Search results

This research aims to study a broad range of sustainability aspects and develop a set of indicators with their subjective relevance to each of the sustainability dimensions that will help to improve the sustainability level of the water system of Nur-Sultan (Kazakhstan).

The broader list of indicators (which were identified through a thorough review of the literature) was assessed by water-related industry professionals and experts who were asked to assess the compliance of suggested indicators to five criteria of sustainability using a Likert scale.

It was found that the highest-ranked indicators across all five categories were mainly related to the chemical and physical quality of water, followed by availability of individual water meters as well as water supply tariffs' adjustment to users' income, and issues of ageing infrastructure. The lowest-ranked indicators among all categories were mainly related to investments into research and development, water management and awareness, feedback systems and flexibility. The least ranked indicators are seen to be more related to the scenarios when basic needs are covered and the stakeholders have extra time and resources for advancing the levels of water infrastructure sustainability.

The ranked and categorized indicators can be used as a powerful decision-making tool to improve the sustainability of the water system of Nur-Sultan or any other city in a developing country.

By conducting this study, it was aimed to address the aforementioned gap in the field in terms of running a wider scope assessment of indicators rather than looking at conventional environmental and socio-economic aspects. This provides novelty to the study, especially in the context of developing countries that need more guidance in terms of sustainable development of the water-related infrastructure.

The study investigates the causes of project cost overruns (COs) that have been reported in the construction-management-related articles since 1985.

To achieve the aim and provide recommendations to avoid project COs, 48 selected journal articles were reviewed and assessed with regard to the countries, institutions and researchers that have contributed to the subject.

The review of the articles shows that the subject has attracted a considerable attention from the researchers worldwide. However, the problem mainly occurred in developing countries and the researchers drew the attention on the resource-related, economic/financial as well as political problems. While 79 causes of COs were identified, the top ten causes of project COs, which have received the highest number of citations by the reviewed articles, were presented and discussed. These causes are: design problems and incomplete design, inaccurate estimation, poor planning, weather, poor communication, stakeholder's skill, experience and competence, financial problems/poor financial management, price fluctuations, contract management issues and ground/soil conditions.

The study findings have several implications, which are not only for the academic world, but also for the construction front line. For scholars, the study provides a list of project COs that the researchers in the area could benefit for their future studies. The industry practitioners could find ways to improve project cost performance by giving attention to the causative factors that are significantly affecting construction projects and investing their resources and efforts towards the most occurred ones.

Thus, this study provides insight into the research output on the subject and a checklist of COs, which is believed to provide a better understanding of significant areas requiring attention where steps should be taken to minimize or control factors causing COs in construction projects.

The aim of the present study is to assess the selected heating systems (furnace and boiler) commonly used in the dwellings of seven post-USSR (the Union of Soviet Socialist Republics) countries. The systems were assessed in terms of their cost and environmental performance, with natural gas and electricity used as the main source of energy.

The cost-effectiveness and environmental performance of the selected heating systems that have been commonly used in the selected post-USSR countries was assessed. Current energy (natural gas and electricity) prices that are applied in those countries were used.

Results show that the furnace is the cheapest option, while natural gas is the cheapest source of energy, despite its high price in Tajikistan and Kyrgyzstan. Both heating systems could be considered eco-friendly options, although their efficiencies need to be considered at the design stage. Turkmenistan, Uzbekistan and Kazakhstan, which are the top natural gas producers, offer natural gas for the selected heating systems as both cost-effective and eco-friendly options.

A considerable reduction in electricity consumption and less harm to our environment can be achieved through the systems used in residential buildings in the region.

The outcomes of the present study offer value (in terms of cost-effective and eco-friendly options) for the end-users in the region.

Homebuyers' motivation to purchase the green building (GB) is vital for the widespread adoption of greener practices and for tackling the adverse impact of the built environment. In this regard, through the lenses of qualified and competent GB developers (GBD) and real estate agents (REAs) using judgment sampling technique, this paper aims to evaluate the factors stimulating the purchase intention of Malaysian homebuyers.

