Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
7-2023
Abstract
This study examined business communication practices with chatbots among various Small and Medium Enterprise (SME) stakeholders in Singapore, including business owners/employees, customers, and developers. Through qualitative interviews and chatbot transcript analysis, we investigated two research questions: (1) How do the expectations of SME stakeholders compare to the conversational design of SME chatbots? and (2) What are the business reasons for SMEs to add human-like features to their chatbots? Our findings revealed that functionality is more crucial than anthropomorphic characteristics, such as personality and name. Stakeholders preferred chatbots that explicitly identified themselves as machines to set appropriate expectations. Customers prioritized efficiency, favoring fixed responses over free text input. Future research should consider the evolving expectations of consumers, business owners, and developers as chatbot technology advances and becomes more widely adopted.
Keywords
business communication, chatbots, interview, qualitative, Small and Medium Enterprise, SME, transcript logs
Discipline
Business and Corporate Communications | Databases and Information Systems | Numerical Analysis and Scientific Computing
Research Areas
Corporate Communication
Publication
CUI '23: Proceedings of the 5th International Conference on Conversational User Interfaces, Eindhoven, July 19-21
First Page
1
Last Page
5
ISBN
9798400700149
Identifier
10.1145/3571884.3604315
Publisher
ACM
City or Country
New York
Citation
MAKANY, Tamas; ROH, Sungjong; HARA, Kotaro; HUA, Jie Min; GOH, Felicia Si Ying; and TEH, Wilson Yang Jie.
Beyond anthropomorphism: Unraveling the true priorities of chatbot usage in SMEs. (2023). CUI '23: Proceedings of the 5th International Conference on Conversational User Interfaces, Eindhoven, July 19-21. 1-5.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/7255
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
External URL
https://api.elsevier.com/content/abstract/scopus_id/85167790827
Included in
Business and Corporate Communications Commons, Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons