Completion Of Construction Projects Research Articles

Enhancing Efficiency in Industrial Metal Roof Replacement: Utilizing Goal Programming for Cost Optimization

This study explores the use of Goal Programming (GP) to optimise project management decisions in the construction industry, focusing on a case study of a roof replacement project. The construction industry is crucial to a country's development, contributing significantly to economic growth and employment rates. However, construction projects are often complex and resource-intensive. Project management is essential in ensuring the successful completion of construction projects. The study uses GP to address the time-cost trade-off in project management, aiming to minimise project costs while meeting project deadlines and quality requirements. The GP model considers various constraints, such as the availability of workers and equipment, project duration, and budget limitations. The study presents two optimisation options: a time-focused option and a cost-focused ed option. The time-focused option prioritises timely project completion, while the cost-focused option aims to minimise project costs. In the case study, the time-focused option is the most suitable choice. This approach allows the project to be completed in time as the alternative option delay delays the project far too unacceptable. Overall, the study demonstrates the effectiveness of GP in optimising project management decisions in the construction industry. By carefully evaluating project constraints and objectives, GP can help construction companies achieve the best possible outcomes in terms of cost, time, and quality. Keywords: Goal Programming, Construction Industry, Project Management, Time-Cost Trade-off, Optimization

Traits and Skills Required by Project Managers to Complete Construction Projects in Guyana's Civil Engineering Firms

Traits and Skills Required by Project Managers to Complete Construction Projects in Guyana's Civil Engineering Firms

The application of Bayesian network analysis in demystifying construction project subcontracting complexities for developing countries

Purpose This study aimed to address a gap in subcontractor management by focusing on previously unexplored complexities surrounding subcontractor management in developing countries. While past studies concentrated on selection and relationships, this study delved into how effective subcontractor management impacts project success. Design/methodology/approach This study used the Bayesian Network analysis approach, through a meticulously developed questionnaire survey refined through a piloting stage involving experienced industry professionals. The survey was ultimately distributed among participants based in Accra, Ghana, resulting in a response rate of approximately 63%. Findings The research identified diverse components contributing to subcontractor disruptions, highlighted the necessity of a clear regulatory framework, emphasized the impact of financial and leadership assessments on performance, and underscored the crucial role of main contractors in Integrated Project and Labour Cost Management with Subcontractor Oversight and Coordination. Originality/value Previous studies have not considered the challenges subcontractors face in projects. This investigation bridges this gap from multiple perspectives, using Bayesian network analysis to enhance subcontractor management, thereby contributing to the successful completion of construction projects.

Strategies for Imputing Missing Values and Removing Outliers in the Dataset for Machine Learning-Based Construction Cost Prediction

Accurately predicting construction costs during the initial planning stages is crucial for the successful completion of construction projects. Recent advancements have introduced various machine learning-based methods to enhance cost estimation precision. However, the accumulation of authentic construction cost data is not straightforward, and existing datasets frequently exhibit a notable presence of missing values, posing challenges to precise cost predictions. This study aims to analyze diverse substitution methods for addressing missing values in construction cost data. Additionally, it seeks to evaluate the performance of machine learning models in cost prediction through the removal of conditional outliers. The primary goal is to identify and propose optimal strategies for handling missing value in construction cost records, ultimately improving the reliability of cost predictions. According to the analysis results, among single imputation methods, median imputation emerges as the most suitable, while among multiple imputation methods, lasso regression imputation produces the most superior outcomes. This research contributes to enhancing the trustworthiness of construction cost predictions by presenting a pragmatic approach to managing missing data in construction cost performance records, thereby facilitating more precise project planning and execution.

An Empirical Study on the Effects of Disputes on Successful Completion of Construction Projects

Disputes are common in construction projects, demanding significant attention in terms of financial resources, time, and manpower to seek resolutions. Conversely, unresolved disputes can create unfavorable effects on project performance. When project leaders recognize the major consequences of disputes, they can formulate strategies to proactively prevent or alleviate such conflicts. This heightened awareness empowers project teams to swiftly identify and resolve disputes, preventing their adverse consequences on successful project completion. The primary objective of this research is to enhance project management practices by providing insights into the effects of disputes, thereby enabling stakeholders to implement proactive strategies for prevention, mitigation, and effective resolution. Utilizing existing literature published between 2019 and 2023, this study critically analyzes 18 selected journal papers sourced from the ProQuest Central database, all of which have undergone rigorous review. This research identified nine major effects that appear due to disputes in construction projects. Further, cost overrun is identified as the major effect of disputes that can impact negatively in project performance and successful completion. This study further identified research gaps that need future studies.

