Eksplorasi Penelitian Chatbot: Tinjauan Literatur tentang Aplikasi, Teknologi, Kesenjangan Penelitian, dan Arah Pengembangan dalam Tiga Tahun Terakhir
Isi Artikel Utama
Abstrak
Chatbot telah berkembang menjadi salah satu teknologi kecerdasan buatan yang banyak dimanfaatkan dalam berbagai sektor, termasuk pendidikan, kesehatan, bisnis, dan layanan pelanggan. Perkembangan Generative Artificial Intelligence (Generative AI) semakin meningkatkan kemampuan chatbot dalam memahami konteks, menghasilkan konten, serta mendukung proses pengambilan keputusan. Tujuan: Penelitian ini bertujuan untuk menganalisis perkembangan penelitian chatbot, mengidentifikasi domain penerapan, teknologi yang digunakan, serta arah penelitian masa depan berdasarkan publikasi terindeks Scopus periode 2024–2026. Metode: Penelitian menggunakan metode Systematic Literature Review (SLR) dengan mengadopsi kerangka kerja PRISMA. Sebanyak 200 artikel diperoleh dari basis data Scopus. Setelah proses penghapusan duplikasi dan penerapan kriteria inklusi serta eksklusi, diperoleh 86 artikel yang memenuhi syarat untuk dianalisis. Analisis dilakukan berdasarkan tren publikasi, domain aplikasi, teknologi yang digunakan, serta kesenjangan penelitian yang ditemukan. Hasil: Hasil kajian menunjukkan bahwa bidang pendidikan, kesehatan, dan layanan pelanggan merupakan domain penerapan chatbot yang paling dominan. Dari sisi teknologi, penelitian terkini banyak memanfaatkan Natural Language Processing (NLP), Machine Learning, Large Language Models (LLMs), dan Retrieval-Augmented Generation (RAG). Selain itu, chatbot berbasis Generative AI menunjukkan kemampuan yang lebih baik dalam penalaran, personalisasi layanan, dan pembuatan konten. Kesimpulan: Chatbot telah berevolusi menjadi asisten digital cerdas yang mendukung transformasi digital di berbagai sektor. Penelitian mendatang perlu difokuskan pada
##plugins.themes.bootstrap3.displayStats.downloads##
Rincian Artikel
Terbitan
Bagian
Artikel ini berlisensi Creative Commons Attribution 4.0 International License.
Cara Mengutip
Referensi
[1] Song, S. W., & Shin, M. (2024). Uncanny Valley Effects on Chatbot Trust, Purchase Intention, and Adoption Intention in the Context of E-Commerce: The Moderating Role of Avatar Familiarity. International Journal of Human-Computer Interaction, 40(2), 441–456. https://doi.org/10.1080/10447318.2022.2121038
[2] Manigandan, L., & Alur, S. (2024). An In-depth Investigation into the Influence of Chatbot Usability and Age on Continuous Intention to Use: A Comprehensive Study. Asia Pacific Journal of Information Systems, 34(1), 351–371. https://doi.org/10.14329/apjis.2024.34.1.351
[3] Sun, Y., Chen, J., & Sundar, S. S. (2024). Chatbot ads with a human touch: A test of anthropomorphism, interactivity, and narrativity. Journal of Business Research, 172. https://doi.org/10.1016/j.jbusres.2023.114403
