Issue |
RAIRO-Oper. Res.
Volume 57, Number 5, September-October 2023
|
|
---|---|---|
Page(s) | 2735 - 2751 | |
DOI | https://doi.org/10.1051/ro/2023130 | |
Published online | 24 October 2023 |
Strategic investment modelling for retail sector post COVID-19
Department of Operational Research, Faculty of Mathematical Sciences, New Academic Block, University of Delhi, Delhi 110007, India
* Corresponding author: ckjaggi@yahoo.com
Received:
31
January
2023
Accepted:
23
August
2023
Amidst the unprecedented COVID-19 pandemic, the online grocery retail industry has faced significant obstacles. To overcome these challenges and adapt to shifting customer attitudes, retailers must embrace innovative strategies. These include implementing a home delivery service with rigorous sanitization measures, leveraging social media advertising to enhance consumer awareness, and utilizing preservation technology to uphold grocery items’ quality and freshness. In such a dynamic setting, it is only rational to acknowledge that the demand for products relies heavily upon the delivery firm’s service performance and the awareness it generates. The present study explores these vital investments within the online grocery retail store, comparing them with models lacking such investments. By optimizing investments in preservation technology, service, and advertisement, the model seeks to maximize the retailer’s overall profit. The findings unequivocally demonstrate that despite incurring additional costs, these investments wield financial dominance, boosting the total profit by an impressive 32%. The study concludes by presenting valuable insights derived from numerical and sensitivity analysis, offering invaluable guidance for the effective management of grocery items in the current post-pandemic era.
Mathematics Subject Classification: 90B05 / 90B30
Key words: Inventory / retail sector / grocery / preservation technology / service facility / advertisement / COVID-19
© The authors. Published by EDP Sciences, ROADEF, SMAI 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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