Applications of using connected vehicle data for pavement quality analysis

Current quantitative methods to evaluate pavement conditions in the United States are most commonly focused on construction acceptance using the International Roughness Index (IRI). However, from an asset management perspective, qualitative visual inspection techniques are the most prevalent. Modern vehicles with factory-equipped sensors drive these roadways daily and can passively assess the condition of infrastructure at an accuracy level somewhere between qualitative assessment and rigorous construction acceptance techniques. This paper compares crowdsourced ride quality data with an industry standard inertial profiler on a 7-mile bi-directional construction zone. A linear correlation was performed on 14 miles of I-65 that resulted in an R2 of 0.7 and a p-value of <0.001, but with a modest fixed offset bias. The scalability of these techniques is illustrated with graphics characterizing IRI values obtained from 730,000 crowdsourced data segments over 5,800 miles of I-80 in April of 2022 and October 2022. This paper looks at the use of standard original equipment manufacturer (OEM) on-board sensor data from production vehicles to assess approximately 100 miles of roadway pavements before, during, and after construction. The completed construction projects observed IRI improvements of 10 in/mi to 100 in/mi. These results suggest that it is now possible to monitor pavement ride quality at a system level, even with a small proportion of connected vehicles (CV) providing roughness data.

Identifying the Causes of Dissatisfaction of Construction Labour: A Case Study of Building Construction of Jajarkot District Hospital, Nepal

The construction industry in Nepal is a significant contributor to the country's economy, but it faces challenges related to construction labor’s dissatisfaction. This study focuses on identifying the causes of dissatisfaction of construction labour during the building construction in Jajarkot. The primary objective of this study is to pinpoint and dissect the critical challenges that confront construction workers and, more importantly, to propose strategies aimed at enhancing their job satisfaction. The ultimate goal is to catalyse improvements in overall productivity and the successful completion of construction projects in the region. The study uses a mixed-method approach, including questionnaire, reports and research papers to gather data. The research identifies several key factors contributing to labour dissatisfaction, including delayed payment, inadequate compensation, inadequate wages, unsafe working conditions, excessive working hours and insufficient safety measures. These issues have a direct impact on construction labour motivation, affects their morale and well-being, leading to unhappiness, reduced productivity and reduced work excellence. The key recommendations include timely payments, improving compensation, enhancing working conditions, offering career growth prospects, promoting open communication, and recognizing workers' contributions. By adopting these measures, the construction industry can foster a positive work environment, leading to increased productivity and timely project completion.

Theft and Vandalism Control Measures on Construction Sites

Purpose: The goal of this study is to determine and improve the best security practices within Ghanaian construction sites to control theft and vandalism incidents.
 Design/Methodology/Approach: A purposive sampling technique was adopted for the population which were indigenous small and medium-sized construction firms of D1KI and D2K2 categories to complete the semi-structured questionnaire. Out of the total of 80 questionnaires distributed, only 65 responses were retrieved for analysis. Descriptive statistics comprising, frequencies and mean scores were used. 
 Findings: The findings showed that the most effective and often utilized security measure on construction sites is the hiring of watchmen, with security cameras, alarm systems, and warning signs being the least frequently employed. Sites would most likely be protected from theft by effective implementation of the most important security measures while also guaranteeing that the value for money invested in site security is also realized.
 Research Limitation/Implications: The effectiveness of theft and vandalism control measures may vary based on specific site characteristics, such as location, size, and type of construction. Generalising findings from one site to all construction contexts may not be applicable.
 Social Implication: Incidents of theft and vandalism can lead to social tensions within the community, especially if residents perceive construction activities as a source of risk. Effective control measures mitigate these tensions, fostering a more harmonious relationship between construction companies and the local population.
 Practical Implication: Minimizing the impact of theft and vandalism contributes to the timely completion of construction projects. Unanticipated delays due to security incidents can be avoided, ensuring that projects adhere to planned schedules and deadlines.
 Originality/ Value: The originality of this paper lies in its targeted investigation into theft and vandalism control measures on small and medium-sized construction sites, offering innovative and contextually relevant solutions that address the unique challenges faced by SMEs in the construction industry.

