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.

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.

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.

Identifying Spatial Heterogeneity in the Effects of High-Tech Firm Density on Housing Prices:Evidence from Guangdong-Hong Kong-Macao Greater Bay Area,China

Innovation capitalization is a new concept in innovation geography research.Extant research on a city scale has proven that innovation is an important factor affecting housing prices and verified that innovation has a capitalization effect.However,few studies investigate the spatial heterogeneity of innovation capitalization.Thus,case verification at the urban agglomeration scale is needed.Therefore,this study proposes a theoretical framework for the spatial heterogeneity of innovation capitalization at the urban agglomeration scale.Examining the Guangdong-Hong Kong-Macao Greater Bay Area(GHMGBA),China as a case study,the study investigated the spatial heterogeneity of the influence of high-tech firms,representing innovation,on housing prices.This work verified the spatial heterogeneity of innovation capitalization.The study constructed a data set influencing housing prices,comprising 11 factors in 5 categories(high-tech firms,convenience of living facilities,built environment,the natural environment,and the fundamentals of the districts)for 419 subdistricts in the GHMGBA.On the global scale,the study finds that high-tech firms have a significant and positive influence on housing prices,with the housing price increasing by 0.0156%when high-tech firm density increases by 1%.Furthermore,a semi-geographically weighted regression(SGWR)analysis shows that the influence of high-tech firms on housing prices has spatial heterogeneity.The areas where high-tech firms have a significant and positive influence on housing prices are mainly in the GuangzhouFoshan metropolitan area,western Shenzhen-Dongguan,north-central Zhongshan-Nansha district,and Guangzhou—all areas with densely distributed high-tech firms.These results confirm the spatial heterogeneity of innovation capitalization and the need for further discussion of its scale and spatial limitations.The study offers implications for relevant GHMGBA administrative authorities for spatially differentiated development strategies and housing policies that consider the role of innovation in successful urban development.

The Diversification Strategy of Securities Firms in China from the Perspective of Enterprise Operational Sustainability

With the intensified competition in the capital market,the continuous development of internet finance,and the gradual loosening of market regulation,the profit pressure on securities firms relying on traditional business is increasing.In order to seek new profit growth points,many securities firms have ventured into business diversification,but with varying results.From the perspective of enterprise operational sustainability,econometric methods are used to explore the relationship between the diversification and business performance of securities firms in China,putting forward diversification strategies suitable for these firms.

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.

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.

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.

Executive Stock Option, Mediation of Agency Costs and Allocation of Power in Levered Firms

The relationship between options and agency costs in levered firms is studied by modeling the effect of executive stock options on the manager's investment strategy in levered firms. Stock options do not necessarily aggravate agency costs in levered firms. The corporate governance affects agency costs greatly. If debt-holders were entitled to design executive stock options together with stockholders, by allocating power properly between stockholders and debt-holders, firm value could be enhanced greatly. The following way of allocating power between the two parties is proposed: the exercise price should be the weighted average of the stockholders' and debt-holders' suggested exercise prices. The weight allocated to debt-holders is positively related to the amount of debts that debt-holders lend to stockholders.

On the‘ENGO+focal firm’governance strategies of pollution of small and medium suppliers

Presently,the environmental pollution problem,especially that of the small and medium-sized enterprises,has become a bottleneck restricting the high-quality development of China’s economy.It is imperative to accelerate the construction of a collaborative governance system with multiple subject participation.The behavior modes of Environmental Non-governmental Organizations(ENGOs),a key player in environmental care,in collaborating with core enterprises to control pollution from small and medium-sized suppliers should be explored.Therefore,we constructed a collaborative governance system consisting of ENGOs,focal firms and small and medium-sized suppliers.Then a two-stage game model was established to analyze the strategies of the governance system.Specifically,we studied the collaborative green cooperation strategy and antagonistic pressure supervision strategy between ENGOs and focal firms,analyzed factors influencing the strategic choices of each subject,and gave the advantages of the cooperation strategies through further comparisons.The results showed that:Under the cooperation strategy,ENGOs provided knowledge of environmental protection to the focal firms,then both the audit efforts of focal firms and the environmental protection efforts of small and medium-sized suppliers were effectively improved.Since ENGOs could not fully obtain the pollution information of small and medium-sized suppliers or accurately trace it from their downstream focal firms,it was difficult to drive the supply chain’s endogenous governance by this external monitoring of ENGOs,making the effect of pressure supervision strategy limited.The effectiveness of green cooperation strategy was positively correlated with the knowledge absorption capacity of focal firms,the unit product revenue,and the focal firms'violation penalties for small and medium-sized suppliers.When ENGOs'violation penalties for small and medium-sized suppliers were higher,or the reputation loss of focal firms was higher,more unfavorable conditions of green cooperation strategy could be achieved.Accordingly,ENGOs should choose to cooperate with focal firms with strong knowledge absorption ability and high profit per product;focal firms should learn environmental protection knowledge to improve the screening standards and review capabilities,and promote the achievement of green cooperation strategy conditions by strengthening active information disclosure;the government should promote the collaboration between ENGOs and focal firms by issuing environmental guidelines.

