EXPLORING CONSUMER RESPONSE TO TEXT-BASED CHATBOTS IN F-COMMERCE: A QUALITATIVE STUDY ON BANGLADESHI SME’S

Authors

  • Md Mehedi Hasan Emon American International University-Bangladesh
  • Tahsina Khan Bangladesh University of Professionals (BUP)
  • Md. Adnan Rahman Atish Dipankar University of Science & Technology
Views: 206 Downloads: 135

DOI:

https://doi.org/10.12962/j24068535.v22i2.a1181

Abstract

This qualitative study examines the consumer response to text-based chat bots in F-commerce, specifically in the context of Bangladeshi SMEs. The study aims to explore the benefits and challenges of using chat bots in F-commerce and identify the factors that influence consumer response to chat bots. The study uses semi-structured interviews to collect data from 15 Bangladeshi consumers who have experience using chat bots in F-commerce. The findings suggest that chat bots can improve customer service, save time and effort, and provide convenience for consumers, but they also face challenges such as technical issues, language barriers, and privacy concerns. The study also identifies several factors that influence consumer response to chat bots, including perceived usefulness, perceived ease of use, trust, familiarity, and personalization. The study concludes by discussing the practical implications of the findings for SMEs in Bangladesh and suggesting directions for future research.

Downloads

Download data is not yet available.

References

D. Buhalis and E. S. Y. Cheng, “Exploring the use of chatbots in hotels: technology providers’ perspective,” in Information and Commu-nication Technologies in Tourism 2020: Proceedings of the International Conference in Surrey, United Kingdom, January 08--10, 2020, 2020, pp. 231–242.

P. Suta, X. Lan, B. Wu, P. Mongkolnam, and J. H. Chan, “An overview of machine learning in chatbots,” Int. J. Mech. Eng. Robot. Res., vol. 9, no. 4, pp. 502–510, 2020.

S. P. R. Karri and B. S. Kumar, “Deep learning techniques for implementation of chatbots,” in 2020 International Conference on Computer Communication and Informatics (ICCCI), 2020, pp. 1–5.

S. Singh and H. K. Thakur, “Survey of various AI chatbots based on technology used,” in 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO), 2020, pp. 1074–1079.

B. Jones and R. Jones, “Public service chatbots: Automating conversation with BBC News,” Digit. Journal., vol. 7, no. 8, pp. 1032–1053, 2019.

R. E. Bawack, S. F. Wamba, and K. D. A. Carillo, “Exploring the role of personality, trust, and privacy in customer experience performance during voice shopping: Evidence from SEM and fuzzy set qualitative comparative analysis,” Int. J. Inf. Manage., vol. 58, p. 102309, 2021.

E. Mogaji, J. Balakrishnan, A. C. Nwoba, and N. P. Nguyen, “Emerging-market consumers’ interactions with banking chatbots,” Telemat. Informatics, vol. 65, p. 101711, 2021.

K. A. Quesenberry, Social media strategy: Marketing, advertising, and public relations in the consumer revolution. Rowman & Littlefield Publishers, 2020.

M. Simić, M. Despotović-Zrakić, and A. Labus, “A Methodological Approach for the Promotion of a New Fashion Brand Based on a Digital Marketing Strategy,” in Sustainable Business Management and Digital Transformation: Challenges and Opportunities in the Post-COVID Era, Springer, 2022, pp. 255–277.

X. Cheng, X. Zhang, J. Cohen, and J. Mou, “Human vs. AI: Understanding the impact of anthropomorphism on consumer response to chatbots from the perspective of trust and relationship norms,” Inf. Process. & Manag., vol. 59, no. 3, p. 102940, 2022.

R. Rahman, M. R. Rahman, N. I. Tripto, M. E. Ali, S. H. Apon, and R. Shahriyar, “AdolescentBot: Understanding opportunities for chat-bots in combating adolescent sexual and reproductive health problems in Bangladesh,” in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 2021, pp. 1–15.

F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Q., pp. 319–340, 1989.

M. A. Selamat and N. A. Windasari, “Chatbot for SMEs: Integrating customer and business owner perspectives,” Technol. Soc., vol. 66, p. 101685, 2021, doi: https://doi.org/10.1016/j.techsoc.2021.101685.

A. Alnefaie, S. Singh, B. Kocaballi, and M. Prasad, “An overview of conversational agent: applications, challenges and future directions,” 2021.

S. I. Lei, G. Liu, H. Shen, S. Ye, and C. F. SiTou, “An Integrated Model of Customers’ Intention to Reuse Information Service: What’s New for Conversational Agents?,” Tour. Anal., 2022.

Downloads

Published

2024-07-31

Issue

Vol. 22, No. 2, July 2024

Section

Articles

How to Cite

[1]
M. M. H. Emon, T. Khan, and M. A. Rahman, “EXPLORING CONSUMER RESPONSE TO TEXT-BASED CHATBOTS IN F-COMMERCE: A QUALITATIVE STUDY ON BANGLADESHI SME’S”, JUTI, vol. 22, no. 2, pp. 78–82, Jul. 2024, doi: 10.12962/j24068535.v22i2.a1181.

License

All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in JUTI unless they receive approval for doing so from the Editor-in-Chief.

JUTI open access articles are distributed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.