Assessing the Impact of Saudi Vision 2030 on Urban Mobility Transitions: The Case of Riyadh

The increasing requirement for mobility in urban centers and the declining level of service of public transportation has led to worsening congestion. The introduction of smartphone application-based modes of transportation has been described as an innovative strategy to address the problem. This paper presents the outcomes of studies on ridesharing in Metro Manila where ridesharing services are classified under Transport Network Services (TNCs). The main objective is to determine the reasons behind the popularity of ridesharing services, specifically Uber and GrabCar, in Metro Manila, and the corresponding decline of preference and patronage of conventional taxis. A comparative analysis of TNCs and conventional taxis is presented using key indicators. These include travel speed, reliability, passenger expense, and quality of service. For completeness, the study included GrabTaxi services, which represented a basic upgrade of conventional taxis through an app-based system designed to facilitate getting rides. Travel diaries from regular users of ridesharing services were collected and analyzed. Other surveys performed included perception surveys among commuters using TNCs and conventional taxis. Based from the results of the analysis, ridesharing services, specifically Uber and GrabCar are preferred over conventional taxis. TNCs perform better in terms of reliability and safety. Uber and GrabCar were found to have better quality of service compared to conventional taxis. Meanwhile, it was also found that the advantages and attractiveness of ridesharing are very similar to app-enhanced taxis (i.e., GrabTaxi). The study presents recommendations on how both ridesharing and conventional taxis may be improved in the context of sustainable transport as ridesharing is perceived to reduce dependence on private cars but at the same time attracts commuters away from other public transport modes in Metro Manila, including the necessity of government to regulate certain aspects of the TNC operations.

Car sharing (CS) and smart mobility have emerged as pivotal components for a sustainable transformation in urban transportation, standing out as central topics in the discussions on sustainable mobility solutions. Nevertheless, the increasing interest from scholars, CS companies’ owners, and policymakers in car sharing services as a viable response to the sustainable urban transport has availed rather mixed considerations, thus calling for further scrutiny. The current endeavor thus seeks to advance a systematic literature review of the body of knowledge correlatively addressing the issues of various forms of smart mobility and car sharing. Four major research questions are envisaged, namely: What are the bibliometric characteristics of the literature related to smart mobility and car sharing? What is the focus of this literature in terms of key concepts? What are the limitations of the existing body of literature? and What are the implications of this literature in terms of future research avenues? With a view to providing pertinent answers, emphasis will be laid on the insights, critique, and transformative redefinitions of the literature in the field via a bibliometric analysis and structured theme-based review. The SPAR-4-SLR protocol is employed while the data retrieved from the Scopus database was processed with the Bibliometrix package (i.e., Biblioshiny) of the R study program. Derived from the thematic mapping and the identified clusters, six key research topics (i.e., car sharing through the lens of urban mobility management, innovative business models and governance, sustainable transportation and e-car sharing, smart mobility and multimodality, sustainable mobility, public transport, and collaborative consumption, climate change and electric vehicles and transport policy and automotive industry) are thoroughly discussed in terms of added value and limitations. The findings manage to clarify the multiplexity of links between the two constructs, by shedding light on the motor, basic, niche, emerging and declining themes which are worthy of further consideration within a structured research agenda. Additionally, they point to the fact that the issues of smart mobility and car sharing are still producing mixed or fragmented conclusions in terms of socio-economic, technological and environmental impacts, calling for further investigation. Manifold implications of the state-of-the-art in the field are brought to the attention of scholars and practitioners interested in achieving a better understanding and integration of car sharing and smart mobility in the broad transport ecosystem.

This chapter reports a study that was conducted on the impact of private transportation sustainability levels in a cross section of Irish towns and a city. It explains the scope and purpose of the study, the “Sustainability and Future Settlement Patterns in Ireland (SFSPI)”, and why transport related issues are important to the sustainable development in Ireland. Research methods that were adopted are briefly discusses and an analysis is provided on some of the results of the study on the effects of sustainability on private transport choices in Irish settlements. The chapter ends with a brief discussion of the current state of private transport, and the possible means of reducing future pollution, which results from private car use. Where comparisons are made with settlements in other countries, these are generally restricted to the developed world. The research was carried out in the Center for Environmental Research (CER) at the University of Limerick and it was funded by the Environmental Protection Agency under the National Development Plan. The chapter aims to derive a general framework for the planning of more sustainable transport by: (1) explaining and evaluating methods that were developed to analyze the extent to which transport is sustainable in settlements classified by size, location, functionality and place within the national settlement hierarchy; (2) examining the extent to which transport sustainability is related to the size, location, functionality and place within the national settlement hierarchy; (3) examining the competing idea that transport sustainability increases with settlement population size; (4) examining the idea that accessibility plays a crucial role in the development of more sustainable settlements; and (5) examining the effects of urban development on sustainable transport and the relationship between the rate of population growth and sustainable transport.

