Research on profit distribution mechanism of green supply chain for precast buildings

Yuliang Guo, Qilan Zhao, Xiaoying Li and Boyang Liu

International Journal of Low-Carbon Technologies, 2025, vol. 20, 990-1000

Abstract: In prefabricated building construction, efficient profit distribution within the supply chain is vital. This study leverages machine learning models decision trees (DT), random forests, k-nearest neighbors, and deep neural networks to classify task groups, including “Design Team,” “Quality,” “Safety,” and “Site Management.” Our analysis evaluates these models’ using accuracy, precision, recall, and F-1 score, revealing high performance, particularly for DT and DNN models, which achieved 97% accuracy. The strong results across all models highlight their reliability for optimizing resource allocation, enhancing project efficiency, and providing key insights into broader construction industry applications.

Keywords: prefabricated building construction; supply chain management; profit distribution; task group classification; deep neural networks (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ijlctc:v:20:y:2025:i::p:990-1000.

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