Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Modelling the strategies for improving maturity and resilience in medical oxygen supply chain through digital technologies

Modelling the strategies for improving maturity and resilience in medical oxygen supply chain... Improving the medical oxygen supply chain (MOSC) is important to cope with the uneven demand and supply seen in the MOSC when India faced the second wave of COVID-19. This improvisation increases the supply chain (SC) maturity and consequently the efficiency and resiliency to tackle oxygen shortage across the country and to prevent another similar scenario from ever happening. The purpose of this study is to identify and prioritize the solutions to overcome the issues faced by the MOSC during the second wave of COVID-19 cases in India and in turn reduce the extent of casualties in the expected third wave.Design/methodology/approachThis paper uses best worst method (BWM) and fuzzy technique for order performance by similarity to ideal solution to classify the sub-criteria for solutions to solve major SC issues. BWM is used to determine the weights of the sub-criteria and fuzzy technique for order performance by similarity to ideal solution for the final ranking of the solutions to be adopted.FindingsThe result of this study shows that the Internet of Things based tagging system is the best solution followed by horizontal and vertical integration of SC in making a resilient and digitized MOSC capable of handling general bottlenecks during a possible third wave.Research limitations/implicationsThe research provides insights that can enable the personnel involved in MOSC. Proper understanding will help the practitioners involved in the SC to effectively tailor the operations and to allocate the resources available in an effective and dynamic manner by minimizing or eliminating the pre-existing bottlenecks within the SC.Originality/valueThe proposed framework provides an accurate ranking and decision-making tool for the implementation of the solutions for the maturity of the MOSC. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Global Operations and Strategic Sourcing Emerald Publishing

Modelling the strategies for improving maturity and resilience in medical oxygen supply chain through digital technologies

Download PDF
33 pages

Loading next page...
 
/lp/emerald-publishing/modelling-the-strategies-for-improving-maturity-and-resilience-in-QdZ0XXc0MZ
Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
2398-5364
DOI
10.1108/jgoss-10-2021-0088
Publisher site
See Article on Publisher Site

Abstract

Improving the medical oxygen supply chain (MOSC) is important to cope with the uneven demand and supply seen in the MOSC when India faced the second wave of COVID-19. This improvisation increases the supply chain (SC) maturity and consequently the efficiency and resiliency to tackle oxygen shortage across the country and to prevent another similar scenario from ever happening. The purpose of this study is to identify and prioritize the solutions to overcome the issues faced by the MOSC during the second wave of COVID-19 cases in India and in turn reduce the extent of casualties in the expected third wave.Design/methodology/approachThis paper uses best worst method (BWM) and fuzzy technique for order performance by similarity to ideal solution to classify the sub-criteria for solutions to solve major SC issues. BWM is used to determine the weights of the sub-criteria and fuzzy technique for order performance by similarity to ideal solution for the final ranking of the solutions to be adopted.FindingsThe result of this study shows that the Internet of Things based tagging system is the best solution followed by horizontal and vertical integration of SC in making a resilient and digitized MOSC capable of handling general bottlenecks during a possible third wave.Research limitations/implicationsThe research provides insights that can enable the personnel involved in MOSC. Proper understanding will help the practitioners involved in the SC to effectively tailor the operations and to allocate the resources available in an effective and dynamic manner by minimizing or eliminating the pre-existing bottlenecks within the SC.Originality/valueThe proposed framework provides an accurate ranking and decision-making tool for the implementation of the solutions for the maturity of the MOSC.

Journal

Journal of Global Operations and Strategic Sourcing – Emerald Publishing

Published: Dec 5, 2022

Keywords: Fuzzy technique for order performance by similarity to ideal solution; BWM; Medical oxygen supply chain maturity; Supply chain resilience; MCDM; Innovation; Risk management; Service design; New business or process or operations models; Business improvement; Both

