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This study focused on exploring the performance factors (PFs) that impact Infrastructure Sanitation Projects (ISSPs) in the construction sector. The aim was twofold: firstly, to identify these crucial PFs and secondly, to develop a robust performance model capable of effectively measuring and assessing the intricate interdependencies and correlations within ISSPs. By achieving these objectives, the study aimed to provide valuable insights into and tools for enhancing the efficiency and effectiveness of sanitation projects in the construction industry.

To achieve the study's aim, the methodology for identifying the PFs for ISSPs involved several steps: extensive literature review, interviews with Egyptian industry experts, a questionnaire survey targeting industry practitioners and an analysis using the Relative Importance Index (RII), Pareto principle and analytic network process (ANP). The RII ranked factor importance,  and Pareto identified the top 20% for ANP, which determined connections and interdependencies among these factors.

The literature review identified 36 PFs, and an additional 13 were uncovered during interviews. The highest-ranked PF is PF5, while PF19 is the lowest-ranked. Pareto principle selected 11 PFs, representing the top 20% of factors. The ANP model produced an application for measuring ISSP effectiveness, validated through two case studies. Application results were 92.25% and 91.48%, compared to actual results of 95.77% and 97.37%, indicating its effectiveness and accuracy, respectively.

This study addresses a significant knowledge gap by identifying the critical PFs that influence ISSPs within the construction industry. Subsequently, it constructs a novel performance model, resulting in the development of a practical computer application aimed at measuring and evaluating the performance of these projects.

The purpose of this paper is to design and manufacture an intelligent 3D printed sensor to monitor the re-occurrence of diaphragmatic hernia (DH; after surgery) in bovines as an Internet of Things (IOT)-based solution.

The approach used in this study is based on a bibliographic analysis for the re-occurrence of DH in the bovine after surgery. Using SolidWorks and ANSYS, the computer-aided design model of the implant was 3D printed based on literature and discussions on surgical techniques with a veterinarian. To ensure the error-proof design, load test and strain–stress rate analyses with boundary distortion have been carried out for the implant sub-assembly.

An innovative IOT-based additive manufacturing solution has been presented for the construction of a mesh-type sensor (for the health monitoring of bovine after surgery).

An innovative mesh-type sensor has been fabricated by integration of metal and polymer 3D printing (comprising 17–4 precipitate hardened stainless steel and polyvinylidene fluoride-hydroxyapatite-chitosan) without sacrificing strength and specific absorption ratio value.

This chapter proposes to understand the prospects of smart technologies that can transform tourism destinations and instigate regenerative development process. Bio-based resource consumption and technology-driven practices aimed for better sustainable development have been the need of the era. This study emphasizes the theory of regenerative tourism, which attempts to preserve and improve a destination's natural and cultural resources while contributing to the socio-economic development of the host communities. It examines how transformational technologies, like smart infrastructure, big data analytics and renewable energy systems, could assist the tourism industry achieve the transition to a green economy. This chapter illustrates the benefits and problems of integrating such technologies into the tourism infrastructure of a destination. Additionally, it highlights the necessity of cooperation among stakeholders and policymakers and examines the possible environmental, social and economic implications of using a regenerative approach to tourism. The results of this study contribute to the expanding body of knowledge on the development of sustainable tourism and shed light on the transformative potential of technology in creating a more sustainable and resilient future.

This study aims to explore the tower crane safety factors (TCSFs) that influence tower crane safe operations (TCSOs) in modular integrated construction (MiC). It evaluates how the adoption of these factors contributes to achieving TCSOs and promoting sustainable practices (SPs) within MiC.

To achieve this aim, the study employed a systematic search to ensure a comprehensive collection of variables. Additionally, it conducted a questionnaire survey involving professionals and utilized a brainstorming technique to categorize the different variables. Finally, partial least squares structural equation modeling (PLS-SEM) was employed to test the relationship between TCSOs and SPs.

The results of measurement models indicated strong convergent and discriminant validity, with each observed variable correlating well with its latent variable. Moreover, a significant positive correlation between TCSOs and SPs was evidenced by a path coefficient (β = 0.755) and a p-value of <0.05. Lastly, the structural model revealed that the independent variables strongly influence the dependent variable (i.e. SPs) by 57%, underscoring safety's pivotal role in advancing sustainability within MiC projects. These findings provide empirical evidence that improving tower crane safety can directly enhance sustainable practices, offering a dual benefit of increased safety and sustainability for the construction sector.

This study makes a unique and previously undiscovered contribution to the field by identifying the TCSFs in MiC and employing a novel approach by utilizing PLS-SEM to create a unique mathematical model. It offers valuable insights into the relationship between TCSFs, TCSOs and SPs, thus contributing to methodological advancements within Safety Science and providing a foundation for future research and practical implementation in the construction industry.

This paper explored the socioeconomic factors affecting green cities development. Extant literature have highlighted green cities as a major path towards sustainability in the construction industry but very little is known on the socioeconomic aspect of green cities and its bid in promoting sustainability in the construction industry; hence, the premise of this study which highlights the socioeconomic factors affecting green cities development in Ghana.

A comprehensive literature review was conducted to identify the socioeconomic factors affecting green cities. A quantitative research strategy was adopted to collect primary data from respondents who have the requisite understanding and knowledge in green cities using questionnaires. The data gathered was then analysed using descriptive statistics and exploratory factor analysis viz principal component analysis.

The socioeconomic factors affecting green city development comprised: Green support mechanisms (i.e. innovation and technology, green city planning (urban planning), stakeholder engagement, awareness, city planning (transportation) and environmental regulations); green inhibitors (i.e. population, culture, housing and policy implementation); green market and finance (i.e. digital finance, green market mechanism, green investment finance, risks and uncertainties, income levels of clients). It was evident that socioeconomic factors are significant to the development of green cities in Ghana and hence policy makers and various stakeholders should prioritize socioeconomic factors in the bid to achieve sustainability through green cities in the construction industry.

This paper presents a foremost and comprehensive study on the socioeconomic factors affecting green cities in Ghana. The study results showed that even though the path to sustainability in green cities has pivoted mainly on environmental factors, socioeconomic factors are also significant to green city development, hence, policy makers and the construction industry should keenly consider the socioeconomic factors affecting green city development in the bid towards sustainability for cities.

Construction project stakeholders can have a major effect on delivering projects on time. However, little attempt has been made to address the influence of internal stakeholders on delaying project delivery. This research aims to propose the internal stakeholders' influence as a solution to improving project delivery performance (PDP) in order to boost the value of investment in the construction industry's projects.

In Yemen, a structured questionnaire was distributed to owners, consultants and contractors, 283 of which were found usable after the data screening. A purposeful sampling technique was used and structural equation modelling (SEM) was adopted for analysis. The structural model was drawn up, based on seven categories of influencing factors: labour, supplier, designer, contractor, consultant, sub-contractor and owner.

The results of the structural model suggest that of these seven categories, designers, owners, suppliers and subcontractors have a significant p-value and impact on PDP, while the labour and consultant's impact was not substantiated. The findings support the proposal that internal stakeholders' influence contributes directly to construction PDP.

The influence of stakeholders on PDP is important. Nonetheless, few studies have focussed on their effectiveness, especially in developing countries. This paper's contribution is evaluating the cause–effect relationship between stakeholders' influence and construction PDP through analysis of moment structures (AMOS) analysis. The policy implications of the research are to encourage governments in general and construction companies in particular to take responsibility for improving PDP, as slow execution of construction projects leads to increased costs, failure and abandoning projects.