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.

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.

Altruism and Pricing Strategy in Dual-Channel Supply Chains

With the development of behavioral operational management, human behavior such as altruism, fairness and trust has received considerable attention. This paper studies the effect of altruism on retailer’s and manufacturer’s pricing strategy in two classic dual-channel supply chains by presenting Stackelberg game models. The analysis shows that the player’s altruism preference strongly affects their pricing strategies. The more altruistic one player is, the more profits the other player obtains. Moreover, the effect of manufacturer’s altruistic preference is larger than that of retailer’s. In addition, online price is always lower than offline price in dual-channel supply chain, which still holds true considering altruism. The results also reveal that the product web-fit has significant effect on the player’s optimal pricing strategies. The more compatible with online market the product is, the lower the retail price is set, and the more profit the manufacturer obtains whereas the less the retailer gets.

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.

Option Pricing and Hedging under a Markov Switching Lévy Process Model

In this paper, we consider a Markov switching Lévy process model in which the underlying risky assets are driven by the stochastic exponential of Markov switching Lévy process and then apply the model to option pricing and hedging. In this model, the market interest rate, the volatility of the underlying risky assets and the N-state compensator,depend on unobservable states of the economy which are modeled by a continuous-time Hidden Markov process. We use the MEMM(minimal entropy martingale measure) as the equivalent martingale measure. The option price using this model is obtained by the Fourier transform method. We obtain a closed-form solution for the hedge ratio by applying the local risk minimizing hedging.

Dynamic Pricing Strategies Using Artificial Intelligence Algorithm

Pricing strategies can have a huge impact on a company’s success. This paper focuses on the advantages and disadvantages of using artificial intelligence in dynamic pricing strategies. A good understanding of the possible benefits and challenges will help companies to understand the impact of their chosen pricing strategies. AI-driven Dynamic pricing has great opportunities to increase a firm’s profits. Firms can benefit from personalized pricing based on personal behavior and characteristics, as well as cost reduction by increasing efficiency and reducing the need to use manual work and automation. However, AI-driven dynamic rewarding can have a negative impact on customers’ perception of trust, fairness and transparency. Since price discrimination is used, ethical issues such as privacy and equity may arise. Understanding the businesses and customers that determine pricing strategy is so important that one cannot exist without the other. It will provide a comprehensive overview of the main advantages and disadvantages of AI-assisted dynamic pricing strategy. The main objective of this research is to uncover the most notable advantages and disadvantages of implementing AI-enabled dynamic pricing strategies. Future research can extend the understanding of algorithmic pricing through case studies. In this way, new, practical implications can be developed in the future. It is important to investigate how issues related to customers’ trust and feelings of unfairness can be mitigated, for example by price framing.

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.

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.

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.

Road Pricing Design Based on Game Theory and Multi-agent Consensus

Consensus theory and noncooperative game theory respectively deal with cooperative and noncooperative interactions among multiple players/agents. They provide a natural framework for road pricing design, since each motorist may myopically optimize his or her own utility as a function of road price and collectively communicate with his or her friends and neighbors on traffic situation at the same time. This paper considers the road pricing design by using game theory and consensus theory. For the case where a system supervisor broadcasts information on the overall system to each agent, we present a variant of standard fictitious play called average strategy fictitious play(ASFP) for large-scale repeated congestion games.Only a weighted running average of all other players actions is assumed to be available to each player. The ASFP reduces the burden of both information gathering and information processing for each player. Compared to the joint strategy fictitious play(JSFP) studied in the literature, the updating process of utility functions for each player is avoided. We prove that there exists at least one pure strategy Nash equilibrium for the congestion game under investigation, and the players actions generated by the ASFP with inertia(players reluctance to change their previous actions) converge to a Nash equilibrium almost surely. For the case without broadcasting, a consensus protocol is introduced for individual agents to estimate the percentage of players choosing each resource, and the convergence property of players action profile is still ensured. The results are applied to road pricing design to achieve socially local optimal trip timing. Simulation results are provided based on the real traffic data for the Singapore case study.

High Altitude Frogs (Rana kukonoris) Adopt a Diversified Bethedging Strategy in the Face of Environmental Unpredictability

Environmental unpredictability can influence strategies of maternal investment among eggs within a clutch. Models predict that breeding females should adopt a diversified bet-hedging strategy in unpredictable environments, but empirical field evidence from Asia is scarce. Here we tested this hypothesis by exploring spatial patterns in egg size along an altitudinal gradient in a frog species （Rana kukunoris） inhabiting the Tibetan Plateau. Within-clutch variability in egg size increased as the environment became variable （e.g., lower mean monthly temperature and mean monthly rainfall at higher altitudes）, and populations in environments with more unpredictable rainfall produced eggs that were smaller and more variable in size. We provide support for a diversified bet-hedging strategy in high-altitude environments, which experience dynamic weather patterns and therefore are of unpredictable environmental quality. This strategy may be an adaptive response to lower environmental quality and higher unpredictable environmental variance. Such a strategy should increase the likelihood of breeding success and maximize maternal lifetime fitness by producing offspring that are adapted to current environmental conditions. We speculate that in high-altitude environments prone to physical disturbance, breeding females are unable to consistently produce the optimal egg size due to physiological constraints imposed by environmental conditions （e.g., duration of the active season, food availability）. Species and populations whose breeding strategies are adapted to cope with uncertain environmental conditions by adjusting offspring size and therefore quality show a remarkable degree of ability to cope with future climatic changes.

