文本挖掘在企业社会责任报告分析中的应用——以石化行业为例

Sheng-Hung Liu, Sih-Yu Chen, Sheng-Tun Li
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引用次数: 6

摘要

在过去的几年里,公司已经加强了责任和履行承诺的重要性。因此,传统的以财务报表和组织自身利益为中心的利益管理已经不能适应我们的社会。因此,企业社会责任(CSR)开始受到越来越多的重视。由于2014年高雄市管道爆炸事件和台湾地区食品安全问题,企业形象受到了不同程度的影响,受到了一定的负面影响。本研究通过文本挖掘确定全球报告倡议组织(Global Reporting Initiative, GRI)中环境绩效指标的基准,并为石油化工企业的企业社会责任报告提供学习的范例模型,为企业决策和战略规划提供有价值的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Text-Mining Application on CSR Report Analytics: A Study of Petrochemical Industry
For the past few years, corporations have reinforced the importance of responsibility and promise fulfillment. Hence, traditional benefit-based management that focused on financial statements and organizations own interests no longer suffices in our society. Therefore, Corporate Social Responsibility (CSR) is starting to be taken more seriously. Due to 2014 pipeline explosion in Kaohsiung City and the food safety problem in Taiwan, corporate images have been affected in various degrees and suffer from certain negative impacts. This study conducts text-mining to determine the benchmark of environment performance indicators defined in the Global Reporting Initiative (GRI) from Top 50 petrochemical industries, and advise an example model to learning for the petrochemical industrys CSR reports with valuable information to decide on decision making and strategy planning.
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