Search Results (40)

Project delays remain a persistent challenge in the construction industry, having significant financial implications and contributing to disputes between project participants. Forensic Delay Analysis (FDA) has emerged as a specialised function that identifies the root causes of such delays, quantifies their duration, and assigns responsibility to the appropriate parties. While FDA is a widely practised process, it has yet to fully exploit the potential of emerging technologies. This study explores the integration of both existing and emerging technologies for enhancing FDA processes. A Design Science Research (DSR) approach is adopted, with data collection methods that involve the use of the literature, archival materials, case studies and survey methods. The research demonstrates how the use of technologies, such as database management systems (DBMSs), building information modelling (BIM), artificial intelligence (AI) and games engines, can improve the analytical efficiency, data management, and presentation of findings through a case study. The study showcases the transformative potential of these interventions in streamlining FDA processes, ultimately leading to more accurate and efficient resolution of construction disputes. The proposed process is exemplified by the development of a prototype: the Forensic Information Modelling Visualiser (FIMViz). The FIMViz is a practical tool that has received positive evaluation by FDA experts. The prototype and the enhanced FDA process model that underpins it demonstrate significant advancement in FDA practices, promoting improved decision-making and collaboration between project participants. Further development is needed, but the results could ultimately streamline the FDA process and minimise the uncertainties in FDA outcomes, thus reducing the incidence of costly disputes to the wider economic benefit of the industry generally. Full article

The construction industry faces persistent challenges from disputes and claims, leading to delays, cost overruns, and strained stakeholder relationships. This study proposes a strategic framework that integrates building information modeling (BIM) as a proactive tool for dispute avoidance. Using a causal loop diagram (CLD), the research maps the relationships among systemic factors contributing to disputes, such as poor communication, ambiguous specifications, and ineffective stakeholder engagement. The study highlights BIM’s transformative potential in enhancing visualization, improving collaboration, and fostering proactive conflict resolution. Validated through expert insights, the framework provides actionable recommendations for integrating BIM (with ISO19650 specs) into construction workflows, addressing the root causes of disputes, and driving project efficiency. This research contributes a structured roadmap for advancing construction management practices, emphasizing early BIM adoption considered with ISO19650, stakeholder alignment, and balancing systemic dynamics. The findings underscore BIM’s pivotal role in reshaping conflict prevention strategies, paving the way for sustainable and dispute-free project delivery. Full article

Frequent ambiguities in contract terms often lead to costly legal disputes and project delays in the construction industry. Large Language Models (LLMs) offer a promising solution, enhancing accuracy and reducing misinterpretations. As studies pointed out, many professionals use LLMs, such as ChatGPT, to assist with their professional tasks at a minor level, such as information retrieval from the Internet and content editing. With access to a construction regulation database, LLMs can automate contract interpretation. However, the lack of Artificial Intelligence tools tailored to industry regulations hinders their adoption in the construction sector. This research addresses the gap by developing and deploying a publicly available specialised chatbot using the ChatGPT language model. The development process includes architectural design, data preparation, vector embeddings, and model integration. The study uses qualitative and quantitative methodologies to evaluate the chatbot’s role in resolving contract-related issues through standardised tests. The specialised chatbot, trained on construction-specific legal information, achieved an average score of 88%, significantly outperforming ChatGPT’s 36%. The integration of a domain-specific language model promises to revolutionise construction practices through increased precision, efficiency, and innovation. These findings demonstrate the potential of optimised language models to transform construction practices. Full article

