AI Chatbots in Customer Service: Adoption Hurdles and Simple Remedies

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL AI Chatbots in Customer Service: Adoption Hurdles and Simple Remedies 44 Pages Posted: 14 Dec 2022 See all articles by Evgeny KaganEvgeny KaganJohns Hopkins University - Carey Business SchoolMaqbool DadaJohns Hopkins University - Carey Business SchoolBrett HathawayJohns Hopkins University - Carey Business School Date Written: November 22, 2022 Abstract Despite recent advances in language processing algorithms, chatbot technology continues to face adoption hurdles. We survey chatbot users about their experiences and use their testimonies to construct a decision model of customer choice between the chatbot service channel and the live agent service channel. The fundamentals of this choice are the time spent in line and in service, the chatbot's success rate, and the qualitative differences in the service experience provided by the chatbot and by the live agent. We then conduct experiments in which participants choose, and then experience, the chatbot or the live agent channel as we vary operational (i.e., times spent and chatbot success rates) and qualitative features of the chatbot. We find that users respond positively to improvements in chatbot operational performance; however, the chatbot channel remains underutilized relative to what expected time minimization would predict. Additional experiments show that this underutilization is caused by two separate mechanisms: algorithm aversion (aversion to an algorithmic service provider), and gatekeeper aversion (aversion to any service format that may involve multiple stages). Examining potential remedies, we find that algorithm aversion can be mitigated by making salient the expected time savings offered by the chatbot. However, gatekeeper aversion is more persistent and harder to overcome. We conclude by building and estimating a structural model of channel demand and by proposing a behavior-aware service design that reduces the firm's staffing costs by up to 22%. Keywords: Human-AI interface, Experiments, Service Operations, Behavioral Queueing Suggested Citation: Suggested Citation Kagan, Evgeny and Dada, Maqbool and Hathaway, Brett, AI Chatbots in Customer Service: Adoption Hurdles and Simple Remedies (November 22, 2022). Available at SSRN: https://ssrn.com/abstract=4283285 Evgeny Kagan (Contact Author) Johns Hopkins University - Carey Business School ( email ) 100 International DriveBaltimore, MD 21202United States Maqbool Dada Johns Hopkins University - Carey Business School ( email ) 100 International DriveBaltimore, MD 21202United States Brett Hathaway Johns Hopkins University - Carey Business School ( email ) 100 International DriveBaltimore, MD 21202United States Download This Paper Open PDF in Browser Do you have a job opening that you would like to promote on SSRN? Place Job Opening Paper statistics Downloads 7 Abstract Views 34 PlumX Metrics Related eJournals Behavioral & Experimental Economics eJournal Follow Behavioral & Experimental Economics eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 958 PAPERS 18,559 This Journal is curated by: Victor Ricciardi at Tennessee Tech University Operations Management eJournal Follow Operations Management eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 801 PAPERS 2,697 Service Management eJournal Follow Service Management eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 776 PAPERS 1,050 Feedback Feedback to SSRN Feedback (required) Email (required) Submit If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday. Submit a Paper Section 508 Text Only Pages SSRN Quick Links SSRN Solutions Research Paper Series Conference Papers Partners in Publishing Jobs & Announcements Newsletter Sign Up SSRN Rankings Top Papers Top Authors Top Organizations About SSRN SSRN Objectives Network Directors Presidential Letter Announcements Contact us FAQs Copyright Terms and Conditions Privacy Policy We use cookies to help provide and enhance our service and tailor content. To learn more, visit Cookie Settings. This page was processed by aws-apollo-4dc in 0.228 seconds