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Syahida Norviana
Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Algorithmic Performance Expectations and Impulsive Buying in E-Commerce: Trust in Algorithm-Generated Recommendations as a Mediator Syahida Norviana; Victoria Kusumaningtyas Priyambodo; Septiningdyah Arianisari; Willa Putri Malinda Buchori
JURNAL ILMU MANAJEMEN Vol. 23 No. 1: JUNE 2026
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jim.v23i1.95607

Abstract

This study investigates the impact of algorithmic performance expectations on impulsive buying behavior within e-commerce platforms, with trust in algorithm-generated recommendations serving as a mediating variable. A structured questionnaire was administered to 116 online shoppers in Yogyakarta, Indonesia. The hypothesized relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The empirical results confirm that algorithmic performance expectations significantly enhance consumer trust (β = 0,627, p < 0,05), which in turn, positively drives impulsive purchasing behavior (β = 0,423, p < 0,05). This findings suggest that consumer perceptions of algorithmic accuracy and transparency are pivotal in fostering trust and spontaneous consumption.
Algorithmic Performance Expectations and Impulsive Buying in E-Commerce: Trust in Algorithm-Generated Recommendations as a Mediator Syahida Norviana; Victoria Kusumaningtyas Priyambodo; Septiningdyah Arianisari; Willa Putri Malinda Buchori
JURNAL ILMU MANAJEMEN Vol. 23 No. 1: JUNE 2026
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jim.v23i1.95607

Abstract

This study investigates the impact of algorithmic performance expectations on impulsive buying behavior within e-commerce platforms, with trust in algorithm-generated recommendations serving as a mediating variable. A structured questionnaire was administered to 116 online shoppers in Yogyakarta, Indonesia. The hypothesized relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The empirical results confirm that algorithmic performance expectations significantly enhance consumer trust (β = 0,627, p < 0,05), which in turn, positively drives impulsive purchasing behavior (β = 0,423, p < 0,05). This findings suggest that consumer perceptions of algorithmic accuracy and transparency are pivotal in fostering trust and spontaneous consumption.
Co-Authors Septiningdyah Arianisari Victoria Kusumaningtyas Priyambodo Willa Putri Malinda Buchori