Investigating Online and Physical Retailing with the Perspective of Traditional Economic Geography in the COVID-19 Era

Alireza Mosafa; Farhad Folad; Hamid Riazi

doi:10.63053/ijmea.6

Authors

Alireza Mosafa CEO Hyperme Chain Store, Tehran, Iran
Farhad Folad Vice Chairman of the Board & Vice President of Commerce Hyperme Chain Store, Tehran, Iran
Hamid Riazi Ph.D. Candidate, Department of Industrial Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

DOI:

https://doi.org/10.63053/ijmea.6

Keywords:

Retailing, Economic Geography, COVID-19 Crisis, Supply Chain

Abstract

It is crucial to understand the needs of consumers, producers, and intermediaries (retailers) in the context of the rapid growth of companies and organizations. The use of a supply chain management system can greatly enhance the efficiency of order transmission and receipt. However, it is unfortunate that management systems, particularly supply chain management, have not fully capitalized on the opportunities offered by today's technology-driven and intelligent world. This presents an interesting challenge for management systems focusing on sustainable development goals, especially during times of crisis like the COVID-19 pandemic. The outbreak and global spread of the coronavirus has exposed the vulnerability of the global supply chain. From the initial stages of sourcing raw materials to the production and distribution of goods, every step is susceptible to disruption. In light of this, companies must proactively anticipate potential issues and implement measures to restore and improve their supply chains. To raise awareness about this critical issue, it is important to identify the challenges faced by companies and businesses. This will enable us to develop strategies for improvement and recovery, both in online and physical retail, from the perspective of traditional economic geography. Supply chain recovery is of utmost importance and goes beyond crisis management, as it involves overcoming numerous challenges during the recovery phase. The severity and adverse effects of the pandemic may vary, making it crucial for businesses to carefully navigate the long-term and destructive impacts on their supply chains. Subsequently, the recovery of the supply chain in the post-pandemic era requires a comprehensive approach that encompasses both online and physical retail, taking into account traditional economic geography. Therefore, in the midst of an epidemic, identifying potential challenges in the supply chain and understanding their impact on post-disaster recovery strategies play a vital role. This understanding will inform the development of appropriate strategies to address these challenges, both in online and physical retail, from a traditional geographic perspective.

References

Ahmad, B., & Benkherouf, L. (2020). On an optimal replenishment policy for inventory models for non-instantaneous deteriorating items with stock dependent demand and partial backlogging. RAIRO-Operations Research, 54(1), 69-79. DOI: https://doi.org/10.1051/ro/2018092

Balkhi, Z. T. (1999). On the global optimal solution to an integrated inventory system with general time varying demand, production and deterioration rates. European Journal of Operational Research, 114(1), 29-37. DOI: https://doi.org/10.1016/S0377-2217(98)00155-6

Barman, A., Das, R., & De, P. K. (2021). Impact of COVID-19 in food supply chain: Disruptions and recovery strategy. Current Research in Behavioral Sciences, 2, 100017. DOI: https://doi.org/10.1016/j.crbeha.2021.100017

Basu, R. (2020). COVID control in India: A look back. Journal of comprehensive health, 8(2), 129-131. DOI: https://doi.org/10.53553/JCH.v08i02.013

Bishi, B., Behera, J., & Sahu, S. K. (2019). Two-warehouse inventory model for non-instantaneous deteriorating items with exponential demand rate. Int. J. Appl. Eng. Res, 14, 495-515.

Dey, J. K., Mondal, S. K., & Maiti, M. (2008). Two storage inventory problem with dynamic demand and interval valued lead-time over finite time horizon under inflation and time-value of money. European Journal of Operational Research, 185(1), 170-194. DOI: https://doi.org/10.1016/j.ejor.2006.12.037

Garg, G., Singh, S., & Singh, V. (2020). A two warehouse inventory model for perishable items with ramp type demand and partial backlogging. International Journal of Engineering Research & Technology (IJERT), 9(6). DOI: https://doi.org/10.17577/IJERTV9IS060999

Gupta, A. S., Mukherjee, J., & Garg, R. (2023). Retailing during the COVID-19 lifecycle: a bibliometric study. International Journal of Retail & Distribution Management. DOI: https://doi.org/10.1108/IJRDM-09-2022-0363

