Maximizing Supermarket Profits:Data-Driven Strategies for Pricing,Sales,and Forecasting

The actual circumstances of daily life are crucial for the purchasing and pricing strategies of supermarkets.Developing strategies based on these circumstances can assist businesses in ensuring profits and fostering win-win cooperation.This paper explores methods to maximize profit through purchasing and sales strategies.Initially,the relevant data for various categories of vegetables is integrated.Through histograms,their sales patterns are directly understood,highlighting the most popular vegetables.Upon analyzing each vegetable category,it becomes evident that their sales data do not conform to normal distributions.Therefore,Spearman correlation coefficients are calculated,revealing strong correlations between certain categories,such as aquatic roots and edible fungi.A line chart depicting the top ten selling vegetables indicates a noticeable periodicity.Traditional fitting methods struggle to adequately model the sales of each vegetable category and their relationship with cost-plus pricing.To address this,additional factors such as holidays,weeks,and months are incorporated using techniques like random forest regression.This approach yields cost-plus pricing dependence curves that better capture the relationship,while effectively managing noise.Regarding sales volume prediction,the original data displays significant volatility,necessitating the handling of outliers using the threshold method.For missing data,linear interpolation is employed to mitigate the impact of continuous missing values on prediction accuracy.Subsequently,Adam-optimized long short-term memory(LSTM)networks are utilized to forecast incoming quantities for the next seven days.By extrapolating from normal sales volume,market capacity is estimated,allowing for additional sales through discount strategies.This framework has the potential to increase original income by 1.1 times.

Coordinating pricing strategies in supply chain under asymmetric information and disruptions

The coordinating pricing strategies with asymmetric cost information under disruptions are investigated in a one-supplier-one-retailer supply chain system.While the retailer's cost structure is asymmetric information,supply chain pricing contract models(a wholesale price contract and an all-unit quantity discount contract)under asymmetric information are proposed by employing the principal-agent principle in a regular scenario.When the retailer's cost distribution is fluctuated by disruptions,we obtain the optimal emergency strategies of the supply chain under asymmetric information by considering deviation costs and show how to effectively handle the cost uncertainty.Using numerical methods,impacts of cost disruptions on the optimal wholesale price,the retailer price,the order quantity and the expected profits of the retailer,the supplier,as well as the total system are analyzed.It is found that the all-unit quantity discount policy can obtain better performance than the wholesale pricing policy.

The Caching and Pricing Strategy for Information-Centric Networking with Advertisers’Participation

As users’access to the network has evolved into the acquisition of mass contents instead of IP addresses,the IP network architecture based on end-to-end communication cannot meet users’needs.Therefore,the Information-Centric Networking(ICN)came into being.From a technical point of view,ICN is a promising future network architecture.Researching and customizing a reasonable pricing mechanism plays a positive role in promoting the deployment of ICN.The current research on ICN pricing mechanism is focused on paid content.Therefore,we study an ICN pricing model for free content,which uses game theory based on Nash equilibrium to analysis.In this work,advertisers are considered,and an advertiser model is established to describe the economic interaction between advertisers and ICN entities.This solution can formulate the best pricing strategy for all ICN entities and maximize the benefits of each entity.Our extensive analysis and numerical results show that the proposed pricing framework is significantly better than existing solutions when it comes to free content.

Revenue management method and critical techniques of railway passenger transport

Purpose–Revenue management(RM)is a significant technique to improve revenue with limited resources.With the macro environment of dramatically increasing transit capacity and rapid railway transport development in China,it is necessary to involve the theory of RM into the operation and decision of railway passenger transport.Design/methodology/approach–This paper proposes the theory and framework of generalized RM of railway passenger transport(RMRPT),and the thoughts and methods of the main techniques in RMRPT,involving demand forecasting,line planning,inventory control,pricing strategies and information systems,are all studied and elaborated.The involved methods and techniques provide a sequential process to help with the decision-making for each stage of RMRPT.The corresponding techniques are integrated into the information system to support practical businesses in railway passenger transport.Findings–The combination of the whole techniques devotes to railway benefit improvement and transit resource utilization and has been applied into the practical operation and organization of railway passenger transport.Originality/value–The development of RMRPT would provide theoretical and technical support for the improvement of service quality as well as railway benefits and efficiency.

