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In successfully meeting city and metropolitan growth, sustainable development is compulsory. Sustainability is a must-focus for any project, particularly for large and mega rail infrastructure. This paper aims to investigate to what degree social, environmental and economic factors influence the government when planning sustainable rail infrastructure projects. To respond to such a matter, this paper focuses on two Australian mega-rail projects: the South West Rail Link (SWRL) and the Mernda Rail Extension (MRE).

As the basis of an experimental evaluation framework strengths, weaknesses, opportunities and threats (SWOT) and factor analysis were used. These two methods were specifically selected as comparative tools for SWRL and SWRL projects, to measure their overall sustainability effect.

Using factor analysis, in the MRE, the factors of network capacity, accessibility, employment and urban planning were seen frequently throughout the case study. However, politics and economic growth had lower frequencies throughout this case study. This difference between the high-weighted factors is likely a key element that determined the SWRL to be more sustainable than the MRE. The SWOT analysis showed the strengths the MRE had over the SWRL such as resource use and waste management, and natural habitat preservation. These two analyses have shown that overall, calculating the sustainability levels of a project can be subjective, based on the conditions surrounding various analysis techniques.

This paper first introduces SWRL and MRE projects followed by a discussion about their overall sustainable development. Both projects go beyond the traditional megaprojects' goal of improving economic growth by developing and enhancing infrastructure. Globally, for such projects, sustainability measures are now considered alongside the goal of economic growth. Second, SWOT and factor analysis are undertaken to further evaluate the complexity of such projects. This includes their overall sustainable development vision alignment with environmental, economic and social factors.

Women's travel pattern is different from those of men. Women who have both paid employment and unpaid care work have more complex travel patterns. However, land-use policies and urban mobility strategies in the Egyptian context do not consider these differences. This paper analyzes and discusses the travel patterns of the Egyptian working women with children. It examines the difference between men's and women's travel behavior in different income levels. The paper aims at determining the main factors that affect working women's travel patterns within the care economy framework and suggesting recommendations for enhancing women's travel patterns in Greater Cairo Region (GCR).

The methodology relies on conducting a quantitative and qualitative analysis using questionnaires and interviews with working women and men from different social/economic levels in two different workplaces in GCR.

The results demonstrate that income level, workplace locations, schools locations, and schools typologies greatly affect working women's travel patterns in GCR.

The study findings will help urban planners and decision-makers to improve working women's mobility to make their daily trips shorter and more accessible to achieve equitable cities through understanding the conducted affecting factors and considering the suggested recommendations.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

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.

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 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.

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.

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.

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.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

This study intends to analyze the trend of walkability research over two years (2021–2022) in several aspects, including the research problem, gap and aim underlying walkability issues, research setting, the scale of analysis, the type of data, the data collection tool, the analysis method and contribution.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) is employed to conduct a systematic literature review from three leading databases including Web of Science (WoS), Scopus and Sage.

From the review, it can be concluded that the research focuses on two aspects, namely, the built environment and people. The studies in this field are conducted at different scales of the built environment, from macroscale to microscale, including region, city, neighborhood and street-level studies that are conducted around the world including Asia, Europe and America which receive high attention from researchers. Meanwhile, the study of walkability in Australia and Africa gains less attention. It is revealed that there are four factors of walkability including land use and accessibility for macroscale which cover region, city and neighborhood, while street network and pedestrian infrastructure and facility are mainly analyzed for street-level. Most of the studies widely utilize a quantitative approach for analyzing physical walkability factors in a measurement-based approach by using certain tools/software, and a perception-based approach by using questionnaires.

The findings can assist to keep up with the rapid pace of scientific publications and help accelerate the understanding of particular ideas in the field of walkability for the planning and design practice and policy that can be used by researchers/academia, urban designers, urban planners, architects, engineers and policymakers. Also, this study hopefully could assist further research direction for the future and could add value to a more advanced way of understanding the research on walkability.

This research provides a robust framework for walkability trend analysis and a comprehensive understanding of the main ideas from the existing research on walkability worldwide.

This paper aims to understand the spatiotemporal influence of metro rail connectivity on housing prices in surrounding areas. The study assesses the average annual price shift for apartments around metro stations in Delhi during the previous decade, specifically from 2010 to 2019. The authors examine the spatiotemporal extents to which housing prices are determined by the prominence of metro stations and spatial development around metro stations.

The authors perform the cross-tabulation analysis to calculate chi-square values to test the hypotheses concerning the responsiveness of the housing market in Delhi to the number of locational variables in the areas connected with the mass public transportation system.

The empirical findings verify the existence of a housing market overvaluation in Delhi around metro stations until 2013, which was eventually re-adjusted after 2014. The key findings of the study suggest the role of location variables concerning metro rails in the shooting up of the housing prices in the city. In addition, the research establishes the association of annual housing price shifts to the metro rails in the short-term, mid-term and long-term in conjunction with the distance from the metro station.

In the market, the prices are often overvalued by real estate agents due to better connectivity to the metro stations. The overvaluation eventually causes massive downfalls in housing markets and rollouts as a risk for the investors. However, the effect of mass transportation on housing prices is mixed in nature, limited to a certain extent only and not as influential as frequently portrayed by the market forces. This effect loses colour with time.

There is lack of knowledge about how the existing streets need to be redesigned and the infrastructural changes that need to be made to adopt autonomous vehicles. The purpose of this study is to investigate the infrastructure requirements of autonomous vehicles in terms of (1) lane widths, (2) parking spaces, (3) drop-off zones and (4) other facilities, followed by analyzing them and suggesting changes in the existing urban design of Msheireb Downtown Doha (MDD).

Mixed method of combining both qualitative (secondary research of analyzing the existing data about the urban design guidelines for an autonomous future, observations of the existing infrastructure) and quantitative methods (on-site measurements of pedestrian walkways and road lane widths) is used.

The outcome of the research consists of a series of major infrastructural changes with regard to lane widths, parking spaces, pick-up and drop-off zones and other facilities needed for the deployment of autonomous vehicles.

The results imply that Qatar can benefit by adopting the proposed urban design suggestions for the implementation of autonomous vehicles on the streets of MDD in particular, and smart cities of Qatar and the region in general.

The proposed changes can work as a reference and serve as a possible setting for addressing Autonomous Vehicle preparations in emerging cities.

The proposed urban design changes can be adapted for an autonomous future in emerging cities.

This paper explores the relationship between state-led urbanization and primary industry development using the difference-in-differences (DiD) method.

The study uses the DiD method.

Exploiting county-city mergers during 2010–2018, the key strategy to expand the city outward and promote urbanization on the urban fringe by local government, the authors find that county-city mergers led to the growth of primary industry decline by 4.23%. The result can be explained by the loss of essential production factors, including land and labor used for farming. In addition, the negative effect is more pronounced for counties with more substantial manufacturing. The results indicate that urbanization in China relocates land and labor; however, it does not improve the efficiency of agricultural output.

This paper contributes to the understanding of urbanization and rural development from the perspective of the primary industry by showing production factor redistribution. Second, this study complements the literature on local government mergers.