Man-Hour Estimation Model Development in BIM-Based Projects with Machine Learning-Regression Algorithms

Construction management is a service that uses project management techniques to planning, design and construction of a project. Another branch of construction management is the planning made during the bidding stages before the construction starts. At this stage, the scheduling of the work, mobilization and most importantly the project design and drawing time should be analyzed and accurate estimates should be made. For this estimation, the experience of the bidding organization is the biggest reference. Construction management techniques in a BIM-based project are challengeable. The biggest reason is that knowledge about BIM is much less than the others and still a developing system. Therefore, the margin of error in the estimated project duration to be predicted in the bids to be made for such projects increases. Considering that man-hour estimations are financially very important for the company. This study is aimed to make observations with advanced technologies which is applied ML algorithms and analysis methods for man-hour estimations in BIM projects at the bidding stage. The project information to perform a man-hour analysis of completed construction projects was requested from offices that have gained experience in BIM projects. The project information of 16 projects were tabulated. The collected information was converted into a data set and transferred into regression analysis algorithms using Python format. Data set, which was turned into a matrix, was analysed and the consistency of the parameters in data set was tested. Spent man-hour estimation was made, graphed over parameters with simple and multiple linear regression algorithms. 
 Keywords: Building Information Modelling (BIM), construction management, bidding, project management, Artificial Intelligence (AI), machine learning, regression analysis

Social-Cultural Factors and Performance of Roads Construction Projects in Nairobi City County, Kenya

The Kenyan Government is on the spot over stalled and poorly done roads construction projects especially in the Nairobi City County. Successful road construction is an impetus to economic development for Kenya as enumerated in the Kenya Vision 2030. However, there has been need for these road construction projects to update their systems due to the ever changing environment factors. Thisstudy therefore sought to determine the relationship between social-cultural factors and the performance of roads construction projectsin Nairobi City County, Kenya. The underpinning theory was the open system theory. Thisstudy used a positivist research philosophy. This study used the descriptive and explanatory research design. In this study, Nairobi City County refers to the five counties in the Nairobi Metropolitan Area namely, Nairobi County, Kiambu County, Kajiado County, Machakos County and Murang'a County. The target population of this research was the 176 completed roads construction projects in Nairobi City County by Kenya Rural Roads Authority (KERRA). The unit of observation was the road engineers, project planners and directors (KERRA), road supervisors, road inspectors, road surveyors, contractors, and project implementation teams’ members (KERRA). The unit of analysis wasthe completed roads construction projectsinNairobi City County. Proportional stratified sampling was used to derive a sample size of 253 respondents. A structured questionnaire was used to collect primary data. Data that was collected from the field was filtered, sorted and cleaned in line with research objectives. This study adopted both descriptive and inferential statistics. Descriptive statisticsincluding frequencies, percentages, mean scores, and standard deviation was produced for all the quantitative data. The results were presented using tables. Inferential statistics were done using the multiple linear regression. The study established a positive significant relationship between socio-cultural factors (t=2.417, p < 0.05) and project performance. The study concludes that human relationship influences project performance since projects operate within the society. Project culture is developed by communicating priority, status, and the alignment of official and operational rules. The study recommends that project leaders should be sensitive and aware of multicultural preferences guided by individual identity and role within the project versus family of origin and community, verbal and emotional expressiveness, relationship expectations, style of communication, language, personal priorities, values, and beliefs and time orientation.

Research on the Application of Construction Robots in the Context of Construction Industrialization

Based on the original construction technology, construction robots are realized by integrating industrial information technology, and construction robots are used to replace manual labor in completing construction projects. China’s research on construction robots is still in its early stages. Research efforts need to be increased in order to promote better applications of construction robots. To this end, by analyzing the application of modern construction robots, we conduct a comprehensive study on the development of construction robots to ensure that construction robots can be widely used in the future.

