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Studies showed that construction digitalisation could prevent or mitigate accidents rate on sites. Digitalisation applications may prevent or mitigate building project collapse (BPC) but with some encumbrances, especially in developing countries. There is a paucity of research on digital technologies application to prevent or mitigate BPC in Nigeria. Thus, the research aims to explore the perceived barriers that may hinder digital technologies from preventing or mitigating building collapse and recommend measures to improve technology applications during development.

The study is exploratory because of the unexplored approach. The researchers collected data from knowledgeable participants in digitalisation and building collapse in Nigeria. The research employed a phenomenology approach and analysed collected data via a thematic approach. The study achieved saturation at the 29th interviewee.

Findings show that lax construction digitalisation implementation, absence of regulatory framework, lax policy, unsafe fieldworkers' behaviours, absence of basic infrastructure, government attitude, hesitation to implement and high technology budget, especially in developing countries, are threats to curbing building collapse menace via digitalisation. The study identified technologies relevant to preventing or mitigating building collapse. Also, it proffered measures to prevent or mitigate building collapse via improved digital technology applications during development.

This research contributes to the construction digitalisation literature, especially in developing countries, and investigates the perceived barriers that may hinder digital technologies usage in preventing or mitigating building collapse in Nigeria.

Enterprise resource planning (ERP) systems that are equipped with numerous features and functionalities help to improve the profitability of construction corporations around the world through enhancing the efficiency of the functions related to cost management. Thus, the purpose of this study was to investigate the applicability of ERP systems for cost management of building construction projects in Sri Lanka.

A qualitative technique was used in this study, which comprised two-round Delphi-based semistructured interviews. Purposive sampling was used to determine the interviewees. Content analysis was used to evaluate the collected data.

The findings of this study identified the ERP system as a strategic tool for gaining a competitive advantage for an organization while confirming 14 uses of ERP systems and 16 stages of the cost management process. Eighteen issues were finalized at the end of the interview rounds while categorizing the suitable ERP applications at each stage of the cost management process.

Even though there are numerous distinct studies conducted on cost management and ERP systems, there has been a lack of studies conducted on the synergy between these two areas that can be adapted for the building projects in the Sri Lankan context. Therefore, the findings of this study can bring a new paradigm to the Sri Lankan construction sector by influencing the adaption of correct ERP systems at numerous project stages by providing a competitive edge.

Step length is a key factor for pedestrian dead reckoning (PDR), which affects positioning accuracy and reliability. Traditional methods are difficult to handle step length estimation of dynamic gait, which have larger error and are not adapted to real walking. This paper aims to propose a step length estimation method based on frequency domain feature analysis and gait recognition for PDR, which considers the effects of real-time gait.

The new step length estimation method transformed the acceleration of pedestrians from time domain to frequency domain, and gait characteristics of pedestrians were obtained and matched with different walking speeds.

Many experiments are conducted and compared with Weinberg and Kim models, and the results show that the average errors of the new method were improved by about 2 meters to 5 meters. It also shows that the proposed method has strong stability and device robustness and meets the accuracy requirements of positioning.

A sliding window strategy used in fast Fourier transform is proposed to implement frequency domain analysis of the acceleration, and a fast adaptive gait recognition mechanism is proposed to identify gait of pedestrians.

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.

Recent research advocates that there are plenty of opportunities for key players in the offsite construction (OSC) sector to harness the full potential of advanced project management techniques. While previous research mainly focuses on transformations related to digital and advanced technologies driven by industry 4.0 principles, a research gap still exists on the intersection of project management capabilities and OSC. This study attempts to bridge this gap by capturing the homogeneity of different capabilities and integrating them into an overarching framework.

A scientometric analysis is conducted to provide an overview of the co-occurrence network of keywords in the representative studies. A systematic literature review (SLR) of articles published between 2010 and 2022, followed by a subsequent full-text examination of 63 selected articles, revealed 34 interrelated capabilities to be categorised under three exhaustive planning-oriented, design-oriented and delivery-oriented groups.

This review revealed an upward trend of publication on project management capabilities for OSC with a specific interest in optimisation of resources allocated to offsite operations. The top five capabilities discussed more frequently in the literature include (1) artificial intelligence for design error detection, (2) enhanced resource productivity, (3) cost saving in offsite production, (4) real-time traceability of modules and (5) applying lean agile production principles to OSC, which imply the critical role of quality, cost saving, traceability and agility in OSC.

This study elicits core capabilities and develops a new offsite project management framework for the first time. The authors provide directions for researchers and practitioners to apply capabilities for obtaining better outcomes and higher value out of offsite operations.

The construction industry in emerging economies have suffered from productivity issues related to poor resource management as a result of theft. Therefore, this study aims to carry out an exploratory factor analysis of the key causes of theft in the construction industry in Nigeria.

The methodology entailed a review of the literature which identified 58 causes of construction theft. The causes were operationalized through a Likert-scale questionnaire survey, which was revised in a pilot study with ten industry experts. The questionnaire was further distributed to experienced construction professionals in Nigeria. A total of 63 respondents participated in the study, and the results were analyzed through an exploratory factor analysis.

A Kruskal–Wallis test showed no difference in perception of the various group of respondents, while Cronbach alpha test indicated an acceptable level of internal consistency and reliability. The top causes from the literature review were determined through descriptive statistics. However, a Kaiser–Meyer–Olkin measurement resulted in the exclusion of ten causes, and exploratory factor analysis yielded twenty causes in six dominant factors that together account for 55.7% of the variance. The six dominant factors were general theft prevention measures, site security measures, site layout planning, management of materials and equipment, construction project management and policy and safety management.