Price leadership strategy or branding strategy:an empirical test of indigenous Chinese exporters

The effects of price leadership strategies and branding strategies on the export performance of indigenous Chinese exporters with a focus on developing country markets and developed country markets are examined based on the principles of strategy-environment co-alignment and marketing segmentation theory. Findings suggest that when focusing on developing country markets, the use of a branding strategy is more likely to enhance export performance. When focusing on developed country markets, neither the use of a price leadership strategy nor the use of a branding strategy enhances export performance. Finally, theoretical and managerial implications of the findings are discussed.

Mobile telecommunication companies’investment and pricing strategies for content service

Several mobile telecommunication companies(MTCs),such as AT&T,Verizon,and China Mobile,are investing in content services to drive continued growth as the telecom industry has become saturated.In this study,we investigate the competition between two MTCs,one of which(MTC 1)provides both data and content services,while the other(MTC 2)provides only data services.We propose a two-stage game-theoretic model to analyze the two MTCs'optimal pricing strategies for data service and content service as well as the investment strategy for the content service.Our analysis reveals that a higher value of value-added service offered by MTC 1 will incentivize it to raise its subscription fee for the content service and induce both MTCs to reduce the prices of their data services,which results in an increased demand for the content service and a decreased demand for MTC 2's data service.As MTC 1 invests further in the quality of the content service,it would benefit from increasing the subscription fee for the content service,and the two MTCs should increase the subscription fee for the data service.However,compared to the decisions in the scenario where MTC 1 does not provide content service,the provision of this service by MTC 1 leads to a lower subscription fee for the two MTCs'data services,an increase in the demand for MTC 1's data service,and a decrease in the demand for MTC 2's data service.These findings reveal that regularly monitoring market competition,as well as adjusting pricing strategies based on market scenarios and the value of services,can enhance competitiveness and long-term profitability for MTCs.

Optimal pricing and production decisions in a supply chain with e-marketplace

The concept of the e-marketplace is introduced.Considering a supply chain with a single manufacturer who sells a single item in an e-marketplace,an analytical model for the use of the e-marketplace in a supply chain is provided.Assuming the market demand is stochastic and price-dependent,the conditions under which the manufacturer and the e-marketplace owner share the market in equilibrium is developed.The existence and uniqueness of the optimal selling price,quantity and transaction percentage are proved.An integrated supply chain is put forward,and then the efficiency of supply chain coordination is studied by comparing the integrated supply chain with the decentralized supply chain.To gain further insights on the theoretical models,extensive simulations are then carried out.

Dynamic Pricing Model of E-Commerce Platforms Based on Deep Reinforcement Learning

With the continuous development of artificial intelligence technology,its application field has gradually expanded.To further apply the deep reinforcement learning technology to the field of dynamic pricing,we build an intelligent dynamic pricing system,introduce the reinforcement learning technology related to dynamic pricing,and introduce existing research on the number of suppliers(single supplier and multiple suppliers),environmental models,and selection algorithms.A two-period dynamic pricing game model is designed to assess the optimal pricing strategy for e-commerce platforms under two market conditions and two consumer participation conditions.The first step is to analyze the pricing strategies of e-commerce platforms in mature markets,analyze the optimal pricing and profits of various enterprises under different strategy combinations,compare different market equilibriums and solve the Nash equilibrium.Then,assuming that all consumers are naive in the market,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.By comparing and analyzing the optimal pricing and total profit of each enterprise under different strategy combinations,the subgame refined Nash equilibrium is solved.Finally,assuming that the market includes all experienced consumers,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.

NOVEL POWER CONTROL GAME VIA PRICING ALGORITHM FOR COGNITIVE RADIOS

To compensate the service providers who have paid billions of dollars to use spectrum and to satisfy secondary users' requirements in cognitive radios, a Non-cooperative Power Control Game and Pricing algorithm (NPGP) is proposed. Simulation results show that the proposed algorithm can regulate the secondary users' transmitter powers, optimally allocate radio resource and increase the total throughput effectively.

Enhancing customers prevention efforts:An incentive feedback mechanism design

To improve the inefficient prevention caused by customers unwillingness to adopt prevention strategies in health management,an incentive feedback mechanism that is based on game theory and contract design theory is introduced.The conditions for making customers and health maintenance organizations(HMOs)willing to participate in the proposed mechanism are given.A dual nonlinear programming model is used to identify the optimal prevention effort of customers and the pricing strategy of HMOs.Results show that to generate increased benefits,HMOs need to consider cost sharing when customers are not familiar with the proposed health services.When health services are gradually accepted,the cost sharing factor can be gradually reduced.Simulation shows that under random circumstances in which the market reaches a certain size,the proposed method exhibits a positive network externality.Motivated by network externality,HMOs only need to make their customers understand that the larger the number of participants,the greater the utility of each person.Such customers may then spontaneously invite others to purchase insurance.

