Field Of Construction Management Research Articles

A REVIEW OF AGENT-BASED MODELING IN CONSTRUCTION MANAGEMENT: AN ANALYTICAL FRAMEWORK BASED ON MULTIPLE OBJECTIVES

The increased complexity of construction projects has caused various management challenges. To clarify the mechanism of construction system complexity and improve the ability to manage the complexity of construction projects, the Agent-based modeling (ABM) method has been introduced and used in the construction management field. Nevertheless, a systematic, holistic, and panoramic understanding of the use of the ABM model in the construction management field is still lacking. To address this research gap, this study reviewed 133 historical explorations retrieved from the database of Web of Science. By using the multiple objectives of construction management as the literature classification framework, the study described the research status of the agent-based modeling method in the field of construction management. On this basis, this paper suggested the improvement paths in the application of this method from three aspects. It is expected that this study will provide a theoretical basis for enhancing understanding of the use of the ABM method in construction management, and also provide insights for future explorations in the area.

Analysis of the Сonstruction Market in Russia and Abroad in Order to Сurb the Growth of Construction Costs and Ensure the Сompetitiveness of Enterprises by Increasing the Efficiency of the Cost Accounting and Сontrol System

The purpose of the study is to analyze the Russian construction market and the prospects for its development in the context of large contracting companies, as well as to determine contractor competitiveness and the place of the largest domestic construction companies in the world ranking. Comparison, analysis, as well as graphical, tabular methods of data presentation and visualization were used as research methods. The paper presents an analysis and characteristics of the Russian and world construction market, its dynamics, structure and key players. The main trends and drivers of the construction industry are described. The volume of construction is growing every year, despite the economic and political crises of past five years. This fact indicates a high demand for construction products. The article considers the main players in the Russian and foreign markets. The leading positions in terms of construction volumes are occupied by such countries as China, the USA, Japan and the EU, while the Russian Federation lags behind in terms of construction production volume. Only four construction companies in the world have a turnover of more than $ 100 billion, while maintaining a significant lead over other players. Whereas the development of the global construction market is associated with population dynamics, an influx of investments in the Asian region is expected, which in turn will contribute to the development of technologies and the introduction of innovations in the field of construction management. The study revealed a direct correlation and relationship between the competitiveness of construction companies and internationalization. Despite the increasing interest of Russian developers in foreign projects, at the moment the expansion trend of Russian construction companies is just beginning to take shape. It is concluded that in order to increase the competitiveness of Russian construction companies in the world market, the efficiency of project management and cost optimization, it is necessary to introduce an effective system of projects cost accounting and control.

Construction Instance Segmentation (CIS) Dataset for Deep Learning-Based Computer Vision

Deep learning-based computer vision (DLBCV) techniques have played an important role in intelligent construction. Image datasets are essential for developing DLBCV algorithms. However, a large-scale construction-specific dataset of major construction elements, such as precast components (PCs), PC delivery trucks, and workers not wearing safety helmets, remains absent. This paper presents the Construction Instance Segmentation (CIS) dataset, a new image dataset aimed at advancing state-of-the-art instance segmentation in the field of construction management. It contains 50,000 images with ten object categories belonging to construction workers, machines, and materials. Two rounds of algorithmic analysis have been conducted to refine and balance the dataset. Finally, a detailed statistical analysis of the dataset is presented.

Operational Barriers against the Use of Smart Contracts in Construction Projects

As an emerging but embryonic way of contract administration, smart contracts can play a prominent role in managing construction projects in an effective manner. However, there are still some barriers preventing the implementation of them in the life cycles of construction projects. This study investigates operational barriers against the adoption of smart contracts in construction projects and explores the challenges in this process. Operational barriers against smart contract implementation are identified through a comprehensive literature review and a focus group discussion is performed to refine the identified barriers. These barriers are evaluated through fuzzy analytical hierarchy process analysis. Finally, a framework is proposed for the adoption of smart contracts effectively in construction projects. 20 operational barriers were attained based on four main barrier categories: technical, financial, security/technological, and time. The results show that financial and technical aspects establish the most significant categories hindering the adoption of smart contracts, while expensive and clunky drafting and registration process, and cost of upskilling are the most significant barriers. Overall, the proposed framework might be useful for practitioners and project managers, who decide to use smart contracts in managing construction projects. The motive behind understanding critical operational barriers is to assist construction practitioners in automating contract execution processes. This study provides a basis for recommending the necessary strategies for the use of smart contracts in the industry to researchers in the construction management field.

