IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v8y2024i3p87-d1472135.html
   My bibliography  Save this article

Ranking and Challenges of Supply Chain Companies Using MCDM Methodology

Author

Listed:
  • Alaa Fouad Momena

    (Department of Industrial Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al Kharj 11942, Saudi Arabia)

  • Kamal Hossain Gazi

    (Department of Applied Mathematics, Maulana Abul Kalam Azad University of Technology, Haringhata 741249, West Bengal, India)

  • Mostafijur Rahaman

    (Department of Mathematics, School of Liberal Arts & Sciences, Mohan Babu University, Tirupati 517102, Andhra Pradesh, India)

  • Anna Sobczak

    (Faculty of Economics, The Jacob of Paradies University, 66-400 Gorzów Wielkopolski, Poland)

  • Soheil Salahshour

    (Faculty of Engineering and Natural Sciences, Istanbul Okan University, Istanbul 34959, Turkey
    Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul 34488, Turkey
    Department of Computer Science and Mathematics, Lebanese American University, Beirut 13-5053, Lebanon)

  • Sankar Prasad Mondal

    (Department of Applied Mathematics, Maulana Abul Kalam Azad University of Technology, Haringhata 741249, West Bengal, India)

  • Arijit Ghosh

    (Department of Mathematics, St. Xavier’s College (Autonomous), Kolkata 700016, West Bengal, India)

Abstract

Background : Supply chain companies have merits and demerits regarding operational and economic transactional policies. The effectiveness of supply chain companies corresponds to a cumulative score on a multi-criteria and perspectives-based evaluation. In this paper, we analyse the performances and challenges of several celebrated e-commerce companies to perceive their overall impression of supply chain management. Method : A mathematical model is framed as a multi-criteria decision-making (MCDM) problem with challenges as criteria and companies as alternatives. The criteria importance through inter-criteria correlation (CRITIC) method is used in this paper to adjust weights representing the available data. The ranking of e-commerce companies is evaluated using multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method. Results : This model investigates the most dependent criteria and sub-criteria for the adaptation challenges of supply chain companies (SCCs). Furthermore, the SCCs are prioritized based on various conflicting criteria. Conclusion : Various challenges of SCCs, like logistics constraints, disruptions in supply chains, issues with technology, ethical sourcing and inconsistency between the products’ availability and the pace of consumption, are considered and analysed. We amassed the difficulties as criteria and sub-criteria in a numerical process using the MCDM approach. Additionally, the sensitivity and comparative of several optimal phenomena are analysed based on distinctive combinations of challenges in the ranking arena.

