1. Introduction
The number of prefabricated building projects has been growing rapidly in China under the strong support of recent policies. The Opinions on Promoting Green Development of Urban and Rural Construction press conference in October 2021 revealed that the gross area of new prefabricated construction projects in China reached 740 million square meters in 2021, an increase of 18% compared with 2020, accounting for roughly a quarter of all new construction project types; around two-thirds of the new prefabricated construction projects were concrete structures with a total gross area of 490 million square meters [
1]. Along with this growth in prefabricated buildings, the incident rate of hoisting operations has been continuously rising. The Ministry of Housing and Urban-Rural Development of China defines a construction safety incident as an accident that occurs suddenly in the production and operation activities of the on-site construction unit, harming personal safety and health, damaging equipment and facilities, or causing economic losses, resulting in the temporary suspension or permanent termination of the original production and operation activities. The Ministry’s 2021 Housing and Municipal Engineering Production Safety Accidents Report, as shown in
Table 1, reveals that 99 safety incidents and 123 deaths occurred during the first quarter of 2021, an increase of 17 incidents (21%) and 22 deaths (22%) compared with the same period of the previous year. Among the fatalities, 54 were falls and 12 were from crane injuries.
Because most of these fatalities occurred in the construction and hoisting stage and have posed a serious threat to the safety of workers, it is of significant importance that construction workers’ unsafe behaviors in hoisting operations of prefabricated buildings are identified and analyzed. To achieve this goal, this study uses the Hazard and Operability (HAZOP) method combined with survey questionnaires, statistical analysis, and field verification through a case study to improve construction safety in the hoisting operations of prefabricated buildings.
2. Literature Review
Safety behavior refers to behavior that will not infringe, endanger, harm, or cause los, and which is affected by personality traits [
2], emotion control [
3], work–life conflicts [
4,
5], etc. The unsafe behaviors of employees can cause many injury incidents, especially in the construction industry. At present, research on the unsafe behavior of construction workers mainly focuses on the safety culture at the group level and behavioral safety at the individual level. For example, He [
6] discussed the differences between supervisors and workers in the dimensions of safety environment and safety behavior at the group level, while Zhang [
7] started from the perspective of the individual level. The paper adopts a psychological method to study how personality traits affect the occurrence of unsafe behaviors of construction workers.
Quantitative analysis methods are widely used in the study of workers’ unsafe behavior. Guo [
8] used the skeleton-based real-time identification method, developed by Guo to capture the dynamic movement of workers, to identify unsafe behaviors. Qi [
9] revealed the occurrence mechanism of workers’ unsafe behaviors from the perspective of occupational stress through the developed structural equation model. Hung [
10] used a deep convolutional neural network to propose a system to identify workers’ dangerous behaviors and classify unsafe behaviors. Qualitative analysis methods have also been used in studying workers’ unsafe behaviors and have focused on areas such as social psychology and modular construction. Khan [
11] evaluated fire safety performance according to the characteristics of multi-story garment (RMG) buildings in India, and Zermane [
12] used fault tree analysis to assess the risk of high-altitude work in Malaysian buildings. Chih [
13] studied the negative impact of psychological contract breach (PCB) on workers’ safety, Guo [
14] used an intelligent video surveillance method to carry out an early warning of workers’ illegal behaviors, and Chatzimichailidou [
15] studied the safety risk of modular construction in the construction industry. Although these studies have revealed the causes of workers’ unsafe behaviors to a certain extent, they are limited to traditional buildings and rarely involve new trends such as prefabricated buildings.
