Evaluación de los robots conversacionales en la comunicación asegurado-asegurador en el mercado español con un modelo de aceptación tecnológica

Autores/as

DOI:

https://doi.org/10.26360/2023_6

Palabras clave:

Insurtech, Chatbots, Modelo de Aceptación Tecnológica, Gestiones con el asegurador, Modelo de Ecuaciones Estructurales

Resumen

Esta investigación analiza la percepción de 63 profesionales de la industria del seguro acerca de la utilidad de los robots conversacionales (chatbots) en las interacciones de los clientes con las aseguradoras en relación a las pólizas en vigor. Para explicar dicha percepción, se utiliza un Modelo de Aceptación Tecnológica (Technology Acceptance Model, TAM) que incluye como variables la utilidad percibida, la facilidad de uso y la confianza en los chatbots. Además, se utilizan dos preguntas abiertas sobre las ventajas y desventajas del uso de esta tecnología. Así, se lleva a cabo un análisis cuantitativo mediante un Modelo de Ecuaciones Estructurales estimado por Mínimos Cuadrados Parciales (MEE-MCP), y un Análisis Cualitativo de las respuestas abiertas.

Los resultados del análisis del MEE-MCP muestran una buena adecuación del TAM a la encuesta utilizada en la investigación, y revelan una influencia significativa directa de la utilidad percibida en la aceptación de los chatbots, así como un impacto también significativo de la facilidad de uso y la confianza, pero mediado por la utilidad percibida. En general, la actitud de los encuestados hacia los chatbots es negativa. Se identificaron diversas razones relacionadas con la dificultad en la interacción con estos, la necesidad de recurrir a la ayuda de un operador humano, la falta de habilidades emocionales como la empatía, la preocupación por la destrucción de puestos de trabajo, la poca fiabilidad y la ausencia de percepción de ventajas en términos de la repercusión de la reducción de costes administrativos en mejoras en los productos ofrecidos.

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Baabdullah, A.M., Alalwan, A.A., Algharabat, R.S., Metri, B. and Rana, N.P. (2022). Virtual agents and flow experience: An empirical examination of AI-powered chatbots. Technological Forecasting and Social Change, 181, 121772. https://doi.org/10.1016/j.techfore.2022.121772

Balakrishnan, J., Abed, S. S., and Jones, P. (2022). The role of meta-UTAUT factors, perceived anthropomorphism, perceived intelligence, and social self-efficacy in chatbot-based services?. Technological Forecasting and Social Change, 180, 121692. https://doi.org/10.1016/j.techfore.2022.121692

Balasubramanian, R., Libarikian, A. and McElhaney, D. (2018). Insurance 2030 - The impact of AI on the future of insurance. McKinsey & Company. Consultado en https://www.mckinsey.com/industries/financial-services/our-insights/insurance-2030-the-impact-of-ai-on-the-future-of-insurance#/ el 12/02/2023.

Bashir, I. and Madhavaiah, C. (2015). Consumer attitude and behavioral intention toward Internet banking adoption in India. Journal of Indian Business Research, 7(1), 67-102. https://doi.org/10.1108/JIBR-02-2014-0013

Belzunegui-Eraso A. and Erro-Garcés A. (2020). Teleworking in the Context of the Covid-19 Crisis. Sustainability, 12(9), 3662. https://doi.org/10.3390/su12093662

Bhattacherjee, A. and Premkumar, G. (2004) Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quaterly, 28(2), 229–254. https://doi.org/10.2307/25148634

Bittini, J. S., Rambaud, S. C., Pascual, J. L. and Moro-Visconti, R. (2022). Business models and sustainability plans in the FinTech, InsurTech, and PropTech industry: Evidence from Spain. Sustainability, 14(19), 12088. https://doi.org/10.3390/su141912088

Bohnert, A., Fritzsche, A. and Gregor, S. (2019). Digital agendas in the insurance industry: the importance of comprehensive approaches. The Geneva Papers on Risk and Insurance - Issues and Practice, 44, 1–19. https://doi.org/10.1057/s41288-018-0109-0

