Search results

Blockchain is a developing technology that affects numerous industries, including facility management (FM). Many barriers are associated with adopting blockchain-enabled building information modeling (BEBIM) in FM. This research aims to identify and prioritize the barriers to adopting BEBIM in FM.

To address the knowledge gap, this study employs a two-phase methodology for evaluating the barriers to adopting BEBIM in FM. The first phase involves a comprehensive literature review identifying 14 barriers to BEBIM adoption. Using a Delphi approach, the identified barriers were categorized into 6 groups and finalized by 11 experts, adding 3 more barriers to the list. The best-worst method (BWM) determines the priority weights of identified barriers and sub-barriers in the second phase.

This study reveals that adopting BEBIM for FM in India faces significant hurdles. The most critical barriers are “limited collaboration” and “communication among stakeholders,” “legal constraints in certain jurisdictions” and “challenges in establishing trust and governance models.” To mitigate these barriers, stakeholders should foster collaboration and communication, develop efficient blockchain technology (BT) and establish a trust and governance model.

This work underscores the importance of formulating effective strategies to overcome the identified barriers and emphasizes implications that can assist policymakers and industry stakeholders in achieving successful BEBIM adoption for improved FM practice.

The study provides valuable insights for policymakers, construction industry stakeholders and facility managers interested in leveraging this technology to improve the efficiency and effectiveness of FM practice in India.

Claims are increasingly becoming a norm in construction projects and thus an area that is attracting interventions through researches. This paper aims to establish causes–effects relationship of claims in construction projects.

This is correlation study type of study that attempts to establish causes–effects relationship of claims in construction projects. Significant causes and effects of construction claims were determined using one-sample t-test. To establish the relationship, the significant causes and effects of construction claims were correlated using bivariate correlation analysis.

Among the significant causes, variations, change of scope of the project and delay in completion of works have high level of significant positive relationship with five to six other causes and positive relationship with multiple effects ranging from five to six. Besides, among significant effects, delay in completion and delivering of construction projects, poor contractual relationship among parties and extension of time have significant positive relationship with multiple causes.

The findings of this study are limited to causes-causes relationship and causes–effects relationship of claims in construction projects. This means effects–effects relationship was not covered that could be an important area to investigate as some of causes and effects are at times termed interchangeably.

With reference to previous studies which have focused on determining the causes and effects of construction claims, the findings of the current study have specific contribution on claims management as it divulges the causes of constructions claims that have multiplier effects to the project as a result of their linkage.

The paper unveils causes of claims with multiplier effects to construction projects for project participants to devise strategies to minimize and consequently eliminate them.

This study aims to develop a collaborative governance framework (CGF) to systematically investigate the impeding factors (IFs) in terms of the operational sustainability of PPPs. It examines the transmission pattern (i.e. the way in which network members react to each other) of the IFs network.

Literature review and interview were adopted to identify the IFs. Then, with the data collected from the interview in China, the social network analysis and interpretive structure model were synergised to examine the chain reaction, driving and dependent powers, and hierarchical structure of the identified IFs.

The results reveal that the cognition, institutional, financial and participation aspects are key barriers confronted by PPP sustainability, and the government plays a leading role in controlling factors causing sustainability-related problems in PPPs. Weak government leadership and institutional environment were identified as the most fundamental reasons triggering a chain of IFs, while project governance and management activities act as bridge nodes that play an intermediary role in the IFs network.

This research contributes to the literature on PPP governance by (1) bridging the literature gap through the development of CGF for explaining the governance of PPP sustainability with a holistic view that considers both macro environment and operational project processes; and (2) identifying the transmission pattern of IFs network which uncovers the underlying dynamics causing the unsustainable operation of PPPs.

This research provides practitioners with a list of key checkpoints for preventing failure escalation, enables decision-makers to prioritise obstacle-mitigation efforts and develop a feasible process to control PPP operation, and offers management countermeasures to remove the key barriers impeding PPP sustainability.

This study is novel for adopting network-oriented techniques to quantify the relative importance of the IFs and examine the transmission pattern of the IFs system. Therefore, it visualises the complex underlying dynamics causing unsustainable PPP operation, identifies root and direct causes of PPP failures, and provides decision-makers with insights into sustaining PPP sustainability from a network-oriented perspective.

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

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

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

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

The dispute resolution process in the construction industry is known for delays in settlement, with some cases even escalating to complex arbitration and litigation. To avoid conflicts turning into disputes, the parties need to be proactive in identifying and resolving conflicts in their nascent stages. It is here that innovative lean construction practices can potentially act as a game-changer to avoid disputes, and this study aims to attempt to understand this phenomenon empirically.

A questionnaire-based empirical study, followed by semi-structured interviews, is conducted to understand the relevance of key tenets of lean principles in dispute avoidance.

Although stakeholders agree on the usefulness and practicality of lean principles in dispute avoidance, the extent of agreement is lesser when it comes to its implementation practicality. Moreover, there is a demographic influence observed on lean tenets such as “open communication”, “stakeholder collaboration” and “constraint identification”.

The results point towards an approach that combines contractual mandate, training and awareness creation to iron out the differences in the usefulness and practicality of lean approaches to avoid disputes.

