The Role of Algorithmic Ad Personalization in Driving Impulse Buying Behavior: Mediating Effects of Perceived Value and Moderating Personality Traits
Author: Muhammad Shafqat Rasool, Ali Sajjad, Syeda Aneeqa Touseef
Abstract
This research investigates how personalized advertisements in algorithms can cause people to shop on impulse, and it reveals that this effect is influenced by perceptions of value (emotion, social & price) and influenced by trait personality (extraversion and agreeableness). A sample of 106 responses were collected using Likert scales that had been changed to fit the purpose of the study. The collected data were analyzed using PLS-SEM, and the results showed that customized ads can lead people to make impulsive purchases. It was found that the value individuals anticipate before making a purchase, along with its social, emotional, and price elements, affects the link between algorithmic ad personalization and impulsive buying. In addition, having an extroverted and agreeable personality helps make this type of mediation stronger. The research integrates the S-O-R framework and considers the impact of different factors to explain how someone’s traits influence their buying decisions when seeing personalized ads on the internet. As a result, marketers are able to target ads and campaigns toward specific traits to boost the effectiveness of what they do online. For greater generalizability, researchers need to consider traits like neuroticism or conscientiousness in their future studies, use designs that last a long time, and test specific hypotheses.
Keywords
Algorithmic Ad Personalization, Impulsive Buying Behavior, Perceived Value, Personality Traits, Extraversion, Agreeableness, Emotional and Social Value, Consumer Behavior, Digital Marketing
References
Ali, F., Tauni, M. Z., Ali, A., & Ahsan, T. (2021). Do buyer–seller personality similarities impact
compulsive buying behaviour?. Journal of Consumer Behaviour, 20(4), 996-1011.
Ampadu, S., Jiang, Y., Debrah, E., Antwi, C. O., Amankwa, E., Gyamfi, S. A., & Amoako, R. (2022).
Online personalized recommended product quality and e-impulse buying: A conditional
mediation analysis. Journal of Retailing and Consumer Services, 64, 102789.
Bell, E., Harley, B., & Bryman, A. (2022). Business research methods. Oxford university press.
Chap, C. (2022). How Machine Learning Artificial Intelligence Improves Users’ Perceptions of
Facebook Ads: A Model of Personalization, Advertising Value and Purchase Intention. Ohio
University.
Chen, S., Zhi, K., & Chen, Y. (2022). How active and passive social media use affects impulse buying
in Chinese college students? The roles of emotional responses, gender, materialism and selfcontrol. Frontiers in Psychology, 13, 1011337.
Chu, J. (2023). The Effects of Personalized Advertisements on Consumer Decision-Making
Behavior. International Journal of High School Research, 5(3).
Kerley, T. (2024). Digital Influencers’ Visual Narratives and Algorithmic Power: Identity
Construction and Impulsive Consumption on Social Networks. International Journal of
Scientific Management and Tourism, 10(6), e1196-e1196.
Nablsi, R. (2024). “Buy Now, Think Later?”: The AI Product Recommendations Effect: From
Impulse Buying to Post-Purchase Emotions.
Nazir, S., Khadim, S., Asadullah, M. A., & Syed, N. (2023). Exploring the influence of artificial
intelligence technology on consumer repurchase intention: The mediation and moderation
approach. Technology in Society, 72, 102190.
Ngo, T. T. A., Nguyen, H. L. T., Nguyen, H. P., Mai, H. T. A., Mai, T. H. T., & Hoang, P. L. (2024).
A comprehensive study on factors influencing online impulse buying behavior: Evidence
from Shopee video platform. Heliyon, 10(15).
Ram, M., Maryam, P., & Bernard, A. T. (2024). Beyond the Click: Unveiling the Influence of AI
Personalization on E-commerce Impulse Buys.
Tania, J., & Oktavia, T. (2024). A Bibliometric Analysis of Key Drivers of Online Impulse Buying
Behavior. Journal of System and Management Sciences, 14(5), 489-508.
Walsh, G., Shiu, E., & Hassan, L. M. (2014). Replicating, validating, and reducing the length of the
consumer perceived value scale. Journal of Business Research, 67(3), 260-267.
Wu, L., Chiu, M. L., & Chen, K. W. (2020). Defining the determinants of online impulse buying
through a shopping process of integrating perceived risk, expectation-confirmation model,
and flow theory issues. International Journal of Information Management, 52, 102099.
Xiong, Y., & Tseng, C. J. (2024). The Impact of Social Media Influencer Characteristics on Purchase
Intentions: A Moderated Mediation Effect of Regulatory Focus to Perceived Uniqueness.
Journal of System and Management Sciences, 14(1), 527-546.
Xue, Y., Feng, T., & Wu, C. (2024). How technical and situational cues affect impulse buying
behavior in social commerce? Evidence from bored consumers. Frontiers in Psychology, 15,
1405189.
Zarouali, B., Boerman, S. C., & de Vreese, C. H. (2021). Is this recommended by an algorithm? The
development and validation of the algorithmic media content awareness scale (AMCA-scale).
Telematics and Informatics, 62, 101607.
DOI: 10.52279/jlss.07.02.8598 | 85-98 | PDF