Brachten, F., Kissmer, T. and Stieglitz, S. (2021). The acceptance of chatbots in an enterprise context - A survey study. International Journal of Information Management, 60, 102375. https://doi.org/10.1016/j.ijinfomgt.2021.102375

Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008

DeAndrade, I.M. and Tumelero, C. (2022). Increasing customer service efficiency through artificial intelligence chatbot. Revista de Gestão, 29(3), 238-251. https://doi.org/10.1108/REGE-07-2021-0120

De Andrés-Sánchez, J., González-Vila Puchades, L. and & Arias-Oliva, M. (2021). Factors influencing policyholders' acceptance of life settlements: a technology acceptance model. The Geneva Papers on Risk and Insurance - Issues and Practice. https://doi.org/10.1057/s41288-021-00261-3

De Andrés-Sánchez, J. and González-Vila Puchades, L. (2023). Combining fsQCA and PLS-SEM to assess policyholders’ attitude towards life settlements. European Research on Management and Business Economics, 29(2), 100220. https://doi.org/10.1016/j.iedeen.2023.100220

De Andrés-Sánchez J. and Gené-Albesa, J. (2023) Assessing Attitude and Behavioral Intention toward Chatbots in an Insurance Setting: A Mixed Method Approach. International Journal of Human–Computer Interaction. https://doi.org/10.1080/10447318.2023.2227833

De Cicco, R., Iacobucci, S., Aquino, A., Romana Alparone, F. and Palumbo, R. (2022). Understanding Users’ Acceptance of Chatbots: An Extended TAM Approach. En A. Følstad, T. Araujo, S. Papadopoulos, E.L.-C. Law, E. Luger, M. Goodwin and P.B. Brandtzaeg (Eds.) Chatbot Research and Design. 5th International Workshop, CONVERSATIONS 2021, Virtual Event, November 23–24, 2021, Revised Selected Papers (pp. 3-22). Springer, Cham. https://doi.org/10.1007/978-3-030-94890-0_1

Eeuwen, M.V. (2017). Mobile conversational commerce: messenger chatbots as the next interface between businesses and consumers [Master's thesis]. University of Twente.

Farah, M.F., Hasni, M.J.S. and Abbas, A.K. (2018). Mobile-banking adoption: empirical evidence from the banking sector in Pakistan. International Journal of Bank Marketing, 36(7), 1386–1413. https://doi.org/10.1108/IJBM-10-2017-0215

Fishbein, M. and Ajzen, I. (1975). Belief, attitude, intention and behavior: an introduction to theory and research. Reading, MA: Addison-Wesley.

Fornell, C. and Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312

Fotheringham, D. and Wiles, M.A. (2023). The effect of implementing chatbot customer service on stock returns: An event study analysis. Journal of the Academy of Marketing Science, 51, 802–822. https://doi.org/10.1007/s11747-022-00841-2

Fung, G., Polania, L. F., Choi, S. C. T., Wu, V. and Ma, L. (2021). Artificial Intelligence in Insurance and Finance. Frontiers in Applied Mathematics and Statistics, 7, 795207. https://doi.org/10.3389/fams.2021.795207

Gansser, O.A. and Reich, C.S. (2021). A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application. Technology in Society, 65, 101535. https://doi.org/10.1016/j.techsoc.2021.101535

Gené-Albesa, J. (2007). Interaction channel choice in a multichannel environment, an empirical study. International Journal of Bank Marketing, 25(7), 490-506. https://doi.org/10.1108/02652320710832630

Greineder, M., Riasanow, T., Böhm, M. and Krcmar, H. (2020). The generic Insurtech ecosystem and its strategic implications for the digital transformation of the insurance industry. En: H.C. Mayr, S. Rinderle-Ma & S. Strecker (Eds.) 40 Years EMISA 2019 (pp. 119-132). Bonn. Gesellschaft für Informatik e.V.

