Unveiling the impact of chatbot characteristics on customer experience and customer immunity under technological readiness
جاري التحميل...
التاريخ
عنوان الدورية
ردمد الدورية
عنوان المجلد
الناشر
Marketing Intelligence & Planning
خلاصة
Purpose – This study aims to investigate the direct effects of key chatbot characteristics – perceived usability,
interactivity, perceived intelligence and anthropomorphism – on customer experience and customer immunity. It
further examines the indirect effects of these characteristics on customer immunity through the mediating role of
customer experience. Additionally, it explores the moderating effect of technological readiness on the
relationship between chatbot characteristics and customer experience within the context of Egypt’s
telecommunications sector.
Design/methodology/approach – Research data were gathered through an online survey administered to a
convenience sample, resulting in 427 valid responses. To evaluate the proposed hypotheses, Partial Least
Squares Structural Equation Modeling (PLS-SEM) and advanced machine learning techniques, including XG
Boost, decision trees and Principal Component Analysis (PCA), were employed.
Findings – The analysis revealed that most chatbot attributes have a significant positive direct effect on
customer experience and immunity, except for perceived intelligence, which has no significant impact on
customer experience. In addition, customer experience has a positive influence on customer immunity and
partially mediates the relationship between chatbot attributes, except for perceived intelligence and customer
immunity. Furthermore, technological readiness directly enhances customer experience and moderates the
impact of chatbot characteristics – except for interactivity – on the customer experience.
Originality/value – Our study introduces “customer immunity” as a novel behavioral construct in marketing
research that has received limited attention. Specifically, we investigate its relationship with chatbot
characteristics, considering the mediating role of customer experience and the moderating role of technological
readiness, which marks a novel contribution. Additionally, it is the first to integrate four chatbot characteristics
in one model while employing both SEM and AI-driven techniques for richer insights. This dual-method
approach enhances the model’s predictive accuracy and offers theoretical and practical implications for telecom
service design and digital transformation strategies. Finally, we conclude by highlighting potential directions for
future research.