IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i14p8876-d867046.html
   My bibliography  Save this article

Eye-SCOR: A Supply Chain Operations Reference-Based Framework for Smart Eye Status Monitoring Using System Dynamics Modeling

Author

Listed:
  • Saba Pourreza

    (Congdon School of Supply Chain, Business Analytics, and Information Systems, University of North Carolina Wilmington, Wilmington, NC 28403, USA
    These authors contributed equally to this work.)

  • Misagh Faezipour

    (Department of Engineering Technology, Middle Tennessee State University, Murfreesboro, TN 37132, USA
    These authors contributed equally to this work.)

  • Miad Faezipour

    (School of Engineering Technology, Electrical and Computer Engineering Technology, Purdue University, West Lafayette, IN 47907, USA
    These authors contributed equally to this work.)

Abstract

This work is a unique integration of three different areas, including smart eye status monitoring, supply chain operations reference (SCOR), and system dynamics, to explore the dynamics of the supply chain network of smart eye/vision monitoring systems. Chronic eye diseases such as glaucoma affect millions of individuals worldwide and, if left untreated, can lead to irreversible vision loss. Nearly half of the affected population is unaware of the condition and can be informed with frequent, accessible eye/vision tests. Tonometry is the conventional clinical method used in healthcare settings to determine the intraocular pressure (IOP) level for evaluating the risk of glaucoma. There are currently very few (under development) non-contact and non-invasive methods using smartphones to determine the risk of IOP and/or the existence of other eye-related diseases conveniently at home. With the overall goal of improving health, well-being, and sustainability, this paper proposes Eye-SCOR: a supply chain operations reference (SCOR)-based framework to evaluate the effectiveness of smartphone-based eye status monitoring apps. The proposed framework is designed using system dynamics modeling as a subset of a new causal model. The model includes interaction/activities between the main players and enablers in the supply chain network, namely suppliers/service providers, smartphone app/device factors, customers, and healthcare professionals, as well as cash and information flow. The model has been tested under various scenarios and settings. Simulation results reveal the dynamics of the model and show that improving the eye status monitoring device/app factors directly increases the efficiency/Eye-SCOR level. The proposed framework serves as an important step towards understanding and improving the overall performance of the supply chain network of smart eye/vision monitoring systems.

