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Although knowledge transfer in the context of projects and project-based organizations (PBOs) has gained increasing attention from academia and industry, it is not clear how knowledge transfers from projects to their parent PBOs. This research aims to explore the main factors influencing knowledge transfer from projects to their parent PBOs, and analyze how these factors integrate the transfer process as system components using the system dynamics (SD) method.

Based on the literature review, investigation and interview, this paper adopts the event analysis to obtain the influencing factors from historical cases and establishes a conceptual model of knowledge transfer from five dimensions, which simultaneously considers the knowledge sender, knowledge receiver and the relationship between the knowledge sender and receiver, knowledge features and transfer context. Then, the relationships between variables in the qualitative model were clarified, and a quantitative model including seven feedback loops was established using the SD model. Lastly, the system simulation and sensitivity analysis of the main parameters were realized in Vensim PLE software.

The simulation analysis results show that the model can simulate the knowledge transfer process from projects to the PBO to a certain extent. This research fully demonstrates the impact of variables from five dimensions on knowledge transfer and incorporates the knowledge gap and transfer threshold in the research category. Moreover, the rationality of seven feedback loops proposed in the model was verified. And the effects of various factors on the amount of knowledge transferred and the PBO's knowledge stock were examined through sensitivity analysis. Furthermore, recommendations for developing an integrated knowledge transfer mechanism of PBOs and projects to enhance transfer effect are offered.

This research provides other researchers with a systematic understanding of transfer process from projects to PBOs, and insight for further research on knowledge transfer in project and organization contexts. Furthermore, this study guides researchers to focus on the causal processes that constitute knowledge transfer and explores the expected and unexpected phenomena generated over time. However, some variables involved in the transfer process are simplified, and the establishment of a more complex dynamic model needs further research and discussion.

By establishing a simulation model for knowledge transfer from projects to their parent PBOs, this study helps project teams and PBOs grasp the overall picture of the transfer process. Especially, this paper provides target-oriented recommendations for project and PBO managers to implement effective knowledge transfer practices, which have certain practical values for knowledge cultivation, coordination, reuse and innovation in the organization.

This study contributes to knowledge management and project management literature by simulating the knowledge transfer process from projects to their parent PBOs. Additionally, this paper provides a reference for PBO and project managers to establish an integrated knowledge-transfer mechanism in the work process and comprehensively implement effective knowledge transfer practices.

Despite the knowledge transfer between projects has received increasing attention from scholars, few scholars still conduct comprehensive research on inter-project knowledge transfer from both horizontal and vertical perspectives. Besides, knowledge transfer is affected by multiple antecedent conditions, and these factors should be combined for analysis. Therefore, this paper aims to explore the key factors influencing knowledge transfer between projects using the fuzzy-set qualitative comparative analysis (fsQCA) method from both horizontal and vertical perspectives and how these factors combine to improve the effectiveness of knowledge transfer (EKT) between projects.

First, nine factors affecting knowledge transfer between projects were identified, which were from the four dimensions of subject, relationship, channel, and context, namely temporary nature (TN), time urgency (TU), transmit willingness (TW), receive willingness (RW), trust (TR), project-project transfer channels (PPC), project-enterprise transfer channels (PEC), organizational atmosphere (OA), and motivation system (MS). Then, the source of the samples was determined and the data from the respondents was collected for analysis. Following the operation steps of the fsQCA method, variable calibration, single condition necessity analysis, and configuration analysis were carried out. After that, the configurations of influencing factors were obtained and the robustness test was conducted.

The results of the fsQCA method show that there are five configurations that can obtain better EKT between projects. Configuration 3 (∼TN * ∼TU * TW * RW * TR * ∼PPC * PEC * MS) has the highest consistency, indicating that it has the highest degree of the explanatory variable subset. Configuration 1 (∼TN * ∼TU * TW * RW * PEC * OA * MS) has the highest coverage, meaning that this configuration can explain most cases. Also, the five configurations were divided into three types: vertical transfer, horizontal-vertical transfer, and channel-free transfer category.

