Sources of Supply Chain Volatility: A Literature Review

Authors

  • Anguzu Ronald Maseno University
  • Aila Fredrick Maseno University

DOI:

https://doi.org/10.47604/ijscm.2370
Abstract views: 79
PDF downloads: 57

Keywords:

Supply Chain, Volatility, Systematic Review

Abstract

Purpose: The purpose of this study was to identify the main source of supply chain volatility based on empirical literature, addressing the gap in existing research where consensus on this matter has been lacking.

Methodology: Employing an interpretivist approach, this study utilized a bibliographic and qualitative research method. The researchers systematically reviewed literature from top publishing sites and journals, focusing on titles and abstracts containing the keyword 'supply chain volatility' spanning from 2013 to 2023. Through this process, a taxonomy of 15 articles was developed to synthesize existing knowledge on the subject.

Findings: The results of the study indicate that demand variability emerges as the primary source of supply chain volatility, with 60% of the analyzed articles highlighting its significance. This finding underscores the critical role of demand fluctuations in driving supply chain disruptions and challenges.

Unique Contribution to Theory, Practice and Policy: This study makes a unique contribution to existing literature by providing empirical evidence and consensus on the main source of supply chain volatility. By synthesizing and categorizing findings from diverse sources, it advances theoretical understanding of the factors underlying supply chain disruptions. The identification of demand variability as the primary source of supply chain volatility offers valuable insights for practitioners seeking to enhance supply chain resilience and mitigate disruptions. Understanding the central role of demand dynamics can inform strategic decision-making and risk management practices within organizations. The findings of this study have implications for policy-makers involved in shaping regulatory frameworks and industry standards related to supply chain management. By recognizing demand variability as a key driver of volatility, policymakers can tailor interventions and incentives to promote stability and efficiency in supply chains.

Downloads

Download data is not yet available.

References

Abolghasemi, M. Beh, E., Tarr, G. & Gerlach, R. (2020). Demand forecasting in supply chain: the impact of demand volatility in the presence of promotion. Comput. Ind. Eng. Vol (142)

Alharahsheh, H. H., & Pius, A. (2020). A review of key paradigms: Positivism VS interpretivism. Global Academic Journal of Humanities and Social Sciences, 2(3), 39-43

Assefa, T.T., Meuwissen, M.P., & Lansink, A.O. (2015). Price Volatility Transmission in Food Supply Chains: A Literature Review. Agribusiness, 31, 3-13.

Basole, R. C., Bellamy, M. A., Park, H. & Putrevu, J. (2016). Computational analysis and visualization of global supply network risks, IEEE Transactions on Industrial Informatics, Vol. 12, No. 3, pp. 1206–1213.

Briano, E., Caballini, C., & Revetria, R. (2009). Literature review about supply chain vulnerability and resiliency.

Calvo, J.C., Olmo, J.L., & Berlanga, V. (2020). Supply chain resilience and agility: a theoretical literature review. International Journal of Supply Chain and Operations Resilience.

Christopher, M., & Holweg, M. (2017). Supply chain 2.0 revisited: a framework for managing volatility-induced risk in the supply chain. International Journal of Physical Distribution & Logistics Management, 47(1), 2-17.

Craighead, C. W., Ketchen Jr, D. J., & Darby, J. L. (2020). Pandemics and supply chain management research: toward a theoretical toolbox. Decision Sciences, 51(4), 838-866

Ding, S., Cui, T., Wu, X., & Du, M. (2022). Supply chain management based on volatility clustering: The effect of CBDC volatility. Research in International Business and Finance, 62, 101690.

Gaudenzi, B., Zsidisin, G.A. and Pellegrino, R. (2020), "Measuring the financial effects of mitigating commodity price volatility in supply chains", Supply Chain Management, Vol. 26 No. 1, pp. 17-31. https://doi.org/10.1108/SCM-02-2020-0047

Hernes, M., & Sobieska-Karpińska, J. (2019). Reduction of a Forrester effect in a supply chain management system. Journal of Intelligent & Fuzzy Systems, 37(6), 7325-7335

Hu, G. et al. (2019) ‘Potentials of GHG emission reductions from cold chain systems: Case studies of China and the United States’, Journal of Cleaner Production. Elsevier, 239, p. 118053. doi: 10.1016/J.JCLEPRO.2019.118053.

