Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/1966DFC1-9769-4C98-AEFC-AD0BD6E7EEC9 | ||
| Year | 2024 | ||
| Type of Item | Master Thesis | ||
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| Bibliographic Citation | Christina Eleftheraki, "The role of business intelligence in the implementation of ESG principles", Master Thesis, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2024 https://doi.org/10.26233/heallink.tuc.101433 | ||
| Appears in Collections |
This postgraduate thesis explores the role of Business Intelligence (BI) systems in the implementation of ESG (Environmental, Social, Governance) principles in modern businesses. Given the increasing pressure for sustainable development and responsible governance, businesses are required to adopt and monitor ESG criteria, to achieve sustainability goals and comply with investor and regulatory requirements. The study focuses on the connection between Business Intelligence and ESG data, examining how modern technological tools can support decision-making and performance monitoring in the areas of environmental governance, social responsibility, and corporate governance.The thesis analyzes Business Intelligence systems, their architecture, and the benefits and limitations they present in the implementation of sustainability strategies. BI systems offer the capability to collect, analyze, and utilize Big Data, making them essential for measuring ESG indicators and optimizing business processes. At the same time, businesses can predict future trends and adjust their strategies in line with market and regulatory demands.Through examples of companies that have successfully implemented BI systems for managing ESG data, the study highlights best practices and the benefits of adopting these technologies. However, challenges such as the complexity of managing large volumes of data, information security, and the need for regulatory compliance are also addressed.Additionally, the role of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing ESG data analysis is examined, along with the contribution of Blockchain technology to the transparency and reliability of data. It is emphasized how these technologies can enhance the capabilities of BI systems, enabling the development of more reliable and transparent ESG management practices.Finally, the thesis focuses on the ethical and regulatory challenges associated with the use of ESG data, such as privacy protection and compliance with international standards and regulations. Overall, the research demonstrates that business intelligence and data analytics technologies are key factors in promoting sustainable development and corporate governance, offering significant benefits to businesses and society.
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