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Relationship conflict between the owners and contractors is inevitable, which could induce negative consequences. Yet, the existing literature mostly focused on its direct effects on project performance and ignored the process by which relationship conflict gradually deteriorates cooperation as well as corresponding managerial approaches. Given the fact that relationship conflict originates from interdependent tasks, the proposed theoretical model is intended to measure relational behavior as an instant outcome of relationship conflict, and explore the buffering role of contract enforcement approach.

This paper develops the conceptual model based on the literature review. Then the questionnaire survey was conducted. The dyadic data obtained from 168 Chinese construction project professionals were analyzed by the Partial Least squares Structural Equation Modeling (PLS-SEM) technique.

The results show that relational behavior partially mediates the link between relationship conflict and project performance. Besides, three types of contract enforcement approaches are found to differentially change the negative link between relationship conflict and relational behavior. Rigid contract enforcement can worsen the adverse effects of relationship conflict on relational behavior, whereas flexible contract enforcement can alleviate these negative effects. The level of mitigation hinges on whether compromising behaviors or obliging behaviors are chosen.

The study extends the knowledge of conflict theory and contract theory in the construction field. Based on the proposed conceptual model and PLS-SEM results, this study contributes to the understanding of relationship conflict’s consequences between the owners and contractors and enriches conflict management approaches in the construction field.

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.

In today's digital and post-pandemic era, construction teams can span their boundary to obtain important resources and support in computer-mediated ways. However, the benefits of computer-mediated team boundary spanning (TBS) are mostly assumed. Empirical evidence for these benefits is in lack. Thus, this study attempts to investigate the influence of computer-mediated (instant messaging in this study) TBS on construction project performance and the underlying mechanism.

From the multiteam system (MTS) perspective, this study employs the input-process-outcome (IPO) framework and coordination theory to explore the influence of instant messaging-based team boundary spanning (IMTBS) on construction project coordination processes and project performance. A theoretical model is built and validated with a survey involving 206 construction projects.

Results show that IMTBS positively affects knowledge integration and project coordination, but negatively affects project commitment. The positive link between IMTBS and project performance is attributable to knowledge integration and project coordination. Further, project commitment is also found to negatively mediate the relationship between IMTBS and construction project performance.

To the best of the authors’ knowledge, this study is the first to empirically investigate the influence of TBS on construction project performance. As such, this study contributes to the literature on TBS in the construction field. In addition, the findings of this study unveil the double-edged characteristic of IMTBS, which should attract managers' attention. This also indicates that the form of TBS is a significant determinant of its effectiveness, which should attract scholars' attention in the future.

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.

Geographical query formulation is one of the key difficulties for users in search engines. The purpose of this study is to improve geographical search by proposing a novel geographical query reformulation (GQR) technique using a geographical taxonomy and word senses.

This work introduces an approach for GQR, which combines a method of query components separation that uses GeoNames, a technique for reformulating these components using WordNet and a geographic taxonomy constructed using the latent semantic analysis method.

The proposed approach was compared to two methods from the literature, using the mean average precision (MAP) and the precision at 20 documents (P@20). The experimental results show that it outperforms the other techniques by 15.73% to 31.21% in terms of P@20 and by 17.81% to 35.52% in terms of MAP.

According to the experimental results, the best created taxonomy using the geographical adjacency taxonomy builder contains 7.67% of incorrect links. This paper believes that using a very big amount of data for taxonomy building can give better results. Thus, in future work, this paper intends to apply the approach in a big data context.

Despite this, the reformulation of geographical queries using the new proposed approach considerably improves the precision of queries and retrieves relevant documents that were not retrieved using the original queries. The strengths of the technique lie in the facts of reformulating both thematic and spatial entities and replacing the spatial entity of the query with terms that explain the intent of the query more precisely using a geographical taxonomy.