness and car-oriented infrastructure, Southern European island cities and tourist destinations Limassol (Cyprus), Las Palmas de Gran Canaria (Canary Islands, Spain) and the Valletta conurbation (Malta) are all experiencing the implementation of BSSs and policies to promote cycling. In this study, a year of trip data and secondary datasets are used to analyze dock-based BSS usage in the three case-study cities. How land use, socio-economic, network and temporal factors influence BSS use at station locations, both as an origin and as a destination, was examined using bivariate correlation analysis and through the development of linear mixed models for each case study. Bivariate correlations showed significant positive associations with the number of cafes and restaurants, vicinity to the beach or promenade and the percentage of foreign population at the BSS station locations in all cities. A positive relation with cycling infrastructure was evident in Limassol and Las Palmas de Gran Canaria, but not in Malta, as no cycling infrastructure is present in the island’s conurbation, where the BSS is primarily operational. Elevation had a negative association with BSS use in all three cities. In Limassol and Malta, where seasonality in weather patterns is strongest, a negative effect of rainfall and a positive effect of higher temperature were observed. Although there was a positive association between BSS use and the number of visiting tourists in Limassol and Malta, this is predominantly explained through the multi-collinearity with weather factors rather than by intensive use of the BSS by tourists. The linear mixed models showed more fine-grained results and explained differences in BSS use at stations, including differences for station use as an origin and as a destination. The insights from the correlation analysis and linear mixed models can be used to inform policies promoting cycling and BSS use and support sustainable mobility policies in the case-study cities and cities with similar characteristics.
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