Incentive contract design and selection for inhibiting unethical collusion in construction projects

Purpose The construction industry has long been criticized for unethical conduct. The owner usually manages the contractor's opportunistic behaviors by employing a professional supervisor, but there is a risk of covert collusion between the supervisor and contractor. Based on the principal–agent theory and collusion theory, this paper aims to investigate optimal collusion-proof incentive contracts.Design/methodology/approachThis paper presents a game-theoretic framework comprising an owner, supervisor and contractor, who interact and pursue maximized self-profits. Built upon the fixed-price incentive contract, cost-reimbursement contract, and revenue-sharing contract, different collusion-proof incentive contracts are investigated. A real project case is used to validate the developed model and derived results.FindingsThis paper shows that the presence of unethical collusion undermines the owner's interests. Especially, the possibility of agent collusion may induce the owner to abandon extracting quality information from the supervisor. Furthermore, information asymmetry significantly affects the construction contract selection, and the application conditions for different incentive contracts are provided.Research limitations/implicationsThis study still has some limitations that deserve further exploration. First, this study explores contractor–supervisor collusion but ignores the possibility of the supervisor abusing authority to extort the contractor. Second, to focus on collusion, this paper ignores the supervision costs. What's the optimal supervision effort that the owner should induce the supervisor to exert? Finally, this paper assumes that the colluders involved always keep their promises. However, what if the colluders may break their promises?Practical implicationsSeveral collusion-proof incentive contracts are explored in a project management setting. The proposed incentive contracts can provide the project owner with effective and practical tools to inhibit covert collusion in construction management and thus safeguard construction project quality.Originality/valueThis study expands the organization collusion theory to the field of construction management and investigates the optimal collusion-proof incentive contracts. In addition, this study is the first to investigate the effects of information asymmetry on contract selection.

Comparing Subjective and Objective Measurements of Contract Complexity in Influencing Construction Project Performance: Survey versus Machine Learning

Contracts are the main governance mechanism regulating construction participants’ behaviors and safeguarding project performance. Besides traditional subjective measurement via survey, machine learning has been utilized as a more objective method to measure contract complexity in the field of construction management. However, little is known about whether misalignment between these two measurements exists and whether their impact on project performance differs. To answer these questions, we collected 202 pairs of construction contracts and questionnaires. Construction contracts were analyzed by machine learning to obtain the objective measurement of contract complexity, whereas questionnaires provided the subjective measurement. Through a multifunctional perspective of contracts, we found that the two measures are positively correlated with each other for contractual coordination and adaptation but nonsignificant for control. Regarding the ongoing debate on the relationship between contract complexity and trust, we selected trust as another antecedent of construction project performance. The results showed that trust is only positively related to the subjective measurement of contract complexity, which has a direct impact on project performance. In contrast, the objective measurement strengthens the positive effect of trust on project performance. Theoretically, our study contributes to construction contract research by highlighting that different measures cannot be used interchangeably and that scholars should be aware of the measurement issue when conducting and assessing relevant research. Practically, construction project managers are provided with guidance on performance improvement through perspectives from both objective design and subjective perceptions of contracts.

