The increasing complexity of multinational supply networks has generated a new issue (supplychain uncertainty) for today's managers. This article surveys the existing literature on the topic of supply chain uncertainty and establishes the theoretical framework for future study in this area (in addition to supply chain risk). This literature study identifies fourteen potential causes of uncertainty, including both well-studied phenomena like the bullwhip effect and less well-known ones like parallel interaction. Ten solutions try to eliminate the core source of uncertainty, while eleven others aim to adapt to the existence of these unknowns in order to reduce their effects on manufacturing performance. The theory of manufacturing strategy and core concept of contingency and alignment establish a foundation of the supply chain uncertainty framework that is thus establishment using the research findings. More future empirical study is required to discover which uncertainty exists in distinct industrial settings, the effect of suitable sources and management strategies on productivity, and the intricate interaction between management techniques and diverse uncertainty sources.
S. Guo, X. Sun, and H. K. S. Lam, “Applications of blockchain technology in sustainable fashion supply chains: Operational transparency and
environmental efforts,” IEEE Trans. Eng. Manage., pp. 1–17, 2022.
S. Sharma and K. S. Lote, “Understanding demand volatility in supply chains through the vibrations analogy—the onion supply case,” Logist. Res., vol. 6, no. 1, pp. 3–15, 2013.
R. A. Inman and K. W. Green, “Environmental uncertainty and supply chain performance: the effect of agility,” J. Manuf. Technol. Manag., vol. 33, no. 2, pp. 239–258, 2022.
J. H. Cohen, “Textile production in rural Oaxaca, Mexico: The complexities of the global market for handmade crafts,” in Artisans and Cooperatives, University of Arizona Press, 2022, pp. 129–142.
“Mechanism of strategic management of the country’s Socio-economic system by risk-management methods,” Vestn. Permsk. nac. issledovatel’skogopoliteh. univ. Soc.-èkon. nauki, no. 4, 2020.
S. W. Forbes, “Capital gains, losses, and financial results in the nonlife insurance industry: Author’s reply,” J. Risk Insur., vol. 44, no. 4, p. 707, 1977.
P. Suryawanshi and P. Dutta, “Optimization models for supply chains under risk, uncertainty, and resilience: A state-of-the-art review and future research directions,” Transp. Res. Part E: Logist. Trans. Rev., vol. 157, no. 102553, p. 102553, 2022.
I. M. A. L. Shaar, S. Khattab, R. Alkaied, and L. Al-Abbadi, “Supply chain integration and green innovation, the role of environmental uncertainty: Evidence from Jordan,” Uncertain Supply Chain Manag., vol. 10, no. 3, pp. 657–666, 2022.
R. Atkins, A. Sener, M. Drake, and K. Marley, “Predictors of burnout among supply chain management professionals,” Int. J. Value Chain Manag., vol. 14, no. 1, p. 1, 2023.
D. Kinet, “Giovanni Garbini, History and Ideology in Ancient Israel (Storia e Ideologianell’Israele Antico, Brescia 1986), SCM Press, London 1988, xvi-222 S., £ 10,50,” Biblische Z., vol. 35, no. 1, pp. 115–116, 1991.
N. S. Kwong, K. S. Jaiswal, J. W. Baker, N. Luco, K. A. Ludwig, and V. J. Stephens, “Earthquake risk of gas pipelines in the conterminous United States and its sources of uncertainty,” ASCE ASME J. Risk Uncertain. Eng. Syst. A Civ. Eng., vol. 8, no. 1, 2022.
K. Elango, A. Prakash, and L. Umasankar, “Multiobjective optimization model for renewable energy sources and load demands uncertainty consideration for optimal design of hybrid combined cooling, heating, and power systems,” Int. J. Energy Res., vol. 46, no. 6, pp. 7840–7860, 2022.
M. Wen, Z. Qin, and R. Kang, “The $$\alpha $$ α -cost minimization model for capacitated facility location-allocation problem with uncertain demands,” Fuzzy Optim. Decis. Mak., vol. 13, no. 3, pp. 345–356, 2014.
J. Januardi and E. Widodo, “Response surface methodology of dual-channel green supply-chain pricing model by considering uncertainty,” Supply Chain Forum Int. J., vol. 22, no. 1, pp. 16–27, 2021.
A. E. Aladejare and Y. Wang, “Sources of uncertainty in site characterization and their impact on geotechnical reliability-based design,” ASCE ASME J. Risk Uncertain. Eng. Syst. A Civ. Eng., vol. 3, no. 4, p. 04017024, 2017.
J. Aitken, P. Childerhouse, E. Deakins, and D. Towill, “A comparative study of manufacturing and service sector supply chain integration via the uncertainty circle model,” Int. J. Logist. Manag., vol. 27, no. 1, pp. 188–205, 2016.
R. Wilding, “The supply chain complexity triangle: Uncertainty generation in the supply chain,” Int. j. phys. distrib. logist. manag., vol. 28, no. 8, pp. 599–616, 1998.
