Spontaneous Purchase Patterns in E-Commerce: Determinants of Instant Buying Decisions in Virtual Retail Spaces

This study investigates the determinants of spontaneous purchase patterns in e-commerce, focusing on the psychological, emotional, social, technological, and visual factors that influence instant buying decisions. As online shopping environments evolve, understanding what drives unplanned purchases has become crucial for digital marketers and platform developers. The research adopts a quantitative approach using a structured questionnaire administered to 150 respondents, with data analyzed through SPSS employing reliability analysis, correlation, ANOVA, and multiple regression techniques. The findings reveal that emotional engagement, social influences such as peer reviews and influencer endorsements, personalized technological features, and visually appealing product presentations significantly contribute to impulse buying behaviour. The study demonstrates high internal reliability (Cronbach’s Alpha = 0.949) and strong statistical relationships (R² > 0.86) across key variables. The results support established behavioral theories, including the Theory of Planned Behaviour and Social Proof Theory. Practical implications emphasize the importance of strategic visual content, emotional branding, and urgency cues. This research provides actionable insights for optimizing marketing strategies and enhancing consumer engagement in digital retail platforms.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-07
DOI
https://doi.org/10.5281/zenodo.15718548
Primary Topic
Consumer Retail Behavior Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spontaneous Purchase Patterns in E-Commerce: Determinants of Instant Buying Decisions in Virtual Retail Spaces

Zenodo (CERN European Organization for Nuclear Research)
Consumer Retail Behavior Studies
article

Spontaneous Purchase Patterns in E-Commerce: Determinants of Instant Buying Decisions in Virtual Retail Spaces

article en

Abstract

This study investigates the determinants of spontaneous purchase patterns in e-commerce, focusing on the psychological, emotional, social, technological, and visual factors that influence instant buying decisions. As online shopping environments evolve, understanding what drives unplanned purchases has become crucial for digital marketers and platform developers. The research adopts a quantitative approach using a structured questionnaire administered to 150 respondents, with data analyzed through SPSS employing reliability analysis, correlation, ANOVA, and multiple regression techniques. The findings reveal that emotional engagement, social influences such as peer reviews and influencer endorsements, personalized technological features, and visually appealing product presentations significantly contribute to impulse buying behaviour. The study demonstrates high internal reliability (Cronbach’s Alpha = 0.949) and strong statistical relationships (R² > 0.86) across key variables. The results support established behavioral theories, including the Theory of Planned Behaviour and Social Proof Theory. Practical implications emphasize the importance of strategic visual content, emotional branding, and urgency cues. This research provides actionable insights for optimizing marketing strategies and enhancing consumer engagement in digital retail platforms.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 47%
Consumer Retail Behavior Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.