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In construction projects, engineering variations are very common and create breeding grounds for opportunistic claims. This study investigates the complementary effect between an inspection mechanism and a reputation system in deterring opportunistic claims, considering an employer with limited inspection accuracy and a contractor, which can be either reputation-concerned or opportunistic.

This paper applies a signaling game to investigate the complementary effect between the employer's inspection and a reputation system in deterring the contractor's possible opportunistic claim, considering the information-flow influence of claiming prices.

This study finds that in the exogenous-inspection-accuracy case, the employer does not always inspect the claim. A more stringent reputation system complements a less accurate inspection only when the inspection cost is lower than a threshold, but may decline the employer's surplus or social welfare. In the optimal-inspection-accuracy case, the employer always inspects the claim. However, only a sufficiently stringent reputation system can guarantee the effectiveness of an optimal inspection in curbing opportunistic claims. A more stringent reputation system has a value-stepping effect on the employer's surplus but may unexpectedly impair social welfare, whereas a higher inspection cost efficiency always reduces social welfare.

This article contributes to the project management literature by combing the signaling game theory with the reputation theory and thus embeds the problem of inspection mechanism design into a broader socio-economic framework.

Early termination of public–private partnerships (PPPs) in China is caused by various risk factors, resulting in significant losses. This study aimed to clarify the key factors and identify the causal relationships among these factors.

Social network analysis (SNA) was used to analyze 37 risk factors that were summarized from 97 early terminated PPP cases and to identify the relationships among these key risk factors. Interpretive structural modeling (ISM) was conducted to explore the causal relationships. Data were collected from case documents, questionnaires and interviews.

A total of 17 key risk factors were identified and distributed in a hierarchical structure with six tiers. Among these key risk factors, the root causes affecting the early termination of PPP projects were government oversight in decision-making, local government transition, policy and law changes and force majeure. The direct cause was insufficient returns. Furthermore, local government and private sector defaults were essential mediating factors. Local government transition and the low willingness of the private sector were highlighted as potential key risks.

The cases and experts were all from China, and outcomes in other countries or cultures may differ from those of this study. Therefore, further studies are required.

This research provides knowledge regarding the key risk factors leading to the early termination of PPP projects and guidance on avoiding these factors and blocking the factors' transmission in the project lifecycle.

This study contributes to the knowledge of risk management by emphasizing the importance of local government transition, the low willingness of the private sector and project cooperation and operation, whose significance is ignored in the existing literature. The proposed ISM clarifies the role of risk factors in causing early termination and explains their transmission patterns.

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

Infrastructure projects are pivotal for regional economic development, but also face low project effectiveness. Leadership is always regarded as a key enabler for project team effectiveness, including vertical leadership and team-level leadership. The purpose of this paper is to examine how vertical leadership facilitates shared leadership in infrastructure project teams.

This paper develops the conceptual model based on the literature review. Then the questionnaire survey was conducted. The empirical data obtained from 117 infrastructure project teams in China were analyzed by partial least squares structural equation modeling (PLS-SEM) for validating the proposed model. Finally, the results were comparatively discussed to explain the dual-pathway between vertical leadership and shared leadership. And the practical implications were presented for the project managers in infrastructure project teams.

Drawing on social learning theory and social cognitive theory, the results show that both participative leadership and task-oriented leadership can facilitate shared leadership. Further, team atmosphere fully mediates the link between participative leadership and shared leadership. Team efficacy fully mediates the relation between task-oriented leadership and shared leadership. Also, role clarity has a negative moderating effect on the former path.

The study extends the knowledge of leadership theory in the construction field. Based on the proposed conceptual model and PLS-SEM results, this study unveils the black box between vertical leadership and shared leadership and contributes to the theory of leadership on how the impact of different vertical leadership on team process promotes shared leadership.