DOI: https://doi.org/10.21456/vol13iss1pp78-87

Penambahan Variabel Tingkat Kecerdasan dari Chatbot untuk Mempengaruhi Kepercayaan Pengguna dalam Aplikasi Telekonsultasi Kesehatan

*Hapizin Yonani Panjaitan  -  Universitas Trisakti, Indonesia
Yolanda Masnita orcid scopus publons  -  Universitas Trisakti, Indonesia
Kurniawati Kurniawati orcid  -  Universitas Trisakti, Indonesia
Open Access Copyright (c) 2023 JSINBIS (Jurnal Sistem Informasi Bisnis)

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Abstract

The use of Artificial Intelligence (AI) technology is often encountered in everyday life, especially in the world of business marketing, namely chatbots which are part of the implementation of Natural Language Processing (NLP). However, in its application, it is still felt that it cannot meet the needs of consumers for the specific questions they often ask, especially for those who use health teleconsultation services. In this study, the intelligence variable is added as an additional variable to answer the level of user trust in the chatbot. The data used in this study are quantitative with the target respondents being users of health teleconsultation services with a minimum user experience of 1 year. A total of 178 respondents met the criteria from a total of 238 respondents. In this research, three variables are developed. For each dependent variable, empathy, friendliness, and intelligence are factors moderated by task complexity and chatbot disclosure to determine the results of the independent variable, which is trust towards the chatbot. Based on the results of the outer model and inner model analysis using SmartPLS, it can be concluded that the addition of intelligence variables has a positive effect on user trust in chatbots. In addition, the level of chatbot complexity is also able to mediate the relationship between intelligence and user trust in chatbots. However, chatbot disclosure has a negative effect as mediating the relationship between intelligence and user trust in chatbots. In the application of using chatbots, the level of intelligence may have an effect on user trust, but natural human attitudes such as friendliness from chatbots do not affect user trust.

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Exploring consumers’ response to text-based chatbots in e-commerce: the moderating role of task complexity and chatbot disclosure
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Keywords: Healthcare Teleconsultation App; Chatbot; Artificial Intelligence (AI); Trust of Chatbot; Intelligence of Chatbot

