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Identifying factors that impact workers’ health and performance is extremely important for companies and, in particular, for companies in the construction sector. Despite the evidence, knowledge about the relationship between commuting, health and worker performance is still limited. More specifically on the relationship with work engagement, studies focus on work-related aspects, neglecting individual and behavioral factors. This study aims to verify the relationship between the commuting patterns of workers, their health and their work engagement in a civil construction company located in São José dos Campos, Brazil.

A structured questionnaire was applied to 43 civil construction workers. The participants’ physical and mental health was evaluated using the 12-item short-form health survey. Employees’ work engagement was assessed through the UWES-17 scale. A descriptive statistical analysis was performed on the relationship between physical and mental health, engagement and commuting to work.

The result corroborated the literature showing that the use of active transport positively influenced the mental health of construction workers and negatively affected those who use individual motorized transport. People working from home had the lowest values for total engagement, vigor and dedication.

This study provides evidence and a prior understanding of this relationship, serving as a basis for decision-making processes in the area of transport that contribute to the health and better functioning of companies in the construction sector. This work also contributes to the state of the art on the relationship between commuting, health and worker engagement.

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.

To address the absence of Lean in transportation logistics in the digital era, this study aims to investigate the application of Lean transportation (LT) tools to reduce waste and facilitate the digital transformation of dedicated road transportation in the offshore industry.

The study adopts action research with a multimethod approach, including a scoping review, focus groups (FG) and participant observation. The research is conducted within the offshore supply chain of a major oil and gas company.

Implementing LT’s continuous improvement tools, particularly value stream mapping (VSM), reduces offshore transportation waste and provides empirical evidence about the intersection of Lean and digital technologies. Applying techniques drawn from organisational learning theory (OLT), stakeholders involved in VSM mapping and FGs engage in problem-solving and develop action plans, driving digital transformation. Waste reduction in loading and unloading stages leads to control actions, automation and process improvements, significantly reducing downtime. This results in an annual monetary gain of US$1.3m. The study also identifies waste related to human effort and underutilised digital resources.

This study contributes to theory and practice by using action research and LT techniques in a real intervention case. From the lens of OLT, it highlights the potential of LT tools for digital transformation and demonstrates the convergence of waste reduction through Lean and Industry 4.0 technologies in the offshore supply chain. Practical outputs, including a benchmarking questionnaire and a plan-do-check-act cycle, are provided for other companies in the same industry segment.

COVID-19 lockdown imposed by the government in India affected markets, factories, industries, construction sites, restaurants, transport services, etc. in which migrant workers were engaged. Migrant workers expected that after the imposition of the lockdown government will facilitate transportation facilities to their hometowns as they lost their jobs. But due to negligence from both the central and the state governments, neither transportation was arranged nor food, shelter or health facilities were arranged. This paper aims to investigate the causes of the death of migrant workers under the theoretical framework of negligence theory.

The authors have applied the content analysis method and collected 926 death cases of migrant workers from 28 Indian states. The researchers applied this technique as the newspapers in India are one of the largest and most useful sources to generate a report/record on migrant workers causes during the COVID-19 lockdown. During the lockdown period, due to lack of attention from the government, police atrocities, hunger and accidental cases increased which resulted in the death of migrant workers.

The finding of the study proves that during the first phase of COVID-19 lockdown the death cases of migrant workers increased due to negligence by the governments. The number of death cases of migrant workers has been analysed through applying negligence theory which included duty, breach, cause, in fact, proximate cause and harm which increased the death cases. It has been noticed that the central government without any prior notice-imposed lockdown all over India, in which all the states were not received any guidelines or communication which indicate what they have to do or how to handle the Covid-19 situation.

To the best of the authors’ knowledge, this is an original work of researchers which is basically based on negligence theory.

The purpose of this study is to identify sustainability assessment indicators of road infrastructure projects by analyzing and synthesizing existing literature, considering that, despite being essential to achieving the sustainable development goals, sustainability performance in road infrastructure projects is a persistent challenge. Therefore, determining how sustainability can be assessed in these projects is crucial, necessitating a systematic review of the sustainability assessment indicators of road infrastructure projects.

Using PRISMA principles, 54 peer-reviewed papers from 2010 to 2022 were retrieved from three search databases (Scopus, Research for Life and Google Scholar) as part of a systematic literature review. Data analysis techniques included both descriptive and content analysis.

The study identified 22 indicators. The results emphasized that the sustainability of road infrastructure projects should consider all three sustainability dimensions to provide development while meeting human needs, preserving the planet Earth and enhancing economic growth. Similarly, indicators should be incorporated from the design phase to implement and attain sustainability successfully.

The outcome of this study will serve as a guide to road infrastructure stakeholders to understand the relevant sustainability indicators to assess the sustainability performance of their projects.

The study’s findings provide the sustainability assessment indicators for roads, which serve as a foundation for developing a sustainability assessment indicator framework for road infrastructure projects. Future research can look at establishing the indicators for the end-of-life phase of the project lifecycle.

This paper aims to investigate the challenges faced by the transport infrastructure sector in its civil construction material supply processes, following the 2016 Kaikoura earthquake in New Zealand.

A case study approach was adopted, which included on-site observations, semi-structured interviews and literature-based desktop reviews.