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.

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.

商品期货市场套期保值与价格发现功能关联机制研究——基于市场流动性与参与者结构视角

基于市场流动性与参与者结构视角,探究在商品期货市场发展中套期保值与价格发现功能关联机制,并使用2011年1季度—2022年4季度大连商品交易所12个品种的面板数据进行实证检验。结果表明:期货市场价格发现功能通过市场流动性中介促进套期保值功能,而参与者结构调节期货市场功能关联强度;农产品期货市场的套期保值功能发挥整体较强,工业品期货市场的功能关联较强。为此,建议期货市场在提高市场流动性的同时优化参与者结构,进一步促进期货市场功能协同发挥。

基于经济学视角的数据要素定价研究

随着数字化时代的到来,数据作为一种重要的生产要素正在引起越来越多经济学家的关注。数据要素定价作为一个关键议题,涉及数据的价值评估、交易和分配等方面的研究。首先,结合经济学的视角,阐释数据要素的非竞争性、非排他性、外部性、经济增值性、网络效应以及要素的价格决定理论。其次,对比定量评估、综合市场与非常因素评估,并讨论定价协商、拍卖、订阅与授权等市场机制。再次,基于供需分析、边际分析、效用分析、市场结构阐述经济学理论在数据要素定价中的应用。最后,讨论在经济学视角下数据要素定价面临的挑战,并提出优化数据市场的机制设计、考虑非经济因素的影响、重视数据隐私与知识产权保护、结合新兴技术的应用以及积极开展跨学科研究,以期为我国数据要素及其流通理论体系的建立、数据要素市场体系的建立和发展提供理论支撑。

Effect of the Policies to Prevent Drug Shortage and Stabilize Drug Prices in Medical Institutions

Objective To evaluate the effect of some policies to prevent drug shortage and stabilize drug prices,and to provide reference for improving relevant policies.Methods With a combination of random stratified sampling and quota sampling,532 medical institutions in 20 provinces were selected to carry out questionnaire surveys.Then,a comparative analysis was made to study the changes of drugs on the shortage list and drugs on non-shortage list before and after the release of the policy of ensuring supply and stabilizing prices.Results and Conclusion The policy played an important role in curbing the growth of drug shortage in the medical institutions,but it did not curb the growth of drugs on non-shortage list.Besides,the drugs on non-shortage list showed an overall fluctuation and upward trend.Meanwhile,from the perspective of drug prices,the price stability problem of drugs on the shortage list and on the non-shortage list became more serious,and the average price increase was 256% and 239%,respectively.The implementation of policies related to the supply and price stability of drugs prevents the growth trend of drug shortages in the list of medical institutions,which has been recognized by most medical institutions.However,there is an increasing trend in the number of drugs on non-shortage list.In addition,the price increase of drugs on both the shortage list and non-shortage list is severe.Some medical institutions report that they have difficulties in using the information reporting system of drug shortage and the classification,grading and the alternative use of drug shortages.It is recommended to strengthen the management of price stabilization of drugs on the shortage list.Further attention should be paid to the supply and price stabilization of drugs on non-shortage list.At the same time,trainings in the classification and substitution of drug shortage and information reporting system should be actively organized,thus comprehensively improving the capabilities of medical institutions at all levels to deal with the problem of drug shortage.

基于效果定价模式的网络直播广告定价决策研究

网络直播广告作为一种新型营销方式快速发展,优化直播广告运营主体努力水平及定价策略是一项值得深入研究的课题。本文基于广告投放效果的两种定价模式,构建了包含两个广告商和一个主播的网络直播广告定价决策模型,探索广告商与主播的最优努力水平选择及广告定价策略。研究发现:CPW(cost per watch)定价模式下,广告商承担了消费者是否购买的不确定性风险,当消费者敏感性系数偏低时,广告商会提交较低的出价,且B/D两类广告商赢得竞拍的概率相等;对比CPW模式,在CPA(cost per action)定价模式下广告商的努力水平更低,且CPA定价模式中B型(品牌型)广告商赢得竞拍的概率更大,但赢得竞拍的广告商边际利润往往较低;与广告商相反,主播在CPA定价模式下的收益大于CPW,且随消费者敏感性系数的增加,两种定价模式下的收益差逐渐增大;CPW定价模式下预期观看直播的用户量和购买率均高于CPA,网络直播市场倾向于从CPW广告定价合同中获得较大收益。

衍生品使用对股价波动性的影响——基于中国上市公司的实证研究

理论上,使用衍生品进行套期保值,对冲经营上面临的汇率、大宗商品价格等的价格波动风险,有助于公司的持续稳定经营,从而实现股票价格的稳定性。然而,衍生品的不当使用也会带来额外风险,冲击公司的经营,导致股票价格波动加剧。随着我国衍生品市场的发展及制度法规的落实完善,利用衍生品工具进行套期保值的上市公司群体越来越大。本文以A股上市公司为样本,利用双向固定效应模型研究了上市公司衍生品使用对股价波动率的影响。结果显示上市公司使用衍生品能够显著降低股价波动率,主要是通过降低特质波动率实现的。