Mechanistic Analysis of the Evolution of Trust Level Between Owner and PMC Contractor Based on Dynamic Bayesian Network

The Project Management Contracting (PMC) project espouses a non-confrontational cooperation model. This paper employs a dynamic Bayesian network approach, grounded in social exchange theory, to construct a dynamic model of the evolution of trust levels between owners and PMC contractors. The findings of the study suggest that the trust level between the owner and the PMC contractor is primarily influenced by the extent of calculative and relational trust. Furthermore, the reciprocal behaviours and contractual flexibility emerge as the key drivers of both calculative and relational trust. Furthermore, reciprocal behaviours exert a more pronounced influence on the advancement of relational trust, whereas contract flexibility exerts a more pronounced influence on the advancement of calculative trust. Additionally, the level of calculative trust is higher at the outset of project implementation, with the generation of calculative trust subsequently leading to the generation of relational trust in the middle and later stages. In the middle and later stages of the project, the importance of relational trust increases, reaching a point where it surpasses that of calculative trust. Furthermore, the decline of relational trust has a greater negative impact on the overall trust level than calculative trust. The results of the research can provide theoretical guidance for the construction body to solve the problem of a low level of trust in the process of PMC project implementation.

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Publication Details

Journal
Buildings
Published
2024-10-24
DOI
https://doi.org/10.3390/buildings14113373
Citations
3
Primary Topic
Outsourcing and Supply Chain Management
Type
article
Field-Weighted Citation Impact
1.59

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article

Mechanistic Analysis of the Evolution of Trust Level Between Owner and PMC Contractor Based on Dynamic Bayesian Network

Aobo Yue, Hongyan Li, Abdul Bari
3 citations
Buildings
Outsourcing and Supply Chain Management
1.59
article

Mechanistic Analysis of the Evolution of Trust Level Between Owner and PMC Contractor Based on Dynamic Bayesian Network

Aobo Yue, Hongyan Li, Abdul Bari
article en
3 citations

Abstract

The Project Management Contracting (PMC) project espouses a non-confrontational cooperation model. This paper employs a dynamic Bayesian network approach, grounded in social exchange theory, to construct a dynamic model of the evolution of trust levels between owners and PMC contractors. The findings of the study suggest that the trust level between the owner and the PMC contractor is primarily influenced by the extent of calculative and relational trust. Furthermore, the reciprocal behaviours and contractual flexibility emerge as the key drivers of both calculative and relational trust. Furthermore, reciprocal behaviours exert a more pronounced influence on the advancement of relational trust, whereas contract flexibility exerts a more pronounced influence on the advancement of calculative trust. Additionally, the level of calculative trust is higher at the outset of project implementation, with the generation of calculative trust subsequently leading to the generation of relational trust in the middle and later stages. In the middle and later stages of the project, the importance of relational trust increases, reaching a point where it surpasses that of calculative trust. Furthermore, the decline of relational trust has a greater negative impact on the overall trust level than calculative trust. The results of the research can provide theoretical guidance for the construction body to solve the problem of a low level of trust in the process of PMC project implementation.

BuildingsVol. 14(11)
Chongqing University (CN), Hohai University (CN), Jiangsu University of Science and Technology (CN)
Jiangsu University of Science and Technology
Openalex Percentile: Top 13%
Outsourcing and Supply Chain Management
1.59
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Mechanistic Analysis of the Evolution of Trust Level Between Owner and PMC Contractor Based on Dynamic Bayesian Network — Aobo Yue, Hongyan Li, et al. · Buildings (2024) | TGRS Research Map | TGRS