This research study explores the relationship between green marketing strategies and Pakistani consumers' green buying intentions (GBI), with a focus on the moderating effect of greenwashing. Data was collected quantitatively from 60 participants, covering a variety of different attributes such as age, income level, occupation, and education. The results showed that green pricing strategies have less effect on GBI than green product, place, and promotional initiatives. Altogether the paper highlights that greenwashing has a negative moderating effect on the association between green marketing strategies and GBI, demonstrating that consumers' perception of false environmental promises may hinder marketing endeavors.

Corporate climate disclosures have come to the fore of measuring environmental responsibility, but worries about greenwashing of exaggeration or parts of the environmental performance of exaggerating or overselling environmental performance remain. This paper fulfills this crucial gap in establishing the validity of such revelations by offering the machine learning method of identifying possible greenwashing. It is probable that the mixed-methods design has been used, where the textual analysis of the composed corporate sustainability reports and supervised learning algorithms trained on labeled examples of misleading statements are supplemented. Through the implementation of natural language processing and classification algorithms, the model will recognise patterns that are suggestive of a lack or even exaggeration of commitment with regard to climate pledges. The findings can be used to illustrate industry-related patterns and important language indications linked to greenwashing.