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Developing a weighted synergy network–based model for selecting prefabricated construction services

服务(商务) 选择(遗传算法) 计算机科学 加权 独创性 协同网络 知识管理 人工智能 业务 医学 营销 创造力 政治学 法学 放射科
作者
Xiaomin Qi,Qiang Du,Patrick X.W. Zou,Ning Huang
出处
期刊:Engineering, Construction and Architectural Management [Emerald Publishing Limited]
卷期号:31 (6): 2306-2326 被引量:6
标识
DOI:10.1108/ecam-04-2022-0334
摘要

Purpose The purpose of this paper is to develop a model considering synergy effect for prefabricated construction service combination selection. Design/methodology/approach This research defines prefabricated construction service as a service-led construction method that meets the specific requirements of clients. Based on network theory, the multi-dimensional collaborative relationships of the prefabricated construction inter-services are formulated. The synergy effect is quantitatively calculated through the linear weighting of the strengths of collaborative relationships. Further, a weighted synergy network (WSN) is developed, from which a service composition selection model considering the synergy effect is established. Then, a genetic algorithm is employed to implement the model. Findings The results showed that (1) when the number of prefabricated construction services is increased, the synergy effect of combination options is enhanced; (2) The finer-grained prefabricated construction services, the stronger the synergy effect of service combination; (3) Clients have heterogeneous preferences for collaborative relationships, and there are differences in the synergy effect of service combination. Originality/value The contribution of this research includes proposed a method to quantify the synergy effect from the perspective of collaborative relationships, explored the specific procedure for the prefabricated construction service combination selection under the service-led construction, and provided a reference for promoting the development in construction. Besides, the model proposed could be applied to prefabricated construction service composition selection with diverse research boundaries or client preferences by executing the same procedure.
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