IDEAS home Printed from https://ideas.repec.org/a/ids/ijlsma/v32y2019i2p245-271.html
   My bibliography  Save this article

Managing risks and system performance in supply network: a conceptual framework

Author

Listed:
  • Huy Truong Quang
  • Yoshinori Hara

Abstract

Examining a certain risk will provide an insight into a single dimension, but a picture of different risks in the supply chain (SC) is still lacking, as risks do not take place independently, but typically simultaneously. This research aims to propose and validate a conceptual framework for linking various dimensions of risk to system performance in the SC by applying SC mapping - a new approach in the SC risk body of literature. In the model, risks were classified into three categories with regard to their level of impact on performance: 1) core risks, e.g., supply risk, investor-related operational risks, contractor-related operational risks and demand risks; 2) infrastructure risks, e.g., finance risk, information risk and time risk; 3) external risks, e.g., human-made risks; 4) natural risks. Using the framework, companies will have a systematic view of risks in the whole SC network whereby they can define risks in their own context and ascertain critical SC risks that cause negative effects on SC performance.

Suggested Citation

  • Huy Truong Quang & Yoshinori Hara, 2019. "Managing risks and system performance in supply network: a conceptual framework," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 32(2), pages 245-271.
  • Handle: RePEc:ids:ijlsma:v:32:y:2019:i:2:p:245-271
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=97586
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Z. Jemai & F. Karaesmen, 2005. "The influence of demand variability on the performance of a make-to-stock queue," Post-Print hal-00126137, HAL.
    2. 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.
    3. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2016. "Accuracy of mortgage portfolio risk forecasts during financial crises," European Journal of Operational Research, Elsevier, vol. 249(2), pages 440-456.
    4. Kandil, Magda & Mirazaie, Ida, 2004. "The Effects of Exchange Rate Fluctuations on Output and Prices: Evidence from Developing Countries," Journal of Developing Areas, Tennessee State University, College of Business, vol. 38(2), pages 189-219, January-M.
    5. Ajay Kumar Pandey & Rajiv Kumar Sharma, 2017. "FMEA-based interpretive structural modelling approach to model automotive supply chain risk," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 27(4), pages 395-419.
    6. Fleischhacker, Adam J. & Fok, Pak-Wing, 2015. "On the relationship between entropy, demand uncertainty, and expected loss," European Journal of Operational Research, Elsevier, vol. 245(2), pages 623-628.
    7. Bernanke, Ben S, 1981. "Bankruptcy, Liquidity, and Recession," American Economic Review, American Economic Association, vol. 71(2), pages 155-159, May.
    8. Girish K. Nair & Nidhi Choudhary, 2016. "Influence of critical success factors of total quality management on financial and non-financial performance of hospitality industry: an empirical study," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 17(4), pages 409-436.
    9. Xu, Minghui & Chen, Youhua (Frank) & Xu, Xiaolin, 2010. "The effect of demand uncertainty in a price-setting newsvendor model," European Journal of Operational Research, Elsevier, vol. 207(2), pages 946-957, December.
    10. Axel Dreher & Martin Gassebner, 2013. "Greasing the wheels? The impact of regulations and corruption on firm entry," Public Choice, Springer, vol. 155(3), pages 413-432, June.
    11. Jemai, Zied & Karaesmen, Fikri, 2005. "The influence of demand variability on the performance of a make-to-stock queue," European Journal of Operational Research, Elsevier, vol. 164(1), pages 195-205, July.
    12. DonHee Lee & Byeonghwa Park, 2016. "Impact of manufacturing systems on quality management practices, competitive advantages, and operational performance," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 19(3), pages 301-318.
    13. Ackermann, Fran & Howick, Susan & Quigley, John & Walls, Lesley & Houghton, Tom, 2014. "Systemic risk elicitation: Using causal maps to engage stakeholders and build a comprehensive view of risks," European Journal of Operational Research, Elsevier, vol. 238(1), pages 290-299.
    14. William Ho & Tian Zheng & Hakan Yildiz & Srinivas Talluri, 2015. "Supply chain risk management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 53(16), pages 5031-5069, August.
    15. AfDB AfDB, . "Annual Report 2012," Annual Report, African Development Bank, number 461.
    16. Mitra, Sovan & Date, Paresh & Mamon, Rogemar & Wang, I-Chieh, 2013. "Pricing and risk management of interest rate swaps," European Journal of Operational Research, Elsevier, vol. 228(1), pages 102-111.
