Extending SaaSQual: The Role of Generative AI–Driven Innovation and Price Sensitivity in B2B SaaS Customer Satisfaction and Continuance Intention

초록

This study investigates how SaaS service quality influences customer satisfaction and continuance intention in generative AI–enabled B2B SaaS environments, where AI-powered copilots and intelligent automation are reshaping organizational work practices. Extending the SaaSQual framework, the study reconceptualizes innovation as a core service quality dimension that captures generative AI–driven functionalities beyond traditional quality factors. Drawing on SaaSQual, UTAUT, and Diffusion of Innovations theory, the research model examines the effects of service quality on customer satisfaction and continuance intention, while testing the mediating role of ease of adoption and the moderating role of price sensitivity. Survey data from 200 B2B SaaS users in South Korea were analyzed using structural equation modeling. The results indicate that innovation, security, and ease of use significantly enhance customer satisfaction, with generative AI–driven innovation emerging as the most influential factor. Customer satisfaction strongly affects continuance intention, whereas ease of adoption does not exert an additional direct effect. Price sensitivity partially moderates the relationship between service quality and customer satisfaction. Overall, the findings highlight the strategic importance of generative AI–driven innovation in contemporary B2B SaaS and provide theoretical and practical implications for designing satisfaction-centered, sustainable SaaS offerings.

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