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The aim of this article states that in each stage of the industrial revolution, only a few initiatives have been real game changers. In Industry 3.0, “Internet of Information” has transformed the business landscape via connectivity and communications. Enterprises could come together to spur innovation in a cooperative or competitive manner. In Industry 4.0, the “Internet of Value” has shown considerable benefits; and, blockchain technology is expected to touch all layers of a business ecosystem, and the construction industry is not an exception.

This study aims to answer the “How do enterprise blockchain solutions contribute to the vibrancy of the construction ecosystem from social, economic, and environmental aspects?” Following a comprehensive literature review, the Grey Ordinal Priority Approach (OPA-G) is employed in multiple criteria decision analysis (MCDA). OPA-G can select functionally rich enterprise blockchain solutions that meet the needs of the future construction industry, while there is uncertainty in the input data.

The results from the case study show that organization under observation welcomes an enterprise blockchain solution that delivers services related to “renewable energy certificates” in the context of “smart cities and built environment”. Employing high-ranked blockchain solutions brings vibracy and sustainability to construction ecosystem in terms of “C₆. decentralized finance and investment,” “C₃. multi-party and cross-industry collaboration,” and “C₈. data-driven value creation”.

At the micro level, blockchain solutions automate processes, streamline operations, and build new capacities on a new business model. At the macro level, blockchain creates a vibrant ecosystem based on transparency, decentralization, consensus-based democracy, interoperability, etc. Indeed, the capability of blockchain solutions at an enterprise scale (enterprise blockchain solutions) can shape a new construction ecosystem. The practical implications of current research are preparing executives for a fundamentally different next normal in construction.

In the digital transformation era, the construction industry is not immune to unintended consequences and disruptions of distributed ledger technologies like blockchain. At the micro-level, construction organizations need an in-depth understanding of blockchain risks to take proactive strategies for being on the safe side. This study seeks to answer “What are the risks associated with blockchain technology from the firm-level perspective? And how can this disruptive technology overshadow the business objectives and impact organizational criteria?”

The current research proposes a novel model for risk assessment based on the trapezoidal fuzzy ordinal priority approach (OPA-F) in the multi-criteria decision-making (MCDM) context. The proposed model handles uncertainties of experts' judgment around three primary parameters: the importance of organizational criteria, the impact of blockchain risks on criteria and the probability of risk occurrence.

The case study shows that organizational “communication and information” is exposed to the most blockchain risk. On the contrary, blockchain has less to do with an organization's “corporate social responsibility.” Furthermore, effective blockchain risk management can bring about cost efficiency, quality and improved customer experience for this case study. In the end, the authors develop a conceptual blockchain risk management framework based on findings.

This study will broaden researchers' horizons regarding “blockchain in construction context” and “blockchain risk management.”

Furthermore, executives looking for blockchain-based solutions can benefit from research findings and lessons learned from this case study before decision-making. Lastly, the risk assessment model based on trapezoidal OPA-F can be used both for research purposes and industrial decision problems.

To the best of the authors’ knowledge, it is for the first time that the OPA-F is employed in a risk assessment model. Also, the original OPA-F is extended to trapezoidal OPA-F using trapezoidal fuzzy numbers, and it is the first attempt to evaluate blockchain risks facing construction organizations and develop a blockchain risk management framework accordingly.

This paper aims to explore the key factors affecting knowledge transfer within cross-cultural teams in international construction projects from three levels: individual factors, team factors and knowledge characteristics. It also provides a comprehensive framework to examine how trust, cultural distance, team identification, knowledge tacitness and complexity and members' transfer willingness impact knowledge transfer effectiveness within cross-cultural teams.

A conceptual model and 16 hypotheses were put forward through the literature review and pilot investigation. This study used structural equation modeling to examine how factors affect the effectiveness of knowledge transfer within cross-cultural teams based on the questionnaire data of samples from Chinese international construction projects.

The findings show that affect-based trust and team identification positively affect the willingness to contribute knowledge. Conversely, knowledge tacitness, knowledge complexity and cultural distance negatively influence contribute willingness. Moreover, affect-based trust, cognition-based trust and team identity positively affect receive willingness, while cultural distance negatively impacts receive willingness. Additionally, affect-based and cognition-based trust, knowledge tacitness and complexity affect transfer effectiveness through the full mediation of transfer willingness, while cultural distance and team identity affect transfer effectiveness through the partial mediation of transfer willingness.

