Robots, Artificial Intelligence and Service Automation in Travel, Tourism and Hospitality

Stanislav Ivanov, Craig Webster, Stanislav Ivanov, Craig Webster

• Publisher: Emerald Publishing Limited
• Year: 2019
• ISBN:
  9781787566897
• Topic: Business
• Subtopic: Hospitality, Travel & Tourism Industry
• Index: Business

Using a combination of theoretical discussion and real-world case studies, this book analyses the use of robotics, artificial intelligence and services automation (RAISA) within the travel, tourism and hospitality industries.
Divided into two sections, the book first concentrates on the theoretical aspects surrounding the use of RAISA in travel, tourism and hospitality. Themes explored include:

• economic fundamentals
• customer attitudes
• chatbot adoption
• service quality

Following on from this, the second section concentrates on current and future use of RAISA technologies in specific subsectors of the tourism economy: hotels, restaurants, travel agencies, museums, and events.
With an international scope of authorship and focus, the book is a useful reference source for scholars, students, and general readers interested in robotics, artificial intelligence, and automation technologies. Alongside this, the business insights and case studies examined in the book offer practitioners guidance on how these technologies can and will be incorporated into organizations, particularly those in the travel and tourism industry.

Section 1

Theoretical Issues of Robots, Artificial Intelligence, and Service Automation in Travel, Tourism, and Hospitality

Chapter 1

Conceptual Framework of the Use of Robots, Artificial Intelligence and Service Automation in Travel, Tourism, and Hospitality Companies

Stanislav Ivanov and Craig Webster

Introduction

Tourism and hospitality are usually referred to as a “people business” – services provided by human service providers (receptionists, housekeepers, waiters, cooks, bartenders, guides, drivers, sales agents, event organizers, supervisors, managers, etc.) for human customers (travelers, passengers, tourists, guests, and event attendees). The traditional labor-intensive nature of the business has been necessary because of the complicated nature of many of the tasks required (e.g.,changing the sheets on a bed) and nuances in communications between customers and service providers generally required a human to make judgments, interpret information, and respond to tasks that are not part of standard operational procedures. However, the technological developments at the end of the twentieth and beginning of the twenty-first century such as the Internet, websites, social media, mobile applications, virtual/augmented/mixed reality, chatbots, robotics, and self-service kiosks (Benckendorff, Xiang, & Sheldon, 2019), created an important technological layer in the interaction between companies in travel, tourism, and hospitality (TTH) and their customers. This technological layer reorganized the “human–human” interactions in TTH into “human–machine,” “human–computer,” and, more recently, into “human–robot” interactions. Moreover, the technological layer started to transform the business models of TTH companies – they began to use robots, artificial intelligence, and service automation (RAISA) technologies to design and deliver services to their human guests (Ivanov, Webster, & Berezina, 2017). Because of technological advances, the “high-touch” tourism businesses have been able to add a “high-tech” component (Naisbitt, Naisbitt, & Philips, 2001). Customers take greater role and responsibility in the service-delivery process and evolve into “prosumers” (= “producers” + “consumers”) of TTH services (Ivanov, 2019), while some authors claim that robots would become and should be treated as customers too (Ivanov, 2018; Ivanov & Webster, 2017a) or even have their own rights (Gunkel, 2018).

The advances in RAISA technologies (Bhaumik, 2018; Ertel, 2017; Miller & Miller, 2017; Neapolitan & Jiang, 2018; Russell & Norvig, 2016) allowed their introduction in various sectors of the economy and society such as manufacturing and smart factories (Askarpour, Mandrioli, Rossi, & Vicentini, 2019; Cubero, 2007; Diez-Olivan, Del Ser, Galar, & Sierra, 2019; Low, 2007; Pires, 2007; Wang, S., Wan, Zhang, Li, & Zhang, 2016), agriculture (Driessen & Heutinck, 2015; Slaughter, Giles, & Downey, 2008; Wolfert, Ge, Verdouw, & Bogaardt, 2017; Xiong, Peng, Grimstad, From, & Isler, 2019), warehousing and supply chain management (Mahroof, 2019; Wurman, D’Andrea, & Mountz, 2008), and autonomous vehicles (Fagnant & Kockelman, 2015; Maurer, Gerdes, Lenz, & Winner, 2016), among others. RAISA are also used by service industries (Huang & Rust, 2018; van Doorn et al., 2017; Wirtz et al., 2018), in education (Ivanov, 2016; Timms, 2016; Walkington & Bernacki, 2019), journalism (Clerwall, 2014; Latar, 2018), for trading on financial markets (Dunis, Middleton, Karathanasopolous, & Theofilatos, 2017), and provision of legal services (Remus & Levy, 2015). Robots assist surgeons in medical operations (Kaur, 2012; Mirheydar & Parsons, 2013; Schommer, Patel, Mouraviev, Thomas, & Thiel, 2017), while military drones are used for surveillance and strikes on enemy targets (Crootof, 2015; Koslowski & Schulzke, 2018; Sparrow, 2007). In April 2019, the first academy book written by artificial intelligence (AI) was published by Springer (Writer, 2019). Social robots enter our lives as companions (Nørskov, 2016; Royakkers & van Est, 2016), while sex robots redefine the meaning of love and sex (Cheok, Devlin, & Levy, 2017; Danaher & McArthur, 2017; Lee, 2017). Chatbots already take a significant share of the communication between companies and their customers not only for provision of basic information about offers, but for actual sales and customer support as well (Hill, Ford, & Farreras, 2015; Xu, Liu, Guo, Sinha, & Akkiraju, 2017). Companies adopt RAISA not only to decrease costs, eliminate waste, and improve productivity, economic efficiency, and financial bottom line, but also to streamline operations, design service experiences, and boost revenues as well, which leads to profound transformations in their business models and the nature of work (Agrawal, Gans & Goldfarb, 2018; Corea, 2017; Davenport, 2018; Daugherty & Wilson, 2018; Makridakis, 2017; Talwar, 2015; Talwar, Wells, Whittington, Koury, & Romero, 2017; Webster & Ivanov, 2020). Researchers and business leaders expect that the adoption of robotics, AI, automation technologies, Industry 4.0 (Schwab, 2016; Skilton & Hovsepian, 2018) and the Internet of things (Sendler, 2018) will speed up in the future, fueled by technological progress, the plummeting prices of these technologies and the low birth rates in developed economies (Ivanov & Webster, 2018). In the long run, this process will result in greater automation of production of goods and services, until most of the goods and services are delivered by RAISA technologies, and not by human employees – an economic system known as “robonomics” (Ivanov, 2017).

