COVID -19 Impact on a Sustainable Production Model with Volume Agility and Advertisement Dependent Demand

Document Type : Research Paper

Authors

Department of Operational Research, Faculty Of Mathematical Sciences, University of Delhi, Delhi,India

Abstract

The novel coronavirus has a significant impact on the whole world, especially the manufacturing sector. In this pandemic, the demand of personal protective equipment (PPE) viz., masks, face shields, gloves, hand sanitizer, etc., has increased rapidly, which has put an additional pressure on the manufacturers to increase their production to meet the escalating demand. Thus, the agile nature of demand can be addressed by incorporating volume agility in the production process. Accordingly, there is an urgent need for the manufacturers to promote their products and also to keep the public aware about the importance of various preventive measures. However, as the pandemic continues, the excess production of PPE leads to a considerable amount of carbon emissions and waste in the environment. Motivated by this, the present study develops a sustainable production model with volume agility and advertisement sensitive demand. Sustainability is addressed by incorporating carbon emission costs during the production and inventory holding. The objective is to maximize the total profit by conjointly optimizing the cycle length, advertising cost, and production rate. A numerical example is included to validate the model. Further, the sensitivity analysis unfolds valuable managerial insights for decision-makers to better management in this pandemic.

Keywords


AlDurgam, M., Adegbola, K., and Glock, C. H. (2017). A single-vendor single-manufacturer integrated inventory model with stochastic demand and variable production rate. International Journal of Production Economics, Vol. 191, pp. 335–350.
Alkahtani, M., Omair, M., Khalid, Q. S., Hussain, G., and Sarkar, B. (2020). An Agricultural Products Supply Chain Management to Optimize Resources and Carbon Emission Considering Variable Production Rate: Case of Nonperishable Corps. Processes, Vol. 8(11), 1505.
Belhadia, A., Kamble, S. S., Jabbourc, C. J. C., Ndubisi, N. O., and Venkatesh, M. (2020). Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries. Technological Forecasting and Social Change, 120447.
Belhouideg, S. (2020). Impact of 3D printed medical equipment on the management of the Covid19 pandemic. The International Journal of Health Planning and Management, Vol. 35(5), pp. 1014–1022.
Cárdenas-Barrón, L. E., and Sana, S. S. (2015). Multi-item EOQ inventory model in a two-layer supply chain while demand varies with promotional effort. Applied Mathematical Modelling, Vol. 39(21), pp. 6725–6737.
Chen, X., Benjaafar, S., and Elomri, A. (2013). The carbon-constrained EOQ. Operations Research Letters, Vol. 41(2), pp. 172–179.
Chowdhury, R. R., Ghosh, S. K., and Chaudhuri, K. S. (2014). An inventory model for perishable items with stock and advertisement sensitive demand. International Journal of Management Science and Engineering Management, Vol. 9(3), pp. 169–177.
Čuček, L., Klemeš, J. J., and Kravanja, Z. (2012). A review of footprint analysis tools for monitoring impacts on sustainability. Journal of Cleaner Production, Vol. 34, pp. 9–20.
Goyal, S. K., and Gunasekaran, A. (1995). An integrated production-inventory-marketing model for deteriorating items. Computers & Industrial Engineering, Vol. 28(4), pp. 755–762.
He, P., Zhang, W., Xu, X., and Bian, Y. (2015). Production lot-sizing and carbon emissions under cap-and-trade and carbon tax regulations. Journal of Cleaner Production, Vol. 103, pp. 241–248.
Ivanov, D. (2020). Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case. Transportation Research Part E: Logistics and Transportation Review, Vol. 136, 101922.
Ivanov, D., Dolgui, A., Sokolov, B., and Ivanova, M. (2017). Literature review on disruption recovery in the supply chain. International Journal of Production Research, Vol. 55(20), pp. 6158–6174.
Kamna, K. M., Gautam, P., and Jaggi, C. K. (2020). Sustainable inventory policy for an imperfect production system with energy usage and volume agility. International Journal of System Assurance Engineering and Management, pp. 1–9.
