Search results

Reportedly, green roof (GR) makes a significant contribution towards a truly sustainable-built environment; however, its implementation is yet to hit a sufficient level in developing countries. Thus, this study assesses GR implementation strategies in developing countries by providing a comparative analysis through experts in Kazakhstan, Malaysia and Turkey.

The study adopts a four-step methodological approach to achieve the research aim: literature review, focus group discussion, fuzzy analytical hierarchy process (FAHP) analysis and correlation analyses. First, a literature review followed by a focus group discussion is used to determine 18 (out of 25 initially) strategies for the selected context and these are classified into three categories: governmental and institutional support, knowledge and information and policy and regulation. Afterward, the identified GR strategies are evaluated using the FAHP with the data gathered from the experts in the countries studied. Finally, correlation analyses were used to observe the strength of agreement between the assessments of experts from the included countries.

The findings indicate that financial incentives, low-cost government loans and subsidies and tax rebates are the essential strategies for the wider adoption of GR. Evaluating the policy and regulations strategies also showed that mandatory GR policies and regulations and better enforcement of the developed GR policies are ranked as the most prominent strategies. The findings show a low level of agreement among respondents from Kazakhstan, while there is a high level of agreement between the experts in Malaysia and Turkey.

The research contribution is twofold. First (research implication), the study identifies the strategies through a complete literature review. Second, the identified strategies are evaluated through the lenses of experts in three developing countries which are hoped to provide (practical contribution) a better understanding of the most effective strategies that require attention and enable the frontline stakeholders (particularly government authorities) to focus on them.

The study findings provide a good point of departure to explore the strategies for broader adoption of GRs in developing economic setting.

As a remedy to usually voluminous, complicated and not easily readable construction contracts, smart contracts can be considered as an effective and alternative solution. However, the construction industry is merely known as a frontrunner for fast adoption of recent technological advancements. Numerous administrative risks challenge construction companies to implement smart contracts. To highlight this issue, this study aims to assess the administrative risks of smart contract adoption in construction projects.

A literature survey is conducted to specify administrative risks of smart contracts followed by a pilot study to ensure that the framework is suitable to the research question. The criteria weights are calculated through the fuzzy analytical hierarchy process method, followed by a sensitivity analysis based on degree of fuzziness, which supports the robustness of the developed hierarchy and stability of the results. Then, a focus group discussion (FGD) is performed to discuss the mitigation strategies for the top-level risks in each risk category.

The final framework consists of 27 sub-criteria, which are categorized under five main criteria, namely, contractual, cultural, managerial, planning and relational. The findings show that (1) regulation change, (2) lack of a driving force, (3) works not accounted in planning, (4) shortcomings of current legal arrangements and (5) lack of dispute resolution mechanism are the top five risks challenging the adoption of smart contracts in construction projects. Risk mitigation strategies based on FGD show that improvements for the semi-automated smart contract drafting are considered more practicable compared to full automation.

The literature is limited in terms of the adoption of smart contracts, while the topic is receiving more attention recently. To support easy prevalence of smart contracts, this study attempts the most challenging aspects of smart contract adoption.

Contract incompleteness with deficiency, inconsistency, defectiveness, and ambiguity in contract clauses, which can cause misunderstandings and misinterpretations, may result with disputes in projects. This study aims to investigate contract incompleteness factors with a hybrid fuzzy multi-criteria decision approach.

Contract incompleteness factors were ranked by fuzzy VIKOR (Visekriterijumska Optimizacija I Kompromisno Resenje) method, and the most significant factors were subjected to fuzzy decision-making trial and evaluation laboratory (DEMATEL) to examine their causal relationships. The study is not limited to ranking the identified factors solely, since their cause-effect interactions are also essential for proper risk management in construction projects.

Hybrid use of multi-criteria analysis reveals that ambiguity in enforceability including excessive demands and significant amendments in the scope of works are the top two causal contract incompleteness factors, while lack of implementation details and focus of focal point, and insufficient supporting and technical documents are the most affected ones.

Contractual causes of disputes due to contract incompleteness factors other than requirements of the contracts have been rarely investigated in the literature. The research is one of the first studies in the literature investigating the causal relationship among factors in construction contracts, which might lead to project disputes. Findings are expected to improve contract drafting, eventually contributing to effective risk management in construction projects.

Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world. This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies.

Occupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naïve Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes.

The results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker's age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes.

The proposed framework can be used in construction sites on a monthly-basis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents.

Practitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers' quality of life and well-being.

The literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain. A novel utilization plan was proposed and enhanced by the analysis results.

Work–family conflict is one of the most challenging stressors for construction industry professionals to cope with emotional problems. This study aims to propose a model linking work–family conflict and high-quality relationships among project team members and explore mediating effects of life and job satisfactions.

A theoretical framework was established based on the spillover theory and social exchange theory. Data were obtained by a questionnaire survey conducted with 328 respondents working in construction projects. Structural equation modeling (SEM) was used to test interrelationships among work–family conflict, job satisfaction, life satisfaction and high-quality relationship.

The results indicate that work–family conflict is negatively associated with both job and life satisfactions of construction professionals. In addition, there were direct and positive relationships between satisfaction domains and high-quality relationship capacity. The findings further support that job satisfaction plays a mediating role between work–family conflict and high-quality relationship among construction professionals, while life satisfaction does not mediate the relationship.

The effects of interrole conflicts on the context of satisfaction have been investigated previously; however, there is a lack of knowledge regarding its influence on high-quality relationship among project team members. This study extends the body of knowledge on high-quality relationships among project team members to understand how conflict and satisfaction factors influence interpersonal relationships in construction project management.

