Satisfação do cliente na prestação de serviços com inteligência artificial: Um estudo meta-analítico

Aguiar-Costa, Laura M.; Cunha, Carlos A. X. C.; Silva, Wallysson K. M.; Abreu, Nelsio R.

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Brasil

RAM. Revista de Administração Mackenzie

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Sumário

Special Issue • RAM, Rev. Adm. Mackenzie 23 (06) • 2022 • https://doi.org/10.1590/1678-6971/eRAMD220003.en copiar

Satisfação do cliente na prestação de serviços com inteligência artificial: Um estudo meta-analítico

Autoria SCIMAGO INSTITUTIONS RANKINGS

RESUMO

Objetivo:

O presente estudo tem como objetivo identificar os principais construtos antecedentes e consequentes que compõem a satisfação do consumidor na prestação de serviços que utilizam inteligência artificial (IA) e suas magnitudes.

Originalidade/valor:

Este estudo busca preencher uma lacuna advinda da escassez de pesquisas meta-analíticas sobre a prestação de serviços com IA e sua relação com a satisfação do consumidor.

Design/metodologia/abordagem: O presente trabalho adotou o método meta-analítico e o seu desenvolvimento seguiu três fases: 1. pesquisa; 2. coleta; e 3. codificação e análise de dados. Foram analisados 19 artigos publicados em periódicos de relevância internacional no período de janeiro de 2000 e dezembro de 2020, presentes nas plataformas Web of Science e Science Direct, que totalizaram 128 observações e 28 relações.

Resultados:

Foram identificados cinco construtos antecedentes e um construto consequente. A partir disso, construiu-se um modelo integrado para ilustrar as relações da satisfação do consumidor em serviços inteligentes. Os resultados alcançados demonstram que a satisfação do consumidor na prestação de serviços está significantemente correlacionada a adoção de inteligência artificial. Em suma, a avaliação quantitativa integrada que foi realizada neste estudo, visa contribuir com futuras evidências empíricas de tal maneira que ocorra um aumento do alcance dos estudos em inteligência artificial e satisfação do consumidor, a partir da análise dos seguintes construtos: valor percebido, recursos percebidos, percepção da qualidade, orientação mercadológica, identificação com o serviço e comportamento de uso de AI em serviços.

Palavras-chave
inteligência artificial; serviços; satisfação do consumidor; meta-análise; modelo integrado