V. Neiger and C. Pernet, “Deterministic computation of the characteristic polynomial in the time of matrix multiplication,” J. Complex., vol. 67, no. 101572, p. 101572, 2021.
N. K. Rajagopal et al., “Future of business culture: An artificial intelligence-driven digital framework for organization decision-making process,” Complexity, vol. 2022, pp. 1–14, 2022.
C. C. Binder, “Consumer inflation uncertainty and the macroeconomy: Evidence from a new micro-level measure,” SSRN Electron. J., 2015.
Q. Tian and W. Guo, “Reconfiguration of manufacturing supply chains considering outsourcing decisions and supply chain risks,” J. Manuf. Syst., vol. 52, pp. 217–226, 2019.
L. Li, H. Liao, J. Zhou, and Y. Wang, “Sustainability and optimization methods under uncertainties in closed-loop supply chain,” Comput. Ind. Eng., vol. 171, no. 108396, p. 108396, 2022.
C. P. Nguyen and C. Schinckus, “How do countries deal with global uncertainty? Domestic ability to absorb shock through the lens of the economic complexity and export diversification,” Qual. Quant., 2022.
M. M. Vali-Siar, E. Roghanian, and A. Jabbarzadeh, “Resilient mixed open and closed-loop supply chain network design under operational and disruption risks considering competition: A case study,” Comput. Ind. Eng., vol. 172, no. 108513, p. 108513, 2022.
D. W. Moore, B. Ruffle, A. McQueen, S. Thakali, and D. Edwards, “Frameworks for screening and risk management of chemicals and advanced materials: A critical review,” Integr. Environ. Assess. Manag., 2022.
D. Liu, M. Jaramillo, and D. Vincenzi, “The effects of system reliability and task uncertainty on autonomous unmanned aerial vehicle operator performance under high time pressure: Reliability and task uncertainty on UAV,” Hum. Factors Ergon. Manuf., vol. 25, no. 5, pp. 515–522, 2015.
T. T. Le, T. M. A. Nguyen, V. Q. Do, and T. H. C. Ngo, “Risk-based approach and quality of independent audit using structure equation modeling – Evidence from Vietnam,” Eur. res. manag. bus. econ., vol. 28, no. 3, p. 100196, 2022.
O. Ganbold, A. M. Rose, J. M. Rose, and K. Rotaru, “Increasing reliance on financial advice with avatars: The effects of competence and complexity on algorithm aversion,” J. Inf. Syst., vol. 36, no. 1, pp. 7–17, 2022.
S. Akashi and Y. Tong, “A vulnerability of dynamic network address translation to denial-of-service attacks,” in 2021 4th International Conference on Data Science and Information Technology, 2021.
J. Yang, Y. Liu, and Y. Jia, “Influence of trust relationships with suppliers on manufacturer resilience in COVID-19 era,” Sustainability, vol. 14, no. 15, p. 9235, 2022.
W. Zhao, Y. Yang, L. Xing, C. F. Chuang, and E. Schüler, “Mitigating the uncertainty in small field dosimetry by leveraging machine learning strategies,” Phys. Med. Biol., vol. 67, no. 15, p. 155019, 2022.
J.-Y. Lai, J. Wang, and Y.-H. Chiu, “Evaluating blockchain technology for reducing supply chain risks,” Inf. syst. e-bus. manag., vol. 19, no. 4, pp. 1089–1111, 2021.
A. Oyedijo, A. S. Francois Koukpaki, S. Kusi-Sarpong, F. Alfarsi, and Y. Yang, “Restraining forces and drivers of supply chain collaboration: evidence from an emerging market,” Supply Chain Manage.: Int. J., vol. 27, no. 3, pp. 409–430, 2022.
D. DelliGatti and E. Grugni, “Breaking bad: Supply chain disruptions in a streamlined agent based model,” SSRN Electron. J., 2021.
P. Valera, N. Feliu, and I. Lansberg, “Fit for the future? The cultural DNA of Spanish and Latin American family businesses,” Eur. J. Fam. Bus., vol. 11, no. 1, 2021.
E. S. Palkina, “Model for making decisions on renewal the railway rolling stock of a transport organization,” Transp. Syst. Technol., vol. 6, no. 3, pp. 76–87, 2020.
I. H. S. Sufyati, A. D. Suganda, S. Shafenti, and M. Fahlevi, “Supply chain management, supply chain flexibility and firm performance: an empirical investigation of agriculture companies in Indonesia,” Uncertain Supply Chain Manag., vol. 10, no. 1, pp. 155–160, 2022.
R. A. Richardson and M. Q. Patton, “Leadership‐evaluation partnership: Infusing systems principles and complexity concepts for a transformational alliance,” New Dir. Eval., vol. 2021, no. 170, pp. 139–147, 2021.
A. Tuni, A. Rentizelas, and A. Duffy, “Environmental performance measurement for green supply chains: A systematic analysis and review of quantitative methods,” Int. j. phys. distrib. logist. manag., vol. 48, no. 8, pp. 765–793, 2018.