Lean implementation is widely discussed in many construction contexts, such as sustainability, productivity improvement and planning. However, a discussion on lean philosophy’s role in dispute avoidance is muted. Therefore, this study assumes significance.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.

The poor quality of construction work in war-affected regions is a significant issue. The large-scale destruction to the existing infrastructure from the war necessitates cost and time-efficient delivery of construction projects during and post-war to bring normalcy to affected lives and places. Consequently, there is always a tendency to finish construction projects in the shortest possible time on a limited budget without following the proper quality management processes. However, the poor quality of construction projects continues to affect the country's development, growth, credibility, reputation, and public safety for several years after the war. To this end, the present study was conducted to evaluate the significant attributes and factors contributing to the poor quality of construction projects in the war-affected Afghan construction sector.

A total of 31 attributes influencing construction project quality were ranked based on 110 completed survey responses collected from Afghan construction professionals. Moreover, independent samples t-test, Spearman's rank correlation test, and exploratory factor analysis were conducted.

The study found a moderate consensus between clients and contractors on attributes' rankings. In addition, the independent samples t-test showed statistically significant differences in means values of responses from clients and contractors for eight attributes. Based on factor analysis, 19 important attributes (median value greater than or equal to four) were classified into 4 latent factors – (1) poor-quality assurance and control, (2) unethical practices, (3) design and drawing errors, and (4) knowledge and skills gap.

Evaluating the factors affecting the quality of construction projects will help clients, government departments, and construction practitioners improve the construction quality management practices. The findings will also inform the policies and procedures of international aid providers.

Extant studies have discussed numerous carbon reduction drivers, but there is a dearth of holistic review and understanding of the dynamic interrelationships between the drivers from a system perspective. Thus, this study aims to bridge that gap.

The study conducted a review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses and adopted interpretive structural modelling (ISM) to analyse and prioritise the drivers.

Eighteen drivers were identified and grouped into five, namely, policy instruments, bid-related, cost and risk, education and training, and reward and penalty drivers. The ISM revealed two hierarchical levels of the drivers with only higher cost of electricity/fuel on the higher level, making it the most important driver that could influence others.

The study presents an overview of decarbonisation drivers in the literature and would be of benefit to the government and stakeholders towards achieving net zero emissions in the construction industry.

The findings of the study present drivers of carbon reduction and prioritise and categorise them for tailored interventions within the construction sector. Also, it could serve as foundational knowledge for further study in the construction process decarbonisation research area.

With the surge in public procurement, especially in developing countries, ensuring fair competition in procurement has assumed paramount importance. Academic endeavors in the domain of competition issues have often lacked the views of field-level functionaries. This study aims to involve a large number of expert practitioners in India to identify the significant contemporary competition risks in public procurement from the procurer and supplier sides and develop a model depicting the hierarchy of competition-restrictive actions (CRAs) in procurement based on their mutual interactions.

The significant CRAs along the procurement cycle are identified through literature survey, interactive workshops and expert interviews. A questionnaire survey covering 143 respondents from 12 public organizations is used to evaluate their impact. Considering the complex causal interactions involved, interpretive structural modeling followed by MICMAC (Iimpact matrix cross-reference multiplication applied to a classification analysis is used to develop a hierarchical model of competition risks in procurement.

Tailor-made contracts, splitting of a project below competition thresholds, restrictive selection criteria and awarding the contract on nomination emerge as CRAs with the highest driving power. Horizontal collusion among vendors strongly depends on practices followed in the procuring organization.

The survey data and the experts’ opinions emanate from practitioners in India, which is a limitation. However, with necessary contextual calibrations, the study is of high functional utility to policymakers and practitioners.

The research facilitates a comprehensive understanding to procurement managers/policymakers of the CRAs along the procurement cycle and their interdependencies. It offers valuable insights for improving competition, which is foundational for optimal procurement outcomes.

The study enriches the public procurement domain knowledge by identifying and assessing the significant contemporary CRAs, examining their mutual interactions and developing an interpretive structural model. Although contributing to the body of knowledge, the study is unique in being grounded in field realities.

The Fourth Industrial Revolution (4IR) holds the potential to significantly improve capabilities and performances for architectural, engineering, construction and operation and maintenance (AECO) companies in India. The top management of such companies seems unsure and reluctant to implementation of the 4IR applications. The objective of this research is to identify the 4IR technology applications, which would have a significant impact on the operation of the AECO companies in India. Moreover, the paper further attempts to give a conceptual roadmap for the implementation of these 4IR technologies in the AECO value chain.

The nascent level of research in 4IR in construction necessitated the adoption of mixed methodologies in research. Hypothesis testing has been carried out on the quantitative data to ascertain the potential of 4IR technologies, which could significantly impact the AECO companies. Subsequently, qualitative research has been used to explore the reasons impacting the technology adoption and generate a possible road map for the implementation of the significant 4IR technology applications.

The AECO value chain is challenged due to its complexity, uncertainty, fragmented supply chains, myopic thinking and a culture reluctant to change. The study provides insights into the dilemmas of practitioners in the Indian context while exploring possible approaches to carry out the transformation in AECO.

The study validation relied on the opinions, perspectives and recollections of respondents. The opinion of practicing professionals was limited to the Indian context.

The article may help leaders of AECO firms, industry associations, policymakers and academia to take steps in relevant directions to enable digital transformation.