Menu Costs and the Bullwhip Effect: Supply Chain Implications of Dynamic Pricing

2021 ◽  
Author(s):  
Robert L. Bray ◽  
Ioannis Stamatopoulos
Keyword(s):  
Supply Chain ◽  
Dynamic Pricing ◽  
Adjustment Costs ◽  
Empty Space ◽  
Bullwhip Effect ◽  
Price Adjustment ◽  
Grocery Stores ◽  
Menu Costs ◽  
Overtime Work ◽  
The Difference

Suppose that technology reduces price-adjustment costs (e.g., the costs of printing and changing price tags), and as a result prices at grocery stores change more dynamically. Will this change mean less stability or more stability for grocery supply chains? In other words, will more dynamic pricing downstream mean more last-minute purchases, more overtime work, and more empty space in trucks and warehouses? Or will it mean more regular and more standardized orders, smoother schedules, and less waste? To answer this question, we fit a pricing and ordering model to data from a large Chinese supermarket chain (daily prices, sales, inventories, and shipments from products from seven categories at 78 stores for 3.5 years) and then simulate a counterfactual grocery chain in which the estimated price-adjustment costs are set to zero. We find that the removal of price-adjustment costs stabilizes the supply chain, reducing both its shipment volatility, its sales volatility, and its bullwhip (the difference between the shipment and sales volatility).

scholarly journals Complex Characteristics of Multichannel Household Appliance Supply Chain with the Price Competition

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Junhai Ma ◽  
Wandong Lou
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Price Competition ◽  
Domain Of Attraction ◽  
Bullwhip Effect ◽  
Price Adjustment ◽  
Stable Region ◽  
Supply Chain System ◽  
Household Appliance ◽  
Internet Channel

This paper studies the complex characteristics caused by the price competition in multichannel household appliance supply chains. We consider a two-level household appliance supply chain system consisting of a manufacturer with an Internet channel and a retailer with a traditional channel and an Internet channel. Each channel’s price-setting follows the bounded rational decision process in order to obtain the optimal profit or more market share. Considering that the price competition often leads to the demand and order fluctuation, we also investigate the bullwhip effect of the multichannel supply chains on the basis of the order-up-to-inventory policy. From the numerical simulation, we find a system in a chaotic state will suffer larger bullwhip effect than a stable system, and the manufacturer’s Internet channel is helpful to mitigate the bullwhip effect. Our results provide some useful managerial inspirations for the household manufacturer and retailers. Firstly, each channel should make their retail price with a suitable price adjustment speed in the stable region, and each time pricing cannot exceed the domain of attraction. Secondly, the manufacturer can adopt a more radical pricing strategy in their Internet channel to mitigate the bullwhip effect. Thirdly, the price adjustment should be reviewed and be appropriately reduced if the price adjustment is too large.

Study and Simulation on Dynamics of a Risk-Averse Supply Chain Pricing Model with Dual-Channel and Incomplete Information

2016 ◽  
Vol 26 (09) ◽  
pp. 1650146 ◽  
Author(s):  
Lijian Sun ◽  
Junhai Ma
Keyword(s):  
Supply Chain ◽  
Incomplete Information ◽  
Dynamic Pricing ◽  
Wholesale Price ◽  
Price Adjustment ◽  
Phase Portraits ◽  
Largest Lyapunov Exponent ◽  
Risk Averse ◽  
Dual Channel ◽  
Adjustment Speed

Under the industrial background of dual-channel, volatility in demand of consumers, we use the theory of bifurcations and numerical simulation tools to investigate the dynamic pricing game in a dual-channel supply chain with risk-averse behavior and incomplete information. Due to volatility of demand of consumers, we consider all the players in the supply chain are risk-averse. We assume there exist Bertrand game and Manufacturers’ Stackelberg in the chain which are closer to reality. The main objective of the paper is to investigate the complex influence of the decision parameters such as wholesale price adjustment speed, risk preference and service value on stability of the risk-averse supply chain and average utilities of all the players. We lay emphasis on the influence of chaos on average utilities of all the players which did not appear in previous studies. The dynamic phenomena, such as the bifurcation, chaos and sensitivity to initial values are analyzed by 2D bifurcation phase portraits, Double Largest Lyapunov exponent, basins of attraction and so on. The study shows that the manufacturers should slow down their wholesale price adjustment speed to get more utilities, if the manufacturers are willing to take on more risk, they will get more profits, but they must keep their wholesale prices in a certain range in order to maintain the market stability.

scholarly journals Evolutionary Game Analysis of Information Sharing in Fresh Product Supply Chain