[4] Loureiro, S. M. C., Ali, F., & Ali, M. (2024). Symmetric and Asymmetric Modeling to Understand Drivers and Consequences of Hotel Chatbot Engagement. International Journal of Human-Computer Interaction, 40(3), 782–794. https://doi.org/10.1080/10447318.2022.2124346
[5] Shahzad, M. F., Xu, S., An, X., & Javed, I. (2024). Assessing the impact of AI-chatbot service quality on user e-brand loyalty through chatbot user trust, experience and electronic word of mouth. Journal of Retailing and Consumer Services, 79. https://doi.org/10.1016/j.jretconser.2024.103867
[6] Krutta, M., & Phongpaibul, M. (2024). The Study of User Experience Interview Using Semantic Analysis and Short-Term Memory Chatbot. InCIT 2024, 461–466. https://doi.org/10.1109/InCIT63192.2024.10810597
[7] Preetha, K. G., et al. (2024). Interactive Chatbot with AI Support for Universities: Enhancing Student Engagement and Administrative Efficiency. LNNS, 1049, 284–292. https://doi.org/10.1007/978-3-031-64779-6_27
[8] Kosyluk, K., et al. (2024). Mental distress, label avoidance, and use of a mental health chatbot: Results from a US survey. JMIR Formative Research, 8. https://doi.org/10.2196/45959
[9] Dogan, O., & Gurcan, O. F. (2024). Enhancing Hospital Services: Utilizing Chatbot Technology for Patient Inquiries. LNNS, 1090, 233–239. https://doi.org/10.1007/978-3-031-67192-0_29
[10] Ouaddi, C., et al. (2024). A Graphical DSL for Accelerating Chatbot Development. CommNet 2024. https://doi.org/10.1109/CommNet63022.2024.10793369
[11] Cheah, M. H., et al. (2024). Testing the Feasibility and Acceptability of Using an Artificial Intelligence Chatbot to Promote HIV Testing and Pre-Exposure Prophylaxis in Malaysia. JMIR Human Factors, 11. https://doi.org/10.2196/52055
[12] Gutiérrez-Ferré, A., et al. (2024). Generative AI Chatbot in PyramidApp: Students’ Behaviors and Design Principles. LNCS, 14890, 248–256. https://doi.org/10.1007/978-3-031-67998-8_19
[13] Sato, A., et al. (2024). Preliminary Screening for Hereditary Breast and Ovarian Cancer Using an AI Chatbot as a Genetic Counselor. JMIR, 26(1). https://doi.org/10.2196/48914
[14] Lacerda, A., et al. (2024). Gamified Chatbot Management Process: A Way to Build Gamified Chatbots. LNNS, 1066, 18–36. https://doi.org/10.1007/978-3-031-66428-1_2
[15] Liu, C.-C., et al. (2024). Analysis of a chatbot as a dialogic reading facilitator. Educational Technology Research and Development, 72(4), 2103–2131. https://doi.org/10.1007/s11423-024-10370-0
[16] Zhang, X., et al. (2024). Is AI chatbot recommendation convincing customer? Acta Psychologica, 250. https://doi.org/10.1016/j.actpsy.2024.104501
[17] Malik, A., & Kumar, T. (2024). Design of a Chatbot for Relieving Academic Stress in Adolescent Students. LNNS, 948, 83–102. https://doi.org/10.1007/978-981-97-1329-5_8
[18] Suma Reddy, N., et al. (2024). Analyzing the effectiveness of AI-powered Chatbots. Augmenting Retail Reality, Part B. https://doi.org/10.1108/978-1-83608-708-320241015
[19] Liu, H., et al. (2024). Anthropomorphizing IQ and EQ of Chatbots for Service Recovery. ICIS 2024.