Conflicts between owners and contractors in state-led infrastructure and building projects pose significant challenges to project efficiency, cost control, and stakeholder collaboration. The aim of this study is to identify the primary causes of such conflicts in Norway and evaluate potential mitigation strategies. Deficiencies in tender documentation, unclear risk allocation, and limited early contractor involvement significantly contribute to project disputes considered as central facts. Using a mixed-methods approach, the research integrates survey data from 57 industry professionals and in-depth interviews with senior project managers. Statistical analysis results show that most people believe flawed tender documents and unclear risk sharing are big causes of conflicts. Specifically, 78% said tender documents were a problem, and 65% pointed to unclear risk allocation. Additionally, interviews revealed that involving contractors early in the process helps avoid misunderstandings and encourages better teamwork. The findings indicate sector-specific differences, with infrastructure projects primarily affected by technical ambiguities and contractual disputes, whereas building projects face more scope modifications and interpersonal conflicts. To mitigate these issues, the study recommends improving tender document quality, adopting collaborative contracting models, and increasing early contractor engagement. These measures can enhance project outcomes, reduce societal costs, and foster more efficient stakeholder collaboration in state-led construction initiatives. Full article

The construction industry faces increasing conflicts over additional construction costs due to economic uncertainties, such as global pandemics and wars. These disputes often lead to project delays, legal actions, and even construction halts, causing significant financial and operational losses for stakeholders. To address these challenges, this study develops a simulation model based on evolutionary game theory (EGT) to identify the key influencing factors and applies the Analytic Hierarchy Process (AHP) to analyze and manage the conflicts between contractors and owners in private construction projects. The model quantifies decision-making dynamics by calculating the relative importance of various factors under different scenarios. A proof-of-concept simulation of the model reveals that cooperative evolution dynamics significantly decrease when the cost-sharing ratio reaches 0.5 for contractors and 0.9 for owners. Furthermore, the sensitivity analysis indicates that exceeding cost-sharing thresholds undermines cooperation, increasing the risk of disputes. Through this simulation, this study concludes that fostering mutual trust and informed decision-making on cost-sharing ratio significantly reduces project disputes and enhances the stakeholders’ profitability. The developed model and its framework serve as valuable tools for providing project stakeholders with actionable insights aimed at fostering strategic behaviors that minimize dispute-driven financial risks in construction projects. Full article

The medical industry has made significant advancements in recent years. However, the lack of accountability in medical management has resulted in systemic deficiencies, which have adversely affected patient trust and contributed to an increase in medical disputes. As a result, there is a growing emphasis on managing the quality of medical services, particularly in enhancing patient experience. To address these challenges, we propose a new system for evaluating health services. This system will allow patients to anonymously rate the services they receive while also providing doctors the opportunity to appeal specific reviews. The hospital handles the evaluations and appeals through the management of the cloud platform. We propose a new scheme to assist the work of the platform, which is a lattice-based group signature with verifier-local revocation (VLR-GS). Most of the work on VLR-GS has focused on the random oracle model (ROM) or using non-interactive zero-knowledge proofs (NIZKs). Our construction is anonymous and traceable in the standard model under the hardness of the learning with errors problem and short integer solution problem. Furthermore, theoretically analyzing it has practical significance in both security and efficiency. In conclusion, the proposed scheme establishes a secure and privacy-oriented platform for an anonymous medical service evaluation system, with the goal of fostering patient trust and improving hospital service quality within the healthcare sector. Full article

Timely approvals and payments to the project participants are crucial for successful completion of construction projects. However, the construction industry faces persistent delays and non-payments to contractors. Despite the desirable benefits of automated payments and enhanced access to digitized data progress, most payment applications rely on centralized control mechanisms; inefficient procedures; and documentation that takes time to prepare, review, and approve. As such, there is a need for a reliable payment automation system that guarantees timely execution of payments upon the detection of completed works. Therefore, this study used a cutting-edge approach to automate construction payments by integrating blockchain-enabled smart contracts and scan-to-Building Information Modeling (BIM). In this approach, scan-to-BIM provides accurate, real-time building progress data, which serve as the source of verifiable off-chain data. A chain-link is then used to securely relay these data to the blockchain system. Blockchain-enabled smart contracts automate the execution of payments upon meeting contract conditions. The proposed approach was implemented on a real case study project. The actual site scan was captured using a photogrammetry 360° camera, which uses a combination of structured light and infrared depth sensing technology to capture 3D data and create detailed 3D models of spaces. This study leveraged accurate, real-time building progress data to automate payments using blockchain-enabled smart contracts upon work completion, thus reducing payment disputes by tying payments to verifiable construction progress, leading to faster release of payments. The findings show that this approach provides a transparent basis for payment, enhancing trust and allowing precise project progress tracking. Full article