Influence of the Contractor's Culture on the UAE Construction Project's Performance

Academics have recently paid a lot of attention to culture, as it has been shown to have an impact on organizational performance. There has been little research carried out on assessing the correlation between project organizational culture and performance in the industry of construction. This study aims to verify how the culture of the contractor affects the construction projects performance in the UAE according to work practices at the project level. Data from 124 recently completed construction projects in the UAE were examined using questionnaires to collect specific data for this purpose. This study found a significant relationship between the contractor's culture and the project's performance. The findings reveal that the contractor significantly affects the overall performance of the project. Client satisfaction with quality is more impacted by the contractor's culture, while contractor satisfaction with profitability is least impacted by the contractor's culture. The findings of this study will assist those who work in construction projects in identifying ways to enhance the culture of the contractor at the project level. This can help improve the performance and success of construction projects.

Determining the Critical Risk Factors of Implementing Public–Private Partnership in Water and Wastewater Infrastructure Facilities: Perspectives of Private and Public Partners in Iran

Due to the fact that risks can cause project delays and increase project implementation costs, successful construction project completion requires effective and holistic risk management. Identification and evaluation of critical risk factors (CRFs) associated with different types of projects are the most significant components of accurate risk management. This study aims to identify and evaluate the CRFs inherent with private–public partnership (PPP) projects specifically for the development of water and wastewater infrastructure (WWI) facilities in the developing country of Iran. In this line, a comprehensive literature analysis was undertaken to extract the CRFs in applying PPP projects for the development of infrastructure projects in developing countries in general. Then, four rounds of a Delphi survey were conducted to consolidate the major risks to the circumstances of Iran and WWI facilities. There were a total of 35 risks that were grouped into six categories. The main risks were then analyzed and ranked using the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) technique. The overall ranking results of the various CRFs revealed that “lack of trust in government’s economic programs” risk was ranked first in terms of importance, followed by the risk of “delay in timely fund payment for project financing and credits,” and the risk of “delay in finalizing bank negotiations.” The overall ranking of the risks placed “economic changes, such as inflation, increase or decrease in prices, and exchange rate” risk in the bottom position. According to the risk ranking findings based on the opinions of private experts, “lack of commitment to the project schedule” was placed first. Conversely, experts from the public sector considered “choosing the wrong financing method” to be the most CRF. It is anticipated that the key research findings and effective recommendations of this study will considerably contribute to the smooth development and remarkable improvement of risk management in applying PPP for WWI facilities in developing countries while enhancing different stakeholders’ understanding of the CRFs for PPP projects, particularly towards WWI services in Iran.

Measuring the Benefits and Barriers of the Implementation of BIM in Sustainable Practice in the Construction Industry of Saudi Arabia

The construction industry of Saudi Arabia has witnessed notable innovation in sustainable practices in the form of building information modeling (BIM). Previously, a few studies dealt with either the benefits and barriers of BIM or sustainability. However, there is a limitation in these studies in terms of finding out the benefits and barriers of BIM in sustainable construction projects, especially in the context of Saudi Arabia. Therefore, the present study aimed to examine the determinants that impact the adoption of BIM in the construction industry of Saudi Arabia. A thorough examination of the existing literature was conducted in order to identify the various factors that contribute to the benefits and barriers of BIM. The research employed a questionnaire survey of 152 building engineering professionals from Saudi Arabia. The questionnaire’s results emphasize the key factors that are essential for the implementation of sustainable BIM. Initially, barriers and benefits were prioritized according to the relative importance index (RII). In addition, the study utilized statistical methods to identify the top five barriers that were deemed most significant. The Cronbach alpha test confirmed the presence of a statistically significant level of consistency in the responses provided by stakeholders. Moreover, the Spearman correlation test demonstrated that there was no statistically significant variance among the groups in their responses. The results indicated that among the 28 benefit factors, “improving design efficiency (RII = 0.788)”, “encouraging the use of energy-efficient clean technology (RII = 0.786)”, and “promoting green building design, construction, and management” were the top three benefits from BIM implementation in sustainable construction projects. On the other hand, “recurring demand for increased resources, together with high costs (RII = 0.720)”, “absence of a well-defined method for exchanging operational management data (RII = 0.713)”, and “lack of skilled personnel (RII = 0.708)” were the top five barriers to the incorporation of BIMs in the sustainable construction industry of Saudi Arabia. This study can provide valuable guidance for policymakers in developing countries who seek to successfully complete sustainable construction projects by encouraging factors that drive BIM implementation and enhancing project performance through the utilization of the benefits of BIM.

