What are the right configurations of just-in-time and just-in-case when supply chain shocks increase?

According to contingency theory, organizational performance depends on fit between two or more factors, such as environment, strategy, structure, etc. (Van de Ven and Drazin, 1985). Just-in-time (JIT) manufacturing principles fit with stable environments (Mackelprang and Nair, 2010). During 2020-22, JIT manufacturers were confronted with global supply chain (SC) shocks upstream and downstream, the magnitude of which were never encountered before. The COVID-19 pandemic created panic buying, stockpiling, rationing and shortage gaming (Ali et al., 2022; Choi et al., 2023; Yu et al., 2024). In addition, there were upstream shocks like the global semiconductor chip shortage that disrupted the automotive industry (Mehray, 2021). Likewise, the Russo-Ukrainian war has led to shortages in ingredients like sunflower oil, wheat, and increased prices of substitute ingredients (Castrodale, 2022). Many automobile giants e.g., BMW, VW, Ford, and Toyota, cut output and temporarily closed assembly lines due to a shortage of microchips. As such, JIT's fit with the environment and thus it is ability to drive operational performance was called into question.

JIT manufacturers must adapt when their strategy is no longer a fit with the new environment (Van de Ven and Drazin, 1985). In times of uncertainty, manufacturers may switch to a just-in-case (JIC) model, which differs in several production planning and stock control policies from the JIT model. The JIT model emphasizes reducing inventories and unused capacity, while the JIC model relies on increasing safety stock, alternate suppliers, and buffer capacity. For example, Huawei built a stockpile of chips for its telecom equipment and smart devices (Shead, 2021). Toyota, the pioneer of JIT, took steps to increase its inventory of electronic parts, e.g., semiconductors (Allen, 2022). A McKinsey report (Alicke et al., 2021) indicates that 61% of firms increased inventory, diversified supply bases, or localized or regionalized supply and production networks.

A report by SAP shows that about 84% of firms in the UK plan to proclaim the end of JIT inventory practices in favour of more JIC strategies (Barrett, 2022). Since supply and demand shocks may vary over time, both JIT and JIC practices may be required. Furthermore, some scholars argue manufacturers still need JIT during unstable times to reduce inconsistencies (Choi et al., 2023) or increase resilience (Alemsan et al., 2022; De Sanctis et al., 2018; Ruiz-Benítez et al., 2018). Others (e.g., Yu et al., 2020) show JIT fits well with innovativeness, suggesting it could help firms navigate unstable times by being more innovative. Rather than jettisoning JIT, firms may address varying levels of shocks with an appropriate mix of JIT and JIC. This requires manufacturers address issues of contingency and configuration to develop proper fit given the mission to improve operational performance. Therefore, we pose the research question: what are the right configurations of JIT and JIC when the magnitude of SC shocks vary from low to high?

Therefore, this study addresses the fit between JIT-JIC configurations with varying levels of SC shock. While SC shocks can be detrimental to operations, this study argues both JIT and JIC can improve operational performance to varying degrees at differing levels of SC shocks. Since JIT suits stable environments, when the magnitude of SC shocks is low, a higher level of JIT with a low level JIC is logical. The opposite applies for high magnitude SC shocks. Differences in production planning and inventory policies may produce a misfit, which will in turn reduce operational performance. JIC may leverage scale economies and drive large inventory positions or unused production capacity whereas JIT tends to minimize inventory, maximize utilization, and produce based on demand signals. On the face of it this is an apparent misfit and operational performance could be expected to decline. However, the interactions between JIT and JIC do not necessarily create tensions; they may complement one another. For example, JIT principles can be used to reduce inconsistency in processes (Shah and Ward, 2007), while JIC can complement a JIT environment when there are occasional small changes in supply or demand (Martha and Subbakrishna, 2002; Yu et al., 2024).

This study applies contingency theory and configuration theory to help develop insights into the use of JIT and JIC under different levels of SC shocks. For completeness, we consider both upstream and downstream shocks (Ali et al., 2022; Chen and Paulraj, 2004) caused by the COVID-19 pandemic. By doing so, this study makes significant contributions to theory and practice. From a theoretical perspective, we develop a configurational framework to clarify the impact of low/high levels of JIT and JIC on operational performance under varying magnitudes of SC shocks. The framework clarifies that supply chains can be divided into segments facing different volatilities and matched with suitable capacity and inventory buffers (Choi et al., 2023). We examine empirical evidence to show that the configurational tensions between JIT and JIC vary when SC shocks are small/large. From a practical perspective, this study provides insights to manufacturing managers on whether they should increase the use of JIT/JIC during SC shocks to improve operational performance and when they should vary the use of JIT/JIC. We also show that manufacturers from our samples failed to contain the negative interaction effects between JIT and JIC when SC shocks were large, while relying upon separating the resource configurations for hybrid JIT-JIC.