TTH industries are not an exception to the adoption of RAISA (Collins, Cobanoglu, Bilgihan, & Berezina, 2017; Ivanov et al., 2017; Kuo, Chen, & Tseng, 2017; Murphy, Hofacker, & Gretzel, 2017; Murphy, Gretzel, & Pesonen, 2019). For example, tourists can search for travel information and book a trip via a chatbot (Nica, Tazl, & Wotawa, 2018). Tourists can also use virtual reality to see the attractions at the destination and the hotel they would stay. The destination advertisements they see while visiting various websites and the personalized prices they pay (Ivanov, 2019) would be determined by AI algorithms on the basis of their behavioral characteristics. At the airport, their trip is facilitated by self-check-in machines, self-service baggage drop-off, and automated passport control with face recognition (del Rio, Moctezuma, Conde, de Diego, & Cabello, 2016; Gures, Inan, & Arslan, 2018; Kazda & Caves, 2015; Ueda & Kurahashi, 2018). From the airport, they can reach their hotel by an autonomous vehicle (Cohen & Hopkins, 2019). Upon arrival, they are greeted at the entrance by a robotic porter, they can check-in at a self-service kiosk (Kim & Qu, 2014) and enter their rooms with a mobile application on their smartphones (Cheong, Ling, & The, 2014; Torres, 2018). Within the room, they could control the smart technologies via a mobile phone, a tablet, or a voice-controlled digital assistant. A robotic fish swims in an aquarium. The room service order is delivered by a robot. Robots clean the floors and swimming pools, and cut the grass at hotels’ green areas. In the restaurant, tourists can order their food and drinks through a kiosk or tablet on the table, or take a sushi bowl from a conveyor belt (Collins et al., 2017; Kim, Christodoulidou, & Choo, 2013). Augmented and mixed reality applications will help them see and choose their dish in an interactive way. They can receive information about the destination and offered tours, and book a suitable service from a kiosk in front of the office of a local tourist information center or a travel agency. They can have their pizza ordered through chatbots or voice-controlled digital assistant, and delivered by a drone or an autonomous car (Lui, 2016) while checking the status of their order through a mobile app. And, ultimately, they may have their trip booked before they have even thought of it – their personal digital assistant with strong predictive analytics features may identify the need for a holiday for them, check suitable dates according to tourists’ schedules, stored in assistant’s memory, search for appropriate destination according to the search behavior, preferences, and personality of their owners, and book flights and hotels. Most consumers currently would feel a bit uneasy about putting so much trust into AI, relying upon a computer’s algorithms and calculations to make such judgments and plan such a travel. While technology has not yet reached the stage where this is possible, sooner or later RAISA technologies will take over much of the decision-making process in TTH.

This chapter develops a conceptual framework for the use of RAISA in TTH. It looks at the issue from both supply (companies) and demand (tourists) perspectives, in order to provide a balanced account of the use of RAISA in TTH context. The rest of the text is organized as follows. The next section “RAISA Technologies in TTH” provides an overview of the scope of RAISA technologies in the current world, introducing the basic definitions, and critically evaluating the available literature on RAISA in TTH. Section “RAISA in TTH– A Conceptual Framework” develops the conceptual framework of the use of RAISA in TTH. The last section “Concluding Remarks” summarizes and concludes the chapter.

Raisa Technologies in TTH

Service Automation in TTH

Service automation includes a wide variety of self-service technologies (SST) defined by Meuter, Ostrom, Roundtree, and Bitner (2000, p. 50) as “technological interfaces that enable customers to produce a service independent of direct service employee involvement.” Within TTH service automation, technologies such as check-in or information kiosks at hotels and airport, mobile check-in applications, ticket machines at train and bus stations and at theme parks, vending machines for food and drinks, baggage drop-off counters and automated biometric fingerprint scanners at airports, self-ordering kiosks and conveyor belts in restaurants, etc., are included. Figs. 1–9 present some of the SSTs used by TTH companies.

A common feature of service-automation technologies is that they transfer the responsibility of the service-delivery process from the company employees to the customers and transform them into prosumers of the service process. Th...