[20] Chanakot, B., & Sanrach, C. (2024). A Thai-language chatbot analyzing mosquito-borne diseases using Jaccard similarity. Bulletin of Electrical Engineering and Informatics, 13(1), 648–655. https://doi.org/10.11591/eei.v13i1.6048
[21] Jin, E., & Eastin, M. (2024). Gender Bias in Virtual Doctor Interactions: Gender Matching Effects of Chatbots and Users on Communication Satisfactions and Future Intentions to Use the Chatbot. International Journal of Human-Computer Interaction, 40(23), 8246–8258. https://doi.org/10.1080/10447318.2023.2279402
[22] Kavana, M. D., Tasdeeq, A., Poshitha, D., Hemith Kumar, R., & Dhavan, K. S. (2024). Campus Navigator: Your Go-To Chatbot For Academic Advice And Resources. IEEE International Conference on Recent Advances in Science and Engineering Technology (ICRASET 2024). https://doi.org/10.1109/ICRASET63057.2024.10895595
[23] Kim, A. R., Park, A. Y., Song, S., Hong, J. H., & Kim, K. (2024). A Microlearning-Based Self-directed Learning Chatbot on Medication Administration for New Nurses: A Feasibility Study. CIN: Computers Informatics Nursing, 42(5), 343–353. https://doi.org/10.1097/CIN.0000000000001119
[24] Purbohadi, D. (2024). Architecture Design for a Smart Chatbot to Enhance English Conversation Skills Using RiveScript, NLP, and ChatGPT. ICITCOM 2024, 272–276. https://doi.org/10.1109/ICITCOM62788.2024.10762143
[25] Makudza, F., Jaravaza, D. C., Makandwa, G., & Mukucha, P. (2024). Disruptive Artificial Intelligence: Augmenting Consumer Experience Through Chatbot Banking. In Digital Influence on Consumer Habits: Marketing Challenges and Opportunities (pp. 1–18). https://doi.org/10.1108/978-1-80455-342-820241001
[26] Følstad, A., & Bjerkreim-Hanssen, N. (2024). User Interactions With a Municipality Chatbot—Lessons Learnt From Dialogue Analysis. International Journal of Human-Computer Interaction, 40(18), 4973–4986. https://doi.org/10.1080/10447318.2023.2238355
[27] Martijn, G., Van Hooijdonk, C., Kunneman, F., & Hoeken, H. (2024). Reconfiguring the Customer Service Domain: Perspectives of Managers, Conversational Designers, and Human Agents on Human–Chatbot Collaboration. International Journal of Innovation and Technology Management, 21(4). https://doi.org/10.1142/S0219877024500287
[28] Nikou, S. A., Guliya, A., Van Verma, S., & Chang, M. (2024). A Generative Artificial Intelligence Empowered Chatbot: System Usability and Student Teachers’ Experience. LNCS, 14798, 330–340. https://doi.org/10.1007/978-3-031-63028-6_27
[29] Aksu Dünya, B., & Yıldız Durak, H. (2024). Hi! Tell me how to do it: Examination of Undergraduate Students’ Chatbot-Integrated Course Experiences. Quality and Quantity, 58(4), 3155–3170. https://doi.org/10.1007/s11135-023-01800-x
[30] Fan, H., Han, B., & Wang, W. (2024). Aligning (In)Congruent Chatbot–Employee Empathic Responses with Service-Recovery Contexts for Customer Retention. Journal of Travel Research, 63(8), 1870–1893. https://doi.org/10.1177/00472875231201505
[31] Sriwisathiyakun, K. (2024). The Effect of Using the Chatbot to Improve Digital Literacy Skill of Thai Elderly. LNNS, 800, 348–358. https://doi.org/10.1007/978-3-031-45645-9_33
[32] Krishna, B. S., Nallamothu, V. S., Yadav, M. P. T., & Srisaila, A. (2024). BERT-based Question and Answering Chatbot Based on Indian Law. I3CEET 2024, 1–4. https://doi.org/10.1109/I3CEET61722.2024.10993762
[33] Hsu, C., Tung, H.-C., Shuai, H.-H., & Chang, Y.-J. (2024). Predicting and Exploring Abandonment Signals in a Banking Task-Oriented Chatbot Service. International Journal of Human-Computer Interaction, 40(24), 8497–8511. https://doi.org/10.1080/10447318.2023.2282220
[34] Liang, K.-H., Shi, W., Oh, Y. J., Wang, H.-C., Zhang, J., & Yu, Z. (2024). Dialoging Resonance in Human-Chatbot Conversation: How Users Perceive and Reciprocate Recommendation Chatbot’s Self-Disclosure Strategy. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW1). https://doi.org/10.1145/3653691
