Competitive Advertising Under Uncertainty: A Stochastic Differential Game Approach

We analyze optimal advertising spending in a duopolistic market where each firm's market share depends on its own and its competitor's advertising decisions, and is also subject to stochastic disturbances. We develop a differential game model of advertising in which the dynamic behavior is based on the Sethi stochastic advertising model and the Lanchester model of combat. Particularly important to note is the morphing of the sales decay term in the Sethi model into decay caused by competitive advertising and noncompetitive churn that acts to equalize market shares in the absence of advertising. We derive closed-loop Nash equilibria for symmetric as well as asymmetric competitors. For all cases, explicit solutions and comparative statics are presented.     

Flexible capacity strategy with multiple market periods under demand uncertainty and investment constraint

We establish a flexible capacity strategy model with multiple market periods under demand uncertainty and investment constraints. In the model, a firm makes its capacity decision under a financial budget constraint at the beginning of the planning horizon which embraces n market periods. In each market period, the firm goes through three decision-making stages: the safety production stage, the additional production stage and the optimal sales stage. We formulate the problem and obtain the optimal capacity, the optimal safety production, the optimal additional production and the optimal sales of each market period under different situations. We find that there are two thresholds for the unit capacity cost. When the capacity cost is very low, the optimal capacity is determined by its financial budget; when the capacity cost is very high, the firm keeps its optimal capacity at its safety production level; and when the cost is in between of the two thresholds, the optimal capacity is determined by the capacity cost, the number of market periods and the unit cost of additional production. Further, we explore the endogenous safety production level. We verify the conditions under which the firm has different optimal safety production levels. Finally, we prove that the firm can benefit from the investment only when the designed planning horizon is longer than a threshold. Moreover, we also derive the formulae for the above three thresholds.     

Multistage multiproduct advertising budgeting

We propose and analyze an effective model for the Multistage Multiproduct Advertising Budgeting problem. This model optimizes the advertising investment for several products, by considering cross elasticities, different sales drivers and the whole planning horizon. We derive a simple procedure to compute the optimal advertising budget and its optimal allocation. The model was tested to plan a realistic advertising campaign. We observed that the multistage approach may significantly increase the advertising profit, compared to the successive application of the single stage approach.     

ADAPT: An Adaptive Approach to Media Decisions

A firm's market changes under the impact of the firm's advertising. Feedback information on the market response allows the firm to learn about such changes and to adapt its subsequent media decisions accordingly. This paper presents an adaptive media model (ADAPT) that utilizes feedback information to revise certain parameters in a media decision model. Simulation experiments conducted with the ADAPT model demonstrate how different types of feedback information affect the media decisions and thereby the expected net profit contributions from sales. It is shown how the economic value of feedback information depends on the characteristics of the firm's market and also on the revision rules applied for updating the parameters. The value of the information may actually be negative if it is not used "intelligently".     

Modelling impact of advertising and optimizing advertising policy: an application in recreation

This paper deals with the problem of the desirable level of advertising expenditure, the optimal distribution of this expenditure in time and the allocation over the media: TV, radio and newspaper for a recreation park in the Netherlands.Although the model id developed for the specific situation of this park, in principle it can be applied in all situations where the interest is in short-term (day-by-day) effects of promotional activities on sales. Examples are: other situations in the recreation and leisure business, cultural events (theatre, cinema) and sales promotions (e.g. weekend offerings) for products in supermarkets.First a model was specified and estimated that relates number of visitors to advertising effort. It also takes into account non-advertising variables that effect the number of visitors.Then this model was used in a heuristic advertising planning procedure, which by means of incremental analysis, for a given budget level searches for the optimal allocation of the advertising budget over media and time.With this procedure, ways to readjust the advertising policy were found: by allocating the budget differently over media and time and by changing the overall budget level.Several recommendations were made to the management of the park, a number of which have already been implemented.     

