Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network

This paper establishes a short-term prediction model of weekly retail prices for eggs based on chaotic neural network with the weekly retail prices of eggs from January 2008 to December 2012 in China.In the process of determining the structure of the chaotic neural network,the number of input layer nodes of the network is calculated by reconstructing phase space and computing its saturated embedding dimension,and then the number of hidden layer nodes is estimated by trial and error.Finally,this model is applied to predict the retail prices of eggs and compared with ARIMA.The result shows that the chaotic neural network has better nonlinear fitting ability and higher precision in the prediction of weekly retail price of eggs.The empirical result also shows that the chaotic neural network can be widely used in the field of short-term prediction of agricultural prices.

Uniformity Analysis for Index of Retail Price

Using the Hodges Ajne testing method, the uniformity of China retail price index was tested. The result, that population is submitting to uniform distribution, was obtained. The uniformity of CRPI indicates that the general price level is stable in the Ninth Five Year Plan. Finally, the reasons causing the uniformity was analyzed.

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.

Investing and Pricing with Supply Uncertainty in Electricity Market:A General View Combining Wholesale and Retail Market

Renewable energy,such as wind and solar energy,may vary signifi cantly over time and locations depending on the weather and the climate conditions.This leads to the supply uncertainty in the electricity(power) market with renewable energy integrated to power grid.In this paper,electricity in the market is classified into two types:stablesupply electricity(SSE) and unstablesupply electricity(USE).We investigate the investment and pricing strategies under the electricity supply uncertainty in wholesale and retail electricity market.In particular,our model combines the wholesale and retail market and capture the dominant players,i.e.,consumers,power plant(power operator),and electricity supplier.To derive the market behaviors of these players,we formulate the market decision problems as a multistage Stackelberg game.By solving the game model,we obtain the optimal,with closedform,wholesale investment and retail pricing strategy for the operator.We also obtain the energy supplier's best price mechanism numerically under certain assumption.We fi nd the price of SSE being about 1.4 times higher than that of USE will benefi t energy supplieroptimally,under which power plant's optimal strategy of investing is to purchase USE about 4.5 times much more than SSE.

Analysis on the Comparison of Vegetable Price

In 2010,the garlic,bean and ginger became more expensive than ever,which made some people's life harder.In response to such phenomena,the retail price and wholesale price at the producers' end,the retail price and wholesale price at distributors' end,and consumption related data(disposable income,consumption expenditure,fresh vegetables amount from 2004 to 2011 were compared and analyzed in this paper.Results showed that the average price(selling price,wholesale price and retail price) of five kinds of vegetables generally rose.There was certain differences in the price change range.Since 2004,especially in 2009 the vegetable prices had been so high that it had influenced the life of low income families in China.

Optimal Price Strategy under Price-Matching Policy

The paper explores the optimal price strategy under the price-matching policy. First, the paper formulates the demand function under the price match policy and then discovers the retailer’s best response facing the price-matching pressure. From the theoretical analysis, we discover how the number of retailers plays an important role during the competition. When only two retailers are involved, the final prices may not converge to a single value. However, when more retailers are involved, the final price will converge to a single value. We also use numerical studies to illuminate the change of the prices over the time period, the sensitivity of the final price to the increment/decrement of initial prices. Finally, we provide managerial suggestions to both producers and retailers.

In October, the consumer price of China’s clothing products rose 1.4% year-on-year

According to data from the National Bureau of Statistics,in October 2019,the retail value of apparel products in China's units above the designated size fell by 0.3%year-on-year,which was 5.2 percentage points lower than the same period of the previous year,and 3.6 percentage points lower than the last month of 2019.

监管型小股东对股价同步性的影响研究

基于2016年2月中证中小投资者服务中心(简称投服中心)持股行权试点的研究场景,采用双重差分法考察投服中心对公司股价同步性的影响。研究发现:作为监管型小股东,投服中心持股行权降低了公司的股价同步性。进一步地,投服中心对股价同步性的影响在分析师关注度较低、媒体报道较少时更显著。机制检验显示,投服中心成立后上市公司的信息披露质量提高,管理层业绩预告质量改善,产生了信息效应;投服中心行权引起媒体和监管部门的关注,可减少大股东的利益侵占行为,提高中小股东参与股东大会的积极性,发挥出治理效应。