Suggested Citation

  • Saba Pourreza & Misagh Faezipour & Miad Faezipour, 2022. "Eye-SCOR: A Supply Chain Operations Reference-Based Framework for Smart Eye Status Monitoring Using System Dynamics Modeling," Sustainability, MDPI, vol. 14(14), pages 1-17, July.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8876-:d:867046
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/14/8876/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/14/8876/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tuncdan Baltacioglu & Erhan Ada & Melike D. Kaplan & Oznur Yurt And & Y. Cem Kaplan, 2007. "A New Framework for Service Supply Chains," The Service Industries Journal, Taylor & Francis Journals, vol. 27(2), pages 105-124, March.
    2. M Kunc & R Kazakov, 2013. "Competitive dynamics in pharmaceutical markets: A case study in the chronic cardiac disease market," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(12), pages 1790-1799, December.
    3. Negar Darabi & Niyousha Hosseinichimeh, 2020. "System dynamics modeling in health and medicine: a systematic literature review," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 29-73, January.
    4. Ntabe, E.N. & LeBel, L. & Munson, A.D. & Santa-Eulalia, L.A., 2015. "A systematic literature review of the supply chain operations reference (SCOR) model application with special attention to environmental issues," International Journal of Production Economics, Elsevier, vol. 169(C), pages 310-332.
    5. Misagh Faezipour & Miad Faezipour, 2020. "Sustainable Smartphone-Based Healthcare Systems: A Systems Engineering Approach to Assess the Efficacy of Respiratory Monitoring Apps," Sustainability, MDPI, vol. 12(12), pages 1-18, June.
    6. Dissanayake, C. Kalpani & Cross, Jennifer A., 2018. "Systematic mechanism for identifying the relative impact of supply chain performance areas on the overall supply chain performance using SCOR model and SEM," International Journal of Production Economics, Elsevier, vol. 201(C), pages 102-115.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zanon, Lucas Gabriel & Munhoz Arantes, Rafael Ferro & Calache, Lucas Daniel Del Rosso & Carpinetti, Luiz Cesar Ribeiro, 2020. "A decision making model based on fuzzy inference to predict the impact of SCOR® indicators on customer perceived value," International Journal of Production Economics, Elsevier, vol. 223(C).
    2. Zanon, Lucas Gabriel & Marcelloni, Francesco & Gerolamo, Mateus Cecílio & Ribeiro Carpinetti, Luiz Cesar, 2021. "Exploring the relations between supply chain performance and organizational culture: A fuzzy grey group decision model," International Journal of Production Economics, Elsevier, vol. 233(C).
    3. Zhang, Lu & Cui, Li & Chen, Lujie & Dai, Jing & Jin, Ziyi & Wu, Hao, 2023. "A hybrid approach to explore the critical criteria of online supply chain finance to improve supply chain performance," International Journal of Production Economics, Elsevier, vol. 255(C).
    4. Marcela Marçal Alves Pinto & João Luiz Kovaleski & Rui Tadashi Yoshino & Regina Negri Pagani, 2019. "Knowledge and Technology Transfer Influencing the Process of Innovation in Green Supply Chain Management: A Multicriteria Model Based on the DEMATEL Method," Sustainability, MDPI, vol. 11(12), pages 1-33, June.
    5. Jingshi He & Jiali Zhu, 2022. "Key Drivers of the Emergency Capabilities of Integrated Elderly Services Supply Chains," Information Resources Management Journal (IRMJ), IGI Global, vol. 35(1), pages 1-20, January.
    6. Johnson, Mark & Mena, Carlos, 2008. "Supply chain management for servitised products: A multi-industry case study," International Journal of Production Economics, Elsevier, vol. 114(1), pages 27-39, July.
    7. Claire F. Brereton & Paul Jagals, 2021. "Applications of Systems Science to Understand and Manage Multiple Influences within Children’s Environmental Health in Least Developed Countries: A Causal Loop Diagram Approach," IJERPH, MDPI, vol. 18(6), pages 1-23, March.
    8. Akkermans, H.A. & Voss, C., 2013. "The service bullwhip effect," Other publications TiSEM 94cf4db3-1de0-4b53-897b-8, Tilburg University, School of Economics and Management.
    9. Eko Budi Leksono & Suparno Suparno & Iwan Vanany, 2019. "Integration of a Balanced Scorecard, DEMATEL, and ANP for Measuring the Performance of a Sustainable Healthcare Supply Chain," Sustainability, MDPI, vol. 11(13), pages 1, July.
    10. Boon-itt, Sakun & Wong, Chee Yew & Wong, Christina W.Y., 2017. "Service supply chain management process capabilities: Measurement development," International Journal of Production Economics, Elsevier, vol. 193(C), pages 1-11.
    11. Wang, Yulan & Wallace, Stein W. & Shen, Bin & Choi, Tsan-Ming, 2015. "Service supply chain management: A review of operational models," European Journal of Operational Research, Elsevier, vol. 247(3), pages 685-698.
    12. Talley, Wayne K. & Ng, ManWo, 2016. "Port economic cost functions: A service perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 1-10.
    13. Negar Jalilian & Seyed Mahmoud Zanjirchi & Alireza Naser Sadrabadi & Ahmadreza Asgharpourmasouleh & Mark Goh, 2021. "Agent-Based Approach to Configure Processes in Iran’s Banking Service Supply Chain," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    14. Ekinci, Esra & Mangla, Sachin Kumar & Kazancoglu, Yigit & Sarma, P.R.S. & Sezer, Muruvvet Deniz & Ozbiltekin-Pala, Melisa, 2022. "Resilience and complexity measurement for energy efficient global supply chains in disruptive events," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    15. Orkun İrsoy & Şanser Güz & Naz Beril Akan & Gönenç Yücel, 2020. "Dynamic trade‐offs in granulocyte colony‐stimulating factor (G‐CSF) administration during chemotherapy," System Dynamics Review, System Dynamics Society, vol. 36(4), pages 397-446, October.
    16. Ahmad A. A. Khanfar & Mohammad Iranmanesh & Morteza Ghobakhloo & Madugoda Gunaratnege Senali & Masood Fathi, 2021. "Applications of Blockchain Technology in Sustainable Manufacturing and Supply Chain Management: A Systematic Review," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    17. Badr Bentalha, 2020. "Big-Data and Service Supply chain management: Challenges and opportunities [Big-Data et Service Supply chain management: Challenges et opportunités]," Post-Print hal-02680861, HAL.
    18. Martin Kunc, 2021. "A commentary on Lustick and Tetlock 2021," Futures & Foresight Science, John Wiley & Sons, vol. 3(2), June.
    19. Negar Darabi & Niyousha Hosseinichimeh, 2020. "System dynamics modeling in health and medicine: a systematic literature review," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 29-73, January.
    20. Robert Suurmond & Larry J. Menor & Finn Wynstra, 2022. "Examining service triad operations: Formation, functioning, and feedback exchanges," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3352-3370, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8876-:d:867046. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.