Promoting sustainable transportation, ride-sourcing and dynamic ridesharing (DRS) services have transformative impacts on mobility, congestion, and emissions. As emerging mobility options, the demand for ride-sourcing and DRS services has rarely been simultaneously examined. This study contributes to filling this gap by jointly analyzing the demand for ride-sourcing and DRS services and examining how it varies across neighborhood-level built environment, transit accessibility and crime, behavioral, and sociodemographic factors. To achieve these objectives, unique geo-coded data containing millions of ride-sourcing and DRS trips in Chicago are spatially joined with up-to-date data on the built environment, transit accessibility, crime, active travel, and demographic factors. A novel Markov Random Field-based joint heterogeneous geo-additive copula framework is presented to simultaneously capture random, systematic, and spatial heterogeneity. Characterized by a Frank copula structure, the demand for ride-sourcing and DRS services exhibited a non-linear stochastic dependence pattern. With spatial heterogeneity and spillover effects, the stochastic dependence of ride-sourcing and DRS demand varied across time of day and was the strongest in compact and dense neighborhoods. Key aspects of the built environment related to urban design (pedestrian-oriented infrastructure), density, and land-use diversity were positively associated with ride-sourcing and DRS demand—suggesting that sustainable mobility goals can be achieved by continuing to invest in more walkable neighborhoods. Active travel and telecommuting were positively linked with ride-sourcing and DRS demand. Complementary and substitutive effects for transit accessibility were found. Results show that increasing transit accessibility in areas with low levels of accessibility (compared to those with high transit levels) could be more helpful in increasing the adoption of ride-sourcing and DRS services. Relative to ride-sourcing, the demand for DRS services appeared more responsive to improvements in pedestrian-infrastructure and transit accessibility. Quantification of non-linear associations with ceiling and overdose effects for the built environment, vehicle ownership, and transit accessibility provided deeper insights. The findings can help guide the development of policy interventions and investment decisions to further accelerate the adoption of mobility-on-demand systems.

Sustainable urban expansion and transportation in a growing megacity: Consequences of urban sprawl for mobility on the urban fringe of Beijing

The consequence of our dependency on the private automobile is well documented in the literature. Roadway congestion, injurious and lethal traffic accidents, atmospheric pollution, groundwater contamination, suburban sprawl, social inequity, and fossil fuel depletion are a sampling from a long list of negative externalities associated with automobile dependency. Two observations from this literature have motivated this research. First, the bulk of the current automobile dependency literature applies exclusively to the urban landscape. While urban areas are certainly deserving of this attention, rapid population growth in rural residential areas threaten the sustainability of these areas. Second, while there is broad agreement that public transit offers a viable option to automobile dependency the sustainable transportation literature offers few examples of how community access to public transit can be enhanced in non-urban areas. This paper looks to the practical contributions from the sustainability literature, namely the use of sustainability indicators as a means of measuring community access to public transit in rural residential areas. A set of sustainable transportation indicators is developed based on three indicator types: land use, community design and transit policy. Using these indicators a questionnaire was sent to eight municipal transit systems serving non-urban areas within the Georgia Basin of British Columbia. This research points to the promise of sustainability indicators as a means of providing improved community access to public transit. Keywords Sustainability indicators, sustainable transportation, public transit, accessibility, mobility, automobile dependency

The need to gain a comprehensive understanding of road travelers’ choice of mode and their perceptions of using sustainable urban mobility modes have evolved to shape the form of future transport planning and policymaking. To combat the concern of growing traffic congestion in Riyadh City, the government of Saudi Arabia designed and introduced a sustainable public transport project named “Riyadh Metro”. This study explores the potential commuters’ perception towards the Metro services and the factors that limit their propensity to use Metro and understand the tradeoffs that the individuals make when they are faced with a combination of mode characteristics (e.g., travel time, price, walking time). The stated preferences experiment was conducted on a sample from the Riyadh neighborhood by structured interviews. A discrete choice model based on binary logistic regression has been developed. The coefficient of travel attribute: travel time, fuel cost, Metro fare, and walking time was found to be statistically significant with a different effect on mode choice. The elasticity of the coefficient showed that an increase in the fuel price by 10% would increase the metro ridership by 5.3% and reduce car dependency. Decreasing the walking time by 5 min to the metro station will increase the metro ridership by 22%. Furthermore, the study revealed that implementing a 1 SAR/hour parking charge will decrease car dependency by 14%. Increase Metro fare by 10% will decrease Metro ridership by 6.9%. The socioeconomic factors coefficient shows a marginal effect on the choice decision of passengers.