The study uses the interval-valued fuzzy Delphi method (IVFDM) to identify influential factors, while the cybernetic fuzzy analytic hierarchy process (CFAHP) for prioritizing the identified factors according to their significance in nationwide promotion of GBs is utilized.

The findings, which are consistent with those reported in the literature and validated by the focus group, uncover the most prominent factors that drive the purchase intention of GB homebuyers. The results indicate that the homebuyers are familiar with the benefits of GB; however, the benefits are not sufficient to overcome the perceived “high cost” of green practices. Hence, homebuyers still seek financial incentives, which is a clear indication that financial issues are the most motivating factor.

Increase in informative promotion of GB is necessary, particularly among prospective homebuyers in developing countries where GB adoption is in its infancy. Frontline players (those who are responsible for wider promotion) can utilize the factors that this study found to be important to identify appropriate steps to increase prospective homebuyers' motivation for purchasing greener dwellings.

The contribution of this paper is threefold. First, review and identification of the most cited determinants that have been reported in the context of the subject. Second, this paper presents the most significant determinants in a developing country setting through the lenses of Malaysian experts in the area. Third, improvement measures could be implemented in Malaysia and other developing countries to promote the GB paradigm with an aim to make the building environment more sustainable.

The purpose of this paper is to present a systematic review of studies on CPD published between 1985 and 2018.

Before identifying common CPD, research trends were examined in terms of the number of publications in selected journals, as well as the contributions made by countries, institutions and researchers.

The findings reveal that researchers from developing countries have contributed the most to identifying the causes of CPD. A total of 149 causes of CPD were identified in a thorough review of 97 selected studies. Weather/climate conditions, poor communication, lack of coordination and conflicts between stakeholders, ineffective or improper planning, material shortages, financial problems, payment delays, equipment/plant shortage, lack of experience/qualification/competence among project stakeholders, labour shortages and poor site management were identified as the ten most common CPDs.

Being the first study of its type, this study provides insight into the research output related to this area and identifies a common set of CPDs, which may provide a better understanding of the key areas requiring attention where steps should be taken to minimise or control factors causing delays in construction projects.

Circular economy (CE) is increasingly used as a system solution framework for tackling climate change. Existing CE solutions have been found effective in other sectors but ineffective in the construction sector (CS) due to the inability to account for unique CS dynamics that are essential for its success. With CS being one of the worst polluters, this research aimed to investigate critical success factors (CSFs) and a practical CE implementation framework for the sector.

Mixed methods research involving descriptive surveys of construction professionals in Kazakhstan, Malaysia and Turkey was used to explore priority dimensions of McKinsey’s ReSOLVE (“regenerate, share, optimize, loop, virtualize and exchange”) circulatory framework, and the associated CSFs that underpin successful implementation of CE in the sector. Empirical data were analyzed using the fuzzy analytical hierarchy process (F-AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm.

Results showed that “Optimize” and “Loop” were the most critical of the six dimensions of CE implementation framework for successful circularity transition of the CS in each case study country. Twenty-seven CSFs identified in the study were clustered into seven key action areas for successful rollout of the ReSOLVE framework, namely, legislative and documentation, financial, design, external/stakeholder, technological, internal and construction/production/waste management.

The study makes a unique contribution to existing knowledge by exploring ReSOLVE-based CSFs for successful CE implementation in the CS through the lenses of experienced construction practitioners and experts in developing countries. The findings are expected to provide a deeper insight into the most significant CSFs to be focused on with the limited resources available to decision-makers in the CS. The findings would also inform regulatory policy reformations aimed at facilitating greater rate of implementation of CE in the construction value chain.

The study – the first of its kind – established and validated a wholistic and construction-specific CE implementation framework to guide built environment professionals and policymakers in formulating a roadmap for successful CS’s transition to circularity and hopefully paving the way for improved economic, social and environmental performance of the sector.

This study reviews the extent of application of artificial intelligence (AI) tools in the construction industry.

A thorough literature review (based on 165 articles) was conducted using Elsevier's Scopus due to its simplicity and as it encapsulates an extensive variety of databases to identify the literature related to the scope of the present study.

