ESG, Supply Chain, and Financial Dataset of Indonesian Consumer Goods Companies (2015–2024)

This dataset contains Environmental, Social, and Governance (ESG), supply chain management (SCM), and financial performance data from 12 publicly listed consumer goods companies in Indonesia covering the 2015–2024 period. The dataset was collected from the LSEG Refinitiv database and processed for research related to ESG performance, supply chain efficiency, and AI-driven analytical systems. Variables include ESG scores across environmental, social, and governance dimensions, operational supply chain metrics such as Cash Conversion Cycle (CCC), Days Sales Outstanding (DSO), Days Payables Outstanding (DPO), Average Inventory Days, Inventory Turnover, and financial indicators including ROA, profit margin, revenue, EBITDA, and total assets. The dataset was used to support correlation analysis, K-Means clustering, AI-generated ESG-SCM risk assessment, and interactive dashboard visualization within the research framework. This dataset is intended for academic research, ESG analytics, supply chain analysis, sustainability studies, and AI-driven business intelligence applications.本数据集涵盖2015年至2024年间印度尼西亚12家上市消费品公司的环境、社会及治理（Environmental, Social, and Governance, ESG）、供应链管理（Supply Chain Management, SCM）与财务绩效数据。 本数据集采集自伦敦证券交易所集团（LSEG）路孚特（Refinitiv）数据库，并经处理以支撑ESG绩效、供应链效率及人工智能驱动分析系统相关研究。数据集包含的变量涵盖多维度ESG评分、运营供应链指标（如现金转换周期（Cash Conversion Cycle, CCC）、应收账款周转天数（Days Sales Outstanding, DSO）、应付账款周转天数（Days Payables Outstanding, DPO）、平均库存天数、库存周转率），以及财务指标（如资产收益率（ROA）、利润率、营收、息税折旧摊销前利润（EBITDA）与总资产）。 本数据集曾用于支撑该研究框架内的相关性分析、K-Means聚类、人工智能生成的ESG-SCM风险评估，以及交互式仪表盘可视化工作。 本数据集适用于学术研究、ESG分析、供应链分析、可持续性研究及人工智能驱动的商业智能应用场景。