Visual attention of construction workers is closely related to their safety performance. Identifying and understanding safety signs on workplace effectively is beneficial to improve visual attention. This study focuses on exploring the influencing mechanism of construction safety sign features on visual attention of construction workers using the eye-tracking technology, in order to improve visual attention and workplace safety performance through optimizing the construction safety signs. A theoretical model of influencing mechanism of safety sign features on visual attention was constructed based on visual information processing theory. To verify the theoretical model, an experiment was conducted as follows: 28 pictures of safety signs including visual and cognitive features were shown on the computer screen, then eye movement data from 41 subjects was obtained using EyeLink1000 Plus. Statistical test methods were employed to analyze the relationship between safety sign features and eye-tracking metrics. The statistical results of theoretical model indicate that, among visual features, red and rectangular safety signs can reduce cognitive load of first fixation, green signs can reduce cognitive difficulties, however visual attention is not closely related to auxiliary words. Among the cognitive features, unfamiliar signs require more cognitive effort, while no significant difference exists in visual attention of different levels of concreteness and sematic closeness. This study provides theoretical and practical basis for improving construction workers’ visual attention through optimizing visual and cognitive features of construction safety signs.

The role of economic policy uncertainty in the risk transmission between crude oil and stock market cannot be ignored. However, it is unclear whether economic policy uncertainty always amplifies the impact of oil price shocks on stock market over time. This study employs the time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV) model to examine the dynamic relationship among different types of oil price shocks, economic policy uncertainty, and China’s stock market returns at the aggregate and industry levels. The empirical results are as follows: First, different types of oil price shocks and economic policy uncertainty have significant time-varying impacts on stock market returns, which mainly occur in the short term. During periods of increased economic policy uncertainty, the stock market is more sensitive to oil price shocks. Second, economic policy uncertainty provides a transmission channel for the propagation between oil price shocks and stock markets, but how does economic policy uncertainty connect oil-stock nexus depends on the origins of oil price shocks. Third, the response patterns of stock market to oil price shocks and economic policy uncertainty are heterogeneous in different industries. Our results provide important implications for policymakers and investors.