Abstract
Performance evaluation in construction safety is of great importance to further improve upon safety management processes. This paper develops a data envelopment analysis (DEA) based framework to evaluate the construction safety performance at the macro level. The core of the method is to compare the output-input ratio of construction safety. Using the building practitioner, construction machinery and equipment, and construction area as the inputs, and value added of construction and death toll as the outputs, safety performance score is computed for the China’s provincial construction industries from 2009 to 2017. The results show that the number of benchmark provinces every year is between five and seven. The gap between the best-performing and underperforming province was relatively small in 2012 and big in 2014. Beijing, Qinghai, Hainan, Fujian, Chongqing, and Tianjin can be utilized as role models for the provinces that need to improve their performance in construction safety. The eastern region has the highest score in construction safety performance, followed by the western and central region. This study provides an effective solution to solve performance issue in regional construction safety and improves the tradition performance evaluation system to a certain extent.
Highlights
The construction industry is one of the 20 industrial categories in China’s economy (General Administration of Quality Supervision, Inspection and Quarantine of PRC [GAQSIQ], 2017), which plays an important role in the economic development
Many academic scholars found that partial-factor indicators were not applicable and might be misleading (Hu & Wang, 2006; Boyd, 2008), for example, it is obviously improper to compare the safety performance of decision-making units (DMUs) by means of only the fatality numbers or rates because they ignore the amount of exposure to risk in construction safety
This paper develops a data envelopment analysis (DEA)-based framework to evaluate the construction safety performance at the macro level, combining with both the desirable output and the outputinput ratio
Summary
The construction industry is one of the 20 industrial categories in China’s economy (General Administration of Quality Supervision, Inspection and Quarantine of PRC [GAQSIQ], 2017), which plays an important role in the economic development. Most construction safety performance commonly used are OSHA recordable incidence rates and experience modification rating (Wanberg et al, 2013). These partial-factor indicators have their own advantages and disadvantages as academic scholars investigate further (Stern, 2012). Many academic scholars found that partial-factor indicators were not applicable and might be misleading (Hu & Wang, 2006; Boyd, 2008), for example, it is obviously improper to compare the safety performance of decision-making units (DMUs) by means of only the fatality numbers or rates because they ignore the amount of exposure to risk in construction safety. The total-factor indicators which are based on multiple input-output systems, can effectively remedy the shortage of partial-factor indicators, and have been applied for performance evaluation by many scholars (Feng & Wang, 2017)
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