认知失调
独创性
认知
心理学
价(化学)
脉冲(物理)
社会心理学
价值(数学)
认知需要
营销
业务
创造力
计算机科学
物理
神经科学
机器学习
量子力学
作者
Cherouk Amr Yassin,Ana Maria Soares
出处
期刊:Journal of Consumer Marketing
[Emerald (MCB UP)]
日期:2023-08-25
卷期号:40 (7): 884-896
被引量:2
标识
DOI:10.1108/jcm-09-2020-4116
摘要
Purpose Drawing upon the elaboration likelihood model, this study aims to illuminate contradictory findings from previous research regarding the impact of positive and negative emotions, as well as promotions, on impulse buying (IB). Specifically, this study takes a two-faceted approach to IB, considering both affective IB and cognitive IB. Design/methodology/approach A proposed model of IB is tested using a mall intercept survey. Findings The findings provide evidence for the two-dimensional nature of IB. Cognitive and affective IB are affected differently by promotions and emotions, and in turn, have different impacts on cognitive dissonance (CD). Specifically, promotions have a positive effect only on cognitive IB, while positive emotions have a positive effect only on affective IB. Additionally, cognitive IB positively affects CD, while affective IB does not. Research limitations/implications Future research could explore different types of IB and unplanned purchases, consider the valence and arousal dimensions of emotions and examine how technological changes impact IB. Additionally, studying satisfaction as a mediator between IB and cognitive dissonance can contribute to the understanding of IB post-purchase outcomes. Practical implications By tailoring promotional techniques to cognitive IB and using positive emotions to stimulate affective IB, retailers can enhance the effectiveness of strategies. Furthermore, post-purchase strategies can be developed to reduce the negative effects of CD. Originality/value By exploring the different dimensions of IB and their relationships with CD, this study enhances our understanding of the underlying processes and mechanisms that drive consumer IB behavior during and after shopping trips.
科研通智能强力驱动
Strongly Powered by AbleSci AI