Low cost development strategy for oilfields in China under low oil prices

By reviewing the challenges in the development of oilfields in China under low oil prices,this study analyzes the root causes of cost rising,put forwards the low cost oilfield development strategy and specific paths to realize the strategy,and predicts the development potential and prospect of oilfields in China.In addition to the low grade of the reservoir and high development maturation,the fundamental reasons of development full cost rising of oilfields in China are as follows:(1)Facing the problem of resources turning poorer in quality,we have built production capacity at a pace too fast before making enough technical and experimental preparation;(2)technical engineering service model leads to high service cost;(3)team of oil development expertise and matched engineering system cannot satisfy the technical requirements of stabilizing oil production,controlling water cut and fine development.To realize development at low cost,the core is to increase economic recoverable reserves.The concrete paths include:(1)to explore the"Daqing oilfield development culture",improve the ability of leaders in charge of development,and inspire potential of staff;(2)to improve the ability of reservoir dynamics control,and implement precise development by following scientific principles;(3)to speed up integration of water flooding and enhanced oil recovery(EOR)and technological upgrading in order to enhance oil recovery;(4)to innovate key techniques in gas flooding and accelerate the industrial popularization of gas flooding;(5)to break the related transaction barriers and create new management models;and(6)to collaboratively optimize strategic layout and cultivate key oil bases.Although oilfield development in China faces huge challenges in cost,the low-cost development strategy will succeed as long as strategic development of mature and new oil fields is well planned.The cores to lower cost are to control decline rate and enhance oil recovery in mature oil fields,and increase single well productivity through technical innovation and improve engineering service efficiency through management innovation in new oil fields.

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.

Profit Strategy of CNPC＇s Overseas Business in a Oil Price Downturn

In 2016,CNPC managed to achieve a profit even despite the fact that the international oil price was lingering at a decade low.This was the third year in a row for the group to gain profit.Moreover,2016 was a year that marked significant gains for both CNPC’s operational and non-operational business,and the company also did excellent work in terms of international trading。

Price Paradox and Strategic Choice of "Vegetable Basket" in China

By using the analysis method of game theory,this paper analyzes the phenomenon of price paradox of "vegetable basket" in China and its reason as follows:the price paradox of "vegetable basket" in China is that if the vegetable is cheap,it will harm farmers,and if the vegetable is expensive,it will harm people;high-cost logistics,low negotiation status of vegetable growers and cooperation predicament are responsible for price paradox.Based on the theoretical basis of strategic choice-theory of intermediaries,it indicates that the intermediaries can realize effective transaction and save transaction cost.The strategic choice of solving price paradox of "vegetable basket" is put forward as follows:support vegetable growers' cooperatives,reduce transaction cost and raise the negotiation status of vegetable growers;develop the model of connection of agricultural products and supermarkets,and reduce the cost of transport and distribution;innovate upon intermediaries and develop the third-party logistics.

Comparative Analysis of the Effects of False Low-Price Marketing Strategy on Multiple Platforms

In order to make full use of the characteristics of commodity prices,merchants on e-commerce platforms have adopted the low-price marketing strategy.Regular promotional discounts can bring new vitality to the commodity sales market,but extreme discount marketing methods would lead to serious impacts on the sales of competing products,thus affecting the stable development of the online shopping market.The sales data of four electrical products using the false low-price marketing strategy on three e-commerce platforms(Taobao,JD,and Amazon)were used in this study.The sales data from different e-commerce platforms and different time periods were analyzed,and one-way ANOVA was used on the factors affecting the effect of marketing strategy.The results showed that there is a significant difference between the direct marketing of high-priced products and low-priced products on Taobao;the difference between the marketing effects of high-priced products and mid-priced products on JD and Amazon is significant.This analysis would help businesses formulate reasonable marketing strategies and promote the stable development of the online shopping market.

Research on Optimal Configuration of Energy Storage in Wind-Solar Microgrid Considering Real-Time Electricity Price

Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids.In this paper,an improved energymanagement strategy based on real-time electricity price combined with state of charge is proposed to optimize the economic operation of wind and solar microgrids,and the optimal allocation of energy storage capacity is carried out by using this strategy.Firstly,the structure and model of microgrid are analyzed,and the outputmodel of wind power,photovoltaic and energy storage is established.Then,considering the interactive power cost between the microgrid and the main grid and the charge-discharge penalty cost of energy storage,an optimization objective function is established,and an improved energy management strategy is proposed on this basis.Finally,a physicalmodel is built inMATLAB/Simulink for simulation verification,and the energy management strategy is compared and analyzed on sunny and rainy days.The initial configuration cost function of energy storage is added to optimize the allocation of energy storage capacity.The simulation results show that the improved energy management strategy can make the battery charge-discharge response to real-time electricity price and state of charge better than the traditional strategy on sunny or rainy days,reduce the interactive power cost between the microgrid system and the power grid.After analyzing the change of energy storage power with cost,we obtain the best energy storage capacity and energy storage power.

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。

基于混合博弈的综合能源多园区运行策略研究

为了解决多园区综合能源系统联合调度运行后出现的复杂利益关系和隐私保护问题,提出一种基于博弈论的多园区分布式协调优化策略。由综合能源供应商作为上层领导者制定能源价格,引导下层园区运营商优化园区运行,构成主从博弈关系;下层园区以非合作博弈方式各自追求园区运行成本最小,并应用Kriging元模型结合粒子群算法,实现双层博弈模型的求解。通过算例对比分析,证明了所提多园区分布式协调优化策略可降低各园区的运行成本,并且综合能源供应商制定的能源定价策略也为自身带来了收益。