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.

Optimal Pricing Strategy for Data Center Considering Demand Response and Renewable Energy Source Accommodation

With the continuous development of information technology,data centers(DCs)consume significant and evergrowing amounts of electrical energy.Renewable energy sources(RESs)can act as clean solutions to meet this requirement without polluting the environment.Each DC serves numerous users for their data service demands,which are regarded as flexible loads.In this paper,the willingness to pay and time sensitivities of DC users are firstly explored,and the user-side demand response is then devised to improve the overall benefits of DC operation.Then,a Stackelberg game between a DC and its users is proposed.The upper-level model aims to maximize the profit of the DC,in which the time-varying pricing of data services is optimized,and the lower-level model addresses user’s optimal decisions for using data services while balancing their time and cost requirements.The original bi-level optimization problem is then transformed into a single-level problem using the Karush-Kuhn-Tucker optimality conditions and strong duality theory,which enables the problem to be solved efficiently.Finally,case studies are conducted to demonstrate the feasibility and effectiveness of the proposed method,as well as the effects of the time-varying data service price mechanism on the RES accommodation.

Production quality and pricing strategy for substitutable products under comparison effects

Comparison effects have been studied extensively in many fields.In particular,existing operations management articles have discussed the impact of comparison effects on enterprises'production and pricing decisions.Research has also shown that consumers'purchasing decisions are primarily determined by three factors:product quality,selling price,and comparison effects.The current study introduces the concepts of social and temporal comparison effects to examine how comparison effects influence a monopolist's production quality and pricing strategy for substitutable products.Results reveal the following:(1)Setting different prices for even two types of substitutable products with negligible quality differences can divide customers into three groups under the influence of social comparison effects in a single-stage model.(2)The monopolist should avoid using a price discrimination strategy in which products with a short market life cycle have the same quality but different prices.(3)When the market life cycle of products is sufficiently long in the single-product market and the market with two substitutable products,the monopolist's optimal choice in the second stage is to keep production quality constant and increase the selling price.Consequently,the number of buyers does not decrease because of temporal comparison effects.Therefore,the firm increases its revenue.(4)For the market with two substitutable products with quality differences,one approximate optimal strategy for the enterprise in the second stage is to keep the selling price constant with the assumption that product quality cannot be adjusted after the first period.At this point,the consumption situation in the market is the same as that in the first stage.Therefore,when no external constraints exist,the monopolist firm can obtain more benefits in the second stage than in the first stage by exploiting the temporal comparison effects of consumers in the second stage.(5)When consumer identity information can be confirmed in the market,social comparison effects,similar to temporal comparison effects,could help the enterprise increase its price and profit while maintaining product quality.These social and temporal comparison effects constrain consumers.Thus,the number of people who continueto buyproducts does not decrease.

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.

OPTIMAL PRICING STRATEGY TO REDUCE FUEL CONSUMPTION IN ELECTRICITY GENERATION WITH SMART METER

It has been widely recognized that the efficiency of a thermal power system can be improved by technological advancement of electricity generation and manipulation of electricity consumption. The smart meter enables two-way communication between the customers and the electricity generation system. The electricity generation system uses price incentive （i.e. a higher price in the peak period and a lower price in the off-peak period） to shift part of demands from peak to off-peak period under the smart grid environment. Given the fact that fuel consumption in each period is a strictly increasing convex function of power output, we propose two-period and multi-period pricing strategies, and study the effect of different pricing strategies on reducing fuel consumption.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.