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Construction material management plays a significant role in achieving successful project delivery of a construction project. However, ineffective material management is a critical issue in the construction industry, especially in developing economies, of which Sri Lanka is not an exception. Therefore, this study aims to focus on exploring the causes of ineffective material management practices in civil engineering construction projects in Sri Lanka and their impact on successful project delivery.

Furthermore, the literature findings were validated through the preliminary survey. Subsequently, a quantitative research approach was adopted to pursue the research aim. Questionnaire responses were obtained from 215 construction professionals in civil engineering projects who were selected using the judgemental and snowball sampling techniques. Collected data were analysed through Statistical Package for the Social Sciences (SPSS) V26 and Microsoft Excel 2016.

Moreover, the study revealed that material price fluctuation, shortage of material in the market, delay in material procurement, inadequate planning and delays in material delivery are the most frequent causes of ineffective material management in civil engineering projects. In addition, it was evidenced that most ineffective material management practices cause both time and cost overruns in civil engineering construction projects. Most respondents emphasized inadequate planning, inadequate qualified and experienced staff, lack of supervision and lack of leadership as the causes for both time and cost overruns.

The study was concluded by proposing strategies for effective material management. Education/training/enlightenment of staff in charge of materials management, use of software like Microsoft Project, Primavera and similar software to eliminate manual errors in material management, and providing clear specifications to suppliers were the most agreed strategies for effective material management in civil engineering construction projects.

Construction and Demolition (C&D) Waste Management (WM) poses significant challenges in Sri Lanka, contributing to environmental degradation and resource depletion. To address these issues, this study explores the application of Circular Economy (CE) strategies in minimising waste generation and optimising resource utilisation in Sri Lankan construction industry. The research focuses on the construction and building renovation and use and operate stages of the building project life cycle, recognising their significance in waste generation and resource consumption.

The research employed a qualitative approach, utilising the Delphi technique through three rounds of expert interviews. Seventeen experts were involved in the first round, followed by fifteen in the second round, and twelve in the final round. The collected data was analysed using manual content analysis methods.

The research findings revealed fifteen C&D WM issues in the construction and building renovation stage in Sri Lanka, along with suitable strategies to overcome each of them. Similarly, eight C&D WM issues were identified for the use and operate stage of the building, and corresponding strategies were provided to address each issue. By adopting CE strategies such as modular design and material reuse, construction projects can optimise the project's timeline, cost, and quality factors. These strategies enable efficient resource allocation, reduce waste generation, and contribute to the overall sustainability of the project. The impact of CE strategies on mitigating these issues within the project management iron triangle was also discussed.

This paper entails delving into how construction, building renovation, and operation stages of a building's life cycle intersect with CE strategies, which profoundly influence operational efficiency and long-term sustainability. By incorporating principles such as energy efficiency, water conservation, and circular product design, the paper illuminates how these strategies facilitate decreased energy usage, enhanced resource management, and diminished waste production throughout the building's lifespan.

Cultural heritage archiving is experiencing an increase in digitalisations of artefacts in the last 15 years. The reason behind this trend is a demand for providing information about the artefact in a more accessible way to the audience, for example, through online delivery or virtual reality. Other reasons might be to simplify and automate the management of artefacts. Having a ‘digital copy’ of artefacts, allows one to search an archive and plan its storage and dissemination in a comprehensive manner. With the increased digitalisation comes an increased use of artificial intelligence [AI] applications. AI can be very beneficial in classifying artefacts automatically through machine learning [ML] and natural language processing [NLP]. For example, an algorithm can identify the source and age of artefacts based on an image and can do this much faster for a large collection of photos than a human. Although AI provides many benefits, it also presents challenges: Sophisticated AI techniques require certain insights on how they work, need specialists to customise a solution, and require an existing large dataset to train an algorithm. Another challenge is that typical AI techniques are regarded as black boxes, which means they decide, but it is not obvious why a decision has been made. This chapter describes a project in collaboration with the South Australian Museum [SAM] on the application of AI to extract material lists from a description of artefacts. A large dataset to train an algorithm did not exist, and hence, a customised approach was required. The outcome of the project was the application of NLP in combination with easy-to-customise rules that can be applied by non-IT specialists. The resulting prototype achieved the extraction of materials from a large list of artefacts within seconds and a flexible solution that can be applied on other collections in the future.

