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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/10707
Title: An Intelligent omnichannel assortment model to manage webrooming: an optimization approach
Authors: Sharma, Satyendra Kumar
Keywords: Management
Omnichannel
Retail
COVID-19
E-Commerce
m- commerce
Optimization
Issue Date: May-2022
Publisher: Taylor & Francis
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
URI: https://www.tandfonline.com/doi/full/10.1080/0965254X.2022.2067072
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/10707
Appears in Collections:Department of Management

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