119953 20250722154011.0 doi 10.1177/10946705221107704 sideral 129960 ART-2022-129960 eng Schepers, Jeroen How Smart Should a Service Robot Be? 2022 Access copy available to the general public Unrestricted Service robots are taking over the frontline. They can possess three types of artificial intelligence (AI): mechanical, thinking, and feeling AI. Although these intelligences determine how service robots can help customers, not much is known about how customers respond to robots of different intelligence. This paper addresses this gap, builds on the appraisal theory of emotions, and employs three online experiments and one field study to demonstrate that customers have different emotional responses to the three types of AI. Particularly, the influence of AI on positive emotions becomes stronger as the AI type becomes more sophisticated. That is, feeling AI relates more strongly to positive emotions than mechanical AI. Also, feeling AI and thinking AI increase spending and loyalty intention through customers'' positive emotions. We also identify important contingency effects of service tiers: mechanical AI is more suitable for low-cost firms, whereas feeling AI mainly benefits full-service providers. Remarkably, none of the three intelligences are directly related to negative emotions; perceived robot autonomy is an important mediator in these relationships. The findings yield concrete managerial guidance as to how smart a service robot should be by pinpointing the right type of AI given the market segment of the service provider. info:eu-repo/grantAgreement/ES/DGA-FSE/S20-20R METODO Research Group info:eu-repo/grantAgreement/ES/MICIU/PID2019-105468RB-I00 info:eu-repo/semantics/openAccess by-nc http://creativecommons.org/licenses/by-nc/3.0/es/ 12.4 2022 BUSINESS 10 / 154 = 0.065 2022 Q1 T1 4.981 2022 Information Systems 2022 Q1 Sociology and Political Science 2022 Q1 Organizational Behavior and Human Resource Management 2022 Q1 17.2 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Belanche, Daniel Universidad de Zaragoza (orcid)0000-0002-2291-1409 Casaló, Luis V. Universidad de Zaragoza (orcid)0000-0002-9643-2814 Flavián, Carlos Universidad de Zaragoza (orcid)0000-0001-7118-9013 4011 095 Universidad de Zaragoza Dpto. Direc.Mark.Inves.Mercad. Área Comerci.Investig.Mercados 25, 4 (2022), 565-582 J. serv. res. Journal of Service Research 1094-6705 1468706 http://zaguan.unizar.es/record/119953/files/texto_completo.pdf Versión publicada 2817293 http://zaguan.unizar.es/record/119953/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:119953 articulos driver 2025-07-22-15:35:44 ARTICLE