Factors influencing BIM use in green building construction project management in the UK and China

ABSTRACT Decentralization and a lack of integration in the architecture, engineering and construction (AEC) industry are some of the main challenges for project management in green building construction. To address this problem, many construction companies have attempted to use building information modelling (BIM) to coordinate and optimize the management of green building projects. However, the research on successfully adopting and using BIM in interdisciplinary teams working on green building projects is limited; moreover, comprehensive comparisons across different countries and regions are lacking. Therefore, this study conducts a novel investigation of the key factors affecting the use of BIM in project management for green building construction through case studies in the UK and China. This study uses semi-structured interviews, Python-based term frequency analysis and thematic analysis to identify five key themes, namely, communication, data environment, motivation, project members and policy, which influence the adoption and implementation of BIM. In addition, based on gained insights, the impacts of different green building certification levels on BIM project management during the construction phase must be fully considered. These findings provide practical recommendations for BIM management in green building construction projects and contribute to the field of construction management.

Impact of asymmetric trust on construction project management performance: the mediating role of knowledge sharing

PurposeThe purpose of this study is to explore the impact of asymmetric trust on construction project management performance in China's construction industry. Moreover, the authors explore the mediating role of two types of knowledge sharing (explicit knowledge sharing and tacit knowledge sharing) in explaining the association between asymmetric trust and project management performance.Design/methodology/approachA theoretical model based on the research hypotheses proposed in this study was developed and a questionnaire survey was conducted with 271 professionals. The data collected was analyzed by the structural equation modeling (SEM) technique.FindingsThe results of this study indicate that there is a significant and negative association between asymmetric trust and project management performance. Moreover, two types of knowledge sharing (explicit knowledge sharing and tacit knowledge sharing) have different degrees of impact on improving project management performance. In addition, tacit knowledge sharing is a mediator between asymmetric trust and project management performance.Research limitations/implicationsThe data used in this study is from Chinese scenarios, so the research conclusions and application effects based on this are bound to have certain regional limitations. Besides, there are many factors that affect project management performance improving, and the relationships among them are so complex. The theoretical model proposed in this study may not be fully considered. Therefore, follow-up researchers can consider bringing more suitable variables into their researches, so that the theoretical researches can be more in line with the actual project management practice, and the specific mechanism for improving project management performance can be explained more deeply.Originality/valueThis research's value is as follows: Firstly, this paper contributes to the trust and relational governance literature by expanding the research perspective of mutual trust to asymmetric trust. Specially, this research designs a measurement scale for asymmetric trust and then reveals the impact mechanism of it on project management performance, which will certainly promote research paradigm change of trust. Secondly, this research is beneficial to knowledge sharing literature in the construction management field by expanding the research scope of knowledge sharing from a cross-organizational perspective.

The Success Factors of Green Construction Management Implementation on Building Projects

The importance of implementing green construction has been introduced and campaigned in Indonesia. However, in reality, implementing green construction in Indonesia is still not optimal and has not gone as desired due to several factors. Therefore, it is necessary to identify the factors that affect success in applying green construction. The purpose of this study is to analyze what factors affect the success of the implementation of green construction management. The analysis results of factors that affect the success of the implementation of green construction management are used to determine the dominant success factor in building projects in Malang City. Method data collection in this study is by distributing questionnaires filled out by experts in the Field of Construction Management, Academics, and PUPR Offices in Malang City. Furthermore, the data obtained will be processed using the Simple Additive Weighting method. The results showed that alternative machines and advanced equipment achieved the first rank with a total value of 0,256. The second rank is achieved by material alternatives and implementation methods in green construction with a total value of 0,231. Finally, the third rank is achieved by alternative awareness in green construction with a total value of 0,217. Therefore, the most prevalent factors in applying green construction management are the presence of sophisticated machinery and equipment, the use of materials and methods of implementation, as well as the awareness of contractors to implement green construction. Therefore, these three success factors can be considered when implementing green construction projects in Malang City.

