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.

Pricing Catastrophe Options with Credit Risk in a Regime-Switching Model

In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space.By using the measure change technique,we derive the price expressions of catastrophe put options.Moreover,we conduct some numerical analysis to demonstrate how the parameters of the model affect the price of the catastrophe put option.

Artificial Intelligence-Based Automated Actuarial Pricing and Underwriting Model for the General Insurance Sector

The Automated Actuarial Pricing and Underwriting Model has been enhanced and expanded through the implementation of Artificial Intelligence to automate three distinct actuarial functions: loss reserving, pricing, and underwriting. This model utilizes data analytics based on Artificial Intelligence to merge microfinance and car insurance services. Introducing and applying a no-claims bonus rate system, comprising base rates, variable rates, and final rates, to three key policyholder categories significantly reduces the occurrence and impact of claims while encouraging increased premium payments. We have enhanced frequency-severity models with eight machine learning algorithms and adjusted the Automated Actuarial Pricing and Underwriting Model for inflation, resulting in outstanding performance. Among the machine learning models utilized, the Random Forest (RANGER) achieved the highest Total Aggregate Comprehensive Automated Actuarial Loss Reserve Risk Pricing Balance (ACAALRRPB), establishing itself as the preferred model for developing Automated Actuarial Underwriting models tailored to specific policyholder categories.

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.

From Finnish Assortment Pricing to Market Economy Using Prices for Sawn Wood and Chips in Reference Bucking

Dominant Finnish assortment pricing gives prices for sawlog and pulp wood volumes. Buyers buck stems to sawlogs using secret price matrices. Agreed dimensions allow wide range of sawlog volumes. Forest owners cannot objectively compare biddings: timber trade is a lottery game. Bucking is analyzed in terms of sawlog, pulp wood, log cylinder, sawn wood, value-weighted sawn wood, and chips. Sawn wood and its value are computed from top diameter of the sawlog. Profit maximization requires buyers to buck logs producing smaller than maximal value, causing dead weight loss. Nominal assortment prices have unpredictable relation to effective stumpage price. Assortment pricing does not meet requirements of market economy. If sawmills linked to pulp mills buck smaller sawlog percentages than independent sawmills, as generally believed, they use higher price for chips in their own harvests than they pay for independent sawmills, indicating imperfect competition for chips. Sawn wood potential pricing is suggested which gives prices for sawn wood and chips coming both from sawlogs and pulp wood in reference bucking which maximizes sawn wood for given minimum and maximum log length and minimum top diameter. Simple algorithm generates feasible bucking schedules from which optimum can be selected using any objective. Pricing produces unit price for all commercial wood utilizing ratio of theoretical sawn wood and commercial volume in stand. Unit price can be compared to stem pricing and could be compared to assortment pricing if assortment pricing would produce predictable sawlog percentages. Sawn wood potential pricing is concrete, transparent, easy to compute, considers stem size and tapering, reduces trading cost and is less risky to buyers than stem pricing. It meets requirements of market economy. Readers can repeat computations using open-source software Jlp22.

Analysis of Drug Medical Insurance Access Pricing Based on the Perspective of Binary Equilibrium

Objective To study the influencing factors in the process of national medical insurance negotiation and drug pricing from the dualistic equilibrium perspective,and to provide reference for the harmonious management of drug pricing in China.Methods Through the literature analysis and policy review,the pricing subject,pricing basis and price control system in the pricing process of medical-accessed medicines were analyzed from the perspective of binary equilibrium and harmonious management.Results and Conclusion It is found that four balances in the drug pricing process,two balances in pricing basis and three balances in price control system need to be considered,respectively.Drug pricing is the key content of national medical insurance access,which is also the hotspot of the policy in the pharmaceutical fields in recent years.Drug pricing not only reflects the value of drugs,but also reflects a lot of top-level designs of binary equilibriums in medical insurance policy.While the rational design of drug pricing requires the joint efforts of the government,pharmaceutical companies and relevant experts to comprehensively consider many equilibriums,so as to improve the relevant systems.

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 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.

