THE IMPACT OF RECOMMENDATION ALGORITHMS ON CONSUMER BEHAVIOR IN E-COMMERCE

Personal recommendation algorithms restructure the customer’s usual path: they dramatically reduce the time needed to find a product, stimulate the growth of the average receipt, and strengthen the habit of returning to the site quickly. This article examines exactly how these algorithms change the habits and expectations of online shoppers. Special attention is also paid to psychological triggers – the effect of social proof, a decrease in cognitive costs and an increase in the effect of “loss of lost profits.”

Authors

Publication Details

Journal
EKONOMIKA I UPRAVLENIE PROBLEMY RESHENIYA
Published
2025-01-01
DOI
https://doi.org/10.36871/ek.up.p.r.2025.06.01.027
Primary Topic
Customer churn and segmentation
Type
article
Field-Weighted Citation Impact
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article

THE IMPACT OF RECOMMENDATION ALGORITHMS ON CONSUMER BEHAVIOR IN E-COMMERCE

Madina S. Shakhbazova, Beslan R. Alaudinov
EKONOMIKA I UPRAVLENIE PROBLEMY RESHENIYA
Customer churn and segmentation
article

THE IMPACT OF RECOMMENDATION ALGORITHMS ON CONSUMER BEHAVIOR IN E-COMMERCE

Madina S. Shakhbazova, Beslan R. Alaudinov
article en

Abstract

Personal recommendation algorithms restructure the customer’s usual path: they dramatically reduce the time needed to find a product, stimulate the growth of the average receipt, and strengthen the habit of returning to the site quickly. This article examines exactly how these algorithms change the habits and expectations of online shoppers. Special attention is also paid to psychological triggers – the effect of social proof, a decrease in cognitive costs and an increase in the effect of “loss of lost profits.”

EKONOMIKA I UPRAVLENIE PROBLEMY RESHENIYAVol. 6/1(159)
Openalex Percentile: Top 81%
Customer churn and segmentation
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THE IMPACT OF RECOMMENDATION ALGORITHMS ON CONSUMER BEHAVIOR IN E-COMMERCE — Madina S. Shakhbazova, Beslan R. Alaudinov · EKONOMIKA I UPRAVLENIE PROBLEMY RESHENIYA (2025) | TGRS Research Map | TGRS