Digital World

Managing Supply Chains in an Uncertain World: Challenges and Solutions

Call for papers for: Modern Supply Chain Research and Applications

Managing Supply Chains in an Uncertain World: Challenges and Solutions

 

The businesses and their supply chains were still struggling with the uncertainties that stemmed from the Trade War between the U.S. and China, the world’s largest economies, when another storm hit them in the form of COVID-19 pandemic. The pandemic emerged as a healthcare crisis, but soon it was identified as a cause of supply chain crises at a scale and scope that is unprecedented. Its impact has been felt not only on the supply of healthcare products but also of food, cleaning products, and countless other products and services. Consequently, many businesses are facing existential threats and scrambling to survive in the short term (Wuest et al., 2020). This mega-crisis would be gone sooner or later, but it would leave behind a new world. It would be a world where not only the fear of new exogenous shocks would be real, but the brawl between globalization and trade protectionism is likely to give rise to new forms of business relationships and supply chain disruptions. For example, when the U.S. sanctions on Huawei prevented it from using American chips, the company accelerated the development of its own chips and emerged stronger by improving relations with local suppliers and partners. Recently, as the European Union imposed a ban on Pakistan International Airlines, the company announced a ‘historic reduction in fares’ to offset the damage through increased domestic operations. When the U.S. sanctioned the Nord Stream 2 pipeline project, a multinational gas pipeline to connect Russian supplies to European consumers via Germany, it was enough to scare away Swiss pipelaying firm Allseas Group SA and promoting speculations about project delays. It is evident that different companies respond to supply chain disruptions and uncertainty in different ways in light of their own strengths and limitations. Considering the uncertainty and unpredictability surrounding the business environment of today, studying the factors, both natural and human-made, which can contribute to supply chain uncertainty and disruptions, is an important endeavor with both short-term and long-term implications for suppliers and consumers.  

Because of the lockdown of China, the “world’s factory,” in the first half of 2020, the business experts and consultants started debating the significance of multi-sourcing to make the global supply chain more resilient and flexible (Linton & Vakil, 2020). At the same time, digitalization, which was traditionally viewed as a mean to achieve efficiency, has now been reimagined as a mean to achieve resilience and sustainability for businesses and their suppliers. In these uncertain times, different businesses are likely to respond differently. For example, the lowering oil prices forced countries to cut their oil production, but on the other hand, it was good news for the emerging markets like India and China and other oil-importing countries, who could now get oil at lower prices. As the consumer started moving towards online shopping, the digital giants like Alibaba and Amazon started growing while the traditional suppliers and retailers are experiencing a supply chain crisis (Reeves et al., 2020).

It has become evident that uncertainties are hitting the businesses unevenly. The businesses and supply chains that are most sensitive to market changes and disruption are better equipped to absorb the supply chain uncertainties and resultant impacts. Other than unexpected exogenous factors, the human-made factors like trade-wars, trade protectionism (and assaults on multilateralism), economic sanctions, and political instabilities have also played an important role in aggravating the uncertainties in the business world, and supply chains in different regions have been adversely affected. Interruptions caused by variations in supply and demand can also be added to the list (Jabbarzadeh et al., 2016). Further, globalization and outsourcing trends can also make supply chains more sensitive to disruptions and uncertainties (Ivanov, 2018).

There are multiple sources of uncertainty in supply chain systems, and without handling them, optimization of supply chain operations can face setbacks (Li & Liu, 2013). Thus, how to manage supply chains optimally is an essential question of modern times. As the world is going through unprecedented changes, understanding the sensitivity of supply chains to real-world uncertainties is of crucial importance, and any delay in dealing with them can only amount to financial losses, which would only aggravate if managers failed to timely and effectively incorporate the changes taking place around businesses, their suppliers and their customers.

Supply chain (SC) uncertainty is an issue with which every manager struggles, stemming from the increasing complexity of global supply networks (Simangunsong et al., 2012). There are different uncertainty approaches to deal with supply chain uncertainty, e.g., stochastic methods, interval methods, fuzzy set theory, grey system theory, rough-set theory, among others (Peng et al., 2020; Diba & Xie, 2019; Park, 2017; Bai & Sarkis, 2010; Xu et al., 2009). There is a dire need to execute a systematic assessment of uncertainty factors, methodologies, and solutions. The frequency and severity of different types of uncertainties are different. They may affect supply chains in different ways and may require different response strategies. For instance, some approaches seek to reduce SC uncertainty at its source while others seek to cope with it to minimize its impact on SC performance (Simangunsong et al., 2012).

