The Bullwhip Effect in Supply Networks

2021 ◽  
Author(s):  
Nikolay Osadchiy ◽  
William Schmidt ◽  
Jing Wu
Keyword(s):  
Operations Management ◽  
Aggregate Demand ◽  
Bullwhip Effect ◽  
Data Set ◽  
Supplier Relationships ◽  
Supply Networks ◽  
Customer Base ◽  
Base Management ◽  
Demand Variability ◽  
The Impact

We offer a new network perspective on one of the central topics in operations management—the bullwhip effect (BWE). The topic has both practical and scholarly implications. We start with an observation: the variability of orders placed to suppliers is larger than the variability of sales to customers for most firms, yet the aggregate demand variability felt by suppliers upstream does not amplify commensurably. We hypothesize that changes to the supplier’s customer base can smooth out its aggregate demand. We test the hypothesis with a data set that tracks the evolution of supply relationships over time. We show that the effect of customer base management extends beyond the statistical benefits of aggregation. In particular, both the formation and the dissolution of customer-supplier relationships are associated with the smoothing of the aggregate demand experienced by suppliers. This provides fresh insight into how firms may leverage their customer-supplier relationships to mitigate the impact of the BWE. This paper was accepted by Jay Swaminathan, operations management.

Empirical Assessment of Bullwhip Effect in Supply Networks

2021 ◽  
Vol 14 (2) ◽  
pp. 69-87
Author(s):  
Dazhong Wu ◽  
Joe Teng ◽  
Sergey Ivanov ◽  
Julius Anyu
Keyword(s):  
Regression Analysis ◽  
Supply Chain ◽  
Empirical Studies ◽  
Bullwhip Effect ◽  
Manufacturing Industries ◽  
The Other ◽  
Supply Chain Network ◽  
Supply Networks ◽  
Customer Base ◽  
Demand Variability

Previous empirical studies on bullwhip effects treat each industry or firm as isolated from its supply chain network. In this paper, the authors are interested in the role played by supply chain relational connection in moderating how demand variability signal is transmitted upstream. The paper conducts an empirical study based on a panel data of 55 manufacturing industries and 9 wholesale industries. The regression analysis shows that demand variability is propagated through supply chain upward and the transmission is influenced by the structural relationship between suppliers and customers, which is measured by customer-base concentration and customer interconnectedness. On the other hand, customer demand variability has a greater impact on industries with less concentrated customer base or with less interconnected customers.

Does Water Scarcity Affect Environmental Performance? Evidence from Manufacturing Facilities in Texas

2021 ◽  
Author(s):  
Suresh Muthulingam ◽  
Suvrat Dhanorkar ◽  
Charles J. Corbett
Keyword(s):  
Water Scarcity ◽  
Operations Management ◽  
Environmental Performance ◽  
Data Set ◽  
Full Sample ◽  
Toxic Releases ◽  
Manufacturing Operations ◽  
Toxic Emissions ◽  
Manufacturing Facilities ◽  
The Impact

It is well known that manufacturing operations can affect the environment, but hardly any research explores whether the natural environment shapes manufacturing operations. Specifically, we investigate whether water scarcity, which results from environmental conditions, influences manufacturing firms to lower their toxic releases to the environment. We created a data set that spans 2000–2016 and includes details on the toxic emissions of 3,092 manufacturing facilities in Texas. Additionally, our data set includes measures of the water scarcity experienced by these facilities. Our econometric analysis shows that manufacturing facilities reduce their toxic releases into the environment when they have experienced drought conditions in the previous year. We examine facilities that release toxics to water as well as facilities with no toxic releases to water. We find that the reduction in total releases (to all media) is driven mainly by those facilities that release toxic chemicals to water. Further investigation at a more granular level indicates that water scarcity compels manufacturing facilities to lower their toxic releases into media other than water (i.e., land or air). The impact of water scarcity on toxic releases to water is more nuanced. A full-sample analysis fails to link water scarcity to lower toxic releases to water, but a further breakdown shows that manufacturing facilities in counties with a higher incidence of drought do lower their toxic releases to water. We also find that facilities that release toxics to water undertake more technical and input modifications to their manufacturing processes when they face water scarcity. This paper was accepted by David Simchi-Levi, operations management.