Study on the House Market and Pricing——A Case Study of Nanjing's Building Groups

In this paper,some methods of economics and management were used.Based on analysis of the house market structure,the factors influencing the house price,the house pricing methods and strategies were proposed.Then a case in Nanjing was studied,and the results show:firstly,the house market is a monopolistic competitive market,and in some places it is even an oligopoly market;secondly,the cost-plus pricing method is reasonable and scientific,and the specificity is the base of pricing;thirdly,the average price of a building groups in Nanjing should be 8 906$/sq.m.Finally,aiming at the house pricing,some countermeasures and suggestions are put forward in this paper.

Zero-Coupon bond pricing模型的最优系统与群不变解(英文)

将李群理论用于金融问题中出现的数学模型的微分方程,研究了Zero-Coupon bond pricing模型.求出了该模型的单参数李点对称及它相应的群伴随表达式,由此求得该模型允许的一维李群的子代数的最优系统并且利用最优系统构造该模型相应的微分方程的一些特殊的不同类的闭解.

GAMES ANALYSIS OF INSURANCE PRICING UNDER CONSIDERING MORAL HAZARD

This paper first gives an explanation of moral hazard in the insurance field,and then offers a game theory model about insurance pricing according to the non zero sum game analysis between the insurer and the insured when moral hazard exists.On the basis of the game analysis,this paper also presents a lowest pricing formula and studies the cost of moral hazard simultaneously.

Time varying congestion pricing for multi-class and multi-mode transportation system with asymmetric cost functions

This paper considers the problem of time varying congestion pricing to determine optimal time-varying tolls at peak periods for a queuing network with the interactions between buses and private cars.Through the combined applications of the space-time expanded network（STEN） and the conventional network equilibrium modeling techniques,a multi-class,multi-mode and multi-criteria traffic network equilibrium model is developed.Travelers of different classes have distinctive value of times（VOTs）,and travelers from the same class perceive their travel disutility or generalized costs on a route according to different weights of travel time and travel costs.Moreover,the symmetric cost function model is extended to deal with the interactions between buses and private cars.It is found that there exists a uniform（anonymous） link toll pattern which can drive a multi-class,multi-mode and multi-criteria user equilibrium flow pattern to a system optimum when the system＇s objective function is measured in terms of money.It is also found that the marginal cost pricing models with a symmetric travel cost function do not reflect the interactions between traffic flows of different road sections,and the obtained congestion pricing toll is smaller than the real value.

Implementing VMI service pricing strategy for 3PL corporation considering recovery costs

The collector managed inventory(CMI)management idea is introduced based on the comparison of manufacturer and third-party logistics(3PL)implementing vendor managed inventory(VMI)services.Considering recovery costs,the service pricing strategies for 3PL corporations implementing VMI are studied to meet two conditions of participation constraints and incentive-compatibility constraints.The numerical simulation results indicate that the supply chain partners' profits change after considering recovery costs,and the 3PL corporation's profits and the total profits increase first,and then decrease.The retailers' and manufacturers' profits also increase.The total profits of the supply chain have a characteristic of increasing first and then decreasing with the increase of the callback ratio of unsold products.The concrete extremum point is codetermined by price flexibility,service pricing of the 3PL corporation,callback price and callback ratio.

Brain-derived neurotrophic factor signaling in the neuromuscular junction during developmental axonal competition and synapse elimination

During the development of the nervous system,there is an overproduction of neurons and synapses.Hebbian competition between neighboring nerve endings and synapses performing different activity levels leads to their elimination or strengthening.We have extensively studied the involvement of the brain-derived neurotrophic factor-Tropomyosin-related kinase B receptor neurotrophic retrograde pathway,at the neuromuscular junction,in the axonal development and synapse elimination process versus the synapse consolidation.The purpose of this review is to describe the neurotrophic influence on developmental synapse elimination,in relation to other molecular pathways that we and others have found to regulate this process.In particular,we summarize our published results based on transmitter release analysis and axonal counts to show the different involvement of the presynaptic acetylcholine muscarinic autoreceptors,coupled to downstream serine-threonine protein kinases A and C(PKA and PKC)and voltage-gated calcium channels,at different nerve endings in developmental competition.The dynamic changes that occur simultaneously in several nerve terminals and synapses converge across a postsynaptic site,influence each other,and require careful studies to individualize the mechanisms of specific endings.We describe an activity-dependent balance(related to the extent of transmitter release)between the presynaptic muscarinic subtypes and the neurotrophin-mediated TrkB/p75NTR pathways that can influence the timing and fate of the competitive interactions between the different axon terminals.The downstream displacement of the PKA/PKC activity ratio to lower values,both in competing nerve terminals and at postsynaptic sites,plays a relevant role in controlling the elimination of supernumerary synapses.Finally,calcium entry through L-and P/Q-subtypes of voltage-gated calcium channels(both channels are present,together with the N-type channel in developing nerve terminals)contributes to reduce transmitter release and promote withdrawal of the most unfavorable nerve terminals during elimination(the weakest in acetylcholine release and those that have already become silent).The main findings contribute to a better understanding of punishment-rewarding interactions between nerve endings during development.Identifying the molecular targets and signaling pathways that allow synapse consolidation or withdrawal of synapses in different situations is important for potential therapies in neurodegenerative diseases.

