Measuring and eliminating the bullwhip in closed loop supply chains using control theory and Internet of Things

Abstract

Closed-loop supply chains are complex systems as they involve the seamless backward and forward flow of products and information. With the advent of e-commerce and online shopping, there has been a growing interest in product returns and the associated impact on inventory variance and the bullwhip effect. In this paper, a novel four-echelon closed-loop supply chain model is presented, where base-stock replenishment policies are modelled by means of a proportional controller. A stochastic state-space model is implemented, initially to capture the supply chain dynamics while the model is analysed under stationarity conditions with the aid of a covariance matrix. This allows the bullwhip effect to be expressed as a function of replenishment policies and product return rates. Next, an optimisation method is introduced to study the impact of the Internet of Things on inventory variance and the bullwhip effect. The results show that the Internet of Things can reduce costs associated with inventory fluctuations and eliminate the bullwhip effect in closed-loop supply chains.

Assessing the Bullwhip effect in supply chain: trends, gaps, and overlaps

“…Papanagnou [60] simulates a CLSC using a control system model to mathematically describe the complex relationships in a four-echelon network, demonstrating that high product return rates with aggressive ordering policies amplify the BWE. The model accomplished the information asymmetry in a CLSC, including the Internet of Things (IoT) concept in the customer-to-retailer loop to share accurate information about the returned products and replenishment policies to mitigate the variations in the demand and the BWE.…”

“…Recently, researchers have considered lead time [95] and collaborative SC actors relationships [96] accurate forecasting [82], and pricing strategy. [28], IS [61], capacity production tunning [84], and handling CLSC returning flow [60] as strategies to mitigate the BWE. This paper used the framework proposed by Wang et al [10] to connect trends, found concepts, and future studies discerned by authors.…”

Understanding product returns: A systematic literature review using machine learning and bibliometric analysis

“…Wang et al, 2021;9 Zhang and Choi, 2020). Inventory management and the Bullwhip Effect are also issues because unsold products are returned to manufacturers, which may induce overstocking or understocking (Dimitrov and Ceryan, 2019;Papanagnou, 2021;D. Wang et al, 2020;.…”

Inhibitory influence of supply chain digital transformation on bullwhip effect feedback difference

“…Information sharing can improve prediction accuracy and weaken bullwhip effect to a certain extent (Shabany Moghadam and Fazel Zarandi, 2022). However, due to inter-firm competition, uncertainty in pricing decisions and the risk of leakage of proprietary information in supply chain networks, firms in the chain may not have a strong willingness to share information (Ghode et al ., 2021), and information sharing alone is not enough to completely eliminate the bullwhip effect but requires effective coordination and feedback of critical information without loss or delay (Papanagnou, 2021).…”