Search results

While the COVID-19 pandemic has impacted the construction industry, it is still unclear from prior studies about adequately positioning the quality assurance (QA) for the post-pandemic era and future pandemics, especially cross-border construction logistics and supply chain (Cb-CLSC). Thus, this study aims to develop a managerial framework to position the QA of Cb-CLSC during pandemics and post-pandemics by taking lessons from how COVID-19 has impacted the existing QA systems and has been managed successfully.

This is achieved pragmatically through an embedded mixed-method design involving a literature review, survey and interview from experts within the Hong Kong SAR–Mainland China links, typically known as the world’s factory. The design is further integrated with the partial least squares structural equation modelling (PLS-SEM) approach.

The study revealed 10 critical managerial practices (MPs) to position the QA to be adequate for the post-pandemic and during future pandemics, with the top three including “strict observance of government regulations (MP1)”, “planning ahead the period of quality assurance with the quarantine days in host countries (MP6)” and “modification of contract to cater for uncertainties (MP4)”. This attained a relatively good percentage agreement of 53% between the industry and academia. However, the top four MPs regarded as very effective include “implementing digital collaborative inspections with subcontractors and trades (MP8)”, “implementing a digital centralized document and issue management system (MP7)”, “strict observance to government regulations, including vaccination of workers, social distancing, use of prescribed nose masks, etc. (MP1)” and “planning ahead the period of quality assurance with the quarantine days in host countries (MP6)”. Two underlying components of the MPs were revealed as policy-process (PP)-related practices and people-technology-process (PTP)-related practices, and these can be modelled into a managerial framework capable of effectively positioning the QA to be adequate during pandemics through to the post-pandemic era.

The findings of this study depicted significant theoretical and practical contributions to the proactive management of QA activities during pandemics through to the post-pandemic era. It could empower organisations to pay attention to smartly and innovatively balancing people, processes, pandemic policy and technology to inform decisions to effectively position the QA for the post-pandemic era and survive the risks of future pandemics.

The study contributes to the body of knowledge in that it develops a managerial framework to position the QA of Cb-CLSC during pandemics and post-pandemics by taking lessons from how COVID-19 has impacted the existing QA systems and has been managed successfully. It is original research with invaluable primary data in the form of surveys and interviews from experts within the Hong Kong SAR–Mainland China links, typically known as the world’s factory.

The present paper reports on the development of SITE EXPERT: a prototype knowledge‐based expert system. It is an advisory system. SITE EXPERT is intended to be used for productivity improvement in construction and provides advice on: (1) the productivity of three basic operations of construction, i.e. pouring and placing of concrete, erection and removal of formwork, and fixing reinforcement; and (2) human resources and site layout as productivity factors. The system uses information from construction experts, text books, data recorded at construction sites and the engineer's own knowledge, as well as knowledge obtained by running simulation models. In the present paper, the development, operation and evaluation of the prototype system is described. The results of this prototype system development demonstrate that artificial intelligence methodologies provide powerful facilities for capturing information about construction processes and advising the practitioners of construction on productivity improvement within a computer format close to human reasoning.

The workforce management model conceptualised for the effective management of the construction workforce was subjected to expert scrutiny to determine the suitability and applicability of the identified practices and their attributed variables to the construction industry. In achieving this, a Delphi approach was adopted using experts from construction organisations in South Africa. These experts comprised workforce management personnel and construction professionals in senior management positions. The data were analysed using appropriate statistical tools such as interquartile deviation, Kendell’s coefficient of concordance, and chi square to determine consensus among these experts. After a two-round Delphi, the seven constructs proposed in the conceptualised workforce management model were adjudged to be important and worthy of adoption by construction organisations seeking to improve workforce management in the current fourth industrial revolution era.

Construction projects are susceptible to cost and time overruns. Variations from planned schedule and cost estimates can result in huge losses for owners and contractors. In extreme cases, the viability of the project itself is jeopardised as a result of variations from baseline plans. Hence new methods and techniques which assist project managers in forecasting the expected variance in schedule and cost should be developed. This paper proposes a judgment‐based forecasting approach which will identify schedule variances from a baseline plan for typical construction projects. The proposed forecasting approach adopts multiple regression techniques and further utilises neural networks to capture the decision‐making procedure of project experts involved in schedule monitoring and prediction. The models developed were applied to a multistorey building project under construction and were found feasible for use in similar construction projects. The advantages and limitations of these two modelling process for prediction of schedule variance are discussed. The developed models were integrated with existing project management computer systems for the convenient and realistic generation of revised schedules at appropriate junctures during the progress of the project.

While COVID-19 mitigation measures (CMMs) aided in steady recovery during the pandemic, they also impeded movement across economies/borders, affecting quality assurance (QA) of Cross-border Construction Logistics and Supply Chain (Cb-CLSC). However, prior studies on the pandemic in the construction project industry have not revealed how CMMs have impacted QA. Thus, this study aims to evaluate the impact of the CMMs on the QA of Cb-CLSC.

This is achieved by adopting an embedded mixed-method approach involving a desk literature review and engaging 150 experts from different economies across the globe using expert surveys, and results verified via semi-structured expert interviews. Structural equation modelling-based multiple regression analysis (SEM-MRA) was integrated to examine the impact of the CMMs on the QA, along with descriptive and content analysis.

