Researchers in e-commerce impulse buying studies are increasingly utilizing technology-assisted data collection methods, such as mobile app analytics, machine learning user behavior classification, and AI-generated recommendation response tracking, to move beyond static metrics toward dynamic modeling of impulse buying paths.
Survey-based quantitative studies on impulse buying frequently utilize established scales such as the Impulse Buying Tendency Scale (IBTS), the Consumer Decision-Making Styles Inventory (CDMSI), and extensions of the Technology Acceptance Model (TAM).
As social media becomes more integrated into e-commerce, impulse buying is evolving from isolated acts into socially constructed behaviors co-constructed through digital interactions and emotional cues, as described in the study referenced as [92].
Emotional arousal, product novelty, and social comparison exert a stronger influence on consumers than rational evaluation, creating opportunities for impulse purchases.
Cakanlar A and Nguyen T published 'The influence of culture on impulse buying' in the Journal of Consumer Marketing in 2019, which examines how cultural factors impact impulse purchasing behavior.
The final review of studies on impulse buying in e-commerce included 70 peer-reviewed studies after applying exclusion criteria that removed conceptual papers, literature reviews, meta-analyses, and studies unrelated to consumer purchasing behavior.
E-commerce platforms utilize social proof, personalized content, and targeted marketing to appeal to consumer psychological needs, thereby encouraging impulse purchases.
Impulse buying has evolved from a spontaneous in-store occurrence into a purposefully designed result of algorithm-driven, emotionally charged virtual experiences as digital platforms increasingly define consumer interactions.
Juan X. (2025) proposed a multiple mediation model linking mental simulation and compulsive buying through the mechanisms of impulse buying and self-control.
Many behavioral experiments on impulse buying utilize eye-tracking or clickstream data to analyze patterns of consumer attention and digital navigation behavior.
The convergence of customized user experience design, AI-powered recommendation systems, and social media integration has increased the speed and frequency of impulse purchases by bypassing consumers' sensible filters and promoting habitual consumption patterns.
To be included in the literature review, studies on impulse buying were required to be published in peer-reviewed journals, involve empirical research, focus on online or e-commerce environments, and utilize behavioral, psychological, or marketing-related frameworks.
Survey-based quantitative studies on impulse buying typically assess variables including impulsivity, hedonic drive, perceived pleasure, website happiness, and emotional triggers such as anxiety, thrill, or social comparison.
Meryl P. Gardner and Dennis W. Rook authored 'Effects of impulse purchases on consumers’ affective states,' published in Advances in Consumer Research in 1988, volume 15, issue 1, pages 127–30.
Gardner and Rook (1988) examined the effects of impulse purchases on the affective states of consumers in the journal Advances in Consumer Research.
Impulse buying is predominantly governed by System 1 thinking, which responds quickly to sensory stimuli such as visually appealing product displays, flash sales, and persuasive call-to-action buttons.
Consumers often make unplanned purchases to satisfy unconscious emotional or psychological needs, with Maslow's Hierarchy of Needs serving as a behavioral model for this phenomenon.
Qualitative research accounted for approximately 15% of the studies examined in the review, utilizing methods such as in-depth interviews, focus groups, and thematic content analysis to explore personal experiences and subjective meanings behind impulse buying.
Silvera DH, Lavack AM, and Kropp F published 'Impulse buying: the role of affect, social influence, and subjective wellbeing' in the Journal of Consumer Marketing in 2008, which examines the impact of affect, social influence, and subjective wellbeing on impulse buying.
Stern H published 'The Significance of Impulse Buying Today' in the Journal of Marketing in April 1962.
As social media becomes more integrated into e-commerce, impulse buying is evolving from isolated acts into socially constructed behaviors co-constructed through digital interactions and emotional cues.
Xie et al. (2025) found that personality traits, specifically conscientiousness and agreeableness, have significant negative correlations with impulse buying (IB) among Chinese college students, while neuroticism and extroversion have positive correlations.
Positively emotional attitudes, such as joy and satisfaction derived from online shopping, play a significant role in predicting impulse purchases.
Survey-based quantitative studies on impulse buying typically utilize sample sizes ranging from 200 to 700 participants, often recruited via convenience or snowball sampling on platforms like Amazon, Alibaba, or general digital retail interfaces.
Sharma P, Sivakumaran B, and Marshall R published 'Impulse buying and variety seeking: A trait-correlates perspective' in the Journal of Business Research in 2010, which investigates the relationship between impulse buying and variety-seeking traits.
Survey-based quantitative research accounted for approximately 55% of the research examined in the review of impulse buying in e-commerce.
Behavioral experiments accounted for approximately 30% of the research examined in the review of impulse buying in e-commerce.
Many recent studies on impulse buying employ hybrid or mixed-method techniques, such as combining survey data with purchase records, browser history, or real-time tracking plugins to validate self-reported impulsivity against observed digital behavior.
