Factors motivating construction safety knowledge sharing in online social media

Sung, W-K (2017) Factors motivating construction safety knowledge sharing in online social media. Unpublished PhD thesis, University of Hong Kong, Hong Kong.

Abstract

The construction industry has the highest accident and fatality rates among all industries. According to the figures collected from the Labour Department of Hong Kong, there were nearly 3500 construction-related accidents in 2014. Government and organizations have put resources into trainings, accident information dissemination, management systems, and safe equipment in order to provide a safe work environment, while researchers have integrated visualization, data mining, knowledge management systems and various technologies into reducing the number of accidents and injuries in the construction industry. There has been, however, limited research on the usage of online social media in supplementing conventional training and enhancing the tacit knowledge of construction safety shared by individuals in the construction industry. This study aims to understand the current use of online social media in construction safety knowledge sharing and the motivations for such knowledge sharing. Social cognitive theory has been adopted in developing the research model, as this study focuses on the individual learning and knowledge building processes through collaboration in the social context. The research model is constructed with eight hypotheses to test the influence of the determinants of knowledge sharing behavior: community identity, social awareness, knowledge sharing self-efficacy, altruism, overconfidence, and intention to share knowledge. Aiming to provide a current picture of knowledge sharing behavior and a practical analysis of the research model, this study undertakes quantitative research methodology using a four-page self-reflective questionnaire for data collection. The snowball sampling method was adopted and 21 companies were invited to participate in the study. Out of the 816 questionnaires collected from March to May 2015, there are 741 valid responses for statistical analysis. The statistical software SmartPLS v3.0 was used to test the eight hypotheses. The results show that five hypotheses are statistically significant. One determinant, community identity, is statistically significant in determining knowledge sharing self-efficacy and social awareness. Three determinants—knowledge sharing self-efficacy, altruism, and intention to share knowledge—have a positive influence on knowledge sharing behavior. Unlike previous research, this research reveals that factors such as ”community identity”, ”social awareness” and ”overconfidence” do not have a statistically significant relationship with the intention to share knowledge about construction accident prevention. The sample population possesses an average of 9.7 years of Internet experience and 6.2 years of online social media experience. The individuals perceive that they have discussed safety- and accident-prevention-related matters in online social media like Whatsapp, Facebook and Wechat. The exploratory questions in this study reveal that the respondents are positive in the trend of using online social media in the workplace and for accident prevention, though there is concern about confidentiality, timeliness, and credibility of the information sources. Organizations interested in using online social media for construction safety knowledge sharing to supplement existing training programs should emphasize the direct determinants, i.e., knowledge sharing self-efficacy, altruism, and intention to share knowledge. The indirect factor, community identity, can also be included in boosting the knowledge sharing self-efficacy and social awareness of the construction community.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: confidentiality; population; tacit knowledge; construction safety; equipment; collaboration; government; knowledge management; learning; safety; visualization; Hong Kong; data mining; statistical analysis; quantitative research; motivation; training
Date Deposited: 16 Apr 2025 19:34
Last Modified: 16 Apr 2025 19:34