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The purpose of this study is to discuss how consumers accept advanced artificial intelligence (AI) robots in hospitality and tourism and provide a typology and conceptual framework to support future research on advanced robot applicability.

This research reviews current cases of AI use and technology acceptance model (TAM) studies and proposes a framework, interactive technology acceptance model (iTAM), to identify key determinants that stimulate consumer perceptions of advanced robot technology acceptance.

The main constructs and types of advanced robots were identified by reviewing TAM studies and AI robots that are currently used in the tourism and hospitality industry. This research found that as technologies tested in TAM studies have been improved by highly interactive systems, increased capability and a more user-friendly interface, examining perceived interactivity of technology has become more important for advanced robot acceptance models. The examples of advanced robot uses indicate that each machine learning application changes the robots’ task performance and interaction with consumers. Conducting experimental studies and measuring the interactivity of advanced robots are vital for future research.

To the authors’ knowledge, this is the first study on how consumers accept AI robots with machine learning applications in the tourism and hospitality industry. The iTAM framework provides fundamental constructs for future studies of what influences consumer acceptance of AI robots as innovative technology, and iTAM can be applied to empirical experiments and research to generate long-term strategies and specific tips to implement and manage various advanced robots.

旅游和酒店业机器人的机器学习：交互式技术接受模型（iTAM）–前沿研究

这项研究旨在讨论消费者如何在酒店和旅游业中接受先进的人工智能（AI）机器人, 并提供类型学和概念框架来支持有关先进机器人适用性的未来研究。

这项研究回顾了AI使用和技术接受模型（TAM）研究的当前案例, 并提出了一个框架, 即交互式技术接受模型（iTAM）, 以识别能够激发消费者对先进机器人技术接受程度的认知的关键因素。

通过回顾当前在旅游和酒店业中使用的TAM研究和AI机器人, 本文确定了高级机器人的主要结构和类型。研究发现, 由于TAM中的技术已通过高度互动的系统, 增强的功能以及更友好的用户界面进行了改进, 因此, 对于先进的机器人接受模型而言, 检查感知技术交互性已变得越来越重要。先进的机器人使用案例表明, 每个机器学习应用程序都会改变机器人的任务性能以及与消费者的互动。进行实验研究和测量高级机器人的交互性对于将来的研究来说是至关重要的方向。

这是关于消费者如何在旅游和酒店业中接受具有机器学习应用程序的AI机器人的首次研究。iTAM框架为将来的研究提供了基础结构, 以了解哪些因素会影响消费者对AI机器人作为创新技术的接受程度。iTAM亦可以用于实证实验和研究, 以提供实施和管理各种先进机器人的长期策略和具体技巧。

iTAM,机器学习,人工智能机器人, 技术接受, 感知交互性, 人工智能机器人的类型

纸张类型概念纸

概念性文章

El Machine Learning (Aprendizaje Automático) de robots en turismo y hotelería: Modelo de Aceptación de Tecnología Interactiva (iTAM): tecnología de punta

El objetivo de este estudio, es analizar la aceptación que tienen los robots avanzados de Inteligencia Artificial (IA) por parte de los consumidores de hoteles y turismo y proporcionar una tipología y un marco conceptual para apoyar la investigación futura sobre la aplicabilidad avanzada de estos robots.

Esta investigación, revisa los casos actuales de uso de IA y estudios del Modelo de Aceptación de Tecnología (TAM) y propone: el Modelo de Aceptación de Tecnología Interactiva (iTAM) para identificar los determinantes clave que estimulan las percepciones del consumidor sobre la aceptación avanzada de la tecnología de robots.

Los principales prototipos de robots avanzados se identificaron mediante la revisión de los estudios TAM y de IA sobre robots que se utilizan actualmente en la industria del turismo y la hostelería. Esta investigación, encontró que a medida que las tecnologías testadas en los estudios TAM, se han mejorado mediante la incorporación de sistemas altamente interactivos, aumentando la capacidad y mejorando la usabilidad de la interfaz; se ha vuelto más importante examinar la interactividad percibida de la tecnología para los modelos avanzados de aceptación de robots. Los ejemplos de usos avanzados de robots, indican que cada aplicación de aprendizaje automático varía el rendimiento de la tarea de los robots y la interacción con los consumidores. La realización de estudios experimentales y la medición de la interactividad de los robots avanzados son vitales para futuras investigaciones.