Research on travelers’ transportation mode choice between carsharing and private cars based on the logit dynamic evolutionary game model

Currently, an increasing number of private cars drive on roads and produce a massive volume of trajectory data. These data provide a new opportunity for understanding people's travel behavior. In this paper, we conduct an in-depth empirical study of people's travel behavior using private car trajectory data. First, we conduct the study in terms of four metrics, namely, number of trips, average velocity, trip distance, and entropy, and compare the data with those from taxi and ridesharing. Through experiments, we find that the number of trips, average velocity, and trip distance of private cars are more in line with people's travel habits, and the entropy values of private cars are lower. Therefore, we consider private car trajectory data capable of well characterizing people's travel behavior, even better than that from floating cars (such as taxis and buses) or ridesharing services. Moreover, we reveal that a unique metric (so-called dwell time) from the private car trajectory data helps to further understand people's travel behavior. Finally, we propose a fine-grained destination prediction algorithm as a case study, enhancing the state-of-the-art SubSyn algorithm, and show a good understanding of people's travel behavior facilitate a more personalized prediction of final destinations for private cars.

This paper aims to find out the reduction of energy consumption by applying only one item of renewable energy devices. Also, it attempts to reveal the benefits of using means of sustainable transportation on Saudi’s social lifestyle for a specific province which is Asir. Saudi Arabia is looking to enhance its economic resources and social needs. They announced their vision based on specific dimensions; social, economic, and urbanization. Asir province is in the southwest of the Arabian peninsula. It has many potentials for energy efficiency and water resources. Unfortunately, the most important mean of transportation in Asir and all of Saudi Arabia is the private car. The whole country suffers from high energy consumption. It is approximately 1.7 times higher than in Europe per capita. Houses in Asir and the whole of Saudi Arabia consume more energy and there is no implementation for renewable energy resources or devices. They can save the building’s energy consumption and protect the ecology through renewable resources and its devices. On the other hand, installing sustainable means of transportation will enhance Saudi’s lifestyle besides saving fuel consumption. Saudi’s vision is based on urban connectivity development and social enhancement for all sectors that need to apply sustainable development.

Purpose This study examines the integration of generative and predictive artificial intelligence (AI) models within smart cities, focusing on how user readiness and technology adoption influence their contribution to sustainable urban development and governance. Design/methodology/approach The study applies a systematic literature review following PRISMA guidelines and synthesizes evidence from 50 peer-reviewed studies (2018–2025) indexed in Scopus and Web of Science. It combines bibliometric mapping using VOSviewer with thematic analysis to examine the drivers, barriers and governance mechanisms shaping the adoption of generative, predictive and hybrid applications in urban contexts. Findings Generative AI fosters participatory engagement, citizen co-design and interactive simulations, advancing SDG 11 (Sustainable Cities and Communities) and SDG 4 (Quality Education) through enhanced digital literacy and inclusive planning. Predictive AI improves operational efficiency, forecasting accuracy and data-driven policymaking, supporting SDG 9 (Industry, Innovation and Infrastructure) and SDG 13 (Climate Action) by promoting sustainable resource use and climate-resilient management. Hybrid AI integrates these strengths, addressing both social and operational aspects of smart city development and aligning with SDG 17 (Partnerships for the Goals) through cross-sector collaboration and shared governance. Collectively, these models contribute to broader sustainability goals, including SDGs 3, 7 and 12. Research limitations/implications This review acknowledges several key limitations. Reliance on Scopus and Web of Science may exclude regionally significant or domain-specific studies not indexed in these databases. The focus on English-language publications introduces potential language bias, possibly overlooking relevant research from non-English-speaking regions. Restricting the timeframe to 2018–2025 captures recent developments but may omit earlier foundational work or the most recent studies not yet indexed. Differences in research design, policy contexts and sample characteristics also affect comparability and limit generalizability. Future research should broaden data sources, include multilingual literature and adopt mixed-methods and longitudinal approaches to enhance contextual diversity and empirical robustness. Practical implications The findings provide practical guidance for policymakers, urban planners and technology developers to design AI governance systems that are transparent, accountable and aligned with the SDGs. Integrating generative and predictive AI can enhance operational efficiency, support participatory planning and promote responsible decision-making. The findings inform the development of adaptive policy frameworks that advance SDG 9 (Industry, Innovation and Infrastructure), SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action) through digital literacy initiatives, cross-sector collaboration and data-informed management. Strengthening these practices enables cities to translate AI’s potential into tangible contributions to inclusive and sustainable urban transformation. Social implications Integrating user readiness and digital literacy into AI adoption is essential for building inclusive and trustworthy smart cities. These efforts support SDG 4 (Quality Education), SDG 10 (Reduced Inequalities) and SDG 16 (Peace, Justice and Strong Institutions). Generative AI encourages citizen participation and collaborative planning, while predictive AI improves service accessibility and data-informed governance. Promoting ethical awareness and community engagement helps narrow digital divides and address bias. Collectively, these elements advance SDG 11 (Sustainable Cities and Communities) and SDG 17 (Partnerships for the Goals) by fostering socially responsive and transparent AI-driven urban development. Originality/value This review is among the first to integrate perspectives on user readiness and technology adoption with comparative insights into generative and predictive AI in smart cities. It advances understanding of how AI-driven urban innovation supports inclusivity, efficiency and sustainability, while outlining policy directions and a future research agenda for equitable and transparent AI governance.

