Iranian Journal of Information Processing and Management

Iranian Journal of Information Processing and Management

Presenting a Model of the Impact of AI-Based Chatbots on Purchase Behavior with the Mediation of Satisfaction and Loyalty (Case Study of SnappFood)

Document Type : Original Article

Authors
1 M.A. Student, Department of Business Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Iranian Research Institute for Information Science and Technology
3 Associate Professor of Information Technology Management, Department of Information Technology Management, Iran Research Institute for Information Science and Technology (IRANDOC), Tehran, Iran
10.22034/jipm.2026.2084243.2187
Abstract
The expansion of artificial intelligence applications in digital platforms, particularly intelligent chatbots, has transformed the way customers interact with online services. This study aims to present a model of the impact of intelligent chatbot characteristics on customer purchase behavior through the mediating roles of satisfaction and loyalty on the SnappFood platform. This research is applied in terms of purpose and descriptive-survey in terms of method. The statistical population consisted of SnappFood users in Tehran who had at least one documented interaction with the platform's chatbot system during the three months leading up to October and November 2025. Convenience sampling was employed, and 150 valid questionnaires were collected. Data were analyzed using Structural Equation Modeling with Partial Least Squares (PLS-SEM) and SmartPLS software. The key findings indicate that chatbot characteristics—including user-friendliness (0.342), communicability (0.306), reliability (0.243), security and privacy (0.226), and perceived usefulness (0.172)—have a positive and significant effect on customer satisfaction (p ≤ 0.001). Furthermore, customer satisfaction strongly influences loyalty (0.597), and customer loyalty has a very strong impact on purchase behavior (0.655). The proposed model explained 62% of the variance in satisfaction, 35% of the variance in loyalty, and 43% of the variance in purchase behavior. Analysis of indirect effects confirmed the chain mediation role of satisfaction and loyalty in transmitting the effect of chatbot characteristics to purchase behavior. Practical recommendations derived from the findings include: (1) prioritizing user-friendly design and communicability as the strongest predictors of customer satisfaction; (2) investing in improving chatbot interaction experience as part of brand loyalty strategy; (3) clarifying privacy and data security policies as essential prerequisites for digital interaction; and (4) utilizing chatbots to increase customer lifetime value (CLV) through smart reminders, personalized suggestions, and loyalty discounts. Implementing these recommendations can lead to increased conversion rates, repeat purchases, and market share for online food ordering platforms.
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Articles in Press, Accepted Manuscript
Available Online from 18 July 2026

  • Receive Date 31 January 2026
  • Revise Date 15 June 2026
  • Accept Date 16 June 2026