[35] Mihalache, A., Huang, R. S., Mikhail, D., Popovic, M. M., Shor, R., Pereira, A., Kwok, J., Yan, P., Wong, D. T., Kertes, P. J., Kohly, R. P., & Muni, R. H. (2024). Interpretation of Clinical Retinal Images Using an Artificial Intelligence Chatbot. Ophthalmology Science, 4(6). https://doi.org/10.1016/j.xops.2024.100556
[36] Rajasekaran, K., Amose, J., Preethika, G., Sangamithrra, S., & Gayathiri, G. (2024). Innovations in Dental Care: Chatbot-Driven Efficiency. ICACCS 2024, 852–857. https://doi.org/10.1109/ICACCS60874.2024.10717127
[37] Larbi, D., Løvas, S. E., Årsand, E., Denecke, K., Gabarron, E., & Henriksen, A. (2025). Designing and Testing a Physical Activity App with a ChatGPT-Based Chatbot. Studies in Health Technology and Informatics, 327, 1155–1159. https://doi.org/10.3233/SHTI250571
[38] Dierolf, U., Kurze, T., Polgart, F., Skarupianski, M., & Breyer, B. (2025). The AI Chatbot “BibKI” of the KIT Library. Information-Wissenschaft Und Praxis, 76(2–3), 95–103. https://doi.org/10.1515/iwp-2025-2002
[39] Sánchez-Vera, F. (2025). Subject-Specialized Chatbot in Higher Education as a Tutor for Autonomous Exam Preparation. Education Sciences, 15(1). https://doi.org/10.3390/educsci15010026
[40] Mathur, S., Eromhonsele, A. F., Vallarino, Z., Savel, C., Oche, E., Ononye, O., Shoyemi, E., & Tun, W. (2025). “Let’s Chat!” Piloting a Digital Chatbot for HIV Prevention Among Cisgender Women and Transgender Men in Nigeria. AIDS Care, 37(6), 1015–1025. https://doi.org/10.1080/09540121.2025.2470318
[41] Cardon de Lichtbuer, P., Declerck, W., Rosseel, Q., Savieri, P., Oellerich, S., & Dhubhghaill, S. N. (2025). Enhancing Patient Education in Cataract Surgery Using a Conversational Artificial Intelligence Chatbot: A Pilot Randomized Controlled Trial. Journal of Cataract and Refractive Surgery, Publish Ahead of Print. https://doi.org/10.1097/j.jcrs.0000000000001856
[42] Rupani, N., Vasquez, D. H., Contreras, C., Menacho, L., Kolevic, L., Franke, M. F., & Galea, J. T. (2025). “Like Someone Is Paying Attention to You, Listening to You, and Guiding You”: Acceptability of a Mental Health Chatbot Among Caregivers of Adolescents Living With HIV. Journal of the International Association of Providers of AIDS Care, 24. https://doi.org/10.1177/23259582251327911
[43] Asyraff, M. A., Md Zain, N. A., Ismail, H., & Hanafiah, M. H. (2025). Young Travellers’ Engagement and Satisfaction with Online Travel Agency’s (OTA) Chatbot Troubleshooting Services. Asia-Pacific Journal of Innovation in Hospitality and Tourism, 14(1), 47–66.
[44] Sfar, N., Sboui, M., & Baati, O. (2025). The Impact of Chatbot Anthropomorphism on Customer Experience and Chatbot Usage Intention: A Technology Acceptance Approach. International Journal of Quality and Service Sciences, 17(2), 168–194. https://doi.org/10.1108/IJQSS-06-2024-0079
[45] Atma, Y. A., Idmayanti, R., & Mulya, A. F. D. (2025). A Retrieval-Augmented Generation-Based Chatbot Using Llama 3. AIP Conference Proceedings, 3334(1). https://doi.org/10.1063/5.0295034
[46] Ho, S. S., Wijaya, S. A., & Ou, M. (2025). Designing Chatbots for Misinformation Correction: Examining the Roles of Chatbot Expertise and Anthropomorphism. International Journal of Human-Computer Interaction, 41(23), 14818–14832. https://doi.org/10.1080/10447318.2025.2490703
[47] Levner, E., & Kriheli, B. (2025). Analysis of Reliability and Efficiency of Information Extraction Using AI-Based Chatbot: The More-for-Less Paradox. Algorithms, 18(7). https://doi.org/10.3390/a18070412
[48] Rahi, S., Ngah, A. H., Alnasr, F., Alghizzawi, M., Rasheed, R., & Rashid, A. (2025). Unlocking the Precursors of Customer Service Experience Using Artificial Intelligence-Driven Chatbot: Calibration of Gratification Theory and Expectation Confirmation Model. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-10-2024-0551
[49] Fröbel, L. (2025). The Bond of User-Chatbot Identification: Understanding Users’ Relationships with Chatbot Avatars and Their Parasocial Preference for Them. Americas Conference on Information Systems (AMCIS 2025), 7, 4493–4502.