Guiso, L. (2012). Trust and insurance markets. Economic Notes, 41(1‐2), 1-26. https://doi.org/10.1111/j.1468-0300.2012.00239.x

Guiso, L. (2021). Trust and insurance. The Geneva Papers on Risk and Insurance - Issues and Practice, 46, 509-512. https://doi.org/10.1057/s41288-021-00241-7

Hair, J.F., Risher, J.J., Sarstedt, M. and Ringle, C.M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203. 0203

Han, J. and Conti, D. (2020). The use of UTAUT and post acceptance models to investigate the attitude towards a telepresence robot in an educational setting. Robotics, 9(2), 34. https://doi.org/10.3390/robotics9020034

Hari, H., Iyer, R. and Sampat, B. (2022). Customer Brand Engagement through Chatbots on Bank Websites – Examining the Antecedents and Consequences, International Journal of Human–Computer Interaction, 38(13), 1212-1227. https://doi.org/10.1080/10447318.2021.1988487

Huang, W.S., Chang, C.T. and Sia, W.Y. (2019). An empirical study on the consumers’ willingness to insure online. Polish Journal of Management Studies, 20(1), 202-212. https://doi.org/10.17512/pjms.2019.20.1.18

Hussain, M., Mollik, A.T., Johns, R. and Rahman, M.S. (2019). M-payment adoption for bottom of pyramid segment: an empirical investigation. International Journal of Bank Marketing, 37(1), 362–381. https://doi.org/10.1108/IJBM-01-2018-0013

Jenneboer, L., Herrando, C. and Constantinides, E. (2022). The Impact of chatbots on customer loyalty: a systematic literature review. Journal of Theoretical and Applied Electronic Commerce Research, 17, 212–229. https://doi.org/10.3390/jtaer17010011

Joshi, H. (2021). Perception and Adoption of Customer Service Chatbots among Millennials: An Empirical Validation in the Indian Context. Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST, (pp. 197-208). https://doi.org/10.5220/0010718400003058

Kaleka, A. (2002). Resources and capabilities driving competitive advantage in export markets: guidelines for industrial exporters. Industrial Marketing Management, 31(3), 273-283. https://doi.org/10.1016/S0019-8501(00)00148-6

Kasilingam, D.L. (2020). Understanding the attitude and intention to use smartphone chatbots for shopping. Technology in Society, 62, 101280. https://doi.org/10.1016/j.techsoc.2020.101280

Kim, D.J., Ferrin, D.L. and Rao, H.R. (2008). A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544-564. https://doi.org/10.1016/j.dss.2007.07.001

Kock, N. and Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227-261. https://doi.org/10.1111/isj.12131

Koetter, F., Blohm, M., Drawehn, J., Kochanowski, M., Goetzer, J., Graziotin, D. and Wagner, S. (2019). Conversational agents for insurance companies: from theory to practice. En J. Van den Herik, A.P. Rocha & L. Steels (Eds.). Agents and Artificial Intelligence: 11th International Conference, ICAART 2019, Revised Selected Papers 11 (pp. 338-362). Prague, Czech Republic, February 19–21, 2019, Springer International Publishing. https://doi.org/10.1007/978-3-030-37494-5_17

Kovacs, O. (2018). The dark corners of industry 4.0–Grounding economic governance 2.0. Technology in Society, 55, 140-145. https://doi.org/10.1016/j.techsoc.2018.07.009

Kuberkar, S. and Singhal, T.K. (2020). Factors influencing adoption intention of AI powered chatbot for public transport services within a smart city. International Journal of Emerging Technologies, 11(3), 948-958. Available on https://www.researchtrend.net/ijet/pdf/Factors%20Influencing%20Adoption%20Intention%20of%20AI%20Powered%20Chatbot%20for%20Public%20Transport%20Services%20within%20a%20Smart%20City%20Tarun%20Kumar%20Singhal%20947.pdf

Lanfranchi, D. and Grassi, L. (2022). Examining insurance companies’ use of technology for innovation. The Geneva Papers on Risk and Insurance - Issues and Practice, 47, 520-537. https://doi.org/10.1057/s41288-021-00258-y

Lee, S., Oh, J. and Moon, W.-K. (2022) Adopting Voice Assistants in Online Shopping: Examining the Role of Social Presence, Performance Risk, and Machine Heuristic, International Journal of Human–Computer Interaction. https://doi.org/10.1080/10447318.2022.2089813

