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Purpose: This chapter describes the design and implementation, at the computer hardware and software level, of the Greggg robot. Greggg is a scalable high performance, low cost hospitality robot constructed from off-the-shelf parts. Greggg has a robust architecture and acts as a tour guide on-campus, both indoors or outdoors. This research allows one to build a customized robot at a low cost, under U.S. $2,000, for accomplishing the desired hospitality tasks, and scale, and expand the capability of the robot as required.

Practical Implications: The practical implication of the research is the capability to build and program a robot for hospitality tasks. Greggg is a customizable robot capable of giving on-campus tours both indoors and outdoors. In its current architecture, Greggg can be trained to be a museum docent and give directions to visitors on-campus or at an airport and scaled up for other hospitality tasks using off-the-shelf components. Enhancing the robot by scaling it up and expanding it, in addition to testing it with a range of increasingly more difficult tasks using machine learning algorithms, is highly beneficial to advancing research on the use of robots in the hospitality sector. Greggg can also be used for Robot-as-a-service (Rass) applications.

Societal Implications: The economic implication of Greggg is the ease and low cost with which one, with minimal technology know-how, can construct an autonomous hospitality industry robot. This chapter details the hardware and software needed to build a low cost scalable and customizable autonomous robot for the hospitality industry without having to pay an exorbitant price.

Research/Limitations/Implications: This research allows one to build their own customized hospitality robot under U.S. $2,000. Given the cost of building the robot, it has limitations on the hospitality tasks it can perform. It can navigate on flat surfaces, has limited vision and speech processing capabilities and has a battery life not exceeding an hour. Furthermore, it does not have any robotic manipulators or tactile processing capabilities.

This paper aims to review the extant hospitality and tourism literature on the state of robotics and artificial intelligence (AI) in the service industry. The aim was to highlight the current areas of research on this emerging topic and identify areas for future application and study.

A list of hospitality and tourism journals was used to identify articles related to AI and robotics using the terms AI, robots, robotics, hospitality and tourism, and several combinations thereof. Additional sources were identified through the literature reviews from the identified works.

The findings revealed several studies on the current state of robotics and AI in hospitality and tourism. Additional research examines and discusses implications for internal and external customer service, legal and ethical issues and theory.

This paper provides a compilation of the current studies that examine the impact of robotics and AI in hospitality and tourism. It offers scholars an overview of the current knowledge in the field on this rapidly emerging and evolving topic.

本文审阅了有关服务行业中机器学和智能技术（AI）发展的相关文献。其研究目的在于强调有关这个新兴话题的研究领域和指出未来研究方向。

本文样本包括有关AI和机器学的期刊文献，关键搜索词包括AI、机器人、机器学、酒店管理、旅游，以及几项关键词组合。本文还通过文献综述审阅了多个数据源。

研究结果描述了目前酒店旅游行业机器学和AI有关领域的研究状态。此外本文还研究和提出对于内部和外部客户服务、法律伦理问题、以及理论等领域做出研究启示。

本文对目前有关机器学和AI酒店旅游学术研究进行系统梳理。为学者对其相关领域的现状提供全局视角，并且显示这个新兴话题的迅速发展。

文献综述、AI、机器学、酒店科技

This paper aims to provide a comprehensive review of research on robotics in travel, tourism and hospitality, and to identify research gaps and directions for future research.

This paper analyzes 131 publications published during 1993-2019, identified via Scopus, Web of Science, ResearchGate, Academia.edu and Google Scholar. It offers quantitative analysis of frequencies and cross-tables and qualitative thematic analysis of the publications within each of seven identified domains.

The paper identifies “Robot,” “Human,” “Robot manufacturer,” “Travel/tourism/hospitality company,” “Servicescape,” “External environment” and “Education, training and research” as the research domains. Most research studies are dedicated to robots in restaurants, airports, hotels and bars. Papers tend to apply engineering methods, but experiments and surveys grow in popularity. Asia-Pacific countries account for much of the empirical research.

The analysis was limited to publications indexed in four databases and one search engine. Only publications in English were considered. Growing opportunities for those who are anxious to publish in the field are identified. Importantly, emerging research is branching out from the engineering of robots to the possibilities for human/robot interactions and their use for service providers, opening up new avenues of research for tourism and hospitality scholars.

The paper identified a myriad of application areas for robots across various tourism and hospitality sectors. Service providers must critically think about how robots affect the servicescape and how it needs to be adjusted or re-imagined to ensure that robots and employees can augment the service experiences (co-)created within it.

This is the first study to systematically analyze research publications on robotics in travel, tourism and hospitality.