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yanhui Li ◽  
He Xu ◽  
Yan Zhao
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Product Information ◽  
Fresh Produce ◽  
Evolutionary Game ◽  
Information Leakage ◽  
Bullwhip Effect ◽  
Agricultural Product ◽  
Modeling And Analysis ◽  
The Difference

Fresh produce has increasingly become an important part of people’s diet. However, the loss of fresh produce in the supply chain has existed for a long time and is difficult to overcome. Some companies use their own information management systems or use information systems built by other companies to release and manage fresh agricultural product information in a timely manner, thereby reducing product loss caused by the “bullwhip effect.” However, this will also bring pressure on construction costs and the risk of information leakage. Based on the evolutionary game model, this paper conducts process modeling and analysis on the behavior of enterprise groups participating in information sharing. It is concluded that the greater the difference between the income obtained through information sharing and the cost of building information system, the higher the likelihood of enterprises participating in information sharing. In addition, the greater the profit from the construction of information platform, the smaller the profit of “free rider,” and the smaller the risk of information leakage, the greater the enthusiasm of enterprises to participate in information sharing. Finally, some suggestions are proposed from the perspective of maximizing supply chain benefits.

A Review on the Application of Neural Networks for Decreasing Bullwhip Effect in Supply Chain

2015 ◽  
Vol 9 (5) ◽  
pp. 438
Author(s):  
Milad Yousefi ◽  
Moslem Yousefi ◽  
Ricardo Poley Martins Ferreira
Keyword(s):  
Neural Networks ◽  
Supply Chain ◽  
Bullwhip Effect

Classification of Operational and Financial Variables Affecting the Bullwhip Effect in Indian Sectors: A Machine Learning Approach

2019 ◽  
Vol 12 (3) ◽  
pp. 171-179 ◽  
Author(s):  
Sachin Gupta ◽  
Anurag Saxena
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Product Life Cycle ◽  
Consumer Preference ◽  
Bullwhip Effect ◽  
Machine Learning Techniques ◽  
Chain Management ◽  
Financial Variables

Background: The increased variability in production or procurement with respect to less increase of variability in demand or sales is considered as bullwhip effect. Bullwhip effect is considered as an encumbrance in optimization of supply chain as it causes inadequacy in the supply chain. Various operations and supply chain management consultants, managers and researchers are doing a rigorous study to find the causes behind the dynamic nature of the supply chain management and have listed shorter product life cycle, change in technology, change in consumer preference and era of globalization, to name a few. Most of the literature that explored bullwhip effect is found to be based on simulations and mathematical models. Exploring bullwhip effect using machine learning is the novel approach of the present study. Methods: Present study explores the operational and financial variables affecting the bullwhip effect on the basis of secondary data. Data mining and machine learning techniques are used to explore the variables affecting bullwhip effect in Indian sectors. Rapid Miner tool has been used for data mining and 10-fold cross validation has been performed. Weka Alternating Decision Tree (w-ADT) has been built for decision makers to mitigate bullwhip effect after the classification. Results: Out of the 19 selected variables affecting bullwhip effect 7 variables have been selected which have highest accuracy level with minimum deviation. Conclusion: Classification technique using machine learning provides an effective tool and techniques to explore bullwhip effect in supply chain management.

The Effects of Menu Costs on Retail Performance: Evidence from Adoption of the Electronic Shelf Label Technology

2020 ◽  
Author(s):  
Ioannis Stamatopoulos ◽  
Achal Bassamboo ◽  
Antonio Moreno
Keyword(s):  
Shelf Life ◽  
Operations Management ◽  
Cost Savings ◽  
Labor Cost ◽  
Price Adjustment ◽  
Menu Costs ◽  
Price Changes ◽  
Product Categories ◽  
Material Costs ◽  
Gross Margins

We use the adoption of electronic shelf labels (ESLs) by an international grocery retailer in 2015 to identify the effects of physical menu costs (i.e., labor and material costs of price adjustment) on retail performance. We find that the installation of ESLs increased gross margins substantially, which implies profit gains that go far beyond labor cost savings. We also explore the mechanism behind this effect. We find that the lift in gross margins was associated with an increase in quantity sold and a decrease in price per unit sold, and that the lift primarily came from low-shelf life product categories. Moreover, we find that more and smaller price changes occurred with ESLs. These additional price changes were mostly price decreases, and they were dispersed in time. Our findings are consistent with reductions in both variable and fixed menu costs (i.e., both costs that scale with the number of products affected and costs that do not). This paper was accepted by Vishal Gaur, operations management.

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