A Blockchain-based Framework for Secure and Transparent ESG Certification = 안전하고 투명한 ESG 인증을 위한 블록체인 기반 프레임워크

국문 초록 (Abstract)

환경(Environmental), 사회(Social), 지배구조(Governance)로 구성되는 ESG 보고는 규 제 강화와 지속가능성을 요구하는 소비자 증가로 인해 전 세계 기업의 최우선 과제가 되었다. 그러나 현재 널리 사용되는 ESG 인증 방식은 일관성이 부족하며, 검증 가능성 (auditability) 측면에서도 충분히 신뢰할 수 있는 구조를 제공하지 못하고 있다. 본 논 문은 스마트컨트랙트, 역할 기반 접근통제, 그리고 암호화된 프라이빗 데이터 컬렉션 을 결합하여 투명성과 기밀성을 동시에 충족하는 블록체인 기반 ESG 인증 시스템을 제안한다. 본 연구는 화장품 리퍼비시 분야를 주요 사례로 다루지만, 제안된 구조는 더 넓은 지속가능성 산업 전반으로 확장이 가능한 특징을 가진다. 본 시스템은 ESG 평가 를 정형화된 인증 절차로 체계화한다. 기업은 환경, 사회, 지배구조 요소에 대한 데이 터를 제출하고, 해당 데이터는 체인코드에 정의된 기준(임계값)에 따라 평가된다. 그 결과(인증 통과 또는 실패)는 허가형 블록체인에 기록되어 재현 가능성과 추적 가능성 을 확보한다. 이 과정에서 배출량 비율, 근로자 준수 정보 등 민감한 데이터는 감사인· 규제기관·소비자 등 이해관계자의 권한 수준에 따라 선택적으로 공유된다. 평가 시스 템은 Hyperledger Fabric v2.5.0 기반으로 구현되었으며, 스마트컨트랙트는 Go 언어로 작성되었다. 실제 및 대표 화장품 기업(아모레퍼시픽, 이니스프리 등)의 ESG 보고서 78 건을 데이터셋으로 사용하여 실험을 수행하였다. 분석 결과, 75.6%의 보고서는 인증 기준을 충족하였으나, 24.4%는 환경·사회·거버넌스 여러 측면에서의 복합적 미흡으로 인해 인증에 실패하였다. 이는 ESG 실패가 단일 요인보다는 다차원적인 결함이 동시 에 발생하는 경향이 있음을 보여준다. 블록체인은 제출 이후의 데이터 무결성과 인증 결과의 신뢰성을 보장하지만, 제출 이전 단계(pre-chain)에서 입력되는 정보의 정확성 과 진실성은 감사인의 검증에 의존한다는 점 또한 중요하다. 본 논문의 주요 기여점은 다음과 같다. (1) 블록체인을 활용하여 ESG 인증 결과의 추적 가능성과 감사 가능성을 보장하는 프레임워크를 제시하였으며, (2) Hyperledger Fabric의 역할 기반 접근 제어 와 프라이빗 데이터 컬렉션을 활용한 조건부 프라이버시 보호 모델을 구현하였다. (3) 환경·사회·지배구조 전 영역을 포괄하는 정형화된 ESG 인증 논리를 제안하여 데이터 를 일관된 기준에 따라 평가할 수 있도록 하였고, (4) 실제 및 대표 화장품 기업의 ESG 데이터를 활용한 시뮬레이션을 통해 시스템의 적용 가능성과 확장성을 검증하였다. 본 연구는 화장품 리퍼브 산업을 중심으로 출발하였으나, 제안된 구조는 다양한 산업 분 야로 확장 가능하며 투명하고 책임성 있는 ESG 인증 생태계 구축에 기여할 수 있다.

