Scientific Mapping of Chatbot Literature: A Bibliometric Analysis-Reference-Cited by-同舟云学术

Scientific Mapping of Chatbot Literature: A Bibliometric Analysis

Published:2024-04-01 Issue:2 Volume:9 Page:323-340
ISSN:2455-7749
Container-title:International Journal of Mathematical, Engineering and Management Sciences
language:en
Short-container-title:Int. j. math. eng. manag. sci.

Author:

Tanwar Manju¹,Verma Harsh V.²

Affiliation:

1. Department of Commerce, Shaheed Bhagat Singh College (M), University of Delhi, Delhi, India.

2. Faculty of Management Studies, University of Delhi, Delhi, India.

Abstract

The use of chatbots for customer service has gained momentum in recent years. Increasing evidence has shown that chatbots can transform the customer service landscape. Nevertheless, this topic currently lacks adequate bibliometric and visualization research. In order to review and summarise the research on chatbots, the study employs a bibliometric analysis approach to gain a comprehensive understanding of chatbots. The study uses bibliometric analysis of 798 documents sourced from the Scopus database from 2001 to 2022. The combination of biblioshiny (web interface application of Bibliometrix) and VOS viewer software was used to visualize the analysis. The study's findings reveal three prominent areas in the current research: antecedents of the adoption of chatbots, application of chatbots and behavioural & relational outcomes of the application of chatbots. The future directions and implications have been discussed in the study's conclusion.

Publisher

Ram Arti Publishers

Reference80 articles.

1. Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427-445.

2. Adamopoulou, E., & Moussiades, L. (2020). Chatbots: History, technology, and applications. Machine Learning with Applications, 2, 100006.

3. Ahmad, R., Siemon, D., & Robra-Bissantz, S. (2020). ExtraBot vs introBot: The influence of linguistic cues on communication satisfaction. In Americas Conference on Information Systems (pp.1-10). Association for Information Systems.

4. Ahn, J., Kim, J., & Sung, Y. (2022). The effect of gender stereotypes on artificial intelligence recommendations. Journal of Business Research, 141, 50-59.

5. Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers in Human Behavior, 85, 183-189.