The CEEQUAL certification system promotes sustainable development (SD) principles in infrastructure construction, with 12 categories of criteria and indicators. ENVISION assigns 60 points to five categories, while Green Guide is divided into seven classifications. SD certification requires 11 requirements, including an ecological assessment procedure, life-cycle costing assessment, quality control plan, noise mitigation plan, waste management plan, pollution prevention plan, low impact development, pavement management system, site maintenance plan, and educational outreach. SD certification technique provides 8 critical criteria, 153 standards, 17 stringent prerequisites, and 8 categories of points. Culp (2011) developed a grading system to incorporate SD principles into infrastructure projects; Shen et al. (2011) explored significant assessment parameters for the SD of infrastructure projects using the fuzzy set method; Lui and Cui (2012) studied SD frameworks for building projects, Montgomery et al. (2014) and Lim (2009) identified 77 major SD indicators based on a comprehensive review of the relevant literature, and the Transport Division of New South Wales established a Transportation Project Sustainability Framework to ensure the long-term viability of their transportation network and the continuous improvement of their environmental and sustainability performance. Assah Amiril (2014) revealed a global network of 27 SD criteria produced by professionals, for-profit and non-profit organizations, divided into five groups: ecological, financial, sociological, engineering, asset use, and project management. The most important details in this study are that 57 indicators were categorized into eight types, weighted according to their respective impacts, and the influence of each component on SD was evaluated using a 100-dimensional scale. This study investigated the eight criteria and the impact of three additional criteria (public participation, climate change response, and stakeholder management). This chapter examined the criteria and indicators of SD criteria and indicators for road infrastructure development in developing countries. The most important findings are that the CEEQUAL, Ugwu, Haupt, and Lim models are the most comprehensive theoretical models of SD requirements for infrastructure design, and that all frameworks and models promote the sharing, promotion, and acknowledgement of SD concepts.

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

This study examines how applying innovative I4.0 technologies at the design stage can help reduce construction waste and improve the recovery, reuse, and recycling of construction materials.

The study adopts a three-stage sequential mixed methods approach, involving a thorough review of current literature, interviews with six experts in digital construction, and a survey of 75 experienced industry practitioners.

The study identifies and discusses how ten specific digital technologies can improve design stage processes leading to improved circularity in construction, namely, (1) additive and robotic manufacturing; (2) artificial intelligence; (3) big data analytics; (4) blockchain technology; (5) building information modelling; (6) digital platforms; (7) digital twins; (8) geographic information systems; (9) material passports and databases; and (10) Internet of things. It demonstrates that by using these technologies to support circular design concepts within the sector, material recycling rates can be improved and unnecessary construction waste reduced.

This research provides researchers and practitioners with improved understanding of the potential of digital technology to recycle construction waste at the design stage, and may be used to create an implementation roadmap to assist designers in finding tools and identifying them.

Little consideration has been given to how digital technology can support design stage measures to reduce construction waste. This study fills a gap in knowledge of a fast-moving topic.

This paper aims to explore the intellectual structure shaping the circular economy (CE) discourse within the built environment in Africa.

The study adopted a bibliometric analysis approach to explore the intellectual structure of CE in the built environment in Africa. The authors collected 31 papers published between 2005 and 2021 from the Scopus database and used VOSviewer for data analysis.

The findings show that there are six clusters shaping the intellectual structure: demolition, material recovery and reuse; waste as a resource; cellulose and agro-based materials; resilience and low-carbon footprint; recycling materials; and the fourth industrial revolution. The two most cited scholars had three publications each, while the top journal was Resources, Conservation and Recycling. The dominant concepts included CE, sustainability, alternative materials, waste management, lifecycle, demolition and climate change. The study concludes that there is low CE research output in Africa, which implies that the concept is either novel or facing resistance.

The data were drawn from one database, Scopus; hence, adoption of alternative databases such as Web of Science, Google Scholar and Dimensions could potentially have yielded a higher number of articles for analysis which potentially would result in different conclusions on the subject understudy.

This study made a significant contribution by articulating the CE intellectual structure in the built environment, identified prominent scholars and academic platforms responsible for promoting circularity in Africa.