Construct	Definition
Perceived value	Set of values that impact consumers’ perceptions of the use of AI in the services provided
Components	Definitions	References
Trust	Intentions and behaviors that indicate in the security that the service has added value from the use of AI.	Ameen et al. (2021)Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. http://doi.org/10.1016/j.chb.2020.106548 http://doi.org/10.1016/j.chb.2020.106548... , Purwanto et al. (2020)Purwanto, P., Kuswandi, K., & Fatmah, F. (2020). Interactive Applications with Artificial Intelligence: The Role of Trust among Digital Assistant Users. Journal of the National Research University Higher School of Economics, 14(2), 64-75. https://doi.org/10.17323/2500-2597.2020.2.64.75 https://doi.org/10.17323/2500-2597.2020.... , Chen et al. (2021)Chen, T., Guo, W., Gao, X., & Liang, Z. (2021). AI-based self-service technology in public service delivery: User experience and influencing factors. Government Information Quarterly, 38(4), 101520. https://doi.org/10.1016/j.giq.2020.101520 https://doi.org/10.1016/j.giq.2020.10152... , Chiang and Trimi (2020)Chiang, A. H., & Trimi, S. (2020). Impacts of service robots on service quality. Service Business, 14, 439-459. https://doi.org/10.1007/s11628-020-00423-8 https://doi.org/10.1007/s11628-020-00423... , Payne et al. (2018)Payne, E. M., Peltier, J. W., & Barger, V. A. (2018). Mobile banking and AI-enabled mobile banking: The differential effects of technological and non-technological factors on digital natives’ perceptions and behavior. Journal of Research in Interactive Marketing, 12(3), 328-346. https://doi.org/10.1108/jrim-07-2018-0087 https://doi.org/10.1108/jrim-07-2018-008... , Pillai et al. (2020), Zeinalizadeh et al. (2015)Zeinalizadeh, N., Shojaie, A. A., & Shariatmadari, M. (2015). Modeling and analysis of bank customer satisfaction using neural networks approach. International Journal of Bank Marketing, 33(6), 717-732. https://doi.org/10.1108/IJBM-06-2014-0070 https://doi.org/10.1108/IJBM-06-2014-007... , Kervenoael et al. (2020)Kervenoael, R. D., Hasan, R., Schwob, A., & Goh, E. (2020). Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots. Tourism Management, 78, 104042. https://doi.org/10.1016/j.tourman.2019.104042 https://doi.org/10.1016/j.tourman.2019.1... .
Control	Perception of control that the consumer has that he can influence the service that relies on an AI.	Purwanto et al. (2020)Purwanto, P., Kuswandi, K., & Fatmah, F. (2020). Interactive Applications with Artificial Intelligence: The Role of Trust among Digital Assistant Users. Journal of the National Research University Higher School of Economics, 14(2), 64-75. https://doi.org/10.17323/2500-2597.2020.2.64.75 https://doi.org/10.17323/2500-2597.2020.... , Kervenoael et al. (2020)Kervenoael, R. D., Hasan, R., Schwob, A., & Goh, E. (2020). Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots. Tourism Management, 78, 104042. https://doi.org/10.1016/j.tourman.2019.104042 https://doi.org/10.1016/j.tourman.2019.1... , Pillai et al. (2020)Pillai, R., Sivathanu, B., & Dwivedi, Y. K. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services, 57, 102207. https://doi.org/10.1016/j.jretconser.2020.102207 https://doi.org/10.1016/j.jretconser.202... , Söderlund (2020)Söderlund, M. (2020). Employee encouragement of self-disclosure in the service encounter and its impact on customer satisfaction. Journal of Retailing and Consumer Services, 53, 102001. https://doi.org/10.1016/j.jretconser.2019.102001 https://doi.org/10.1016/j.jretconser.201... .
Empathy	Perception of care from a service delivery that uses AI.	Chiang and Trimi (2020)Chiang, A. H., & Trimi, S. (2020). Impacts of service robots on service quality. Service Business, 14, 439-459. https://doi.org/10.1007/s11628-020-00423-8 https://doi.org/10.1007/s11628-020-00423... , Gursoy et al. (2019), Lin et al. (2020)Lin, H., Chi, O. H., & Gursoy, D. (2020). Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing & Management, 29(5), 530-549. https://doi.org/10.1080/19368623.2020.1685053 https://doi.org/10.1080/19368623.2020.16... , Pillai et al. (2020)Pillai, R., Sivathanu, B., & Dwivedi, Y. K. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services, 57, 102207. https://doi.org/10.1016/j.jretconser.2020.102207 https://doi.org/10.1016/j.jretconser.202... , Prentice et al. (2020)Prentice, C., Lopes, S. D., & Wang, X. (2020). The impact of artificial intelligence and employee service quality on customer satisfaction and loyalty. Journal of Hospitality Marketing & Management, 29(7), 739-756. https://doi.org/10.1080/19368623.2020.1722304 https://doi.org/10.1080/19368623.2020.17... , Qiu et al. (2020), Söderlund (2020)Söderlund, M. (2020). Employee encouragement of self-disclosure in the service encounter and its impact on customer satisfaction. Journal of Retailing and Consumer Services, 53, 102001. https://doi.org/10.1016/j.jretconser.2019.102001 https://doi.org/10.1016/j.jretconser.201... , Zhu and Chang (2020)Zhu, D. H., & Chang, Y. P. (2020). Robot with humanoid hands cooks food better? Effect of robotic chef anthropomorphism on food quality prediction. International Journal of Contemporary Hospitality Management, 32(3), 1367-1383. https://doi.org/10.1108/IJCHM-10-2019-0904 https://doi.org/10.1108/IJCHM-10-2019-09... , Kervenoael et al. (2020)Kervenoael, R. D., Hasan, R., Schwob, A., & Goh, E. (2020). Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots. Tourism Management, 78, 104042. https://doi.org/10.1016/j.tourman.2019.104042 https://doi.org/10.1016/j.tourman.2019.1... .
Hedonism	Perception of pleasure associated with a service that uses AI.	Gursoy et al. (2019)Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008 https://doi.org/10.1016/j.ijinfomgt.2019... , Lin et al. (2020)Lin, H., Chi, O. H., & Gursoy, D. (2020). Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing & Management, 29(5), 530-549. https://doi.org/10.1080/19368623.2020.1685053 https://doi.org/10.1080/19368623.2020.16... .
