Managing emergent uncertainties through adaptable supply chain planning


Submit your paper here!


Traditional supply chain planning (SCP) practice, such as sales and operations planning (S&OP), is based on a somewhat rigid structure to generate stability and proactiveness, and is therefore not sufficient for today's complex supply chains, particularly to meet the dynamic requirements of the planning environment including social and environmental sustainability goals (Jonsson et al., 2021; Sodhi and Tang, 2021). While supply chain planning seeks a static equilibrium in which the planning system is assumed to bring back a steady state position, in practice this stability is largely non-existent since the system is in a constant state of flux due to the dynamic complexity and volatile planning environment (Choi, et al., 2001).  

Over the past decades, SCP practice has moved beyond demand-supply integration for value creation (Esper et al., 2010), coordination (Tuomikangas and Kaipia, 2014) and cross-functionality. SCP research must evolve into a more practice-relevant and data-driven intervention for problem-solving (Jonsson and Holmström, 2016) dealing with sustainability challenges such as waste or surplus prevention. In particular, this shift relies on advanced and emerging industry 4.0 technologies (Schlegel et al., 2021; Xu et al., 2021; Sengupta and Dreyer, 2023) and building adaptability to manage supply chain dynamics (Dittfeld et al., 2022). Adaptability requires the capability to deal with unforeseen changes by enhancing responsiveness to the system through loose and weak couplings between the agents in place (Choi et al., 2001; Pike et al., 2010). Adaptability, in fact, can be framed as a reinterpretation of resilience in today’s unpredictable dynamic and complex social-ecological supply chain systems (Feizabadi et al., 2023; Wieland et al., 2023).  

The nature of serious supply chain disruptions requires continuous and dynamic decision making and applying the full range of entrepreneurial decisions (Packard et al., 2017). Consequent uncertainties in the supply chain, due to geopolitical activities and critical environmental and climate crises, harm supply chain operations by causing delays, stockouts, excess inventory, surplus products and waste, higher costs, and lower customer satisfaction. The planning requirements of circular supply chains (Ponte et al., 2020; De Lima and Seuring, 2023) ‒ characterized by a high number of actors of new types, uncertainties connected to demand and supply in terms of volumes and quality of return materials ‒ are still largely unexplored. Applying static planning practices in a dynamic environment, which primarily focus on optimizing responses to known risks rather than on emergent and unknown problems, can be counter-productive and cause nervousness in planning and efficiency losses (Kaipia et al., 2006) and lead to continuous replanning of capacity and loss of planning confidence (De Kok and Inderfurth, 1997). Understanding how SCP practices work together to embrace emergent uncertainties and simultaneously address the dynamic complexities and sustainability goals is crucial, especially in light of advanced and emerging technologies. These observations necessitate more scholarly research (Jonsson et al., 2021; Browning et al., 2023). 

To be adaptable, firms must not only build resilience to recover from disruptions but also make proactive preparations to mitigate future shocks, possibly by developing innovative models and new value propositions (Kauffman et al., 2018; Cohen and Kouvelis, 2021). Proactive firms influence and create dynamic conditions, resources, or structural flexibilities that will shape those trajectories to embrace disruptions or uncertainties as an opportunity (Christopher and Holweg, 2011). To enable resilience building, supply chain planning needs to be redirected away from predicting future development trajectories towards coordinating planning and execution efforts (Lapide, 2022), addressing contextualized planning solutions (Kaipia et al., 2017) and developing innovative solutions to rapidly deal with emergent situations (Xu et al., 2021; Lapide, 2022). This directs toward a new paradigm in SCP research, assuring capability for evolutionary tinkering in planning and decision making (Packard et al., 2017; Kauffman, et al., 2018). This SI intends to address these developments in SCP – extending the theory and the nature of SCP, while advancing the contemporary discussion on practices such as S&OP, integrated business planning, demand management, quick response planning, supply chain control towers for adaptability – with an emphasis on the role of technologies and the circularity and sustainability agendas.  

