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This article examines restaurant customers’ online activity following visits to restaurants. Differences in customers’ opinions based on gender and location are discussed. Sentiment analysis was used to analyze customers’ social media behavior in terms of liking, rating, and reviewing restaurants. User‐generated reviews and comments about experiences influence potential customers’ decisions. The results of this study show that gender and location of customers influence restaurant ratings. This article shows that sentiment analysis (using Natural Language Toolkit and TextBlob) can help marketers by providing a useful tool for big data analysis. Sentiment analysis can be used to interpret customer behavior and highlight how presales, sales, and after‐sales strategies can be improved.

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Purpose The hospitality and tourism sector has witnessed phenomenal growth in customer numbers during the postpandemic times. This growth has been accompanied by the use of technologies in customer interface and backend activities, including the adoption of self-serving technologies. This study aims to analyze the existing practices and challenges and establish a research agenda for the implementation of generative artificial intelligence (AI) (such as ChatGPT) and similar tools in the hospitality and tourism industry. Design/methodology/approach This study analyzes the existing literature and practices. This study draws upon these practices to outline a novel research agenda for scholars and practitioners working in this domain. Findings The integration of generative AI technologies, such as ChatGPT, will have a transformational impact on the hospitality and tourism industry. This study highlights the potential challenges of implementing such technologies from the perspectives of companies, customers and regulators. Research limitations/implications This study serves as a reference material for those who are planning to use generative AI tools like ChatGPT in their hospitality and tourism businesses. This study also highlights potential pitfalls that ChatGPT-enabled systems may encounter during service delivery processes. Originality/value This study is a pioneering work that assesses the applications of ChatGPT in the hospitality and tourism industry. This study highlights the potential and challenges in implementing ChatGPT within the hospitality and tourism industry.

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The entrepreneurial resilience of eco-label product retailers emphasises their adaptive capability for renewal after the economic crisis. This paper explores the resilience of the market intelligence techniques adopted by the eco-label product retailers in order to contribute to sustainable development of this market in Romania. The research, conducted on a sample of Romanian retailers of eco-label products, analyses the main sources for gathering data about their competitors, the reasons for monitoring the strategic options of their competitors and the specific market intelligence techniques employed within the entrepreneurial resilience approach, aiming to overcome the negative crisis effects. The research outlines, from an entrepreneurial resilience perspective, several positioning opportunities of the eco-label product retailers after the crisis, which have affected the Romanian economy in the period 2008-2009 and have implicitly affected the eco-label market.