Determining Safety Climate Factors in the Repair, Maintenance, Minor Alteration, and Addition Sector of Hong Kong

Abstract

Accident record of the repair, maintenance, minor alteration, and addition (RMAA) sector has been alarmingly high; however, research in the RMAA sector remains limited. Unsafe behavior is considered one of the key causes of accidents. Thus, the organizational factors that influence individual safety behavior at work continue to be the focus of many studies. The safety climate, which reflects the true priority of safety in an organization, has drawn much attention.Safety climate measurement helps to identify areas for safety improvement. The current study aims to identify safety climate factors in the RMAA sector. A questionnaire survey was conducted in the RMAA sector in Hong Kong. Data were randomly split into the calibration, and the validation samples. RMAA safety climate factors were determined by exploratory factor analysis on the calibration sample.

Motivating Project Owners to Increase Their Commitment towards Improving the Delivery Performance of Green Building Projects

“…The correlation between factors 1 and 2 is significant (ρ< 0.05) at 0.448, but not large enough (≥0.85) to cause multicollinearity or discriminant validity problems (Kenny, 2016). The results of the discriminant validity test showed that the structure has dissimilar constructs for the two factors because the AVE of factor 1 (INT = 0.649) and factor 2 (EXT = 0.736), are greater than the squared factor correlation between INT and EXT (R 2 = 0.230) (Hon, et al, 2012). Finally, the internal consistency of observed variables within latent variables, (known as construct reliability), and calculated based on Equation 1, for INT and EXT are 0.808 and 0.821 respectively, was above the "good quality" level of 0.70 (Bagozzi & Yi, 1988).…”

“…5 and ≤1.0) for standardized factor loading in construction management research (e.g. (Hon, et al, 2012;Oladinrin & Ho, 2015;Xiong, et al, 2015b). Of note is the reduced number of the observed variables (or indicators) of owner commitment from eight (OC1-OC8) to three (OC2-OC4).…”

“…Assessing the suitability of the data for factor analysis, the Kaiser-Meyer-Olkin (KMO) value of 0.791 indicated sufficient sampling adequacy (Williams, Brown, & Onsman, 2012), while the Bartlett's test of sphericity (χ 2 = 250.464; df = 21) is significant at ρ < 0.01, which indicated that the correlations were sufficiently large for EFA (Hooper, 2012). In line with Hon, et al (2012), the correlation matrix contained numerous coefficients of 0.3 and above, and the factor loading cut-off was fixed at 0.4. On this basis, no item removed.…”

“…The average variance extracted (AVE) was calculated to assess the discriminant validity (Xiong, et al, 2015a). According to Hon, et al (2012), the discriminant validity (that constructs in the model are significantly different from one another) is affirmed when the AVE of a factor is greater than its squared correlations with other factors.…”

“…Lastly, over half of the most recently executed green building projects by the project owners are 5 Star rated, followed by 6 Star and 4 Star. DATA ANALYSIS Similar to Hon, Chan, and Yam (2012), data were randomly split into calibration sub-sample and validation sub-sample for data analysis. The calibration sub-sample data were analysed with exploratory factor analysis (EFA) in IBM SPSS statistics 21 -which helped to find the latent structure of the dataset by uncovering common factors empirically (Hooper, 2012).…”