IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v16y2023i4p242-d1124548.html
   My bibliography  Save this article

Supply Chain Risk Management in a Digital Era: Evidence from SMEs of Clothing Retailers in Australia

Author

Listed:
  • Mehadi Mamun

    (Department of Business Administration, Victorian Institute of Technology, Sydney 2000, Australia)

Abstract

With the increased globalisation and disruptions faced by businesses in this digital era and the occurrence of natural disasters such as floods and disease outbreaks in the world, supply chain risks and management of those risks are major challenges for businesses, especially for SMEs of clothing retailers in Australia. This study, hence, is carried out using an exploratory case study research method, and the data have been collected through semi-structured face-to-face interviews with key informants from managerial levels of 20 Australian SMEs of clothing retailing businesses to identify various supply chain risks and their management processes. This study finds five supply chain risks, namely supply risk, demand risk, financial risk, environmental risk, and operational risk, that the SMEs of clothing retailers mostly face in the supply chain. This study also finds that most of the investigated retailers lack a formal risk identification approach, though they informally use the reactive and proactive methods of risk identification. Furthermore, the assessment methods are not well established in most of the participating firms, and supplier monitoring receives more attention compared to their own performance to deal with their supply chain risks. This study contributes to the body of knowledge by being one of the first empirical studies to explore the SMEs of clothing retailers’ supply chain risks and their management processes in the Australian business context, which can add value in guiding supply chain design decisions for SMEs in other sectors.

Suggested Citation

  • Mehadi Mamun, 2023. "Supply Chain Risk Management in a Digital Era: Evidence from SMEs of Clothing Retailers in Australia," JRFM, MDPI, vol. 16(4), pages 1-11, April.
  • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:4:p:242-:d:1124548
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/16/4/242/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/16/4/242/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Goh, Mark & Lim, Joseph Y.S. & Meng, Fanwen, 2007. "A stochastic model for risk management in global supply chain networks," European Journal of Operational Research, Elsevier, vol. 182(1), pages 164-173, October.
    2. Tang, Ou & Nurmaya Musa, S., 2011. "Identifying risk issues and research advancements in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 133(1), pages 25-34, September.
    3. Wiesner, Retha & McDonald, Jim & Banham, Heather C, 2007. "Australian small and medium sized enterprises (SMEs): A study of high performance management practices," Journal of Management & Organization, Cambridge University Press, vol. 13(3), pages 227-248, September.
    4. Thun, Jörn-Henrik & Hoenig, Daniel, 2011. "An empirical analysis of supply chain risk management in the German automotive industry," International Journal of Production Economics, Elsevier, vol. 131(1), pages 242-249, May.
    5. Hamideh Khanzadeh Charkhab & Mohammad Reza Eslami & Hassan Dehghan Dehnavi, 2014. "Linking Risk Management Practices and Strategies to Performance. Case Study: Ceramic and Tiles Industry," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 4(2), pages 413-424, April.
    6. Sime Curkovic & Thomas Scannell & Bret Wagner & Mike Vitek, 2013. "Supply Chain Risk Management within the Context of COSO¡¯s Enterprise Risk Management Framework," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 2(1), pages 15-28, April.
    7. Nina Shin & Sangwook Park, 2019. "Evidence-Based Resilience Management for Supply Chain Sustainability: An Interpretive Structural Modelling Approach," Sustainability, MDPI, vol. 11(2), pages 1-23, January.
    8. Soroush Saghafian & Mark Van Oyen, 2012. "The value of flexible backup suppliers and disruption risk information: newsvendor analysis with recourse," IISE Transactions, Taylor & Francis Journals, vol. 44(10), pages 834-867.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mahmoud Z. Mistarihi & Ghazi M. Magableh, 2023. "Unveiling Supply Chain Nervousness: A Strategic Framework for Disruption Management under Fuzzy Environment," Sustainability, MDPI, vol. 15(14), pages 1-26, July.