List of Topic Areas

The SI is seeking theoretical and empirical studies that offer novel conceptualizations, frameworks, and solutions to the problems outlined. They should contribute to contemporary discussions of adaptable SCP. We encourage contributions from the wider OSCM community (e.g.  purchasing, logistics, manufacturing, supply networks, operations planning & control, behavioral operations, innovation, strategy, organizational, information management, digitalization, lean management), which could inform adaptable supply chain planning. We will accept both theoretical development and robust empirical research with a clear theoretical and practical contribution. Papers adopting mixed methodology are also welcome. We would also like to see high-quality critical reviews and impact pathway papers, but pure modeling and simulation papers or literature reviews are beyond our consideration. The following are examples of topics, but not limited to: 

  • Balancing supply chain planning and execution capabilities for adaptability 
  • The role of managerial decision-making speed and reactiveness in adopting adaptable supply chain practices  
  • Dynamic and structural flexibilities for adaptable supply chain planning 
  • Adaptable supply chain planning and its impacts on the bullwhip effect 
  • Supply chain planning for managing unknown-unknowns  
  • Ex-ante and ex-post strategies to disruptions 
  • Sharing economy models and implications for adaptable supply chain planning 
  • Adaptable supply chain planning and sustainability/circularity  
  • Supply chain transparency and visibility for adaptable supply chain planning 
  • Addressing the planning trade-offs and paradoxes under supply chain uncertainty 
  • Role of digitalization in cross-functional and organizational collaborative planning  
  • Dark side of digitalization for supply chain planning 
  • Industry 4.0-enabled adaptable supply chain planning 
  • Implications of design (supply chain, product, process) on adaptable supply chain planning, 
  • Functional planning and the role of functions (e.g. sales, R&D, finance, purchasing) in adaptable supply chain planning 
  • Human factors (such as behaviors and biases) and their impact on supply chain planning adaptability  
  • Managing lean operations and achieving adaptability through supply chain planning 
  • Organizational path dependencies and process innovation for adaptable supply chain planning 
  • Implementation of adaptable supply chain planning practice 

Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available here.
Author guidelines must be strictly followed. Please see here.
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to ““Please select the issue you are submitting to”. 
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Key Deadlines

Submissions open on: 1 February 2024 
Submission deadline: 8 July 2024 

Guest Editors

Patrik Jonsson is Professor of Operations and Supply Chain Management at Chalmers University of Technology. His expertise is in supply chain planning, particularly demand management, sales & operations planning, material management, sourcing management, within which areas he has managed several external research projects, authored textbooks and published academic papers in journals such as Journal of Operations Management, International Journal of Operations and Production Management, International Journal of Production Economics, International Journal of Production Research, Journal of Purchasing and Supply Management, Supply Chain Management: An International Journal, International Journal of Physical Distribution and Logistics Management and received several publishing awards. He is an active member of EurOMA where he has been on the board and co-chair of the annual conference. He has guest edited journal special issues, and is currently an associate editor for the International Journal of Operations and Production Management, Journal of Business Logistics, and International Journal of Physical Distribution and Logistics Management.  

Thomas Choi is the AT&T Professor of the W. P. Carey School of Business at Arizona State University. As a researcher of supply chain management, he has studied the upstream side of supply chains. He has published articles in Decision Sciences, Harvard Business Review, Journal of Operations Management, Journal of Supply Chain Management, Production and Operations Management, and others. He currently serves as co-director of the Complex Adaptive Supply Networks Research Accelerator (CASN-RA). He has co-authored three practitioner books. He served as the lead editor of the Oxford Handbook of Supply Chain Management and has a forthcoming book, The Nature of Supply Networks. From 2014 to 2019, he served as the Executive Director of CAPS Research, where he oversaw research projects involving supply management planning and Industry 4.0 related technologies. From 2011 to 2014, he served as co-editor in chief of the Journal of Operations Management. Since 2018, he has been listed as a Highly Cited Researcher by Clarivate’s Web of Science. 