The study confirmed that CMMs have not only impacted the QA negatively but also influenced the positioning of the QA for the post-pandemic era and probably to survive the risks of future pandemics. Among all the identified CMMs, the top three critical measures include “lockdown (CMM2)”, “use of personal protective equipment, such as nose masks, disinfects, etc. (CMM5)”, and “electronic/virtual meetings (CMM7)”. However, CMM5 possesses the highest contributory power to form CMM in impacting the QA, and this can be regarded as largely positive by strengthening health and safety management systems. Its negative impact lies with the project cost increment and the inconveniences of using nose and face masks.

This study provides a better understanding to construction practitioners and policy makers on how the pandemic policies, i.e. CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics.

The study contributes to knowledge in that it provides a better understanding of how the pandemic policies, such as CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics. This area of study has been given limited attention among prior studies during the pandemic.

Construction cost management is one of the important processes that should be achieved effectively and accurately for successful project delivery. Modern-day construction cost management demands a high level of spatial skills. Augmented reality (AR) can potentially increase the stakeholders’ spatial skills as a supportive technology to traditional cost management tools and techniques. AR is a breakthrough technology that could considerably ease execution in various industries, but AR applicability in cost management has not been studied extensively. Thus, this study aims to explore the use of AR in construction cost management tools and techniques.

Data were collected using a qualitative approach consisting of two rounds of the Delphi technique. A total of 22 experts in the construction and information technology fields were interviewed using a purposive sampling technique. The manual content analysis helped analyse data.

The study identified AR features with the potential to increase the usage of cost management tools and techniques. AR can enable spatial skills (abilities, thinking and tasks) in most cost management tools and techniques. However, technical, cultural and technical and cultural barriers obstruct the use of AR in the construction industry.

The usage of AR in construction cost management tools and techniques has not been examined in detail until now. Thus, the study was developed to meet the industry needs and fill the literature gap to investigate the potential use of AR in construction cost management tools and techniques.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

The building industry, through its structure and its mandate, faces endemic information problems; expert systems are expected to impact positively. Expert systems are suited to situations of uncertainty; knowledge and reasoning are separated, allowing easier updating. Knowledge acquisition from human experts is difficult and problems of information reliability arise, suggesting the scope for cooperation between knowledge engineers and documentalists familiar with the domain. In building, prevailing conditions seem to indicate the appropriateness of expert systems, particularly during the design phase; however, written documentation and general research results are rarely consulted. This highlights the need for an information ‘refining’ stage between production and use. It is easier to set up expert systems for specialised sub‐domains; however, on‐going research is attempting to develop a comprehensive approach to project‐specific information that would be operational from initial design through to completed construction. Criteria for a comprehensive design information system can be listed.

To deal with the present situation and recover after the COVID-19 pandemic, construction firms are required to recognise the trends in construction supply chain management (CSCM) for the upcoming years and determine the appropriate practices towards the trends for the improvement of construction activities in terms of strategy, tactic and operations. This paper aims to recognise key trends in CSCM and uses these trends as strategic criteria for the evaluation and prioritisation of lean construction (LC) tools at different project phases including design and architectural engineering, planning and control, on-site construction and safety management.

The integrated analytic hierarchy process–Delphi method is used to collect and analyse the data from construction experts to evaluate the importance levels of the CSCM trends and recommend the appropriate tools for LC practices to improve project performances.

Seven key CSCM trends are identified: lean supply chain management (SCM), supply chain (SC) integration, SC standardisation, SC problem-solving, SC information-sharing, SC flexibility and SC sustainability. Based on these trends, a set of prioritised lean tools are suggested for LC practices, in which “virtual design construction” (VDC) and “last planner system” are considered as the central tools. These two LC practices can be integrated with other effective tools to support the strategic, tactical and operational targets in construction supply chain (CSC) projects.

This study gives the managerial implications by developing an application framework of LC practices for CSC projects. The framework promotes “VDC” as a strategic tool for the phase of design and architectural engineering and considers “last planner system” as the central LC practice for the phase of project planning and control. The framework also focuses on the improvement of efficiency in construction operations by taking into account the aspects of on-site collaboration, problem-solving, improvement and safety.

Up to date, there is still a lack of researches in classifying and prioritising the significant LC tools for each project phase to deal with CSC issues in both breadth and depth. Thus, this study is performed to provide construction managers with the awareness of CSCM trends on which they can focus to have strategic criteria for selecting LC practices to improve CSC performances.

The purpose of this paper is to investigate the factors that discourage construction workers from undergoing skill development training, and to suggest steps for making the training programmes more attractive to them.

The research used an exploratory approach of unstructured interviews with construction workers (bottom-up approach), and the guided group brainstorming technique with the help of experienced industry professionals (top-down approach).

From the unstructured interviews, five inhibiting factors were identified which discourage construction workers from undergoing training. Furthermore, to recognise the causes of the inhibiting factors, 13 possible causal attributes (PCAs) were identified from the brainstorming approach. Subsequently, these PCAs were classified into five possible causal factors (PCFs) on the basis of those concerned stakeholder(s) that are most closely involved and most responsible for fixing them.

The research provides recommendations to practitioners for pragmatic and permanent resolution of each of the PCFs, which serves as a framework for the construction industry to reduce the scarcity of trained workers in the industry. Also, the results may serve as a model for the planning and successful implementation of any new skill-training programme for the construction workers in any developing economy, such as India.

This research contributes to the literature by highlighting the views of construction workers on the training establishments, which very few studies have considered in the past. Also, the research provides a detailed process of brainstorming approach, which will help the research community to appreciate its use in studies related to the construction industry.