Assessment of Demski’s Model in House Construction Planning

The construction industry has witnessed significant advancements in recent years, particularly in the area of planning and project management. Efficient and effective planning plays a vital role in the successful completion of construction projects, ensuring timely delivery, cost-effectiveness, and quality. One prominent planning model that has gained attention is Demski's Model, which aims to optimize the house construction planning process by incorporating various factors and variables. This research paper presents an in-depth assessment of Demski's Model in the context of house construction planning. The objective is to evaluate the model's effectiveness, its applicability in realworld scenarios, and the potential benefits it offers to the construction industry. The assessment process involves a comprehensive literature review, analyzing existing studies, scholarly articles, and relevant industry reports. The gathered information provides a foundation for understanding the fundamental principles and components of Demski's Model. The research methodology consists of both quantitative and qualitative analysis. Quantitative analysis involves examining key performance indicators such as project duration, cost, and resource allocation, comparing projects that utilized Demski's Model with those that followed traditional planning approaches. Qualitative analysis focuses on gathering feedback from project stakeholders, including contractors, homebuilders, and house owners, to gauge their experiences and perceptions regarding the model's effectiveness and practicality. The findings of this research contribute to the existing knowledge base on house construction planning methodologies. The assessment of Demski's Model provides insights into its strengths, weaknesses, and potential areas for improvement. It also sheds light on the challenges and limitations that may arise during its implementation. By understanding these factors, construction professionals can make informed decisions when considering the adoption of Demski's Model in their planning processes. Ultimately, this research aims to provide a comprehensive assessment of Demski's Model in house construction planning, offering valuable insights for researchers, practitioners, and decision-makers in the construction industry. By evaluating the model's effectiveness and practicality, this study contributes to advancing planning methodologies and optimizing construction project outcomes in the pursuit of enhanced efficiency, reduced costs, and improved quality.

The Effect of Non-Excusable Delay Factors on The Completion of Building Construction Projects

A problem that often occurs in construction projects is the delay in the implementation process. Various factors cause the delay, but in developing countries such as Indonesia, the dominant delay occurs because the implementing contractor causes it for unforgivable reasons (non-excusable delay). This study aims to determine the influence of the non-excusable delay parameter and the relationship between these factors. The research is quantitative with data collection techniques in the form of unstructured interviews, field observations, and surveys using research questionnaires with the number of respondents obtained as many as 33 people consisting of the owner, construction management consultant, quantity surveyor consultant, and ends with confirmation of the results. Research on the implementing contractor. Data analysis was performed using multiple linear regression analysis. The test results of multiple linear regression analysis show that the non-excusable delay factor can significantly affect the completion of construction projects. The influence of each element is 0.434 units for the lack of contractor competence, 0.067 units for inappropriate implementation planning, and -0.097 for inefficient field management units. And simultaneously, these three factors can significantly increase the project delay value index.

Critical success factors and performance of completed construction projects at National Social Security Fund, Nairobi City County, Kenya

This paper aims to examine the effect of selected factors that link to completion of NSSF construction projects and how they are influenced by the various critical factors. The main objective was to establish the critical success factors and their effects on performance of construction projects. Four theories namely Game theory, Principal-Agent theory, Construction Management, and Soft Value Management (SVM) theory served as the foundation for this research. Descriptive research design was employed for data collection, analysis, presentation and interpretation.The target population was 512 stakeholders from six complete commercial and residential projects. Purposive sampling was used to select 84 participants for the study. Semi-structured questionnaires were used in the study to collect data. The data was analyzed using SPSS whereby descriptive and inferential statistics were used. The results show that the R-square value was 0.282 and R was 0.531. An analysis of variance (ANOVA) was significant at p=0.001 with an F statistic of 9.961 indicating that the model used was fit for the data. The data also revealed that client variations (p= 0.05), financial availability (p = 0.047), and construction disputes (p = 0.001) are statistically significant determinants affecting the performance of NSSF construction projects. The main findings of the study demonstrate that the key critical success factors used in this study affected the performance of NSSF-completed construction projects either positively or negatively. The study recommends that companies should adhere to the principles that safeguard project management to adequately manage the critical factors and ultimately minimize project delays.

