Service Quality and Algorithmic Matching as Predictors of Customer Satisfaction Among Muslimah University Students in Surabaya, Indonesia
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Abstract
The rapid expansion of digital ride-hailing platforms in Indonesia has intensified scholarly interest in understanding the determinants of user satisfaction, particularly among underrepresented demographic groups. This study investigates the extent to which service quality and algorithmic driver-passenger matching influence the satisfaction of Muslimah, defined here as Muslim women, who utilize the Gocar ride-hailing service in Surabaya, Indonesia. Employing a mixed-method research design, the study gathered quantitative data through structured Likert-scale questionnaires administered to 100 Muslimah university students, supplemented by thematic interviews conducted with 20 purposively selected respondents. Multiple linear regression analysis was performed to assess the partial and simultaneous effects of the independent variables on customer satisfaction. The results demonstrate that both service quality and algorithmic matching exert significant positive influences on customer satisfaction, both individually and jointly. Together, the two variables account for 44.6% of the variance in satisfaction outcomes, as indicated by the coefficient of determination. Qualitative findings further reveal that persistent concerns include intrusive interactions initiated by male drivers and extended waiting periods attributable to suboptimal algorithmic matching. These findings carry direct implications for platform operators seeking to refine service delivery models for Muslimah user segments. The study contributes to the nascent literature on gender-sensitive digital service design within the context of Islamic consumer behavior. The findings are specific to the Surabaya urban context and should be generalized with caution to broader Muslimah populations across diverse urban settings in Indonesia.
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