How Price Dispersion Changes When Upgrades Are Introduced: Theory and Empirical Evidence from the Airline Industry

2019 ◽  
Vol 65 (8) ◽  
pp. 3835-3852 ◽  
Author(s):  
Yao Cui ◽  
A. Yeşim Orhun ◽  
Izak Duenyas
Keyword(s):  
Operations Management ◽  
Airline Industry ◽  
Price Dispersion ◽  
Consumer Welfare ◽  
Data Set ◽  
Differentiation Strategy ◽  
Valuation Effect ◽  
Price Distribution ◽  
The One ◽  
The Impact

This paper studies the effect of introducing a new vertical differentiation strategy, paying for an upgrade to a premium product after purchasing the base product, on the price dispersion of the base product arising from existing price discrimination strategies. In particular, we examine how a major U.S. airline’s price dispersion in the coach cabin changes after introducing the option to upgrade to a new type of premium economy seating within the coach cabin. We first provide a theoretical analysis that highlights two competing pressures that the new premium economy seating upgrades created on coach class prices. On the one hand, the airline benefits from lowering its prices because by allowing more customers to purchase in the first place, it increases the probability of selling upgrades (admission effect). On the other hand, for some customers, the value of flying with the airline increases because of the upgrade availability, therefore the airline may find it optimal to increase its prices (valuation effect). In the second part of the paper, we conduct an empirical investigation of the impact of upgrade introduction on coach class prices, based on a proprietary transaction-level data set from a major U.S. airline company. The empirical analysis tests the main predictions of our theoretical model and examines further nuances. The results show that the introduction of the premium economy seating upgrades is associated with an increase in the price dispersion and revenues in the coach class, the admission effect is stronger than the valuation effect on the low end of the price distribution, and the opposite is true on the high end of the price distribution. Finally, we discuss implications of our results for firm revenues and consumer welfare. This paper was accepted by Serguei Netessine, operations management.

The Impact of Workload on Operational Risk: Evidence from a Commercial Bank

2021 ◽  
Author(s):  
Yuqian Xu ◽  
Tom Fangyun Tan ◽  
Serguei Netessine
Keyword(s):  
Commercial Bank ◽  
Error Rate ◽  
Operations Management ◽  
Financial Services ◽  
Operational Risk ◽  
Data Set ◽  
Risk Event ◽  
Significant Performance ◽  
The Impact ◽  
The Empirical Analysis

Operational risk has been among the three most significant types of risks in the financial services industry, and its management is mandated by Basel II regulations. To inform better labor decisions, this paper studies how workload affects banks’ operational risk event occurrence. To achieve this goal, we use a unique data set from a commercial bank in China that contains 1,441 operational risk events over 16 months. We find that workload has a U-shaped impact on operational risk error rate. More specifically, the error rate of operational risk events decreases first, as workload increases, and then increases. Furthermore, when workload is low, employees tend to make performance-seeking risks; however, when workload is high, employees tend to exhibit quality degradation due to cognitive multitasking. Based on the causal relationship between workload and operational risk events from the empirical analysis, we discuss staffing policies among branches aimed at reducing operational risk losses. We find that employing a flexible staffing rule can significantly reduce the number of operational risk events by 3.2%–10% under different scenarios. In addition, this significant performance improvement can be achieved by adding even a little bit of flexibility to the process by allowing employees to either switch their business lines in the same branch or switch branches within the same business lines on a quarterly basis. This paper was accepted by Vishal Gaur, operations management.

Customer–Supplier Relationships and Abnormal Accruals

2020 ◽  
Vol 23 (04) ◽  
pp. 2050027
Author(s):  
May Xiaoyan Bao ◽  
Matthew T. Billett ◽  
Yixin Liu
Keyword(s):  
Supply Chain ◽  
Coefficient Of Variation ◽  
Bullwhip Effect ◽  
Transmission Channel ◽  
Customer Demand ◽  
Demand Shock ◽  
Supplier Relationships ◽  
Amplification Ratio ◽  
Abnormal Accruals ◽  
The Impact

We investigate the relationship between customer and supplier firms’ abnormal accruals to examine whether the supply chain is an important transmission channel of abnormal accruals. We propose “earnings management” hypothesis and “customer demand shock” hypothesis. Empirically, we examine the relation between a supplier’s estimated abnormal accruals and those of its major customers using Compustat Business Segment Files over the period 1987–2015. To further explore the demand shock channel, we directly test the impact of the bullwhip effect (BWE) on the linkage in abnormal accruals along the supply chain. Following the literature in operation management, we construct the amplification ratio, measured as the coefficient of variation of a firm’s orders divided by the coefficient of variation of the firm’s demand. We find that customer firms’ demand shocks link customer and supplier abnormal accruals as they propagate along the supply chain, via the BWE. Our evidence supports “customer demand shock” hypothesis. Consistent with the view that improving predictions on orders from their customers would mitigate this BWE, we find that a customer’s abnormal accruals have a much smaller impact on those of its suppliers whose auditors have expertise in the customer’s industries. Overall, our results suggest that the supply chain is an important transmission channel of abnormal accruals, and auditor expertise serves to reduce information opaqueness during this process. Our paper contributes to the literature examining the impact of BWEs on firms’ financial performance and the role of auditors’ expertise in reducing information opaqueness in supply chain.

scholarly journals Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Salvatore Cannella ◽  
Roberto Dominguez ◽  
Jose M. Framinan ◽  
Manfredi Bruccoleri
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Negative Impact ◽  
Positive Impact ◽  
Bullwhip Effect ◽  
Sources Of Information ◽  
Short Delay ◽  
Demand Information ◽  
Demand Variability ◽  
The Impact

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.

