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Sustainable tourism is becoming more popular all over the world. Eco-friendly (green) hotels are properties that are friendly to the environment and are becoming increasingly popular among green travellers. Electronic word-of-mouth is a technique of communicating with consumers in order to share their experiences, and it is a significant marketing tool for hotels. This paper aims to identify the main themes shared in online reviews by tourists visiting eco-friendly hotels, and which of these themes were associated with satisfaction and dissatisfaction ratings.

The research used qualitative content analyses to analyse 1,202 user-generated content of the top 10 hotels in UK shared by guests on an online platform.

The analyses revealed nine themes in descriptions of airline travel experiences. These are “hotel amenities”, “services”, “location”, “staff”, “eco” (eco-friendly activities), “value” and “recommend/revisit” (intentions). Negative comments are associated with the “bathroom”, “mattress”, “water”, “bed”, “price”, “shower”, “Wi-Fi” and “restaurant” concepts.

This study differs from previous research in which it aims to address a void in the literature on the shortcomings of research focused on finding the dominant themes expressed in online reviews by tourists visiting eco-friendly hotels, and it does so using data mining approach.

The interconnected challenges of climate change and social inclusivity have placed unprecedented pressure on businesses to adopt responsible practices. While previous research has explored the individual impacts of environmental, social, and governance (ESG) performance and diversity initiatives, there remains a dearth of comprehensive investigations into how these factors collectively influence carbon emission scores. Drawing on the legitimacy theory, we explore whether ESG and diversity scores predict global companies' carbon emission scores. As concerns about the environmental impact of businesses grow, understanding the relationships between ESG performance, diversity management, and carbon emissions becomes imperative for sustainable corporate practices.

The primary dataset for this study includes 1,268 worldwide firm-year data for 2021. The sample is subjected to missing data examination as a component of the filtration process. Data preprocessing is performed before machine learning analysis, including verifying missing data. Our research resulted in the final sample, which includes 627 worldwide firm data from 2021. Data regarding all publicly traded companies was obtained from Refinitiv Eikon.

Our findings showed that corporate carbon emission performance in global corporations is influenced by ESG performance and total diversity score.

Firms involve in ESG as well as diversity practices to be able to achieve sustainable success. Yet, the forecasting of carbon emissions based on ESG scores and diversity scores remains inadequately established due to conflicting findings and enigmas prevalent in the literature.