Makanyeza, C. and Mutambayashata, S. (2018). Consumers’ acceptance and use of plastic money in Harare, Zimbabwe: application of the unified theory of acceptance and use of technology 2. International Journal of Bank Marketing, 36(2), 379–392. https://doi.org/10.1108/IJBM-03-2017-0044

Martínez Ávila, M. y Fierro Moreno, E. (2018). Aplicación de la técnica PLS-SEM en la gestión del conocimiento: un enfoque técnico práctico. RIDE. Revista Iberoamericana para la Investigación y el Desarrollo Educativo, 8(16), 130-164. https://doi.org/10.23913/ride.v8i16.336

Milanović, N., Milosavljević, M., Benković, S., Starčević, D. and Spasenić, Ž. (2020). An Acceptance Approach for Novel Technologies in Car Insurance. Sustainability, 12(24), 10331. https://doi.org/10.3390/su122410331

Morgan, R.M. and Hunt, S.D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20-38. https://doi.org/10.2307/1252308

Mostafa, R.B. and Kasamani, T. (2022). Antecedents and consequences of chatbot initial trust. European Journal of Marketing, 56(6), 1748-1771. https://doi.org/10.1108/EJM-02-2020-0084

Nirala, K.K., Singh, N.K. and Purani, V.S. (2022). A survey on providing customer and public administration based services using AI: chatbot. Multimedia Tools and Applications, 81, 22215-22246. https://doi.org/10.1007/s11042-021-11458-y

Nuruzzaman, M. and Hussain, O.K. (2020). IntelliBot: A Dialog-based chatbot for the insurance industry. Knowledge-Based Systems, 196, 105810. https://doi.org/10.1016/j.knosys.2020.105810

Oktariyana, M.D., Ariyanto, D. and Ratnadi, N.M.D (2019). Implementation of UTAUT and D&M Models for Success Assessment of Cashless System. Research Journal of Finance and Accounting, 10(12), 127-137. https://doi.org/10.7176/RJFA/10-12-16

Pawlik, V.P. (2022). Design Matters! How Visual Gendered Anthropomorphic Design Cues Moderate the Determinants of the Behavioral Intention Towards Using Chatbots. En A. Følstad, T. Araujo, S. Papadopoulos, E.L.-C. Law, E. Luger, M. Goodwin & P.B. Brandtzaeg (Eds.) Chatbot Research and Design. 5th International Workshop, CONVERSATIONS 2021, Virtual Event, November 23–24, 2021, Revised Selected Papers (pp. 196-208). Springer, Cham https://doi.org/10.1007/978-3-030-94890-0_12

PromTep, S.P., Arcand, M., Rajaobelina, L. and Ricard, L. (2021). From What Is Promised to What Is Experienced with Intelligent Bots. En K. Arai (Eds.). Advances in Information and Communication: Proceedings of the 2021 Future of Information and Communication Conference (FICC), Volume 1 (pp. 560-565). Springer International Publishing. https://doi.org/10.1007/978-3-030-73100-7_40

Rajaobelina, L., PromTep, S.P., Arcand, M. and Ricard, L. (2021). Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot. Psychology & Marketing, 38(12), 2339-2356. https://doi.org/10.1002/mar.21548

Riikkinen, M., Saarijärvi, H., Sarlin, P. and Lähteenmäki, I. (2018). Using artificial intelligence to create value in insurance. International Journal of Bank Marketing, 36(6), 1145-1168. https://doi.org/10.1108/IJBM-01-2017-0015

Rodríguez-Cardona, D., Werth, O., Schönborn, S. and Breitner, M.H. (2019). A mixed methods analysis of the adoption and diffusion of Chatbot Technology in the German insurance sector. AMCIS 2019 Proceedings. Twenty-fifth Americas Conference on Information Systems. Cancun. https://aisel.aisnet.org/amcis2019/adoption_diffusion_IT/adoption_diffusion_IT/18