Negative effects	Perception that using AI in service may not generate value.	Ameen et al. (2021)Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. http://doi.org/10.1016/j.chb.2020.106548 http://doi.org/10.1016/j.chb.2020.106548... , Pillai et al. (2020)Pillai, R., Sivathanu, B., & Dwivedi, Y. K. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services, 57, 102207. https://doi.org/10.1016/j.jretconser.2020.102207 https://doi.org/10.1016/j.jretconser.202... , Pillai and Sivathanu (2020)Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199-3226. https://doi.org/10.1108/IJCHM-04-2020-0259 https://doi.org/10.1108/IJCHM-04-2020-02... , Sorderlund and Trivedi (2019)Trivedi, J. (2019). Examining the customer experience of using banking chatbots and its impact on brand love: The moderating role of perceived risk. Journal of internet Commerce, 18(1), 91-111. https://doi.org/10.1080/15332861.2019.1567188 https://doi.org/10.1080/15332861.2019.15... .
Construct	Definition
Perceived value	Set of values that impact consumers’ perceptions of the use of AI in the services provided
Components	Definitions	References
Utility	Perception that there is useful value in services that make use of AI.	Payne et al. (2018)Payne, E. M., Peltier, J. W., & Barger, V. A. (2018). Mobile banking and AI-enabled mobile banking: The differential effects of technological and non-technological factors on digital natives’ perceptions and behavior. Journal of Research in Interactive Marketing, 12(3), 328-346. https://doi.org/10.1108/jrim-07-2018-0087 https://doi.org/10.1108/jrim-07-2018-008... , Prentice et al. (2020)Prentice, C., Lopes, S. D., & Wang, X. (2020). The impact of artificial intelligence and employee service quality on customer satisfaction and loyalty. Journal of Hospitality Marketing & Management, 29(7), 739-756. https://doi.org/10.1080/19368623.2020.1722304 https://doi.org/10.1080/19368623.2020.17... , Zeinalizadeh et al. (2015)Zeinalizadeh, N., Shojaie, A. A., & Shariatmadari, M. (2015). Modeling and analysis of bank customer satisfaction using neural networks approach. International Journal of Bank Marketing, 33(6), 717-732. https://doi.org/10.1108/IJBM-06-2014-0070 https://doi.org/10.1108/IJBM-06-2014-007... , Kervenoael et al. (2020).
Construct	Definition
Perceived resources	Tangible and intangible resources perceived in customer service from the use of AI
Components	Definitions	References
Access	Perception of tangibility in a service using AI.	Chiang and Trimi (2020)Chiang, A. H., & Trimi, S. (2020). Impacts of service robots on service quality. Service Business, 14, 439-459. https://doi.org/10.1007/s11628-020-00423-8 https://doi.org/10.1007/s11628-020-00423... , Zhu and Chang (2020)Zhu, D. H., & Chang, Y. P. (2020). Robot with humanoid hands cooks food better? Effect of robotic chef anthropomorphism on food quality prediction. International Journal of Contemporary Hospitality Management, 32(3), 1367-1383. https://doi.org/10.1108/IJCHM-10-2019-0904 https://doi.org/10.1108/IJCHM-10-2019-09... , Kervenoael et al. (2020)Kervenoael, R. D., Hasan, R., Schwob, A., & Goh, E. (2020). Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots. Tourism Management, 78, 104042. https://doi.org/10.1016/j.tourman.2019.104042 https://doi.org/10.1016/j.tourman.2019.1... .
Customization	Perception that it is possible to adapt a service with AI to the consumer’s needs.	Ameen et al. (2021)Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. http://doi.org/10.1016/j.chb.2020.106548 http://doi.org/10.1016/j.chb.2020.106548... , Chen et al. (2021)Chen, T., Guo, W., Gao, X., & Liang, Z. (2021). AI-based self-service technology in public service delivery: User experience and influencing factors. Government Information Quarterly, 38(4), 101520. https://doi.org/10.1016/j.giq.2020.101520 https://doi.org/10.1016/j.giq.2020.10152... , Pillai et al. (2020)Pillai, R., Sivathanu, B., & Dwivedi, Y. K. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services, 57, 102207. https://doi.org/10.1016/j.jretconser.2020.102207 https://doi.org/10.1016/j.jretconser.202... , Söderlund (2020)Söderlund, M. (2020). Employee encouragement of self-disclosure in the service encounter and its impact on customer satisfaction. Journal of Retailing and Consumer Services, 53, 102001. https://doi.org/10.1016/j.jretconser.2019.102001 https://doi.org/10.1016/j.jretconser.201... .
Usability	Perception that there are facilities in the effort employed to use the service with AI.	Chen et al. (2021)Chen, T., Guo, W., Gao, X., & Liang, Z. (2021). AI-based self-service technology in public service delivery: User experience and influencing factors. Government Information Quarterly, 38(4), 101520. https://doi.org/10.1016/j.giq.2020.101520 https://doi.org/10.1016/j.giq.2020.10152... , Qiu et al. (2020)Qiu, H., Li, M., Shu, B., & Bai, B. (2020). Enhancing hospitality experience with service robots: The mediating role of rapport building. Journal of Hospitality Marketing & Management, 29(3), 247-268. https://doi.org/10.1080/19368623.2019.1645073 https://doi.org/10.1080/19368623.2019.16... , Zeinalizadeh et al. (2015)Zeinalizadeh, N., Shojaie, A. A., & Shariatmadari, M. (2015). Modeling and analysis of bank customer satisfaction using neural networks approach. International Journal of Bank Marketing, 33(6), 717-732. https://doi.org/10.1108/IJBM-06-2014-0070 https://doi.org/10.1108/IJBM-06-2014-007... .
Performance	Expectation that the service using AI will meet expected performance.	Purwanto et al. (2020)Purwanto, P., Kuswandi, K., & Fatmah, F. (2020). Interactive Applications with Artificial Intelligence: The Role of Trust among Digital Assistant Users. Journal of the National Research University Higher School of Economics, 14(2), 64-75. https://doi.org/10.17323/2500-2597.2020.2.64.75 https://doi.org/10.17323/2500-2597.2020.... , Gursoy et al. (2019)Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008 https://doi.org/10.1016/j.ijinfomgt.2019... , Lin et al. (2019).
