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DC Field | Value | Language |
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dc.contributor.author | Shuvam Chatterjee | - |
dc.contributor.author | Aritra Kundu | - |
dc.date.accessioned | 2023-10-13T09:55:16Z | - |
dc.date.available | 2023-10-13T09:55:16Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/1792 | - |
dc.description.abstract | Today's world of marketing is a highly dynamic and volatile place due to high competitive clutter, and hence, every industry needs to accept the understanding of impulsive change as a new standard. This article focused on understanding brand awareness of consumers from an embedded cognitive state. Consumer's decision making for a brand mainly results from both conscious and non-conscious experiences that a consumer has been exposed to. Consumers preserve this brand knowledge in a non-conscious level of their mind. Marketers depend upon the use of multi-sensory metaphors to bring out that digged-in knowledge. This paper introduced ZMET as a method to elicitate hidden understanding about a consumer’s decision making process by stimulating human senses and understanding about the attributes that ultimately contribute in consumer decision making. The research threw light on a qualitative example considering the wellness industry by identifying the hidden metaphors that contributed in understanding the consumer's satisfaction. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Indian Journal of Marketing | en_US |
dc.subject | Consumer loyalty | en_US |
dc.subject | Relationship patterns | en_US |
dc.subject | Wellness industry | en_US |
dc.subject | ZMET | en_US |
dc.subject | Attribute mapping | en_US |
dc.title | Sub-Conscious Decision Mapping and Network Framework for Retail Market Consumption | en_US |
dc.type | Article | en_US |
Appears in Collections: | Article Archives |
Files in This Item:
File | Description | Size | Format | |
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Sub-Conscious Decision Mapping and Network Framework.pdf Restricted Access | Sub-Conscious Decision Mapping and Network Framework | 3.2 MB | Adobe PDF | View/Open Request a copy |
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