File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.3390/su11205831
- Scopus: eid_2-s2.0-85074280129
- WOS: WOS:000498398900287
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Sustainable Construction Safety Knowledge Sharing: A Partial Least Square-Structural Equation Modeling and A Feedforward Neural Network Approach
Title | Sustainable Construction Safety Knowledge Sharing: A Partial Least Square-Structural Equation Modeling and A Feedforward Neural Network Approach |
---|---|
Authors | |
Keywords | construction safety Web 2.0 Internet of Things mobile apps artificial neural network |
Issue Date | 2019 |
Publisher | MDPI. 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? |
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. |
Persistent Identifier | http://hdl.handle.net/10722/293434 |
ISSN | 2023 Impact Factor: 3.3 2023 SCImago Journal Rankings: 0.672 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Li, RYM | - |
dc.contributor.author | Tang, B | - |
dc.contributor.author | Chau, KW | - |
dc.date.accessioned | 2020-11-23T08:16:42Z | - |
dc.date.available | 2020-11-23T08:16:42Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Sustainability, 2019, v. 11 n. 20, p. article no. 5831 | - |
dc.identifier.issn | 2071-1050 | - |
dc.identifier.uri | http://hdl.handle.net/10722/293434 | - |
dc.description.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. | - |
dc.language | eng | - |
dc.publisher | MDPI. The Journal's web site is located at http://www.mdpi.com/journal/sustainability | - |
dc.relation.ispartof | Sustainability | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | construction safety | - |
dc.subject | Web 2.0 | - |
dc.subject | Internet of Things | - |
dc.subject | mobile apps | - |
dc.subject | artificial neural network | - |
dc.title | Sustainable Construction Safety Knowledge Sharing: A Partial Least Square-Structural Equation Modeling and A Feedforward Neural Network Approach | - |
dc.type | Article | - |
dc.identifier.email | Chau, KW: hrrbckw@hku.hk | - |
dc.identifier.authority | Chau, KW=rp00993 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.3390/su11205831 | - |
dc.identifier.scopus | eid_2-s2.0-85074280129 | - |
dc.identifier.hkuros | 319868 | - |
dc.identifier.volume | 11 | - |
dc.identifier.issue | 20 | - |
dc.identifier.spage | article no. 5831 | - |
dc.identifier.epage | article no. 5831 | - |
dc.identifier.isi | WOS:000498398900287 | - |
dc.publisher.place | Basel, Switzerland | - |