Unveiling the path to AI adoption in healthcare: The mediating influence of professional trust across technical, ethical, and psychological factors

Abstract

Research on mapping data types and information processing algorithms in the era of digital transformation for corporate quality information systems is highly urgent in 2026. The era of digital transformation demands that companies transform data from a passive asset into a strategic asset to increase efficiency and competitive advantage. The purpose of this study is to analyze the relationship between data type mapping and the quality of corporate information systems in the digital era, as well as the relationship between information processing algorithms and the quality of corporate information systems in the digital era. This research method is quantitative, using SmartPLS to analyze variance-based structural equation modeling (PLS-SEM). Research data were analyzed from questionnaires using a Likert scale (e.g., 1 = Strongly Disagree to 5 = Strongly Agree) to measure related variables. Online questionnaires were distributed through social media. The respondents of this study were 345 company managers who use management information systems. The analysis process involves two main stages, namely: (1) testing the validity (convergent and discriminant) and reliability (internal consistency, composite reliability, and Cronbach's alpha) of the questionnaire instrument, and (2) testing causal relationships or hypotheses between latent variables, including testing mediation and moderation effects, to predict relationships and confirm theories. With its ability to handle complex models and small samples, SmartPLS is a powerful tool for analyzing factors that influence the quality of information systems. The variables in this study are independent variables, namely data type mapping and information processing algorithms. The dependent variable is the quality of the information system. The results of this study indicate that data type mapping has a positive relationship with the quality of corporate information systems in the digital era, and that information processing algorithms have a positive relationship with the quality of corporate information systems in the digital era.