本论文全面评论了在旅游酒店业中的机器人技术的研究, 并指出文献缺口和未来研究方向。

本论文分析了在1993年至2019年发布在Scopus、Web of Science、ResearchGate、Academia.edu、和Google Scholar的131篇文献。本论文对文献做了一系列定量分析, 包括频率分析、交叉表、定性文本分析、在七大确立的领域中对每个领域的文献进行分析。

本论文确立了七个研究领域：机器人、人类、机器生产者、旅游酒店企业、Servicescape、外部环境、和教育培训和研究。大多数文献集中在对饭店、机场、酒店、和酒吧的机器人研究。文献往往采用工程手段进行研究, 但是实验和问卷方式正在呈增长趋势。亚太国家占据大多数实证研究作品。

本论文样本库局限于四个数据库和一个搜索引擎。只有英文文献被采样。本论文为对相关领域感兴趣的学者指出研究方向。重要的是, 本论文发现用工程角度研究机器人的文献有了分支, 有一小部分文献开始着手研究人/机器人交互和其在服务过程中的使用的研究, 这对旅游酒店学者提供新研究视角。

本论文指出了一系列有关旅游酒店领域中机器人的应用。服务商必须重视机器人如何影响Servicescape以及如何审视机器人与人的交互, 确保其与员工加强消费者的服务体验（价值共创）。

本论文是首篇系统评论旅游酒店领域中机器人研究文献的文章。

关键词：机器人、机器人经济、机器人设计、机器人使用、Servicescape、rService、人-机器人交互、研究议程

This paper aims to explore the implications of integrating humanoid service robots into hospitality service encounters by evaluating two service prototypes using Softbank Robotics’ popular service robot Pepper™: to provide information (akin to a receptionist) and to facilitate order-taking (akin to a server). Drawing both studies together, the paper puts forward novel, theory-informed yet context-rooted design principles for humanoid robot adoption in hospitality service encounters.

Adopting a multiple method qualitative approach, two service prototypes are evaluated with hospitality and tourism experts (N = 30, Prototype 1) and frontline hospitality employees (N = 18, Prototype 2) using participant observation, in situ feedback, semi-structured interviews and photo-elicitation.

The adoption of humanoid service robots in hospitality is influenced by the following four layers of determinants: contextual, social, interactional and psychological factors, as well as extrinsic and intrinsic drivers of adoption. These empirical findings both confirm and extend previous conceptualizations of human-robot interaction (HRI) in hospitality service.

Despite using photo-elicitation to evoke insight regarding the use of different types of service robots in hospitality, the paper mostly focuses on anthropomorphized service robots such as Pepper™.

Adopting humanoid service robots will transform hospitality operations, whereby the most routine, unpleasant tasks such as taking repeat orders or dealing with complaints may be delegated to service robots or human-robot teams.

Working with and receiving service from Pepper™ changes the service encounter from direct practical, technical considerations to more nuanced social and psychological implications, particularly around feelings of self-esteem, social pressure and social judgment.

This paper presents one of the first empirical studies on HRI in hospitality service encounters using Softbank Robotics’ Pepper™. In doing so, the paper presents a novel framework for service robot adoption rooted in first-hand user interaction as opposed to previous, theory-driven conceptualizations of behavior or empirical studies exploring behavioral intention.

Purpose: This paper presents a review of the current state and potential capabilities for application of robots, artificial intelligence and automated services (RAISA) in hotel companies.

Design/methodology/approach: A two-step approach was applied in this study. First, the authors make a theoretical overview of the robots, artificial intelligence and service automation (RAISA) in hotels. Second, the authors make a detailed overview of various case studies from global hotel practice.

Findings: The application of RAISA in hotel companies is examined in connection with the impact that technology has on guest experience during each of the five stages of the guest cycle: pre-arrival, arrival, stay, departure, assessment.

Research implications: Its implications can be searched with respect to future research. It deals with topics such as how different generations (guests and employees) perceive RAISA in the hotel industry and what is the attitude of guests in different categories of hotels (luxury and economy) towards the use of RAISA. It also shows what is the attitude of different types of tourists (holiday, business, health, cultural, etc.) and what kinds of robots (androids or machines) are more appropriate for different types of hotel operations.

Practical implications: The implications are related to the improvement of operations and operational management, marketing and sales, enhancement of customer experience and service innovation, training and management.

Originality/value: This book chapter complements and expands research on the role of RAISA in the hotel industry and makes some projections about the use of technologies in the future.

Purpose: The research investigates the presence of technology ideologies in consumer discourse on tourism and hospitality robots.

Design/methodology/approach: Using a netnographic approach, the research involved immersion in online discourses and collection of consumer posts from a variety of social media platforms. Data was subjected to a thematic analysis informed by the technology ideology framework described in the literature review.

Findings: Online consumer narratives about tourism and hospitality robots are dynamic and varied and reveal a multitude of technology ideology-related positions. The research confirms the applicability of the technology ideology framework to online discourses on service robots and finds that anthropomorphism triggers additional concerns.

Research implications: The findings suggest that future research on the acceptance and use of service robots should go beyond psychological concepts.

Practical implications: Without uncovering and understanding technology sensemaking processes with respect to service robots, the introduction of service robots in hospitality and tourism might trigger consumer resistance or lead to inferior service experiences.

Social implications: The research suggests that sensemaking of technology, specifically service robots, is complex and colored by pertinent ideologies. Policies and regulations regarding service robot adoption and implementation should consider these various positions.

Originality/value: The paper introduces technology sensemaking and technology ideology as important theoretical frameworks to understand consumer perceptions, attitudes, uses and relationships in regard to service robots in hospitality and tourism contexts.