The resolution of disputes is one of the most critical aspects of construction projects as it directly impacts the success of construction projects. The standard methods in which conflicts are usually resolved in the construction industry in Norway include negotiation, mediation, and litigation. Standard methods used at the international level include negotiation, mediation, and arbitration. This research work tried to establish the effectiveness of different dispute resolution mechanisms in Norway by conducting interviews with professionals dealing with construction disputes. Our study has found that PRIME is the most preferred approach in the Norwegian construction industry because it mainly focuses on negotiations and mediation, while lawsuits are the least preferred. It is in light of the excellent dispute resolution methods that the study should be tailor-made for the specific dispute and include all parties. Such findings would be significant as they would help in coming up with more appropriate dispute resolution mechanisms and, therefore, benefit the construction professionals and policymakers and furnish valuable insight into the field. Full article

This study explores the increasing adoption of virtual alternative dispute resolution (VADR) in the construction industry, enhancing efficiency and accessibility in dispute resolution. VADR is crucial for streamlining processes and reducing participation barriers. The study aims to investigate the critical success factors (CSFs) influencing the adoption of VADR in the construction sector. Given the rising importance of VADR technologies, understanding the key factors driving their acceptance is crucial. The background highlights the growing reliance on innovative technologies to boost operational efficiency and decision-making processes. The data for the study were collected using a cross-sectional design with online structured survey questionnaire (N = 97) from diversified construction industries. Using Smart PLS 4, structural equation modeling (SEM) was employed to test the validity, reliability, and proposed hypotheses of the study. The results showed that cost factors had the greatest impact on VADR acceptance, followed by user competence and training, procedural adaptability, and technological infrastructure. Logistical assistance and legal frameworks also had a considerable favorable impact. However, stakeholder buy-in had no significant influence on VADR implementation. The implications indicate that economic feasibility, logistical readiness, flexible procedures, supportive legal contexts, and user skills are significant factors for successful VADR integration. Governments and organizations should deploy VADR technologies to encourage innovation and operational improvement in the construction industry. Full article

Despite stiff competition in the construction industry, housing quality remains a problem. From the consumer’s perspective, these quality problems are called defects. Homeowners experience inconvenience and suffering due to home defects, and developers and builders also experience severe damage in time, costs, and reputation due to defect repairs. In Korea, lawsuits are increasing due to the rise in housing defects, and the cost of repairing defects determined by lawsuits is of great concern. Litigation is a burden to consumers and producers, requiring a hefty court fee, as well as attorneys and specialist firms, and takes some years. Suppose it is possible to predict the repair costs based on the outcome of a lawsuit and present it as objective supporting data. In that case, it can be of great help in bringing a settlement between consumers and producers. According to previous studies on housing repair costs, linear regression models were mainly used. Accordingly, in this study, a linear regression model was adopted as a method to predict housing repair costs. We analyzed the defect repair costs in 100 cases in which lawsuits were filed and the verdict was finalized for housing complexes in Korea. Previous studies investigated using the following independent variables: elapsed period, litigation period, claim amount, home warranty deposit, total floor area, households, and main building’s quantity, construction cost, region, and highest floor. Among these, the floor area, elapsed period, and litigation period were determined to be valid independent variables. In addition, the construction period was discovered as a valid independent variable. The present research model, which combines these independent variables, was compared with previous research models. The results showed that the earlier research model was found to have a multicollinearity issue among some independent variables. Also, the coefficients of some independent variables were not statistically significant. This research model did not have a multicollinearity problem; all independent variables’ coefficients were statistically significant, and the coefficient of determination was higher than other linear research models. Our proposed regression model, which accounts for the interaction of each independent variable, is a significant step forward in our research. This model, using the number of households multiplied by the construction period, the construction period multiplied by the litigation period, and the litigation period multiplied by the litigation period as independent variables, has been rigorously tested and found to have no multicollinearity issue. The coefficients of all independent variables are statistically significant, further bolstering the model’s reliability. Additionally, the explanatory power of this model is comparable to the previous model, suggesting its potential to be used in conjunction with the existing model. Therefore, the linear regression model predicting the repair cost of housing defects following litigation in this study was considered the best. Utilizing the model proposed in this study is expected to play a major role in reconciling disputes between consumers and producers over housing defects. Full article

