×

Strategic investment modelling for retail sector post COVID-19. (English) Zbl 1531.90083

Summary: 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.

MSC:

90B50 Management decision making, including multiple objectives
90B60 Marketing, advertising
90B05 Inventory, storage, reservoirs
90B30 Production models

References:

[1] H.M. Al Hamadi, N. Sangeetha and B. Sivakumar, Optimal control of service parameter for a perishable inventory system maintained at service facility with impatient customers. Ann. Oper. Res. 233 (2015) 3-23. · Zbl 1325.90024
[2] L.S. Alaimo, M. Fiore and A. Galati, How the COVID-19 pandemic is changing online food shopping human behaviour in Italy. Sustainability 12 (2020) 9594.
[3] S.R. Baker, R.A. Farrokhnia, S. Meyer, M. Pagel and C. Yannelis, How does household spending respond to an epidemic? Consumption during the 2020 COVID-19 pandemic. Rev. Asset Pricing Stud. 10 (2020) 834-862.
[4] S. Bardhan, H. Pal and B.C. Giri, Optimal replenishment policy and preservation technology investment for a non-instantaneous deteriorating item with stock-dependent demand. Oper. Res. 19 (2019) 347-368.
[5] R. Batarfi, M.Y. Jaber and S. Zanoni, Dual-channel supply chain: a strategy to maximize profit. Appl. Math. Modell. 40 (2016) 9454-9473. · Zbl 1480.90152
[6] A. Baveja, A. Kapoor and B. Melamed, Stopping COVID-19: a pandemic-management service value chain approach. Ann. Oper. Res. 289 (2020) 173-184. · Zbl 1493.90020
[7] U.K. Bhattacharya, A chance constraints goal programming model for the advertising planning problem. Eur. J. Oper. Res. 192 (2009) 382-395. · Zbl 1157.90490
[8] A.K. Bhunia and M. Maiti, A two warehouse inventory model for deteriorating items with a linear trend in demand and shortages. J. Oper. Res. Soc. 49 (1998) 287-292. · Zbl 1111.90308
[9] S. Borocci, F. Brunet, S. Cisnal De Ugarte, M. L. Yuen and M. Tagara, The EU commission publishes a temporary framework to provide guidance to companies that are cooperating to ensure the supply and distribution of grocery products during the COVID-19 outbreak. e-Competitions Bulletin (2020) (Preview).
[10] D. Burgos and D. Ivanov, Food retail supply chain resilience and the COVID-19 pandemic: a digital twin-based impact analysis and improvement directions. Transp. Res. Part E: Logistics Transp. Rev. 152 (2021) 102412.
[11] L. Chenarides, C. Grebitus, J.L. Lusk and I. Printezis, Food consumption behavior during the COVID-19 Pandemic. Agribusi-ness 37 (2021) 44-81.
[12] T. Chernonog and T. Avinadav, Pricing and advertising in a supply chain of perishable products under asymmetric information. Int. J. Prod. Econ. 209 (2019) 249-264.
[13] H. Chesbrough, To recover faster from COVID-19, open up: managerial implications from an open innovation perspective. Ind. Marketing Manage. 88 (2020) 410-413.
[14] M.R.Ćirić, D.S. Ilić, S.D. Ignjatijević and S.D. Brkanlić, Consumer behaviour in online shopping organic food during the COVID-19 pandemic in Serbia. Food Feed Res. 47 (2020) 149-158.
[15] D.E. Dumitras, R. Harun, F.H. Arion, D.I. Chiciudean, E. Kovacs, C.F. Oroian, A. Porutiu and I.C. Muresan, Food consumption patterns in Romania during the COVID-19 pandemic. Foods 10 (2021) 2712.
[16] C.Y. Dye and T.P. Hsieh, An optimal replenishment policy for deteriorating items with effective investment in preservation technology. Eur. J. Oper. Res. 218 (2012) 106-112. · Zbl 1244.90016
[17] S.K. Goyal and A. Gunasekaran, An integrated production-inventory-marketing model for deteriorating items. Comput. Ind. Eng. 28 (1995) 755-762.
[18] M.C. Hall, G. Prayag, P. Fieger and D. Dyason, Beyond panic buying: consumption displacement and COVID-19. J. Serv. Manage. 32 (2020) 113-128.
[19] N. Hao, H.H. Wang and Q. Zhou, The impact of online grocery shopping on stockpile behavior in COVID-19. China Agric. Econ. Rev. 12 (2020) 459-470.
[20] P.H. Hsu, H.M. Wee and H.M. Teng, Preservation technology investment for deteriorating inventory. Int. J. Prod. Econ. 124 (2010) 388-394.
[21] D. Ivanov and A. Dolgui, Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. Int. J. Prod. Res. 58 (2020) 2904-2915.
[22] V. Kämäräinen and M. Punakivi, Developing cost-effective operations for the e-grocery supply chain. Int. J. Logistics 5 (2002) 285-298.
[23] M.A.A. Khan, A.A. Shaikh, I. Konstantaras, A.K. Bhunia and L.E. Cárdenas-Barrón, Inventory models for perishable items with advanced payment, linearly time-dependent holding cost and demand dependent on advertisement and selling price. Int. J. Prod. Econ. 230 (2020) 107804.