The research findings show that there were supply problems for aggregates, concrete, stormwater pipes and some specialised products for the repair and rebuild of transport facilities. Those supply problems were largely caused by (1) difficulty in predicting material requirements, (2) constrained supply capability, (3) inadequate local freight capacity, (4) legal, cultural and/or environmental considerations on resource exploitation and utilisation, (5) impacts of COVID-19 and (6) ineffective communication and coordination.

For future research, it is recommended that a comparative analysis of multiple disaster cases be undertaken to further explore the generalisability of the research findings.

The research findings will inform the development of post-earthquake recovery policies and material supply chain operation strategies, in order to expedite the recovery of transport networks if a future earthquake strikes.

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.

With the rise in demand and adoption of smart city initiatives, it is imperative to plan the railway infrastructure, as it will have a huge positive impact if adequately integrated into the planning process. Given the complexities involved, a whole systems thinking framework provides a useful platform for rail transport planners.

This paper proposes a simple, adoptable framework utilising systems thinking concepts and techniques taking into cognisance the key stakeholders. Milton Keynes in the United Kingdom is the adopted case study.

Selected systems thinking tools and techniques are adopted to develop a framework for mapping stakeholders and attributes when developing sustainable rail transport systems, taking note of their core functionalities and the complex systems wherein they exist.

The desire to build future (smart) cities is to effectively match infrastructural resources with a rapidly growing population, and the railway sector can play a strategic role in building a much more competitive low-carbon-emission transport system, which is a driving force for sustainable development.

The urban rail service has become vital to urban development as railway stations serve as hubs for sustainable mobility to meet local requirements. Moreover, it takes extra effort to input railway development into smart city plans, as it is a herculean task to get governments to focus on it with clarity of purpose in passing legislation.

The developed framework reduces complexities when planning and designing rail transport systems compared to many of the existing reductionist planning approaches. The simplicity of the framework would also make it easily adoptable by a wide range of users.

This study examines the carbon emissions of Australia’s agriculture, forestry and fishing sectors from a consumption perspective to develop effective policy frameworks. The objective is to identify key supply chains, industries and products contributing to these emissions and provide recommendations for sustainable development.

A multiregional input-output lifecycle assessment was conducted using the Australian Industrial Ecology Virtual Laboratory (IELab) platform to disaggregate sectors and enable benchmarking against other economic sectors.

In 2018, the “agriculture, forestry, and fishing” sector was responsible for 12.15% of Australia’s carbon footprint. Major contributors included the “electricity, gas, water, and waste” category (26.1%) and the sector’s activities (24.3%). The “transport, postal, and warehousing” sector also contributed 18.4%. Within the industry, the agriculture subsector had the highest impact (71.3%), followed by forestry and logging (15%) and fishing, hunting and trapping (7.6%). Aquaculture and supporting services contributed 6.1%.

The principal constraint encountered by the present study pertained to the availability of up-to-date data. The latest accessible data for quantifying the carbon footprint within Australia’s agriculture, forestry and fishing sector, utilizing the Input-Output analysis methodology through the Australian Industrial Ecology Virtual Laboratory (IELab) platform, about 2018.

The findings of this study provide policymakers with detailed insights into the carbon footprints of key sectors, highlighting the contributions from each subsector. This information can be directly used to develop effective emission-reduction policies, with a focus on reducing emissions in utility services, transport and warehousing.

The study, by raising public awareness of the significant role of industrial agricultural methods in Australia’s carbon footprint and emphasizing the importance of renewable energy and sustainable fuels for electricity generation and road transport, underscores the urgent need for action to mitigate climate change.

This study stands out by not only identifying the most impactful industries but also by providing specific strategies to reduce their emissions. It offers a comprehensive breakdown of specific agricultural activities and outlines mitigation strategies for utility services, agricultural operations and transport, thereby adding a unique perspective to the existing knowledge.

This systematic literature review aims to investigate the application and integration of Industry 4.0 (I4.0) technologies in transportation infrastructure construction projects focusing on sustainability pillars.

The study employs a systematic literature review approach, combining qualitative review and quantitative analysis of 142 academic articles published between 2011 and March 2023.

The findings reveal the dominance of Building Information Modelling (BIM) as a central tool for sustainability assessment, while other technologies such as blockchain and autonomous robotics have received limited attention. The adoption of I4.0 technologies, including Internet of Things (IoT) sensors, Augmented Reality (AR), and Big Data, has been prevalent for data-driven analyses, while Unmanned Aerial Vehicle (UAVs) and 3D printing are mainly being integrated either with BIM or in synergy with Artificial Intelligence (AI). We pinpoint critical challenges including high adoption costs, technical barriers, lack of interoperability, and the absence of standardized sustainability benchmarks.

This research distinguishes itself by not only mapping the current integration of I4.0 technologies but also by advocating for standardization and a synergistic human-technology collaborative approach. It offers tailored strategic pathways for diverse types of transportation infrastructure and different project phases, aiming to significantly enhance operational efficiency and sustainability. The study sets a new agenda for leveraging cutting-edge technologies to meet ambitious future sustainability and efficiency goals, making a compelling case for rethinking how these technologies are applied in the construction sector.