scholarly journals Heat, Hills and the High Season: A Model-Based Comparative Analysis of Spatio-Temporal Factors Affecting Shared Bicycle Use in Three Southern European Islands

2021 ◽  
Vol 13 (6) ◽  
pp. 3274
Author(s):  
Suzanne Maas ◽  
Paraskevas Nikolaou ◽  
Maria Attard ◽  
Loukas Dimitriou

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.

2021 ◽  
Vol 13 (7) ◽  
pp. 4023
Author(s):  
Silvia Marcu

Using the case study of Romanians in Spain, this article highlights how the COVID-19 crisis presents both challenges and opportunities when it comes to human mobility and sustainability. Drawing on in-depth interviews with mobile people during the period of lockdown and circulation restrictions, and in accordance with the objectives of the Sustainable Development Goals (SDGs), the paper advances and contributes to the relevance of sustainability and its impact on people’s mobility in the context of the COVID-19 pandemic. I argue that even in the midst of the crisis, sustainable ways may be found to promote and protect human mobility. The paper raises the way sustainability acts as a driver, gains relevance and influence, and contributes to the creation of new models of resilient mobility in times of crisis. The conclusions defend the respect for the SDGs regarding human mobility and emphasise the role of people on the move as sustainable actors learning to overcome distance and the barriers to their mobility during the pandemic.


2021 ◽  
Vol 13 (4) ◽  
pp. 2189
Author(s):  
Aurore Flipo ◽  
Madeleine Sallustio ◽  
Nathalie Ortar ◽  
Nicolas Senil

Sustainable mobility issues in rural areas, compared with urban mobility issues, have so far been poorly covered in the French and European public debate. However, local mobility issues are determining factors in territorial inequalities, regional development and ecological transition. This paper is based on preliminary findings of qualitative socio-anthropological fieldwork carried out in two rural departments of the Auvergne-Rhône-Alpes region: Drôme and Ardèche. Our objective is to highlight how the question of sustainable local mobility is linked to governance issues and multiple overlapping institutions. We argue that analyzing stakeholders’ strategies and territorial governance is key to understanding the contemporary dynamics surrounding a transition towards a more sustainable mobility in rural areas. In order to do so, we show how the debates surrounding the adoption of a law allowing for the transfer of responsibility to local authorities for the organization of mobility services reveals the complexity of local mobility governance in rural areas and provides material for the analysis of the logics of stakeholder engagement, cooperation and conflict within the field of sustainable mobility. Through the case study of the organization of a local public transport service in a rural area, we shed light on the action of multiple stakeholders and their potentially antagonistic objectives.


Author(s):  
Beniamino Di Martino ◽  
Dario Branco ◽  
Luigi Colucci Cante ◽  
Salvatore Venticinque ◽  
Reinhard Scholten ◽  
...  

AbstractThis paper proposes a semantic framework for Business Model evaluation and its application to a real case study in the context of smart energy and sustainable mobility. It presents an ontology based representation of an original business model and examples of inferential rules for knowledge extraction and automatic population of the ontology. The real case study belongs to the GreenCharge European Project, that in these last years is proposing some original business models to promote sustainable e-mobility plans. An original OWL Ontology contains all relevant Business Model concepts referring to GreenCharge’s domain, including a semantic description of TestCards, survey results and inferential rules.


2020 ◽  
Vol 3 (S1) ◽  
Author(s):  
Yousra Sidqi ◽  
Pierre Ferrez ◽  
Dominique Gabioud ◽  
Pierre Roduit

Abstract In this paper, a thorough analysis of quantification of the heating appliances’ flexibility provided by 200 households located in the Sion area (Switzerland) is presented. An extended evaluation of the available flexibility throughout the year as well as a correlation analysis between the outside temperature and flexibility is performed. The influence of pooling households in the prediction process is assessed. The impact of cutting the power to heating appliances and the incurred rebound effect are also described.


2019 ◽  
Vol 38 (30) ◽  
pp. 5603-5622 ◽  
Author(s):  
Bernard G. Francq ◽  
Dan Lin ◽  
Walter Hoyer

Author(s):  
Kevin P. Josey ◽  
Brandy M. Ringham ◽  
Anna E. Barón ◽  
Margaret Schenkman ◽  
Katherine A. Sauder ◽  
...  

2021 ◽  
pp. 096228022110175
Author(s):  
Jan P Burgard ◽  
Joscha Krause ◽  
Ralf Münnich ◽  
Domingo Morales

Obesity is considered to be one of the primary health risks in modern industrialized societies. Estimating the evolution of its prevalence over time is an essential element of public health reporting. This requires the application of suitable statistical methods on epidemiologic data with substantial local detail. Generalized linear-mixed models with medical treatment records as covariates mark a powerful combination for this purpose. However, the task is methodologically challenging. Disease frequencies are subject to both regional and temporal heterogeneity. Medical treatment records often show strong internal correlation due to diagnosis-related grouping. This frequently causes excessive variance in model parameter estimation due to rank-deficiency problems. Further, generalized linear-mixed models are often estimated via approximate inference methods as their likelihood functions do not have closed forms. These problems combined lead to unacceptable uncertainty in prevalence estimates over time. We propose an l2-penalized temporal logit-mixed model to solve these issues. We derive empirical best predictors and present a parametric bootstrap to estimate their mean-squared errors. A novel penalized maximum approximate likelihood algorithm for model parameter estimation is stated. With this new methodology, the regional obesity prevalence in Germany from 2009 to 2012 is estimated. We find that the national prevalence ranges between 15 and 16%, with significant regional clustering in eastern Germany.


2015 ◽  
Author(s):  
Dário Ferreira ◽  
Sandra S. Ferreira ◽  
Célia Nunes ◽  
João T. Mexia

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