다국어 초록 (Multilingual Abstract)

Environmental, Social, and Governance (ESG) reporting has become a top priority worldwide as companies are under increasing pressure from regulations and a growing demand from consumers for sustainable practices. The prevalent methodology of ESG certifications is currently inconsistent and not necessarily audit-proof. This thesis describes a blockchain-enabled ESG certification system that incorporates smart contracts, role-based management access, and encrypted private data sets to meet both transparency and confidentiality demands. As much as this work targets ESG certifications within the cosmetics industry, it can prove to be adaptable across sectors within the wider sustainability ecosystem. The proposed system institutionalizes ESG analysis into a formalized certification process. This is whereby organizations supply information on their environmental, social, and governance aspects, which are assessed against specific thresholds contained within chaincode. The results, whether certified to comply or fail to comply, are recorded on a permissioned blockchain, such that results can be rebuilt and traced to enhance auditability. This is while specific information like emissions ratios and workers’ compliance is shareable only on the basis of stakeholders like auditors, regulators, and consumers. The evaluation is implemented on Hyperledger Fabric v2.5.0, with smart contracts written in Go, and using a dataset consisting of 78 ESG reports pertaining to actual and representative cosmetic brands such as Amorepacific and Innisfree. The results show that 75.6% of ESG reports meet certified requirements, while 24.4% fail to comply because of flaws across multiple ESG aspects. This is particularly true because failure is seldom an isolated incident and may involve flaws within environmental aspects. Though blockchain technology is responsible for ESG certificate integrity after being submitted, this system relies on auditors to endorse both the precision and trustworthiness of information being inputted into this technology. The importance and value added by this thesis relate to: (1) ESG certificate issuance via this blockchain technology, which is traceable and can be certified to the true and correct, (2) designing a privacy paradigm within this ESG project utilizing Hyperledger Fabric’s private data collections, (3) deriving a comprehensive ESG formalized certificate logic that encompasses each ESG domain, and finally (4) analytical approaches to track ESG dynamics over time.

목차 (Table of Contents)

