Sustainable Construction Safety Knowledge Sharing: A Partial Least Square-Structural Equation Modeling and A Feedforward Neural Network Approach

Rita Yi Man Li, Beiqi Tang and Kwong Wing Chau
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Rita Yi Man Li: Department of Economics and Finance/HKSYU Real Estate and Economics Research Lab/Sustainable Real Estate Research Centre, Hong Kong Shue Yan University, Hong Kong, China
Beiqi Tang: Department of Economics and Finance/HKSYU Real Estate and Economics Research Lab/Sustainable Real Estate Research Centre, Hong Kong Shue Yan University, Hong Kong, China
Kwong Wing Chau: Department of Real Estate and Construction, The University of Hong Kong, Hong Kong, China

Sustainability, 2019, vol. 11, issue 20, 1-18

Abstract: Most studies focused on the introduction of new technologies have not investigated the psychological factors affecting the willingness to use them or conducted empirical studies to explore whether willingness and actual construction safety knowledge-sharing behavior are associated with fewer construction incidents. We conducted face-to-face and LinkedIn open-ended interviews as well as a global survey to study the willingness and actual behavior to share construction knowledge via social software Web 2.0, Internet of Things (IoT) and mobile apps. Then, the Partial Least Square-Structural Equation Model (PLS-SEM) for willingness and actual knowledge-sharing behavior, as well as the Multilayer Perceptron (MLP) Neural Network were used to illustrate the effect of various factors on predicting the willingness to share knowledge via Web 2.0, mobile apps and IoT. Results of the interviews found that practitioners use IoT for knowledge sharing, mainly because they do not want to fall behind the curve. PLS-SEM and MLP revealed that practitioners share construction safety knowledge are not driven by safety-related reasons such as safety awareness enhancement but perceived organization support from their companies. Employees who agree that their organization cared about their employees’ well-being was the strongest predictor in influencing people’s decision to use tools for knowledge sharing. Moreover, many respondents claimed that factors such as monetary rewards have little impact on motivating people to use tools for knowledge sharing.

Keywords: construction safety; Web 2.0; Internet of Things; mobile apps; artificial neural network; partial least square-structural equation model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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