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This study aims to examine the role of Pakistan’s banking industry in the transition toward a circular economy (CE) and the implementation of sustainable development goals (SDGs).

This study uses a qualitative content analysis technique on 75 annual reports of 25 Pakistani banks. Data has been collected from websites and annual reports of concerned banks incorporating CE practices and SDGs in their annual reports. In addition, the data collected from the annual reports of concern sample is based on three dimensions of sustainable development (environmental, social and governance) along with the leading practices of CE to reduce, reuse, recycle, redesign, restructure, and recover.

The findings show that most firms have reported CE and SDGs. Also, the study explores the level and linkage of CE and SDGs practices among the sample firms.

This study provides important insights for the regulators, policymakers, State Bank of Pakistan, commercial banks and stakeholders in Pakistan’s banking industry. It adds significant value to the CE and SDGs, especially in developing economies like Pakistan.

The study has explored and examined the ever-investigated dimensions of SDGs and CE in the banking industry of Pakistan.

Brand reputation (BR) is one of the most important factors that affect the consumer–brand relationship and give businesses a competitive advantage. Businesses with a strong BR can increase their market shares and product market prices, in addition to gaining a competitive advantage. In order for businesses to have these advantages, they need to know and analyze their consumers. This study aimed to develop an alternative analysis method by using classification algorithms and regression analysis to measure and evaluate the effect of consumers' BR perceptions on their willingness to pay premium prices (WPP).

The research data were collected from 483 participants by the online survey method due to the COVID-19 pandemic. The data were first analyzed with regression analysis, and the effect of BR on WPP was found to be significant. Then, using artificial intelligence (AI) methods that were not used in previous studies, consumers' perceptions of BR and WPP were clustered and classified.

The results revealed the highest and lowest customer groups with BR and WPP and empirically demonstrated that highly accurate practical classification models can be applied to determine strategies in line with these findings.

The model proposed in this study offers an integrated approach by using AI and regression analysis together and tries to fill the gap in the literature in this field. Therefore, the novelty of this study is to quantitatively reveal and evaluate the relationship between BR and WPP by using AI classification algorithms and regression analysis together.