Este es el primer estudio sobre como los consumidores del sector turístico y hotelero aceptan los robots de IA basado en aplicaciones de machine learning (aprendizaje automático). El marco iTAM proporciona constructos fundamentales para futuros estudios sobre los factores que influyen en el consumidor a la hora de aceptar los robots de IA como tecnología innovadora. iTAM se podría aplicar a experimentos empíricos e investigaciones con el objetivo de generar estrategias a largo plazo y consejos específicos para implementar y administrar varios robots avanzados.

iTAM, Aprendizaje automático, Robot de inteligencia artificial, Aceptación de tecnología, Interactividad percibida, Tipo de robot IA

Tipo de papel Papel conceptual

The service industry is facing the huge impact of digital transformation, in which artificial intelligence (AI) plays one of the most important roles. This study aims to expand the understanding of the AI acceptance framework and confirm whether consumers’ digital skills have a moderating effect on the research model.

Hypotheses were tested using a data set of 1,641 individuals. Partial least squares structural equation modeling and multi-group analysis were used to estimate the model.

The results indicate that antecedent factors influence consumers’ willingness to use AI devices in services. The two groups of different digitally savvy respondents differ because the influence of anthropomorphism, social influence and hedonic motivation on respondents’ perceived efforts to use AI devices in service delivery depends on respondents’ digital skills.

The novel contribution of this study is reflected in a comprehensive model that explains the moderating effect of individual digital skills on willingness to use AI devices. The attitudes of experienced and digitally skilled consumers are valuable and highlight some important theoretical, practical implications and future lines of research.

This study aims to investigate the consumer acceptance of robots in hotels before and after COVID-19, with a specific emphasis on whether COVID-19 had a significant effect on the acceptance of robots by hotel guests and whether guests had higher levels of acceptance of hotel robots since the initial COVID-19 outbreak was brought under control in China.

The sample for this research included Chinese hotel guests before and after COVID-19, with 247 responses obtained before its outbreak and a further 601 responses gathered after. Several hypotheses were developed and tested in a pseudo-experimental design.

The results showed that COVID-19 increased hotel guest acceptance of robots. After COVID-19, the perceived importance of the usefulness, social influence, attitude and value of robots increased, while the perceived importance of the ease of use and anthropomorphism of robots decreased. As a contactless service, the usefulness of robots was more valued by customers. This led customers to lower their requirements for the ease of use of robots. In addition, people were more concerned about the social influences on robot use.

Hotel guest attitudes and behavioral intentions toward robots and the services they can provide are changing. However, whether this change is purely ephemeral and motivated by a pragmatic stance triggered by COVID-19 remains to be established.

The hospitality industry is encouraged to create a new profile of guests in terms of their favorable or unfavorable disposition toward being served by robots. Hotels should consider the deployment of robots according to the demographic characteristics of customers (e.g. according to guest age levels).

This research demonstrated that major crises affect customer attitudes and behaviors toward new technologies. COVID-19 resulted in guests paying more attention to the advantages of services offered by hotel robots as a means of reducing the probability of contagion.

疫情前后酒店机器人非接触式服务的技术接受度对比研究

摘要

本研究调查了新冠疫情爆发前后酒店顾客对机器人接受程度的变化, 重点研究了新冠疫情是否对机器人的潜在接受程度有显著影响, 以及自疫情在中国得到控制以来, 顾客对酒店机器人的接受程度是否有所提高。

本研究的样本主要是新冠疫情爆发前后的中国酒店顾客, 在疫情爆发前收集了217份样本, 在疫情爆发后收集了601份样本。研究提出了若干假设, 并采用伪实验设计进行了检验。

结果显示, 新冠疫情的爆发提高了酒店顾客对机器人的潜在接受度。新冠疫情后, 机器人的有用性, 社会影响, 态度和价值的影响增加了, 而机器人的易用性和拟人化的影响降低了。由于机器人的无接触服务, 使得顾客更加关注有用性。这导致顾客对易用性的关注降低。此外, 顾客更加关注使用机器人的社会影响。

酒店顾客对机器人服务的态度和行为意图正在发生变化。然而, 这一变化是否是短暂的, 只是由新冠疫情驱动的, 仍有待确定。

我们鼓励酒店业根据客人对机器人的接受/不接受程度来创建一个新的客户档案。酒店也可以根据顾客的人口统计学特征（比如年龄）来部署机器人。

这项研究表明, 重大灾难会影响顾客对新技术的态度和行为。 COVID-19的爆发导致客人更加关注酒店机器人的服务优势（降低传染概率）。

Aceptación de la tecnología antes y después de la pandemia del COVID-19: Servicios ofrecidos por robots en hoteles

Resumen

Esta investigación analiza la aceptación por parte de clientes del uso de robots en hoteles antes y después del comienzo de la pandemia del COVID-19, prestando una atención especial a si dicha pandemia ha tenido un efecto significativo sobre los niveles de aceptación de robots por parte de clientes en hoteles en China a raíz de la pandemia del COVID-19.