Modelling time series properties of Australian lending interest rates

The purpose of this paper is to examine the time series properties of Australian residential mortgage interest rates, and in doing so, establish whether or not selected home loan rates （product-level monthly home loan interest rates for CBA） exhibit the expected cyclical and seasonal variations and whether seasonality, if present, is stochastic or deterministic. In particular, due to a well established presence of cyclicality in financial markets＇ interest rates and strong correlation between financial markets＇ interest rates and home loan interest rates, the paper presumes that cyclicality is also to be found in home loan interest rates. Furthermore, the paper tests the hypothesis that home loan interest rates, for selected products, exhibit the three identified （＂Spring＂, ＂Autumn＂ and ＂The end of the Financial Year＂） season-related interest rate reductions. The paper uses a structural time series modelling approach and product-level home loan interest rates data from one of the biggest banks in Australia, Commonwealth Bank of Australia （CBA）. As expected, the results overall confirm the existence of cyclicality in home loan interest rates. With respect to the seasonality of home loan interest rate, although most of the analysed variables show the presence of statistically significant seasonal factors, the majority of the statistically significant seasonal factors observed cannot be attributed to any of the three considered seasonal effects.

ReasOns Analysis and Countermeasures Research on Enterprise Sinking Kamikaze Pricing

The penetration pricing strategy is discussed in this paper firstly, and then the Kamikaze pricing and relevant problems are analyzed. Finally some countermeasures are presented for enterprise to avoid sinking Kamikaze pricing.

Study on the Strategy of Pricing for Enterprise Merger and Acquisition

Enterprise merger and acquisition is one of the property right exchanges. This paper researches the strategy of pricing for enterprise merger and acquisition, displays finance decision-making model, program and method.

A Practical Framework for Pricing of Backup Reserve and Wheeling in Power System

This paper presents a practical pricing model for backup reserve and wheeling, which attains a balanced strategy that ensures perceived benefits to both the buyer and the seller. The model and the associated computerized algorithm deal collectively with diverse issues, including： （1） fulfilling local firm real （and reactive） power demand requirements, （2） fulfilling local power reserve requirements, （3） buying firm real （and reactive） power from the grid, （4） buying reserve power from the grid, （5） exporting firm real （and reactive） power demand to remote load centers via the grid, （6） exporting reserve power via the grid, （7） wheeling of firm power demand to remote owned sites using the grid, and （8） wheeling reserve power to remote owned sites using grid. Practical implementation features of the computerized algorithms are also discussed with an illustrative case example.

Power ＂Smart Pricing＂ with and without Smart Meters

Over the past several years, the Taiwan Power Company has launched two smart pricing programs to assess the demand response of residential customers： the TOU （time-of-use） rate scheme and the DRI （demand reduction incentive） scheme. This paper discusses these two programs and evaluates their respective performances. We develop an efficient approach based on marginal cost pricing to redesign the TOU rate scheme. In our finding, the TOU price levels could be revised to encourage more customers to participate by enlarging the price gap. Moreover, the DRI scheme can be further improved in order to reach an efficient win-win solution among customers, the utility and society. This can be achieved via a careful design of incentive tariff discounts to take account of the time-of-use or location-specific features of the power supply/demand condition.

Dual Channel Pricing of Large Fresh Chain Stores Considering Distribution Costs under Split Quotation

After large fresh food chain stores have opened online channels,distribution costs are a key factor affecting consumers'online buying behavior,which affects dual-channel pricing.This paper studies the dual-channel pricing strategy of large fresh food chain stores on the premise of dividing the quotation,considering the consumer's acceptance of online channels and the sensitivity to distribution costs.The research found that the optimal pricing of online channels is lower than that of retail channels.The optimal pricing of online channels is positively correlated with the acceptance of online channels,and negatively correlated with the sensitivity of consumer distribution costs.Moreover,after retailers have opened online channels,the market scale has expanded compared with traditional retail channels.Finally,numerical experiments are used to analyze the influence of various influencing factors on retailers'decision-making.

