Factors influencing continuous intention to use chatbots and their socio-economic development implications: evidence from Jordan’s telecommunications industry
Year: 2025
Type: article
Study design: Observational Study
Abstract: Purpose This study aims to examine the factors influencing customers’ continuous intention to use chatbots in Jordan’s telecommunications industry by integrating the Stimulus-Organism-Response (S-O-R) framework with the technology acceptance model. Design/methodology/approach A quantitative research design was employed to examine the relationships between stimulus factors and users' continuous intention to use telecom chatbots. Data were collected from 331 users of Jordan’s 3 major telecom providers through an online questionnaire and analysed using structural equation modelling. Findings The results show that perceived responsiveness and usefulness significantly influence customers’ continuous intention to use chatbots in the telecommunications industry. Moreover, trust fully mediates the relationship between anthropomorphism and continuous intention and partially mediates the link between responsiveness and continuous intention, highlighting its central role in fostering sustained use. In contrast, perceived enjoyment was not a significant predictor. Additionally, age was found to moderate the relationship between perceived usefulness and continuous intention, with younger users demonstrating a stronger intention to continue using chatbots. Practical implications The findings highlight that human–chatbot interaction is shaped by both logical assessment and emotional processes. This study provides insights for designing and implementing chatbots that drive economic efficiencies and social inclusion in the telecommunications industry. Originality/value The study highlights the critical role of functional performance and trust in driving users’ continuous intention to use chatbots, particularly in emerging markets where artificial intelligence is still gaining user acceptance. These insights contribute to the growing body of literature on chatbot usage and sustainable digital services.
Institution: University of Jordan
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7116983385