Optimizing Linguistic Outcomes in Education: A CRM-Based Structural Equation Modeling Approach

In the evolving landscape of education, optimizing linguistic outcomes through Customer Relationship Management (CRM) has emerged as a strategic approach to enhancing student engagement and institutional performance. This study investigates the role of Educational Customer Relationship Management (EdCRM) in supporting language learning within higher education institutions (HEIs) in the Republic of Indonesia. Conducted in 2024, the research draws insights from a Structural Equation Modeling (SEM) framework to examine how institutional capability (IC), student orientation (SO), digital technology (DT), and facilitating conditions (FC) contribute to EdCRM success. Additionally, the study evaluates the impact of FC and EdCRM success on institutional performance (IP) in the context of language education. A validated survey instrument adapted from existing literature was employed, and data were collected through a stratified random sampling method from 537 respondents, comprising students and faculty members. Descriptive statistics indicated that 58% of respondents were female, with an average age of 21.6 years. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that IC, SO, and DT significantly enhance EdCRM success, while FC does not have a direct predictive effect. Nevertheless, both FC and EdCRM success positively influence institutional performance. Based on these insights, the study provides practical recommendations for strengthening EdCRM implementation to support language learning and optimize institutional outcomes in higher education.

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