The limited amount of research on construction site theft in emerging construction environments such as Nigeria contributes to poor construction productivity. This study advances our knowledge of construction site theft and is of significant value to construction stakeholders in effective material and resource management through theft mitigation measures.

The construction of smart cities holds the potential to drive digital innovation in the construction industry through various means, such as enhancing supply and demand. This study echoes the urgent need for the construction industry to overcome development challenges. Hence, it is necessary to study the extent and ways in which smart city policies promote digital innovation in the construction industry.

This study treats China’s smart city policies as quasi-natural experiments. Using a dataset of Chinese prefecture-level cities from 2007 to 2021 and a difference-in-differences model, the study scrutinizes the impact of smart city policies on digital innovation within the construction industry.

The study reveals a substantial positive influence of smart city policies on digital innovation in the construction industry. In addition, the study explains these results by analysing supply-side and demand-side mechanisms. Moreover, the effect of smart city pilot policies on promoting digital innovation within the construction industry displays noteworthy heterogeneity across cities at different regional and political levels.

By exploring the impact and mechanisms of smart city policies on digital innovation in the construction industry, this research contributes to a more comprehensive and profound comprehension of the role of policies in facilitating the digital transformation of the construction sector. It is a valuable reference for policymakers and industry practitioners aiming to advance digital development.

Unlocking the potential of Big Data Analytics (BDA) has proven to be a transformative factor for the Architecture, Engineering and Construction (AEC) industry. This has prompted researchers to focus attention on BDA in the AEC industry (BDA-in-AECI) in recent years, leading to a proliferation of relevant research. However, an in-depth exploration of the literature on BDA-in-AECI remains scarce. As a result, this study seeks to systematically explore the state-of-the-art review on BDA-in-AECI and identify research trends and gaps in knowledge to guide future research.

This state-of-the-art review was conducted using a mixed-method systematic review. Relevant publications were retrieved from Scopus and then subjected to inclusion and exclusion criteria. A quantitative bibliometric analysis was conducted using VOSviewer software and Gephi to reveal the status quo of research in the domain. A further qualitative analysis was performed on carefully screened articles. Based on this mixed-method systematic review, knowledge gaps were identified and future research agendas of BDA-in-AECI were proposed.

The results show that BDA has been adopted to support AEC decision-making, safety and risk assessment, structural health monitoring, damage detection, waste management, project management and facilities management. BDA also plays a major role in achieving construction 4.0 and Industry 4.0. The study further revealed that data mining, cloud computing, predictive analytics, machine learning and artificial intelligence methods, such as deep learning, natural language processing and computer vision, are the key methods used for BDA-in-AECI. Moreover, several data acquisition platforms and technologies were identified, including building information modeling, Internet of Things (IoT), social networking and blockchain. Further studies are needed to examine the synergies between BDA and AI, BDA and Digital twin and BDA and blockchain in the AEC industry.

The study contributes to the BDA-in-AECI body of knowledge by providing a comprehensive scope of understanding and revealing areas for future research directions beneficial to the stakeholders in the AEC industry.

Smart libraries are the result of the application of smart technologies in the era of digital intelligence. The establishment and improvement of its service evaluation system serve as indicators for evaluating the growth of smart libraries.

This study introduces and improves the capability maturity model (CMM), creatively constructs a service maturity model specifically designed for smart libraries and combines the Delphi method with the analytic hierarchy process (AHP) to establish a service maturity evaluation system for smart libraries while calculating indicator weights. Finally, two representative smart libraries are selected as case studies, and an empirical application is conducted using the fuzzy comprehensive evaluation method.

The empirical study shows that the developed smart libraries service maturity evaluation system holds significant theoretical and practical value in evaluating smart libraries.

Enhances the CMM and creatively constructs a service maturity model for smart libraries. Combines the Delphi method with AHP to establish a service maturity evaluation system while calculating indicator weights. Uses a fuzzy comprehensive evaluation method to evaluate two representative smart libraries. Demonstrates that the smart library services maturity evaluation system holds significant theoretical and practical value.

Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational boundaries, firms need to conduct PM jointly with multiple organizations to optimize their operations. However, current knowledge on cross-organizational process mining (coPM) is widely dispersed. Therefore, we synthesize current knowledge on coPM, identify challenges and enablers of coPM, and build a socio-technical framework and agenda for future research.

We conducted a literature review of 66 articles and summarized the findings according to the framework for Information Technology (IT)-enabled inter-organizational coordination (IOC) and the refined PM framework. The former states that within inter-organizational relationships, uncertainty sources determine information processing needs and coordination mechanisms determine information processing capabilities, while the fit between needs and capabilities determines the relationships’ performance. The latter distinguishes three categories of PM activities: cartography, auditing and navigation.

Past literature focused on coPM techniques, for example, algorithms for ensuring privacy and PM for cartography. Future research should focus on socio-technical aspects and follow four steps: First, determine uncertainty sources within coPM. Second, design, develop and evaluate coordination mechanisms. Third, investigate how the mechanisms assist with handling uncertainty. Fourth, analyze the impact on coPM performance. In addition, we present 18 challenges (e.g. integrating distributed data) and 9 enablers (e.g. aligning different strategies) for coPM application.

This is the first article to systematically investigate the status quo of coPM research and lay out a socio-technical research agenda building upon the well-established framework for IT-enabled IOC.