面向城市政策制定的智慧城市可持续交通治理——范围审查和概念模型

IF 3.5 Q3 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY
Bokolo Anthony Jnr
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引用次数: 0

摘要

本研究的目的是提出一种治理模式和关键绩效指标,以指导政策制定者如何在智慧城市内部和城市之间促进更便捷、更包容和更可持续的交通,并以公共交通基础设施的合理管理为基础,研究可持续的城市交通。设计/方法/方法本研究采用桌面研究方法,基于现有文件和先前研究的二手数据,开发了一个可持续的交通治理模型,探讨了影响未来城市政策制定的关键因素。收集的二手数据进行了描述性分析,以提供在智慧城市中实现可持续移动服务所需的举措和要素。本研究的结果为城市如何从不同来源的数据应用中获益提供了证据,以提供增值服务,促进综合和可持续的交通。此外,本研究的结果还讨论了智能移动在可持续服务中的作用,以及数据驱动计划在可持续智慧城市中的应用,以增强移动互联性、可达性和多模态。本研究的结果确定了影响可持续交通转型的技术和非技术因素。实际上,本研究提倡在智慧城市中使用智能交通和数据驱动服务,通过提高社会意识和支持政策制定者做出明智的决策,改善通勤者的行为,以实现长期行为改变,从而实现可持续的交通。本研究的启示为政策制定者和市政当局实施数据驱动的移动服务提供了信息支持。本研究对个人行为的改变提供了启示,通过将可持续性维度纳入其当前和未来的发展,采用更可持续的旅行模式,提高公民的生活质量,提高提供交通相关服务的企业的经济可行性,并为市政当局和决策者在城市规划和设计过程中提供决策支持。本文探讨了城市交通如何大大减少温室气体排放,并为城市改善公共交通的可达性和可持续性提供了启示,同时促进了城市内部和城市之间采用更环保的交通方式。此外,本研究还详细讨论了城市环境在实现可持续交通方面面临的潜在机遇和挑战。本研究中开发的治理模型也可以被技术初创公司和运输公司用来评估他们需要到位或改进的因素,以提供可持续的移动服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sustainable mobility governance in smart cities for urban policy development – a scoping review and conceptual model
Purpose The aim of this study is to propose a governance model and key performance indicators on how policymakers can contribute to a more accessible, inclusive and sustainable mobility within and across smart cities to examine sustainable urban mobility grounded on the rational management of public transportation infrastructure. Design/methodology/approach This study employed desk research methodology grounded on secondary data from existing documents and previous research to develop a sustainable mobility governance model that explores key factors that influence future urban policy development. The collected secondary data was descriptively analyzed to provide initiatives and elements needed to achieve sustainable mobility services in smart cities. Findings Findings from this study provide evidence on how cities can benefit from the application of data from different sources to provide value-added services to promote integrated and sustainable mobility. Additionally, findings from this study discuss the role of smart mobility for sustainable services and the application for data-driven initiatives toward sustainable smart cities to enhance mobility interconnectivity, accessibility and multimodality. Findings from this study identify technical and non-technical factors that impact the sustainable mobility transition. Practical implications Practically, this study advocates for the use of smart mobility and data-driven services in smart cities to improve commuters' behavior aimed at long-term behavior change toward sustainable mobility by creating awareness on the society and supporting policymakers for informed decisions. Implications from this study provide information that supports policymakers and municipalities to implement data-driven mobility services. Social implications This study provides implications toward behavioral change of individuals to adopt a more sustainable mode of travels, increase citizens’ quality of life, improve economic viability of business involved in providing mobility-related services and support decision-making for municipalities and policymakers during urban planning and design by incorporating the sustainability dimension into their present and future developments. Originality/value This paper explores how urban transportation can greatly reduce greenhouse gas emissions and provides implications for cities to improve accessibility and sustainability of public transportation, while simultaneously promoting the adoption of more environmentally friendly means of mobility within and across cities. Besides, this study provides a detailed discussion focusing on the potential opportunities and challenges faced in urban environment in achieving sustainable mobility. The governance model developed in this study can also be utilized by technology startups and transportation companies to assess the factors that they need to put in place or improve for the provision of sustainable mobility services.
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来源期刊
Smart and Sustainable Built Environment
Smart and Sustainable Built Environment GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY-
CiteScore
9.20
自引率
8.30%
发文量
53
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