PENGARUH ALGORITHMIC RECOMMENDATION DAN INFORMATION OVERLOAD TERHADAP E-COMMERCE PURCHASE DECISIONS: MEDIASI TRUST IN PLATFORM ALGORITHMS

Daniel Fonseca; Fry Melda Saragih

doi:10.37888/bjrm.v9i2.1091

Authors

Daniel Fonseca Institut Teknologi dan Bisnis Sabda Setia
Fry Melda Saragih Institut Teknologi dan Bisnis Sabda Setia

DOI:

https://doi.org/10.37888/bjrm.v9i2.1091

Keywords:

Algoritmic Recommendations, Information Overload, Trust in Platform Algorithm, Purchase Decision, E-commerce

Abstract

This study aims to analyze the influence of algorithmic recommendation and information overload on purchase decisions in e-commerce platforms, with trust in platform algorithms acting as a mediating variable. This study employs a quantitative approach grounded in the Stimulus-Organism-Response (S-O-R) theoretical framework. Data was collected via questionnaires from 172 university students actively using e-commerce in Indonesia, aged 18-25, utilizing a purposive sampling technique. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS software. The results indicate that algorithmic recommendation has a positive and significant effect on both trust in platform algorithms and purchase decision. A unique finding of this study reveals that information overload also exerts a positive and significant impact on trust and purchase decision. Contrary to classic cognitive fatigue theories, digital native students perceive excessive information as information richness, which strengthens the platform's legitimacy. Furthermore, trust in platform algorithms is proven to positively affect purchase decisions while partially mediating the relationship between both stimuli (algorithmic recommendation and information overload) and purchase decisions. Practically, this study suggests that e-commerce businesses should focus on transparent and structured information presentation with optimal UI, rather than restricting the amount of product information for Generation Z consumers.

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