Khanna, A., and Yadav, S. (2020). Effect of Carbon-tax and Cap-and-trade mechanism on an inventory system with price-sensitive demand and preservation technology investment. Yugoslav Journal of Operations Research, Vol. 30(3), pp. 361–380.
Klemeš, J. J., Van Fan, Y., and Jiang, P. (2020a). The energy and environmental footprints of COVID-19 fighting measures–PPE, disinfection, supply chains. Energy, Vol. 211, 118701.
Klemeš, J. J., Van Fan, Y., Tan, R. R., and Jiang, P. (2020b). Minimising the present and future plastic waste, energy and environmental footprints related to COVID-19. Renewable and Sustainable Energy Reviews, Vol. 127, 109883.
Kozlenkova, I. V., Hult, G. T. M., Lund, D. J., Mena, J. A., and Kekec, P. (2015). The role of marketing channels in supply chain management. Journal of Retailing, Vol. 91(4), pp. 586–609.
Kumar, A., Luthra, S., Mangla, S. K., and Kazançoğlu, Y. (2020). COVID-19 impact on sustainable production and operations management. Sustainable Operations and Computers, Vol. 1, pp. 1–7.
Md Mashud, A., and Hasan, M. R. (2019). An economic order quantity model for decaying products with the frequency of advertisement, selling price and continuous time dependent demand under partially backlogged shortage. International Journal of Supply and Operations Management, Vol. 6(4), pp. 296–314.
Metcalf, G. E. (2009). Market-based policy options to control US greenhouse gas emissions. Journal of Economic Perspectives, Vol. 23(2), 5–27.
Navarro, K. S., Chedid, J. A., Florez, W. F., Mateus, H. O., Cárdenas-Barrón, L. E., and Sana, S. S. (2020). A collaborative EPQ inventory model for a three-echelon supply chain with multiple products considering the effect of marketing effort on demand. Journal of Industrial & Management Optimization, Vol. 16(4), 1613.
Ouyang, L.-Y., Ho, C.-H., and Su, C.-H. (2008). Optimal strategy for an integrated system with variable production rate when the freight rate and trade credit are both linked to the order quantity. International Journal of Production Economics, Vol. 115(1), pp. 151–162.
Paul, S. K., and Chowdhury, P. (2020). A production recovery plan in manufacturing supply chains for a high-demand item during COVID-19. International Journal of Physical Distribution & Logistics Management.
Rowan, N. J., and Laffey, J. G. (2020). Challenges and solutions for addressing critical shortage of supply chain for personal and protective equipment (PPE) arising from Coronavirus disease (COVID19) pandemic–Case study from the Republic of Ireland. Science of The Total Environment, 138532.
Ruidas, S., Seikh, M. R., and Nayak, P. K. (2019). An EPQ model with stock and selling price dependent demand and variable production rate in interval environment. International Journal of System Assurance Engineering and Management, pp. 1–15.
Sana, S., and Chaudhuri, K. S. (2006). On a volume flexible stock-dependent inventory model. PROCEEDINGS-NATIONAL ACADEMY OF SCIENCES INDIA SECTION A, Vol. 76(4), 309.
Sana, S. S. (2010). Demand influenced by enterprises’ initiatives—A multi-item EOQ model of deteriorating and ameliorating items. Mathematical and Computer Modelling, Vol. 52(1–2), pp. 284–302.
Sarkar, B., Majumder, A., Sarkar, M., Kim, N., and Ullah, M. (2018). Effects of variable production rate on quality of products in a single-vendor multi-buyer supply chain management. The International Journal of Advanced Manufacturing Technology, Vol. 99(1–4), pp. 567–581.
Sethi, A. K., and Sethi, S. P. (1990). Flexibility in manufacturing: A survey. International Journal of Flexible Manufacturing Systems, Vol. 2(4), pp. 289–328.
Shokrani, A., Loukaides, E. G., Elias, E., and Lunt, A. J. (2020). Exploration of alternative supply chains and distributed manufacturing in response to COVID-19; a case study of medical face shields. Materials & Design, Vol. 192, 108749.
Zenetti, G., and Klapper, D. (2016). Advertising effects under consumer heterogeneity–the moderating role of brand experience, advertising recall and attitude. Journal of Retailing, Vol. 92(3), pp. 352–372.