Identity Disclosure and Anthropomorphism in Voice Chatbot Design: A Field Experiment

53 Pages Posted: 21 Dec 2022 Last revised: 19 Jan 2024

See all articles by Yuqian Xu

Yuqian Xu

University of North Carolina (UNC) at Chapel Hill - Kenan-Flagler Business School

Hongyan Dai

Central University of Finance and Economics

Wanfeng Yan

Yunyou Freight

Date Written: December 7, 2022

Abstract

Fueled by the widespread adoption of algorithms and artificial intelligence (AI), the use of chatbots has become increasingly popular in various business contexts. In this paper, we study how to effectively and appropriately use voice chatbots, particularly by leveraging two design features: identity disclosure and anthropomorphism, and evaluate their impact on the firm operational performance. In collaboration with a large truck-sharing platform, we conducted a field experiment that randomly assigned 11,000 truck drivers to receive outbound calls from the voice chatbot dispatcher of our focal platform. Our empirical results suggest that disclosing the identity of the chatbot at the beginning of the conversation negatively affects operational performance, leading to around 11% reduction in the response rate. However, humanizing the voice chatbot by adding our proposed anthropomorphism features (i.e., interjections and filler words) significantly improves response rate, conversation length, and order acceptance intention by over 5.6%, 24.9%, and 10.1%, respectively. Moreover, even when the chatbot's identity is disclosed along with humanizing features, the operational outcomes still improve. This finding suggests that enhancing anthropomorphism may potentially counteract the negative effects of chatbot identity disclosure.
Finally, we propose one plausible explanation for the performance improvement---the enhanced trust between humans and algorithms and provide empirical evidence that drivers are more likely to disclose information to chatbot dispatchers with anthropomorphism features. Our proposed anthropomorphism improvement solutions are currently being implemented and utilized by our collaborator platform.

Keywords: Chatbot, Field Experiment, Artificial Intelligence, Operational Transparency, Anthropomorphism

Suggested Citation

Xu, Yuqian and Dai, Hongyan and Yan, Wanfeng, Identity Disclosure and Anthropomorphism in Voice Chatbot Design: A Field Experiment (December 7, 2022). Kenan Institute of Private Enterprise Research Paper No. 4296708, Available at SSRN: https://ssrn.com/abstract=4296708 or http://dx.doi.org/10.2139/ssrn.4296708

Yuqian Xu (Contact Author)

University of North Carolina (UNC) at Chapel Hill - Kenan-Flagler Business School ( email )

McColl Building
Chapel Hill, NC 27599-3490
United States

Hongyan Dai

Central University of Finance and Economics ( email )

No 39. Xueyuan South Road
Haidai District
Beijing, 100081
China

Wanfeng Yan

Yunyou Freight ( email )

Zhengxue Road 77
Shanghai, Shanghai 200000
China
18821236769 (Phone)
200000 (Fax)

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