Engineering transaction structure optimization via improved social network dynamics and entropy integration

Mega engineering projects often encounter issues such as project delays and cost overruns due to their complexity and uncertainty. To enhance project management effectiveness, it is essential to design a rational engineering transaction governance structure tailored to the characteristics of each engineering project. To address the design issues of transaction governance structures for specific projects, this study first constructs an improved social network model within a dual-layer linguistic term framework to characterize the dynamic evolution of trust relationships among experts and quantify their weights. Subsequently, a hybrid weighting method that integrates the average method, entropy weighting, and game-theoretic approaches is employed to optimize attribute weight calculation, thereby enhancing the objectivity and accuracy of the decision-making process. On this basis, a trust-based reward and penalty mechanism is introduced to facilitate the gradual convergence of group opinions and achieve efficient consensus. Consequently, a multi-attribute group decision-making method is developed for engineering project transaction governance structure optimization, which integrates the dual-layer linguistic term environment with improved dynamic social network modeling and information entropy. Then, the model proposed in this paper is applied to a mega engineering project, verifying the feasibility of the model. Finally, by comparing with other group decision-making methods, the effectiveness and accuracy of the decision model for the governance structure decision-making in mega engineering project transactions are validated. The results could provide support for the decision-making of the governance structure in project legal entity transactions.