The research on occupational safety in the field of prefabricated construction mainly focuses on safety-influencing factors and intervention measures. James [
16] proposed that the standardized use of mechanical equipment can effectively reduce the occurrence of safety accidents in prefabricated construction. Lee [
17] used the AHP method to analyze the weight of the influencing index of safety management in prefabricated construction and evaluated project safety based on it. Francisco [
18] put forward a risk assessment theory applicable to the construction site of prefabricated buildings, which concluded that safety accidents due to falling from high altitude and lifting injury accounted for a high proportion and suggested that the causes of accidents in the process of installation and demolition were due to non-compliance with operating procedures and other unsafe behaviors. Fard [
19] made statistics on the data of safety accidents of prefabricated buildings in the United States in recent years and concluded that in falls from height, instability of the connection points of prefabricated members was the main factor inducing unsafe behaviors. In a study of intervention measures, Zou [
20] focused on the relationship between prefabricated construction personnel and the management system and concluded that the key to safety management for prefabricated construction lies in human management. Xu [
21] and Zhang [
22] identified and analyzed the unsafe behaviors of construction workers using computer vision and proposed targeted prevention and treatment measures. Chang [
23] reduced the construction safety risk level of prefabricated buildings to the maximum extent through a novel dual-objective optimization model. However, most of the above studies focused on the whole process of prefabricated building construction: the analysis was not detailed enough due to the large scope of involvement. In addition, more attention was paid to the hazard factors leading to unsafe behaviors, while less attention was paid to the possible consequences of unsafe behaviors and subsequent preventive measures.
The main research fields for HAZOP analysis are concentrated in petrochemical, thermal, and chemical engineering. Marhavilas [
24] used HAZOP–DMRA technology to evaluate the safety of petrochemical industry operations, while Sirima [
25] chose fault tree analysis and HAZOP analysis to explore the risks in the steam production process. Patle [
26] proposed a holistic method for the safety analysis of the formic acid production process by using the improved HAZOP model. HAZOP analysis is often used in combination with sensitivity analysis and survey questionnaires. Sbaaei [
27] used a sequential module simulation method and automated HAZOP study to conduct dynamic modeling. Zhao [
28] used the deep learning method to improve the safety assessment process of HAZOP in the chemical production process. Danko [
29] and Yang [
30] both used survey questionnaires to simulate the “expert brainstorming” segment of HAZOP analysis. Some scholars also applied HAZOP analysis to the field of construction; for example, Niu [
31] used HAZOP analysis to identify and manage the unsafe behavior of crane workers, and Wang [
32] combined this method with accident analysis to build a knowledge database of construction expert systems.
Although various studies have investigated the unsafe behaviors of construction workers, few have focused on the unsafe behaviors during the construction and hoisting operation of prefabricated buildings. Since the HAZOP analysis method can be utilized to identify the deviation and change of unsafe behaviors as well as their causes, consequences, and countermeasures, it was applied in this study to investigate the unsafe behaviors during hoisting operations of prefabricated buildings. The application of HAZOP provides an innovative method and theoretical foundation for reducing unsafe behaviors in hoisting operations of prefabricated buildings and serves as a reference for decision-making for hoisting safety policies in prefabricated construction projects.
3. Methodology
Based on the findings of the literature review, a survey questionnaire was first developed and administered at selected construction sites of prefabricated buildings to gather respondents’ perceptions of potential safety risks and influencing factors. The collected survey dataset was then statistically analyzed using the SPSS software to ensure its integrity and reliability. Next, the survey results were summarized to identify the safety risks and safety-influencing factors during each stage of hoisting operations. After that, HAZOP was applied to identify the deviation and change of the unsafe behaviors as well as their causes, consequences, and countermeasures. Finally, a case study was presented to verify the effectiveness of the countermeasures through comparison and evaluation method in experimental economics.
3.1. Survey Questionnaire
The survey was administered at a construction site of prefabricated buildings located in the city of Zibo, China to ensure the sample size and representativeness. A total of 300 survey questionnaires were distributed on-site to hoisting workers, of which 263 were recovered (87.7%). After sorting out the incomplete questionnaires, 203 were determined to be valid (67.7%).
The questionnaires are divided into four sections with objective questions in each section, including (1) basic personal information such as gender, age, occupation, etc., (2) workers’ perception of risks during hoisting operations, (3) the most common safety hazards during hoisting operations, and (4) the causes of safety hazards during hoisting operations. The workers’ perception of risks during hoisting operations describes the degree of danger perceived in different phases of hoisting operations. The most common safety hazards during hoisting operations include a list of 33 potential safety hazards concluded from the literature review based on a 5-point Likert scale. The causes of safety hazards include a list of 16 potential factors contributing to the occurrence of safety hazards based on a 5-point Likert scale.