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.

Completing construction projects within the planned schedule has widely been considered as one of the major project success factors. This study investigates the use of technologies to address delays in construction projects and aims to address three research questions (1) to identify the adopted technologies and proposed solutions in the literature, (2) to explore the reasons why the delays cannot be prevented despite disruptive technologies and (3) to determine the major strategies to prevent delays in construction projects.

In total, 208 research articles that used innovative technologies, methods, or tools to avoid delays in construction projects were investigated by conducting a comprehensive literature review. An elaborative content analysis was performed to cover the implemented technologies and their transformation, highlighted research fields in relation to selected technologies, focused delay causes and corresponding delay mitigation strategies and emphasized project types with specific delay causes. According to the analysis results, a typological framework with appropriate technological means was proposed.

The findings revealed that several tools such as planning, imaging, geo-spatial data collection, machine learning and optimization have widely been adopted to address specific delay causes. It was also observed that strategies to address various delay causes throughout the life cycle of construction projects have been overlooked in the literature. The findings of the present research underpin the trends and technological advances to address significant delay causes.

Despite the technological advancements in the digitalization era of Industry 4.0, many construction projects still suffer from poor schedule performance. However, the reason of this is questionable and has not been investigated thoroughly.

Competent contractors are one of the critical stakeholders to achieve targeted sustainability objectives in green building (GB) projects. Prior to contractor selection, prequalification is an important step, which requires contractors with certain capabilities in addition to traditional features. This study aims to develop a systematic and practical model for prequalification in GB projects using a multi-criteria decision-making (MCDM) approach by adopting the analytical hierarchy process (AHP).

The AHP model with 8 main criteria groups and 25 sub-criteria is structured based on literature review and professional opinions accompanied by a pilot study. Then, interviews with experts, who are experienced in the development and application phases of GB projects in Turkey, are arranged to collect judgements. The agreement levels between different groups of experts are analysed via Pearson's and Spearman's rank correlation coefficient. Model applicability is tested on six hypothetical contractors for practicality.

The results show that i) financial capabilities, ii) legal status and iii) sustainability groups are the top three main criteria, while i) compliance with schedule requirements of the client, ii) current legal status including suits, iii) negative litigation history records, iv) contractor's compliance capacity to client's sustainability checklist for the proposed project and v) sustainability with lower life cycle cost (durability, maintenance, constructability) are the top five sub-criteria.

There is a gap in the literature analysing contractor prequalification phase in GB projects. This study attempts to fill this lack provided with a practical evaluation tool.

Building information modeling (BIM) is a prominent concept to digitalize data collection and analysis processes. Small and medium-sized enterprises (SMEs) account for a considerable percentage of the works performed in the construction industry. The adoption rate of BIM by SMEs is still, however, not at the desired level in the New Zealand construction industry. This study aims to evaluate barriers to BIM implementation for SMEs in the New Zealand construction industry.

This study adopted four-step methodology to evaluate barriers to BIM adoption for SMEs. First, a comprehensive literature review, followed by a focus group discussion was performed to identify barriers to BIM adoption. Then, analytical hierarchy process (AHP) was used to assess identified barriers. Finally, experts’ agreements (both internal and external) were ensured by consistency analysis and Kendall’s coefficient of concordance (Kendall’s W) tests.

The findings indicate that (1) interoperability between software platforms, (2) lack of government mandate on BIM usage at project level, (3) high cost of acquiring the software and licensing required to use BIM and (4) lack of client demand for adopting BIM were the most significant barriers in terms of technological, governmental, resource and cultural categories, respectively. Further investigation of the expert evaluation showed strong consistencies (each expert separately) and agreements (among experts) in each AHP matrix.

Primary focus should be training of local market (particularly SMEs) professionals as the shortage in qualified professionals makes the country-wide adoption challenging. The publicity in the local market can help SMEs understand how BIM is leveraged for further improvements in project performance.

Overall, this research not only provides a roadmap for the widespread adoption of BIM within SMEs in New Zealand through analysis of the barriers encountered but also highlights the power that policymakers hold over the mass adoption of BIM within SMEs.

Conflicts, claims and disputes are inherent in most construction projects. Acceptable degree of commonality in the interpretation of contract provisions is critical in effective contract administration. This study aims to assess the effects of contract ambiguity factors on construction conflicts, highlighting the causes of divergent interpretations using fuzzy technique for order of preference by the similarity-to-ideal-solution (TOPSIS) method.

Fuzzy TOPSIS framework with 27 ambiguity factors is constructed by conducting a comprehensive literature review, accompanied by a pilot study. Questionnaire survey is formed, and one-to-one interviews are arranged with 35 contract administration experts.

The findings indicate that (1) ambiguity due to excessive changes in the bill of quantity (BOQ) (including ambiguous provisions related to BOQ changes), (2) incomplete clauses that do not describe the scope of the intended work purely, (3) ambiguity due to excessive amendments in the scope of works (including ambiguous provisions related to scope changes), (4) ambiguous enforceability including excessive demands and (5) ambiguous goal and performance requirements are the top five ambiguity factors affecting construction conflicts.

Presented framework is performed referring to ambiguity factors in all type of construction contracts in the general sense. However, the identified factors may vary depending on the project type, contract type, procurement method or use of standard contract forms (such as NEC, FIDIC).

The literature lacks the investigation of ambiguity factors in construction contracts, yet the assessment of the effects of contract ambiguity is essential to minimize conflicts.