Heidi C. Dreyer is a Professor of Supply Chain Management at NTNU. Her expertise is in supply chain management, particularly supply chain planning and supply chain planning and control, and has managed several external national and international research projects. Her research is published in journals such as International Journal of Operations and Production Management, International Journal of Production Economics, Computers in Industry, Production Planning & Control, and has received publishing awards. She is an active member of EurOMA, NOFOMA and APMS (Advances in Production Management Systems) – in APMS she has been on the board since 1998. She has also been on the board of EurOMA, co-chair of the annual EurOMA and NOFOMA conferences, and guest editor of journal special issues.  

Dr Riikka Kaipia is a dedicated SCM researcher, research leader and educator. Since finalizing her doctoral thesis in 2007 in Aalto University, she has been conducting research and university teaching in Turku University and Aalto University in Finland and Chalmers University of Technology in Sweden. Her expertise areas are connected to intelligent supply chains, supply chain planning processes, circular economy supply chains, and procurement management. She has Co-Editor in a Special Issue in the IJPDLM about S&OP. Her research is published in International Journal of Operations and Production Management, Journal of Operations Management, Research Policy, Journal of Purchasing and Supply Management, Supply Chain Management: An International Journal, and International Journal of Physical Distribution and Logistics Management, and has received several publishing awards. 

Sourav Sengupta is a postdoctoral fellow at the Norwegian University of Science and Technology (NTNU). He holds a joint Ph.D. in Operations and Supply Management from the Indian Institute of Technology Bombay and Monash University, Australia.  His current research focuses on how industry 4.0 technologies can be leveraged in supply chain planning. His co-authored work on digital twin-driven sales and operations planning, understanding OSM departmental thought worlds for cross-functional integration, and artificial intelligence-based decision systems for supply chain integration, clustering, and cellular manufacturing have appeared in journals such as Computers in Industry, Journal of Supply Chain Management, International Journal of Production Research, and Computers & Industrial Engineering. He has also published in the areas of service purchasing and logistics in journals such as the International Journal of Physical Distribution and Logistics Management and the Service Industries Journal.  