Suggested Citation

  • Alaa Fouad Momena & Kamal Hossain Gazi & Mostafijur Rahaman & Anna Sobczak & Soheil Salahshour & Sankar Prasad Mondal & Arijit Ghosh, 2024. "Ranking and Challenges of Supply Chain Companies Using MCDM Methodology," Logistics, MDPI, vol. 8(3), pages 1-32, September.
    • Handle: RePEc:gam:jlogis:v:8:y:2024:i:3:p:87-:d:1472135
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/8/3/87/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2305-6290/8/3/87/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Miguel Afonso Sellitto & Giancarlo Medeiros Pereira & Miriam Borchardt & Rosnaldo Inácio da Silva & Cláudia Viviane Viegas, 2015. "A SCOR-based model for supply chain performance measurement: application in the footwear industry," International Journal of Production Research, Taylor & Francis Journals, vol. 53(16), pages 4917-4926, August.
    2. Alberto Cavallo & Eduardo Cavallo & Roberto Rigobon, 2014. "Prices and Supply Disruptions during Natural Disasters," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(S2), pages 449-471, November.
    3. Pınar Miç & Z. Figen Antmen, 2021. "A Decision-Making Model Based on TOPSIS, WASPAS, and MULTIMOORA Methods for University Location Selection Problem," SAGE Open, , vol. 11(3), pages 21582440211, August.
    4. Mohsen Ramezanzade & Hossein Karimi & Khalid Almutairi & Hoa Ao Xuan & Javad Saebi & Ali Mostafaeipour & Kuaanan Techato, 2021. "Implementing MCDM Techniques for Ranking Renewable Energy Projects under Fuzzy Environment: A Case Study," Sustainability, MDPI, vol. 13(22), pages 1-38, November.
    5. Amir Khorram-Manesh & Maxim A. Dulebenets & Krzysztof Goniewicz, 2021. "Implementing Public Health Strategies—The Need for Educational Initiatives: A Systematic Review," IJERPH, MDPI, vol. 18(11), pages 1-21, May.
    6. Chen, Jen-Yi & Slotnick, Susan A., 2015. "Supply chain disclosure and ethical sourcing," International Journal of Production Economics, Elsevier, vol. 161(C), pages 17-30.
    7. Adnan Veysel Ertemel & Akin Menekse & Hatice Camgoz Akdag, 2023. "Smartphone Addiction Assessment Using Pythagorean Fuzzy CRITIC-TOPSIS," Sustainability, MDPI, vol. 15(5), pages 1-19, February.
    8. Kefan Xie & Benbu Liang & Maxim A. Dulebenets & Yanlan Mei, 2020. "The Impact of Risk Perception on Social Distancing during the COVID-19 Pandemic in China," IJERPH, MDPI, vol. 17(17), pages 1-17, August.
    9. Somayeh Soheilirad & Kannan Govindan & Abbas Mardani & Edmundas Kazimieras Zavadskas & Mehrbakhsh Nilashi & Norhayati Zakuan, 2018. "Application of data envelopment analysis models in supply chain management: a systematic review and meta-analysis," Annals of Operations Research, Springer, vol. 271(2), pages 915-969, December.
    10. repec:bla:revinw:v:60:y:2014:i::p:s449-s471 is not listed on IDEAS
    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. Rola Khamisy-Farah & Peter Gilbey & Leonardo B. Furstenau & Michele Kremer Sott & Raymond Farah & Maurizio Viviani & Maurizio Bisogni & Jude Dzevela Kong & Rosagemma Ciliberti & Nicola Luigi Bragazzi, 2021. "Big Data for Biomedical Education with a Focus on the COVID-19 Era: An Integrative Review of the Literature," IJERPH, MDPI, vol. 18(17), pages 1-16, August.
    2. Alex Nikolsko‐Rzhevskyy & Oleksandr Talavera & Nam Vu, 2023. "The flood that caused a drought," Economic Inquiry, Western Economic Association International, vol. 61(4), pages 965-981, October.
    3. Haroon Mumtaz & Fulvia Marotta, 2023. "Vulnerability to Climate Change: Evidence from a Dynamic Factor Model," Working Papers 961, Queen Mary University of London, School of Economics and Finance.
    4. Jennifer Peña & Elvira Prades, 2021. "Price setting in Chile: Micro evidence from consumer on-line prices during the social outbreak and Covid-19," Working Papers 2112, Banco de España.
    5. Suriyan Jomthanachai & Wai Peng Wong & Khai Wah Khaw, 2024. "An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 741-792, February.
    6. Emmanuel Apergis & Nicholas Apergis, 2021. "The impact of COVID-19 on economic growth: evidence from a Bayesian Panel Vector Autoregressive (BPVAR) model," Applied Economics, Taylor & Francis Journals, vol. 53(58), pages 6739-6751, December.
    7. Jina Choo & Sooyeon Park & Songwhi Noh, 2021. "Associations of COVID-19 Knowledge and Risk Perception with the Full Adoption of Preventive Behaviors in Seoul," IJERPH, MDPI, vol. 18(22), pages 1-14, November.
    8. Miguel Afonso Sellitto & Guilherme Schreiber Pereira & Rafael Marques & Daniel Pacheco Lacerda, 2018. "Systemic Understanding of Coopetitive Behaviour in a Latin American Technological Park," Systemic Practice and Action Research, Springer, vol. 31(5), pages 479-494, October.
    9. Miles Parker, 2018. "The Impact of Disasters on Inflation," Economics of Disasters and Climate Change, Springer, vol. 2(1), pages 21-48, April.
    10. Etienne Gagnon & David López-Salido, 2020. "Small Price Responses to Large Demand Shocks," Journal of the European Economic Association, European Economic Association, vol. 18(2), pages 792-828.
    11. Gabriel J. Felbermayr & Jasmin Katrin Gröschl & Benedikt Heid, 2020. "Quantifying the Supply and Demand Effects of Natural Disasters Using Monthly Trade Data," CESifo Working Paper Series 8798, CESifo.
    12. Bian, Junsong & Liao, Yi & Wang, Yao-Yu & Tao, Feng, 2021. "Analysis of firm CSR strategies," European Journal of Operational Research, Elsevier, vol. 290(3), pages 914-926.
    13. Venkatesh, V.G. & Zhang, Abraham & Deakins, Eric & Mani, Venkatesh, 2021. "Antecedents of social sustainability noncompliance in the Indian apparel sector," International Journal of Production Economics, Elsevier, vol. 234(C).
    14. Shengnan Sun & Xinping Wang & Yan Zhang, 2017. "Sustainable Traceability in the Food Supply Chain: The Impact of Consumer Willingness to Pay," Sustainability, MDPI, vol. 9(6), pages 1-19, June.
    15. Talieh Abdolkhaninezhad & Masoud Monavari & Nematollah Khorasani & Maryam Robati & Forogh Farsad, 2022. "Analysis Indicators of Health-Safety in the Risk Assessment of Landfill with the Combined Method of Fuzzy Multi-Criteria Decision Making and Bow Tie Model," Sustainability, MDPI, vol. 14(22), pages 1-24, November.
    16. Kanika Mahajan & Shekhar Tomar, 2021. "COVID‐19 and Supply Chain Disruption: Evidence from Food Markets in India†," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(1), pages 35-52, January.
    17. Teng Zhao, 2022. "Impact of COVID-19 Awareness on Protective Behaviors during the Off-Peak Period: Sex Differences among Chinese Undergraduates," IJERPH, MDPI, vol. 19(20), pages 1-11, October.
    18. Xiaodan Pan & Martin Dresner & Benny Mantin & Jun A. Zhang, 2020. "Pre‐Hurricane Consumer Stockpiling and Post‐Hurricane Product Availability: Empirical Evidence from Natural Experiments," Production and Operations Management, Production and Operations Management Society, vol. 29(10), pages 2350-2380, October.
    19. Nebiyu Kedir & Phuong H. D. Nguyen & Citlaly Pérez & Pedro Ponce & Aminah Robinson Fayek, 2023. "Systematic Literature Review on Fuzzy Hybrid Methods in Photovoltaic Solar Energy: Opportunities, Challenges, and Guidance for Implementation," Energies, MDPI, vol. 16(9), pages 1-38, April.
    20. Panda, S. & Modak, N.M. & Basu, M. & Goyal, S.K., 2015. "Channel coordination and profit distribution in a social responsible three-layer supply chain," International Journal of Production Economics, Elsevier, vol. 168(C), pages 224-233.

    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:jlogis:v:8:y:2024:i:3:p:87-:d:1472135. 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.