Service	Expectation that employees are trained to provide a service that uses AI.	Prentice and Nguyen (2020)Prentice, C., & Nguyen, M. (2020). Engaging and retaining customers with AI and employee service. Journal of Retailing and Consumer Services, 56, 102186. https://doi.org/10.1016/j.jretconser.2020.102186 https://doi.org/10.1016/j.jretconser.202... , Prentice et al. (2020), Söderlund (2020)Söderlund, M. (2020). Employee encouragement of self-disclosure in the service encounter and its impact on customer satisfaction. Journal of Retailing and Consumer Services, 53, 102001. https://doi.org/10.1016/j.jretconser.2019.102001 https://doi.org/10.1016/j.jretconser.201... , Zeinalizadeh et al. (2015)Zeinalizadeh, N., Shojaie, A. A., & Shariatmadari, M. (2015). Modeling and analysis of bank customer satisfaction using neural networks approach. International Journal of Bank Marketing, 33(6), 717-732. https://doi.org/10.1108/IJBM-06-2014-0070 https://doi.org/10.1108/IJBM-06-2014-007... .
Construct	Definition
Quality perception	Perceptions of the quality involved in the services provided with the adoption of AI
Components	Definitions	References
Quality in the use of AI	Evaluation of the quality perceived by the adoption of AI in the execution of the service.	Ameen et al. (2021)Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. http://doi.org/10.1016/j.chb.2020.106548 http://doi.org/10.1016/j.chb.2020.106548... , Payne et al. (2018)Payne, E. M., Peltier, J. W., & Barger, V. A. (2018). Mobile banking and AI-enabled mobile banking: The differential effects of technological and non-technological factors on digital natives’ perceptions and behavior. Journal of Research in Interactive Marketing, 12(3), 328-346. https://doi.org/10.1108/jrim-07-2018-0087 https://doi.org/10.1108/jrim-07-2018-008... , Prentice and Nguyen (2020)Prentice, C., & Nguyen, M. (2020). Engaging and retaining customers with AI and employee service. Journal of Retailing and Consumer Services, 56, 102186. https://doi.org/10.1016/j.jretconser.2020.102186 https://doi.org/10.1016/j.jretconser.202... , Moriuchi et al. (2021), Pillai and Sivathanu (2020)Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199-3226. https://doi.org/10.1108/IJCHM-04-2020-0259 https://doi.org/10.1108/IJCHM-04-2020-02... .
Quality in service	Perception of quality of the support given in the service.	Payne et al. (2018)Payne, E. M., Peltier, J. W., & Barger, V. A. (2018). Mobile banking and AI-enabled mobile banking: The differential effects of technological and non-technological factors on digital natives’ perceptions and behavior. Journal of Research in Interactive Marketing, 12(3), 328-346. https://doi.org/10.1108/jrim-07-2018-0087 https://doi.org/10.1108/jrim-07-2018-008... , Moriuchi et al. (2021)Moriuchi, E., Landers, V. M., Colton, D., & Hair, N. (2021). Engagement with chatbots versus augmented reality interactive technology in e-commerce. Journal of Strategic Marketing, 29(5), 375-389. https://doi.org/10.1080/0965254X.2020.1740766 https://doi.org/10.1080/0965254X.2020.17... , Trivedi (2019)Trivedi, J. (2019). Examining the customer experience of using banking chatbots and its impact on brand love: The moderating role of perceived risk. Journal of internet Commerce, 18(1), 91-111. https://doi.org/10.1080/15332861.2019.1567188 https://doi.org/10.1080/15332861.2019.15... .
Quality in the systems	Perception of the quality of service technology systems using AI.	Purwanto et al. (2020)Purwanto, P., Kuswandi, K., & Fatmah, F. (2020). Interactive Applications with Artificial Intelligence: The Role of Trust among Digital Assistant Users. Journal of the National Research University Higher School of Economics, 14(2), 64-75. https://doi.org/10.17323/2500-2597.2020.2.64.75 https://doi.org/10.17323/2500-2597.2020.... , Trivedi (2019)Trivedi, J. (2019). Examining the customer experience of using banking chatbots and its impact on brand love: The moderating role of perceived risk. Journal of internet Commerce, 18(1), 91-111. https://doi.org/10.1080/15332861.2019.1567188 https://doi.org/10.1080/15332861.2019.15... , Zeinalizadeh et al. (2015)Zeinalizadeh, N., Shojaie, A. A., & Shariatmadari, M. (2015). Modeling and analysis of bank customer satisfaction using neural networks approach. International Journal of Bank Marketing, 33(6), 717-732. https://doi.org/10.1108/IJBM-06-2014-0070 https://doi.org/10.1108/IJBM-06-2014-007... .
Construct	Definition
Quality perception	Perceptions of the quality involved in the services provided with the adoption of AI
Components	Definitions	References
Quality in the results	Perception of the quality of the results generated after contact with the service you use AI.	Purwanto et al. (2020)Purwanto, P., Kuswandi, K., & Fatmah, F. (2020). Interactive Applications with Artificial Intelligence: The Role of Trust among Digital Assistant Users. Journal of the National Research University Higher School of Economics, 14(2), 64-75. https://doi.org/10.17323/2500-2597.2020.2.64.75 https://doi.org/10.17323/2500-2597.2020.... , Choi et al. (2020)Choi, Y., Choi, M., Oh, M. M., & Kim, S. S. (2020). Service robots in hotels: Understanding the service quality perceptions of human-robot interaction. Journal of Hospitality Marketing & Management, 29(6), 613-635. https://doi.org/10.1080/19368623.2020.1703871 https://doi.org/10.1080/19368623.2020.17... , Moriuchi et al. (2021)Moriuchi, E., Landers, V. M., Colton, D., & Hair, N. (2021). Engagement with chatbots versus augmented reality interactive technology in e-commerce. Journal of Strategic Marketing, 29(5), 375-389. https://doi.org/10.1080/0965254X.2020.1740766 https://doi.org/10.1080/0965254X.2020.17... , Zeinalizadeh et al. (2015)Zeinalizadeh, N., Shojaie, A. A., & Shariatmadari, M. (2015). Modeling and analysis of bank customer satisfaction using neural networks approach. International Journal of Bank Marketing, 33(6), 717-732. https://doi.org/10.1108/IJBM-06-2014-0070 https://doi.org/10.1108/IJBM-06-2014-007... .
Construct	Definition
Marketing orientation	Strategies used by service providers that adopt AI to meet market demands
Components	Definitions	References
