How do customers respond to robotic service? A scenario-based study from the perspective of uncertainty reduction theory
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A4 Artikkeli konferenssijulkaisussa
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en
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Proceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021, pp. 576-585, Proceedings of the Annual Hawaii International Conference on System Sciences ; Volume 2020-January
Abstract
Confronted with an increasing popularization and advancement of applying artificial intelligence in robotic technology, practitioners in the service sector have been increasingly deploying service robots in their operations. Motivated by a paucity of knowledge on how consumers would respond to the robotic service, this study establishes on the uncertainty reduction theory to advance a research model that seeks to unveil how both customer trait and service characteristic affect customers' revisit intention to robotic service via perceived risk. Based on a scenario-based experiment with 190 responses in the hotel reception service context, our results reveal that perceived risk partially mediates the relationship between personal innovativeness and service revisit intention, so does between service heterogeneity and revisit intention. Furthermore, the service context, i.e., whether the prior service experience satisfies the customer, can moderate the relationship between personal innovativeness (service heterogeneity) and perceived risk. This study also draws related theoretical and practical implications.Description
Publisher Copyright: © 2021 IEEE Computer Society. All rights reserved.
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Lin, Y, Zhou, X & Fan, W 2021, How do customers respond to robotic service? A scenario-based study from the perspective of uncertainty reduction theory. in T X Bui (ed.), Proceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021. Proceedings of the Annual Hawaii International Conference on System Sciences, vol. 2020-January, Hawaii International Conference on System Sciences, pp. 576-585, Annual Hawaii International Conference on System Sciences, Maui, Hawaii, United States, 05/01/2021. < http://hdl.handle.net/10125/70681 >