 

Even though some scholars use SC risk and SC uncertainty interchangeably, one can argue that the term ‘supply-chain uncertainty’ is broader, and can be used to cover issues that have at times only been discussed under SC risks (Simangunsong et al., 2012). The current Special Issue takes a broader look at supply chain uncertainty (incorporating supply chain risks) and seeks to advance the knowledge about the impact of multiple sources of uncertainties on supply chains, especially to prepare better supply chain managers and the policymakers for the unexpected exogenous disruptions in future, and to better illuminate the role of data-driven technologies in mitigation of risks, disruptions, and uncertainties associated with supply chain across different industries.

 

The Special Issue welcomes submissions focusing on different types of uncertainties and risks, which may affect supply chains in different ways and may require different response strategies and techniques. We invite authors from academia and industry to contribute. Your submission should be within the scope of the journal and aligned with the objectives of the Special Issue.

Topics include but are not limited to:

  • The role of different uncertainty methodologies (e.g., fuzzy set theory, grey system theory, rough set theory, stochastic methods, etc.) in improving the management of supply chain under uncertainty (and risks)
  • How to deal with uncertainties, rather than simply recognizing the sources of uncertainty
  • Exploring the characteristics of the uncertain world in which businesses and their suppliers and customers operate
  • Exploring best practices in managing supply chain risks and uncertainty
  • The changing landscapes of supply chain and logistics as new disruptions and sources of uncertainty are emerging.
  • Antecedents, precedents, barriers, and drivers of uncertainty (and risk) in supply chains
  • Role of data-driven decision-making and forecasting methodologies and technologies in overwhelming supply chain uncertainty and risks
  • Business opportunities untapped in new supply chain uncertainties and complexities
  • Achieving resilience and sustainability through mitigation of supply chain uncertainties (and risks)

 

Important Dates:

Submission due by: October 30, 2020

First notification to authors: December 30, 2020

Final version due by: January 30, 2021

Final decision notification: February 30, 2021

Publication: Online after acceptance

 

Guest Editors:

Dr. Saad Ahmed Javed (Leading Guest Editor),

School of Business, Nanjing University of Information Science and Technology, P. R. China.

Email: [email protected]

 

Dr. Mostafa Salari

Department of Civil Engineering, University of Calgary, Canada

Email: [email protected]

 

Dr. Seyed Farid Ghannadpour,

Department of Industrial Engineering, Iran University of Science and Technology, Iran.

Email: [email protected]

 

Amin Mahmoudi,

School of Civil Engineering, Southeast University, P. R. China.

Email: [email protected]

 

References:

Bai, C., & Sarkis, J. (2010). Green supplier development: analytical evaluation using rough set theory. Journal of Cleaner Production18(12), 1200–1210.

Diba, S., & Xie, N. (2019). Sustainable supplier selection for Satrec Vitalait Milk Company in Senegal using the novel grey relational analysis method. Grey Systems: Theory and Application9(3), 262–294.

Ivanov, D. (2018). Structural Dynamics and Resilience in Supply Chain Risk Management. Springer.

Jabbarzadeh, A., Fahimnia, B., Sheu, J.-B., & Moghadam, H. S. (2016). Designing a supply chain resilient to major disruptions and supply/demand interruptions. Transportation Research Part B-Methodological, 94, 121–149.

Li, C., & Liu, S. (2013). A robust optimization approach to reduce the bullwhip effect of supply chains with vendor order placement lead time delays in an uncertain environment. Applied Mathematical Modelling, 37(3), 707–718.

Linton, T. & Vakil, B. (2020). Coronavirus Is Proving We Need More Resilient Supply Chains. Harvard Business Review.

Park, K. (2017). A Grey-based risk selection model using fuzzy information of a supply chain. Multimedia Tools and Applications76(17), 18083–18097.

Peng, H., Shen, N., Liao, H., Xue, H., & Wang, Q. (2020). Uncertainty factors, methods, and solutions of closed-loop supply chain — A review for current situation and future prospects. Journal of Cleaner Production, 254, 120032.

Reeves, M., Carlsson-Szlezak, P., Whitaker, K., & Abraham, M. (2020). Sensing and Shaping the Post-COVID Era.’. The BCG Henderson Institute.

Simangunsong, E. S., Hendry, L., & Stevenson, M. (2012). Supply-chain uncertainty: a review and theoretical foundation for future research. International Journal of Production Research, 50(16), 4493–4523.

Wuest, T., Kusiak, A., Dai, T., & Tayur, S. R. (2020). Impact of COVID-19 on Manufacturing and Supply Networks—The Case for AI-Inspired Digital TransformationSSRN.

Xu, J., Li, B., & Wu, D. (2009). Rough data envelopment analysis and its application to supply chain performance evaluation. International Journal of Production Economics122(2), 628–638.