Optimal Dispatch and Pricing of Industrial Parks Considering CHP Mode Switching and Demand Response

Industrial parks(IPs)play a crucial role in facilitating economic efficiency and comprehensive energy utilization in the industrial age.At the same time,multi-energy coupling and management of various types of energy in IP have become serious challenges.In this paper,combined heat and power unit(CHP)model considering operation mode switching characteristics is formulated by exploring its internal composition to improve output flexibility of the energy supply side.Then,heat and electricity integrated energy system(HE-IES)optimal dispatch and pricing model are established,taking electricity and heat demand response strategy and steam thermal inertia property into account.Based on the above models,a mixed-integer bilinear programming framework is designed to coordinate the day-ahead operation and pricing strategy of the HE-IES in the IP.The scenario study is carried out on a practical industrial park in Southern China.Numerical results indicate the proposed mechanism can effectively improve IP’s energy utilization and economic efficiency.

PRICING STRATEGIES IN A SUPPLY CHAIN WITH MULTI-MANUFACTURER AND A COMMON RETAILER UNDER ONLINE REVIEWS

Online reviews play an important role in consumer purchasing behavior when shopping online, and in turn affect pricing strategies of sellers. We consider a supply chain consisting of three competitive manufacturers and an e-tailer, which sells multiple substitutable products procured from different manufacturers. Considering reviews in terms of quality information and fit information, we study the effect of online reviews on consumers＇ purchasing decisions as well as pricing strategies of manufacturers and the e-retailer. Through modelling customer choice with online reviews based on neo-Hoteling model and solving Stackelberg game composed by manufacturers and e-tailer, we obtain the optimal equilibrium prices of manufacturers and the e-tailer. And we distinguish two kinds of effect from online reviews： effect of the opinion bias in product quality and effect of the match informativeness. Furthermore, compared to the case without online reviews, we find online reviews improve a manufacturer＇s optimal wholesale price, profit as well as the retailer＇s optimal retailing price, when the adjusted quality revealed by reviews is high; however, online reviews can improve the e-tailer＇s optimal profit, only when the standard deviation of products＇ quality revealed by reviews is large enough. Last, we get that the increase of competing manufacturers＇ quantity would change the dominance between two kinds of effect from reviews on supply chain members.

Optimal Pricing Strategies for a Manufacturer and a Value-Adding Retailer in a Dual-Channel Environment

In this paper,we study a supply chain that consists of a manufacturer and a value-adding retailer that sell a product to customers through dual channels,i.e.a traditional channel(TC)and an online channel(OC).Observing that in practice,the manufacturer may or may not offer an OC guide price to the retailer and/or act as the leader in the supply chain,we discuss and compare two practical pricing strategies,with and without an OC guide price,under two different power configurations based on which member of the supply chain acts as the leader.Our results show that if the manufacturer does not provide a guide price,the retailer might/might not set a higher TC price than the two OC prices,depending on the level of migration effectiveness and the potential market demand.However,if the manufacturer does provide a guide price,the retailer will always charge a higher TC price than the guide price(or the two OC prices)when the retailer acts as the leader.Moreover,we show that the two players in the supply chain might or might not prefer the pricing strategies with an OC guide price.Our results also indicate that migration effectiveness harms the retailer's profit,and the manufacturer may benefit from mild competition between the two channels.Finally,we show that regardless of whether the manufacturer chooses to offer an OC guide price or not,both the manufacturer and the retailer prefer to act as the follower for high migration effectiveness and the profit of the supply chain will increase when the retailer acts as the leader for low migration effectiveness.

HOW DOES THE RETAILER MAKE PRICING DECISION WHEN CONSUMERS HAVE JUSTICE REFERENCE PRICE

A series of studies demonstrate that consumers have fairness judgments about the retailer＇s price which will impact their shopping decisions. Thus, it is necessary for the retailer to take consumers＇ fairness concerns into account when setting his pricing policies. We assume that when the retailer＇s price is lower than a consumer＇s justice reference price, the consumer is likely to sense a positive price unfairness that will lead to increased consumer utility, and when the retailer＇s price is higher than a consumer＇s justice reference price, the consumer is likely to sense a negative price unfairness-that will have a negative effect on consumer utility. According to the information conditions of the consumers＇ justice reference price, the retailer should consider three situations： certain information, random information and partial information. In all situations, we show that the retailer has a unique optimal pricing strategy. Finally, through numerical examples, we find that our distribution-free policies perform almost the same as the results under the distributions that maximize the entropy. Our results reveal that it is important for the retailer to consider consumers＇ fairness concerns, otherwise he may suffer losses when Pc is very small.