Allocation of advertising budget between multiple channels to support sales in multiple markets

We consider the allocation of a limited marketing budget between multiple channels in order to promote sales at multiple markets. The channels differ in their type, level of targetability (or reach), and costliness. We incorporate the “threshold effect” from each market in our resource allocation which requires some positive advertising investment in each market before much sales impact can be observed from it. The increased number of channels in recent years with the advent of digital advertising, along with the added complexity created by the threshold effect, necessitates the development of new allocation approaches. In this paper, we formulate the firm’s resource allocation decision as a nonlinear and nonseparable knapsack problem. We develop a branch and cut solution method which is enhanced by a heuristic approach. A set of numerical experiments illustrate the performance of our methods and evaluate the usefulness of two rule-of-thumb strategies commonly used in practice.     

需求中断下具有提前期的双渠道供应链的风险规避决策

讨论了由一个制造商和一个零售商所组成的双渠道供应链在需求中断下具有提前期的双渠道供应链的风险规避问题.给出了在需求中断前后的最优价格、最优提前期和最优生产决策.研究表明决策变化量是需求中断量的线性函数,在集中式下最优的决策和销售量与供应链的市场份额和需求中断有关,模型的最优生产体现了一定的稳健性.对于提前期来说,当市场份额较大时,最优提前期关于风险规避系数呈正比例,当市场份额较小时,最优提前期关于风险规避系数呈反比例.     

New product advertising in dynamic oligopolies

The success of the introduction of a new product in a market is very sensitive to the marketing decision variables adopted by the firm. In the present paper we are concerned with the question of new product advertising in a heterogeneous oligopoly market consisting of N firms. A dynamic game is formulated to model strategic as well as sales interactions in such a market. Optimal advertising strategies are identified as open-loop Nash solutions.The comments of two anonymous referees are appreciated. The first author wishes to acknowledge support from NSERC (Grant No. OGP0037342).     

风险中性零售商的合作广告策略与订货模型

考虑了由一个制造商与一个零售商构成的单期二阶段供应链是否进行合作广告的博弈问题.面对市场需求的不确定性,零售商从制造商处订购报童类型产品销售给消费者,零售商具有风险中性的行为特征.通过不合作广告与合作广告两种情形,制造商与零售商进Stackelberg主从博弈,得到了均衡解,比较后发现,合作广告下的最优解及利润总是优于不合作广告下的最优解和利润,告诉了上下游企业采用合作广告的广告策略.最后,通过数值算例,给出了需求敏感系数对最优决策的影响,同时也论证了有关结论.     

National and store brand advertising strategies

As the propensity of premium store brands (SBs) increases, retailers must consider different ways to drive sales besides promotional strategies. With this in mind, we consider a national brand (NB) and a (premium) SB co-existing in a market. Each brand has to decide the amount to invest in advertising its product and the prices to charge its customers, which can be determined separately or in unison. When either advertising expenditures or pricing decisions are set, each brand must keep in mind that the advertising efforts and revenue may spillover between the two brands, customers who intend to purchase the NB may end up purchasing the SB and vice versa. We derive an analytical model of the situations described and characterize equilibrium advertising decisions. We find that the characteristics of a premium SB may depend on which marketing/promoting instrument (advertising or pricing) is the primary method for driving demand; and in some situations an NB may be better off to not advertise at all and instead let the premium SB carry out all of the advertising.     

供应链互补产品广告投入和捆绑销售联合决策研究

以一个制造商和一个零售商的供应链为研究对象,制造商生产两种互补产品,零售商可选择分开或捆绑两种销售策略。考虑互补品的负交叉弹性和广告外部性的特点,构建基于溢出效应的需求模型,运用博弈论的方法,求解零售商采取分开和捆绑两种销售策略时的均衡结果。通过比较不同销售策略下的均衡结果及利润关系,探讨在分散式和集中式两种情况下,零售商的最优广告投入和捆绑销售的联合决策问题。最后,通过数值算例,讨论产品互补程度和广告成本系数对决策结果的影响。研究结果表明,无论是在分散式还是集中式决策下,当产品互补程度较高或广告成本系数低时,分开销售是占优策略而广告费用较高;当产品互补程度较低且广告成本系数高时,捆绑销售是占优策略且广告费用较低。     

