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The purpose of this study is to explore the causal relationship between smart transportation technology innovation and green transportation efficiency.

A comprehensive framework is used in this paper to assess the level of green transportation efficiency in China based on the instrumental variable – generalized method of moments model, followed by an examination of the impact of innovation in smart transportation technology on green transportation efficiency. Additionally, their non-linear relationship is explored, as are their important moderating and mediating effects.

The findings indicate that, first, the efficiency of green transportation is significantly enhanced by innovation in smart transportation technology, which means that investing in such technologies contributes to improving green transportation efficiency. Second, in areas where green transportation efficiency is initially low, smart transportation technology innovation exerts a particularly potent influence in driving green transportation efficiency, which underscores the pivotal role of such innovation in bolstering efficiency when it is lacking. Third, the relationship between smart transportation technology innovation and green transportation efficiency is moderated by information and communication technology, and the influence of smart transportation technology innovation on green transportation efficiency is realized through an increase in energy efficiency and carbon emissions efficiency.

Advancing green transportation is essential in establishing a low-carbon trajectory within the transportation sector.

The concept of green urban mobility has emerged as one of the best approaches for promoting environmental-friendly transportation in local communities. Green urban mobility aims to reshape public transportation system and enhance mobility, with emphasis on deploying digital technologies to promote sustainable public transportation. Therefore, this study aims to analyze existing public transportation policies by exploring how local communities can facilitate green urban mobility by developing a sociotechnical urban-based mobility model highlighting key factors that impact regions transitioning toward sustainable transportation.

This study investigates “the role of data for green urban mobility policies toward sustainable public transportation in local communities” in the form of a systematic literature review and insights from Norway. Secondary data from the literature and qualitative analysis of the national transport plan document was descriptively analyzed to provide inference.

Findings from this study provides specific measures and recommendations as actions for achieving a national green mobility practice. More important, findings from this study offers evidence from the Norwegian context to support decision-makers and stakeholders on how sustainable public transportation can be achieved in local communities. In addition, findings present data-driven initiatives being put in place to promote green urban mobility to decrease the footprint from public transportation in local municipalities.

This study provides green mobility policies as mechanisms to be used to achieve a sustainable public transportation in local communities. Practically, this study advocates for the use of data to support green urban mobility for transport providers, businesses and municipalities administration by analyzing and forecasting mobility demand and supply in terms of route, cost, time, network connection and mode choice.

This study provides factors that would promote public and nonmotorized transportation and also aid toward achieving a national green urban mobility strategy. Socially, findings from this study provides evidence on specific green urban mobility measures to be adopted by stakeholders in local communities.

This study presents a sociotechnical urban-based mobility model that is positioned between the intersection of “human behavior” and “infrastructural design” grounded on the factors that influence green urban mobility policies for local communities transiting to a sustainable public transportation. Also, this study explores key factors that may influence green urban mobility policies for local communities toward achieving a more sustainable public transportation leading to a more inclusive, equitable and accessible urban environment.

Present study aimed to integrate Geographic Information Systems (GIS) and Building Information Modeling (BIM) in conjunction with multicriteria decision-making (MCDM) to enhance infrastructure investment planning.

This analysis combines GIS databases with BIM simulations for a novel highway project. Around 150 potential alternatives were simulated, narrowed to 25 more effective routes and 3 options underwent in-depth analysis using PROMETHEE method for decision-making, based on environmental, cost and safety criteria, allowing for comprehensive cross-perspective comparisons.

A comprehensive framework proposed was validated through a case study. Demonstrating its adaptability with customizable parameters. It aids decision-making, cost estimation, environmental impact analysis and outcome prediction. Considering these critical factors, this study holds the potential to advance new techniques for assessment and planning railways, power lines, gas and water.

The study acknowledges limitations in GIS data quality, particularly in underdeveloped areas or regions with limited technology access. It also overlooks other pertinent variables, like social, economic, political and cultural issues. Thus, conclusions from these simulations may not entirely represent reality or diverse potential scenarios.

The proposed method automates decision-making, reducing subjectivity, aids in selecting effective alternatives and considers environmental criteria to mitigate negative impacts. Additionally, it minimizes costs and risks while demonstrating adaptability for assessing diverse infrastructures.

By integrating GIS and BIM data to support a MCDM workflow, this study proposes to fill the existing research gap in decision-making prioritization and mitigate subjective biases.

This empirical research aims to provide organisations with useful information on how teleworking has affected employee commuting, allowing organisations to adapt working conditions to the new social context. This research sets out to provide evidence on the behaviour of teleworkers in terms of the mode of transport chosen when commuting to work physically.

This research is based on a survey conducted in Madrid based on a theoretical approach grounded in the theory of planned behaviour (TPB) and discrete choice models. Exploratory factor analysis (EFA) and discriminant analysis have been used to determine the variables that influence the mode of transport chosen by teleworkers when commuting in person.

The results indicate the prevalence of private car use by teleworkers when working at the office, finding that attitudes and satisfaction with modes of transport significantly influence their choice. The characteristics and frequency of teleworking, however, are not significant, which indicates that teleworkers attach greater importance to their preferred mode of transport, regardless of the disadvantages.

This research provides empirical evidence using an inductive approach to understand the challenges that organisations are facing with regard to teleworking since commuting behaviour has changed for teleworkers. This requires organisations to give significant reconsideration to the issue of commuting as an important component of working time that could condition employee satisfaction and, therefore, the retention or recruitment of talent. Furthermore, residence and mobility changes afford organisations better access for recruitment, notwithstanding urban planning implications.

