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Open AccessArticle

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

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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
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Department of Real Estate and Construction, The University of Hong Kong, Hong Kong, China
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(20), 5831; https://doi.org/10.3390/su11205831
Received: 6 September 2019 / Revised: 17 October 2019 / Accepted: 18 October 2019 / Published: 21 October 2019
(This article belongs to the Special Issue Sustainable Construction Quality and Safety Management)
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. View Full-Text
Keywords: construction safety; Web 2.0; Internet of Things; mobile apps; artificial neural network; partial least square-structural equation model construction safety; Web 2.0; Internet of Things; mobile apps; artificial neural network; partial least square-structural equation model
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Li, R.Y.M.; Tang, B.; Chau, K.W. Sustainable Construction Safety Knowledge Sharing: A Partial Least Square-Structural Equation Modeling and A Feedforward Neural Network Approach. Sustainability 2019, 11, 5831.

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