Journal
ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT
Volume -, Issue -, Pages -Publisher
EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/ECAM-12-2021-1143
Keywords
Construction safety; Safety training; Persona; Personalization; Hybrid recommendation
Categories
Funding
- National Natural Science Foundation of China [72171224, 71871116]
- Humanities and Social Sciences Foundation of China's Education Ministry [19YJAZH122]
- Doctor Joint-Training Program of China Scholarship Council [202106420087]
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This paper proposes a persona-based approach to improve the participation and effect of safety training for construction workers. By extracting tags and calculating learning needs, and integrating collaborative filtering recommendation method, the training effect can be effectively improved.
Purpose Effective construction safety training has been considered to play a significant role in reducing the incidence of accidents. However, the current safety training methods pay less attention to the relationship between workers' personalized characteristics and their learning needs, which results in workers' low learning participation and poor training effect. The purpose of this paper is to improve the participation and effect of safety training for construction workers with a persona-based approach. Design/methodology/approach This paper presents a persona-based approach to safety tag generation and training material recommendation. By extracting the demographic characteristics and behavior patterns tags of construction workers, a neural network algorithm is introduced to calculate the learning needs tags of workers, and the collaborative filtering recommendation method is integrated to enrich the innovation of recommendation results. Offline experiments and online experiments are designed to verify the rationality of the proposed method. Findings The results show that the learning needs of workers are closely related to their background. The proposed method can effectively improve workers' interest in materials and the training effect compared with conventional safety training methods. The research provides a theoretical and practical reference for promoting active safety management and achieving worker-centered safety management. Originality/value First, a persona-based approach is introduced to establish a novel framework for solving the problem of personalized construction safety management. Second, an artificial intelligence algorithm is used to automatically extract the learning needs tag values and design a hybrid recommendation method for construction workers' personalized safety training. The collaborative filtering method is integrated to enrich the innovation of recommendation results.
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