延迟决策对一类双寡头广告博弈模型的影响分析

将延迟决策引入到双寡头有限理性广告博弈模型中,研究了其对系统的影响,并对该模型进行了稳定性分析.在此基础上,以累计利润为指标,通过数值模拟与仿真发现延迟变量的引入并不一定能够为企业带来竞争优势,而这主要取决于引入延迟变量的时间点和延迟变量系数的大小.同时对延迟变量系数与系统参数的稳定域之间的关系做了探讨,指出在混沌时如果延迟变量系数取得适当,将会极大地提高自身的竞争优势和系统的稳定性.另外,对混沌时降低单位广告所产生的平均需求的两种方式对企业的不同影响做了研究,并指出通过降低广告制作成本来降低单位广告所产生的平均需求将会为企业赢得更大的竞争优势.     

金融风险系统混沌效应的分析与控制

复杂性是金融风险系统的本质属性.通过建立一个金融风险系统三层结构模型,计算受到扰动状态下系统的Lyapunov指数,从而证明金融风险系统中的混沌现象.在此基础上,进一步探讨了混沌状态下金融风险系统存在着混沌效应的原因及其危害.研究中采用RBF神经网络的参数训练法,给出混沌同步控制器的设计原理和方法,并通过仿真实验表明这种方法对抑制混沌效应为有效.     

零售商竞争下纵向合作广告的微分对策模型

利用随机微分对策理论研究了供应链中零售商竞争下的纵向合作广告问题,建立了一个随机微分对策模型.运用汉密尔顿-雅可比-贝尔曼方程分别求得了Stackelberg博弈和合作博弈下均衡的全国性广告投入、地方性广告投入、制造商商誉的期望值和方差、商誉的概率分布函数以及Stackelberg博弈下的广告分担比例,并对此两种博弈进行了比较.研究发现,两种博弈下的零售商的地方性广告投入和制造商的商誉与零售商之间的广告竞争强度相关;在一定条件下,制造商具有一致渐进稳定的商誉概率分布函数.最后,运用效用理论对合作博弈下的增量利润进行了划分.     

虚假广告行为中的博弈分析

虚假广告的泛滥已成为严重的社会问题,本文针对广告行为中两个重要主体广告主与广告发布者建立博弈模型并进行求解和分析,提出了综合治理虚假广告的建议措施.对广告的监管和对虚假广告的治理应以对广告主的监管为重点,设立专门的广告审查机构,并强化对广告发布者和代言人的管理,同时还要增进消费者的维权和法律意识,积极发挥广告业行业协会的作用.这样方可有效遏制虚假广告.     

重庆市主城区基站电磁辐射现状调查与评价

随着社会现代化和信息化的飞速发展,移动通信基站数量不断增加,其电磁辐射问题被越来越多的人关注.本文根据重庆市主城区近两年基站监测数据,分析重庆市主城区两年内新建移动基站电磁辐射情况,结果显示:2007年电场强度平均值2.76V/m,功率密度平均值0.0153 W/m2;2008年电场强度平均值1.64V/m,功率密度平均值0.0643 W/m2,均低于国家相关标准.     

基于微分对策的多寡头品牌和大类广告策略研究

本文利用微分对策理论研究了多寡头品牌和大类广告策略,发展了Bass等的双寡头竞争模型,提出了一个多方竞争下的微分时策模型,采用汉密尔顿.雅可比.贝尔曼方程求得了模型的均衡价格、品牌广告、大类广告和价值函数,给出了市场份额计算公式,推广了Prasad和Sethi的结论,同时发现市场中只有两家或三家企业时总能保证企业得到正利润,一旦企业数量增多则不能保证.     

双寡头市场中品牌广告竞争和大类广告合作策略研究

利用微分对策理论研究了一强一弱双寡头垄断市场中的品牌广告竞争和大类广告合作策略,提出了一个Stackelberg博弈模型,采用汉密尔顿-雅可比-贝尔曼方程求得了模型的均衡品牌广告、大类广告和价值函数,给出了市场份额计算公式。研究发现:与非合作策略相比,大类广告合作策略下,无论强者还是弱者,他们的销售量都增加了,同时两个企业的品牌广告投入也增加了;通过大类广告合作策略,无论强者(领导者)还是弱者(追随者),他们的利润都得到了提高;强者、弱者和行业的大类广告投入分别高于非合作下强者、弱者和行业的大类广告投入。     

经济管理混沌模型的控制域研究

在进行混沌控制时,有时要经过很长时间才到达目标轨道,有时甚至不能有效控制,正如 在基于预测的反馈控制中看到的,究其原因一是混沌模型有时有多个不动点,二是混沌轨道的 稠密性. 提出一种等价关系,计算基于概率的动力系统的特征指数,给出混沌经济动力系统的 不稳定周期轨道的有用信息,通过讨论特征指数的符号,选择有效的控制参数,得到相应的控 制参数取值范围,从而得到混沌经济模型中的参数变量的混沌控制域.     

