ESG Performance, Digital Capability, and Corporate Outcomes : Evidence from Firm Valuation and Green Innovation in Chinese A-Share Innovation Technology Companies = 중국 A-share 혁신기술기업의 ESG 성과, 디지털 역량 및 기업성과 : 기업가치와 녹색혁신에 관한 분석

다국어 초록 (Multilingual Abstract)

This dissertation examines how environmental, social, and governance performance, hereafter ESG performance, and firm-level digital capability are associated with firm valuation and green innovation among Chinese A-share innovation technology companies during the joint transition toward sustainability and digitalization. It addresses three questions. First, it asks whether ESG performance is associated with firm value. Second, it examines whether ESG performance is associated with green invention output through a pattern consistent with internal resource allocation. Third, it evaluates whether digital capability conditions ESG–outcome associations in valuation and innovation settings. Study I estimates the ESG–valuation relationship using a 2012–2022 sample of 165 Chinese A-share innovation technology companies and 1,652 firm-year observations. Tobin’s Q is the valuation outcome, and the Digital Capability Gauge, abbreviated DCG, is the Study I digital-capability proxy. Study II analyzes listed FinTech firms over 2010–2020 as a digital-finance-oriented subcategory of Chinese A-share innovation technology companies. It measures green innovation through green invention patent applications and uses logged R＆D expenditure, abbreviated RDexp, and logged digital-transformation intensity, abbreviated lnDIG, to examine channel-consistency and digital-capability moderation. DCG and lnDIG are retained as study-specific proxies for the same umbrella construct rather than interchangeable measurements. Under firm and year two-way fixed effects with cluster-robust standard errors, Study I reports that ESG performance exhibits a positive and statistically significant association with Tobin’s Q, providing support for H1 within the broad innovation technology company sample. The ESG–Tobin’s Q slope is materially stronger among firms with higher digital capability, consistent with H2. In Study II, the FinTech subcategory evidence indicates that ESG is positively associated with green invention patent applications, RDexp provides evidence consistent with an internal resource-allocation channel, and the ESG–green innovation association is stronger when lnDIG is higher. The two studies jointly support an association-based ESG–digital capability complementarity within China’s A-share innovation technology setting, while preserving explicit boundaries around causality, proxy comparability, sample scope, and external validity.

국문 초록 (Abstract)

본 논문은 지속가능성과 디지털화가 동시에 진전되는 환경에서 중국 A-share 혁신기술기업의 환경·사회·지배구조（ESG） 성과와 기업 수준의 디지털 역량이 기업가치 및 녹색혁신과 어떠한 관련성을 갖는지를 분석한다. 본 연구는 세 가지 질문을 다룬다. 첫째, ESG 성과는 기업가치와 관련되는가. 둘째, ESG 성과는 내부 자원배분과 일치하는 양상을 통해 녹색 발명 성과와 관련되는가. 셋째, 디지털 역량은 기업가치와 혁신의 맥락에서 ESG 와 결과변수 간의 관계를 어떻게 달라지게 하는가.
Study I 은 2012 년부터 2022 년까지의 중국 A-share 혁신기술기업 165 개사, 1,652 개 기업-연도 관측치를 사용하여 ESG 와 기업가치의 관계를 추정한다. 기업가치 결과변수는 Tobin’s Q 이며, Study I 의 디지털 역량 대리변수는 DCG 이다. Study II 는 2010 년부터 2020 년까지의 상장 FinTech 기업을 중국 A-share 혁신기술기업 안의 디지털 금융 중심 하위 범주로 분석한다. 녹색혁신은 녹색 발명 특허출원으로 측정하며, RDexp 와 lnDIG 는 각각 자원배분 경로와 디지털 역량 조절효과를 검토하는 데 사용한다. DCG 와 lnDIG 는 동일한 상위 개념인 디지털 역량에 대한 연구별 대리변수이므로 상호 대체 가능한 동일 측정치로 해석하지 않는다.
기업 및 연도 이원 고정효과와 클러스터-강건 표준오차를 적용한 결과, Study I 에서는 ESG 성과가 Tobin’s Q 와 정（+）의 통계적으로 유의한 관련성을 보였으며, 이는 광범위한 혁신기술기업 표본에서 H1 을 지지한다. 또한 ESG–Tobin’s Q 기울기는 디지털 역량이 높은 기업에서 더 강하게 나타나 H2 와 일치한다.
Study II 의 FinTech 하위 범주 증거는 ESG 가 녹색 발명 특허출원과 정（+）의 관련성을 가지며, RDexp 가 내부 자원배분 경로와 일치하는 증거를 제공하고, lnDIG 가 높을수록 ESG 와 녹색혁신의 관련성이 더 강해짐을 보여준다. 두 연구는 중국 A-share 혁신기술 맥락에서 ESG 와 디지털 역량의 상호보완성이 존재함을 시사한다. 다만 본 논문은 인과성, 대리변수의 비교가능성, 표본 범위 및 외적 타당성의 한계를 명확히 구분하여 해석한다.