Sá Siqueira, M.A. de, Müller, B.C.N. and Bosse, T. (2023). When Do We Accept Mistakes from Chatbots? The Impact of Human-Like Communication on User Experience in Chatbots That Make Mistakes. International Journal of Human–Computer Interaction. https://doi.org/10.1080/10447318.2023.2175158

Sánchez-Torres, J.A., Canada, F.-J.A., Sandoval, A.V. and Alzate, J.-A.S. (2018). E-banking in Colombia: factors favoring its acceptance, online trust and government support. International Journal of Bank Marketing, 36(1), 170–183. https://doi.org/10.1108/IJBM-10-2016-0145

Silva, F.A., Shojaei, A.S. and Barbosa, B. (2023). Chatbot-based services: a study on customers’ reuse intention. Journal of Theoretical and Applied Electronic Commerce Research, 18, 457–474. https://doi.org/10.3390/jtaer18010024

Sosa, I. y Montes, Ó. (2022). Understanding the InsurTech dynamics in the transformation of the insurance sector. Risk Management and Insurance Review, 25(1), 35-68. https://doi.org/10.1111/rmir.12203

Standaert, W. and Muylle, S. (2022). Framework for open insurance strategy: insights from a European study. The Geneva Papers on Risk and Insurance - Issues and Practice, 47, 643-668. https://doi.org/10.1057/s41288-022-00264-8

Stoeckli, E., Dremel, C. and Uebernickel, F. (2018). Exploring characteristics and transformational capabilities of InsurTech innovations to understand insurance value creation in a digital world. Electronic Markets, 28, 287-305. https://doi.org/10.1007/s12525-018-0304-7

Vassilakopoulou, P., Haug, A., Salvesen, L.M. and Pappas, I.O. (2023). Developing human/AI interactions for chat-based customer services: lessons learned from the Norwegian government. European Journal of Information Systems, 32(1), 10-22. https://doi.org/10.1080/0960085X.2022.2096490

Venkatesh, V. and Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x

Venkatesh, V. and Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478. http://doi.org/10.2307/30036540

Venkatesh, V., Thong, J.Y.L. and Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. http://doi.org/10.2307/41410412

Vogelsang, K., Steinhüser, M. and Hoppe, U. (2013). A qualitative approach to examine technology acceptance. Thirty Fourth International Conference on Information Systems, Milan 2013. Consultado en https://core.ac.uk/download/pdf/301361231.pdf el 03/01/2023

Warsame, M.H. and Ireri, E.M. (2018). Moderation effect on mobile microfinance services in Kenya: an extended UTAUT model. Journal of Behavioral and Experimental Finance, 18, 67–75. https://doi.org/0.1016/j.jbef.2018.01.008

Warwick, K. and Shah, H. (2016) Can machines think? A report on Turing test experiments at the Royal Society. Journal of Experimental & Theoretical Artificial. Intelligence, 28(6), 989-1007, http://doi.org/10.1080/0952813X.2015.1055826

Xie, C., Wang, Y. and Cheng, Y. (2022). Does Artificial Intelligence Satisfy You? A Meta-Analysis of User Gratification and User Satisfaction with AI-Powered Chatbots. International Journal of Human–Computer Interaction. https://10.1080/10447318.2022.2121458

Xing, X., Song, M., Duan, Y. and Mou, J. (2022). Effects of different service failure types and recovery strategies on the consumer response mechanism of chatbots. Technology in Society, 70, 102049. https://doi.org/10.1016/j.techsoc.2022.102049

Yan, T.C., Schulte, P. and Chuen, D.L.K. (2018). InsurTech and FinTech: Banking and Insurance Enablement. En: Handbook of Blockchain, Digital Finance, and Inclusion, 1 (pp. 249-281). https://doi.org/10.1016/B978-0-12-810441-5.00011-7

Publicado

13-12-2023

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de Andres Sanchez, J., Gene-Albesa, J., & González-Vila Puchades, L. (2023). Evaluación de los robots conversacionales en la comunicación asegurado-asegurador en el mercado español con un modelo de aceptación tecnológica. Anales Del Instituto De Actuarios Españoles, (29), 111–135. https://doi.org/10.26360/2023_6

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