Purpose: 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. Design/methodology/approach: The study employs a systematic literature review approach, combining qualitative review and quantitative analysis of 142 academic articles published between 2011 and March 2023. Findings: 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. Originality/value: 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.

Purpose: Most educational institutions worldwide have shifted to online teaching and learning approaches to mitigate risks imposed by the COVID-19 pandemic. This causes several issues, particularly in delivering the construction management (CM) courses which require site visits, interpreting technical drawings and developing 3D building models. This paper aims to identify the key strategies for online learning and teaching adopted during the COVID-19 pandemic and to investigate the implications for construction management education.Design/methodology/approach: The research approach is twofold. First, the study presents a systematic literature review (SLR) through a synthesis of the existing literature to identify the key strategies and lessons learned about online education during the COVID-19 pandemic in tertiary programs. It also discusses their implications in the context of the construction management (CM) sector in particular. Secondly, the authors shared their hands-on experience as construction management course facilitators – using the autoethnography approach – during the COVID-19 crisis.Findings: In addition to identifying the key strategies such as online course delivery and assessments, the paper critically discusses the barriers to online learning and teaching, including (1) the technological and infrastructure barriers; (2) required online teaching skills and competencies; (3) issues surrounding mental health and wellbeing; (4) lack of consistency in the online delivery of various courses in a given program (5) difficulties around students' engagement and (6) the course characteristics and requirements.Originality/value: The study offers some implications and recommendations not only for educational institutions and staff but also for vendors of online course delivery software. To prepare educational institutions for future online course delivery, the paper proposes several strategies. These include developing a set of guidelines for online course delivery, incorporating online teaching training modules into the recruitment process for academic staff, applying agile and resilience teaching and learning methods, wellbeing and mental health support and continuously improving course features to adapt to the online environment.

The aim of this study is to provide an overview of the current state of Industry 4.0 (IR 4.0) with regard to construction in Australia and to identify the key factors that are driving and hindering its adoption. A literature review and desktop review were conducted to extract mainstream topics, followed by a two-folded workshop designed with a multidisciplinary team of academics, as well as representatives of mainstream firms and peak bodies from the construction value chain. Our study has highlighted the importance of considering both technological and human-related factors in the adoption of IR 4.0 to address barriers that have been traditionally overlooked, and work towards a more successful and holistic implementation of this transformative paradigm. By considering the social aspects of construction, prioritizing data-driven approaches with a focus on privacy and ethics, and emphasizing integration, these facilitators contribute to the effective implementation and success of IR 4.0 in the construction industry. The findings of this study have significant implications for the construction industry in Australia. Addressing the barriers to digital construction adoption and embracing IR 4.0 technologies can help the industry to improve productivity, reduce costs, and enhance sustainability. Additionally, investing in education and training can help to build the necessary skills and capabilities needed to drive the industry forward in the digital age.

Purpose: The rapid integration of artificial intelligence (AI) in technical and engineering higher education presents both unprecedented opportunities and significant challenges. This study investigates how disciplinary characteristics, cultural contexts and institutional readiness influence AI implementation success in higher education. Design/methodology/approach: This study analyzes AI integration in higher education through a dual methodological approach combining systematic literature review and ethnographic observations across different institutes and then proposes a multilevel integration framework that addresses implementation challenges across institutional, departmental and course-specific levels. Findings: The study identifies three distinct approaches to AI integration in assessment: AI-inclusive assessment design, case study-based resistance strategies and hybrid examination models. The bibliometric analysis reveals ChatGPT as the dominant focus in current AI education research. The analysis identifies critical dialectical tensions that shape the integration of AI within higher education assessment practices – namely, the Authenticity–Innovation Paradox (balancing authentic assessment with AI-driven innovation), the Competency–Augmentation Dilemma (preserving core skills amid AI support) and the Scale–Customization Conflict (reconciling scalable models with personalized learning needs). The findings suggest that effective AI integration necessitates a shift from isolated individual innovations to coordinated, institution-wide strategies, conceptualized as “structured flexibility frameworks,” while acknowledging significant regional and cultural variations in implementation approaches worldwide. Originality/value: This study makes several significant contributions to AI integration in technical and engineering higher education. First, it develops a comprehensive multilevel framework that links institutional strategy, departmental approaches and classroom practices, addressing the complex dynamics of AI implementation. Through ethnographic observations across multiple Australian universities, the study provides empirical evidence of successful adaptation strategies, documenting real-world outcomes. Finally, the research establishes a theoretical foundation for understanding how disciplinary and cultural factors influence AI implementation success, providing insights into why certain approaches succeed or fail in different educational contexts. This work advances both theoretical understanding and practical strategies for AI integration in diverse higher education settings.

This study presents a mixed-method systematic literature review (SLR) investigating the applications of Industry 4.0 (I4.0) technologies for enhancing sustainability in transportation infrastructure projects from a construction perspective. A corpus of 199 scholarly articles published between 2009 and November 2023 was meticulously selected from the Scopus database. The thematic analysis categorised the publications into four main clusters: infrastructure type, technology types, project lifecycle stages, and geographic context. The scientometric analysis revealed a burgeoning interest in the integrating of I4.0 technologies to enhance sustainability—particularly environmental sustainability. Among these, Building Information Modelling (BIM)-related tools emerged as the most extensively studied domain (33.50%), followed by the Internet of Things (IoT) and sensors (14%), and Artificial Intelligence (AI) (13.22%). The findings demonstrate that roads, highways, and bridges are the most studied infrastructure types, with BIM being predominantly utilised for energy assessment, sustainable design, and asset management. The main contributions of this review are threefold: (1) providing a comprehensive framework that categorises I4.0 applications and their sustainability impacts across transportation infrastructure types and project lifecycle stages, (2) identifying key technical challenges in integrating I4.0 technologies with sustainability assessment tools, and (3) revealing underexplored areas and providing clear directions for future research. The findings provide actionable insights for researchers and industry practitioners aiming to adopt integrated, sustainability-driven digital approaches in transport infrastructure delivery.

This study presents a quantitative approach to exploring the spatio-functional characteristics of historic Chinese towns (HCTs) from a heritage tourism perspective. In recent years, HCTs have evolved from being resident-oriented to being more tourist-oriented, in part due to their heritage significance for attracting tourists. Spatio-functional qualities of a historic town are essential elements of the town’s urban morphology and of great concern for preservation. Previous studies that discussed this issue often used qualitative descriptions, and only limited studies have systematically explored the spatio-functional qualities of HCTs. Thus, there is presently a lack of understanding around this issue, especially based on rigorous quantitative approaches. This study examines the spatio-functional qualities of HCTs using space syntax, a commonly used method in urban studies that enables measurement of spatial characteristics through mathematical means. Four HCTs with heritage significance, Pingyao, Lijiang, Kulangsu, and Wuzhen, were selected as case studies. The study has examined the role of heritage tourism and the results show that tourist-focused functions tend to distribute and aggregate in the urban core of HCTs. By contrast, cultural relics are freely distributed and not expanded over time. Spatio-functional patterns of the four HCTs were theorised, and the paper concludes with suggestions regarding future land-use optimisation for the four HCTs concerning heritage tourism.