Browning, T., Kumar, M., Sanders, N., Sodhi, M. S., Thürer, M., & Tortorella, G. L. (2023), “From supply chain risk to system-wide disruptions: Research opportunities in forecasting, risk management and product design”, International Journal of Operations & Production Management, pp. 0144-3577. 
Choi, T. Y., Dooley, K., & Rungtusanatham, M. (2001), “Supply networks and complex adaptive systems: Control versus emergence”, Journal of Operations Management, Vol. 19, No. 3, pp. 351-366.   
Cohen, M. A. & Kouvelis, P. (2021), “Revisit of AAA excellence of global value chains: Robustness, resilience, and realignment”, Production and Operations Management, Vol. 30, No. 3, pp. 633-643. 
Christopher, M., & Holweg, M. (2011), “Supply Chain 2.0”: Managing supply chains in the era of turbulence”, International Journal of Physical Distribution & Logistics Management, Vol. 41. No. 1, pp. 63-82. 
De Kok, T., & Inderfurth, K. (1997), “Nervousness in inventory management: Comparison of basic control rules”, European Journal of Operational Research, Vol. 103, No. 1, pp. 55-82. 
De lima, F.A., & Seuring, S. (2023), “A Delphi study examining risk and uncertainty management in circular supply chains”, International Journal of Production Economics, Vol. 258, 108810. 
Dittfeld, H., van Donk, D. P., & van Huet, S. (2022), “The effect of production system characteristics on resilience capabilities: A multiple case study”, International Journal of Operations & Production Management, Vol. 42, No. 13, pp. 103-127. 
Esper, T. L., Ellinger, A. E., Stank, T. P., Flint, D. J., & Moon, M. (2010), “Demand and supply integration: A conceptual framework of value creation through knowledge management”, Journal of the Academy of Marketing Science, Vol. 38, pp. 5-18. 
Feizabadi, J., Gligor, D. M., & Choi, T. Y. (2023), “Examining the resiliency of intertwined supply networks: A jury-rigging perspective”, International Journal of Production Research, Vol. 61, pp. 8, pp. 2432-2451. 
Jackson, S., Wilson, J.R., MacCarthy, B. (2004), “A new model of scheduling in manufacturing: Tasks, roles and monitoring”, Human Factors, Vol. 46, No. 3, pp. 533-550. 
Jonsson, P., & Holmström, J. (2016), “Future of supply chain planning: Closing the gaps between practice and promise”, International Journal of Physical Distribution & Logistics Management, Vol. 46, No. 1, pp. 62-81. 
Jonsson, P., Kaipia, R. & Barratt, M. (2021), “Guest editorial: The future of S&OP: Dynamic complexity, ecosystems and resilience”, International Journal of Physical Distribution & Logistics Management, Vol. 51, No. 6, pp. 553-565. 
Kaipia, R., Korhonen, H., & Hartiala, H. (2006), “Planning nervousness in a demand supply network: An empirical study”, International Journal of Logistics Management, Vol. 17, No. 1, pp. 95-113. 
Kaipia R., Holmström J., Småros, J., Rajala R. (2017), “Information sharing for sales and operations planning: Contextualized solutions and mechanisms”, Journal of Operations Management, Vol. 52, pp. 15-29.  
Kauffman, S., Pathak, S., Sen, P.K. & Choi, T. (2018), “Jury rigging and supply network design: Evolutionary tinkering in the presence of unknown-unknowns”, Journal of Supply Chain Management, Vol. 54, No.1, pp. 51-63. 
Lapide, L. (2022), “Quick response forecasting & planning: Revisited, Journal of Business Forecasting, Vol. 41, No. 2, pp. 9-13. 
Oliva, R., & Watson, N. (2011), “Cross-functional alignment in supply chain planning: A case study of sales and operations planning”, Journal of Operations Management, Vol. 29, No. 5, pp. 434-448. 
Packard, M.D., Clark, B.B., & Klein, P.G. (2017), “Uncertainty Types and Transitions in the Entrepreneurial Process”, Organization Science, Vol. 28, No. 5, pp. 840-856.  
Pike, A., Dawley, S. & Tomaney, J. (2010), “Resilience, adaptation and adaptability”, Cambridge Journal of Regions, Economy and Society, Vol. 3, No. 1, pp. 59-70. 
Ponte, B., Naim, M.M., & Syntetos, A.A. (2020), “The effect of returns volume uncertainty on the dynamic performance of closed-loop supply chains”, Journal of Remanufacturing, Vol. 10, pp.1–14 
Schlegel, A., Birkel, H. S. & Hartmann, E. (2020), “Enabling integrated business planning through big data analytics: A case study on sales and operations planning”, International Journal of Physical Distribution & Logistics Management, Vol. 51, No. 6, pp. 607-633. 
Sengupta, S., & Dreyer, H. (2023), “Realizing zero-waste value chains through digital twin-driven S&OP: A case of grocery retail”, Computers in Industry, Vol. 148, 103890. 
Sodhi, M. S., & Tang, C. S. (2021), “Extending AAA capabilities to meet PPP goals in supply chains”, Production and Operations Management, Vol. 30, No. 3, pp. 625-632. 
Son, B. G., Kim, H., Hur, D., & Subramanian, N. (2021), “The dark side of supply chain digitalisation: Supplier-perceived digital capability asymmetry, buyer opportunism and governance”, International Journal of Operations & Production Management, Vol. 41, No. 7, pp. 1220-1247. 
Sydow, J., Schreyögg, G., & Koch, J. (2009), “Organizational path dependence: Opening the black box”, Academy of Management Review, Vol. 34, No. 4, pp. 689-709. 
Tuomikangas, N., & Kaipia, R. (2014), “A coordination framework for sales and operations planning (S&OP): Synthesis from the literature”, International Journal of Production Economics, Vol. 154, pp. 243-262. 
Wieland, A., Stevenson, M., Melnyk, S. A., Davoudi, S., & Schultz, L. (2023), “Thinking differently about supply chain resilience: What we can learn from social-ecological systems thinking”, International Journal of Operations & Production Management, Vol. 32, No. 1, pp. 1-21. 
Xu, J., Pero, M. E. P., Ciccullo, F. & Sianesi, A. (2021), “On relating big data analytics to supply chain planning: Towards a research agenda”, International Journal of Physical Distribution & Logistics Management, Vol. 51, No. 6, pp. 656-682.