The Stimulus-Organism-Response (S-O-R) framework, Dual-Process Theory, and the Theory of Planned Behavior are theoretical models that explain the interaction between environmental stimuli and internal psychological processes in the context of impulse buying.
Survey-based quantitative studies on impulse buying typically assessed variables including impulsivity, hedonic drive, perceived pleasure, website happiness, and emotional triggers such as anxiety, thrill, or social comparison.
Future research into impulse buying should incorporate dynamic real-time data gathering techniques, such as biometric and sentiment analysis, to better capture the visceral and situational nature of the behavior.
Qualitative research on impulse buying often focuses on young adults and digital natives, aiming to reveal emotional narratives, identity-related purchasing drives, and the influence of cultural or financial elements on consumer spontaneity in online environments.
Qualitative research accounted for approximately 15% of the research examined in the review of impulse buying in e-commerce.
Behavioral experiments on impulse buying often manipulate independent variables such as website design components, product images, urgency indicators, and advertising stimuli, while measuring dependent variables like emotional excitement, decision speed, and unexpected purchasing behavior.
AL Coley authored a work titled 'Affective and cognitive processes involved in impulse buying' published by the University of Georgia in 2025.
E-commerce platforms utilize social proof, personalized content, and targeted marketing to directly appeal to consumers' psychological needs for belonging and esteem, thereby encouraging impulse purchases.
Synchronous shopping, where multiple people shop together, is more potent in driving impulse purchases than solo shopping because the act of purchasing and sharing items can multiply the perceived happiness of the experience.
Behavioral experiments on impulse buying typically utilized independent variables such as website design components, product images, urgency indicators, and advertising stimuli, while measuring dependent variables like emotional excitement, decision speed, and unexpected purchasing behavior.
The review of impulse buying in e-commerce included 70 peer-reviewed studies after excluding conceptual or theoretical papers, literature reviews, meta-analyses, and studies unrelated to consumer purchasing behavior.
The convergence of customized UX design, AI-powered recommendation systems, and social media integration has increased the speed and frequency of impulse purchases by bypassing consumer sensible filters and promoting habitual consumption patterns.
Emotion-aware, socially intelligent systems will influence the future of impulse buying in e-commerce by allowing marketers to access subconscious triggers and provide individualized, immersive, and responsive experiences.
Impulse buying in e-commerce has evolved from a spontaneous in-store occurrence to a purposefully designed result of algorithm-driven, emotionally charged virtual experiences.
Amos et al. (2019) conducted a meta-analytic review finding that mood, boredom, stress, and emotional regulation significantly predict impulse buying.
Interface design, marketing cues, and social validation mechanisms serve as external stimuli for impulse buying, while mood states, personality characteristics, emotional regulation, and cognitive biases serve as internal influences.
Verplanken and Herabadi (2001) identified that individual differences in impulse buying tendency are characterized by a distinction between 'feeling' and 'no thinking'.
While interface design, marketing cues, and social validation mechanisms serve as external stimuli for impulse buying, internal influences include mood states, personality characteristics, emotional regulation, and cognitive biases.
Impulse buying is predominantly governed by System 1 thinking, which responds quickly to sensory stimuli such as visually appealing product displays, flash sales, and persuasive call-to-action buttons.
Beatty SE and Ferrell ME published 'Impulse buying: Modeling Its Precursors' in the Journal of Retailing in June 1998.
The Theory of Planned Behavior has been extended to e-commerce by analyzing how positive attitudes toward online shopping, social pressure from peers, and a consumer's perception of their own control over purchasing behavior predict impulse purchases.
Many recent studies on impulse buying validated self-reported impulsivity with observed digital behavior by combining survey data with purchase records, browser history, or real-time tracking plugins.
MA Jones, KE Reynolds, S Weun, and SE Beatty published 'The product-specific nature of impulse buying tendency' in the Journal of Business Research in 2003.
Verplanken and Herabadi (2001) identified individual differences in impulse buying tendency, characterizing the behavior as involving feeling rather than thinking.
Mandolfo and Lamberti (2021) conducted a systematic literature review of past, present, and future research methods regarding impulse buying.
Marco Mandolfo and Lucio Lamberti conducted a systematic literature review in 2021 regarding the past, present, and future of research methods used to study impulse buying.
Future research on impulse buying should incorporate dynamic real-time data gathering techniques, such as biometric and sentiment analysis, to better capture the visceral and situational nature of the behavior.
The psychological and behavioral aspects of impulse buying are expected to be redefined as e-commerce evolves and integrates social media analysis into retail tactics.
Maslow's Hierarchy of Needs provides a perspective for understanding impulse buying, particularly regarding emotional spending in online shopping.
Jones MA, Reynolds KE, Weun S, and Beatty SE established that impulse buying tendency is product-specific.
M.A. Jones, K.E. Reynolds, S. Weun, and S.E. Beatty authored the article 'The product-specific nature of impulse buying tendency,' published in the Journal of Business Research in July 2003.