Hung, K.-C. (2011). An inventory model with generalized type demand, deterioration and backorder rates. European Journal of Operational Research, 208(3), 239-242. DOI: https://doi.org/10.1016/j.ejor.2010.08.026

Jaggi, C. K., Aggarwal, K., & Goel, S. (2006). Optimal order policy for deteriorating items with inflation induced demand. International Journal of Production Economics, 103(2), 707-714. DOI: https://doi.org/10.1016/j.ijpe.2006.01.004

Koul, S., & Jasrotia, S. S. (2019). Product adoption by small retailers in India. International Journal of Retail & Distribution Management, 47(11), 1163-1180. DOI: https://doi.org/10.1108/IJRDM-03-2018-0053

Kumar, N., Dahiya, S., & Kumar, S. (2022). Two warehouse inventory model for deteriorating items with fixed shelf-life stock-dependent demand and partial backlogging. J. Math. Comput. Sci., 12, Article ID 85. DOI: https://doi.org/10.22214/ijraset.2021.39265

Mohanta, K. K., Sharanappa, D. S., & Aggarwal, A. (2021). Efficiency analysis in the management of COVID-19 pandemic in India based on data envelopment analysis. Current Research in Behavioral Sciences, 2, 100063. DOI: https://doi.org/10.1016/j.crbeha.2021.100063

Panda, G. C., Khan, M. A.-A., & Shaikh, A. A. (2019). A credit policy approach in a two-warehouse inventory model for deteriorating items with price-and stock-dependent demand under partial backlogging. Journal of Industrial Engineering International, 15(1), 147-170. DOI: https://doi.org/10.1007/s40092-018-0269-3

Paul, S. K., Chowdhury, P., Moktadir, M. A., & Lau, K. H. (2021). Supply chain recovery challenges in the wake of COVID-19 pandemic. Journal of Business Research, 136, 316-329. DOI: https://doi.org/10.1016/j.jbusres.2021.07.056

Prasad, K., & Mukherjee, B. (2016). Optimal inventory model under stock and time dependent demand for time varying deterioration rate with shortages. Annals of Operations Research, 243, 323-334. DOI: https://doi.org/10.1007/s10479-014-1759-3

Rastogi, M., Singh, S., Kushwah, P., & Tayal, S. (2017). Two warehouse inventory policy with price dependent demand and deterioration under partial backlogging. Decision Science Letters, 6(1), 11-22. DOI: https://doi.org/10.5267/j.dsl.2016.8.004

Riazi, H., Doroodian, M., & Afshar-Nadjafi, B. (2022). Inventory Control of Perishables based on Shelf Space and Effects of Face Changes of Products with Total Minimum Commitment. Industrial Management Journal, 14(1), 168-194.

Rout, C., Chakraborty, D., & Goswami, A. (2021). A production inventory model for deteriorating items with backlog-dependent demand. RAIRO-Operations Research, 55, S549-S570. DOI: https://doi.org/10.1051/ro/2019076

Shaikh, A. A., Cárdenas-Barrón, L. E., & Tiwari, S. (2019). A two-warehouse inventory model for non-instantaneous deteriorating items with interval-valued inventory costs and stock-dependent demand under inflationary conditions. Neural Computing and Applications, 31, 1931-1948. DOI: https://doi.org/10.1007/s00521-017-3168-4

Tiwari, S., Cárdenas-Barrón, L. E., Goh, M., & Shaikh, A. A. (2018). Joint pricing and inventory model for deteriorating items with expiration dates and partial backlogging under two-level partial trade credits in supply chain. International Journal of Production Economics, 200, 16-36. DOI: https://doi.org/10.1016/j.ijpe.2018.03.006

Wee, H.-M. (1993). Economic production lot size model for deteriorating items with partial back-ordering. Computers & Industrial Engineering, 24(3), 449-458. DOI: https://doi.org/10.1016/0360-8352(93)90040-5

Zhang, J., Bai, Z., & Tang, W. (2014). OPTIMAL PRICING POLICY FOR DETERIORATING ITEMS WITH PRESERVATION TECHNOLOGY INVESTMENT. Journal of Industrial & Management Optimization, 10(4). DOI: https://doi.org/10.3934/jimo.2014.10.1261