Performance	Use of process improvement-oriented systems.	Ameen et al. (2021)Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. http://doi.org/10.1016/j.chb.2020.106548 http://doi.org/10.1016/j.chb.2020.106548... , Chen et al. (2021)Chen, T., Guo, W., Gao, X., & Liang, Z. (2021). AI-based self-service technology in public service delivery: User experience and influencing factors. Government Information Quarterly, 38(4), 101520. https://doi.org/10.1016/j.giq.2020.101520 https://doi.org/10.1016/j.giq.2020.10152... , Gursoy et al. (2019)Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008 https://doi.org/10.1016/j.ijinfomgt.2019... , Lin et al. (2020)Lin, H., Chi, O. H., & Gursoy, D. (2020). Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing & Management, 29(5), 530-549. https://doi.org/10.1080/19368623.2020.1685053 https://doi.org/10.1080/19368623.2020.16... , Zeinalizadeh et al. (2015)Zeinalizadeh, N., Shojaie, A. A., & Shariatmadari, M. (2015). Modeling and analysis of bank customer satisfaction using neural networks approach. International Journal of Bank Marketing, 33(6), 717-732. https://doi.org/10.1108/IJBM-06-2014-0070 https://doi.org/10.1108/IJBM-06-2014-007... .
Competitiveness	Service management with the goal of gaining a competitive advantage.	Payne et al. (2018)Payne, E. M., Peltier, J. W., & Barger, V. A. (2018). Mobile banking and AI-enabled mobile banking: The differential effects of technological and non-technological factors on digital natives’ perceptions and behavior. Journal of Research in Interactive Marketing, 12(3), 328-346. https://doi.org/10.1108/jrim-07-2018-0087 https://doi.org/10.1108/jrim-07-2018-008... , Pillai et al. (2020)Pillai, R., Sivathanu, B., & Dwivedi, Y. K. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services, 57, 102207. https://doi.org/10.1016/j.jretconser.2020.102207 https://doi.org/10.1016/j.jretconser.202... , Kervenoael et al. (2020)Kervenoael, R. D., Hasan, R., Schwob, A., & Goh, E. (2020). Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots. Tourism Management, 78, 104042. https://doi.org/10.1016/j.tourman.2019.104042 https://doi.org/10.1016/j.tourman.2019.1... , Moriuchi et al. (2021)Moriuchi, E., Landers, V. M., Colton, D., & Hair, N. (2021). Engagement with chatbots versus augmented reality interactive technology in e-commerce. Journal of Strategic Marketing, 29(5), 375-389. https://doi.org/10.1080/0965254X.2020.1740766 https://doi.org/10.1080/0965254X.2020.17... .
Financial advantage	Consideration of the financial impact of adopting AI on service execution.	Zeinalizadeh et al. (2015)Zeinalizadeh, N., Shojaie, A. A., & Shariatmadari, M. (2015). Modeling and analysis of bank customer satisfaction using neural networks approach. International Journal of Bank Marketing, 33(6), 717-732. https://doi.org/10.1108/IJBM-06-2014-0070 https://doi.org/10.1108/IJBM-06-2014-007... .
Construct	Definition
Identification with the service	Factors that demonstrate the consumer’s identification with the service they use AI
Components	Definitions	References
Relationship	Perception that the service connects with the consumer from the use of AI.	Qiu et al. (2020)Qiu, H., Li, M., Shu, B., & Bai, B. (2020). Enhancing hospitality experience with service robots: The mediating role of rapport building. Journal of Hospitality Marketing & Management, 29(3), 247-268. https://doi.org/10.1080/19368623.2019.1645073 https://doi.org/10.1080/19368623.2019.16... , Trivedi (2019)Trivedi, J. (2019). Examining the customer experience of using banking chatbots and its impact on brand love: The moderating role of perceived risk. Journal of internet Commerce, 18(1), 91-111. https://doi.org/10.1080/15332861.2019.1567188 https://doi.org/10.1080/15332861.2019.15... .
Emotions	Evaluations of the feelings generated in the service experience with AI.	Gursoy et al. (2019)Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008 https://doi.org/10.1016/j.ijinfomgt.2019... , Lin et al. (2020)Lin, H., Chi, O. H., & Gursoy, D. (2020). Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing & Management, 29(5), 530-549. https://doi.org/10.1080/19368623.2020.1685053 https://doi.org/10.1080/19368623.2020.16... , Pillai et al. (2020)Pillai, R., Sivathanu, B., & Dwivedi, Y. K. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services, 57, 102207. https://doi.org/10.1016/j.jretconser.2020.102207 https://doi.org/10.1016/j.jretconser.202... , Prentice and Nguyen (2020)Prentice, C., & Nguyen, M. (2020). Engaging and retaining customers with AI and employee service. Journal of Retailing and Consumer Services, 56, 102186. https://doi.org/10.1016/j.jretconser.2020.102186 https://doi.org/10.1016/j.jretconser.202... , Qiu et al. (2020)Qiu, H., Li, M., Shu, B., & Bai, B. (2020). Enhancing hospitality experience with service robots: The mediating role of rapport building. Journal of Hospitality Marketing & Management, 29(3), 247-268. https://doi.org/10.1080/19368623.2019.1645073 https://doi.org/10.1080/19368623.2019.16... .
Environment	Perception of the service atmosphere created from the use of AI.	Pillai and Sivathanu (2020)Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199-3226. https://doi.org/10.1108/IJCHM-04-2020-0259 https://doi.org/10.1108/IJCHM-04-2020-02... , Qiu et al. (2020)Qiu, H., Li, M., Shu, B., & Bai, B. (2020). Enhancing hospitality experience with service robots: The mediating role of rapport building. Journal of Hospitality Marketing & Management, 29(3), 247-268. https://doi.org/10.1080/19368623.2019.1645073 https://doi.org/10.1080/19368623.2019.16... , Zhu and Chang (2020)Zhu, D. H., & Chang, Y. P. (2020). Robot with humanoid hands cooks food better? Effect of robotic chef anthropomorphism on food quality prediction. International Journal of Contemporary Hospitality Management, 32(3), 1367-1383. https://doi.org/10.1108/IJCHM-10-2019-0904 https://doi.org/10.1108/IJCHM-10-2019-09... , Payne et al. (2018).
Construct	Definition
Usage behavior	Intentions and behaviors that result from consumers’ satisfaction with the use of AI in services
Components	Definitions	References
