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    The Effect of Government Subsidies on Corporate Green Innovation : The Mediation of AI Focus

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    https://www.riss.kr/link?id=T17553630

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Against the backdrop of China's vigorous endeavors to accomplish the carbon peaking and carbon neutrality targets, this study selects Chinese listed manufacturing enterprises spanning from 2014 to 2023 as the research sample. By incorporating the viewpoints of internal drivers (such as artificial intelligence and total factor productivity) and external facilitators (government subsidies), which impact enterprises' green innovation performance, this research empirically probes into the mediating role of AI and the moderating influence of TFP. The research finds that government subsidies significantly boost enterprises' green innovation performance, and this effect is primarily mediated by AI technology implementation. The moderating effect of TFP demonstrates heterogeneity, it negatively adjusts the direct connection between government subsidies and green innovation, while positively moderating the association between AI application and green innovation. Nonetheless, the moderating effect of TFP on the relationship between government subsidies and improvements in AI capabilities is not significant. The research results provide a reference for policy design regarding the green transformation of the manufacturing industry, suggesting that the subsidy structure should be optimized to strengthen AI empowerment, and enterprises' TFP should be improved in a differentiated manner to enhance their technology conversion capability.
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    Against the backdrop of China's vigorous endeavors to accomplish the carbon peaking and carbon neutrality targets, this study selects Chinese listed manufacturing enterprises spanning from 2014 to 2023 as the research sample. By incorporating the view...

    Against the backdrop of China's vigorous endeavors to accomplish the carbon peaking and carbon neutrality targets, this study selects Chinese listed manufacturing enterprises spanning from 2014 to 2023 as the research sample. By incorporating the viewpoints of internal drivers (such as artificial intelligence and total factor productivity) and external facilitators (government subsidies), which impact enterprises' green innovation performance, this research empirically probes into the mediating role of AI and the moderating influence of TFP. The research finds that government subsidies significantly boost enterprises' green innovation performance, and this effect is primarily mediated by AI technology implementation. The moderating effect of TFP demonstrates heterogeneity, it negatively adjusts the direct connection between government subsidies and green innovation, while positively moderating the association between AI application and green innovation. Nonetheless, the moderating effect of TFP on the relationship between government subsidies and improvements in AI capabilities is not significant. The research results provide a reference for policy design regarding the green transformation of the manufacturing industry, suggesting that the subsidy structure should be optimized to strengthen AI empowerment, and enterprises' TFP should be improved in a differentiated manner to enhance their technology conversion capability.

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    목차 (Table of Contents)

    • CHAPTER 1 Introduction 1
    • 1.1 Research background 1
    • 1.2 Research Objectives 6
    • 1.3 Research Significance 8
    • CHAPTER 2 Literature review 11
    • CHAPTER 1 Introduction 1
    • 1.1 Research background 1
    • 1.2 Research Objectives 6
    • 1.3 Research Significance 8
    • CHAPTER 2 Literature review 11
    • 2.1 Resource-Based View 11
    • 2.2 Dynamic Capabilities View 13
    • 2.3 Absorptive Capacity Theory 16
    • 2.4 Government subsidies 19
    • 2.5 Green innovation 23
    • 2.6 AI Focus 26
    • 2.7 Total Factor Productivity 29
    • CHAPTER 3 Hypothesis Development 33
    • 3.1Government Subsidies and Green Innovation Performance 33
    • 3.2 Government Subsidies, AI, and Green Innovation Performance 36
    • 3.3 The Moderating Effect of Total Factor Productivity 38
    • CHAPTER 4 Data and Methodology 44
    • 4.1 Data and Sampling 44
    • 4.2 Variable definition 45
    • 1) Dependent variable 45
    • 2) Independent variable 45
    • 3) Moderator variables 46
    • 4) Mediator variable 46
    • 5) Control variables 47
    • 4.3 Model Specification 49
    • Chapter 5 Empirical Results 51
    • 5.1 Descriptive Statistics 51
    • 5.2 Main Effect Regression Analysis 54
    • 5.3 Mediating Effect Regression Analysis 54
    • 5.4 Moderating Effect Regression Analysis 57
    • 5.5 Robustness test 61
    • Chapter 6 Discussion 66
    • 6.1 General Discussion 66
    • 6.2 Implication 68
    • 6.3 Limitations and Further works 69
    • References 71
    • 국문 초록 91
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