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  1. Akdim, K., Belanche, D., Flavián, M., 2021. Attitudes toward service robots: analyses of explicit and implicit attitudes based on anthropomorphism and construal level theory. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/IJCHM-12-2020-1406
  2. Ali, F., Ali, L., Gao, Z., Terrah, A., Turktarhan, G., 2022. Determinants of user’s intentions to book hotels: a comparison of websites and mobile apps. Aslib Journal of Information Management, ahead-of-print (ahead-of-print). https://doi.org/10.1108/AJIM-05-2022-0239
  3. Andrade, I. M. De., Tumelero, C., 2022. Increasing customer service efficiency through artificial intelligence chatbot. Revista de Gestao 29(3), 238–251. https://doi.org/10.1108/REGE-07-2021-0120
  4. Antonio, R., Tyandra, N., Nusantara, L. T., Gunawan, A. A. S., 2022. Study literature review: discovering the effect of chatbot implementation in e-commerce customer service system towards customer satisfaction. 2022 International Seminar on Application for Technology of Information and Communication (ISemantic) 296–301. https://doi.org/10.1109/iSemantic55962.2022.9920434
  5. Bilquise, G., Ibrahim, S., Shaalan, K., 2022. Emotionally Intelligent chatbots: a systematic literature review. Human Behavior and Emerging Technologies 9601630. https://doi.org/10.1155/2022/9601630
  6. Borges, A. F. S., Laurindo, F. J. B., Spínola, M. M., Gonçalves, R. F., Mattos, C. A., 2021. The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions. International Journal of Information Management 57, 102225. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2020.102225
  7. Boucher, E. M., Harake, N. R., Ward, H. E., Stoeckl, S. E., Vargas, J., Minkel, J., Parks, A. C., Zilca, R., 2021. Artificially intelligent chatbots in digital mental health interventions: a review. Expert Review of Medical Devices 18(1), 37–49. https://doi.org/10.1080/17434440.2021.2013200
  8. Casadei, A., Schlögl, S., Bergmann, M., 2022. Chatbots for robotic process automation: investigating perceived trust and user satisfaction. 2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS) 1–6. https://doi.org/10.1109/ICHMS56717.2022.9980826
  9. Chen, J. S., Le, T. T. Y., Florence, D., 2021. Usability and responsiveness of artificial intelligence chatbot on online customer experience in e-retailing. International Journal of Retail and Distribution Management 49(11). https://doi.org/10.1108/IJRDM-08-2020-0312
  10. Cheng, X., Bao, Y., Zarifis, A., Gong, W., Mou, J., 2022. Exploring consumers’ response to text-based chatbots in e-commerce: the moderating role of task complexity and chatbot disclosure. Internet Research 32(2), 496–517. https://doi.org/10.1108/INTR-08-2020-0460
  11. Chong, T., Yu, T., Keeling, D. I., de Ruyter, K., 2021. AI-chatbots on the services frontline addressing the challenges and opportunities of agency. Journal of Retailing and Consumer Services 63, 102735. https://doi.org/https://doi.org/10.1016/j.jretconser.2021.102735
  12. De Cicco, R., da Costa e Silva, S. C. L., Palumbo, R., 2021. Should a chatbot disclose itself? implications for an online conversational retailer. In A. Følstad, T. Araujo, S. Papadopoulos, E. L.-C. Law, E. Luger, M. Goodwin, dan P. B. Brandtzaeg (Eds.), Springer International Publishing, Chatbot Research and Design, 3–15
  13. El Hefny, W., El Bolock, A., Herbert, C., Abdennadher, S., 2021. Chase away the virus: a character-based chatbot for COVID-19. SeGAH 2021 - 2021 IEEE 9th International Conference on Serious Games and Applications for Health. https://doi.org/10.1109/SEGAH52098.2021.9551895
  14. Fotheringham, D., Wiles, M. A., 2022. The effect of implementing chatbot customer service on stock returns: an event study analysis. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-022-00841-2
  15. Gamble, A., 2020. Artificial intelligence and mobile apps for mental healthcare: a social informatics perspective. In Aslib Journal of Information Management 72(4). https://doi.org/10.1108/AJIM-11-2019-0316
  16. Henk, A., Nilssen, F., 2021. Can AI become a state servant? A case study of an intelligent chatbot implementation in a scandinavian public service. Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-January. https://doi.org/10.24251/hicss.2021.670
  17. Ilmi, M., Setyo Liyundira, F., Rachmawati, A., Juliasari, D., Habsari, P., 2020. Perkembangan dan penerapan theory of acceptance model (TAM) di Indonesia. Relasi : Jurnal Ekonomi 16(2), 436–458. https://doi.org/10.31967/relasi.v16i2.371
  18. Ischen, C., Araujo, T., Voorveld, H., van Noort, G., Smit, E., 2020. Privacy Concerns in Chatbot Interactions. In A. Følstad, T. Araujo, S. Papadopoulos, E. L.-C. Law, O.-C. Granmo, E. Luger, dan P. B. Brandtzaeg (Eds.), Springer International Publishing, Chatbot Research and Design, 34–48
