Learning from incidents (LFI) is a process to seek, analyse, and disseminate the severity and causes of incidents, and take corrective measures to prevent the recurrence of similar events. However, the effects of LFI on the learner’s safety performance remain unexplored. This study aimed to identify the effects of the major LFI factors on the safety performance of workers. A questionnaire survey was administered among 210 construction workers in China. A factor analysis was conducted to reveal the underlying LFI factors. A stepwise multiple linear regression was performed to analyse the relationship between the underlying LFI factors and safety performance. A Bayesian Network (BN) was further modelled to identify the probabilistic relational network between the underlying LFI factors and safety performance. The results of BN modelling showed that all the underlying factors were important to improve the safety performance of construction workers. Additionally, sensitivity analysis revealed that the two underlying factors—information sharing and utilization and management commitment—had the largest effects on improving workers’ safety performance. The proposed BN also helped find out the most efficient strategy to improve workers’ safety performance. This research may serve as a useful guide for better implementation of LFI practices in the construction sector.

Accidents in Repair, Maintenance, Alteration, and Addition (RMAA) work have become a growing concern, in recent years. The repair and maintenance works of electrical and mechanical (E&M) installations involves a variety of trades, a large number of practitioners and a series of high-risk activities. The uniqueness of E&M work, in the RMAA sector, requires a discrete and specific research to improve its safety performance. Understanding the causal relationships between safety factors and the number of accidents becomes crucial to develop a more effective safety management strategy. The Bayesian Network (BN) model is proposed to establish a probabilistic relational network between the causal factors, including both safety climate factors and personal experience factors that have influences on the number of accidents related to E&M RMAA work. The data were collected using a survey questionnaire, involving a hundred and fifty-five E&M practitioners. The BN results demonstrated that safety attitude and safety procedures were the most important factors to reduce the number of accidents. The proposed BN provides the ability to find out the most effective strategy with the best utilization of resources, to reduce the chance of a high number of E&M accidents, by controlling a single factor or simultaneously controlling, both, the safety climate and personal factors, to improve safety performance.

The airport at the Kai Tak district was relocated to Chek Lap Kok in 1998. The Hong Kong Government endeavors to redevelop Kai Tak into a mixed-use community. A total of eight fatal construction accidents have happened since the Kai Tak Development (KTD) commenced in 2013, and seven of them occurred between 2020 and 2021. The alarming figures call for an in-depth investigation of fatal accidents, hence the aim of the current research. Detailed accident investigation reports that outlined accident causation and preventive measures for the eight accidents were collected. With a detailed examination of validity and reliability, the modified loss causation model was applied to analyze the situational variables, incident sequences, and causes of accidents. The results showed that “fall” and “struck by” were the most common accidents in the KTD. Several risk factors for fatal accidents were identified, including “aging workers”, “new to a construction site”, “ethnic minority”, “illegal worker”, “working on weekends”, and “subcontracting companies”. Preventive measures were offered to help government authorities and construction practitioners enhance the safety performance of the ongoing KTD projects. This study contributes to the knowledge of construction safety by identifying safety issues of mega interfacing projects. The practice of learning from accidents should be promoted in order to prevent similar accidents from occurring again.

Having a higher educational level has been proposed to reduce workers’ unsafe behavior. It remains unclear whether the improvement in safety performance can be enhanced by workers with higher education levels, an individual’s learning ability, and a resilient safety culture. This study aims to examine the moderating effects of individual learning ability and resilient safety culture on the relationship between workers’ educational level and safety performance. A questionnaire survey was conducted to assess the education level, resilience safety culture, safety learning ability, and safety performance of workers. The results indicated that the educational level of construction workers has a significant positive impact on safety performance. They confirmed that an individual’s learning ability and a resilient safety culture have a positive moderating effect. This study supports the crucial relationship between worker education levels and safety performance. Thus, organizations and government entities can leverage this understanding to promote worker engagement in training programs and extend educational support. The study underscores the pivotal role of a resilient safety culture in bolstering the impact of worker educational level on safety performance. Finally, the study acknowledges the influence of an individual’s learning ability on safety performance. Integrating educational levels with individual learning abilities can facilitate the development of targeted strategies to improve safety performance.

This study investigates how firm attributes affect construction contractors’ efficiency in Hong Kong and Mainland China, from the period 2004 to 2010. This study finds that the efficiency of Hong Kong contractors is associated with their managerial capability to control business costs and financial capability to manage both short-term and long-term capital liquidity. The efficiency of Mainland China contractors is also associated with their managerial capability to control business and administrative costs but not with their financial capability to maintain capital liquidity. Theoretically, this study shows that managerial and technological abilities are two common factors that transcend different institutions and systems. Hong Kong is the freest economy in the world, whereas the economy of Mainland China is more regulated. Methodologically, data envelopment analysis is adopted to establish the efficiency scores of contractors to be analyzed by panel data regression, which controls individual cont...

A study on electrical and mechanical (E&M) works-related accidents for public sector projects provided the opportunity to gain a better understanding of the causes of accidents by analyzing the circumstances of all E&M works accidents. The research aims to examine accidents of E&M works which happened in public sector projects. A total of 421 E&M works-related accidents in the “Public Works Programme Construction Site Safety and Environmental Statistics” (PCSES) system were extracted for analysis. Two-step cluster analysis was conducted to classify the E&M accidents into different groups. The results identified three E&M accidents groups: (1) electricians with over 15 years of experience were prone to ‘fall of person from height’; (2) electricians with zero to five years of experience were prone to ‘slip, trip or fall on same level’; (3) air-conditioning workers with zero to five years of experience were prone to multiple types of accidents. Practical measures were recommended for each specific cluster group to avoid recurrence of similar accidents. The accident analysis would be vital for industry practitioners to enhance the safety performance of public sector projects. This study contributes to filling the knowledge gap of how and why E&M accidents occur and promulgating preventive measures for E&M accidents which have been under researched.