Factor Price Distortion, Technological Innovation Pattern and the Biased Technological Progress of Industry in China: An Empirical Analysis Based on Mediating Effect Model

2018 ◽  
pp. 247-275
Author(s):  
Xuejie Bai ◽  
Shuang Li
Keyword(s):  
Empirical Analysis ◽  
Technological Innovation ◽  
Technological Progress ◽  
Mediating Effect ◽  
Factor Price ◽  
Price Distortion ◽  
Effect Model

scholarly journals The Mechanism And Effects of National Smart City Pilots In China On Environmental Pollution: Empirical Evidence Based On A DID Model

2021 ◽  
Author(s):  
Guoxiang Xu ◽  
Zhijiu Yang
Keyword(s):  
Water Pollution ◽  
Environmental Pollution ◽  
Technological Innovation ◽  
Smart City ◽  
Mediating Effect ◽  
Allocation Efficiency ◽  
Mediating Role ◽  
Effect Model ◽  
Fiscal Support ◽  
Reduction Effect

Abstract The policy of the national smart city (NSC) pilots, a new type of urbanization for future development, has been implemented in China in batches. This paper investigates the mechanism and effects of the NSC pilots on the environment. Using the prefecture-level panel data during 2004-2018 period, our dynamic difference-in-differences (DID) estimation shows that the NSC pilots causally mitigate air (water) pollution by 21.5% (23.3%). The mediating effect model indicates that the allocation efficiency and technological innovation play a partial mediating role in the impacting mechanism. After introducing the two mediating channels into the dynamic DID model, the reduction effect for air (water) pollution drops to 15.5% (17.3%). Comparatively, improving allocation efficiency instead of technological innovation takes the major mediating role in reducing air pollution, while water pollution the opposite. The result of city heterogeneity shows that cities with high human capital and fiscal support contribute to the reduction of environmental pollution. This study also provides some related policy suggestions by analyzing the initial mechanism and city heterogeneity of the NSC pilots.

scholarly journals Impact of Energy Price Distortion on Green TFP Based on Spatial Econometric Model

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Huayu Guan ◽  
Mengyue Xing
Keyword(s):  
Energy Conservation ◽  
Environmental Protection ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Mediating Effect ◽  
Factor Price ◽  
Energy Price ◽  
Factor Productivity ◽  
Price Distortion ◽  
The Impact

With environmental regulation as the intermediary, this paper studies the influence mechanism and mediating effect of energy price distortion on green total factor productivity. On the basis of the panel data of 30 provinces in China (except Tibet, Hong Kong, Macao, and Taiwan), the research results from the study of panel and spatial metrology show that energy price distortion has a significant negative effect on the improvement of green total factor productivity. Different environmental regulation tools have different impacts, and the impact effect of fiscal energy conservation and environmental protection expenditure is better than that of pollution punishment. The transmission effect of energy price on environmental regulation policies is different when environmental regulation is the intermediary. The increase of the degree of energy price distortion will increase the financial expenditure of energy conservation and environmental protection, while the energy factor price will increase the green total factor productivity with the increase of pollution punishment.

scholarly journals The Influencing Mechanism of Internal Control Effectiveness on Technological Innovation: CSR as a Mediator

2021 ◽  
Vol 13 (23) ◽  
pp. 13122
Author(s):  
Xinyuan Wang ◽  
Zhenyang Zhang ◽  
Dongphil Chun
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Technological Innovation ◽  
Internal Control ◽  
Listed Companies ◽  
Mediating Effect ◽  
Mediating Role ◽  
Control Effectiveness ◽  
Effect Model ◽  
Corporate Social

The study explores the relationship between internal control effectiveness, corporate social responsibility (CSR), and technological innovation. By establishing a mediating effect model, we analyzed the effect of internal control effectiveness on technological innovation. The study selected the data of Chinese A-share listed companies between 2014 and 2019 as the sample. The sources of variable indicators include China Stock Market and Accounting Research (CSMAR), DIB Internal Control database, and Hexun CSR score. The empirical study shows that internal control effectiveness is significantly and positively related to technological innovation. Enhancing internal control effectiveness has a significant positive effect on the fulfillment of corporate social responsibility. In the process of internal control effectiveness on technological innovation, corporate social responsibility functions as a mediating variable and plays a partial mediating role. The study provides empirical data to support listed companies’ emphasis on internal control and active fulfillment of social responsibility, thereby enhancing their technological innovation performance.

scholarly journals The Impact of Stable Customer Relationships on Enterprises’ Technological Innovation Based on the Mediating Effect of the Competitive Advantage of Enterprises

2021 ◽  
Vol 13 (7) ◽  
pp. 3610
Author(s):  
Yan Chen ◽  
Yingying Xin ◽  
Zhengying Luo ◽  
Min Han
Keyword(s):  
Competitive Advantage ◽  
Technological Innovation ◽  
Large Scale ◽  
Customer Relationships ◽  
Mediating Effect ◽  
Small Scale ◽  
Manufacturing Companies ◽  
Effect Model ◽  
The Impact ◽  
Capital Intensive

