Research Structure and Trends of Smart Urban Mobility

Abstract

Mobility is a subject of increasing importance in a time when cities have gained prominence, as they are home to over 56% of the world’s population and generate over 80% of global GDP. Urban planning principles have traditionally been developed to promote urban efficiency and enhance productivity. The emergence of ‘Smart Mobility’ has provided researchers and policy practitioners new ways to understand and plan cities. With rapid urbanization growth and the sustained mobility challenges faced in most global cities, this paper sets forth to understand and map the evolution of the concept of ‘Smart Urban Mobility’ through a bibliometric analysis and science mapping techniques using VOSviewer. In total, 6079 articles were retrieved from the Web of Science database over 5 decades, from 1968 to 2021, and divided into four sub-periods, namely 1968 to 2010, 2011 to 2015, 2016 to 2019, and 2020 to 2021. The paper provides a better understanding of the thematic focus and associated trends of smart mobility beyond technical issues related to Intelligent Transport Systems (ITS), where due to diverse dynamics, such as unprecedented growth and advancement in technologies, attention has extended to incorporating the impacts of the application of different technologies in urban mobility as well as associated fields. This paper further identifies major sources, authors, publications, and countries that have made more contributions to the development of this field. The findings of this study can help researchers better understand the evolution of the subject, and help policymakers make better-informed decisions on investable infrastructures for better mobility outcomes in urban regeneration pursuits and future cities.

Emerging Trends and Knowledge Structures of Smart Urban Governance

“…Much of the criticism in this respect relates to social sustainability and the balance between the three dimensions of sustainability, especially in relation to citizen participation. Therefore, several studies have argued for the urgency and need for a transformative perspective on smart urban governance as a context-based, socio-technical way of governing cities (e.g., Jiang, Geertman and Witte [14], Pereira et al [154], Webster and Leleux [155]), as well as new forms of human collaboration to attain the desired outcomes, including sustainable mobility to increase the quality of life in cities [156].…”

Examining the Adoption of Sustainable eMobility-Sharing in Smart Communities: Diffusion of Innovation Theory Perspective

“…In the ecosystem, the supply side comprises the transport and logistics service providers level, whereas the demand side is linked to the user interface. The public and regulatory level and eMobility service level comprise the most relevant stakeholders/actors within the ecosystem, which includes the local and national agencies (for example, the Ministry of Transport, urban planning department, and road safety agencies), and the municipality transport service providers and eMobility operator [28,31]. Evidently, mobility-sharing schemes such as car-sharing or ridesharing are one of the sustainable economic models employed in the eMobility business model.…”

Exploring the Evolution and Trends in the Peri-Urban Planning: A Bibliometric Overview

“…SciMAT is another tool used with a longitudinal framework; it provides a mapping of domains, disciplines, articles, or authors correlated using co-word analysis, h-index, number of documents, and citations, etc., over different periods [13]. The analysis yields four different visualizations: (i) strategic diagrams, (ii) thematic networks, (iii) evolution maps, and (iv) overlay graphs [14].…”

“…The incorporation of these periodicals signifies an acknowledgment of the significance of technology and spatial analytic methods in tackling the difficulties faced by peri-urban areas. The publications with the most influence can be identified with the analysis of co-citations by references [13]. The most influential publications in the created database of peri-urban planning can be clustered into three groups as shown in Figure 5.…”