Student Perception of AI-Powered Service Quality and Customer Satisfaction: A Case Study of Higher Learning Institution in Malaysia

Abstract

As service providers increasingly employ AI-powered service agents (AISAs), concerns about how these interactions influence consumers' perceptions of service quality have grown. This study aims to analyze the effect of AI-powered service quality on customer satisfaction, specifically focusing on chatbots. Data were collected via a Google Forms survey from 113 MBA students and analyzed using SPSS for descriptive statistics and SmartPLS version 4.0 for assessing relationships between service quality dimensions and customer satisfaction. Descriptive analysis showed moderate levels of efficiency, anthropomorphism, and satisfaction, with lower scores for security. Availability received a high mean rating, suggesting a strong presence of resources. These findings indicate that while customers perceive moderate levels of efficiency, anthropomorphism, and satisfaction, improvements are needed in the security aspect of AI-powered services. The structural model assessment using PLS-SEM revealed that the availability of AI-chatbot services has the most significant positive relationship with customer satisfaction (path coefficient = 0.367, t-value = 3.997, p < 0.001). This highlights the importance of constant service availability for enhancing customer satisfaction. Anthropomorphism features also have a significant positive relationship with customer satisfaction (path coefficient = 0.252, t-value = 2.418, p < 0.01), emphasizing the positive impact of human-like interaction styles. Efficiency in AI-chatbot services similarly shows a significant positive relationship with customer satisfaction (path coefficient = 0.241, t-value = 2.348, p < 0.01). However, there is no significant positive relationship between security in AI-chatbot services and customer satisfaction. In conclusion, this study provides insights into key dimensions of AI-powered service quality and their impact on customer satisfaction, highlighting the need for improved security to enhance customer experiences.