  19. Jiang, K., Qin, M., Li, S., 2022. Chatbots in retail: How do they affect the continued use and purchase intentions of Chinese consumers? Journal of Consumer Behaviour 21(4), 756–772. https://doi.org/https://doi.org/10.1002/cb.2034
  20. Jiménez-Barreto, J., Rubio, N., Molinillo, S., 2021. “Find a flight for me, Oscar!” Motivational customer experiences with chatbots. International Journal of Contemporary Hospitality Management 33(11). https://doi.org/10.1108/IJCHM-10-2020-1244
  21. Jin, E., Eastin, M. S., 2022. When a chatbot smiles at you: the psychological mechanism underlying the effects of friendly language use by product recommendation chatbots. Cyberpsychology, Behavior, and Social Networking 25(9), 597–604. https://doi.org/10.1089/cyber.2021.0318
  22. Lee, J. C., Chen, X., 2022. Exploring users’ adoption intentions in the evolution of artificial intelligence mobile banking applications: the intelligent and anthropomorphic perspectives. International Journal of Bank Marketing 40(4). https://doi.org/10.1108/IJBM-08-2021-0394
  23. Lei, S. I., Shen, H., Ye, S., 2021. A comparison between chatbot and human service: customer perception and reuse intention. International Journal of Contemporary Hospitality Management 33(11). https://doi.org/10.1108/IJCHM-12-2020-1399
  24. Liu, B., Sundar, S. S., 2018. Should machines express sympathy and empathy? experiments with a health advice chatbot. Cyberpsychology, Behavior, and Social Networking 21(10). https://doi.org/10.1089/cyber.2018.0110
  25. Mehta, R., Verghese, J., Mahajan, S., Barykin, S., Bozhuk, S., Kozlova, N., Vasilievna Kapustina, I., Mikhaylov, A., Naumova, E., Dedyukhina, N., 2022. Consumers’ behavior in conversational commerce marketing based on messenger chatbots. F1000Research 11, 647. https://doi.org/10.12688/f1000research.122037.1
  26. Mittal, M., Battineni, G., Singh, D., Nagarwal, T., dan Yadav, P., 2021. Web-based chatbot for Frequently Asked Queries (FAQ) in Hospitals. Journal of Taibah University Medical Sciences 16(5), 740–746. https://doi.org/10.1016/j.jtumed.2021.06.002
  27. Mozafari, N., Weiger, W. H., Hammerschmidt, M., 2022. Trust me, I’m a bot – repercussions of chatbot disclosure in different service frontline settings. Journal of Service Management 33(2). https://doi.org/10.1108/JOSM-10-2020-0380
  28. Mozafari Nika, W. W. H. M., 2021. 53rd Hawaii International Conference on System Sciences (HICCS), online, January 5-8, 2021. University of Hawai’i at Manoa. https://scholarspace.manoa.hawaii.edu/items/ee3bb519-4451-49db-8b16-390e777f2f0c
  29. Olfat, M., Ahmadi, S., Shokouhyar, S., Bazeli, S., 2022. Linking organizational members’ social-related use of enterprise social media (ESM) to their fashion behaviors: the social learning and stimulus-organism-response theories. Corporate Communications 27(1). https://doi.org/10.1108/CCIJ-04-2021-0044
  30. Palomino-Navarro, N., Arbaiza, F., 2022. The role of a chabot personality in the attitude of consumers towards a banking brand. Information Systems and Technologies 390–400. Springer International Publishing
  31. Savanur, A., M, N., P, A. M., P, D., 2021. Application of chatbot for consumer perspective using artificial intelligence. 2021 6th International Conference on Communication and Electronics Systems (ICCES) 1479–1483. https://doi.org/10.1109/ICCES51350.2021.9488990
  32. Shen, S., Xu, K., Sotiriadis, M., Wang, Y., 2022. Exploring the factors influencing the adoption and usage of Augmented Reality and Virtual Reality applications in tourism education within the context of COVID-19 pandemic. Journal of Hospitality, Leisure, Sport and Tourism Education 30. https://doi.org/10.1016/j.jhlste.2022.100373
  33. Sidaoui, K., 2021. Chatbots in Healthcare-The Effects of Affective and Cognitive Empathy on the User’s Satisfaction with, Trust in, and Loyalty to the Service. Radboud University Press, Netherlands
  34. Skjuve, M., Følstad, A., Fostervold, K. I., Brandtzaeg, P. B., 2021. My chatbot companion - a study of human-chatbot relationships. International Journal of Human-Computer Studies 149, 102601. https://doi.org/https://doi.org/10.1016/j.ijhcs.2021.102601
  35. Wang, P., Shao, J., 2022. Escaping loneliness through tourist-chatbot interactions. In Information and Communication Technologies in Tourism 2022. https://doi.org/10.1007/978-3-030-94751-4_44
  36. Yun, J., Park, J., 2022. The effects of chatbot service recovery with emotion words on customer satisfaction, repurchase intention, and positive word-of-mouth. Frontiers in Psychology 13. https://doi.org/10.3389/fpsyg.2022.922503

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