供应中断风险下竞争零售商的采购与定价决策

针对由两个竞争供应商和两个竞争零售商组成的二级供应链,研究供应中断风险下企业的最优决策问题。考虑供应商的供应中断之间存在相关性以及零售商的响应定价,建立供应商定价、零售商决定采购量、零售商定价的三阶段博弈模型,得到供应商和零售商各自的最优策略。研究发现:①虽然供应商之间相关性的增加削弱了双源采购的风险分散好处,但加剧了供应商之间的价格竞争,使得零售商的利润增加,因此零售商会选择相关性更高的两个供应商。②零售商之间的竞争越激烈,供应的可靠性越重要,于是零售商向可靠性更高的供应商采购更多的数量。③供应商提高其可靠性不仅有利于供应商自身,而且对零售商也有益。

双寡头在线零售商的退货运费险策略研究

在线零售商提供的免费退货运费险能有效解决顾客线上购物的退货风险,提升其购买意愿,但同时也提高了退货率,增加了在线零售商的运营成本,因此退货运费险受到广泛关注。文章假设双寡头在线零售商分别向同一市场的顾客销售高、低质量的产品,同时决策是否向顾客免费提供退货运费险,在4种策略组合下分别构建以零售商各自利润最大化的数学模型,得到最优零售价格、需求及利润,求出两零售商的纳什均衡策略,并对保费等关键参数进行了灵敏度分析。

多渠道零售产品定价与交付的研究进展及展望

线上渠道或数字渠道(如移动网络、社交媒体)的出现加速了零售商业模式的转型,如何在多渠道零售下进行产品的定价与交付,以满足消费者的多元化需求,使零售商保持竞争优势是一个日益受到关注的研究主题。通过对多渠道零售产品定价与交付领域相关文献进行系统回顾,归纳了研究方法及其适用领域,分析了热点主题及主要的研究进展,有助于厘清多渠道零售产品定价与交付领域研究的发展趋势,为后续相关研究打下基础。

资金约束下双渠道逆向供应链零售商的定价与融资决策

针对由制造商和资金约束零售商组成的双渠道逆向供应链,研究银行贷款和股权融资下零售商的定价与融资决策。首先,构建两种融资决策下的Stackelberg模型,求解并分析制造商和零售商的最优决策和利润;然后,分析不同情形下零售商的定价与融资决策。研究发现:银行贷款利率和持股比例分别对零售商回收价格具有非线性负向和正向的影响,对零售商回收数量的影响则相反。在两种融资情形下,零售商回收价格和融资决策应综合考虑银行贷款和持股比例。

动态价格约束下生鲜无人零售点选址-路径方法研究

“新零售”创新了生鲜无人零售的渠道和销售模式,通过研究网络化无人售货的技术优势,引入在线动态定价机制,解决了生鲜无人销售品控难、客户黏度低的问题,有效减低了系统综合成本;同时构建了一种面向生鲜商品的无人零售的干线和支线混杂配送模型,在多目标求解、问题解耦和PSO全局优化等方面进行突破,建立了一种动态价格约束下的带时间窗选址-路径二级运输模型(2E-dPLRPTW),并进行了案例验算,确认该方法能有效提升生鲜商品无人售卖的效益。

创新电力零售市场价格机制研究

【目的】在电力零售市场发展尚不充分的情况下,为了合理传导批发市场价格,降低市场化用电成本,预防售电公司风险。【方法】首先结合山西、广东等地区的情况,分析了我国电力零售市场的现状及存在的问题;其次从合理设计零售套餐、建立专项账户、建议电力零售市场的收益约束和奖励机制、建立相应的清算机制等几方面提出了创新零售电力市场价格机制。【结论】利用某省的数据测算了电力零售价格的上限及奖励机制的有效性。

考虑策略型消费者后悔行为的易逝品零售商最优库存策略

易逝品零售商降价销售时,策略型消费者往往会经历高价后悔和缺货后悔,这两种后悔行为均会降低他们的购买效用,从而影响零售商库存决策和利润。因此,本文分别研究了价格外生和内生两种情形下高价后悔和缺货后悔对策略型消费者行为以及零售商库存决策和利润的影响。研究表明,对于高利润产品,零售商应实施瞄准短视型消费者(target myopic consumers,TMC)的策略。相反,对于低利润产品,零售商应实施瞄准短视和策略型消费者(target both myopic and strategic consumers,TBC)的策略。此外,随着高价(缺货)后悔水平的增加,策略型消费者原来认为是低(高)利润的产品,现在可能认为是高(低)利润产品,因此零售商最优策略可能会相应地改变。其次,对于低利润产品,当高价(缺货)后悔显著时,后悔行为对零售商产生负(正)影响,且高价后悔和缺货后悔呈现相反的作用;对于高利润产品,后悔行为不对零售商造成影响。再次,对于低利润产品,高价后悔加剧了(缺货后悔缓解了)策略型消费者行为的负影响;对于高利润产品,后悔行为不影响策略型消费者行为的负影响。最后,当零售商拥有全价决策权时,零售商总是能够利用决策全价的优势来消除高价后悔的负影响或发挥缺货后悔的正影响。

