講座題目：Identity Disclosure and Anthropomorphism in Voice Chatbot Design：A Field Experiment
主 講 人：代宏硯 教授
講座時間：2024年3月91766559日（周四）13:00
講座地點：MBA教育中心階梯教室
主 持 人：劉小元 彩神v商學院教授
主講人介紹：
代宏硯，彩神v商學院教授、博士生導師，中財MBA課程教授/導師，美國杜克大學訪問學者。獲得清華大學碩士學位，香港科技大學博士學位。研究方向為數據驅動的優化決策、物聯網、人機交互。發表40餘篇論文，包括Management Science，European Journal of Operational Research，管理科學學報，管理工程學報等國內外旗艦期刊，主持國家自然科學基金重大研究計劃培育項目、國家自然科學基金麵上項目等多項國家省部級科研項目。獲得全國物流學會優秀論文第一名，浙江省科技進步三等獎，中國物流與采購聯合會科學技術獎二等獎等多項科研獎勵。為京東到家、易點雲、國家電網、香港Esquel集團等多家國內國際知名企業提供數據驅動的運營管理解決方案，並獲得全球華人學者管理科學與工程年會“管理科學實踐獎”二等獎。
講座摘要：
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 evalsuate 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 a reduced 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. Moreover, interestingly, even when the chatbot’s identity is disclosed along with humanizing features, the operational outcomes still improve. The magnitude of improvement is comparable to the enhancement achieved by humanizing the chatbot without disclosing its identity. 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. On a broader note, this study contributes valuable insights into the effective implementation of voice chatbots in business settings.