Consumer experience	Intentions and behaviors that indicate favorable or unfavorable perceptions in the service user experience.	Ameen et al. (2021)Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. http://doi.org/10.1016/j.chb.2020.106548 http://doi.org/10.1016/j.chb.2020.106548... , Purwanto et al. (2020)Purwanto, P., Kuswandi, K., & Fatmah, F. (2020). Interactive Applications with Artificial Intelligence: The Role of Trust among Digital Assistant Users. Journal of the National Research University Higher School of Economics, 14(2), 64-75. https://doi.org/10.17323/2500-2597.2020.2.64.75 https://doi.org/10.17323/2500-2597.2020.... , Chen et al. (2021)Chen, T., Guo, W., Gao, X., & Liang, Z. (2021). AI-based self-service technology in public service delivery: User experience and influencing factors. Government Information Quarterly, 38(4), 101520. https://doi.org/10.1016/j.giq.2020.101520 https://doi.org/10.1016/j.giq.2020.10152... , Chiang and Trimi (2020)Chiang, A. H., & Trimi, S. (2020). Impacts of service robots on service quality. Service Business, 14, 439-459. https://doi.org/10.1007/s11628-020-00423-8 https://doi.org/10.1007/s11628-020-00423... , Choi et al. (2020)Choi, Y., Choi, M., Oh, M. M., & Kim, S. S. (2020). Service robots in hotels: Understanding the service quality perceptions of human-robot interaction. Journal of Hospitality Marketing & Management, 29(6), 613-635. https://doi.org/10.1080/19368623.2020.1703871 https://doi.org/10.1080/19368623.2020.17... , Qiu et al. (2020)Qiu, H., Li, M., Shu, B., & Bai, B. (2020). Enhancing hospitality experience with service robots: The mediating role of rapport building. Journal of Hospitality Marketing & Management, 29(3), 247-268. https://doi.org/10.1080/19368623.2019.1645073 https://doi.org/10.1080/19368623.2019.16... , Zeinalizadeh et al. (2015)Zeinalizadeh, N., Shojaie, A. A., & Shariatmadari, M. (2015). Modeling and analysis of bank customer satisfaction using neural networks approach. International Journal of Bank Marketing, 33(6), 717-732. https://doi.org/10.1108/IJBM-06-2014-0070 https://doi.org/10.1108/IJBM-06-2014-007... , Zhu and Chang (2020)Zhu, D. H., & Chang, Y. P. (2020). Robot with humanoid hands cooks food better? Effect of robotic chef anthropomorphism on food quality prediction. International Journal of Contemporary Hospitality Management, 32(3), 1367-1383. https://doi.org/10.1108/IJCHM-10-2019-0904 https://doi.org/10.1108/IJCHM-10-2019-09... .
Intention to use	Behaviors that indicate that there is a propensity for a consumer to use a service that contains AI.	Gursoy et al. (2019)Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008 https://doi.org/10.1016/j.ijinfomgt.2019... , Lin et al. (2020)Lin, H., Chi, O. H., & Gursoy, D. (2020). Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing & Management, 29(5), 530-549. https://doi.org/10.1080/19368623.2020.1685053 https://doi.org/10.1080/19368623.2020.16... , Pillai et al. (2020)Pillai, R., Sivathanu, B., & Dwivedi, Y. K. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services, 57, 102207. https://doi.org/10.1016/j.jretconser.2020.102207 https://doi.org/10.1016/j.jretconser.202... , Kervenoael et al. (2020)Kervenoael, R. D., Hasan, R., Schwob, A., & Goh, E. (2020). Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots. Tourism Management, 78, 104042. https://doi.org/10.1016/j.tourman.2019.104042 https://doi.org/10.1016/j.tourman.2019.1... .
Use objection	Behaviors that indicate that there is no propensity for a consumer to use a service that contains AI.	Gursoy et al. (2019)Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008 https://doi.org/10.1016/j.ijinfomgt.2019... , Lin et al. (2020)Lin, H., Chi, O. H., & Gursoy, D. (2020). Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing & Management, 29(5), 530-549. https://doi.org/10.1080/19368623.2020.1685053 https://doi.org/10.1080/19368623.2020.16... .
Attitude towards AI	Perceptions of a consumer’s action when experiencing a service encounter that used AI.	Payne et al. (2018)Payne, E. M., Peltier, J. W., & Barger, V. A. (2018). Mobile banking and AI-enabled mobile banking: The differential effects of technological and non-technological factors on digital natives’ perceptions and behavior. Journal of Research in Interactive Marketing, 12(3), 328-346. https://doi.org/10.1108/jrim-07-2018-0087 https://doi.org/10.1108/jrim-07-2018-008... .
Loyalty	A consumer’s intention to maintain long-term contact with a service company using AI.	Moriuchi et al. (2021)Moriuchi, E., Landers, V. M., Colton, D., & Hair, N. (2021). Engagement with chatbots versus augmented reality interactive technology in e-commerce. Journal of Strategic Marketing, 29(5), 375-389. https://doi.org/10.1080/0965254X.2020.1740766 https://doi.org/10.1080/0965254X.2020.17... , Prentice and Nguyen (2020)Prentice, C., & Nguyen, M. (2020). Engaging and retaining customers with AI and employee service. Journal of Retailing and Consumer Services, 56, 102186. https://doi.org/10.1016/j.jretconser.2020.102186 https://doi.org/10.1016/j.jretconser.202... , Prentice et al. (2020)Prentice, C., Lopes, S. D., & Wang, X. (2020). The impact of artificial intelligence and employee service quality on customer satisfaction and loyalty. Journal of Hospitality Marketing & Management, 29(7), 739-756. https://doi.org/10.1080/19368623.2020.1722304 https://doi.org/10.1080/19368623.2020.17... , Trivedi (2019)Trivedi, J. (2019). Examining the customer experience of using banking chatbots and its impact on brand love: The moderating role of perceived risk. Journal of internet Commerce, 18(1), 91-111. https://doi.org/10.1080/15332861.2019.1567188 https://doi.org/10.1080/15332861.2019.15... .
Purchase intention	Perception of the influence of AI on the propensity of a consumer to contract a service.	Moriuchi et al. (2021)Moriuchi, E., Landers, V. M., Colton, D., & Hair, N. (2021). Engagement with chatbots versus augmented reality interactive technology in e-commerce. Journal of Strategic Marketing, 29(5), 375-389. https://doi.org/10.1080/0965254X.2020.1740766 https://doi.org/10.1080/0965254X.2020.17... , Pillai et al. (2020)Pillai, R., Sivathanu, B., & Dwivedi, Y. K. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services, 57, 102207. https://doi.org/10.1016/j.jretconser.2020.102207 https://doi.org/10.1016/j.jretconser.202... .