    17. Parks, Richard W, 1978. "Inflation and Relative Price Variability," Journal of Political Economy, University of Chicago Press, vol. 86(1), pages 79-95, February.
    18. Ali Haj Aghapour & Govindan Marthandan & David Yong Gun Fie & Suhaiza Zailani, 2017. "Risk management process towards operation performance in supply chain management: a survey of manufacturing SMEs," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 27(1), pages 78-114.
    19. Hau L. Lee & Corey Billington, 1993. "Material Management in Decentralized Supply Chains," Operations Research, INFORMS, vol. 41(5), pages 835-847, October.
    20. Kim, Kwansoo & Chavas, Jean-Paul, 2003. "Technological change and risk management: an application to the economics of corn production," Agricultural Economics, Blackwell, vol. 29(2), pages 125-142, October.
    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. Fleischhacker, Adam J. & Fok, Pak-Wing, 2015. "On the relationship between entropy, demand uncertainty, and expected loss," European Journal of Operational Research, Elsevier, vol. 245(2), pages 623-628.
    2. Qazi, Abroon & Dickson, Alex & Quigley, John & Gaudenzi, Barbara, 2018. "Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 196(C), pages 24-42.
    3. Silvia Carpitella & Ilyas Mzougui & Joaquín Izquierdo, 2022. "Multi-criteria risk classification to enhance complex supply networks performance," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 769-785, September.
    4. Ewing, Bradley T. & Thompson, Mark A., 2008. "Industrial production, volatility, and the supply chain," International Journal of Production Economics, Elsevier, vol. 115(2), pages 553-558, October.
    5. Noblesse, Ann M. & Boute, Robert N. & Lambrecht, Marc R. & Van Houdt, Benny, 2014. "Lot sizing and lead time decisions in production/inventory systems," International Journal of Production Economics, Elsevier, vol. 155(C), pages 351-360.
    6. Jamshed Raza & Yuxin Liu & Jianwei Zhang & Nan Zhu & Zohaib Hassan & Habib Gul & Sikander Hussain, 2021. "Sustainable Supply Management Practices and Sustainability Performance: The Dynamic Capability Perspective," SAGE Open, , vol. 11(1), pages 21582440211, March.
    7. Nishat Alam Choudhary & Shalabh Singh & Tobias Schoenherr & M. Ramkumar, 2023. "Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications," Annals of Operations Research, Springer, vol. 322(2), pages 565-607, March.
    8. Amirmohsen Golmohammadi & Alireza Tajbakhsh & Mohamed Dia & Pawoumodom M. Takouda, 2022. "Effect of timing on reliability improvement and ordering decisions in a decentralized assembly system," Annals of Operations Research, Springer, vol. 312(1), pages 159-192, May.
    9. Margolis, Joshua T. & Sullivan, Kelly M. & Mason, Scott J. & Magagnotti, Mariah, 2018. "A multi-objective optimization model for designing resilient supply chain networks," International Journal of Production Economics, Elsevier, vol. 204(C), pages 174-185.
    10. Awi Federgruen & Min Wang, 2013. "Monotonicity properties of a class of stochastic inventory systems," Annals of Operations Research, Springer, vol. 208(1), pages 155-186, September.
    11. Robert N. Boute & Marc R. Lambrecht & Benny Van Houdt, 2007. "Performance evaluation of a production/inventory system with periodic review and endogenous lead times," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(4), pages 462-473, June.
    12. Cheung, Ki Ling & Song, Jing-Sheng & Zhang, Yue, 2017. "Cost reduction through operations reversal," European Journal of Operational Research, Elsevier, vol. 259(1), pages 100-112.
    13. 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.
    14. Rožāns Edgars, 2016. "The Benchmarking Practices of the Economically Freest Countries in Europe and the World," Ekonomika (Economics), Sciendo, vol. 95(2), pages 73-97, February.
    15. ur Rehman, Attique & Shakeel Sadiq Jajja, Muhammad & Farooq, Sami, 2022. "Manufacturing planning and control driven supply chain risk management: A dynamic capability perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    16. 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.
    17. 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.
    18. Apurva Jain, 2006. "Priority and dynamic scheduling in a make‐to‐stock queue with hyperexponential demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(5), pages 363-382, August.
    19. Shuting Li & Xiangfeng Chen, 2019. "The role of supplier collaboration and risk management capabilities in managing product complexity," Operations Management Research, Springer, vol. 12(3), pages 146-158, December.
    20. Sanajian, Nima & BalcIog[small tilde]lu, BarIs, 2009. "The impact of production time variability on make-to-stock queue performance," European Journal of Operational Research, Elsevier, vol. 194(3), pages 847-855, May.

    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:ids:ijlsma:v:32:y:2019:i:2:p:245-271. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=134 .

    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.