The history of academic research in marketing and its implications for the future

Ratchford, Brian T.

doi:10.1108/sjme-11-2019-0096

Cited by 27 publications

(22 citation statements)

References 369 publications

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“…Huang and Rust (2018) predict that robots will not only replace mechanical jobs, but also those involving analytical, intuitive and empathetic skills. With the application of automation in the frontline, such as in retailing and customer service operations, the study of robots and AI has become an incipient field of research in marketing (Grewal et al, 2017; Ratchford, 2020). Much of the current contributions are conceptual in nature though.…”

Section: Literature Backgroundmentioning

confidence: 99%

Examining the effects of robots' physical appearance, warmth, and competence in frontline services: The Humanness‐Value‐Loyalty model

Belanche

Casaló

Schepers

et al. 2021

Psychology and Marketing

162

132

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Because of continuous improvements in their underlying technologies, customers perceive frontline robots as social actors with a high level of humanness, both in appearance and behavior. Advancing from mere theoretical contributions to this study field, this article proposes and empirically validates the humanness‐value‐loyalty model (HVL model). This study analyzes to what extent robots' perceived physical human‐likeness, perceived competence, and perceived warmth affect customers' service value expectations and, subsequently, their loyalty intentions. Following two pretests to select the most suitable robots and ensure scenario realism, data were collected by means of a vignette experimental study and analyzed using the partial least squares method. The results reveal that human‐likeness positively affects four dimensions of service value expectations. Perceived competence of the robot influences mainly utilitarian expectations (i.e., functional and monetary value), while perceived warmth influences relational expectations (i.e., emotional value). Interestingly, and contrary to theoretical predictions, the influence of the robot's warmth on service value expectations is more pronounced for customers with a lower need for social interaction. In sum, this study contributes to a better understanding of customers' reactions to artificial intelligence‐enabled technologies with humanized cognitive capabilities and also suggests interesting research avenues to advance on this emerging field.

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Section: Literature Backgroundmentioning

confidence: 99%

Examining the effects of robots' physical appearance, warmth, and competence in frontline services: The Humanness‐Value‐Loyalty model

Belanche

Casaló

Schepers

et al. 2021

Psychology and Marketing

162

132

View full text Add to dashboard Cite

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“…Hospitality employees provide affective experiences to customers, whereas robots do not (Chan and Tung, 2019). Despite living in the automation age (Ratchford, 2020), machines do not fully substitute for humans yet (Ghazizadeh et al, 2012) and provoke a loss of human contact during the service delivery, a key element in tourism and hospitality industries (Leung, 2019;Tussyadiah, 2020). Therefore, the higher the social presence, and hence the more human contact that the customer expects to lose because of automation, the lower the attitude toward the robot must be.…”

Section: Social Presencementioning

confidence: 99%

Service robots and COVID-19: exploring perceptions of prevention efficacy at hotels in generation Z

Romero

Lado

2021

IJCHM

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Purpose COVID-19 is expected to enhance hospitality robotization because frontline robots facilitate social distancing, lowering contagion risk. Investing in frontline robots emerges as a solution to recover customer trust and encourage demand. However, we ignore how customers perceive these initiatives and, therefore, their efficacy. Focusing on robot employment at hotels and on Generation Z customers, this study aims to analyze guests’ perceptions about robots’ COVID-19 prevention efficacy and their impact on booking intentions. Design/methodology/approach This study tests its hypotheses combining an experimental design methodology with partial least squares. Survey data from 711 Generation Z individuals in Spain were collected in 2 periods of time. Findings Generation Z customers consider that robots reduce contagion risk at hotels. Robot anthropomorphism increases perceived COVID-19 prevention efficacy, regardless of the context where the robots are used. Robots’ COVID-19 prevention efficacy provokes better attitudes and higher booking intentions. Research limitations/implications The sampling method used in this research impedes this study’s results generalization. Further research could replicate this study using random sampling methods to ensure representativeness, even for other generational cohorts. Practical implications Employing robots as a COVID-19 prevention measure can enhance demand, especially if robots are human-like. Hoteliers need to communicate that robots can reduce contagion risk, particularly in markets more affected by COVID-19. Robots must be employed in low social presence contexts. Governments could encourage robotization by financially supporting hotels and publicly acknowledging its benefits regarding COVID-19 prevention. Originality/value This study combines preventive health, robotics and hospitality literature to study robot implementation during the COVID-19 pandemic, focusing on Generation Z guests – potential facilitators of robot diffusion.

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“…From the above considerations, it appears that more research on human–IVA interaction is needed (Belanche et al , 2020a; Ratchford, 2020; Tussyadiah, 2020). A fundamental driver of the quality of close relationships is how individuals relate to each other and how they are attached (Eastwick and Finkel, 2008).…”

Section: Introductionmentioning

confidence: 99%

Stand by me: analyzing the tourist–intelligent voice assistant relationship quality

Loureiro

Japutra

Molinillo

et al. 2021

IJCHM

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Purpose This paper aims to explore tourist perceived value and attachment to intelligent voice assistants (IVAs) as antecedents of the quality of the human–IVA relationship in the hospitality domain. This research also examines the moderating role of psychological factors (self-esteem) and knowledge factors (past experience and technology expertise) in the relationships between antecedents and relationship quality. Design/methodology/approach The researchers conducted two quantitative studies, collecting data via online surveys in Mechanical Turk (n1 = 124 and n2 = 281). The proposed model was tested using partial least squares structural equation modeling. Findings The first study uncovers that tourist perceived value is the main influence on the quality of the relationship between tourists and IVAs. The second study confirms the direct relationships of the first and shows that self-esteem and technology expertise act as moderators. Practical implications This study advances the understanding of the tourism and hospitality stakeholders in using modern technologies (e.g. IVAs). Through comprehending the relationship building between individuals and IVAs, the stakeholders will be able to craft better strategies. Originality/value The study extends the attachment and social exchange theories to the tourist–IVA relationship context. Specifically, this research demonstrates the impact of tourist perceived value on the quality of the relationship with the IVA. It also points out that tourists’ self-esteem and technology expertise can weaken the tourist–IVA relationship.

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The history of academic research in marketing and its implications for the future

Cited by 27 publications

References 369 publications

Examining the effects of robots' physical appearance, warmth, and competence in frontline services: The Humanness‐Value‐Loyalty model

Examining the effects of robots' physical appearance, warmth, and competence in frontline services: The Humanness‐Value‐Loyalty model

Service robots and COVID-19: exploring perceptions of prevention efficacy at hotels in generation Z

Stand by me: analyzing the tourist–intelligent voice assistant relationship quality

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