Standardization versus customization in artificial intelligence-based services: what fuels continuous intention to use on digital platforms?

초록

This study investigates how standardization and customization influence AI service quality and their subsequent effects on user satisfaction and continuous intention to use, with a focus on AI service preference as a moderating factor. Analysis of 1032 survey responses using PLS-SEM revealed that while standardization positively affects AI service quality dimensions, customization shows a stronger positive impact. AI service satisfaction significantly influences continuous intention to use. Additionally, AI service preference demonstrates dual moderating effects: positive between AI system quality and satisfaction and negative between AI recommendation quality and satisfaction. These findings provide valuable insights for service providers seeking to enhance their market competitiveness through AI-based services.

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