Does a cute artificial intelligence assistant soften the blow? The impact of cuteness on customer tolerance of assistant service failure

Lv, Xingyang; Liu, Yue; Luo, Jingjing; Yu-qing, Liu; Li, Chunxiao

doi:10.1016/j.annals.2020.103114

Cited by 155 publications

(110 citation statements)

References 70 publications

Supporting

Mentioning

109

Contrasting

Order By: Relevance

“…From the perspective of multiple intelligence theory, the quality of the environment has a very important impact on the development of individuals [17,[20][21][22]. Whether it is the natural environment, the social environment, or the educational environment, it can affect and restrict the development of individuals to varying degrees from all aspects.…”

Section: Features Of Multiple Intelligence Eorymentioning

confidence: 99%

Optimization of Teaching Evaluation System for Football Professional Teachers Based on Multievaluation Model

Chen

2021

Complexity

View full text Add to dashboard Cite

The introduction of multiple intelligence theory into sports professional football teaching is a requirement of educational innovation, which helps to expand and play the multiple functions of football, and can effectively improve the comprehensive quality of football professional science. Under the perspective of multiple intelligence theory, college sports professional football teaching will focus on the all-round development of students, actively cultivate students’ multiple intelligence, and reflect the democratization, individualization, and diversification of teaching in the process of educational concept innovation. This article explains the origin and characteristics of the particle swarm optimization algorithm and discusses the application status of the PSO algorithm in detail. We introduced the standard PSO algorithm, including mathematical forms, iteration steps, and flowcharts. In addition, it also specifically describes the proposed new PSO improved algorithm, including the food chain strategy and reproduction strategy, as well as the implementation of the algorithm. Through analysis, it is concluded that the implementation and implementation of relevant systems is the guarantee for the sustained and sound development of campus football. The amount of football lessons is insufficient, and the classroom teaching effect is not ideal. Physical education teachers are acceptable, but the football professional knowledge training of physical education teachers needs to be strengthened. The selection and setting of the teaching content of football lessons lack systematic, scientific, and adaptable, and the teaching methods and teaching model concepts are backward. In the process of football teaching, teachers ignored the evaluation and assessment of students’ nonphysical and nonintellectual factors, and campus football activities did not achieve the expected goals.

show abstract

Section: Features Of Multiple Intelligence Eorymentioning

confidence: 99%

Optimization of Teaching Evaluation System for Football Professional Teachers Based on Multievaluation Model

Chen

2021

Complexity

View full text Add to dashboard Cite

show abstract

“…However, it is still clearly a robot and not a human, thus positioning it outside of Mori’s (1970) uncanny valley. Looking at robot-use in hotels, Tussyadiah and Park (2017) found anthropomorphism as particularly important for adopting service robots that interact directly with customers, while Lv et al (2021) emphasize the impact of “cuteness” on AI-assistant adoption in service contexts. Human-like features may evoke emotional responses such as feelings of familiarity or attachment (Murphy et al , 2019).…”

Section: Discussionmentioning

confidence: 99%

Spicing up hospitality service encounters: the case of Pepper™

Tuomi

Tussyadiah

Hanna

2021

IJCHM

View full text Add to dashboard Cite

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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™. Practical implications 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. Social implications 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. Originality/value 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.

show abstract

“…ITI and RTI are both measured by four items. The measurement items for ITI are “① improving existing products and services [ 20 ]; ② enhancing existing production efficiency [ 21 ]; ③ adding extended services to existing customers [ 22 ]; ④adapting the types of existing products and services [ 23 ].” RTI are measured by “①developing new products and services [ 25 ]; ②developing new markets [ 26 ]; ③opening up new sales channels [ 27 ]; ④introducing new processes and technologies [ 28 ].” The authors used exploratory factor analysis to optimize the questionnaire, eliminating the items with poor consistency and selecting eight items to measure EBMD and NBMD [ 29 ]. The measurement items of EBMD are “①high transaction speed [ 30 ]; ②low inventory costs of suppliers and partners [ 31 ]; ③simplifying transaction process [ 32 ]; ④reducing error rate [ 33 ]; ⑤reducing partner cost [ 34 ]; ⑥easy access for consumers to gain enterprise information [ 35 ]; ⑦providing product and service information to participants [ 36 ]; ⑧making transactions faster and more efficient [ 37 ]."…”

Section: Methodsmentioning

confidence: 99%

“…It provides new products for customers, increases the number of types of transactions ( T ↑) and provides for customers with unique products to increase the switching cost of customers, which creates a lock-in effect, so core companies can charge customers at higher price ( P ( t )↑) (at least initially). When it comes to suppliers or partners, core enterprises can first enter the market as a result of RTI, and gain the right to speak in the supply chain to have a high bargaining power [ 22 , 23 ]. This enables the enterprise to increase income ( Ri ( t )↑) and reduce expenditure ( Ci ( t )↓) in the process of cooperation with suppliers and partners.…”

Section: Related Workmentioning

confidence: 99%

Research on enterprise business model and technology innovation based on artificial intelligence

Zhao

et al. 2021

J Wireless Com Network

View full text Add to dashboard Cite

Small- and medium-sized enterprises (SEMs) are the important part of economic society whose innovation activities are of great significance for building innovative country. In order to investigate how technological innovation (TI) and business model design (BMD) affect the business performance of SMEs, samples of 268 SMEs in the artificial intelligence industry and hierarchical regression models are used in the analysis. The results indicate that TI, BMD, and the matching of them have different effects on the innovation of SMEs of different sizes. These findings are helpful for enriching the theory of the fit between TI and BMD and providing theoretical guidance for the innovation activities in SEMs.

show abstract

Does a cute artificial intelligence assistant soften the blow? The impact of cuteness on customer tolerance of assistant service failure

Cited by 155 publications

References 70 publications

Optimization of Teaching Evaluation System for Football Professional Teachers Based on Multievaluation Model

Optimization of Teaching Evaluation System for Football Professional Teachers Based on Multievaluation Model

Spicing up hospitality service encounters: the case of Pepper™

Research on enterprise business model and technology innovation based on artificial intelligence

Contact Info

Product

Resources

About