References

  • Effect of supply-chain resilience on firm performance and competitive advantage: a study of the Sri Lankan apparel industry
    Abeysekara, N.; Wang, H.; Kuruppuarachchi, D.
  • Assessing supply chain robustness to links failure
    Adenso-Díaz, B.; Mar-Ortiz, J.; Lozano, S.
  • Evaluating solutions to overcome humanitarian supply chain management barriers: a hybrid fuzzy SWARA-Fuzzy WASPAS approach
    Agarwal, S.; Kant, R.; Shankar, R.
  • Towards supply chain visibility using internet of things: a dyadic analysis review
    Ahmed, S.; Kalsoom, T.; Ramzan, N.; Pervez, Z.; Azmat, M.; Zeb, B.; Ur Rehman, M.
  • Assessing the leanness of a supply chain using multi-grade fuzzy logic: a health-care case study
    Almutairi, A.M.; Salonitis, K.; Al-Ashaab, A.
  • Achieving supply chain resilience: the role of supply chain ambidexterity and supply chain agility
    Aslam, H.; Khan, A.Q.; Rashid, K.; Rehman, S.U.
  • Multi-criteria decision making using TOPSIS method under fuzzy environment. Application in spillway selection
    Balioti, V.; Tzimopoulos, C.; Evangelides, C.
  • Social capital and the spread of COVID-19: insights from European countries
    Bartscher, A.K.; Nationalbank, D.; Seitz, S.; Siegloch, S.; Slotwinski, M.; Wehrhöfer, N.
  • Methods for mitigating disruptions in complex supply chain structures: a systematic literature review
    Bier, T.; Lange, A.; Glock, C.H.
  • Digital supply chain: literature review and a proposed framework for future research
    Büyüközkan, G.; Göçer, F.
  • Managing supply chain resilience to pursue business and environmental strategies
    Centobelli, P.; Cerchione, R.; Ertz, M.
  • Evaluating critical barriers and pathways to implementation of e-waste formalization management systems in Ghana: a hybrid BWM and fuzzy TOPSIS approach
    Chen, D.; Faibil, D.; Agyemang, M.
  • Industry 4.0 and circular economy: operational excellence for sustainable reverse supply chain performance
    Dev, N.K.; Shankar, R.; Qaiser, F.H.
  • Supply chain and logistics controller–two promising professions for supporting transparency in supply chain management
    Dobroszek, J.
  • Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain
    Dolgui, A.; Ivanov, D.; Potryasaev, S.; Sokolov, B.; Ivanova, M.; Werner, F.
  • Supply chain risk mitigation strategies during COVID-19: exploratory cases of ‘make-to-order’ handloom saree apparel industries
    Dohale, V.; Ambilkar, P.; Gunasekaran, A.; Verma, P.
  • Paths to innovation in supply chains: the landscape of future research
    Fornasiero, R.; Marchiori, I.; Pessot, E.; Zangiacomi, A.; Sardesai, S.; Barros, A.C.; Muerza, V.
  • Towards a supply chain 4.0 on the post-COVID-19 pandemic: a conceptual and strategic discussion for more resilient supply chains
    Frederico, G.F.
  • Supply chain 4.0: concepts, maturity and research agenda
    Frederico, G.F.; Garza-Reyes, J.A.; Anosike, A.; Kumar, V.
  • A SIDARTHE model of COVID-19 epidemic in Italy
    Giordano, G.; Blanchini, F.; Di Filippo, A.; Di Matteo, A.; Colaneri, M.
  • Green supplier selection using multi-criterion decision making under fuzzy environment: a case study in automotive industry
    Gupta, S.; Soni, U.; Kumar, G.
  • A fuzzy rule-based industry 4.0 maturity model for operations and supply chain management
    Gusmão Caiado, R.G.; Scavarda, L.F.; Gavião, L.O.; Ivson, P.; Luiz de Mattos Nascimento, D.; Garza-Reyes, J.A.
  • Analytical design and experimental verification of geofencing control for aerial applications
    Ghaffari, A.
  • Supplier selection among SMEs on the basis of their green innovation ability using BWM and fuzzy TOPSIS
    Gupta, H.; Barua, M.K.
  • Horizontal and vertical integration of health care providers: a framework for understanding various provider organizational structures
    Heeringa, J.; Mutti, A.; Furukawa, M.F.; Lechner, A.; Maurer, K.A.; Rich, E.
  • Review of quantitative methods for supply chain resilience analysis
    Hosseini, S.; Ivanov, D.; Dolgui, A.
  • Supply chain flexibility concepts, dimensions and outcomes: an organisational capability perspective
    Huo, B.; Gu, M.; Wang, Z.
  • Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak
    Ivanov, D.; Dolgui, A.
  • The impact of digital technology and industry 4.0 on the ripple effect and supply chain risk analytics
    Ivanov, D.; Dolgui, A.; Sokolov, B.
  • Green supplier selection for the steel industry using BWM and fuzzy TOPSIS: a case study of Khouzestan steel company
    Javad, M.O.M.; Darvishi, M.; Javad, A.O.M.
  • Bottleneck identification and ranking model for mine operations
    Kahraman, M.M.; Rogers, W.P.; Dessureault, S.
  • Face masks, public policies and slowing the spread of COVID-19: evidence from Canada
    Karaivanov, A.; Lu, S.E.; Shigeoka, H.; Chen, C.; Pamplona, S.
  • Improving supply chain sustainability in the context of COVID-19 pandemic in an emerging economy: exploring drivers using an integrated model
