The IUP Journal of Operations Management
Impact of Inventory Capacity Constraints on Supply Chain Dynamics: A Computer-Based Simulation Approach

Article Details
Pub. Date : May, 2023
Product Name : The IUP Journal of Operations Management
Product Type : Article
Product Code : IJOM010523
Author Name : Martin Lockstrom
Availability : YES
Subject/Domain : Management
Download Format : PDF Format
No. of Pages : 19



The bullwhip is a well-known phenomenon in supply chain management. Whereas past research has focused on factors like supply rationing, batch-size, lead-time, etc., mainly from an analytical perspective, this paper broadens the research by specifically examining the impact of inventory constraints not only on demand (order size) but also on inventory levels and supply chain cost. The results confirm the findings of past research and bring new insights on the impact on component and compound bullwhip effect behavior across supply chain echelons by showing that inventory acts as a damper on bullwhip effect.


Supply chains are complex, adaptive systems whose behavior depends on a broad range of factors (Choi et al., 2001; Pathak et al., 2007; and Carter et al., 2015). A commonly observed supply chain phenomenon is the so-called "bullwhip effect", also referred to as "Forrester effect" after its discoverer (Lane and Sterman, 2011). The bullwhip effect refers to the phenomenon that occurs in a supply chain when orders submitted to suppliers have a greater variability than those received from customers. Prior research has identified the factors behind it, but mainly from a qualitative and analytical perspective. Interestingly, an "inverse" bullwhip effect has also been discovered and investigated in the past (Li et al., 2017).

Literature Review
Lee (1997) identified demand signal processing (i.e., incorrect demand forecasting), rationing game and lead-time, order batching and prices variations as the main causes of the bullwhip effect. Lee also discovered that the most effective way of reducing it was by reducing uncertainty of end customer demand and order lead-time along the supply chain by providing each stage with more accurate and timely information, for instance, through Electronic Data Interchange (EDI).