Purpose: The goal of the chapter is to define customer attitudes towards robots in travel, tourism and hospitality (TTH) and to analyse their most significant characteristics.

Design/methodology/approach: The book chapter develops a conceptual framework of attitudes towards robots in travel, tourism and hospitality, based on critical analysis of relevant publications.

Findings: The chapter provides a definition and discussion of the characteristics of customer attitudes towards robots in TTH. It elaborates the structural elements of attitudes towards robots, and the links and interactions between the elements.

Research limitations: Research limitations stem from the small number of studies on customer attitudes towards robots in TTH.

Practical implications: The theoretical analysis can be used as a starting point for empirical studies of customer attitudes towards robots in travel, tourism and hospitality.

Social implication: Combined services, based on human employee-service robot collaboration, are the optimal decision for forming favourable customer attitudes towards robotisation and automation in tourism and hospitality. In that way clients’ needs of high technological convenience, interpersonal communication and socialisation are met simultaneously.

Originality/value: This research is among the few publications that study customer attitudes towards robots in travel, tourism and hospitality. The authors develop a matrix of users’ attitudes and behaviours when using robots in travel, tourism and hospitality.

The purpose of this study is to provide an overview of how artificial intelligence (AI) and robotics can and will be utilized by the hospitality industry, providing a glimpse of what their use will look like in 2030.

The paper reviewed both academic and trade literature to provide an overview of how robots will affect the hospitality industry during the 2030s.

Experts predict that by 2030, robots will make up about 25 per cent of the “workforce” in the hospitality industry. The paper also explains the industry challenges the robots will solve, as well as other benefits they provide. One of the findings is that the adoption of robots by the industry will be a disruptive paradigm shift. It will create successful new hospitality companies while putting others out of business. Finally, this paper discusses how to keep the hospitality in hospitality businesses, when machines replace employees.

This paper is one of the first to discuss the disruption that robots will cause in the industry. One of the findings is service delivery systems will need to be redesigned to maximize the benefits of robots, while still maintaining the hospitality of a customer service orientation.

This paper aims to analyze if and to what extent mechanical artificial intelligence (AI)-embedded in hotel service robots-influences customers’ evaluation of AI-enabled hotel service interactions. This study deploys online reviews (ORs) analytics to understand if the presence of mechanical AI-related text in ORs influences customers’ OR valence across 19 leading international hotels that have integrated mechanical AI – in the guise of service robots – into their operations.

First, the authors identified the 19 leading hotels across three continents that have pioneered the adoption of service robots. Second, by deploying big data techniques, the authors gathered the entire population of ORs hosted on TripAdvisor (almost 50,000 ORs) and generated OR analytics. Subsequently, the authors used ordered logistic regressions analyses to understand if and to what extent AI-enabled hospitality service interactions are evaluated by service customers.

The presence of mechanical AI-related text (text related to service robots) in ORs influences positively electronic word-of-mouth (e-WOM) valence. Hotel guests writing ORs explicitly mentioning their interactions with the service robots are more prone to associate high online ratings to their ORs. The presence of the robot’s proper name (e.g., Alina, Wally) in the OR moderates positively the positive effect of mechanical AI-related text on ORs ratings.

Hospitality practitioners should evaluate the possibility to introduce service robots into their operations and develop tailored strategies to name their robots (such as using human-like and short names). Moreover, hotel managers should communicate more explicitly their initiatives and investments in AI, monitor AI-related e-WOM and invest in educating their non-tech-savvy customers to understand and appreciate AI technology. Platform developers might create a robotic tag to be attached to ORs mentioning service robots to signal the presence of this specific element and might design and develop an additional service attribute that might be tentatively named “service robots.”

The current study represents the first attempt to understand if and to what extent mechanical AI in the guise of hotel service robots influences customers’ evaluation of AI-enabled hospitality service interactions.

The hospitality industry has recently witnessed explosive growth in robotization with the replacement of robots in many areas. Yet, a key consideration in this robotics wave is whether competition (i.e. robots take over all human tasks) or collaboration (i.e. humans collaborate closely with robots to perform work better) will define the future of the hospitality workspace. The purpose of this paper is to shed light on this controversial issue by taking a collaborative perspective to address the future human–robot relationship in hospitality workplace (i.e. cobotic team).

Drawing upon relevant theories and extant robotics literature, this paper will develop a critical reflection on the management of future cobotic team as a new phenomenon in hospitality industry.

The successful management of cobotics in hospitality lies in three interrelated key domains: feeling intelligence training for frontline employees, ethics governance for cobotics and trust building toward robot partners.

How to manage this cobotic team efficiently will be a focus for hospitality managers in the coming years. This paper offers several managerial insights for hospitality managers and practitioners regarding effectively managing the future collaboration between humans and robots within a dynamic work environment.

This study addresses cobotics as a critical yet unaddressed shift in the contemporary hospitality sector and proposes a framework highlighting three key domains for managing this cobotic team effectively. This framework also sets the direction to encourage more future empirical research exploring cobotic workforce in hospitality.