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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.

Artificial intelligence (AI) has a large number of applications at the industry and user levels. However, AI's uniqueness neglect is becoming an obstacle in the further application of AI. Based on the theory of innovation resistance, this paper aims to explore the effect of AI's uniqueness neglect on consumer resistance to AI.

The authors tested four hypothesis across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI's uniqueness neglect leads to consumer resistance to AI; Studies 2 focused on the role of human–AI interaction trust as an underlying driver of resistance to medical AI. Study 3–4 provided process evidence by way of a measured moderator, testing whether participants with a greater sense of non-verbal human–AI communication are more reluctant to have consumer resistance to AI.

The authors found that AI's uniqueness neglect increased users' resistance to AI. This occurs because the uniqueness neglect of AI hinders the formation of interaction trust between users and AI. The study also found that increasing the gaze behavior of AI and increasing the physical distance in the interaction can alleviate the effect of AI's uniqueness neglect on consumer resistance to AI.

This paper explored the effect of AI's uniqueness neglect on consumer resistance to AI and uncovered human–AI interaction trust as a mediator for this effect and gaze behavior and physical distance as moderators for this effect.

The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.

This essay asks: How can we understand and theorise the impacts of robots and Artificial Intelligence (AI) on everyday life based on Radical Humanism? How can Lefebvre's ideas be used to reveal the ideological character of contemporary accounts of the impacts of robots and AI on society? It engages with rather unknown works of the Radical Humanist Henri Lefebvre on the sociology and philosophy of technology such as Vers le cybernanthrope (Towards the Cybernanthrope). Foundations of a Lefebvrian, dialectical, Radical Humanist approach to the sociology and philosophy of technology are presented. This essay introduces Lefebvre's notion of the cybernanthrope and sets it in relation to robots and AI in contemporary society. Based on Lefebvre's critique of the cybernanthrope, this chapter develops foundations of the ideology critique of robots and AI in digital capitalism. It discusses examples of technological deterministic and social constructivist thought in the context of robotics, AI, and cyborgs and argues for an alternative, Lefebvrian, dialectical approach. This essay situates Humanism in the context of computing, AI and robotics. The chapter advances a Lefebvrian Radical Humanism by engaging in analyses of AI and robots in Post-humanism, Transhumanism, techno-deterministic approaches, social construction of technology approaches, techno-optimism, techno-pessimism, acceleratonism, the mass unemployment hypothesis and Spike Jonze's movie Her. This chapter shows that the major lesson we can learn from the Radical Humanist sociology of technology and Henri Lefebvre's works on technology is that Radical Humanism helps creating and sustaining technologies for the many, not the few. This insight remains of high relevance in the age of digital capitalism, smart robots and AI.

Drawing on the Service Robot Acceptance Model (sRAM) proposed by Wirtz et al. (2018), this study aims to examine how functional and social-emotional antecedents affect relational elements and the critical functions that trust and rapport play in robot acceptance in hotel services. Additionally, this study incorporates customer characteristics into the modified sRAM.

Consistent partial least squares (PLSc) was used to test the proposed model utilizing data collected from 456 Chinese customers.

The results indicated that effort expectancy and performance expectancy positively affect hotel guests’ trust toward and rapport with service robots. However, the effect of social influence on trust and rapport is insignificant. Additionally, perceived humanness and perceived social interactivity positively influence rapport, and perceived social presence positively affects both trust and rapport. Furthermore, trust and rapport positively influence hotel guests’ acceptance of service robots. The results also revealed the moderating role of age.

This study contributes to service robot literature by providing insights into how functional and social-emotional factors affect relational factors and the key role of relational factors in robot acceptance based on the sRAM. This study also advances this body of knowledge by highlighting the moderating effect of age.

基于Wirtz等人（2018）提出的服务机器人接受模型（sRAM）, 本研究旨在探讨功能性和社会-情感性前因如何影响关系元素, 以及信任和融洽在酒店服务中对机器人接受度的关键作用。此外, 本研究将顾客特征纳入修改后的 sRAM 中。

采用一致性偏最小二乘法（PLSc）对来自456名中国顾客的数据进行分析，以验证所提出的模型。

结果表明, 努力期望和绩效期望积极影响酒店客人对服务机器人的信任和融洽。然而, 社会影响对信任和融洽的影响不显著。此外, 感知人性化和感知社会互动积极影响融洽, 感知社会临场感积极影响信任和融洽。此外, 信任和融洽积极影响酒店客人对服务机器人的接受度。结果还揭示了年龄的调节作用。

本研究通过提供关于功能性和社会-情感性因素如何影响关系因素以及关系因素在机器人接受度中的关键作用的见解, 为服务机器人文献做出了贡献。本研究还通过强调年龄的调节效应, 推进了这一知识体系的发展。

Artificial intelligence (AI) will be performing 52% of the tasks in companies by 2025. The increasing adoption of AI is generating technological turbulence in the business environment. Previous studies have also shown that employees are aware of the high risk of losing their jobs when being replaced by AI. The risk of employees engaging in opportunistic behaviors, such as knowledge hiding, is thus fairly high. Therefore, the aim of this paper is to analyze the mediating effect of employee’s AI awareness on the relationship between technological turbulence generated by AI and the three types of knowledge hiding: evasive hiding, playing dumb and rationalized hiding.

Structural equations by the partial least squares method were used to test the proposed research model.

The most interesting finding is that employee’s AI and robotics awareness fulfills almost all mediating functions in the relationship between technological turbulence generated by AI and the three types of knowledge hiding.

The results show that knowledge hiding in the digital age is first and foremost a strategy by employees to sabotage and induce failure in process automation, to reduce the risk of being replaced in the workplace by AI. This study indicates that employees are willing to hide knowledge in all possible ways when perception that AI is a threat to their job increases. In other words, technological turbulence generated by AI and employee’s AI awareness are the two great new triggers of knowledge hiding in the digital age.

This study profiles and segments potential tourists on the basis of their various attitudes toward artificial intelligence (AI) services. Furthermore, this study distinguishes descriptors among the different clusters, such as preference for using diverse AI services, overall image of AI services, willingness to use AI services (WUAI), willingness to pay more for AI services (WPAI) in tourism and hospitality, and characteristics of respondents.

An online survey was conducted in South Korea. Data on 758 potential tourists were used for K-means cluster analysis.

This study identified three distinct tourist segments with differentiated attitudes toward AI services: the group aspiring to use or fantasizing about AI services (Cluster 1), the group being knowledgeable and supportive of AI services (Cluster 2), and the group having low interest about AI services (Cluster 3).

Members of Cluster 2 were the most marketable as this segment exhibited the greatest knowledge of and support for AI services, while Cluster 1 would be an ideal segment to launch and test novel AI services.

This study extends the authors’ knowledge of AI scholarship by unpacking the existing market segments, which could be tapped to sustain AI penetration in the tourism industry. Hence, this study contributes to existing debates on AI scholarship, which is predominated by conceptual reflections and issues of AI services in the tourism and hospitality field.

The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.

The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.

Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.

The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.

The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.