dc.contributor.author |
Sharma, Satyendra Kumar |
|
dc.date.accessioned |
2023-05-09T05:41:25Z |
|
dc.date.available |
2023-05-09T05:41:25Z |
|
dc.date.issued |
2022-05 |
|
dc.identifier.uri |
https://www.tandfonline.com/doi/full/10.1080/0965254X.2022.2067072 |
|
dc.identifier.uri |
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/10707 |
|
dc.description.abstract |
Global retail industry players have witnessed a grave scenario due to the impact of the COVID-19 pandemic. The pandemic has changed the way shoppers think, manifested in the decelerating footfall and increasing threat for traditional brick and mortar stores. The strategy of switching over to omnichannel seemed to have provided the needed relief to traditional retailers and manufacturers in the consumer goods industry. However, a robust omnichannel product assortment model requires integrating channels and remodeling managers’ roles to provide consumer experience and satisfaction and maximize profitability across all touchpoints with minor disruptions. The paper formulates and simulates an omnichannel data-driven fulfillment analytical model to analyze customers’ product mix and manage assortment accordingly. Further, an optimization model that maximizes revenue and profitability is formulated as a suggestive framework with strategies for the current scenario. The paper is helpful for marketing researchers and retail planners for omnichannel assortment management |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Taylor & Francis |
en_US |
dc.subject |
Management |
en_US |
dc.subject |
Omnichannel |
en_US |
dc.subject |
Retail |
en_US |
dc.subject |
COVID-19 |
en_US |
dc.subject |
E-Commerce |
en_US |
dc.subject |
m- commerce |
en_US |
dc.subject |
Optimization |
en_US |
dc.title |
An Intelligent omnichannel assortment model to manage webrooming: an optimization approach |
en_US |
dc.type |
Article |
en_US |