On the one hand, this research provides a holistic framework for factors affecting knowledge transfer within cross-cultural teams from three levels: individual factors, team factors and knowledge characteristics. On the other hand, the paper gives other researchers in international project management the enlightenment of focusing on members' cultural structure and the cross-cultural training of the team.

This study offers the direction for cross-cultural team managers to formulate helpful approaches for knowledge transfer and assist corporate leaders in taking integral control measures to enhance knowledge transfer effectiveness within the team.

This study provides other researchers with a comprehensive understanding of the key factors affecting knowledge transfer within cross-cultural teams in international construction projects and insight for further research on project management and knowledge management.

The purpose of this paper is to extend the PROMETHEE method under typical hesitant fuzzy information for solving multi-attribute decision-making problem in which there is hesitancy among experts.

Different aggregation and distance functions were developed to deal with HFS. But it is rational that different operators applying in existing methods can produce different results. Also, it is difficult for decision makers to select suitable operators. To address the drawback, this paper develops the PROMETHEE method as an outranking approach to accommodate hesitant fuzzy information. Since the proposed method is constructed on the basis of the pair-wise comparisons, it is independent of the aggregation and distance functions.

To demonstrate the efficiency and accuracy of the proposed method, the authors provide a numerical example and a comparative analysis. The results indicate that outranking-based methods suggest a better ranking than the aggregation- and distance-based methods.

The proposed approach does not consider the hesitant fuzzy linguistic information decision-making problem.

The proposed approach can be applied in many group decision-making problems in which there is hesitancy among experts.

This paper proposes an extension on PROMETHEE method under hesitant fuzzy information, which has not been reported in the existing academic literature.

Users are the key players in an online social network (OSN), so the behavior of the OSN is strongly related to their behavior. User weight refers to the influence of the users on the OSN. The purpose of this paper is to propose a method to identify the user weight based on a new metric for defining the time intervals.

The behavior of an OSN changes over time, thus the user weight in the OSN is different in each time frame. Therefore, a good metric for estimating the user weight in an OSN depends on the accuracy of the metric used to define the time interval. New metric for defining the time intervals is based on the standard deviation and identifies that the user weight is based on a simple exponential smoothing model.

The results show that the proposed method covers the maximum behavioral changes of the OSN and is able to identify the influential users in the OSN more accurately than existing methods.

In event detection, when a terrorist attack occurs as an event, knowing the influential users help us to know the leader of the attack. Knowing the influential user in each time interval based on this study can help us to detect communities which formed around these people. Finally, in marketing, this issue helps us to have a targeted advertising.

User effect is a significant issue in many OSN domain problems, such as community detection, event detection and recommender systems.

Previous studies do not give priority to the recent time intervals in identifying the relative importance of users. Thus, defining a metric to compute a time interval that covers the maximum changes in the network is a major shortcoming of earlier studies. Some experiments were conducted on six different data sets to test the performance of the proposed model in terms of the computed time intervals and user weights.

Selecting a suitable contract to outsource construction projects is an ongoing concern for project managers and organizational directors. This study aims to propose a comprehensive model to manage the risks of outsourced construction project contracts.

To employ the proposed model, firstly, the types of contracts and risks in the organization should be identified, then, to prioritize the contracts, the identified risks are considered as criteria. After receiving the experts' opinions, the best–worst method (BWM) integrated with grey relation analysis (GRA) method was used to prioritize the contracts. BWM and GRA are multi-criteria decision-making methods with different approaches and applications. In the current study, BWM has been employed to calculate the weights of criteria because it has better performance than other methods such as the analytic hierarchy process (AHP). After calculating the weights of criteria, the GRA method has been utilized for ranking the alternatives.

According to the results obtained from the case study, the cost plus award fee contract is the most suitable alternative for outsourcing construction projects. The proposed methodology can be practically applied through different types of the projects such as construction or “engineering, procurement and construction”.

To the best of our knowledge, this is the first time a conceptual model has been proposed to select an appropriate contract for construction projects. Also, for the first time, the BWM integrated with GRA method has been used to prioritize project contracts based on the potential risks. The proposed model can contribute to project managers for selecting a suitable contract with the least risk in construction projects.