制造商广告和零售商动态定价联合决策模型

考虑由一个制造商和一个零售商组成的供应链,制造商以批发价格为零售商提供一种产品,零售商再以零售价格将产品销售给顾客;制造商可以做广告来提高销售量,零售商的零售价格和制造商的广告不仅对本期的需求有影响,而且对下期的需求也有影响.在这样的条件下刻画两周期的需求函数,提出一个两周期动态定价和广告联合模型.在集中式供应链下,采用两阶段逆向归纳法给出两周期定价和广告决策,分析价格敏感系数和广告敏感系数对决策的影响;在分散式供应链下,制造商为Stackelberg博弈的领导者,零售商为追随者,采用四阶段逆向归纳法给出两周期定价和广告决策的均衡解,并给出了批发价格协调供应链的条件.结果表明,下期的定价和广告决策很大程度上依赖于本期的定价和广告决策.     

基于Vidale-Wolfe模型的多市场广告预算分配决策模型

广告决策问题很长时间以来都是营销经理和学者们关注的热点。随着社会经济发展,越来越多的企业面对多个市场。如何在多个市场、广告总预算固定的状况下,合理分配各个市场广告预算以收到最优广告效果,是一个企业关心的较为重要的问题。经过比较,选择Vidale-Wolfe模型作为广告反应模型,在此基础上建立了多市场广告预算分配决策模型。考虑到一些营销策略对某些市场有特殊销售速率要求,该模型分为无特殊销售速率维持要求的多市场广告预算分配决策模型和有特殊销售速率维持要求的多市场广告预算分配决策模型两类,后者探讨了销售速率变化与达到指定销售速率两种要求下的广告预算最优分配问题,构建了优化模型,提出了模型参数取值与模型求解方法,最后给出了一个算例。     

Computer-aided formulation and optimal control of an integrated production system for competitive products

An integrated production, inventory and advertising system has been formulated based on control engineering principles. In this system, the customer's demand is satisfied from stock, which in turn is replenished from production facilities. But sales reflect the advertising effort, present as well as past. The past effort has been considered as a delay with an assumed delay period. The problem is formulated as a state and observation model. Out of this an augmented model of state and parameters is formed. The parameters describing the model are estimated from MAP discrete filter algorithm. It is shown that sales of product 1 or product 2 at (k + l)th period is effected by sales and advertising of product 1 or product 2 at the kth period, and also by sales and advertising of product 2 or product 1 at (k-θ)th period, where 6 is the delay.     

A Two-Period Repeated Game Advertising Investment Model for Oligopolistic Markets with an Application to the Beer Industry*

This paper proposes a simple analytical model of advertising competition in oligopoly markets. The widely used log-log sales response function underlies the model specification. Advertising carryover effects are assumed to persist for one period following the period in which the expenditure occurs. Firms are assumed to be engaged in a repeated competitive game in which in every period advertising levels are set such that they maximize current and next period (i.e., two-period) profits. A Nash equilibrium solution is sought for the game. Compared with previous empirical studies of advertising competition in a game theoretic framework, the proposed model offers the following advantages: (1) oligopoly, not duopoly, markets are analyzed; (2) industry sales is allowed to vary over time as a function of advertising expenditures; (3) non-zero discount rates are used for the players. An empirical application is provided using data from the beer market on sales and advertising expenditures of Anheuser-Busch and Miller Brewing. Comparisons are provided with policies that ignore the dependence of next period profits on current advertising levels, reaction function strategies and spending levels obtained from a market share game. Extension of the model formulation to multiple marketing instruments is briefly discussed.     

基于巴斯模型的消费者推荐奖励和广告投入动态定价决策

本文从新产品扩散的过程出发，构建了同时考虑口碑效应和广告效应的产品扩散模型，研究企业推荐奖励和广告投入的动态定价问题。利用汉密尔顿函数和最大值原理得到最优解，并结合多个关键参数对最优解进行了敏感性分析。研究发现：最优推荐奖励呈先减少后增加趋势，最优广告投入则是逐渐减少；对于高价值产品，企业应采取高价格高奖励的策略；企业的推荐奖励策略和广告投入策略会受到推荐奖励效率、广告效率、自发购买比率和传统口碑效的影响。本文的研究结论对企业的推荐奖励和广告策略设计有一定的理论指导意义。     

A Mobile Platform's In‐App Advertising Contract Under Agency Pricing for App Sales

Unlike advertising in traditional media, a mobile platform's in‐app advertising market exhibits two unique features—split structure of the mobile platform with a platform owner and an app developer jointly provisioning in‐app advertising, and agency pricing for app sales. We develop a two‐sided market model to analyze the role of these two unique features in determining the platform owner's optimal advertising revenue‐sharing contract. Our results reveal an interesting N‐shaped dynamic regarding the platform owner's optimal choice of her ad revenue share with respect to the overall advertisers’ valuation of in‐app ads. We identify a between‐agent subsidization strategy for the platform owner, where she finds it optimal to subsidize the developer via the advertising channel, leading to greater profits for both of them. We find that the advertising revenue‐sharing contract under agency pricing for app sales leads to a higher app price than would be offered by the integrated platform found in traditional advertising. However, the ad price is coordinated under the platform owner's optimal choice of ad revenue share when she obtains revenue from both the advertising and app sales channels, leading to an alignment of her interest with the app developer's on ad level.     