목차 (Table of Contents)

• Chapter 1. Introduction 9
• 1.1 Research Background and Motivation 9
• 1.1.1 ESG and Sustainable Finance in China’s A-Share Market 9
• 1.1.2 Digital Capability, Innovation Technology, and Digital Financial Infrastructure 10
• 1.1.3 Dual Pressures: Carbon Neutrality, Regulation and Digitalization 11
• 1.2 Research Questions and Objectives 13
• 1.3 Study Design and Empirical Roadmap 14
• 1.4 Contributions, Boundary Conditions, and Chapter Organization 17
• Chapter 2. Literature Review 20
• 2.1 ESG literature: concepts, measures, and firm outcomes 20
• 2.1.1 ESG constructs and measurement in capital markets 20
• 2.1.2 ESG and firm value / financing 21
• 2.1.3 ESG and innovation 24
• 2.2 Digital capability and innovation technology literature: definitions, domains and firm-level effects 25
• 2.2.1 What Counts as Digital Capability at the Firm Level 25
• 2.2.2 Digital capability and corporate outcomes 26
• 2.2.3 RegTech, governance, and risk 29
• 2.3 ESG × digital capability: synergy, disclosure quality, and innovation channels 30
• 2.3.1 How digital infrastructure enables ESG associations 30
• 2.3.2 Evidence on firm value under ESG × digital capability 31
• 2.3.3 Evidence on green innovation under ESG × digital capability 34
• 2.4 Methods used in prior work: identification and measurement 35
• 2.4.1 Designs and estimators 35
• 2.4.2 Outcome and Regressor Construction 36
• 2.5 Synthesis and targeted gaps 37
• 2.5.1 Evidence matrix 37
• 2.5.2 Existing Research Gaps 39
• 2.5.3 Synthesis for Hypothesis Development 41
• Chapter 3. Theoretical Framework and Hypotheses 44
• 3.1 Theoretical Foundations 44
• 3.1.1 Stakeholder and Legitimacy Views 44
• 3.1.2 Information Asymmetry and Agency Problems 45
• 3.1.3 Resource-Based View and Dynamic Capabilities 46
• 3.1.4 Sustainable Finance and Digital Infrastructure 46
• 3.2 Conceptual Model and Mechanisms 48
• 3.2.1 Information Transparency Pathway 50
• 3.2.2 Resource Allocation and R＆D Reorientation Pathway 51
• 3.2.3 Digital Capability as an Amplifier of ESG Associations 51
• 3.3 Hypotheses for Firm Value and Scope Boundary （Study I: H1-H2） 54
• H1: ESG and Firm Value 54
• Debt-Financing Channel as Scope Boundary 55
• H2: Digital Capability as a Moderator of Firm Value （Value） 56
• 3.4 Hypotheses for Green Innovation （Study II: H3-H5） 56
• H3: ESG and Green Innovation 57
• H4: Logged R＆D Expenditure as an Innovation Channel 57
• H5: Digital Capability as a Moderator （Innovation） 58
• 3.5 Measurement and Empirical Linkage 59
• 3.5.1 Operational Definitions of Core Variables 59
• 3.5.2 Mapping Hypotheses to Models and Outcomes 61
• Chapter 4. Empirical Study I: ESG, Digital Capability, and Firm Value 64
• 4.1 Introduction 64
• 4.2 Data, Sample, and Empirical Window 65
• 4.3 Variable Map and Baseline Models 68
• 4.4 Data Analysis and Results 74
• 4.4.1 Descriptive Statistics, Correlations, and Multicollinearity 74
• 4.4.2 Baseline Regression Results 78
• 4.4.3 Lagged and Dynamic Specifications 80
• 4.4.4 Digital Capability Moderation 82
• 4.5 Robustness Tests and Boundary Conditions 86
• 4.6 Heterogeneity Analysis 88
• 4.7 Endogeneity Boundary and Supplementary Sensitivity Evidence 90
• 4.8 Chapter Conclusion 91
• Chapter 5. Empirical Study II: ESG, Digital Capability and Green Innovation 93
• 5.1 Introduction 93
• 5.2 Data, Sample, and Variable Definitions 94
• 5.3 Data Analysis and Results 98
• 5.3.1 Descriptive Statistics and Correlation Analysis 98
• 5.3.2 Benchmark Regression Analysis 103
• 5.3.3 Analysis of Intermediate Channel-Consistency Evidence 104
• 5.3.4 Digital Capability Moderation Analysis 106
• 5.3.5 Robustness Testing 109
• 5.3.6 Heterogeneity Analysis 112
• 5.3.7 Endogeneity Boundary and Retained Evidence 113
• 5.4 Conclusion and Implications 116
• Chapter 6. Conclusion and Integrated Discussion 117
• 6.1 Purpose of the Conclusion and Reconnection to the Research Questions 118
• 6.1.1 Restatement of the research questions and the empirical scope 118
• 6.1.2 Alignment between hypotheses, models, and reported evidence 119
• 6.2 Summary of Empirical Findings Across the Two Studies 122
• 6.2.1 Key findings from Study I on firm value outcomes 122
• 6.2.2 Key findings from Study II on green innovation and the R＆D channel 123
• 6.2.3 Cross-study synthesis: context dependence, digital conditioning, and evidentiary boundaries 125
• 6.3 Implications of the ESG and Digital-Capability Evidence 126
• 6.3.1 Theoretical implications for ESG, digital capability, and corporate outcomes 126
• 6.3.2 Managerial implications for ESG execution, digital governance, and innovation management 128
• 6.3.3 Policy implications for disclosure, assurance, and digital infrastructure 131
• 6.4 Contributions and Closing Synthesis 134
• Chapter 7. Practical Extensions, Policy Relevance, Limitations, and Future Research 136
• 7.1 Practical Extensions and Applications 136
• 7.1.1 Implementation logic for ESG and digital-capability co-deployment in firms 136
• 7.1.2 Capital market relevance for investors 137
• 7.2 Policy Relevance in China’s Institutional Context 139
• 7.2.1 ESG disclosure and assurance related implications 139
• 7.2.2 Data governance and innovation technology oversight related implications 140
• 7.3 Limitations 141
• 7.3.1 Data, sample, and measurement constraints 141
• 7.3.2 Identification and generalizability constraints 143
• 7.4 Future Research 146
• 7.4.1 Stronger causal designs and mechanism tests 146
• 7.4.2 Extended outcomes, longer horizons, and cross-context comparisons 147
• 7.5 Conclusion 148
• References 150