[24] S. Laato, A.N. Islam, A. Farooq and A. Dhir, Unusual purchasing behavior during the early stages of the COVID-19 pandemic: the stimulus-organism-response approach. J. Retail. Consum. Serv. 57 (2020) 102224.
[25] K. Mahajan and S. Tomar, COVID-19 and supply chain disruption: evidence from food markets in India. Am. J. Agric. Econ. 103 (2021) 35-52.
[26] A.H.M. Mashud, M.R. Hasan, H.M. Wee and Y. Daryanto, Non-instantaneous deteriorating inventory model under the joined effect of trade-credit, preservation technology and advertisement policy. Kybernetes 49 (2020) 1645-1674.
[27] S. Meyer, Understanding the COVID-19 effect on online shopping behavior. The BigCommerce Blog (2020).
[28] U. Mishra, L.E. Cárdenas-Barrón, S. Tiwari, A.A. Shaikh and G. Treviño-Garza, An inventory model under price and stock dependent demand for controllable deterioration rate with shortages and preservation technology investment. Ann. Oper. Res. 254 (2017) 165-190. · Zbl 1369.90007
[29] U. Mishra, J.Z. Wu, Y.C. Tsao and M.L. Tseng, Sustainable inventory system with controllable non-instantaneous deterioration and environmental emission rates. J. Cleaner Prod. 244 (2020) 118807.
[30] N.A. Omar, M.A. Nazri, M.H. Ali and S.S. Alam, The panic buying behavior of consumers during the COVID-19 pandemic: examining the influences of uncertainty, perceptions of severity, perceptions of scarcity, and anxiety. J. Retail. Consum. Serv. 62 (2021) 102600.
[31] T. Perdana, D. Chaerani, A.L.H. Achmad and F.R. Hermiatin, Scenarios for handling the impact of COVID-19 based on food supply network through regional food hubs under uncertainty. Heliyon 6 (2020) e05128.
[32] I.G. Pérez Vergara, M.C. López Gómez, I. Lopes Martínez and J. Vargas Hernández, Strategies for the preservation of service levels in the inventory management during COVID-19: a case study in a company of biosafety products. Global J. Flexible Syst. Manage. 22 (2021) 65-80.
[33] Priyamvada and A. Kumar, Modelling retail inventory pricing policies under service level and promotional efforts during COVID-19. J. Cleaner Prod. 381 (2022) 134784.
[34] Priyamvada, S. Yadav, A. Khanna and C.K. Jaggi, Sustainable preservation strategies with deterioration management and environment sensitive demand. Int. J. Math. Eng. Manage. Sci. 6 (2021) 1089.
[35] M. Punakivi and J. Saranen, Identifying the success factors in e-grocery home delivery. Int. J. Retail Distrib. Manage. 29 (2001) 156-163.
[36] A.L. Roggeveen and R. Sethuraman, How the COVID pandemic may change the world of retailing. J. Retail. 96 (2020) 169.
[37] S. Saha, D. Chatterjee and D. Sarkar, The ramification of dynamic investment on the promotion and preservation technology for inventory management through a modified flower pollination algorithm. J. Retail. Consum. Serv. 58 (2021) 102326.
[38] J. Sarkis, M.J. Cohen, P. Dewick and P. Schröder, A brave new world: lessons from the COVID-19 pandemic for transitioning to sustainable supply and production. Res. Conserv. Recycl. 159 (2020) 104894.
[39] V.G.H. Schmitt, M.M. Cequea, J.M.V. Neyra and M. Ferasso, Consumption behavior and residential food waste during the COVID-19 pandemic outbreak in Brazil. Sustainability 13 (2021) 3702.
[40] M. Sharma, S. Joshi, S. Luthra and A. Kumar, Managing disruptions and risks amidst COVID-19 outbreaks: role of blockchain technology in developing resilient food supply chains. Oper. Manage. Res. 15 (2021) 268-281.
[41] C.K. Singh and P. Rakshit, A critical analysis to comprehend panic buying behaviour of Mumbaikar’s in COVID-19 era. Stud. Indian Place Names 40 (2020) 44-51.
[42] S. Tiwari, C.K. Jaggi, M. Gupta and L.E. Cárdenas-Barrón, Optimal pricing and lot-sizing policy for supply chain system with deteriorating items under limited storage capacity. Int. J. Prod. Econ. 200 (2018) 278-290.
[43] S. Yadav, F. Siddiqui and A. Khanna, Sustainable inventory model with carbon emission dependent demand under different carbon emission policies, in Soft Computing in Inventory Management. Springer Singapore, Singapore (2021) 163-175.
[44] S. Yadav, P. Priyamvada and A. Khanna, COVID-19 impact on a sustainable production model with volume agility and advertisement dependent demand. Int. J. Supply Oper. Manage. 10 (2023) 136-150.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.