Off-site construction (OFC) is a hot topic to remedy the chronic issues of the construction industry, such as low levels of productivity, waste, safety risks, environmental pollution, poor quality, and time and cost issues. However, the lack of standards and knowledge about OFC projects hamper the adaptation process. Disputes are one of the most important hampering factors. Therefore, this study aims to identify contractual and financial disputes and to detect the importance level of disputes in OFC projects. In the study, the Focus Group Discussion (FGD) technique, Pythagorean fuzzy AHP, and fuzzy TOPSIS were employed. As a result of FGD, 42 dispute causes for off-site construction projects were found. The Pythagorean fuzzy AHP method was used to calculate the weights of the criteria (occurrences, severity, and detection) that were used in the evaluation of dispute causes. The Pythagorean fuzzy AHP analysis results indicated that “detection” is more important than other criteria in the evaluation of off-site construction dispute causes. After that, the fuzzy TOPSIS method was used to determine the importance level of off-site construction dispute causes. The analysis results showed that “Increase in contract value due to revision in scope of work” in the contractual factor group and “Extra money for the additional works” in the financial factor group are the most important dispute causes, respectively. The study findings can be used for the evaluation and analysis of OFC project contracts. Full article

Optimization of drilling processes for oil and gas and geothermal wells requires the effective use of mechanical energy for the destruction of rocks. When constructing a well, an important indicator of the drilling stage is the mechanical speed. Therefore, when performing drilling operations, operators usually use blade bits of an aggressive design and often use forced drilling modes. Drill bits under forced operation modes generate a wide range of vibrations in the drilling tools; in turn, a drill string, being a long-dimensional deformable body, causes the development, amplification, and interconnection of vibrations of different types. Vibration loads reduce the technical and economic indicators of drilling, with destructive effects on drill string elements, and cause complications and emergencies. The authors initiated the creation of an informational and analytical database on emergency situations that occurred as a result of excessive vibrations of the drill string during the construction of deep wells in the deposits of the Dnipro–Donetsk Basin. For the first time, the suitability and effectiveness of using the Smart 4 controller (“Innova Power Solutions”, Calgary, Canada) for monitoring the vibration load of the drilling tool was tested in industrial conditions, while the controller was used as a separate element in the drill string. A special module was developed for the reliable installation of the Smart 4 controller, with a power battery in the layout of the lower part of the drill string. During the testing of the proposed device for measuring vibrations in the process of drilling an inclined well, verification of the registered data was carried out with the help of a high-cost telemetry system. The implementation of the proposed innovation will allow each operator to assess the significance of the impact of vibrations and shocks on the production process and, if necessary, adjust the drilling modes or apply vibration protection devices. In addition, service departments that operate and repair drilling equipment will be able to obtain an evidence base for resolving warranty disputes or claims. Full article

