Results of a beer game experiment: Should a manager always behave according to the book?

Edali, Mert; Yasarcan, Hakan

doi:10.1002/cplx.21731

Cited by 14 publications

(14 citation statements)

References 45 publications

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“…Moreover, the three studies adopting a four-echelon structure (see, e.g., [37,40,45,53]) do not provide specific insights on the dynamics of SC under demand information sharing with delays/ errors (in the following, demand delays/errors).…”

Section: Inmentioning

confidence: 99%

Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

2018

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We investigate two main sources of information inaccuracies (i.e., errors and delays) in demand information sharing along the supply chain (SC). Firstly, we perform a systematic literature review on inaccuracy in demand information sharing and its impact on supply chain dynamics. Secondly, we model several SC settings using system dynamics and assess the impact of such information inaccuracies on SC performance. More specifically, we study the impact of four factors (i.e., demand error, demand delay, demand variability, and average lead times) using three SC dynamic performance indicators (i.e., bullwhip effect, inventory variability, and average inventory). The results suggest that demand error has a negative impact on SC performance, which is exacerbated by the magnitude of the error and by low demand variability scenarios. In contrast, demand delay produces a nonlinear behavior in the supply chain response (i.e., a short delay may have a negative impact and a long delay may have a positive impact), being influenced by the supply chain configuration.

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Section: Inmentioning

confidence: 99%

Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

2018

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“…We present the equations of the simplified version below (see Sterman (1989) and Edali and Yasarcan (2016) for an extended version).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

The moderating impact of supply network topology on the effectiveness of risk management

Ledwoch

Yasarcan

Brintrup

2018

International Journal of Production Economics

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While supply chain risk management offers a rich toolset for dealing with risk at the dyadic level, less attention has been given to the effectiveness of risk management in complex supply networks. We bridge this gap by building an agent based model to explore the relationship between topological characteristics of complex supply networks and their ability to recover through inventory mitigation and contingent rerouting. We simulate upstream supply networks, where each agent represents a supplier. Suppliers' connectivity patterns are generated through random and preferential attachment models. Each supplier manages its inventory using an anchor-andadjust ordering policy. We then randomly disrupt suppliers and observe how different topologies recover when risk management strategies are applied. Our results show that topology has a moderating effect on the effectiveness of risk management strategies. Scale-free supply networks generate lower costs, have higher fillrates, and need less inventory to recover when exposed to random disruptions than random networks. Random networks need significantly more inventory distributed across the network to achieve the same fill rates as scalefree networks. Inventory mitigation improves fill-rate more than contingent rerouting regardless of network topology. Contingent rerouting is not effective for scale-free networks due to the low number of alternative suppliers, particularly for short-lasting disruptions. We also find that applying inventory mitigation to the most disrupted suppliers is only effective when the network is exposed to frequent disruptions; and not cost effective otherwise. Our work contributes to the emerging field of research on the relationship between complex supply network topology and resilience.

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“…In recent years, the research has been more focused on how to minimize this bullwhip effect with various inventory management techniques and strategies. 6–8 Simulation modeling is the primary method for analyzing the dynamics of a supply chain. 9 However, a literature review we conducted revealed that the work done for this purpose lacked either the complexity of the supply chain model or the results found were unsatisfactory.…”

Section: Introductionmentioning

confidence: 99%

“…The research that is most similar to our case is that of Edali and Yasarcan. 8 The authors built a system dynamics model of the beer game supply chain and conducted a series of experiments with the aim of minimizing the bullwhip effect. The model decides on order sizes according to a dynamic decision-making heuristic, so that the order size varies at each turn.…”

Section: Introductionmentioning

confidence: 99%

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Minimizing the bullwhip effect in a supply chain: a simulation approach using the beer game

Alabdulkarim

2020

SIMULATION

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In this research, the aim is to find the most appropriate inventory management logic and set of rules along with the optimal decision values that will minimize the bullwhip effect in a supply chain, taking the beer game supply chain as a reference model. In order to achieve this, a simulation model of the beer game supply chain is developed along with an ordering strategy based on the Economic Order Quantity with additional rules, such as no backorder policy, vendor-managed inventory, and taking into consideration route deliveries, all of which are implemented in the ordering algorithm. In the literature, there is extensive research conducted on the causes of the bullwhip effect and in the presence of certain inventory management policies. However, these terms are rarely combined with simulation modeling to provide satisfactory proven results. In this article, our proposed ordering algorithm avoids the bullwhip effect to a very large extent. The results show that approximately half the cost is incurred compared to recent studies with the same settings.

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Results of a beer game experiment: Should a manager always behave according to the book?

Abstract: Abstract

Cited by 14 publications

References 45 publications

Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

The moderating impact of supply network topology on the effectiveness of risk management

Minimizing the bullwhip effect in a supply chain: a simulation approach using the beer game

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