Components	k	o	N	ES	d of Cohen	IClower	ICupper	Q	FSN
Trust	9	10	3705	0.63	2.06	0.60	0.66	356.33	114
Control	6	8	3661	0.75	2.16	0.71	0.78	961.33	89
Empathy	9	9	4440	0.93	2.30	0.90	0.96	1683.99	167
Hedonism	3	3	2294	0.52	2.25	0.47	0.56	1466.94	31
Negative effects	5	6	3760	0.80	2.19	0.76	0.83	1144.62	80
Interaction	7	7	3752	0.86	2.27	0.82	0.89	1559.16	120
Utility	4	6	1558	0.34	2.23	0.29	0.39	1364.03	27

Components	k	o	N	ES	d of Cohen	IClower	Icupper	Q	FSN
Access	3	4	865	0.16	2.10	0.09	0.23	64.23	10
Customization	4	4	2401	0.57	2.41	0.53	0.62	541.73	46
Usability	3	3	995	0.23	2.32	0.17	0.29	189.15	14
Performance	3	3	1194	0.29	2.44	0.23	0.35	282.02	17
Service	4	4	1615	0.36	2.27	0.31	0.41	264.90	29

Components	k	o	N	ES	d of Cohen	IClower	ICupper	Q	FSN
Quality in the use of AI	5	5	2580	0.63	2.44	0.59	0.66	609.39	63
Quality in the service	3	3	544	0.13	2.41	0.05	0.21	121.71	8
Quality in the systems	3	4	808	0.20	2.55	0.13	0.27	218.48	12
Quality in the results	4	4	957	0.24	2.55	0.18	0.30	258.77	19