Platform-independent visual installation progress monitoring for construction automation

Efficient interior progress monitoring is crucial for the timely completion of construction projects. Although robots have been used for data acquisition to automate interior progress monitoring, existing methods do not adequately consider the variations of robot platforms and different types of construction environments, which makes it challenging to apply these methods to various robots and environments. This paper proposes an integrated system that achieves automated interior installation progress monitoring, which can be applied to various construction environments and robot platforms. Algorithms are proposed to systematically generate navigation goal points for robot navigations based on BIM information of objects, which enables the detection of target objects with the proper viewing distance and angle. A transformer-based object detector is used to recognize the installation status of building elements, and a progress updating module is developed to correlate the detection results with the robot’s sensory and BIM information to generate a construction progress report for interior installation. This framework hierarchically estimates the percentage of project completion and allows for tracking of the installation work progress. The proposed system has been verified through laboratory and onsite experiments using various platforms, including a mobile robot, a four-legged robot, a drone, and a smartphone camera.

EVALUATION OF TIME OVERRUNS AND TIME MANAGEMENT TECHNIQUES IN ROAD CONSTRUCTION PROJECTS IN ERBIL CITY

Successful people utilize their time judiciously. The challenge of completing construction projects within the estimated time frame is the biggest concern among practitioners. In this research two aspects have been highlighted, first; the most significant factor of time overrun in construction projects performed by Erbil Municipality during road construction. The second aspect is the time management methods held by the project team. A random sampling technique was used to administer 126 questionnaires to professionals such as Project managers, Engineers, and contractors working on road construction projects for Erbil municipality. On the other hand, a case study has been conducted for 70 constructed projects during 2018-2022 for the evaluation of time management techniques in road construction projects by identifying the process of monitoring, software packages that are used for that, the progress of work, and investigating how progress records are kept in Erbil City municipality projects. The results revealed that the most significant factor for time overrun was the economic crisis which led to the failure to pay contractors' dues in a timely manner, followed by the unreasonable time frame for the completion of projects. Used techniques and software packages for time management were identified It is revealed that there is no specific method for managing time. Multiple methods are used depending on the situation.

How Team Voice Contributes to Construction Project Performance: The Mediating Role of Project Learning and Project Reflexivity

Voice behavior has been widely recognized as having various benefits for organizations, while researchers seldom notice its consequences in construction projects. Against this context, this study empirically explores the impact path of team voice on project performance in construction projects from a multi-team system (MTS) perspective. Considering the essence of voice behavior is to provide information, this study introduces the input–process–outcome (IPO) framework to verify how team voice can affect project performance by influencing project learning and project reflexivity. The online survey method, monetary incentive method, and chain-referral sampling method are adopted to distribute the designed questionnaire. A total of 184 data points from completed construction projects in China supported the research conclusion by adopting the partial least squares structural equation modeling (PLS-SEM) technique. Project learning and project reflexivity positively mediate the relationship between team voice and project performance in construction projects. Specifically, team voice can first positively influence project learning and project reflexivity, which both have a positive relationship with project performance. For theory, this study opens the black box between team voice and project performance in the context of construction projects by unveiling the mediating path of project learning and project reflexivity, which also enriches the literature on voice behavior and expands its application. Furthermore, this study provides one new perspective for MTS knowledge by adopting the IPO framework to explore the underlying mechanism between the focal team and the overall team performance of the MTS. For practice, this study has a directive function for construction project management and MTS management, while providing reminders for policymakers, researchers, and practitioners about the significance of project learning and project reflexivity on project performance.