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Control, coordination, and adaptation functions in construction contracts: A machine-coding model
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AI
DOI：10.1016/j.autcon.2023.104890.png)
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Extant literature lacks an accurate and efficient measurement of construction contracts. Drawing on the control, coordination and adaptation functions of contracts, this study aims to develop a machine-coding model that provides a fine-grained and efficient tool for measuring complexity of construction contracts. To achieve this, we first constructed a dataset by manually coding 17 standard contract forms and 35 representative contracts selected from real construction projects. The DeBERTa language model, pre-trained on massive text data in the Natural Language Processing (NLP) field, was selected and fine-tuned for machine coding, achieving a high accuracy of 77.69%. The model provides a valuable tool for scholars to enrich construction contract research and for practitioners to design appropriate contracts by balancing different contract functions. This study inspires future research in the application of state-of-the-art NLP techniques to contract analysis and management in the construction industry.
Keyword:
Natural language processing
Machine coding
Contractual functions
Content analysis
Manual coding
Contract complexity
期刊
IF:
11.5
论文数:
6.3K
被引数:
4.2W
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