    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. Seyyed Mohammad Seyyed Alizadeh Ganji & Mohammad Hayati, 2016. "Identifying and Assessing the Risks in the Supply Chain," Modern Applied Science, Canadian Center of Science and Education, vol. 10(6), pages 1-74, June.
    2. Rika Ampuh Hadiguna, 2012. "Decision support framework for risk assessment of sustainable supply chain," International Journal of Logistics Economics and Globalisation, Inderscience Enterprises Ltd, vol. 4(1/2), pages 35-54.
    3. Hatem Elleuch & Wafik Hachicha & Habib Chabchoub, 2014. "A combined approach for supply chain risk management: description and application to a real hospital pharmaceutical case study," Journal of Risk Research, Taylor & Francis Journals, vol. 17(5), pages 641-663, May.
    4. Damianos P. Sakas & Ioannis Dimitrios G. Kamperos & Panagiotis Reklitis, 2021. "Estimating Risk Perception Effects on Courier Companies’ Online Customer Behavior during a Crisis, Using Crowdsourced Data," Sustainability, MDPI, vol. 13(22), pages 1-26, November.
    5. Laurent Lim, Lâm & Alpan, Gülgün & Penz, Bernard, 2014. "Reconciling sales and operations management with distant suppliers in the automotive industry: A simulation approach," International Journal of Production Economics, Elsevier, vol. 151(C), pages 20-36.
    6. Aqlan, Faisal & Lam, Sarah S., 2015. "A fuzzy-based integrated framework for supply chain risk assessment," International Journal of Production Economics, Elsevier, vol. 161(C), pages 54-63.
    7. Kauppi, Katri & Longoni, Annachiara & Caniato, Federico & Kuula, Markku, 2016. "Managing country disruption risks and improving operational performance: risk management along integrated supply chains," International Journal of Production Economics, Elsevier, vol. 182(C), pages 484-495.
    8. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    9. Sreedevi, R. & Saranga, Haritha, 2017. "Uncertainty and supply chain risk: The moderating role of supply chain flexibility in risk mitigation," International Journal of Production Economics, Elsevier, vol. 193(C), pages 332-342.
    10. Tianjian Yang & Weiguo Fan, 2016. "Information management strategies and supply chain performance under demand disruptions," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 8-27, January.
    11. Diedrich, Katharina, 2017. "Framework for digitalized proactive supply chain risk management," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Digitalization in Supply Chain Management and Logistics: Smart and Digital Solutions for an Industry 4.0 Environment. Proceedings of the Hamburg Inter, volume 23, pages 381-403, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    12. Neungho Han & Juneho Um, 2024. "Risk management strategy for supply chain sustainability and resilience capability," Risk Management, Palgrave Macmillan, vol. 26(2), pages 1-26, May.
    13. Mishra, Deepa & Sharma, R.R.K. & Kumar, Sameer & Dubey, Rameshwar, 2016. "Bridging and buffering: Strategies for mitigating supply risk and improving supply chain performance," International Journal of Production Economics, Elsevier, vol. 180(C), pages 183-197.
    14. Diedrich, Katharina & Klingebiel, Katja, 2019. "Smart risk analytics design for proactive early warning," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg Int, volume 27, pages 559-585, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    15. Shao, Xiao-Feng, 2012. "Demand-side reactive strategies for supply disruptions in a multiple-product system," International Journal of Production Economics, Elsevier, vol. 136(1), pages 241-252.
    16. Muhammad Junaid & Ye Xue & Muzzammil Wasim Syed & Ji Zu Li & Muhammad Ziaullah, 2019. "A Neutrosophic AHP and TOPSIS Framework for Supply Chain Risk Assessment in Automotive Industry of Pakistan," Sustainability, MDPI, vol. 12(1), pages 1-26, December.
    17. Ualison Rébula Oliveira & Camila Oliveira Santos & Gabriel Elias Lunz Chaves & Vicente Aprigliano Fernandes, 2022. "Analysis of the MORT method applicability for risk management in supply chains," Operations Management Research, Springer, vol. 15(3), pages 1361-1382, December.
    18. Guertler, Benjamin & Spinler, Stefan, 2015. "Supply risk interrelationships and the derivation of key supply risk indicators," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 224-236.
    19. Soumyatanu Mukherjee & Sidhartha S. Padhi, 2022. "Sourcing decision under interconnected risks: an application of mean–variance preferences approach," Annals of Operations Research, Springer, vol. 313(2), pages 1243-1268, June.
    20. Chih-Hung Hsu & Ru-Yue Yu & An-Yuan Chang & Wan-Ling Liu & An-Ching Sun, 2022. "Applying Integrated QFD-MCDM Approach to Strengthen Supply Chain Agility for Mitigating Sustainable Risks," Mathematics, MDPI, vol. 10(4), pages 1-41, February.

    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:jjrfmx:v:16:y:2023:i:4:p:242-:d:1124548. 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.