<![CDATA[Purpose: The research aims to determine the factors that encourage users to upgrade service packages, provide actual recommendations for application developers to improve service quality, and provide insights for the development of similar applications in the future. Future Link is an application that offers efficient online fingerprint analysis with the support of artificial intelligence (AI). Despite these advantages, user acceptance and satisfaction remain challenges that hinder service package upgrades. Methods: This study combines the TAM and EUCS models to identify the variables that influence users' intentions to upgrade their service packages in a fingerprint analysis application. TAM includes key constructs such as perceived usefulness and attitude toward using, while EUCS encompasses dimensions like content, accuracy, format, timeliness, and ease of use, which collectively represent users’ satisfaction with the quality of information provided by the application. Additionally, two external variables curiosity and buying intention were added. A quantitative approach was employed using a survey method, with data collected from 151 respondents who are active users of the application. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through Smart-PLS 3.29. The analysis process included instrument development based on validated indicators, testing for construct reliability and validity, followed by evaluation of the structural model to assess the significance and explanatory power of the hypothesized relationships among variables. Result: The findings show that eight out of nine hypotheses were accepted. Significant variables influencing attitude toward use include curiosity, content, format, accuracy, perceived usefulness, and ease of use. User attitude significantly influences satisfaction, which in turn impacts service package upgrade intentions. Novelty: The combination of two theoretical models the TAM and EUCS model is used to analyze user behavior in the context of service package upgrades in fingerprint analysis applications. While previous studies have applied TAM and EUCS separately to evaluate general technology adoption or information satisfaction, this study integrates both models to provide a more comprehensive framework that considers both perceptual and experiential factors influencing user decisions. Furthermore, this study introduces two additional variables curiosity and purchase intention to reflect emerging user motivations in the use of digital services. The results are expected to support the development and improvement of applications in the future.]]>
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