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Article
Publication date: 30 August 2022

Pinsheng Duan, Jianliang Zhou and Wenhan Fan

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…

Abstract

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.

Details

Engineering, Construction and Architectural Management, vol. 31 no. 1
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 1 November 2022

Zechen Guan, Tak Wing Yiu, Don Amila Sajeevan Samarasinghe and Ravi Reddy

The aim of this paper is to review and analyze the research literature on the health and safety issues of migrant workers in the construction industry from 2000 to 2022.

Abstract

Purpose

The aim of this paper is to review and analyze the research literature on the health and safety issues of migrant workers in the construction industry from 2000 to 2022.

Design/methodology/approach

5 steps method is used to conduct a systematic review to achieve the objectives. After scanning two authoritative search engines “Web of Science” and “Scope”, 60 articles are selected from 225 publications for identification and review. These identified articles are classified by research fields, countries and time span.

Findings

The review finds that with the increasing influence of migrant construction workers, the number of publications on the health and safety of migrant workers has shown a rapid upward trend. Moreover, language barriers are the most dominant safety risk factors encountered by on-site migrant workers. This systematic literature review also summarizes the definition of migrant workers and solutions to reduce safety risk factors.

Originality/value

The research data on the health and safety issues and risk factors of migrant workers in the construction industry is still limited. This literature review summarizes the research trends and contributions of the literature in this field in the past 22 years and provides theoretical support for future research on the safety management of the migration construction field.

Details

Engineering, Construction and Architectural Management, vol. 31 no. 3
Type: Research Article
ISSN: 0969-9988

Keywords

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