Peningkatan Kemampuan Administrasi dan Akuntansi dalam menghitung Biaya Kontrak pada Konsultan Perencana dan Pengawas Konstruksi di Surabaya

Accounting is a practical science in its application in accordance with the specific applications and needs of each type of business entity. This community service activity is designed to provide assistance in preparing CV X's financial reports in the field of construction management consulting services that require progress reports on the progress of each contract. This community service activity is carried out by providing training to administrative staff so they can use Microsoft Excel from templates that have been made and guided by the community service team. Management expects that the output of this accounting information system can evaluate every ongoing project or project that has completed the contractual period. The output of this community service activity from this accounting information system is to accurately calculate the value of the cost of each project so that evaluation of the physical progress of the project and evaluation of the price and profitability analysis of each service contract can be carried out for monitoring and subsequent planning. The following evaluation needs follow-up to evaluate the application of PSAK 34 related to accounting for construction management consulting services.

A new perspective in construction management; the metaverse

A conceptual construction management model can be applied to the metaverse 3D technology in this study, which demonstrates how accelerated back-and-forth replays of the construction process can be used to evaluate the impact of new decisions on the project. Participants in the proposed model will be able to see exactly how their decisions during construction affect the progress of the project. In order to develop this model, three phases are required: 1) Analyzing the problem and planning the algorithm, 2) collecting data and designing the hybrid model utilizing artificial intelligence and construction network scheduling techniques, and 3) coding the algorithm. The design-based research will contribute to the development of new meta-models for construction management, present innovative ideas for students, engineers, and managers working in the field of construction management.

The Padma Multipurpose Bridge: Construction Challenges and Sustainable Management

An iconic building linking Bangladesh's southwest to its northern and eastern areas is the Padma bridge, which spans the third-largest river in the world with a complicated topology. By boosting production, employment, transportation, and the national and regional economy, this multipurpose bridge is projected to boost GDP growth by 1.2%. This study's primary goal is to pinpoint the greatest challenges encountered during Padma Bridge's construction and explain how sustainable management procedures might be put in place to address such difficulties. The most challenging tasks included finding a suitable site, dealing with complex river morphology, overcoming geotechnical barriers, controlling unfavorable environmental conditions, assembling massive construction equipment and materials, maintaining the construction schedule, and dealing with the COVID epidemic. To resolve these construction challenges, massive river training works and a unique pile foundation design that consists of six floating heaps and one center pile with the largest raking pile in the center were both utilized. To get around the difficulties in superstructural design, longer pre-assembled steel truss girders, pre-tensioned Super-T girders in viaducts, seismic isolation devices, and the largest friction pendulum bearings in the world were all made. Only a small number of people experienced COVID-19 without any fatalities or causing delays in the construction schedule since the Project was kept operational during the COVID-19 period by tightly enforcing the COVID laws and limits on people's mobility. The field of construction management would undergo a paradigm shift with this sustainable management of construction-related difficulties, which might later be used to design more intricate bridges.

Application of Artificial Neural Networks in Construction Management: A Scientometric Review

As a powerful artificial intelligence tool, the Artificial Neural Network (ANN) has been increasingly applied in the field of construction management (CM) during the last few decades. However, few papers have attempted to draw up a systematic commentary to appraise the state-of-the-art research on ANNs in CM except the one published in 2000. In the present study, a scientometric analysis was conducted to comprehensively analyze 112 related articles retrieved from seven selected authoritative journals published between 2000 and 2020. The analysis identified co-authorship networks, collaboration networks of countries/regions, co-occurrence networks of keywords, and timeline visualization of keywords, together with the strongest citation burst, the active research authors, countries/regions, and main research interests, as well as their evolution trends and collaborative relationships in the past 20 years. This paper finds that there is still a lack of systematic research and sufficient attention to the application of ANNs in CM. Furthermore, ANN applications still face many challenges such as data collection, cleaning and storage, the collaboration of different stakeholders, researchers and countries/regions, as well as the systematic design for the needed platforms. The findings are valuable to both the researchers and industry practitioners who are committed to ANNs in CM.