Components	k	o	N	ES	d of Cohen	IClower	ICupper	Q	FSN
Performance	5	5	2257	0.57	2.55	0.53	0.61	610.29	57
Competitiveness	4	4	1979	0.49	2.51	0.45	0.54	514.74	39
Financial advantage	1	2	400	0.07	2.08	-0.03	0.17	24.01	1

Components	k	o	N	ES	d of Cohen	IClower	ICupper	Q	FSN
Relationship	2	3	474	0.13	2.76	0.04	0.22	154.00	5
Emotions	5	5	2890	0.76	2.67	0.72	0.79	880.59	76
Environment	4	4	2135	0.65	4.10	0.61	0.69	1016.47	52

Components	k	O	N	ES	d of Cohen	IClower	ICupper	Q	FSN
Consumer experience	9	9	2558	0.67	2.66	0.63	0.71	773.80	120
Intention to use	4	4	2967	0.82	2.94	0.78	0.85	1068.12	65
Use objection	3	2	1044	0.30	3.40	0.24	0.37	441.09	18
Attitude towards AI	1	1	218	0.04	2.06	-0.10	0.17	9.61	1
Loyalty	4	4	1203	0.35	3.25	0.29	0.40	488.14	28
Purchase intention	3	2	1318	0.38	3.28	0.33	0.43	539.85	23

Editora Mackenzie; Universidade Presbiteriana Mackenzie Rua da Consolação, 896, Edifício Rev. Modesto Carvalhosa, Térreo - Coordenação da RAM, Consolação - São Paulo - SP - Brasil - cep 01302-907 - São Paulo - SP - Brazil
E-mail: revista.adm@mackenzie.br

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[1] Authors’ notes

Laura M. Aguiar-Costa is now a Ph.D. student at the Postgraduate Program in Administration (PPGA) of Federal University of Paraíba (Universidade Federal da Paraíba - UFPB); Carlos A. X. C. Cunha is now a Ph.D. student at the PPGA-UFPB; Wallysson K. M. Silva is now a Ph.D. student at the PPGA-UFPB; Nelsio R. Abreu is now a professor and researcher at the Department of Administration of UFPB.