    Karmaker, C.L.; Ahmed, T.; Ahmed, S.; Ali, S.M.; Moktadir, M.A.; Kabir, G.
  • Supply chain resilience: a systematic literature review and typological framework
    Kochan, C.G.; Nowicki, D.R.
  • Developing a maturity model for supply chain management
    Lahti, M.; Shamsuzzoha, A.H.M.; Helo, P.
  • The development of a supply chain management process maturity model using the concepts of business process orientation
    Lockamy, A.; McCormack, K.
  • COVID-19 and increasing demand for medical oxygen: can impurity be a problem
    Malik, S.; Ravindra, K.; Singh, M.
  • Impact of digitalization on the efficiency of supply chain management in the digital economy
    Mikhaylova, A.; Sakulyeva, T.; Shcherbina, T.; Levoshich, N.; Truntsevsky, Y.
  • A multi-objective model for risk mitigating in supply chain design
    Nooraie, V.; Fathi, M.; Narenji, M.; Parast, M.M.; Pardalos, P.M.; Stanfield, P.M.
  • ICU outcomes and survival in patients with severe COVID-19 in the largest health care system in Central Florida
    Oliveira, E.; Parikh, A.; Lopez-Ruiz, A.; Carrilo, M.; Goldberg, J.; Cearras, M.; Finkler, N.
  • Evaluation of criteria and COVID-19 patients for intensive care unit admission in the era of pandemic: a multi-criteria decision-making approach
    Özkan, B.; Özceylan, E.; Kabak, M.; Dikmen, A.U.
  • The architectural framework of a cyber physical logistics system for digital-twin-based supply chain control
    Park, K.T.; Son, Y.H.; Noh, S.D.
  • Industry 4.0 and resilience in the supply chain: a driver of capability enhancement or capability loss?
    Ralston, P.; Blackhurst, J.
  • Thermodynamic and economic performance of oxy-combustion power plants integrating chemical looping air separation
    Qing, M.; Jin, B.; Ma, J.; Zou, X.; Wang, X.; Zheng, C.; Zhao, H.
  • RFID tags for IOT (internet of things)
    Raj, N.
  • Internet of Things research in supply chain management and logistics: a bibliometric analysis
    Rejeb, M.A.; Simske, S.; Rejeb, K.; Treiblmaier, H.; Zailani, S.
  • Quality provision in hospital markets with demand inertia: the role of patient expectations
    Sa, L.; Straume, O.R.
  • Firm innovation and supply chain resilience: a dynamic capability perspective
    Sabahi, S.; Parast, M.M.
  • Sustainable collection center location selection in emerging economies for electronic waste with fuzzy best-worst and fuzzy TOPSIS
    Sagnak, M.; Berberoglu, Y.; Memis; Yazgan, O.
  • A maturity model for assessing industry 4.0 readiness and maturity of manufacturing enterprises
    Schumacher, A.; Erol, S.; Sihn, W.
  • Physician investment in hospitals: specialization, selection, and quality in cardiac care
    Swanson, A.
  • Blockchain technology and its relationships to sustainable supply chain management
    Saberi, S.; Kouhizadeh, M.; Sarkis, J.; Shen, L.
  • Supply chain digitalization: past, present and future
    Seyedghorban, Z.; Tahernejad, H.; Meriton, R.; Graham, G.
  • Supply chain security management: a citation network analysis
    Tong, X.; Lo, C.K.; Lai, K.H.; Cheng, T.C.E.
  • Regional water resources security evaluation based on a hybrid fuzzy BWM-TOPSIS method
    Tu, Y.; Chen, K.; Wang, H.; Li, Z.
  • Industry 4.0-based manufacturing systems: smart production, sustainable supply chain networks, and real-time process monitoring
    Tuffnell, C.; Kral, P.; Durana, P.; Krulicky, T.
  • Evaluating on-demand warehousing via dynamic facility location models
    Unnu, K.; Pazour, J.A.
  • The digitization of a food package’s life cycle: existing and emerging computer systems in the logistics and post-logistics phase
    Vanderroost, M.; Ragaert, P.; Verwaeren, J.; De Meulenaer, B.; De Baets, B.; Devlieghere, F.
  • Owned vertical integration and health care: promise and performance
    Walston, S.L.; Kimberly, J.R.; Burns, L.R.
  • Big data analytics in logistics and supply chain management: certain investigations for research and applications
    Wang, G.; Gunasekaran, A.; Ngai, E.W.T.; Papadoulos, T.
  • Application of TOPSIS and AHP in the multi-objective decision-making problems
    Wang, Y.
  • Intelligent supply chain performance measurement in industry 4.0
    Xie, Y.; Yin, Y.; Xue, W.; Shi, H.; Chong, D.
  • Supply chain management 4.0: a literature review and research framework
    Zekhnini, K.; Cherrafi, A.; Bouhaddou, I.; Benghabrit, Y.; Garza-Reyes, J.A.
  • Prioritisation of drivers of sustainable additive manufacturing using best worst method
    Agrawal, R.; Vinodh, S.
  • Assembly line balancing with parallel workstations
    Álvarez-Miranda, E.; Chace, S.; Pereira, J.
  • The grimmest days of the COVID-19 pandemic coincide with the most severe forms of rationing
    Cohen, J.
  • Assessing supply chain robustness to links failure
    Díaz Fernández, B.A.; Mar Ortiz, J.; Lozano, S.
  • India’s COVID19 surge is highlighting a ruthless global black market for oxygen where sellers jack prices up to 1000%