Please use this identifier to cite or link to this item:
https://repository.iimb.ac.in/handle/2074/18182
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Prabhu, Ganesh N | - |
dc.contributor.author | Singh, Ashutosh Kumar | |
dc.contributor.author | Vidhya, D | |
dc.date.accessioned | 2021-04-21T12:32:57Z | - |
dc.date.available | 2021-04-21T12:32:57Z | - |
dc.date.issued | 2011 | |
dc.identifier.uri | https://repository.iimb.ac.in/handle/2074/18182 | - |
dc.description.abstract | The retail industry in India can be classified into two: organized and unorganized sectors. Organized retail comprises of large-scale chain stores backed by corporate, governed by modern technology with ample space and ambience and mostly self-serviced in nature. It accounts small percent of the trade and employs approximately 0.5 million persons. Whereas the unorganized retail is characterized by traditional formats of low-cost retailing such as kirana shops, family-owned general stores, convenience shops, paan/beedi shops etc are small in size (less than 500 sq ft), owned by individuals and stocks only limited quantities and is in neighborhood to the residential area which make up for 90 to 95 percent of the sales. This study aimed to find out strategies for small Kirana stores to survive against the threat from organized retail. We begin our research with focus group discussions and depth interviews to identify key attributes that affect the buying behavior of Indian consumers. Then the detailed survey was conducted to find out the relative importance of these attributes with respect to each other and to classify these attributes into factors which will represent a class of key attributes. Customer segmentation and profiling was also part of the exercise in order to identify customers using their demographics. Focus group discussions and depth interviews with customers and shopkeepers helped in identifying 27 key attributes that affect buying behavior of customers. Factor analysis segregated these 27 attributes into 5 prime factors or buying behavior types and Cluster analysis resulted in 3 clusters. Customer profiling helped in associating customer‘s demographics to their buying behavior. As the part of our research, we also came up with recommendations for Kirana Stores to combat against the large retailers and we discussed about the limitations and scope for further study. | |
dc.publisher | Indian Institute of Management Bangalore | |
dc.relation.ispartofseries | PGP_CCS_P11_050 | |
dc.subject | Retail industry | |
dc.title | Combating large retailers: What should small retailers do? | |
dc.type | CCS Project Report-PGP | |
dc.pages | 26p. | |
dc.identifier.accession | E36500 | |
Appears in Collections: | 2011 |
Files in This Item:
File | Size | Format | |
---|---|---|---|
PGP_CCS_P11_050_E36500_CSP.pdf | 1.38 MB | Adobe PDF | View/Open Request a copy |
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.