The purpose of this study was constructed a behavioral observation scale for avoiding food waste from the point of view of Chinese cuisine, used as an evaluation tool to examine food waste in the process of food preparation for hospitality students in Taiwan.

The status of food handling in the preparation process was understood through a literature review and interviews. In addition, the indicators that may cause food waste behaviors were established, and the observation and self-evaluation scales of food waste behaviors in the preparation process were developed.

Avoiding water waste, removing excessive edible parts, avoiding waste on seasonings, avoiding cooking for too long and avoiding water stains in the cleaning process were considered by both the observers and the students as items for improvement in the cooking process. The results of this study will help in understanding the intervention in the teaching practice of avoiding students’ food waste behaviors.

This study can only be based on the test results of the current observation behaviors. Meanwhile, many factors need to be taken into consideration, such as the differences in the amount of knowledge students have about food waste, the differences in preparation techniques, and other different factors, which may lead to differences in the research results.

The behavioral observation and self-evaluation behavior scales of “exploring food waste behaviors in the preparation process” were developed and implemented for the current status. The differences between the results of the observation scale and the self-evaluation scale were compared. In addition, the behaviors that may cause students’ food waste were pointed out. Then, the direction of the teaching content was formulated, and the curriculum plan integrating the content of avoiding food waste into teaching was evaluated. Furthermore, the scales can be applied to kitchen staff handling food materials to understand the current situation of their food handling, which can be used as a driving tool for restaurants to reduce food waste.

The construction industry continues to struggle to deliver a right first time culture, seeking a panacea for improvement whilst maintaining project milestones. Complex construction projects demand stringent programmes, however, (un)foreseen changes, political influences and human behaviours all have significant impacts on delivering schemes without error. Previous studies have questioned the ability of the construction industry to successfully learn from errors. A major barrier has been the sharing of sensitive data from failed outcomes. Hence, this paper investigates non-conformance on an existing scheme and suggests avenues for improvement.

A mixed-method approach was adopted whereby 1,260 non-conformance reports (NCRs) from a highways megaproject were interrogated using root cause analysis (RCA) techniques to uncover the most frequent and costly areas. This was followed by a survey to industry professionals within a tier 1 principal contractor to gain insight into their perceptions of non-conformance and rework on construction projects.

Using Pareto analysis, the authors find that materials management, workmanship (poor quality execution) and supervision issues are the most frequently occurring and costly root causes of non-conformance on a major highways scheme. Furthermore, the authors link corresponding viewpoints of two project professional groups to the posed, achieving a high degree of consensus for the areas requiring development. Lastly, the authors suggest avenues for improvement via lessons learnt. These include greater emphasis on quality culture via a strong leadership mandate, enhanced vetting of workforce competence and improving the way materials are managed by embracing technology to drive efficiency.

This paper interrogates a current highways scheme using a uniquely rich, sensitive dataset to determine how the construction sector may improve efforts to achieving right first time outcomes.

Completing construction projects within the planned schedule has widely been considered as one of the major project success factors. This study investigates the use of technologies to address delays in construction projects and aims to address three research questions (1) to identify the adopted technologies and proposed solutions in the literature, (2) to explore the reasons why the delays cannot be prevented despite disruptive technologies and (3) to determine the major strategies to prevent delays in construction projects.

In total, 208 research articles that used innovative technologies, methods, or tools to avoid delays in construction projects were investigated by conducting a comprehensive literature review. An elaborative content analysis was performed to cover the implemented technologies and their transformation, highlighted research fields in relation to selected technologies, focused delay causes and corresponding delay mitigation strategies and emphasized project types with specific delay causes. According to the analysis results, a typological framework with appropriate technological means was proposed.

The findings revealed that several tools such as planning, imaging, geo-spatial data collection, machine learning and optimization have widely been adopted to address specific delay causes. It was also observed that strategies to address various delay causes throughout the life cycle of construction projects have been overlooked in the literature. The findings of the present research underpin the trends and technological advances to address significant delay causes.

Despite the technological advancements in the digitalization era of Industry 4.0, many construction projects still suffer from poor schedule performance. However, the reason of this is questionable and has not been investigated thoroughly.