Interpretive structural model of trust factors in construction virtual project teams

Purpose Organisational dependence on virtual project teams (VPTs) is growing dramatically due to the substantial benefits they offer, such as efficiently achieving objectives and improving organisational performance. One of the major issues that influence the effectiveness of VPTs is trust building. This study aims to determine the key factors of trust in VPTs and design a model by identifying the interrelationships among the trust factors. Design/methodology/approach Focus group discussion was used to gather data on factors affecting trust in VPTs and their interrelationships. Interpretive structural modelling (ISM) was used to establish the relationship among the factors. Cross-impact matrix multiplication applied to classification analysis was conducted to identify the driving power and the dependence power towards effective VPTs in the construction sector. Findings The finding revealed that “characteristics of team members” (such as ability, integrity, benevolence, competence, reliability and professionalism) is the most significant factor for building trust in virtual team members. Some factors were further identified as having high driving power, while others were defined as having high dependence variables. Practical implications The findings will assist construction managers and practitioners dealing with VPTs identify the factors influencing trust among team members. Taking cognisance of the factors that influence trust will enable them to design more effective virtual team arrangements. Originality/value As the first research of its kind using ISM technique, the study offers insights into interrelationships between trust factors in the construction VPTs. It provides guides for construction managers on the effective management of trustworthy VPTs.

Quantitative visualization of physical barriers for vulnerable pedestrians based on photogrammetry

Purpose The purpose of this study is to propose a method for vulnerable pedestrians to visualize potential obstacles on sidewalks. In recent years, the number of vulnerable pedestrians has been increasing as Japanese society has aged. The number of wheelchair users is also expected to increase in the future. Currently, barrier-free maps and street-view applications can be used by wheelchair users to check possible routes and the surroundings of their destinations in advance. However, identifying physical barriers that pose a threat to vulnerable pedestrians en route is often difficult. Design/methodology/approach This study uses photogrammetry to create a digital twin of the three-dimensional (3D) geometry of the existing walking space by collecting photographic images taken on sidewalks. This approach allows for the creation of high-resolution digital elevation models of the entire physical sidewalk surface from which physical barriers such as local gradients and height differences can be detected by uniform image filtering. The method can be used with a Web-based data visualization tool in a geographical information system, permitting first-person views of the ground and accurate geolocation of the barriers on the map. Findings The findings of this study showed that capturing the road surface with a small wide-angle camera while walking is sufficient for recording subtle 3D undulations in the road surface. The method used for capturing data and the precision of the 3D restoration results are described. Originality/value The proposed approach demonstrates the significant benefits of creating a digital twin of walking space using photogrammetry as a cost-effective means of balancing the acquisition of 3D data that is sufficiently accurate to show the detailed geometric features needed to navigate a walking space safely. Further, the findings showed how information can be provided directly to users through two-dimensional (2D) and 3D Web-based visualizations.

Investigation of the current usage of BIM capabilities by large-sized building contractors in Kenya based on theory of innovation diffusion

Purpose This study aims to focus on the four user characteristics of innovation diffusion (availability, observability and trialability [AOT], simplicity, relative advantage [RA] and interoperability) to observe their influence on building information modelling (BIM) usage. This study focuses on the Kenyan construction industry, specifically the building contractors. Design/methodology/approach This study uses purposive sampling and specifically focusses on active construction sites that met requirements needed for BIM usage to thrive. Data was collected manually using questionnaires (N = 62). Findings This paper contributes to the analysis of the current state of BIM usage by the Kenyan construction industry specifically among building contractors and confirms that Kenya is at the early majority adopters’ stage of diffusion characterised by low BIM usage. In terms of correlation, this study found out that AOT had a strong positive correlation with usage, RA had a moderate positive correlation with usage, simplicity had a weak positive correlation with usage and interoperability had no correlation with usage. Practical implications This study gives a clear trend on BIM usage among building contractors to assist potential BIM users make informed decision. The recommendations in this study can be adopted by any late adopter jurisdiction whose structure of the construction industry is similar to Kenya’s. Originality/value This paper highlights variables that enable or subdue BIM usage. It goes further to localise and contextualise the barriers for deeper understanding of what makes these barriers be major hindrances towards BIM usage and giving practical solutions to these barriers.