A fuzzy-based competitiveness assessment tool for construction SMEs

PurposeIn highly competitive industries such as the construction sector, companies with limited capabilities struggle to maintain their current standing, let alone acquire more market share. Before they are able to address their shortcomings, these companies need to pinpoint where their performance stands when it comes to market demand. Furthermore, competitiveness is strongly linked with companies' ability to win tenders and deliver the associated construction projects. Tenders are, therefore, a mechanism that reflects the strengths and weaknesses of construction firms and can be deemed an indicator of competitiveness. This paper aims to help small and medium-sized enterprises (SMEs) increase their presence in the construction sector by suggesting a systematic approach to evaluate their competitiveness.Design/methodology/approachParticipation requirements were extracted from 11 calls for tenders and organized into categories using a qualitative content analysis. These requirements along with winning assets deduced from the literature constitute the basis of the tool. The qualitative evaluation of the difficulty in satisfying requirements or acquiring assets was transformed into unified, quantifiable scores by means of fuzzy numbers.FindingsA total of 233 requirements were found and classified in 3 main categories. In addition, a list of 54 assets organized into five categories was compiled. The entire methodology led to a five-step assessment tool whose output can be depicted on the proposed competitiveness readiness matrix (CRM).Research limitations/implicationsThis study contributes to the limited number of articles discussing the contractor's side in the tendering process. Furthermore, it combines three theoretical perspectives (i.e. resource-based view, relational view, and industry structure perspective), which are scarcely applied in the construction management field. Consideration of the calls for tenders when developing solutions is also a unique aspect of this research when compared to previous studies.Practical implicationsThis tool may help practitioners navigate the rather elusive tendering process by outlining the necessary elements to participate in and win tenders. It may also allow construction firms to better position themselves in the market with respect to customers' requirements and competitors' performances.Originality/valueThis study provides an approach of both self-assessment and market benchmarking. It assists companies in formulating strategies to become more competitive in general and make better bidding decisions. This is especially interesting because of three aspects: the study is based on a fundamental element of the construction competitiveness concept, i.e. calls for tenders; it offers a mechanism to transform systematically qualitative attributes into quantifiable scores; and it provides a practical and reliable display of the assessment results.

Selection of Construction Bidders Using the Analytical Hierarchy Process and Friedman Theory

Selecting a suitable bidder to execute a construction project is not an easy task, especially for the short bidder list. The consequences of the selection might affect the project performance in terms of cost, money, and quality. The current research in this work deals with the selection of a contractor, who bids on a specific project. The historical data of contractors are a key of the selection based on three approaches: the quick selection approach (QSA), generic selection approach (GSA), and comprehensive selection approach (CSA). The QSA relies on the scoring system according to delay factors. The QSA is the weighted average of the delay factors using the analytical hierarchy process (AHP), the CSA is based on the integrated QSA and the bidding strategy using Friedman’s theory. The current three approaches can be utilized by public and private owners, who intend to select a general contractor to execute new construction projects. A hypothetical case study is implemented to demonstrate the developed models. Several experts in the field of construction management have confirmed the findings. The third strategy (CSA) is found to be the most appropriate for selecting construction bidders.

Using immersive video technology for construction management content delivery: a pilot study

Construction management is considered a hands-on field of study which requires good spatial and visual cognitive ability. Virtual reality and other innovative immersive technologies have been used to facilitate experiential learning and to improve students’ spatial cognitive abilities. Virtual environments have been criticized due to the gamified look of the environment. Static panorama pictures have been previously used to bring a better sense of reality and immersion at the same time in construction education. However, they cannot provide a continuous experience, and the sense of presence (immersion) is not ideal either. Immersive videos such as 360-degree videos can address this shortfall by providing a continuous experience and a better sense of presence. The use of this technology in construction education field is very limited. As a result, this study investigated a pilot experiment where a combination of 360, 180 3D, and flat videos was incorporated as an educational instrument in delivering construction management content. The content was recorded using different configurations from different body postures to further investigate the optimal way of utilizing this technology for content delivery. The content of the videos was focused on construction means and methods. Students reviewed the content using head-mounted display devices and laptop screens and answered a survey designed to capture their perception and experience of using this technology as an educational tool in the construction management field. The results show a positive perception toward using immersive videos in construction education. Furthermore, the students preferred the head-mounted display as their favorite delivery method. As a result, the prospect of incorporating immersive videos to enhance construction management education is promising.