The purpose of this paper is to propose a method for solving multi-objective linear programming (MOLP) with interval coefficients using positioned programming and interactive fuzzy programming approaches.

In the proposed algorithm, first, lower and upper bounds of each objective function in its feasible region will be determined. Afterwards using fuzzy approach, considering a membership function for each objective function and finally using grey linear programming, the solution for this problem will be obtained.

According to the presented example, in this paper, the proposed method is both simple in use and suitable for solving different problems. In the numerical example mentioned in this paper, the proposed method provides an acceptable solution for such problems.

As in most real-world situations, the coefficients of decision models are not known and exact. In this paper, the authors consider the model of MOLP with interval data, since one of the solutions to cover uncertainty is using interval theory.

Based on using grey theory and interactive fuzzy programming approaches, an appropriate method has been presented for solving MOLP problems with interval coefficients. The proposed method, against the complex methods, has less effort and offers acceptable solutions.

The study aims to introduce two new models of project scheduling by incorporating potential quality loss cost (PQLC) in time–cost tradeoff problems by overcoming the drawbacks of the existing Kim, Khang and Hwang (KKH) model. The proposed methods are named the Revised KKH-I (RKKH-I) and Revised KKH-II (RKKH-II) models for project scheduling.

The performance of the existing KKH model has been tested using a numerical example followed by the identification of the main shortcomings of the KKH method. Later, a concrete effort has been made to address its shortcomings while improving its performance significantly. The comparative analysis of the Revised KKH models with the original model has also been presented along with sensitivity analyses.

The study recognizes that the construct on which the original KKH method was built is important; however, certain drawbacks make it unable to consider PQLC in projects, thus making its practical use questionable. The comparative analysis of the proposed methodology with the original method demonstrated that the new models (RKHH-I and II) are more comprehensive and intelligent than the existing KKH model.

The comparative analysis of the original KKH model and its improved version reveals that the revised model is far more suitable for project scheduling. The study is important for project managers who recognize project scheduling being one of the key parameters associated with project management process, crucial to control every day during the management of projects.

The purpose of this paper is to examine projects crashing based on the factors including cost, time, quality, risk and the law of diminishing returns.

The paper first investigated effective factors on project crashing then proposed a grey linear programming model. In the proposed grey linear programming model, the costs of quality of works that include the cost of conformance and non-conformance of deliverables in the project were studied. The results are presented for considering the existing uncertainties using positioned programming under the sensitivity analysis table and graphs.

The lack of consideration of project risks will reduce the project success probability in future. The proposed model reduces the existing uncertainties to a significant extent by covering the project risks completely. Based on the law of diminishing returns, after a certain point technically known as saturation point, the increase of resources does not lead to the reduction of time and may even have negative impacts. Finding the saturation point for each activity prevents the excessive allocation of resources that can lead to reduction of productivity.

The main duty of each project manager is finishing the project in the framework of the determined objectives. In most of the cases, after the preparation of the initial project schedule by the project team, it is seen that there is a need for the time reduction. This study has used a grey linear programming model for optimum crashing of project activities. In order to make the model more realistic and applicable, the authors endeavoured to consider most of the factors that are involved in doing a project.

In the present study, to the best of the authors’ knowledge the factors of time, cost, quality, risk and the law of diminishing returns are simultaneously considered in project crashing for the first time and the grey theory was used for considering the uncertainties of project parameters. Also, “the law of diminishing returns” has not been considered during crashing in the studies conducted so far.

Previous fraud studies focused on the influence of external environmental factors rather than the actor's own cognition or psychological factors. This paper aims to explore the influence of cognitive factors on people's intention to commit fraud in the construction industry.

A scenario-based questionnaire survey was conducted with 248 Chinese construction practitioners. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the data.

The findings showed that perceived threat possibility and perceived threat severity positively affected people's attitudes towards fraud. The reward for compliance and response cost had adverse effects on people's attitudes. Attitude towards fraud and response efficacy directly influenced people's intentions to commit fraud.

The limitations of this study are that only behavioral intention data were collected, and a single scenario was designed. Despite these limitations, this study proposed a cognitive model to understand fraud in the construction industry and provided an empirical analysis using data from Chinese construction practitioners.

This study reveals the impact of cognitive factors on fraud in the construction industry. The results expand the understanding of fraud and propose a cognitive intervention framework to reduce fraud.