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The main objective of this chapter is broadening the understanding of anthropomorphic artificial intelligence (AI) (e.g. avatars, humanoid robots, chatbots) in both physical and digital environments. The chapter strives to demonstrate how organisations can curate relationship marketing and enhance customer experience by employing anthropomorphic AI. To achieve this, the chapter extends existing understanding in three ways. First, it explains the interconnectivity between relationship marketing and customer experience. Second, it presents anthropomorphic AI along with its different characteristics and technologies. Third, it offers some real-life uses cases and examples of such AI drawing from practical insights into five selected industries. Overall, the chapter provides some food of thoughts concerning the successful application and deployment of anthropomorphic AI in marketing practices.

Voice command and voice search are becoming increasingly popular in the hospitality and tourism industry, with many hotels and travel companies investing in voice-enabled technology to improve guest experiences and streamline operations. This technology allows travellers to manage their travel plans, request services and get information through natural voice commands on any voice-enabled device. Voice assistants are also multilingual, allowing hotels to customise responses to guests who do not speak the local language. Angie, a multilingual, in-room voice assistant, is an example of this technology. It can fulfil guest requests, answer common questions about the property and create streamlined access to a wide range of hotel amenities, such as ordering room service or requesting extra towels. Hotels can control questions and responses to assist stretched staff and provide upsell and advertising revenue through digital promotions or recommended onsite amenities or discounts. In addition, voice command technology can be used to book travel and find things to do at a destination. Google Assistant can help with travel plans like booking a hotel, checking flight status and finding things to do at a destination. In conclusion, voice command and voice search technology are transforming the hospitality and tourism industry by improving guest experiences, reducing operational costs and increasing revenue.

Mobile marketing, the two- or multi-way communication and promotion of an offer between a firm and its customers using a mobile medium, device, platform, or technology, has made rapid strides in the past several years. Mobile marketing has entered its second phase or Mobile Marketing 2.0. The surpassing of desktop by mobile devices in digital media consumption, diffusion of wearable devices among customers, and an overall integration and interconnectedness of devices characterize this phase. Against this backdrop, we present a synthesis of the most recent literature in mobile marketing. We discuss three key advances in mobile marketing research relating to mobile targeting, personalization, and mobile-led cross-channel effects. We outline emerging industry trends in mobile marketing, including mobile app monetization, augmented reality, data and privacy, wearable devices, driverless vehicles, the Internet of Things, and artificial intelligence. Within each extant and emerging area, we delineate the future research opportunities in mobile marketing. Finally, we discuss the impact of mobile marketing on customer, firm, and societal outcomes.

This study aimed to identify distinctive characteristics of hotel guests and understand their perception of guestroom technologies (GRTs) in hotels by utilizing the theory of consumer innovativeness and the social influence theory.

The data were collected from 268 hotel guests. The K-means clustering algorithm was employed to identify participants based on their views on the significance of technologies provided in guest rooms. A multivariate analysis of variance was applied to investigate if there were significant differences among clusters regarding social influence on hotel bookings, technology innovativeness and technology expertise and knowledge.

Two clusters were identified: technology compassionates and casual users of technology. Findings revealed that technology compassionates are more influenced by their friends when booking a hotel compared to casual users of technology. The ability to link up multiple wireless mobile devices, accessible outlets and mobile websites were the most critical GRTs for technology compassionates.

Technology should be considered a crucial part of the hotel guest experience. Hoteliers ought to continue investing in smart technologies to improve their guests' experiences. GRTs can reduce overhead staff costs while giving guests more control over their stay by utilizing everyday items like smartphones and offering them more power over their lodging experience.

This study advances the existing literature on GRTs by identifying which GRTs produce the most customer satisfaction. Moreover, this study explores the impact of social influence, innovativeness as a personality trait and having expert knowledge of technologies on preferences for GRTs.

Extending the technology acceptance model (TAM) to a new context, the purpose of this paper is to propose an integrative model of the brand of artificial intelligence-enabled voice assistants (AI-EVA) and customers’ perceptions and behavioral intentions of using AI-EVA in hotels. Moderating effects of construal levels and hotel scales were examined.

This paper adopted a mixed method approach. A qualitative and phenomenological methodology was adopted in Study 1 to explore hotel customers’ experience with AI-EVA. Study 2 applied experimental design to investigate the effects of the brand of AI-EVA and construal level on customers’ perceptions and behavioral intentions of using AI-EVA. Based on Studies 1 and 2 results, Study 3 examined how the brand of AI-EVA and hotel scale affect customers’ perceptions and behavioral intentions of using AI-EVA during hotel stays.

This research found that customers perceive a higher level of perceived usefulness, perceived ease of use and anthropomorphism when AI-EVA is branded (vs off-brand). Perceived usefulness positively affects customers’ intention to use and to spread positive word-of-mouth. Anxiety of using AI-enabled devices and privacy concerns inhibit customers’ intention to use AI-EVA. Anthropomorphism increases customers’ willingness to spread positive word-of-mouth. Construal level moderates the effect of the brand of AI-EVAs on perceived ease of use and anthropomorphism. Hotel scale moderates the effect of brand on perceived usefulness.

This paper is one of the first attempts to uncover and integrate different factors underlying customers’ perceptions of using AI-EVA in an extended TAM in hotel settings. This paper provides an integrative model extending the TAM to a new context by deploying a mixed-method approach across three studies.

The research aims to understand how smart speakers are perceived by their actual and potential users, their attitude towards smart speakers and consequently their intention to use them.

The authors apply a structural equation modelling (SEM) approach to test the research hypotheses through data coming from a structured questionnaire.

The results show that the higher the importance attributed to usefulness and ease of use, the higher the positive attitude that in turn positively affects the intention to use smart speakers. A significant relationship also emerged between task technology fit and attitude towards smart speakers, as well as between perceived enjoyment and attitude towards smart speakers. Perceived privacy risk, innovativeness and social attraction have been found to not significantly impact attitudes towards smart speakers.

Although several academic studies have focused on various aspects of smart technologies, only a few studies discuss the factors that push consumers to use smart speakers for activities related to commercial transactions. Therefore, looking at the rapid rise of smart speakers for daily tasks and the gradual acceptance of voice interaction with digital tools, the authors proposed a study about Italian users' intention to use smart speakers. Specifically, to fill the gap in the existing literature, the authors applied a SEM approach to identify utilitarian and hedonic benefits that motivate the use of these devices.

Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.

Internet of Things (IoT) involves connecting physical objects to the internet to provide opportunities to build smart systems or applications. IoT paradigm assumes many devices connected over a conventional intent network. These devices usually have restricted resources, so moving part of the service implementation to a cloud infrastructure is a prominent solution. This study aims to proposes in this project human voice as a potential interface for one or more devices in IoT ecosystem enabling issuing commands and receiving information.

System design is the process of defining the elements of a system such as the architecture, modules and components, the different interfaces of those components and the data that goes through that system. It is meant to satisfy specific needs and requirements of a business or organization through the engineering of a coherent and well-running system.

The main aim of this proposed work is to develop a ticket booking application that performs all the operations by speech recognition. Hence, visually impaired people can make use of this application. There are several applications that help visually impaired people. This application adds extra features to those available soft wares. Using this, visually impaired people can book the tickets without the help of personal assistants. For future research, this study hopes to extend this application to perform various other operations that will help visually impaired people to do their daily activities like normal people without the help of personal assistants. For example, making a phone call, sending text messages, booking a taxi, easy navigation, etc.

System design involves the identification of classes, their relationship as well as their collaboration. In objector, classes are divided into entity classes and control classes.