碳约束下基于双重博弈的电力零售商售电价格决策优化

在碳约束下,市场中的多零售商竞争售电和多用户购电给电力零售商制定售电价格提高自身利润带来了挑战。为解决零售商售电价格制定的问题,提出了在碳约束条件下多电力零售商竞争售电和多用户购电的双重博弈价格决策优化模型。首先,建立各市场参与者的决策模型。其次,建立并描述电力零售商的双重博弈架构,其中,各电力零售商间构成非合作博弈,各零售商与各用户间构成主从博弈。然后,采用循环迭代嵌套IPOPT求解器的方法求解零售商的双重博弈问题。最后,通过仿真算例对所提模型进行验证分析。仿真结果表明,通过所提模型寻优合理的售电价格可以实现各零售商自身售电利润的最大化,同时用户也能通过博弈模型得到最优的购电策略,以提升用电综合满意度。

价格敏感性突变下零售商竞争时供应链的协调应对策略

针对含有两个竞争零售商的供应链遭受价格敏感性突变时的应对策略进行研究,基于Stackelberg博弈构建了零售商竞争时的供应链应急模型。研究结果表明,当价格敏感性变化不是很大时,仅通过调整产品的零售价格以及横向调配零售商的供货量,就能实现供应链的最优应对;当价格敏感性变化较大时,则需要同时调整生产计划。同时,设计了Groves批发价契约实现分权供应链的协调应对,数值算例显示应急策略是有效的,而且供应商作为协调者有动力采取该应急策略。此外,当生产成本可变时,产品的替代性是不容忽视的因素,尤其是在价格敏感性降低时,对于扩大市场份额具有重要作用。

Optimal Time-of-use Pricing for Renewable Energy-powered Microgrids: A Multi-agent Evolutionary Game Theory-based Approach

While price schedules can help improve the economic efficiency of renewable energy-powered microgrids,timeof-use(TOU)pricing has been identified as an effective way for microgrid development,which is presently limited by its high costs.In this study,we propose an evolutionary game theoretic model to explore optimal TOU pricing for development of renewable energy-powered microgrids by applying a multi-agent system,that comprises a government agent,local utility company agent,and different types of consumer agents.In the proposed model,we design objective functions for the company and the consumers and obtain a Nash equilibrium using backward induction.Two pricing strategies,namely,the TOU seasonal pricing and TOU monthly pricing,are evaluated and compared with traditional fixed pricing.The numerical results demonstrate that TOU schedules have significant potential for development of renewable energy-powered microgrids and are recommended for an electric company to replace traditional fixed pricing.Additionally,TOU monthly pricing is more suitable than TOU seasonal pricing for microgrid development.

A Distributionally Robust Optimization Scheduling Model for Regional Integrated Energy Systems Considering Hot Dry Rock Co-Generation

Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is proposed.First,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the RIES.HDR-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in space.Secondly,peak-hour loads are shifted using price demand response guidance in the context of time-of-day pricing.Finally,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with HDR-EGS.By simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.

两零售商竞争下考虑企业社会责任投入的供应链决策研究

处于供应链的末端,直接面向市场的零售商面临激烈的市场竞争。供应链中零售商之间的竞争普遍存在,零售价格是竞争的主要决定因素,除了价格,由于当前的动态和市场环境,零售商必须采用更复杂的策略来竞争,而不是简单地降低零售价格。零售商还必须考虑一些非价格因素,如进行企业社会责任投入(Corporate Social Responsibility,CSR)。今天的人们对CSR的认知渐深,企业正通过不同的方式履行CSR。文章研究两个竞争型零售商在不同的CSR投入模式下供应链最优定价决策,首先,构建分散决策下,两零售商考虑不同CSR投入模式的博弈模型。接着,对比分析了各模式下供应链成员的最优决策,探讨了CSR投入水平在供应链定价决策中的作用,总结出最优的CSR投入策略。