Managing Retail Budget Allocation between Store Labor and Marketing Activities

The performance of a retail store depends on its ability to attract customer traffic, match labor with incoming traffic, and convert the incoming traffic into sales. Retailers make significant investments in marketing activities (such as advertising) to bring customers into their stores and in‐store labor to convert that traffic into sales. Thus, a common trade‐off that retail store managers face concerns the allocation of a store's limited budget between advertising and labor to enhance store‐level sales. To explore that trade‐off, we develop a centralized model to allocate limited store budget between store labor and advertising with the objective of maximizing store sales. We find that a store's inherent potential to drive traffic plays an important role, among other factors, in the relative allocation between advertising and store labor. We also find that as advertising instruments become more effective in bringing traffic to stores, managers should not always capitalize this effectiveness by increasing their existing allocations to advertising. In addition, we discuss a decentralized setting where budget allocation decisions cannot be enforced by a store manager and present a simple mechanism that can achieve the centralized solution. In an extension, we address the budget allocation problem in the presence of marketing efforts to shift store traffic from peak to off peak hours and show that our initial findings are robust. Further, we illustrate how the solution from the budget allocation model can be used to facilitate store level sales force planning/scheduling decisions. Based on the results of our model, we present several insights that can help managers in budget allocation and sales force planning.     

Supply chain coordination through cooperative advertising with reference price effect

Cooperative advertising, which usually occurs in a vertical supply chain, is typically a cost sharing and promotion mechanism for the manufacturer to affect retail performance. Research in the literature, however, rarely considers the important phenomenon that advertising has a positive effect on the consumer's reference price. In fact, when a consumer makes a decision to buy a product or not, a reference price is usually in his mind and plays a determinant role. Taking into account the impact of advertising on the reference price, this paper proposes a dynamic cooperative advertising model for a manufacturer–retailer supply chain and analyzes how the reference price effect would influence the decisions of all the channel members. In our model, both the consumer's goodwill and reference price for the product are assumed to be influenced by the advertising and are modeled in differential dynamic equations. In addition, the advertising level, the consumer's goodwill and the reference price are all assumed to have positive effect on sales. Utilizing differential game theory, this paper formulates the optimal decisions of the manufacturer and the retailer in two different game scenarios: Stackelberg game and cooperative game. Also, this paper proposes a new mechanism to coordinate the supply chain in which both the manufacturer and the retailer share each other's advertising costs.     

考虑延时效应的供应链动态合作广告策略研究

广告的延时效应是供应链广告过程中的普遍现象,对供应链合作广告策略的制定具有重要影响.文章研究当产品品牌信誉受广告延时效应影响时供应链的合作广告策略问题,建立了含有时间延迟的品牌信誉动态模型和考虑品牌信誉的产品销售量模型.运用极大值原理,得到了制造商和零售商在分散式决策和集中式决策下的最优广告投入、品牌信誉和利润,以及分散式决策下制造商的最优合作广告参与率.研究发现:在集中式决策下制造商和零售商的最优广告投入和产品销售量均高于分散式决策下的相应值;延迟时间存在一个阈值,当延迟时间低于该阈值时,集中式决策下的供应链利润较高,反之则分散式决策下的供应链利润较高.研究结果为供应链合作广告策略的制定及供应链决策机制的选择提供了一定的参考.最后,通过数值算例分析了广告延迟时间对供应链最优广告策略及决策机制的影响.     

Measurement of the effect of wool advertising

The paper reports a recent International Wool Secretariat (I.W.S.) study to measure the overall effect on sales of fibre advertising, based on annual data for eight major wool-consuming countries, collected from 1960 to 1970. An economic model of the fibre market is set up, and multiple linear regression is used to demonstrate a significant positive relationship between fibre sales and advertising. The effect of wool advertising is quantified, using the estimated regression coefficients, and its cost is compared with the estimated benefits to the wool industry in terms of increased revenue. Possible drawbacks of the approach described are considered, and aspects of the work requiring further study are also mentioned.     

The newsvendor problem with advertising: an overview with extensions

The effect of advertising on sales has been the subject of recent studies as an important aspect in many demand-based problems. Herein, we deal with the newsvendor problem, due to its simple structure, as a suitable tool for illustrating how facets of marketing may affect decision-making concerning operational problems. In the setting presented, the newsvendor is faced with advertising-sensitive stochastic demand, where a demand-related random element comprises an advertising decision of the multiplicative or additive form. We assume that a suitable advertising strategy results in increased sales. Two advertising response functions are considered, these being concave downward and S-shaped. We review and extend the existing results relating to the newsvendor problem with marketing effects, which mostly pertain to the concave function. These are generalized by defining the S-shaped function, and some original insights into the effect of advertising are given. We establish that the optimal advertising expenditure for the multiplicative case is always less than or equal to the optimal amount in the equivalent deterministic model while it is always equal in the additive case. We finally illustrate the results that are obtained by providing numerical examples involving various advertising response functions, as well as management-related interpretations.