Purpose The purpose of the present article is to highlight the role of Artificial Intelligence (AI) and Robotics in the tourism industry. The various technologies being integrated to improve the service and customer experience in tourism. The expected changes and challenges in tourism in the future are focused in this paper. Design/methodology/approach A systematic study on the emerging technologies of AI and Robotics applied in the tourism sector is presented in the form of a viewpoint. Findings AI certainly enhances tourism experiential services however cannot surpass the human touch which is an essential determinant of experiential tourism. AI acts as an effective complementary dimension to the future of tourism. With the emergence of artificial travel intelligence, it is simpler to make travel arrangements. AI offers travel services that are automated, customized and insightful. AI allows travelers to learn about their behaviors, interests to inclinations and provide a personalized experience. Gone are the days to consult a travel agent, meet him physically and indulge in an endless chain of troubling phone calls to inquire about travel arrangements. Practical implications Tourism marketing to see a positive and improved change that will enhance the tourists’ overall experience due to the application of AI and Robotics. New emerging technologies like chatbots, virtual reality, language translators, etc. can be effectively applied in Travel, Tourism & Hospitality industry. Originality/value The present viewpoint discusses the application and role of AI and Robotics with the help of relevant industry examples and theory. The present paper highlights the different technologies being used and will be used in the future.

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Purpose In business, online reviews have an economic impact on firm performance. Customers’ data in the form of online reviews was used to understand the appreciation and service complaints written by previous customers. The study is an analysis of the online reviews written by the customers about Indian heritage hotels. This study aims to understand the dimensions of service appreciation and service complaints by comparing positive- and negative-rated reviews and find the patterns in the determinants of the satisfaction and dissatisfaction of the customers. Design/methodology/approach A total of 23,643 online reviews about heritage hotels were collected from the TripAdvisor website by using a Web crawler developed in Python. A total of 1000 reviews were randomly selected for further analysis to eliminate the bandwagon effect. Unsupervised text mining techniques were used to analyze reviews and find out the interesting patterns in text data. Findings Based on Herzberg two-factor theory, this study found satisfied and dissatisfied determinants separately. The study revealed some common categories discussed by satisfied and dissatisfied customers. The factors which satisfy the customers may also dissatisfy the customers if not delivered properly. Satisfied customers mentioned about tangible features of the hotel stay, which includes physical signifiers, traditional services, staff behavior and professionalism and core products (rooms, food). However, most of the customers complained about intangible service problems, such as staff attitude, services failure, issues with reservation and food, value for money and room condition. The results are contradicting with commercial hotels-based studies owing to the unique services provided by heritage hotels. Practical implications The dimensions for satisfaction and dissatisfaction among customer of heritage hotels provide marketers to understand the real emotion and perception of the customers. As these dimensions were extracted through text mining of the reviews written by the customer of heritage hotels, the results would certainly give better insights to the hotel marketers. Originality/value The study is a rare attempt to study online reviews of customers on heritage hotels through a text mining approach and find the patterns in the behavior and the determinants of satisfaction and dissatisfaction of customers.