Service chatbot: Co-citation and big data analysis toward a review and research agendaopen access
- Authors
- Lee, Sae Eun; Ju, Naan; Lee, Kyu-Hye
- Issue Date
- Sep-2023
- Publisher
- ELSEVIER SCIENCE INC
- Keywords
- Retail service chatbot; Documentation co-citation analysis; Intellectual structure; Topic modeling; News analysis
- Citation
- TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, v.194, pp.1 - 14
- Indexed
- SSCI
SCOPUS
- Journal Title
- TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
- Volume
- 194
- Start Page
- 1
- End Page
- 14
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/192299
- DOI
- 10.1016/j.techfore.2023.122722
- ISSN
- 0040-1625
- Abstract
- This study identified the research trends and intellectual structure of chatbots, through chatbot-related articles to suggest a future research agenda. Systematic literature reviews were performed on 386 articles from the Web of Science database. The intellectual structure investigated major articles and research topics, wherein the research gap and agenda were identified by analyzing keywords. Research on chatbots has been rapidly increasing since 2021, and is being conducted based on the theory of technology adoption. Althrough the bias of chatbots as well as issues related to ethics and security were treated as important topics in newspaper articles, studies were found to be insufficient. As a research variable, there have been many studies verifying the effect of chatbot humanness. However, studies on individual factors and strategies that influence the adoption and proliferation of chatbots are insufficient.
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Collections - 서울 생활과학대학 > 서울 의류학과 > 1. Journal Articles
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