In this study, the deployment of an integrated Quality Function Deployment (QFD) decision framework is presented to help cities design targeted strategies to become “smart”. Arguably smart cities leverage advanced technologies to enhance their smartness to improve everyday urban life. To this end, a QFD – Analytic Hierarchy Process – Analytic Network Process (QFD-AHP-ANP) framework is proposed to deliver guidance for selecting the appropriate mix of smart technologies based on the specific smart needs of each city.

The AHP and ANP methods are incorporated into QFD to enhance its methodological robustness in formulating the decision problem. AHP accurately captures and translates the “Voice of the Experts” into prioritized “Smart City” dimensions, while establishing inter-relationships between these dimensions and “Smart City Technologies”. Meanwhile, ANP explores tradeoffs among the technologies, enabling well-informed decisions. The framework’s effectiveness is evaluated through an illustrative application in the city of Thessaloniki.

Applying the framework to this real-world context confirms its practicality and utility, demonstrating its ability to particularize local, social, political, environmental and economic trends through the resulting mix of technologies in smart urban development strategies.

The importance of this study lies in several aspects. Firstly, it introduces a novel QFD decision framework tailored for smart city strategic planning. Secondly, it contributes to the operationalization of the smart city concept by providing guidance for cities to effectively adopt smart technologies. Finally, this study represents a new field of application for QFD, expanding its scope beyond its traditional domains.

Urban mobility has substantially evolved in several western countries, shifting from interest in road expansion strategies to cater motorized movement to the emphasis on sustainable mobility. This is, however, not the case in several developing countries that still try to accommodate vehicular flows in inner historic cities. This paper aims at providing an assessment framework that helps in evaluating the effect of streetscape development on the walking and cycling environment in historic contexts.

This research follows a two-phase methodology. Phase 1 is the investigation of the literature review including the streetscape design, Sustainable Development Goals (SDGs) and indicators for the assessment of walking and cycling environment. This phase results in developing a set of indicators for the assessment. Phase 2 is the case study including, methods, steps and results of the assessment based on the output of Phase 1. This phase concludes with a discussion on the challenges and recommendations for the enhancement.

The streetscape development in Afrang was insufficient and negatively affected the walking and cycling environment. It was motorized-oriented, instead of enhancing green mobility. The interventions led to more crowds, safety risks and less pleasant experience. Moreover, the car users' experience was enhanced initially; however, the traffic situation did not persist. A sustainable urban mobility approach is necessary to be implemented with consideration to the global level and the relation to SDGs.

There is a gap in tackling the research problem both within the context of Port Said in particular and Egyptian context in general. Local authorities need a clear structured methodology to follow in the development of the streetscape. The assessment indicators gathered can be the basis for evaluating future plans.

This study aims to evaluate the key factors affecting the behavioural intention of urban tourists towards visiting national parks by integrating the theory of planned behaviour (TPB) and expectancy theory (ET).

Data were collected from urban tourists using an online questionnaire developed through Google forms. A total of 489 valid online questionnaires were considered for this study. The proposed research model was empirically evaluated using the structural equation modelling method.

According to the results of this research, TPB constructs are significantly and positively associated with the behavioural intention of urban tourists towards visiting national parks in India and out of ET constructs, only expectancy and valence are significantly and positively associated with behavioural intention while instrumentality does not.

This study manifests the behaviour of urban tourists towards national parks and contributes to academics by incorporating existing literature. The findings of this study also help policymakers in formulating innovative strategies for national parks. It presents an integrated framework that lays the platform for a new study domain on urban tourists' intentions to visit national parks, which will be useful to urban managers, officials and the tourism sector. Furthermore, as the scope of this study is confined to assessing the intentions of urban tourists toward visiting national parks, it is difficult to generalize the findings.

To the best of the authors' knowledge, this is the first research of its kind to provide an understanding of the behavioural intention of urban tourists towards visiting the national parks in India by optimizing the TPB and ET.

In an increasingly interconnected world, transportation infrastructure has emerged as a critical determinant of economic growth and global competitiveness. High-speed rail (HSR), characterized by its exceptional speed and efficiency, has garnered widespread attention as a transformative mode of transportation that transcends borders and fosters economic development. The Kuala Lumpur – Singapore (KL-SG) HSR project stands as a prominent exemplar of this paradigm, symbolizing the potential of HSR to serve as a catalyst for national economic advancement.

This paper is prepared to provide an insight into the benefits and advantages of HSR based on proven case studies and references from global HSRs, including China, Spain, France and Japan.

The findings that have been obtained focus on enhanced connectivity and accessibility, attracting foreign direct investment, revitalizing regional economies, urban development and city regeneration, boosting tourism and cultural exchange, human capital development, regional integration and environmental and sustainability benefits.

The KL-SG HSR, linking Kuala Lumpur and Singapore, epitomizes the potential for HSR to be a transformative agent in the realm of economic development. This project encapsulates the aspirations of two dynamic Southeast Asian economies, united in their pursuit of sustainable growth, enhanced connectivity and global competitiveness. By scrutinizing the KL-SG High-Speed Rail through the lens of economic benchmarking, a deeper understanding emerges of how such projects can drive progress in areas such as cross-border trade, tourism, urban development and technological innovation.

This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.