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Artificial Intelligence for Greenwashing Detection: A Conceptual Analysis of NLP and LLM in Sustainability Reporting Mohammad Mostaf Fauzil Mufti; Tiara Rizky Cahya; Zahwa Nura Aziza; Khristina Putri Kasihwigati; Maureen Cahayli; Dina Safitri; Diajeng Fitri Wulan
Hikamatzu | Journal of Multidisciplinary Vol. 3 No. 1 (2026): Multidisciplinary Approach
Publisher : Hikamatzu | Journal of Multidisciplinary

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Abstract

Greenwashing, the practice of making misleading environmental claims, continues to hinder genuine progress toward sustainable development. Studies show that a significant proportion of corporate sustainability claims are exaggerated or unfounded, creating a demand for effective tools to identify such practices. Traditional methods of detecting greenwashing, such as manual reviews and basic keyword analysis, are often insufficient due to the complexity and volume of data involved. This study uses a conceptual and analytical research design to summarize existing evidence on the use of Artificial Intelligence (AI), including Natural Language Processing (NLP) and Large Language Models (LLMs), in detecting greenwashing. By analyzing sustainability reports, press releases, and social media content, these AI tools offer a more efficient and accurate approach to identifying discrepancies between corporate claims and actual practices. The findings demonstrate that AI technologies can significantly advance greenwashing detection, contributing to more reliable and accessible sustainability assessments. However, limitations remain, as the study focuses on only two AI methodologies. Future research should explore a wider range of AI tools and techniques to address industry-specific challenges and regulatory concerns, ensuring a more comprehensive approach to detecting greenwashing in corporate practices.
The Effect of Experiential Marketing on Customer Commitment with Customer Satisfaction as a Mediating Variable at Nuju Coffee Bandar Lampung Tiara Rizky Cahya; Satria Bangsawan; Nuzul Inas Nabila
Al-Zayn: Jurnal Ilmu Sosial, Hukum & Politik Vol 4 No 2 (2026): 2026
Publisher : Yayasan pendidikan dzurriyatul Quran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61104/alz.v4i2.4735

Abstract

The rapid growth of the coffee shop industry in Bandar Lampung has intensified competition among businesses, encouraging companies to focus not only on product quality but also on delivering meaningful customer experiences. This study aims to examine the effect of experiential marketing on customer commitment, with customer satisfaction acting as a mediating variable at Nuju Coffee Bandar Lampung. This research employs a quantitative approach using a non-probability purposive sampling technique. Data were collected through questionnaires distributed to 180 respondents who had visited and dined in at Nuju Coffee Bandar Lampung within the last three months. Experiential marketing serves as the independent variable, customer satisfaction as the mediating variable, and customer commitment as the dependent variable. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) with the assistance of SmartPLS 4.0 software. The results indicate that experiential marketing has a positive and significant effect on customer satisfaction. Furthermore, customer satisfaction has a positive and significant effect on customer commitment. The findings also reveal that customer satisfaction significantly mediates the relationship between experiential marketing and customer commitment. These results demonstrate that experiential marketing plays a crucial role in enhancing customer satisfaction and strengthening long-term customer commitment in the coffee shop industry.