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All Journal Jurnal Ilmu Manajemen Jurnal Ilmu Manajemen
Willa Putri Malinda Buchori
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 findings indicate that algorithmic performance expectations significantly enhance consumer trust, which subsequently drives spontaneous purchasing decisions. These insights suggest that consumers’ perceptions of the accuracy and transparency of AI recommendation systems are crucial factors for e-commerce businesses in building platform trust, reducing user skepticism, and effectively encouraging spontaneous consumption among digital shoppers.
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 findings indicate that algorithmic performance expectations significantly enhance consumer trust, which subsequently drives spontaneous purchasing decisions. These insights suggest that consumers’ perceptions of the accuracy and transparency of AI recommendation systems are crucial factors for e-commerce businesses in building platform trust, reducing user skepticism, and effectively encouraging spontaneous consumption among digital shoppers.
Co-Authors Septiningdyah Arianisari Syahida Norviana Victoria Kusumaningtyas Priyambodo