Open Access
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
  • 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. [CrossRef] [MathSciNet] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • S.R. Baker, R.A. Farrokhnia, S. Meyer, M. Pagel, 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. [CrossRef] [Google Scholar]
  • 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. [Google Scholar]
  • R. Batarfi, M.Y. Jaber and S. Zanoni, Dual-channel supply chain: a strategy to maximize profit. Appl. Math. Modell. 40 (2016) 9454–9473. [CrossRef] [Google Scholar]
  • A. Baveja, A. Kapoor and B. Melamed, Stopping COVID-19: a pandemic-management service value chain approach. Ann. Oper. Res. 289 (2020) 173–184. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  • U.K. Bhattacharya, A chance constraints goal programming model for the advertising planning problem. Eur. J. Oper. Res. 192 (2009) 382–395. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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). [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • L. Chenarides, C. Grebitus, J.L. Lusk and I. Printezis, Food consumption behavior during the COVID-19 Pandemic. Agribusiness 37 (2021) 44–81. [CrossRef] [PubMed] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • H. Chesbrough and To recover faster from COVID-19, open up: managerial implications from an open innovation perspective. Ind. Marketing Manage. 88 (2020) 410–413. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [PubMed] [Google Scholar]
  • 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. [Google Scholar]
  • S.K. Goyal and A. Gunasekaran, An integrated production-inventory-marketing model for deteriorating items. Comput. Ind. Eng. 28 (1995) 755–762. [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • P.H. Hsu, H.M. Wee and H.M. Teng, Preservation technology investment for deteriorating inventory. Int. J. Prod. Econ. 124 (2010) 388–394. [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • V. Kämäräinen and M. Punakivi, Developing cost-effective operations for the e-grocery supply chain. Int. J. Logistics 5 (2002) 285–298. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [PubMed] [Google Scholar]
  • 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. [Google Scholar]
  • S. Meyer, Understanding the COVID-19 effect on online shopping behavior. The BigCommerce Blog (2020). [Google Scholar]
  • 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. [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [PubMed] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • Priyamvada, A. Kumar, Modelling retail inventory pricing policies under service level and promotional efforts during COVID-19. J. Cleaner Prod. 381 (2022) 134784. [CrossRef] [Google Scholar]
  • S. Priyamvada, A.Khanna Yadav and C.K. Jaggi, Sustainable preservation strategies with deterioration management and environment sensitive demand. Int. J. Math. Eng. Manage. Sci. 6 (2021) 1089. [Google Scholar]
  • M. Punakivi and J. Saranen, Identifying the success factors in e-grocery home delivery. Int. J. Retail Distrib. Manage. 29 (2001) 156–163. [CrossRef] [Google Scholar]
  • A.L. Roggeveen and R. Sethuraman, How the COVID pandemic may change the world of retailing. J. Retail. 96 (2020) 169. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [Google Scholar]
  • 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. [Google Scholar]
  • 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. [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • 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. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.