La muestra de este estudio incluye clientes de hoteles en China encuestados antes y después del brote de COVID-19, con 247 cuestionarios recogidos antes del brote y otros 601 después del mismo. Este estudio incluye una serie de hipótesis puestas a prueba adoptando un diseño de investigación de carácter pseudo-experimental.

Los resultados de este estudio apuntan a que el brote de COVID en China conllevó un incremento en la proporción de los clientes de hoteles propensos a aceptar el uso de robots en este contexto. Después de la pandemia, hubo un incremento en la percepción de la importancia de su utilidad, influencia social, actitud y valor de los robots en este contexto, mientras que descendió la percepción de la importancia de la facilidad del use de robots y antropomorfismo descendió. Como servicio sin necesidad de contacto físico, la utilidad de los robots en hoteles fue más valorada por los clientes Esto produjo una disminución en los requisitos de los usuarios en lo referente a la facilidad del uso de robots en hoteles. Además, los participantes en esta encuesta se mostraron más propensos a valorar la influencia sobre la sociedad del uso de robots.

La actitud de clientes de hoteles y su aceptación del uso de robots en este contexto, así como los servicios que éstos proveen están cambiando rápidamente. No obstante, aún no se sabe con certeza hasta que punto estos cambios son meramente efímeros y motivados por una actitud pragmática hacia la crisis creada por la pandemia del COVID-19.

El sector de la hostelería debería intentar desarrollar un perfil de clientes nuevo en lo referente a su grado de aceptación de los robots como parte de los servicios ofrecidos. Los hoteles deberían considerar el uso de robots en los servicios ofrecidos dependiendo de las características demográficas de sus clientes (ejem. Nivel de estudios y formación).

Este estudio demuestra que las crisis de gran magnitud, como lo es la pandemia actual de COVID-19, pueden afectar las actitudes y comportamientos del consumidor en lo referente al uso de nuevas tecnologías. La pandemia del COVID-19 ha llevado a muchos clientes de hoteles a prestar una mayor atención a las ventajas de los servicios ofrecidos por robots como forma de reducir las posibilidades de contagio.

Service robots are gradually becoming more anthropomorphic and intelligent. This research aims to investigate how anthropomorphic service robots with different levels of intelligence affect their human counterparts.

Two between-subject experimental studies were used to test whether different levels of service robot anthropomorphism with different levels of intelligence influence employees' morale and resistance to service robots.

Study 1 shows that the effect of service robot anthropomorphism (low vs. high) on employees' resistance and morale is mediated by perceived job-security threat. Study 2 validates this mediating effect and shows that it is moderated by the type of AI (mechanical vs. analytical). Specifically, when exposed to mechanical AI-powered service robots, employees exhibit a higher perceived job-security threat toward robots with a high (vs. low) degree of anthropomorphism. This moderating effect is not observed when employees are exposed to analytical AI-powered service robots. This moderated mediation effect is also found for the signing of a petition as the behavioral outcome.

Service firms considering the adoption of mechanical AI-powered service robots should choose a low (vs. high) anthropomorphic robot to reduce the sense of job-security threat felt by human employees, which subsequently increases their acceptance. However, if analytical AI-powered service robots with are to replace their human employees, the degree of anthropomorphism becomes irrelevant.

This is the first empirical study to explore how anthropomorphic service robots can influence human employees' evaluations and behaviors.

Anthropomorphism in Artificial Intelligence (AI)-powered devices is being used increasingly frequently in consumer-facing situations (e.g., AI Assistants such as Alexa, virtual agents in websites, call/chat bots, etc.), and therefore, it is essential to understand anthropomorphism in AI both to understand consequences for consumers and to optimize firms' product development and marketing. Extant literature is fragmented across several domains and is limited in the marketing domain. In this review, we aim to bring together the insights from different fields and develop a parsimonious conceptual framework to guide future research in fields of marketing and consumer behavior.

We conduct a review of empirical articles published until November 2021 in Financial Times Top 50 (FT50) journals as well as in 41 additional journals selected across several disciplinary domains: computer science, robotics, psychology, marketing, and consumer behavior.

Based on literature review and synthesis, we propose a three-step guiding framework for future research and practice on AI anthropomorphism.

Our proposed conceptual framework informs marketing and consumer behavior domains with findings accumulated in other research domains, offers important directions for future research, and provides a parsimonious guide for marketing managers to optimally utilize anthropomorphism in AI to the benefit of both firms and consumers.

We contribute to the emerging literature on anthropomorphism in AI in three ways. First, we expedite the information flow between disciplines by integrating insights from different fields of inquiry. Second, based on our synthesis of literature, we offer a conceptual framework to organize the outcomes of AI anthropomorphism in a tidy and concise manner. Third, based on our review and conceptual framework, we offer key directions to guide future research endeavors.