[50] Hadzhikoleva, S., Borisova, M., Hadzhikolev, E., & Raykova, Z. (2025). Building and Utilizing a Specialized Chatbot in Physics Education: Experiment and Results. INFOTEH 2025 Proceedings. https://doi.org/10.1109/INFOTEH64129.2025.10959194
[51] Pepping, J., De Wit, J., Kamoen, N., & Liebrecht, C. (2025). User-Chatbot Similarity in Communication Style and Avatar Appearance for Enhanced Learning in Education. International Journal of Human-Computer Interaction. https://doi.org/10.1080/10447318.2025.2600535
[52] Jitsangob, S., Amornsamankul, S., Hobanluekit, B., Sriwiboon, M., & Unhapipat, S. (2025). Application of Conversational Chatbot for Brake Pads Business in Thailand via LINE Application. ICIC Express Letters Part B: Applications, 16(5), 559–565. https://doi.org/10.24507/icicelb.16.05.559
[53] Guo, K., Zhong, Y., Qin, J., & Chu, S. K. W. (2025). Investigating EFL Teachers’ Lesson Planning for Chatbot-Assisted Learning of Argumentative Writing: A TPACK Perspective. Interactive Learning Environments, 33(2), 1520–1541. https://doi.org/10.1080/10494820.2024.2372646
[54] Mahendran, K., & Hooi, Y. K. (2025). English-Malay FAQ Chatbot System Using NLP. Lecture Notes in Electrical Engineering, 1417, 379–389. https://doi.org/10.1007/978-981-96-5848-0_32
[55] Kumaran, S., Bharathi, B. S., & Pradeepa, R. (2025). A College Enquiry Text-Based AI Chatbot Using Python. AIP Conference Proceedings, 3159(1). https://doi.org/10.1063/5.0247111
[56] Pan, S., & De Graaf, M. M. A. (2025). Developing a Social Support Framework: Understanding the Reciprocity in Human-Chatbot Relationship. CHI Conference on Human Factors in Computing Systems Proceedings. https://doi.org/10.1145/3706598.3713503
[57] Han, H., Park, B., & Seo, K. (2025). A Self-Determination Theory-Based Career Counseling Chatbot: Motivational Interactions to Address Career Decision-Making Difficulties and Enhance Engagement. CHI Conference on Human Factors in Computing Systems Proceedings. https://doi.org/10.1145/3706599.3720286
[58] Payonyim, N., Jandum, K., & Vachirasricirikul, S. (2025). The Design of the Conversational Chatbot Using Facebook Messenger to Support Patient Services: A Case Study of a Dental Clinic, University of Phayao. DAMT 2025 & NCON 2025, 270–275. https://doi.org/10.1109/ECTIDAMTNCON64748.2025.10962100
[59] Chen, J., Guo, F., Ren, Z., Wang, X., & Ham, J. (2025). Human-Chatbot Interaction Studies Through the Lens of Bibliometric Analysis. Universal Access in the Information Society, 24(1), 79–98. https://doi.org/10.1007/s10209-023-01058-y
[60] Chih, W.-H., Wang, K.-Y., & Banda, H. W. (2025). Chatbots at the Frontline: Unveiling Antecedents of Customers’ Willingness to Accept Chatbot Intervention in Service Recovery. Journal of Retailing and Consumer Services, 84. https://doi.org/10.1016/j.jretconser.2025.104254
[61] Kavianpour, A. (2025). Integration of Chatbot with Your Course. ASEE Annual Conference and Exposition, Conference Proceedings. https://doi.org/10.18260/1-2--56858
[62] Ni, Z., Oh, S., Saifi, R., Azwa, I., & Altice, F. L. (2025). Evaluating the Usability of an HIV Prevention Artificial Intelligence Chatbot in Malaysia: National Observational Study. JMIR Human Factors, 12. https://doi.org/10.2196/70034
[63] Sundjaja, A. M., Utomo, P., & Colline, F. (2025). The Determinant Factors of Continuance Use of Customer Service Chatbot in Indonesia E-Commerce: Extended Expectation Confirmation Theory. Journal of Science and Technology Policy Management, 16(1), 182–203. https://doi.org/10.1108/JSTPM-04-2024-0137
[64] Ehrenpreis, M., & DeLooper, J. (2025). Chatbot Assessment: Best Practices for Artificial Intelligence in the Library. Portal, 25(4), 671–702. https://doi.org/10.1353/pla.2025.a971028
[65] Cha, H., & Oh, M. (2025). An Analysis of the Learning Experience and Impact of a Chatbot Tutor in AI Education for a Liberal Course. Journal of Institutional Research South East Asia, 23(3), 348–372.
