<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-07-18T15:08:25Z</responseDate><request verb="GetRecord" identifier="oai:docta.ucm.es:20.500.14352/4621" metadataPrefix="marc">https://docta.ucm.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:docta.ucm.es:20.500.14352/4621</identifier><datestamp>2023-08-27T23:13:08Z</datestamp><setSpec>com_20.500.14352_14</setSpec><setSpec>col_20.500.14352_15</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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      <subfield code="a">Arias Molinares, Daniela</subfield>
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      <subfield code="a">Romanillos Arroyo, Gustavo</subfield>
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      <subfield code="a">García Palomares, Juan Carlos</subfield>
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      <subfield code="a">Gutiérrez Puebla, Javier</subfield>
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      <subfield code="c">2021-09-14</subfield>
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      <subfield code="a">Spain is one of the countries with the highest shared mobility fleet in the world. The shared use of motorcycles, also known as moped-style scooter sharing, has spread far and wide throughout the country at a dramatic pace in recent years. Despite its increasing popularity and impact on urban mobility, efforts devoted to the study of its spatio-temporal travel patterns are still scant. Based on the analysis of GPS records of an operator present in seven Spanish cities, this study aims to contribute to this research gap by analysing mopeds’ location patterns over time and assessing how different dynamics influence its usage level and self-balance potential. Our study is replicable to different cities and different shared modes, since we propose a methodology to identify the most important origins and destinations over time and analyse the system’s self-balance capacity based on spatial autocorrelation tools. These insights are useful for operators to adjust and optimise vehicle distribution routes and maintenance/recharge tasks, decreasing congestion and increasing efficiency. The results may also be helpful for policy makers when planning and offering effective policies and infrastructure to encourage shared mobility.</subfield>
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      <subfield code="a">10.1016/j.jtrangeo.2021.103193</subfield>
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      <subfield code="a">https://hdl.handle.net/20.500.14352/4621</subfield>
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      <subfield code="a">https://doi.org/10.1016/j.jtrangeo.2021.103193</subfield>
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      <subfield code="a">Exploring the spatio-temporal dynamics of moped-style scooter sharing services in urban areas</subfield>
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