Application of Artificial Neural Networks in Construction Management: Current Status and Future Directions

Artificial neural networks (ANN) exhibit excellent performance in complex problems and have been increasingly applied in the research field of construction management (CM) over the last few decades. However, few papers draw up a systematic review to evaluate the state-of-the-art research on ANN in CM. In this paper, content analysis is performed to comprehensively analyze 112 related bibliographic records retrieved from seven selected top journals published between 2000 and 2020. The results indicate that the applications of ANN of interest in CM research have been significantly increasing since 2015. Back-propagation was the most widely used algorithm in training ANN. Integrated ANN with fuzzy logic/genetic algorithm was the most commonly employed way of addressing the CM problem. In addition, 11 application fields and 31 research topics were identified, with the primary research interests focusing on cost, performance, and safety. Lastly, challenges and future directions for ANN in CM were put forward from four main areas of input data, modeling, application fields, and emerging technologies. This paper provides a comprehensive understanding of the application of ANN in CM research and useful reference for the future.

Examining the Critical Factors for Managing Workplace Stress in the Construction Industry: A Cross-Regional Study

Construction professionals (CPs) usually bear significant responsibilities for the achievement of project success and, thus, have long experienced numerous workplace stressors in the demanding construction industry. The perception of stressors and, in turn, the generation of stress is largely affected by an individual’s socioeconomic background and cultural values. However, previous research mainly examined the factors for CPs’ stress in a single location. Little is known about regional differences in stressor-stress patterns globally. To better manage stress and enhance the well-being of CPs worldwide, comprehensively examining the stressor-stress interaction of CPs through a cross-regional study is necessary. This research involved a questionnaire survey with more than three hundred and fifty CPs from Hong Kong (HK) and Suzhou. A series of statistical analyses on the collected data produced a number of major findings about the stressors and stress experienced by CPs in the two cities: (1) the HK CPs experienced a higher level of objective stress but a lower level of subjective stress than their Suzhou counterparts did; (2) the HK and Suzhou CPs faced different stressors at work; (3) work overload and poor environment were critical stressors for both the HK and Suzhou CPs; and (4) group cohesion significantly affected only the stress of Suzhou CPs. Practical suggestions were provided for managing CPs’ stressors and stress, including realistic job assignments and organizing of frequent social gatherings, team-building activities, stress management seminars, and training. This study reveals different patterns of stressor-stress interactions for CPs in the two typical developed regions, which might inspire a future comparative study to explore the underlying mechanisms for CPs’ stress in the context of different regions globally. This study further extends the body of knowledge on global stress management in the construction management field and is valuable to improving the effectiveness of existing stress management practices.

The role of value engineering in reducing the costs of constructing governmental housing.

The role of value engineering in reducing the costs of constructing governmental housing.

Research trends analysis using text mining in construction management: 2000–2020

PurposeThis study aims to identify the trends that have changed in the field of construction management over the last 20 years.Design/methodology/approachIn this study, 3,335 journal articles published in the years 2000–2020 were collected from the Web of Science database in construction management. The authors applied bibliometric analysis first and then detected topics with the latent Dirichlet allocation (LDA) topic detection method.FindingsIn this context, 20 clusters from cluster analysis were found and the topics were extracted in clusters with the LDA topic detection method. The results show “building information modeling” and “information management” are the most studied subjects, even though they have emerged in the last 15 years “building information modeling,” “information management,” “scheduling and cost optimization,” “lean construction,” “agile approach” and “megaprojects” are the trend topics in the construction management literature.Research limitations/implicationsThis study uses bibliometric analysis. The authors accept that the co-citation and co-authorship relationship in the data is ethical. They accept that honorary authorship, self-citation or honorary citation do not change the pattern of the construction management research domain.Originality/valueThere has been no study conducted in the last 20 years to examine research trends in construction management. Although bibliometric analysis, systematic literature reviews and text mining methods are used separately as a methodology for extracting research trends, no study has used enhanced bibliometric analysis and the LDA topic detection text mining method.