Humair, s, John D. R., Brian T. & Sean P. W. (2013). Incorporating Stochastic Lead Times Into the Guaranteed Service Model of Safety Stock Optimization, Interfaces, 43, (5), 421-434

Juttner, U., Peck, H. & Christopher, M. (2003). Supply chain risk management: Outlining an agenda for future research, International Journal of Logistics: Research & Applications, Vol. 6, No. 4, pp. 197–210

Kazaz, B. (2014). 1> 2? Less is more under volatile exchange rates in global supply chains. Business Horizons, 57(4), 521-531.

Koberg, E., & Longoni, A. (2019). A systematic review of sustainable supply chain management in global supply chains. Journal of cleaner production, 207, 1084-1098.

Nitsche, B., & Durach, C. F. (2018). Much discussed, little conceptualized: supply chain volatility. International Journal of Physical Distribution & Logistics Management, 48(8), 866-886.

Nitsche, B., & Straube, F. (2020). Efficiently managing supply chain volatility–a management framework for the manufacturing industry. Procedia Manufacturing, 43, 320-327.

Nitsche, B., Straube, F., & Verhoeven, P. (2019). Assessing the current state of supply chain volatility: development of a benchmarking instrument. Production, 29

Olson, D. L. & Wu, D. (2011). Risk management models for supply chain: A scenario analysis of outsourcing to China, Supply Chain Management: An International Journal, Vol. 16, No. 6, pp. 401–408

Radhakrishnan, S., Harris, B.A., & Kamarthi, S.V. (2018). Supply Chain Resiliency: A Review.

Ravindran, A. R. & Warsing, D. P. (2013). Supply Chain Engineering: Models and Applications, CRC Press Taylor & Francis Group

Shahbaz, M. S., Chandio, A. F. Oad, M., Ahmed, A. & Ullah, R. (2018). Stakeholders’ management approaches in construction supply chain: A new perspective of Stakeholder’s theory, International Journal of Sustainable Construction Engineering & Technology, Vol. 9, No. 2, pp.16–26

Shahbaz, Sohu, Khaskhelly, Bano and Soomro, 2019). A Novel Classification of Supply Chain Risks A Review. Engineering, Technology & Applied Science Research Vol. 9, No. 3, 2019, 4301-430

Stadtler, H. (2015). Supply chain management: An overview. Supply chain management and advanced planning: Concepts, models, software, and case studies, 3-28

Van der Walt, J. L. (2020). Interpretivism-constructivism as a research method in the humanities and social sciences-more to it than meets the eye. International Journal of Philosophy and Theology, 8(1), 59-68

Wagner, S. M. Bode, C. (2008). An empirical examination of supply chain performance along several dimensions of risk, Journal of Business Logistics, Vol. 29, No. 1, pp. 307–325

Yang, Y., Lin, J., Liu, G., & Zhou, L. (2021). The behavioural causes of bullwhip effect in supply chains: A systematic literature review. International Journal of Production Economics, 236, 108120

Zekhnini, K., Cherrafi, A., Bouhaddou, I., Benghabrit, Y., & Garza-Reyes, J. A. (2021). Supply chain management 4.0: a literature review and research framework. Benchmarking: An International Journal, 28(2), 465-501

Zhao, G., Liu, S. & Lopez, C. (2017). A literature review on risk sources and resilience factors in agri-food supply chains. http://hdl.handle.net/10026.1/10208

Downloads

Published

2024-02-28

How to Cite

Anguzu, R., & Aila, F. (2024). Sources of Supply Chain Volatility: A Literature Review. International Journal of Supply Chain Management, 9(2), 20–36. https://doi.org/10.47604/ijscm.2370

Issue

Section

Articles