The effects of COVID-19 pandemic on the UK construction industry and the process of future-proofing business

Purpose COVID-19 was officially declared as a worldwide pandemic by the World Health Organisation on 11th March 2020, before the UK was put into lockdown on the 23rd March 2020. Organisations had to reconsider their policies and procedures to allow their businesses to continue. This paper aims to focus on the effects of COVID-19 that the UK construction sector has had to undertake to enable businesses while employees had to adhere to COVID-19 lockdown rules. In addition, how the sector can positively continue once normality has returned within the industry. In doing so, this paper understands the historical issues within the construction sector and has had an effect during COVID-19. Design/methodology/approach A qualitative research methodology approach was taken to help obtain live information. In total, 19 semi-structured interviews from 15 organisations related to the construction sector were conducted to collect data. This information was evaluated using thematic analysis to arrive at the results, inferences and recommendations to the sector. Findings This research has revealed that companies have had to adopt a three-stage process to overcome a new dimensional challenge of COVID-19. These include: 1. Making quick decisions during the first stage of the pandemic. 2. Producing new policies and procedures to restart businesses enabling staff to return to the workplace safely. 3. Implementing methods to future-proof organisations against any potential pandemics. To help organisations future-proof their business five C’s are recommended. Originality/value This paper provides a rich insight into the understanding and awareness of the effects of COVID-19 and the changes that the construction sector has had to undertake to adhere to the lockdown rules while remaining productive. This research contributes towards informing policymakers on some of the lessons learned during the management of the COVID-19 pandemic from a construction sector perspective.

Exploring BIM-triggered organisational and professional culture change: a systematic literature review

Purpose Building information modelling (BIM) has had a considerable impact on the socio-technical aspects of construction organisations. Culture has been considered an essential element in BIM practice. Hence, this paper aims to explore existing research relates to culture in the BIM context. Design/methodology/approach A systematic literature review (SLR) was conducted based on the PRISMA guidelines using 104 articles published between 2011 and 2020 and directed with a descriptive and content analysis. Findings The SLR results give evidence that culture in the BIM context is still an under-researched topic. Culture has been considered as both a dependent and independent factor in the BIM domain. Organisational BIM culture is a collection of fundamental beliefs established in a BIM using organisation and passed to new employees with the use of BIM. BIM using organisations are have either weak or strong BIM cultures. Proper analysis and understanding of the BIM culture of different organisations are necessary to realise the strategies of transformation from a weak BIM culture to a strong BIM culture. Originality/value To the best of the author's knowledge, this is the first SLR in BIM research that investigates the role of culture in the BIM setting. This study contributed to the existing body of knowledge by proposing a conceptual framework to understand and change a weak BIM culture of an organisation to a strong, matured BIM culture. This SLR serves as a future research basis in BIM-triggered culture.

The application of “deep learning” in construction site management: scientometric, thematic and critical analysis

Purpose The digital construction transformation requires using emerging digital technology such as deep learning to automate implementing tasks. Therefore, this paper aims to evaluate the current state of using deep learning in the construction management tasks to enable researchers to determine the capabilities of current solutions, as well as finding research gaps to carry out more research to bridge revealed knowledge and practice gaps. Design/methodology/approach The scientometric analysis is conducted for 181 articles to assess the density of publications in different topics of deep learning-based construction management applications. After that, a thematic and gap analysis are conducted to analyze contributions and limitations of key published articles in each area of application. Findings The scientometric analysis indicates that there are four main applications of deep learning in construction management, namely, automating progress monitoring, automating safety warning for workers, managing construction equipment, integrating Internet of things with deep learning to automatically collect data from the site. The thematic and gap analysis refers to many successful cases of using deep learning in automating site management tasks; however, more validations are recommended to test developed solutions, as well as additional research is required to consider practitioners and workers perspectives to implement existing applications in their daily tasks. Practical implications This paper enables researchers to directly find the research gaps in the existing solutions and develop more workable applications to bridge revealed gaps. Accordingly, this will be reflected on speeding the digital construction transformation, which is a strategy over the world. Originality/value To the best of the authors’ knowledge, this paper is the first of its kind to adopt a structured technique to assess deep learning-based construction site management applications to enable researcher/practitioners to either adopting these applications in their projects or conducting further research to extend existing solutions and bridging revealed knowledge gaps.

Exploring the design risk factors for modular integrated construction projects

Purpose Modular integrated construction (MiC) is considered as a process innovation to improve the performance of construction projects. However, effective delivery of MiC projects requires management of risks and uncertainties throughout its delivery chain. Although the design stage of MiC projects is usually managed with limited knowledge based on highly uncertain data and associated with epistemic uncertainties, MiC design risks have not received adequate research attention relative to other stages. The purpose of this paper is to conduct a knowledge-based evaluation and ranking of the design risk factors (DRFs) for MiC projects. Design/methodology/approach The paper reviewed the relevant literature to identify potential DRFs and validated their relevance through pilot expert review. The paper then used questionnaires to gather data from international MiC experts from 18 countries and statistically analyzed the data set. Findings Analysis results showed that the five most significant DRFs for MiC projects include unsuitability of design for the MiC method; late involvement of suppliers, fabricators and contractors; inaccurate information, defective design and change order; design information gap between the designer and fabricator; and lack of bespoke MiC design codes and guidelines. A correlation analysis showed that majority of the DRFs have statistically significant positive relationships and could inform practitioners on the dynamic links between the DRFs. Practical implications The paper provides useful insight and knowledge to MiC practitioners and researchers on the risk factors that could compromise the success of MiC project designs and may inform design risk management. The dynamic linkages among the DRFs instruct the need to adopt a system-thinking philosophy in MiC project design. Originality/value This paper presents the first study that specifically evaluates and prioritizes the risk events at the design stage of MiC projects. It sets forth recommendations for addressing the identified DRFs for MiC projects.