The following items were extracted: type of AI tools used, the major purpose of application, the geographical location where the study was conducted and the distribution of studies in terms of the journals they are published by. Based on the review results, the disciplines the AI tools have been used for were classified into eight major areas, such as geotechnical engineering, project management, energy, hydrology, environment and transportation, while construction materials and structural engineering. ANN has been a widely used tool, while the researchers have also used other AI tools, which shows efforts of exploring other tools for better modelling abilities. There is also clear evidence of that studies are now growing from applying a single AI tool to applying hybrid ones to create a comparison and showcase which tool provides a better result in an apple-to-apple scenario.

The findings can be used, not only by the researchers interested in the application of AI tools in construction, but also by the industry practitioners, who are keen to further understand and explore the applications of AI tools in the field.

There are no studies to date which serves as the center point to learn about the different AI tools available and their level of application in different fields of AEC. The study sheds light on various studies, which have used AI in hybrid/evolutionary systems to develop effective and accurate predictive models, to offer researchers and model developers more tools to choose from.

Universities have recognized their rich endowments in research, academic skills and facilities, as uniquely suited to finding “green” solutions. Moreover, the campus setting itself presents as a microcosm of greater society through which to investigate and test innovations. Thus, the “living lab” was born, a means of coupling sufficient resources and active stakeholders in the pursuit of practical, sustainable solutions. Much of the work to date, however, remains piecemeal, small-scale and disparate. This study aims to propose that the work of such labs must ultimately be directed, coordinated and integrated under a “university sustainability office,” if they are to be ultimately effective.

The research approach is twofold. In the first instance, a literature review charting the history and progress of living labs is reported, with emphasis of the university context. Second, a case study appraisal of Deakin University’s initiatives in adopting and promoting sustainability through the living lab framework is undertaken.

A main finding of this paper is that current efforts remain piecemeal and peripheral. If the apparent ambiguity regarding commitment is to be overcome, Deakin University should adopt measures as adopted by peer leaders in the field. Specifically, the setting up of a centralizing sustainability function bestowed with the capacity to coordinate university-wide living lab efforts, and at such a scale that substantial benefits transferable to greater society is generated.

This paper stands out among previous studies in the field through facilitating a transition to living lab for other universities, where findings facilitate that progress and consider how the lessons learnt might inform the further evolution of university living lab initiatives.

Construction projects in Malaysia are often delayed and over budget due to heavy reliance on labor. Linear regression (LR) models have been used in most labor cost (LC) studies, which are less accurate than machine learning (ML) tools. Construction management applications have increasingly used ML tools in recent years and have greatly impacted forecasting. The research aims to identify the most influential LC factors using statistical approaches, collect data and forecast LC models for improved forecasts of LC.

A thorough literature review was completed to identify LC factors. Experienced project managers were administered to rank the factors based on importance and relevance. Then, data were collected for the six highest ranked factors, and five ML models were created. Finally, five categorical indices were used to analyze and measure the effectiveness of models in determining the performance category.

Worker age, construction skills, worker origin, worker training/education, type of work and worker experience were identified as the most influencing factors on LC. SVM provided the best in comparison to other models.

The findings support data-driven regulatory and practice improvements aimed at improving labor issues in Malaysia, with the possibility for replication in other countries facing comparable problems.

This study aims to investigate the impact of primary building information modelling (BIM)-related factors, extracted from the literature on the subject, on construction project performance.

Based on data collected from 134 BIM users, this study used structural equation modelling to assess the impact of these factors in five main BIM-related factor clusters.

The results of the analysis confirmed the reliability and validity of the research design and outcomes. The findings indicated that the BIM-related external factors cluster is the most influential cluster affecting construction project performance. BIM-related project factors and BIM-related technological factors also had a significant impact on project performance. These were followed by the BIM-related management factors cluster, while the BIM-related human factors cluster had a low impact on project performance.

This study will contribute to fostering BIM adoption and implementation in the construction industry in developing countries.

This study has filled a crucial knowledge gap by providing information on manageable primary BIM-related factors affecting construction project performance.