Technological innovation and stable customer relationships are both important factors for the sustainable development of enterprises. However, it remains unclear whether there is a relationship between stable customer relationships and technological innovation. In this work, we manually collected data regarding customer relationships and the innovation of manufacturing companies listed in the A-Share index in China from 2009 to 2016. Through empirical analysis, this work used a two-way fixed effect model and intermediary effect model tests to explore the impact of stable customer relationships on technological innovation. The empirical research found the following. (1) Stable customer relationships significantly promote the technological innovation of enterprises, and the empirical results are still valid after a variety of robust tests. The competitive advantage of enterprises forms a part of the intermediary role in the relationship above. (2) Comparing the samples of large-scale enterprises, state-owned enterprises, mature enterprises, and low-capital-intensive enterprises, the research found that stable customer relationships can significantly promote corporate technological innovation in small-scale enterprises, non-state-owned enterprises, young enterprises, and highly capital-intensive enterprises. This article enriches and deepens our understanding of the mechanism by which stable customer relationships affect enterprises’ technological innovation. At the same time, this research is helpful for better evaluating the impact of establishing a stable customer relationship on the sustainable competitive advantage of enterprises.

scholarly journals The Influence of Urban Sprawl on Air Pollution and the Mediating Effect of Vehicle Ownership

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1261
Author(s):  
Aiping Tao ◽  
Qun Liang ◽  
Peng Kuai ◽  
Tao Ding
Keyword(s):  
Air Pollution ◽  
Urban Sprawl ◽  
Negative Impact ◽  
Empirical Support ◽  
Mediating Effect ◽  
Vehicle Ownership ◽  
Mediating Role ◽  
Effect Model ◽  
Significant Negative Impact ◽  
The Impact

Based on the panel data of 224 prefecture-level and above cities in China from 2003 to 2016, this paper empirically studies the impact of urban sprawl on air pollution and introduces a mediating effect model to test the mediating role of vehicle ownership concerning the impact of urban sprawl on air pollution. The research in this paper arrives at three conclusions. First, urban sprawl has a significant positive effect on air pollution, and this conclusion is still valid after solving the endogeneity problem and conducting a robustness test. Second, the results of mediating effect test show that urban sprawl indirectly affects air pollution through the partial mediating effect of vehicle ownership. By removing the mediating effect, urban sprawl has a significant negative impact on air pollution, indicating that the mediating effect of vehicle ownership is higher concerning the impact of urban sprawl on air pollution. Third, further panel quantile regression results show that the higher the level of air pollution, the weaker the mediating effect of vehicle ownership and the stronger the direct effect of urban sprawl on air pollution. These conclusions can provide some empirical support for solving the air pollution problems caused by urban sprawl in China.

Big data analytics capabilities and organizational performance: the mediating effect of dual innovations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaofeng Su ◽  
Weipeng Zeng ◽  
Manhua Zheng ◽  
Xiaoli Jiang ◽  
Wenhe Lin ◽  
...  
Keyword(s):  
Big Data ◽  
Organizational Performance ◽  
Empirical Analysis ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Mediating Effect ◽  
Content Type ◽  
Mediating Role ◽  
The Relationship

PurposeFollowing the rapid expansion of data volume, velocity and variety, techniques and technologies, big data analytics have achieved substantial development and a surge of companies make investments in big data. Academics and practitioners have been considering the mechanism through which big data analytics capabilities can transform into their improved organizational performance. This paper aims to examine how big data analytics capabilities influence organizational performance through the mediating role of dual innovations.Design/methodology/approachDrawing on the resource-based view and recent literature on big data analytics, this paper aims to examine the direct effects of big data analytics capabilities (BDAC) on organizational performance, as well as the mediating role of dual innovations on the relationship between (BDAC) and organizational performance. The study extends existing research by making a distinction of BDACs' effect on their outcomes and proposing that BDACs help organizations to generate insights that can help strengthen their dual innovations, which in turn have a positive impact on organizational performance. To test our proposed research model, this study conducts empirical analysis based on questionnaire-base survey data collected from 309 respondents working in Chinese manufacturing firms.FindingsThe results support the proposed hypotheses regarding the direct and indirect effect that BDACs have on organizational performance. Specifically, this paper finds that dual innovations positively mediate BDACs' effect on organizational performance.Originality/valueThe conclusions on the relationship between big data analytics capabilities and organizational performance in previous research are controversial due to lack of theoretical foundation and empirical testing. This study resolves the issue by provides empirical analysis, which makes the research conclusions more scientific and credible. In addition, previous literature mainly focused on BDACs' direct impact on organizational performance without making a distinction of BDAC's three dimensions. This study contributes to the literature by thoroughly introducing the notions of BDAC's three core constituents and fully analyzing their relationships with organizational performance. What's more, empirical research on the mechanism of big data analytics' influence on organizational performance is still at a rudimentary stage. The authors address this critical gap by exploring the mediation of dual innovations in the relationship through survey-based research. The research conclusions of this paper provide new perspective for understanding the impact of big data analytics capabilities on organizational performance, and enrich the theoretical research connotation of big data analysis capabilities and dual innovation behavior.

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