Developing a formative scale to measure consumers’ trust toward interaction with artificially intelligent (AI) social robots in service delivery

Hengxuan, Oscar; Jia, Shizhen; Li, Yafang; Gürsoy, Doğan

doi:10.1016/j.chb.2021.106700

Cited by 127 publications

(82 citation statements)

References 92 publications

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“…Except for a few studies that use experimental manipulation to verify a specific single dimension [19], [63]- [65], most studies have multiple dimensional constructs for r-service quality, ranging from 2 [16], [48] to 11 dimensions [52]. Due to the lack of consensus regarding constructs of r-service quality on its dimensions, many dimensions merely appear in specific studies or research contexts.…”

Section: R-service Quality Constructsmentioning

confidence: 99%

“…It refers to that a robot is humanlike regarding either physical appearance or psychological features, such as emotions and gestures [3]. Anthropomorphism plays an essential role in affecting human-robot interaction [1] and acts as a determinant in consumer trust [38], [52], willingness to use [3], [26], [47], and intention to (re)use [14], [28], [51]. Many studies exploring the impact of anthropomorphism draw upon Uncanny Valley Theory (UVT).…”

Section: R-service Quality Constructsmentioning

confidence: 99%

“…Notably, several dimensions that are tailored for robotics, particularly humanoid robots, take essential parts in r-service quality. These dimensions include anthropomorphism [1], [3], [14], [26], [28], [38], [47], [51], [52], perceived intelligence [14], [28], [38], [51], social presence [8], [49], autonomy [70], animacy [69], imitation [70], etc. Past studies usually allude that human appearance tends to trigger positive perceptions and attitudes towards robots [14], [23].…”

Section: With Conventional Service Qualitymentioning

confidence: 99%

“…Regarding quantitative studies, online surveys are the most widely used by researchers. The online distribution platforms include Amazon Mechanical Turk [26], [47], [48], [52] and personal networks [8], [14], [63], [64], whereas in-person surveys are among guests in hotels [5], [13], café or restaurant [11], [29], etc. Given the importance of survey administration, the administration mode needs to be clarified in more detail.…”

Section: Survey Administrationmentioning

confidence: 99%

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Instrument Development for R-Service Quality: A Literature Review

Lin¹

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Motivated by a paucity of knowledge on the measurement of robotic service (r-service) quality, the current study strives to review the existing literature on rservice quality, with a focus on the potential methodological issues of developing measurement instruments and identifying the dimensionality of r-service quality. With a content analysis of 55 articles, this study identifies several methodological limitations of existing studies in developing measurement scales of r-service quality. This review reveals that dimensions of r-service quality are prone to be contingent on specific contexts of service industry and service type. Several common dimensions regarding evaluating r-service are identified, including tangibility, responsiveness, reliability, empathy, assurance, ease of use/usability, usefulness, anthropomorphism, perceived intelligence, and social presence. This study is the first systematic literature review on r-service quality dimensionality.

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Section: R-service Quality Constructsmentioning

confidence: 99%

Section: R-service Quality Constructsmentioning

confidence: 99%

Section: With Conventional Service Qualitymentioning

confidence: 99%

Section: Survey Administrationmentioning

confidence: 99%

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Instrument Development for R-Service Quality: A Literature Review

Lin¹

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Consumers’ willingness to use robots in service encounters often depends on prior positive interactions with robots ( Chi et al, 2021 ). For the hospitality industry, this presents a cyclical obstacle: the low number of robots used by the hospitality industry results in a lack of familiarity with robots, which leads to less likelihood of prior consumer engagement with robots in the service setting, yielding a lack of propensity for consumer interaction or acceptance, resulting in a low adoption rate of robots, which then returns to a low number of robots in hospitality businesses.…”

Section: Introductionmentioning

confidence: 99%

Together We can Figure It out: Groups Find Hospitality Robots Easier to Use and Interact With Them More than Individuals

et al. 2021

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As robots are becoming more prevalent and entering hospitality settings, understanding how different configurations of individuals and groups interact with them becomes increasingly important for catering to various people. This is especially important because group dynamics can affect people’s perceptions of situations and behavior in them. We present research examining how individuals and groups interact with and accept a humanoid robot greeter at a real-world café (Study 1) and in an online study (Study 2). In each study, we separately examine interactions of individuals, groups that participants formed after they arrived at the café (new-formed groups), and groups that participants arrived with at the café (pre-formed groups). Results support prior findings that groups are more likely to interact with a public robot than individuals (Study 1). We also report novel findings that new-formed groups interacted more with the robot than pre-formed groups (Study 1). We link this with groups perceiving the robot as more positive and easier to use (Study 2). Future research should examine perceptions of the robot immediately after interaction and in different hospitality contexts.

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Artificial intelligence in marketing: A meta‐analytic review

Mehta¹,

Jebarajakirthy

Maseeh

et al. 2022

Psychology and Marketing

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This study synthesizes the artificial intelligence literature into a Meta-analytic framework based on the theory of reasoned action and the unified theory of acceptance and use of technology 2, and examines concrete relationships between the constructs of this framework. This meta-review also performed a moderation analysis to investigate the possible reasons for inconsistent findings across studies.The findings suggest that three methodological moderators (sample type, gender dominance, and publication type), and one contextual moderator (level of country's technology advancement) lead to inconsistencies in the relationships between study constructs. Academically, this review synthesizes the artificial intelligence literature and resolves inconsistencies in the literature and also adds constructs to both theory of reasoned action and the unified theory of acceptance and use of technology 2.

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Developing a formative scale to measure consumers’ trust toward interaction with artificially intelligent (AI) social robots in service delivery

Cited by 127 publications

References 92 publications

Instrument Development for R-Service Quality: A Literature Review

Instrument Development for R-Service Quality: A Literature Review

Together We can Figure It out: Groups Find Hospitality Robots Easier to Use and Interact With Them More than Individuals

Artificial intelligence in marketing: A meta‐analytic review

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