The Relationship between Trade Liberalization and Environmental Pollution across Enterprises with Different Levels of Viability in China

Zheng, Shijun; Zhou, Fengxiu; Wen, Huwei

doi:10.1080/1540496x.2021.1961738

Cited by 28 publications

(9 citation statements)

References 37 publications

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“…This finding indicates that strengthening environmental regulations restrains the increasing energy consumption caused by digital economy development. In addition, green technological innovations can partly moderate the negative effect of environmental regulations on haze pollution in dynamic situations (Feng et al 2021;Zheng et al 2021), and information can also improve energy efficiency (Henryson et al 2000). Therefore, technical progress eliminates the negative effect of digital economy development on GTFEE.…”

Section: Estimation Results For the Dynamic Panel Modelmentioning

confidence: 99%

Nonlinear and spatial spillover effects of the digital economy on green total factor energy efficiency: evidence from 281 cities in China

Zhao

Peng

Wen

et al. 2022

Environ Sci Pollut Res

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Although the digital economy has become a new driving force for development worldwide, it is still unclear how digital economy development affects green total factor energy efficiency (GTFEE). Using panel data from 281 prefecture-level cities in China from 2003 to 2018, this study empirically analyzes the effect of digital economy development on GTFEE by adopting a dynamic panel model, a mediation effect model, a dynamic threshold panel model, and a spatial Durbin model. The empirical results show that digital economy development has a significantly negative direct effect on GTFEE. The digital economy can impact GTFEE by the mechanisms of electrification, hollowing out of industrial scale, and hollowing out of industrial efficiency. Neither innovation nor environmental regulations significantly change this negative impact. The dynamic threshold panel model shows a nonlinear relationship between digital economy development and GTFEE, which indicates that the effect of digital economy development on GTFEE significantly inverts from negative to positive as the digital economy develops. In addition, GTFEE has a significantly positive spatial correlation, and the digital economy has a positive spatial spillover effect on GTFEE.

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Section: Estimation Results For the Dynamic Panel Modelmentioning

confidence: 99%

Nonlinear and spatial spillover effects of the digital economy on green total factor energy efficiency: evidence from 281 cities in China

Zhao

Peng

Wen

et al. 2022

Environ Sci Pollut Res

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“…The coefficient of the production scale is positive and significant. The more resources an enterprise has, the more likely it is to overcome the iceberg costs required for international market development (Zheng et al, 2022). More importantly, the production scale is the most critical factor hindering SME internationalization; thus, the corporate scale significantly impacts internationalization.…”

Section: Empirical Results and Analysismentioning

confidence: 99%

“…The competitiveness of SMEs has always been an important issue in the field of management (Piperopoulos & Scase, 2009; Schaefer et al, 2023), and in the era of economic globalization, the competitiveness of SMEs is oriented toward the international market (Bilali, 2022). The international competitiveness of a company refers to its superior performance in market share, export trade, and financial performance compared to its competitors in international business operations (Moen & Servais, 2002; Peña-Vinces et al, 2017) or its ability to adapt to changes in the international market (Zheng et al, 2022). The development of digital technology has led to the increasing integration of SMEs into the global industrial division of the labor system (Zhou et al, 2022), and the international competitiveness of SMEs is an essential driving force for economic growth and residents’ well-being in developing countries (Cravo et al, 2012).…”

Section: Background and Theoretical Analysismentioning

confidence: 99%

Promoting the International Competitiveness of Small and Medium-Sized Enterprises Through Cross-Border E-Commerce Development

Wen,

Liu,

Zhou

2023

SAGE Open

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Based on 14,020 observations of Chinese A-share listed SMEs from 2007 to 2021, this study uses the difference-in-differences (DID) model to investigate the impact of cross-border e-commerce on enterprises’ international competitiveness. The results show that the comprehensive pilot zone of cross-border e-commerce significantly promotes SMEs’ overseas business income of SMEs, indicating that cross-border e-commerce is a powerful tool for improving corporate international competitiveness. In addition, the total factor productivity (TFP) of SMEs has been significantly improved in the process of expanding overseas markets. The triple DID model shows that the pilot policies of cross-border e-commerce significantly promoted the TFP of international enterprises, which means that cross-border e-commerce is conducive to improving international competitiveness. This study also verifies the market information mechanism of cross-border e-commerce, which enables SMEs to improve their international competitiveness. Developing and emerging countries should accelerate the institutional reform of digital trade to facilitate SME internationalization.

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“…According to the new structural economic theory, technological progress that violates the advantage of factor endowment may reduce economic and environmental performances. 62,63 This means that if a city has scarce human resources and while it is strongly developing a labor-biased digital economy (such as the sharing economy) to achieve digital transformation, then the cost of developing the sharing economy cannot be effectively shared due to the lack of human resources, which inevitably reduces the positive economic and environmental performances generated by digitalization. The reverse is also true; if a city is a labor-abundant region, then it is not wise to drive a capital-biased digital transformation.…”

Section: Theoretical Mechanisms and Hypotheses’ Developmentmentioning

confidence: 99%

The impact of digitalization on green economic efficiency: Empirical evidence from city-level panel data in China

Wen

2022

Energy & Environment

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The digital transformation of global economic and social activities brought about by advanced information and communication technology (ICT) may have a profound impact on sustainable economic development. This research measures the digitalization of the economy and society in cities of China based on Internet-related indicators and digital financial development and investigates the economic and environmental effects of their digitalization. The empirical results show that digitalization has significantly improved green economic efficiency (GEE), and this finding remains valid after a series of robust analyses. However, there is regional heterogeneity in the improvement effect of GEE. The green effect of digitalization is significant only in the cities with a high degree of economic servitization, capital-abundant cities, and eastern cities. Although digitalization has promoted the green development of the urban economy, it also has a negative spatial spillover effect on the GEE of neighboring cities. One explanation is that cities are shifting polluting industries to other areas during the process of digital transformation.

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The Relationship between Trade Liberalization and Environmental Pollution across Enterprises with Different Levels of Viability in China

Cited by 28 publications

References 37 publications

Nonlinear and spatial spillover effects of the digital economy on green total factor energy efficiency: evidence from 281 cities in China

Nonlinear and spatial spillover effects of the digital economy on green total factor energy efficiency: evidence from 281 cities in China

Promoting the International Competitiveness of Small and Medium-Sized Enterprises Through Cross-Border E-Commerce Development

The impact of digitalization on green economic efficiency: Empirical evidence from city-level panel data in China

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