Search results
1 – 2 of 2Wanyi Chen and Fanli Meng
Corporate digital transformation (CDT) has challenged traditional tax administration systems. This study examines the impact of CDT on tax avoidance behavior and tests whether tax…
Abstract
Purpose
Corporate digital transformation (CDT) has challenged traditional tax administration systems. This study examines the impact of CDT on tax avoidance behavior and tests whether tax authorities can identify this behavior.
Design/methodology/approach
Using data on listed companies on the Shanghai and Shenzhen Stock Exchanges from 2008 to 2020, this study applies the Heckman two-stage and cross-section models.
Findings
The results show that the higher the degree of CDT, the more aggressive the tax avoidance behavior. The CDT's impact on corporate tax avoidance is more significant under strong government tax efforts.
Originality/value
This study expands research on the economic consequences of CDT and the factors influencing corporate tax avoidance behavior. Moreover, it has important implications for governments to monitor tax avoidance behavior under the CDT, improve digital tax systems, and pay more attention to the tax administration of digital assets.
Details
Keywords
Hongya Niu, Zhaoce Liu, Wei Hu, Wenjing Cheng, Mengren Li, Fanli Xue, Zhenxiao Wu, Jinxi Wang and Jingsen Fan
Severe airborne particulate pollution frequently occurs over the North China Plain (NCP) region in recent years. To better understand the characteristics of carbonaceous…
Abstract
Purpose
Severe airborne particulate pollution frequently occurs over the North China Plain (NCP) region in recent years. To better understand the characteristics of carbonaceous components in particulate matter (PM) over the NCP region.
Design/methodology/approach
PM samples were collected at a typical area affected by industrial emissions in Handan, in January 2016. The concentrations of organic carbon (OC) and elemental carbon (EC) in PM of different size ranges (i.e. PM2.5, PM10 and TSP) were measured. The concentrations of secondary organic carbon (SOC) were estimated by the EC tracer method.
Findings
The results show that the concentration of OC ranged from 14.9 μg m−3 to 108.4 μg m−3, and that of EC ranged from 4.0 μg m−3 to 19.4μg m−3, when PM2.5 changed from 58.0μg m−3 to 251.1μg m−3 during haze days, and the carbonaceous aerosols most distributed in PM2.5 rather than large fraction. The concentrations of OC and EC PM2.5 correlated better (r = 0.7) than in PM2.5−10 and PM>10, implying that primary emissions were dominant sources of OC and EC in PM2.5. The mean ratios of OC/EC in PM2.5, PM2.5–10 and PM>10 were 4.4 ± 2.1, 3.6 ± 0.9 and 1.9 ± 0.7, respectively. Based on estimation, SOC accounted for 16.3%, 22.0% and 9.1% in PM2.5, PM2.5–10 and PM>10 respectively.
Originality/value
The ratio of SOC/OC (48.2%) in PM2.5 was higher in Handan than those (28%–32%) in other megacities, e.g. Beijing, Tianjin and Shijiazhuang in the NCP, suggesting that the formation of SOC contributed significantly to OC. The mean mass absorption efficiencies of EC (MACEC) in PM10 and TSP were 3.4 m2 g−1 (1.9–6.6 m2 g−1) and 2.9 m2 g−1 (1.6–5.6 m2 g−1), respectively, both of which had similar variation patterns to those of OC/EC and SOC/OC.
Details