Control method of spray curing system for cement concrete members based on the AdaBoost.M1 algorithm

Purpose Spray curing has become the preferred curing method for most cement concrete members because of its lower cost and sound effect. However, the spray curing quality of members is vulnerable to random variation environment factors and anthropogenic interferences. This paper aims to introduce the machine learning algorithm into the spray curing system to optimize its control method to improve the spray curing quality of members. Design/methodology/approach The critical parameters affecting the spray curing quality of members were collected through experiments, such as the temperature and humidity of the member's surface, the temperature, humidity and wind speed of the environment. The C4.5 algorithm was used as a weak classifier algorithm, and the AdaBoost.M1 algorithm was used to cascade multiple weak classifiers to form a robust classifier according to the collected data. Findings The results showed that the model constructed by the AdaBoost.M1 algorithm had achieved higher accuracy and robustness among the two algorithms. Based on the classification model built by the AdaBoost.M1 algorithm, the spray curing system can cause automatic decision-making spray switching according to the member's real-time curing state and environment. Originality/value With the classification model constructed by the AdaBoost.M1 algorithm, the spray curing system can overcome the disadvantages that external factors greatly influence the current control method of the spray curing system, and the intelligent control of the spray curing system was realized to a certain extent. This paper provides a reference for applying machine learning algorithms in the intellectual transformation of bridge construction equipment.

Value management implementation barriers for sustainable building: a bibliometric analysis and partial least square structural equation modeling

Purpose The purpose of this paper is to examine the relationship between overcoming the value management (VM) implementation barriers and VM implementation in the Egyptian building sector. Design/methodology/approach A critical review of the literature on VM was used to through bibliometric analysis has been conducted to highlight the studies’ gap and establish the VM barriers. These obstacles were then contextually transformed via a semi-structured interview and a pilot study, and subsequently organized in the form of a theoretical model. The primary data was collected from 335 building stakeholders in Egypt through the administration of questionnaire surveys. Consequently, structural equation models of partial least squares were applied to statistically assess the final model of VM barriers. Findings The bibliometric analysis shows that there is an inadequate study on VM implementation barriers in the Egyptian construction industry and insufficient studies on implementing VM in developing countries. Results obtained from the proposed model showed that overcoming the VM barriers has a major connection with successful VM implementation. This is indicated with the value of ß = 0.743, which is necessary when the firm is overcoming 1 unit of VM barriers. Originality/value This study fills the knowledge gap by identifying and emphasizing the critical obstacles to VM implementation.

Building information modelling (BIM) and the return on investment: a systematic analysis

Purpose The purpose of this study is to identify and analyse the key measurable returning factors, value drivers and strategic benefits associated with building information modelling (BIM) return on investment (ROI). The findings of this study provide researchers and practitioners with up-to-date information in formulating appropriate strategies to quantify the monetary value of BIM. The suggested research agenda provided would also advance what is presently a limited body of knowledge relating to the evaluation of BIM ROI. Design/methodology/approach To fill the identified gap, this study develops a comprehensive systematic review of mainstream studies on factors affecting BIM ROI published from 2000 to 2020. A total of 23 academic records from different sources such as journals, conference proceedings, dissertation and PhD theses were identified and thoroughly reviewed. Findings The reported BIM ROI ranged greatly from −83.3% to 39,900%. A total of 5 returning factors, namely, schedule reduction and compliance, productivity improvement, request for information reduction, rework reduction and change orders reduction were identified as the most commonly reported factors that influence BIM ROI. Four quantification techniques including general assumptions-based theoretical model, perceived BIM ROI based on survey, factors affecting BIM ROI with no reported ROI and quantified BIM ROI based on a case study were observed and pointed out in the review, together with their limitations. Finally, three major gaps were raised as the lack of consideration on the likelihood of BIM assisting in a construction project, intangible returning factors influencing BIM-based projects and industry standards in benchmarking BIM ROI. Practical implications The outcomes of this study would assist practitioners by providing the current evaluation techniques that address the limitations with BIM investment and present issues relating to the economic evaluation of BIM in the construction industry. It is also expected that presenting a deeper and wider perspective of the research work performed until now will direct a more focussed approach on productivity improvement efforts in the construction industry. Originality/value This study identifies and analyses the key measurable returning factors, value drivers and strategic benefits associated with BIM ROI on an industry scale rather than a particular organisation or a project scale.