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

TitleSustainable Construction Safety Knowledge Sharing: A Partial Least Square-Structural Equation Modeling and A Feedforward Neural Network Approach
Authors
Keywordsconstruction safety
Web 2.0
Internet of Things
mobile apps
artificial neural network
Issue Date2019
PublisherMDPI. The Journal's web site is located at http://www.mdpi.com/journal/sustainability
Citation
Sustainability, 2019, v. 11 n. 20, p. article no. 5831 How to Cite?
AbstractMost 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.
Persistent Identifierhttp://hdl.handle.net/10722/293434
ISSN
2018 Impact Factor: 2.592
2015 SCImago Journal Rankings: 0.478
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, RYM-
dc.contributor.authorTang, B-
dc.contributor.authorChau, KW-
dc.date.accessioned2020-11-23T08:16:42Z-
dc.date.available2020-11-23T08:16:42Z-
dc.date.issued2019-
dc.identifier.citationSustainability, 2019, v. 11 n. 20, p. article no. 5831-
dc.identifier.issn2071-1050-
dc.identifier.urihttp://hdl.handle.net/10722/293434-
dc.description.abstractMost 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.-
dc.languageeng-
dc.publisherMDPI. The Journal's web site is located at http://www.mdpi.com/journal/sustainability-
dc.relation.ispartofSustainability-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectconstruction safety-
dc.subjectWeb 2.0-
dc.subjectInternet of Things-
dc.subjectmobile apps-
dc.subjectartificial neural network-
dc.titleSustainable Construction Safety Knowledge Sharing: A Partial Least Square-Structural Equation Modeling and A Feedforward Neural Network Approach-
dc.typeArticle-
dc.identifier.emailChau, KW: hrrbckw@hku.hk-
dc.identifier.authorityChau, KW=rp00993-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/su11205831-
dc.identifier.hkuros319868-
dc.identifier.volume11-
dc.identifier.issue20-
dc.identifier.spagearticle no. 5831-
dc.identifier.epagearticle no. 5831-
dc.identifier.isiWOS:000498398900287-
dc.publisher.placeBasel, Switzerland-

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