TY - GEN
T1 - The Impact of Trust in AI Chatbots on Users’ Behavior in Online Health Communities
AU - Osta, Alain
AU - Kokkinaki, Angelika
AU - Chedrawi, Charbel
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Current literature lacks sufficient evidence on adoption of AI conversational agents (chatbots) in the healthcare industry. This research paper aims to fill this gap by investigating the acceptance of chatbots in Online Health Communities (OHCs) through a defined research model. The study examines the influence of specific features on users’ intentions and actual usage of these communities. A quantitative methodology is employed, utilizing the proposed research model to analyse users’ behavior and intentions towards AI conversational agents/chatbots in OHCs. A total of 632 responses were received from 62 countries, of which 443 were complete. The findings highlight the interconnectedness between AI conversational agents/chatbots and OHCs, particularly their impact on users’ Behavioral Intention (BI). The Trust variable is found to significantly influence participants’ Behavioral Intention (BI) and Usage Behavior (UB) towards AI conversational agents/chatbots in OHCs. Additionally, factors such as experience in chatbots, experience in technology, occupation, and geographical zones are identified as significant moderators that affect BI and UB.
AB - Current literature lacks sufficient evidence on adoption of AI conversational agents (chatbots) in the healthcare industry. This research paper aims to fill this gap by investigating the acceptance of chatbots in Online Health Communities (OHCs) through a defined research model. The study examines the influence of specific features on users’ intentions and actual usage of these communities. A quantitative methodology is employed, utilizing the proposed research model to analyse users’ behavior and intentions towards AI conversational agents/chatbots in OHCs. A total of 632 responses were received from 62 countries, of which 443 were complete. The findings highlight the interconnectedness between AI conversational agents/chatbots and OHCs, particularly their impact on users’ Behavioral Intention (BI). The Trust variable is found to significantly influence participants’ Behavioral Intention (BI) and Usage Behavior (UB) towards AI conversational agents/chatbots in OHCs. Additionally, factors such as experience in chatbots, experience in technology, occupation, and geographical zones are identified as significant moderators that affect BI and UB.
UR - http://www.scopus.com/inward/record.url?scp=85215657701&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-65782-5_14
DO - 10.1007/978-3-031-65782-5_14
M3 - Conference contribution
AN - SCOPUS:85215657701
SN - 9783031657818
T3 - Lecture Notes in Information Systems and Organisation
SP - 205
EP - 219
BT - Leading and Managing in the Digital Era - Shaping the Future of Work and Business Education
A2 - Prastacos, Gregory
A2 - Pouloudi, Nancy
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Leading and Managing in the Digital Era, LMDE 2023
Y2 - 19 June 2023 through 20 June 2023
ER -