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Coevolution of relationship networks and resistance behaviors for building information modeling implementation in construction projects

共同进化 互惠(文化人类学) 抗性(生态学) 社会网络分析 社交网络(社会语言学) 过程(计算) 适应(眼睛) 任务(项目管理) 知识管理 结构方程建模 选择(遗传算法) 工程类 计算机科学 心理学 社会心理学 生态学 社会化媒体 人工智能 生物 机器学习 操作系统 万维网 神经科学 系统工程
作者
Shiting Shao,Dongping Cao
出处
期刊:International Journal of Project Management [Elsevier BV]
卷期号:42 (5): 102617-102617 被引量:3
标识
DOI:10.1016/j.ijproman.2024.102617
摘要

Heterogeneous individual participants are embedded within multiple dynamic intra-project relationship networks, which can both shape and be shaped by individual behaviors through social influence and selection processes, respectively. Yet empirical research on these complex interrelationships within projects remains lacking. This study fills this lacuna by investigating how formal task-oriented communication and informal knowledge-oriented advice networks coevolve with individual resistance behaviors for building information modeling (BIM) implementation in construction projects through social selection and influence processes. Stochastic actor-oriented network models and longitudinal data on project-level BIM implementation practices are used to examine this question. After controlling for related covariate and structural effects, the results provide clear evidence for the social selection process in which communication and advice ties in the networks are both more frequently formed between project participants with more similar resistance behaviors. Concerning the social influence process, the results show that compared with knowledge-oriented advice ties, task-oriented communication ties tend to more significantly influence the assimilation of resistance behaviors. The network-behavior coevolution process is simultaneously associated with the covariate effects related to individual experience as well as the structural effects related to reciprocity and triadic closure. As a pioneering effort of using longitudinal network modeling methods to empirically characterize network-behavior dynamics in projects, this study provides a deepened understanding of how social selection and influence processes collectively shape the dynamic interactions among heterogeneous project participants as a complex adaptive system.
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