Sustainability requirements pose complex challenges for the construction industry, requiring adaptation strategies, innovative solutions, and collaboration between stakeholders to build resilient structures for the future. Nevertheless, effective collaboration between stakeholders is hindered by information asymmetry, which can produce disputes, endanger honest communication between the participants, and in the long term, negatively affect industrial productivity. To improve the sustainability of construction businesses and construction projects, there is a need for the implementation of mitigation measures for information asymmetry risks. This study presents possible mitigation measures for information asymmetry between clients and contractors in the construction industry. Mitigation measures were identified through a literature review and semi-structured interviews with industry professionals. Furthermore, a questionnaire was designed and employed to prioritize mitigation measures and explore their utility for mitigating three types of risks: adverse selection, moral hazard, and hold-up. The results of this study indicate that building trust, regular supervision and monitoring of work, thorough verification of bidders, and fair distribution of risks between the client and the contractor have the most utility in mitigating information asymmetry in construction projects. The practical contribution of this research includes defining the most useful measures to mitigate risks caused by information asymmetry. Project managers can apply the results of this research for more successful achievement of their project goals. Implementing effective risk management strategies, such as building trust between stakeholders, can help mitigate the impacts of unforeseen events and build resilience in construction projects. Full article

The South African preferential procurement policy emerged from the demand for transparency, fair competition, value-for-money, standardised and benchmark pricing, and regulation of public procurement arrangements in the construction industry. The policy aims to address historical inequalities, support economic growth, and foster sustainable development. The effectiveness of the preferential procurement policy in South Africa is affected by the inhibiting factors of its implementation system. Given this, this study assesses the factors inhibiting preferential procurement policy implementation in the South African construction industry. This study reviewed the extant literature from online databases as a secondary data source to identify and understand the factors inhibiting procurement policy implementation. A quantitative research design using a closed-ended survey questionnaire surveyed 31 identified inhibiting factors affecting procurement policy implementation from the literature review. One hundred sixty-seven (167) questionnaires were retrieved from two hundred (200) distributed, representing an 83.5 per cent response rate, distributed through Google Forms to the respondents in Northwest Province, South Africa. The reliability of the data collection instrument was determined using Bartlett’s sphericity, Cronbach’s alpha, and Kaiser–Meyer–Olkin tests. The exploratory factor analysis findings established eight components from the 31 identified inhibiting factors affecting procurement policy implementation, which are the absence of due diligence in procurement screening, corruption and political interference in procurement systems, an ineffective regulatory framework supporting public procurement policy, discrepancies in award of contracts and the absence of dispute resolution, ambiguity in procurement selection criteria, poor enforcement mechanisms, cost discrepancies in advance payment, and excessive bureaucracy in procurement documentation. This study’s practical implications provide an understanding of establishing and prioritising procurement selection criteria, such as project requalification requirements, cost performance requirements, technology integration in the prequalification process, and contract change order requirements, which would improve procurement systems in the South African construction industry. Full article

This study employs an adaptive neuro-fuzzy inference system (ANFIS) to identify critical success factors (CSFs) crucial for the success of pavement construction projects. Challenges such as construction cost delays, budget overruns, disputes, claims, and productivity losses underscore the need for effective project management in pavement projects. In contemporary construction management, additional performance criteria play a vital role in influencing the performance and success of pavement projects during construction operations. This research contributes to the existing body of knowledge by comprehensively identifying a multidimensional set of critical success performance factors that impact pavement and utility project management. A rigorous literature review and consultations with pavement experts identified sixty CSFs, categorized into seven groups. The relative importance of each element and group is determined through the input of 287 pavement construction specialists who participated in an online questionnaire. Subsequently, the collected data undergo thorough checks for normality, dependability, and independence before undergoing analysis using the relative importance index (RII). An ANFIS is developed to quantitatively model critical success factors and assess the implementation performance of construction operations management (COM) in the construction industry, considering aspects such as clustering input/output datasets, fuzziness degree, and optimizing five Gaussian membership functions. The study confirms the significance of three primary CSFs (financial, bureaucratic, and governmental) and communication-related variables through a qualitative structural and behavioral validation process, specifically k-fold cross-validation. The outcomes of this research hold practical implications for the management and assessment of overall performance indices in pavement construction projects. The ANFIS model, validated through robust testing methodologies, provides a valuable tool for industry professionals seeking to enhance the success and efficiency of pavement construction endeavors. Full article