Abstract:

Within the domain of multi-project management， a substantial corpus of research on critical chain buffer settings has rigorously investigated various attributes of activities， including temporal aspects， resource utilization， and the logical interdependencies among activities. However， there appears to be a conspicuous lack of scholarly attention directed toward managerial dimensions， particularly concerning how the social network structure in which a manager is embedded might influence the efficacy of the capacity constraint buffer （CCB） configuration. Moreover， predominant methodologies typically position the buffer at the end of an activity， a practice that can precipitate a domino effect and fails to ensure an optimal distribution of the buffer. In light of these observations， methodologies are integrated from social network analysis into the CCB determination process. It scrutinizes the potential influence of managers' social network affiliations on the CCB configuration， aiming to augment the conventional CCB model theoretically and to furnish managers with more rigorous insights into buffer settings. To effectively navigate the intricate landscape of multi-project management and to fully harness the subjective initiative demonstrated by managers， an innovative method of multi-project capacity constraint buffer setting based on social network analysis is proposed. First， the social network analysis method is applied to the project drum network to quantify the drum network attribute indicators based on the logical relationship of project activity progress. Second， social network analysis is used to analyze manager attributes and characterize the manager's decision-making level under the network information flow， and then construct a new evaluation index system. Then， the gray TOPSIS method is applied to determine the buffer size， and the buffer is adjusted by the project manager after searching for project-supportable resources in the social network. Finally， the buffer is set decentralized based on the drum activity gap， and the arithmetic example is selected to compare this paper's method with the classical method. The simulation results show that under the guarantee of a higher project completion rate， this method sets the buffer smaller and can effectively utilize the buffer， thus shortening the project duration. In summary， social network analysis is integrated into the process of setting capacity constraint buffers for multi-projects， providing a novel perspective on the theory and practice of critical chain project management. The proposed framework not only comprehensively considers the complexity of multi-project management， but also empowers managers to maximize their initiative. Through this innovative approach， project managers can enhance their ability to navigate through the ever-changing project execution environment by adapting their project organizational network structure.

Key words: multi-project management, critical chains, social network analysis, capacity constraint buffer, buffer setting