Based on appraisal theory and social response theory, this study aims to explore the mechanism of AI failure types on consumer recovery expectation from the perspective of service failure assessment and validate the moderate role of anthropomorphism level.

Three scenario-based experiments were conducted to validate the research model. First, to test the effect of robot service failure types on customer recovery expectation; second, to further test the mediating role of perceived controllability, perceived stability and perceived severity; finally, to verify the moderating effect of anthropomorphic level.

Non-functional failures reduce consumer recovery expectation compared to functional failures; perceived controllability and perceived severity play a mediating role in the impact of service failure types on recovery expectation; the influence of service failure types on perceived controllability and perceived severity is moderated by the anthropomorphism level.

The findings enrich the influence mechanism and boundary conditions of service failure types, and have implications for online enterprise follow-up service recovery and improvement of anthropomorphic design.

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.

The research aims to explore the interaction effect of consumer social class and service type on consumers' preference for robot services, as well as the mediating role of risk aversion in this interaction effect.

Experiment 1 is a field experiment with service type being the independent variable. The participants were divided into two groups based on the services they received (diagnostic dental services vs. hotel room services). 93 consumers participated voluntarily in the blind experiment and were asked if they would choose to allow a robot to perform the focal services. Experiment 2 employs a 2 × 2 factorial design: personal fitness trainer services at the gym vs wait staff services in a casual dining restaurant × higher- vs lower-social class, with 196 participants.

Results from the two experiments show that participants in the higher-social classes were more willing than participants in the lower-social classes to choose robot services in credence-based service settings. More significantly, risk aversion mediated the interaction effect of social class and service type on participants' preference for robot services.

Based on the credence-experience typology, this research is the first to discuss the weight of social class in consumer decision-making regarding preference for different types of robot services. Furthermore, by extending risk aversion to the robot services field, the current research sheds new light on this underlying mechanism that can inform future studies.

With the trend of adopting and studying artificial intelligence (AI) service robots at restaurants, the authors’ understanding of how customers perceive robots differently across restaurant segments remains limited. Therefore, building upon expectancy theory, this study aims to propose a trust-based mechanism to explain customers’ support for AI-based service robots.

For cross-segment validation, data were collected from online survey participants under the scenarios of experiencing AI service robots in luxury (n = 428), fine-dining (n = 420), casual (n = 409) and quick-service (n = 410) restaurant scenarios.

In all four segments, trust in technology increased willingness to accept AI service robots, which was then positively related to customers’ support for AI-based service robots. Meanwhile, customers’ AI performance expectancy mediated the relationship between trust in technology and willingness to accept AI service robots. On the other hand, at luxury, fine-dining and casual restaurants, males perceived a stronger positive relationship between trust in technology and AI performance expectancy. No generational differences were found in the four restaurant segments between trust in technology and AI performance expectancy.

To the best of the authors’ knowledge, this study is one of the first attempts in hospitality research to examine cross-segment validation of customers’ responses to AI-based service robots in the luxury, fine-dining, casual and quick-service restaurant segments.

The supposedly radical development of artificial intelligence (AI) has raised questions regarding the moral responsibility of it. In the sphere of business, they are translated into questions about AI and business ethics (BE) and corporate social responsibility (CSR). The purpos of this study is to conceptually reformulate these questions from the point of view of two possible aspect-changes, namely, starting from corporate social irresponsibility (CSI) and starting not from AIs incapability for responsibility but from its ability to imitate human CSR without performing typical human CSI.

The author draws upon the literature and his previous works on the relationship between AI and human CSI. This comparison aims to remodel the understanding of human CSI and AIs inability to be CSI. The conceptual remodelling is offered by taking a negative view on the relation. If AI can be made not to perform human-like CSI, then AI is at least less CSI than humans. For this task, it is necessary to remodel human and AI CSR, but AI does not have to be CSR. It is sufficient that it can be less CSI than humans to be more CSR.

The previously suggested remodelling of basic concepts in question leads to the conclusion that it is not impossible for AI to act or operate more CSI then humans simply by not making typical human CSIs. Strictly speaking, AI is not CSR because it cannot be responsible as humans can. If it can perform actions with a significantly lesser amount of CSI in comparison to humans, it is certainly less CSI.

This paper is only a conceptual remodelling and a suggestion of a research hypothesis. As such, it implies particular morality, ethics and the concepts of CSI and AI.

How this remodelling could be done in practice is an issue of future research.

The author delivers the paper on comparison between human and AI CSI which is not much discussed in literature.