J. W. M. Bertrand, “Quantitative methods in supply chain management, models and algorithms, by Ioannis T. Christou,” Prod. Plan. Control, vol. 25, no. 6, pp. 511–512, 2014.
B. Tundys, “Use of quantitative and qualitative methods for modelling green supply chains,” Oper. Supply Chain Manag. Int. J., pp. 82–97, 2018.
K. Kara and S. Edinsel, “The mediating role of green product innovation (GPI) between green human resources management (GHRM) and green supply chain management (GSCM): evidence from automotive industry companies in Turkey,” Supply Chain Forum Int. J., pp. 1–22, 2022.
E. Kachanova, Russian Presidential Academy of National Economy and Public Administration, A. Kinash, and Russian Presidential Academy of National Economy and Public Administration, “The approaches to assessing the feasibility of Bank rehabilitation: problems and development directions,” Ptpmag, no. 12, pp. 117–142, 2020.
M. Halac, “Commitment vs. Flexibility with costly verification,” SSRN Electron. J., 2016.
G. Ofori, Z. Zhang, and F. Y. Y. Ling, “Initiatives that enable Singapore contractors to improve construction productivity,” Built Environ. Proj. Asset Manag., vol. 11, no. 5, pp. 785–803, 2021.
L. Raymond and F. Bergeron, “Enabling the business strategy of SMEs through e‐business capabilities: A strategic alignment perspective,” Ind. manag. data syst., vol. 108, no. 5, pp. 577–595, 2008.
A. L. Steinbach, T. R. Holcomb, R. M. Holmes Jr, C. E. Devers, and A. A. Cannella Jr, “Top management team incentive heterogeneity, strategic investment behavior, and performance: A contingency theory of incentive alignment: A Contingency Theory of Incentive Alignment,” Strategic Manage. J., vol. 38, no. 8, pp. 1701–1720, 2017.
A. Chakraborty, A. Vashishth, T. Lyambo, and M. Mutingi, “Perceived performance of gasoline supply chains: Empirical evidences from Namibia,” Global Bus. Rev., p. 097215092210834, 2022.
S. DuHadway, S. Carnovale, and B. Hazen, “Understanding risk management for intentional supply chain disruptions: risk detection, risk mitigation, and risk recovery,” Ann. Oper. Res., vol. 283, no. 1–2, pp. 179–198, 2019.
A. Derdar et al., “Photovoltaic energy generation systems monitoring and performance optimization using wireless sensors network and metaheuristics,” Sustain. Comput. Inform. Syst., vol. 35, no. 100684, p. 100684, 2022.
Z. Soraya, W. Warda, A. N. Fitrianti, R. Sulistiyanti, and A. A. Adiningrat, “Strategy analysis of sustainability of small and medium enterprises (MSMEs) in increasing productivity and profit in the middle of Covid-19 pandemic,” JURNAL MANAJEMEN BISNIS, vol. 9, no. 1, pp. 143–154, 2022.
M. Bouchard, S. D’Amours, M. Rönnqvist, R. Azouzi, and E. Gunn, “Integrated optimization of strategic and tactical planning decisions in forestry,” Eur. J. Oper. Res., vol. 259, no. 3, pp. 1132–1143, 2017.
R. E. Brimelow, A. Amalathas, E. Beattie, G. Byrne, and N. N. Dissanayaka, “The use of balanced scorecards in mental health services: An integrative review and thematic analysis,” J. Behav. Health Serv. Res., 2022.
K. T. Kitchin, J. L. Brown, and A. P. Kulkarni, “Predictive assay for rodent carcinogenicity using in vivo biochemical parameters: operational characteristics and complementarity,” Mutat. Res., vol. 266, no. 2, pp. 253–272, 1992.
B.-Z. Zilberfarb, “Interest rates, the liquidity effect, inflation uncertainty and supply shocks: Empirical evidence from a high inflation economy,” Financ. Rev., vol. 22, no. 3, pp. 122–122, 1987.
K. Roushangar, R. Ghasempour, and F. Alizadeh, “Uncertainty assessment of the integrated hybrid data processing techniques for short to long term drought forecasting in different climate regions,” Water Resour. Manage., vol. 36, no. 1, pp. 273–296, 2022.
We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.
No funding was received to assist with the preparation of this manuscript.
Conflict of interest
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Availability of data and materials
No data available for above study.
All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.
Jaime Georges Rouma
Jaime Georges Rouma
Universidad Catolica Boliviana, Esquina, La Paz, Bolivia.
Open Access This article is licensed under a Creative Commons Attribution NoDerivs is a more restrictive license. It allows you to redistribute the material commercially or non-commercially but the user cannot make any changes whatsoever to the original, i.e. no derivatives of the original work. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
Cite this article
Jaime Georges Rouma, “Theoretical Framework of Supply Chain Uncertainties”, Journal of Enterprise and Business Intelligence, vol.2, no.3, pp.153-164, July 2022. doi: 10.53759/5181/JEBI202202016.