Firstly, this study explores the key factors influencing knowledge transfer between projects from four dimensions, which presents the logical chain of influencing factors more clearly. Then, this study divided the five configurations obtained into three categories according to the transfer direction: vertical, horizontal-vertical, and channel-free transfer, which gives implications to focus on both horizontal knowledge transfer (HKT) and (VKT) when studying knowledge transfer between projects. Lastly, this study helps to realize the exploration of combined improvement strategies for EKT, thereby providing meaningful recommendations for enterprises and project teams to facilitate knowledge transfer between projects.

The purpose of this paper is to explore the micro-level variables contributing to political risks in international construction projects.

A total of 25 micro-level variables were identified from the literature review, and a questionnaire survey was performed with 138 professionals from both academia and industry. Then, the Spearman rank correlation was used to test whether there was agreement on ranking between the two respondent groups. Furthermore, the 25 variables were grouped into six underlying factors through the exploratory factor analysis.

The results indicated that the most critical variables were “project desirability to the host country,” “relationship with governments,” “misconduct of contractors,” “public opposition to the project,” “experiential knowledge of political risks” and “advantageous conditions of contract.” In addition, the opinions within each group were consistent and there was no significant disagreement on the rankings of variables between academics and practitioners. However, the academic and practitioner groups held different opinions on some individual variables. The impact direction of the variables was associated with confusion among the respondents.

The findings presented in this paper can help international construction enterprises effectively manage political risks in international construction projects.

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.

This paper aims to explore the key risk factors affecting the Personnel Localization Management of international construction projects under the major public emergencies represented by the novel coronavirus pneumonia pandemic (hereinafter COVID-19) and how the public emergency affected the Personnel Localization Management from three levels: staff turnover rate, the number of different personnel, the salary and performance of workers. The paper also helps to enhance the construction enterprises' response capacity of major public emergencies and provides a comprehensive framework of optimization strategies for the Personnel Localization Management of international construction projects (hereinafter projects).

The main research method of this paper is the case study, and ten representative international construction projects are selected for case study in China construction enterprises (hereinafter CCE). And this study used the failure mode and effects analysis (FMEA) and comparative analysis to find out all potential risk factors under the COVID-19 and analyze how the epidemic affects the Personnel Localization Management of projects which based on the primary data from 10 projects obtained through in-depth interviews and the secondary data from China First Metallurgical Group and Central South Construction Group's Overseas Enterprise.

The findings show that the outbreak of the major public emergencies not only greatly increased eight risk factors but also directly led to an increase in staff turnover rate. Meanwhile, the numbers of Chinese and local managers and workers are all affected, and an increase in the number and the salary performance of local workers can be reduced, to a certain extent, to the cost-to-output ratio of the projects. The findings would help construction enterprises better cope with Personnel Localization Management and enhance the response capacity of major public emergencies.

This study will broaden researchers' horizons regarding “Personnel Localization Management under major public emergencies” and “risk factors of Personnel Localization Management in an international context.” Furthermore, construction enterprises looking for a better mechanism of Personnel Localization Management can benefit from research findings and lessons learned from the authors' case study during or before an outbreak of major public emergency. Lastly, the framework of optimization strategies for Personnel Localization Management can be used both for research purposes and practice issues in international construction projects.

The findings from the authors' case study offer the direction for international construction enterprises in China and other countries to formulate effective measures, strengthen overseas business and establish a crisis management mechanism for Personnel Localization Management under major public emergencies, and the findings provide emergency plans for projects to improve the public crisis handling capacity and respond to major public emergencies such as the COVID-19.

This study analyzes the impact of the COVID-19 on the Personnel Localization Management of international construction projects from the perspective of personnel. This study provides a theoretical reference for the international construction industry to actively respond to major public emergencies. Besides, the research is conducive to improving the emergency response mechanism in the construction industry, and further promoting the high-quality and globalized development of international construction.

This study provides other researchers with a comprehensive understanding of the risk factors affecting the Personnel Localization Management of projects under the COVID-19 and insight for further research on localization management, risk management, and project management.

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.

This study aims to investigate the relationship between individual-level psychological resources and team resilience in the context of expatriate project management teams. It seeks to understand how personal psychological resources contribute to team resilience and explore the dynamic evolution mechanism of team resilience. The goal is to enhance team resilience among expatriates in a BANI (Brittle, Anxious, Nonlinear, and Incomprehensible) world, where organizations face volatile and uncertain conditions.