Masking the bullwhip effect in retail: the influence of data aggregation

2015 ◽  
Vol 45 (8) ◽  
pp. 814-830 ◽  
Author(s):  
Yao 'Henry' Jin ◽  
Brent D. Williams ◽  
Matthew A. Waller ◽  
Adriana Rossiter Hofer
Keyword(s):  
Hierarchical Linear Modeling ◽  
Data Aggregation ◽  
Strong Support ◽  
Bullwhip Effect ◽  
Masking Effect ◽  
Linear Modeling ◽  
Content Type ◽  
Product Categories ◽  
Demand Variability ◽  
The Impact

Purpose – The accurate measurement of demand variability amplification across different nodes in the supply chain, or “bullwhip effect,” is critical for firms to achieve more efficient inventory, production, and ordering planning processes. Building on recent analytical research that suggests that data aggregation tends to mask the bullwhip effect in the retail industry, the purpose of this paper is to empirically investigate whether different patterns of data aggregation influence its measurement. Design/methodology/approach – Utilizing weekly, product-level order and sales data from three product categories of a consumer packaged goods manufacturer, the study uses hierarchical linear modeling to empirically test the effects of data aggregation on different measures of bullwhip. Findings – The authors findings lend strong support to the masking effect of aggregating sales and order data along product-location and temporal dimensions, as well as the dampening effect of seasonality on the measurement of the bullwhip effect. Research limitations/implications – These findings indicate that inconsistencies found in the literature may be due to measurement aggregation and statistical techniques, both of which should be applied with care by academics and practitioners in order to preserve the fidelity of their analyses. Originality/value – Using product-weekly level data that cover both seasonal and non-seasonal demand, this study is the first, to the author’s knowledge, to systematically aggregate data up to category and monthly levels to empirically examine the impact of data aggregation and seasonality on bullwhip measurement.

scholarly journals Inherent Complexity Research on the Bullwhip Effect in Supply Chains with Two Retailers: The Impact of Three Forecasting Methods Considering Market Share

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Junhai Ma ◽  
Binshuo Bao ◽  
Xiaogang Ma
Keyword(s):  
Supply Chain ◽  
Market Share ◽  
Mean Squared Error ◽  
Moving Average ◽  
Bullwhip Effect ◽  
Minimum Mean Squared Error ◽  
Forecasting Methods ◽  
Effect Measure ◽  
Demand Variability ◽  
The Impact

An important phenomenon in supply chain management which is known as the bullwhip effect suggests that demand variability increases as one moves up a supply chain. This paper contrasts the bullwhip effect for a two-stage supply chain consisting of one supplier and two retailers under three forecasting methods based on the market share. We can quantify the correlation coefficient between the two retailers clearly, in consideration of market share. The two retailers both employ the order-up-to inventory policy for replenishments. The bullwhip effect is measured, respectively, under the minimum mean squared error (MMSE), moving average (MA), and exponential smoothing (ES) forecasting methods. The effect of autoregressive coefficient, lead time, and the market share on a bullwhip effect measure is investigated by using algebraic analysis and numerical simulation. And the comparison of the bullwhip effect under three forecasting methods is conducted. The conclusion suggests that different forecasting methods and various parameters lead to different bullwhip effects. Hence, the corresponding forecasting method should be chosen by the managers under different parameters in practice.

When You Work with a Superman, Will You Also Fly? An Empirical Study of the Impact of Coworkers on Performance

2019 ◽  
Vol 65 (8) ◽  
pp. 3495-3517 ◽  
Author(s):  
Tom Fangyun Tan ◽  
Serguei Netessine
Keyword(s):  
Operations Management ◽  
Peer Effects ◽  
Sales Performance ◽  
Sales Managers ◽  
Ability Level ◽  
Data Set ◽  
Ability Levels ◽  
The Impact ◽  
Total Sales ◽  
Operational Data

We examine a large operational data set in a casual restaurant setting to study how coworkers’ sales ability level affects other workers’ sales performance. We find that waiters react nonlinearly to their coworkers’ ability. In particular, when coworkers’ overall sales ability is low, increasing this ability may prompt waiters to redouble both upselling and cross-selling efforts. When overall coworkers’ ability is high, however, further increasing their ability may trigger waiters to reduce sales efforts. Our empirical findings imply that, to maximize sales, managers should mix waiters with heterogeneous ability levels during the same shift. Through a counterfactual analysis, we find that considering the inverted U-shaped peer effects when optimizing current waiters’ schedules without changing their utilization may increase total sales by approximately 2.48% at no extra cost. This paper was accepted by Vishal Gaur, operations management.

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