3.2. HAZOP Analysis
Since the HAZOP analysis method can be utilized to identify the deviation and change of unsafe behaviors as well as their causes, consequences, and countermeasures, it was applied in this study to investigate the unsafe behaviors during hoisting operations of prefabricated buildings. The lead words of the HAZOP analysis were first created to define the workers’ behaviors and describe the various conditions that can occur during hoisting operations.
Table 2 presents the lead words and their meaning used in the HAZOP analysis, which guide the identification of deviations of safety factors in hoisting operations.
3.3. Case Study
A residential prefabricated building project was selected as the case study for the HAZOP analysis. The case study uses the comparison and evaluation method in experimental economics, which is able to obtain the density relationship between the evaluation results and the probability distribution after applying independent variables, allowing a clearer view of the impact of independent variables on the evaluation results. As a result, the comparison and evaluation method can be used to verify the validity of the hypothesis.
5. Field Verification
5.1. Experiment Design
The residential project selected for the case study consists of 14 separate residential buildings numbered Building 1 through Building 14, each containing eleven levels above ground and two levels underground, with a total height of 33.35 m and an elevation difference of 0.45 m between the interior and exterior floor height. The building structure was rated at safety grade two, seismic fortification intensity seven degrees, building site category three, and building anti-floating design grade b.
One independent variable was selected in the case study experiment in order to avoid the uncertain influence of variable mixing and crossing in the experiment, which was whether to implement HAZOP analysis for unsafe behaviors and countermeasures. The countermeasures for workers’ unsafe behaviors in hoisting operations of prefabricated buildings were obtained from the results of the HAZOP analyses presented in this paper.
Two hoisting construction teams in this project were marked as Team A and Team B, and both teams had 30 hoisting workers after adjustment. Team A was selected as the experimental group and strictly implemented the HAZOP analysis for unsafe behaviors and countermeasures in six phases of hoisting operations, whereas Team B was selected as the control group, which maintained its original working habits and did not implement any of the countermeasures for the unsafe behaviors. The duration of the case study was 20 days, which was roughly the schedule to complete the main structure of the four-story building. Due to the maintenance of the structural concrete of each floor, hoisting operations were performed alternatively between two buildings for both teams.
All hoisting workers were asked to wear a wristband sensor to detect when and what unsafe behaviors happened. The jobsite was equipped with 24-h surveillance cameras to capture the type and severity of hoisting workers’ unsafe behaviors. Drone footage was also used to analyze safety risks due to negligence. Through these monitoring measures, the probability density between the independent variable and a reduction in unsafe behaviors was calculated, which consequently determined whether the countermeasures from the HAZOP analysis did help reduce the occurrence of hoisting workers’ unsafe behaviors.
5.2. Experiment Results
The actual experiment case study lasted for 22 days from 29 July to 19 August 2021, including two days of delay due to typhoon weather. Team A completed four floors, including Building 3 floors 2 and 3 and Building 5 floors 2 and 3, while Team B also completed four floors, including Building 1 floors 3 and 4 and Building 6 floors 4 and 5.
By analyzing the wristband sensor data, on-site surveillance images, and drone footage, the unsafe behaviors of the two teams were compared with the safety deviation obtained by the HAZOP analysis method above. After removing the unsafe events that were irrelevant to this study, such as worker heatstroke, fighting, etc., three unsafe behaviors were found in Team A and nine unsafe behaviors were identified in Team B, as shown in
Table 14.
A comparison of worker unsafe behaviors between the two hoisting teams in the case study experiment demonstrates that the HAZOP analysis method can be effectively applied to the study of construction workers’ unsafe behaviors and that the countermeasures obtained by the HAZOP analysis method can significantly reduce the occurrence of unsafe behaviors in prefabricated building hoisting operations.