[66] Cheng, S.-T., & Ng, P. H. F. (2025). The PDC30 Chatbot—Development of a Psychoeducational Resource on Dementia Caregiving Among Family Caregivers: Mixed Methods Acceptability Study. JMIR Aging, 8. https://doi.org/10.2196/63715
[67] Maqbool, M. N., Saleem, R. M., Sarwar, N., Ibrahim, M., & Alam Hashmi, M. S. (2025). A Sentence-Level Encoder–Decoder Architecture for Designing an Administrative Roman Urdu Chatbot. Applied Computational Intelligence and Soft Computing, 2025(1). https://doi.org/10.1155/acis/4728280
[68] Oh, Y. J., Liang, K.-H., Kim, D. D., Zhang, X., Yu, Z., Fukuoka, Y., & Zhang, J. (2025). Enhancing Physical Activity Through a Relational Artificial Intelligence Chatbot: A Feasibility and Usability Study. Digital Health, 11. https://doi.org/10.1177/20552076251324445
[69] Tzitziou, G., Dratsiou, I., Tsoupouroglou, I., Dafli, E., & Bamidis, P. D. (2025). Evaluation of Academic Courses Using Chatbot: An Innovative Approach in Medical Education. Archives of Hellenic Medicine, 42(2), 236–242.
[70] Hossain, R., Khan, R. N., Roy Chowdhury, P. S., Mowla Manarat Huda, S. M., & Ahmed, N. (2025). Joyee—A PCOS Chatbot. Lecture Notes in Computer Science, 15799 LNCS, 186–203. https://doi.org/10.1007/978-3-031-93236-6_13
[71] Alarabiat, A., Alarabiat, Y., Al-Zuabi, M., & Shakatreh, M. (2026). Citizens’ Perceptions of AI Government Chatbot Adoption. Lecture Notes in Networks and Systems, 1758 LNNS, 1–9. https://doi.org/10.1007/978-3-032-13419-6_1
[72] Guatibonza Briceño, P. A., Osorio Cárdenas, D., Manrique Piramanrique, R., Rosales Rosero, E. E., & Sánchez Puccini, M. E. (2026). Evaluating an AI-Driven Chatbot Tutor for Enhancing Introductory Programming Learning. Lecture Notes in Computer Science, 15723 LNCS, 235–245. https://doi.org/10.1007/978-3-031-98281-1_19
[73] Chen, C., Hu, X., & Xu, X. (2026). Blame the Bot: Extending Attribution Dynamics in Chatbot–Consumer–Brand Interactions. Journal of Current Issues and Research in Advertising. https://doi.org/10.1080/10641734.2026.2657272
[74] Nagaraj, B., & Girisha, G. S. (2026). Design and Development of an Optimization Chatbot Using Grid Search Hyper Parameter Tuning with Performance and Execution Time Analysis to Identify Best Machine Learning Classifier. Lecture Notes in Networks and Systems, 1357 LNNS, 155–164. https://doi.org/10.1007/978-981-96-7477-0_13
[75] Han, I., Ji, H., Jin, S., & Choi, K. (2026). Mobile-Based Artificial Intelligence Chatbot for Self-Regulated Learning in a Hybrid Flipped Classroom. Journal of Computing in Higher Education, 38(1), 285–309. https://doi.org/10.1007/s12528-025-09434-8
[76] Chinta, N. M. (2026). Rule-Based Bilingual Chatbot for Student Support in Higher Education. Lecture Notes in Networks and Systems, 1872 LNNS, 79–91. https://doi.org/10.1007/978-3-032-19678-1_9