垄断势力视角下平台大数据杀熟的价格歧视机理

大数据杀熟问题近年来受到各界的广泛关注,政府出台了一系列有关大数据杀熟治理的政策文件。然而,诸多法规相互交叉、竞合,给监管执行造成了巨大的困难。大数据杀熟愈演愈烈,导致了消费者群体与涉事平台企业之间存在严重的信任危机。为了能更好地理解和治理大数据杀熟,本文深入分析了垄断势力视角下平台大数据杀熟的价格歧视机理。通过分析,揭示了大数据杀熟的经济逻辑为(:1)垄断势力是形成大数据杀熟的源泉(;2)大数据杀熟本质是不公平的高价价格歧视。在以上分析的基础上,本文对大数据杀熟的本质、认识误区和治理思路进行了分析,指出大数据杀熟治理的关键是反垄断和防欺诈。总之,本研究通过对大数据杀熟垄断势力下价格歧视机理的分析,厘清了大数据杀熟与价格歧视和精准营销的区别,从而为正确认识大数据杀熟和有效抑制大数据杀熟提供参考。

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.

Modeling and Design of Real-Time Pricing Systems Based on Markov Decision Processes

A real-time pricing system of electricity is a system that charges different electricity prices for different hours of the day and for different days, and is effective for reducing the peak and flattening the load curve. In this paper, using a Markov decision process (MDP), we propose a modeling method and an optimal control method for real-time pricing systems. First, the outline of real-time pricing systems is explained. Next, a model of a set of customers is derived as a multi-agent MDP. Furthermore, the optimal control problem is formulated, and is reduced to a quadratic programming problem. Finally, a numerical simulation is presented.

THE SPIRIT OF CAPITALISM, NON-EXPECTEDUTILITY AND ASSET PRICING

This paper investigates testable restrictions on the time-series behavior of consumption and asset returns implied by a representative agent model with the spirit of capitalism in which intertemporal preference is represented by a utility function that generalizes conventional, time-additive, expected utility. In the recursive structure of preference, the author examines the implication for cosumptions, portfolio holdings, and stock-market prices when investors accumulate wealth not only for the sake of consumption but also for wealth-induced social status. When investors care about relative social status, the propensity to consume and risk-taking behavior will depend on social standards, and stock prices will be volatible. Hence, the spirit of capitalism seems to be a driving force behind stock-market volatility and economic growth. Because the elasticity df substitution and the coefficient of relative risk aversion are independent and the spirit of capitalism is introduced, the equity premium puzzle can be partially explained in the model.

Water pricing towards sustainability of water resources: a case study in Beijing

The role of water pricing for managing water resources is widely recognized in many areas of the world because of the increasing scarcity of water resources, a high competition between water uses and environmental degradation. Based on the analysis of cost of water, this paper explores which types of cost should be reflected in the water pricing enhancing the sustainability of water resources. The principle of full cost pricing in which the cost should include supply cost, opportunity cost and externalities is proposed as a means to achieve the sustainability of water resources. In a case study of Beijing, low water price is analyzed as one reason for unsustainable water consumption. Thus water pricing justified is necessary and pressing. It is proposed to justify water price in phased manner and eventually towards full cost pricing. The assessment of impacts on water resources by raising water price shows water pricing could alleviate the conflict between water supply and demand. This paper concludes that water pricing can play an effective role in enhancing the sustainability of water resources in Beijing.