Evaluating Sustainability Reporting in the Leather Tanning Supply Chain: a NLP approach

In recent years, sustainability has become a critical focus for industries worldwide, and the leather tanning sector is no exception. This study presents a comprehensive sustainability analysis of the leather tanning supply chain, examining the alignment and discrepancies among sustainability reports issued by various stakeholders within the industry. By adopting advanced Natural Language Processing (NLP) techniques, we systematically analyze sustainability reports that were collected from the websites of different companies involved in the leather tanning process. Our research aims to identify the coherence of sustainability information across the supply chain, highlighting areas of consistency as well as divergence. The NLP methodology enables a detailed and nuanced analysis of the textual data contained in these reports, providing deeper insights into the sustainability practices and communications of the industry. The findings of this study offer several advantages. Firstly, they provide a clear picture of the current state of sustainability reporting in the leather tanning industry, identifying best practices and areas needing improvement. Secondly, the study fosters greater transparency and accountability among industry players by exposing inconsistencies in sustainability communication. Finally, by pinpointing alignment or misalignment in sustainability practices, the research supports stakeholders in making informed decisions, driving industry-wide improvements, and fostering a more sustainable leather tanning supply chain. This study not only contributes to the academic discourse on sustainability in supply chains but also serves as a practical tool for industry practitioners seeking to enhance their sustainability reporting and performance. The insights gained from this research will aid in promoting more sustainable practices, ensuring the long-term viability and social responsibility of the leather tanning industry.