Antecedents of Offline Impulsive Buying Behaviour
Annie John1, R Rathidevi2, Jain Mathew3
1Annie John*, Research Scholar, Department of Management Studies, Mother Teresa Women’s University, Kodaikanal.
2R. Rathidevi, Assistant Professor, Department of Management Studies, Mother Teresa Women’s University, Kodaikanal.
3Jain Mathew, Professor, Department of Management Studies, Christ University, Bangalore.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1455-1460 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7516118419/2019©BEIESP | DOI: 10.35940/ijrte.D7516.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Paper Impulsive purchases are defined as those purchase decisions that are unplanned. Sellers are constantly attempting to understand the triggers to impulsive purchases as it provides them with a leverage to increase sales. The current study has identified literature in the area of Impulsive Buying Behaviour and consolidated the findings in order to arrive at a list of possible antecedents to Impulsive Buying Behaviour. The studies chosen were based in the offline context and sourced from ProQuest, ensuring reliability of the findings. The findings were consolidated using Meta-Analysis, carried out in the SPSS software package. The analysis revealed that Brand Preferences, Demographics, Buyer Emotions, Promotions, Store Atmospherics and Buyer Traits had statistically significant relations with Offline Impulsive Buying Behaviour. The findings of this study provide insights into the factors that drive impulsive purchases. The study adds value to the literature in the area of Marketing by consolidating research findings across time and geography.
Keywords: Impulsive Buying Behaviour, Offline Buying, Meta Analysis, Antecedents.
Scope of the Article: Predictive Analysis.