[77] Naveena, A., Zohreen, A., Vyshnavi, T., Likitha, S., & Ponnala, S. S. (2026). Medicare Chatbot. Lecture Notes in Electrical Engineering, 1466 LNEE, 1735–1740. https://doi.org/10.1007/978-981-95-0269-1_195
[78] Lapuz, M. C. M., Navarro, R. A. C., Palomo, M. C. E., Del Fonso, R. G., & Catchillar, J. A. E. (2026). Trust or Convenience: Which Is More Correlated to Continuous Usage of Chatbot Applications in the Travel Trade Industry? Proceedings of the International Conference on Tourism Research, 9(1), 272–280. https://doi.org/10.34190/ictr.9.1.4469
[79] Söderlund, M., & Andersson, M. M. (2026). The Selling-Oriented Versus Customer-Oriented Retail Chatbot and Effects on Customer Satisfaction. Journal of Retailing and Consumer Services, 92. https://doi.org/10.1016/j.jretconser.2026.104805
[80] Ashfaq, M., Makkar, M., Hoang, A.-P., Dang-Pham, D., Do, M. H. T., & Nguyen, A. T. V. (2026). Exploring Customer Stickiness During “Smart” Experiences: A Study on AI Chatbot Affinity in Online Customer Services. Journal of Research in Interactive Marketing, 20(1), 141–160. https://doi.org/10.1108/JRIM-09-2024-0452
[81] Zhang, X., Li, H., Yin, M., Zhang, M., Li, Z., & Chen, Z. (2026). Investigating AI Chatbot Dependence: Associations with Internet and Smartphone Dependence, Mental Health Outcomes, and the Moderating Role of Usage Purposes. International Journal of Human-Computer Interaction, 42(7), 5592–5604. https://doi.org/10.1080/10447318.2025.2545464
[82] Or, A., Sukumar, S., Ma, A., Ang, D., Liu, M., Ritchie, H. E., & Sarrafpour, B. (2026). Enhancing Dental Students’ History-Taking Skills With a Generative Artificial Intelligence Chatbot. Journal of Dental Education, 90(3), 384–390. https://doi.org/10.1002/jdd.13952
[83] Alsoyohi, M. F., & Algethami, N. (2026). Chatbot for Academic Advising: Case Study at Saudi Electronic University. Journal of Computer Science, 22(3), 840–859. https://doi.org/10.3844/jcssp.2026.840.859
[84] Jeon, E., & Kim, J. (2026). When Time Is Crucial: Effects of Compensation Type and Anthropomorphic Chatbots on Chatbot Service Recovery Satisfaction. Journal of Research in Interactive Marketing, 20(3), 362–380. https://doi.org/10.1108/JRIM-05-2024-0238
[85] Coker, K. K., & Thakur, R. (2026). Not All Chatbots Connect Equally: The Moderating Role of Chatbot Type. Electronic Markets, 36(1). https://doi.org/10.1007/s12525-026-00873-4
[86] Kasinathan, V., Tharenpalan, U., Mustapha, A., Xuan, O. C. Y., Li, L. X., & Yan, L. K. (2026). Vertical Chatbot for Sustainable Consumption and Production Patterns: Meet Rearth. Lecture Notes in Networks and Systems, 1566 LNNS, 513–522. https://doi.org/10.1007/978-981-95-0378-0_36