The development and innovation of information, communication, and technology (ICT) are the key in implementing smart mobility in Singapore to create smart and sustainable mobility. One product of them is MyTransport.SG which has website and mobile application display. This research aimed to analyze MyTransport.SG in supporting the implementation of smart mobility and to understand the role of The Government of Singapore in developing this product. This research used qualitative method and collected the data from transportation and geography journal, government publications, direct observation, and interview to LTA representative as creator and developer of MyTransport.SG. The results showed that MyTransport.SG which was launched in 2011 has provided public informations, data, and report by The Government of Singapore. MyTransport.SG website provides static and dynamic transport dataset. Another display named MyTransport.SG mobile application is developed with Global Navigation Satellite System (GNSS) using Global Positioning System (GPS). This product needs to improve data update and information delivery to create inclusive environment and smart mobility. Beside of a new communication platform, this innovation in MyTransport.SG has implemented smart mobility in Singapore by achieving informative, interactive, assistive, and green mobility variables. Also, MyTransport.SG is included to e-services application by The Government of Singapore to provide advanced, renewable, and sustainable transportation around Singapore.

Over the years, Ghana has invested considerable effort and resources together with international partners to develop the energy sector and to mainstream energy low carbon pathways into national development plans. Low carbon development (LCD) provides a good opportunity, of not only building upon earlier energy and climate change local processes and structures but also help to mainstream low carbon agenda in economic activities and national development plans. For this to work however, require efficient institutions and effective institutional arrangements. Based on extensive literature analysis, personal communications and inputs from stakeholders, the paper highlights the key institutional arrangements, their interactions, challenges and proffers recommendations for improvements. To improve energy and low carbon development effort from the perspectives of institutional structures, would require, clearer institutional mandates, continuous improvements in institutional coordination (intra and inter), capacity and skills development, sustained visibility of the essence of energy and LCD at high political levels as well as engagement by civil societies. Equally important are the issues of finance, data availability and quality, monitoring and evaluation.

Since China's reform and opening-up in 1978, Guangzhou's Tianhe District has undergone significant economic restructuring, reflecting broader national urbanization and marketization trends. Tianhe's economic metamorphosis from agrarian to service-innovation nexus demonstrates significant sectoral realignment (1978-2020). Empirical analysis reveals tertiary dominance, expanding from 35% to 92% GDP share, propelled by strategic urban development initiatives and policy reforms. The Zhujiang New Town and Software Park developments served as primary catalysts for this structural transformation. Findings reveal that Tianhe's economic growth correlates with industrial diversification, talent attraction, and global integration, though challenges like spatial inequality and industrial overconcentration persist. The investigation underscores the function of adaptive governance mechanisms in equilibrating accelerated progress with impartial resource distribution. This case underscores the interplay of state-led strategies and market forces in shaping regional development, contributing to debates on sustainable urban transformation in emerging economies.

In the year 2008, the world faced one of the worst economic recessions. At this point in time, the idea of a smart city was floated by IBM which was a part of the smarter planet initiative (Paroutis et al. 2013). As per various definitions, a smart city is an urban development that takes the help of technology to manage its assets like its infrastructure, important buildings, community services, transportation. The concept of smart city was welcomed by China, UAE, Korea and others. There are six indicators of a smart city, namely “smart economy, smart governance, smart citizen, smart living, smart environment and smart mobility” (Kumar and Dahiya 2017)—mobility or transportation takes the most important position due to its influence on all the other indicators. Statistics show that millions of dollars are invested in research and development of new sustainable modes of transportation systems all over the globe. There are innumerable examples of sustainable smart transport all over the world like Paris, Boston, Germany, Singapore. Each one of these examples lays emphasis on the fact that a well-designed and efficient transport system contributes to economic growth and helps in refining the quality of life of the people, thereby becoming one of the most important sectors of urban development. Post-studying these examples, one can realize that sustainable transportation system contributes to all the different indicators or aspects of a smart city. It is projected by the United Nations that in the coming 15 years the population of top 100 cities of India will grow by 60%. Also with growth in opportunities and increase in the buying capacity, personal motor-vehicle ownership doubles every decade. Land is a precious resource, and utilizing it for making roads to meet the needs of the motorized vehicles is not a solution. This chapter examines the Indian scenario and smart city dream and various successful models of sustainable transportation addressing issues similar to the existing Indian cities, and makes recommendations for the same.