An online survey was applied for data collection, and 315 valid samples from Chinese expatriates in international construction projects were utilized for data analysis. A structural equation model (SEM) examines the relationships between personal psychological resources and team resilience. The study identifies five psychological factors influencing team resilience: Employee Resilience, Cross-cultural Adjustment, Self-efficacy, Social Support, and Team Climate. The hypothesized relationships are validated through the SEM analysis. Additionally, a fuzzy cognitive map (FCM) is constructed to explore the dynamic mechanism of team resilience formation based on the results of the SEM.

The SEM analysis confirms that employee resilience, cross-cultural adjustment, and team climate positively impact team resilience. Social support and self-efficacy also have positive effects on team climate. Moreover, team climate is found to fully mediate the relationship between self-efficacy and team resilience, as well as between social support and team resilience. The FCM model provides further insights into the dynamic evolution of team resilience, highlighting the varying impact effects of antecedents during the team resilience development process and the effectiveness of different combinations of intervention strategies.

This study contributes to understanding team resilience by identifying the psychological factors influencing team resilience in expatriate project management teams. The findings emphasize the importance of social support and team climate in promoting team resilience. Interventions targeting team climate are found to facilitate the rapid development of team resilience. In contrast, interventions for social support are necessary for sustainable, long-term high levels of team resilience. Based on the dynamic simulation results, strategies for cultivating team resilience through external intervention and internal adjustment are proposed, focusing on social support and team climate. Implementing these strategies can enhance project management team resilience and improve the core competitiveness of contractors in the BANI era.

The smart contract provides an opportunity to improve existing contract management practices in the construction projects by replacing traditional contracts. However, translating the contracts into computer languages is considered a major challenge which has not been investigated. Thus, it is necessary to: (1) identify the obstructing clauses in real-world contracts; and (2) analyze the replacement's technical and economic feasibility. This paper aims to discuss the aforementioned objectives.

This study identified the flexibility clauses of traditional contracts and their corresponding functions through inductive content analysis with representative standard contracts as materials. Through a speculative analysis in accordance to design science paradigm and new institutional economics, the economic and technical feasibility of existing approaches, including enumeration method, fuzzy algorithm, rough sets theory, machine learning and artificial intelligence, to transform respective clauses (functions) into executable codes are analyzed.

The clauses of semantic flexibility and structural flexibility are identified from the contracts. The transformation of semantic flexibility is economically and/or technically infeasible with existing methods and materials. But with more data as materials and methods of rough sets or machine learning, the transformation can be feasible. The transformation of structural flexibility is technically possible however economically unacceptable.

Given smart contracts' inability to provide the required flexibility for construction projects, smart contracts will be more effective in less relational contracts. For construction contracts, the combination of smart contracts and traditional contracts is recommended. In the long run, with the sharing or trading of data in the industry level and the integration of machine learning or artificial intelligence reducing relevant costs, the automation of contract management can be achieved.

This study contributes to the understanding of the smart contract's limitations in industry scenarios and its role in construction project management.

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.

This study aims to modify the human factors analysis and classification system (HFACS) to make it suitable for collapse accident analysis in construction. Based upon the modified HFACS, distribution patterns of causal factors across multiple levels were discerned among causal factors of various stakeholders at construction sites. It explored the correlations between two causal factors from different levels and further determined causation paths from two perspectives of level and stakeholder.

The main research framework consisted of data collection, coding and analysis. Collapse accident reports were collected with adequate causation information. The modified HFACS was utilized for coding causal factors across all five levels in each case. A hybrid approach with two perspectives of level and stakeholder was proposed for frequency analysis, correlation analysis and path identification between causal factors.

Eight causal factors from external organizations at the fifth level were added to the original HFACS. Level-based correlation analyses and path identification provided safety managers with a holistic view of inter-connected causal factors across five levels. Stakeholder-based correlation analyses between causal factors from the fifth level and its non-adjacent levels were implemented based on client, government and third parties. These identified paths were useful for different stakeholders to develop specific safety plans for avoiding construction collapse accidents.

This paper fulfils an identified need to modify and utilize the HFACS model for correlation analysis and path identification of causal factors resulting in collapse accidents, which can provide opportunities for tailoring preventive and protective measures at construction sites.