A Data-Driven Approach to Evaluation of Sustainability Reporting Practices in Extractive Industries

被引:13
|
作者
Perdeli Demirkan, Cansu [1 ]
Smith, Nicole M. [1 ]
Duzgun, H. Sebnem [1 ]
Waclawski, Aurora [2 ]
机构
[1] Colorado Sch Mines, Min Engn Dept, Golden, CO 80401 USA
[2] Colorado Sch Mines, Civil & Environm Engn Dept, Golden, CO 80401 USA
关键词
sustainability reporting; extractive industries; sustainability indicators; data-driven approach; content analysis; sustainable development; design for sustainability; CORPORATE SOCIAL-RESPONSIBILITY; MINING-INDUSTRY; GAS; OIL; INDICATORS; INNOVATION; FRAMEWORK; BUSINESS;
D O I
10.3390/su13168716
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Sustainability reporting is one of the tools that contribute to incorporating sustainable development in the design of extractive operations (i.e., "Design for Sustainability"), and the demand for sustainability reports is increasing due to the increased focus on sustainable development and sustainable financing efforts. The extractive industries are believed to have unique strengths to contribute to achieving the Sustainable Development Goals. Nonetheless, companies are expected to be transparent and accountable not only to investors but to all stakeholders, including communities, suppliers, clients, employees, and governments. Therefore, extractive industries require effective sustainability accounting and reporting to transition and contribute to sustainable development. Through a data-driven approach, this paper examines the scope and consistency of sustainability indicators used in the sustainability reports of eight oil and gas and eight mining companies from 2012 to 2018. Through content analysis and relevant statistical methods, we analyze the ways in which companies reported on their contributions to sustainable development, with a focus on indicators used and trends over time both within each industry and between industries. We demonstrate that extractive industries' sustainability reporting practices are not consistent over time and that internal issues are better represented than external issues, in particular transportation and supply chain issues. Furthermore, while there are similar trends across the industries in terms of social and environmental indicator reporting, there are significant differences in economic reporting. We conclude that although both industries have established sustainability reporting practices, there are trends that demonstrate what companies are focusing on more, as well as areas for improvement. We see this as an initial step for conceptualizing how these industries can more objectively, consistently, and effectively assess and contribute to sustainable development.
引用
收藏
页数:37
相关论文
共 50 条
  • [21] Data-driven integrated design of solvents and extractive distillation processes
    Wang, Zihao
    Zhou, Teng
    Sundmacher, Kai
    AICHE JOURNAL, 2023, 69 (12)
  • [22] Accident Data-Driven Consequence Analysis in Maritime Industries
    Shi, Jiahui
    Liu, Zhengjiang
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2025, 13 (01)
  • [23] Data-driven Causal Association Discovery in Manufacturing Industries
    Li, Yiming
    Xu, Jia
    Li, Li
    Iung, Benoit
    2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 5566 - 5571
  • [24] A Data-Driven and Probabilistic Approach to Residual Evaluation for Fault Diagnosis
    Svard, Carl
    Nyberg, Mattias
    Frisk, Erik
    Krysander, Mattias
    2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC), 2011, : 95 - 102
  • [25] DATA-DRIVEN APPROACH FOR QUALITY EVALUATION ON KNOWLEDGE SHARING PLATFORM
    Xu, Lu
    Xiang, Jinhai
    Wang, Yating
    Ni, Fuchuan
    PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), 2019, : 649 - 654
  • [26] Data-driven approach to dynamic reliability evaluation of SOA applications
    Wang, Lijun
    Bai, Xiaoying
    Chen, Yinong
    Zhou, Lizhu
    Liu, Rujuan
    Qinghua Daxue Xuebao/Journal of Tsinghua University, 2009, 49 (10): : 1729 - 1732
  • [27] How to improve a technology evaluation model: A data-driven approach
    Noh, Heeyong
    Seo, Ju-Hwan
    Yoo, Hyoung Sun
    Lee, Sungjoo
    TECHNOVATION, 2018, 72-73 : 1 - 12
  • [28] Innovation: A data-driven approach
    Kusiak, Andrew
    INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2009, 122 (01) : 440 - 448
  • [29] Approach to data-driven learning
    Markov, Z.
    International Workshop on Fundamentals of Artificial Intelligence Research, 1991,
  • [30] AN APPROACH TO DATA-DRIVEN LEARNING
    MARKOV, Z
    LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, 1991, 535 : 127 - 140