• Chapter 1. Introduction 1
• 1.1 Background and Motivation 1
• 1.2 Problem Statement 3
• 1.3 Research Objectives 4
• 1.4 Research Contributions 6
• 1.4.1 Classification of ESG Data Sensitivity in Cosmetic Refurbishment 7
• 1.4.2 Conditional Privacy in Blockchain-based ESG Certification 8
• 1.4.3 Holistic ESG certification logic encoded in Chaincode 9
• 1.4.4 Blockchain Framework for Cosmetic Refurbishment Certification 9
• 1.4.5 ESG Performance Monitoring and Benchmarking Methods 10
• 1.4.6 Generalizable Model for the Global Sustainability Ecosystem 11
• 1.4.7 Summary of Contributions 11
• 1.5 Research Questions 14
• 1.6 Structure of the Thesis 15
• Chapter 2. Literature Review of Core System Components 18
• 2.1 Literature Review 18
• 2.2 ESG Reporting and Certification Practices 19
• 2.3 ESG in the Cosmetic Industry 22
• 2.3.1 Case Example: Amorepacific (South Korea) 25
• 2.3.2 Korea ESG Guidelines and Cosmetic Standardization 26
• 2.3.3 Alignment with ESG Standards (K-ESG, MOTIE, KISA, GRI) 27
• 2.4 Blockchain for ESG Reporting 28
• 2.5 Related Works 31
• 2.5.1 Blockchain in Environmental Certification 31
• 2.5.2 Blockchain in Social and Labor Audits 32
• 2.5.3 Governance and Corporate Reporting 33
• 2.5.4 Integrated ESG Approaches 34
• 2.5.5 Limitations in Current Literature 35
• 2.5.6 Positioning of This Research 36
• 2.5.7 Comparative Summary 36
• 2.6 Summary of Literature Review 39
• Chapter 3. System Design for Conditional ESG Certification 43
• 3.1 Proposed Model Overview 43
• 3.2 Role-Based Data Visibility Matrix 48
• 3.3 Privacy-Preserving Mechanism in the Proposed Framework 51
• 3.4 Transaction Sequence (Evaluate & Create) 52
• 3.5 Chaincode Logic for ESG Certification 56
• 3.5.1 Determinism and Auditability 58
• 3.5.2 Computational Complexity 59
• 3.6 Chaincode Design & Integration 60
• 3.6.1 Contract Interfaces 61
• 3.6.2 Data Model 63
• 3.6.3 Certification Logic (Deterministic) 66
• 3.6.4 Access Control & Endorsement 68
• 3.6.5 Transaction Flow (End – to – End) 71
• 3.6.6 Error Handling & Idempotency 75
• 3.6.7 Integration with Network Services 77
• 3.7 System Integration Overview 80
• 3.8 Data Sensitivity and Access Control 81
• 3.9 Generalization and Cross-Industry Applicability 83
• 3.10 System Integration Summary 85
• Chapter 4. Certification Logic and Algorithmic Validation 87
• 4.1 Introduction to Certification Logic 87
• 4.2 ESG Criteria & Threshold Model 88
• 4.2.1 Environmental (E) 90
• 4.2.2 Social (S) 92
• 4.2.3 Governance (G) 94
• 4.2.4 Certification decision rule 96
• 4.2.5 Parameterization & Versioning (on-chain) 98
• 4.2.6 Edge cases & data quality 100
• 4.2.7 Extensibility (weighted model-optional) 101
• 4.3 Algorithmic Formalization of ESG Certification Logic 102
• 4.3.1 Notation and Inputs 102
• 4.3.2 Decision Procedure (Narrative) 103
• 4.3.3 ESG Certification Decision Process 107
• 4.4 Validation Strategies 109
• 4.5 System-Level Summary 111
• 4.6 Conclusion 112
• Chapter 5. System Implementation and Simulation 114
• 5.1 Implementation Environment Setup 114
• 5.2 Smart Contract Implementation 116
• 5.2.1 Overview of the Chaincode 116
• 5.2.2 Data Structure and Storage Model 117
• 5.2.3 Certification Logic 118
• 5.2.4 Auxiliary Functions and Public API 119
• 5.2.5 Role-Based Access (Design Note) 120
• 5.2.6 Mapping Logic to Process Flow 121
• 5.2.7 Performance & Storage Considerations 122
• 5.2.8 Summary of Smart Contract Design 126
• 5.3 Implementation Results 127
• 5.3.1 Querying ESG Records 128
• 5.3.2 Smart Contract Execution Flow 129
• 5.3.3 Transaction Validation and Endorsement Policy 131
• 5.3.4 Data Privacy and Confidentiality Mechanisms 133
• 5.3.5 Performance and Scalability Evaluation 137
• 5.3.6 Storage and Ledger Footprint Analysis 140
• 5.4 System Integration and Workflow Demonstration 144
• 5.5 Analysis of ESG Dataset 146
• 5.5.1 Certification Outcome Distribution 147
• 5.5.2 Certification Trends Over Time 149
• 5.5.3 Brand-Level Performance Analysis 152
• 5.5.4 ESG Dimension Failure Breakdown 155
• 5.5.5 ESG Dimension Contribution Analysis 157
• 5.5.6 Cross-Dimensional Failure Patterns 159
• 5.5.7 Cross-Dimensional Insights and Organizational Implications 162
• 5.6 Summary of Implementation and Analysis 167
• Chapter 6. Evaluation and Discussion 169
• 6.1 Reconnection to Research Questions 169
• 6.2 Interpretation of Results 171
• 6.3 Brand-Level Performance and Improvement Trends 174
• 6.4 ESG Dimension-Level Insights 175
• 6.5 Cross-Brand Comparisons 177
• 6.6 ESG Dimension-Specific Lessons 178
• 6.7 Limitations of the Proposed Framework 180
• Chapter 7. Conclusion 183
• 7.1 Contributions 183
• 7.2 Key Findings 184
• 7.3 Limitations 186
• 7.4 Future Work 189
• Bibliography 192
• Acknowledgements 201
• Glossary 203
• Appendix 206