Modelling Cooperative Advertising Decisions in Franchising

Advertising fee decisions in franchise systems are a frequent source of conflict between franchisors and franchisees. Such disagreements persist because the win-win potential of vertical cooperative advertising is not well appreciated. Our paper introduces a formal normative approach for analyzing, understanding and subsequently making these vertical cooperative advertising decisions within a franchising context in a manner that results in optimal system-wide returns. The model demonstrates that cooperative determination of franchisor's and franchisee's advertising contributions may yield superior payoffs for both exchange partners than the total payoff if the franchisor and franchisee seek to optimize their individual objective functions. Three types of models are developed and evaluated (i.e. deterministic, stochastic and under conditions of differing perceptions of the sales response functions to advertising). Conclusions hold under all three model variants. Industry implications are also presented.     

Modelling advertising budgeting and allocation decisions using modified multinomial logit market share models

Previous research suggests that a multinomial logit model of market share (MNL) is inappropriate for equilibrium analyses of advertising competition. This article shows that when employing simple transformations of the advertising effort, the modified MNL model becomes useful in representing situations of diminishing returns to advertising and appropriate for advertising equilibrium analyses without additional difficulties in its empirical estimation. Using the modified MNL model, optimal advertising budgets together with their allocation over time are derived for both the cases of concave and S-shaped attraction (response) functions in a symmetric oligopoly.     

The stochastic capacitated branch restructuring problem

Traditionally, in the fashion industry, purchasing decisions for retailers are made based on various factors such as budget, profit target, and interest rate. Since the market demand is highly volatile, risk is inherently present and it is critically important to incorporate risk consideration into the decision making framework. Motivated by the observed industrial practice, we explore via a mean-variance approach the multi-period risk minimization inventory models for fashion product purchasing. We first construct a basic multi-period risk optimization model for the fashion retailer and illustrate how its optimal solution can be determined by solving a simpler problem. Then, we analytically find that the optimal ordering quantity is increasing in the expected profit target, decreasing in the number of periods of the season, and increasing in the market interest rate. After that, we propose and solve several extended models which consider realistic and timely industrial measures such as minimum ordering quantity, carbon emission tax, and carbon quota. We analytically derive the necessary and sufficient condition(s) for the existence of the optimal solution for each model and show how the purchasing budget, the profit target, and the market interest rate affect the optimal solution. Finally, we investigate the supply chain coordination challenge and analytically illustrate how an upstream manufacturer can offer implementable supply contracts to optimize the supply chain.     

Assessing the effect of advertising expenditures upon sales: A Bayesian structural time series model

We propose a robust implementation of the Nerlove‐Arrow model using a Bayesian structural time series model to explain the relationship between advertising expenditures of a countrywide fast‐food franchise network with its weekly sales. Due to the flexibility and modularity of the model, it is well suited to generalization to other markets or situations. Its Bayesian nature facilitates incorporating a priori information reflecting the manager's views, which can be updated with relevant data. This aspect of the model will be used to support the decision of the manager on the budget scheduling of the advertising firm across time and channels.     

Optimal advertising pulsation policies: a dynamic programming approach

This study formulates and solves an advertising pulsation problem for a monopolistic firm using dynamic programming (DP). The firm aims at maximising profit through an optimal allocation of the advertising budget in terms of rectangular pulses over a finite planning horizon. Aggregate sales response to the advertising effort is assumed to be governed by a modified version of the Vidale–Wolfe model in continuous time proposed by Little. Using a numerical example in which a planning horizon of one year is divided into one, two through ten equal time periods, computing routines are developed to solve 150 DP problems. Computational results show among other findings that the performance yielded by the DP policy dominates the uniform advertising policy (constant spending) for a concave advertising response function and the advertising pulsing policy (turning advertising on and off) for a linear or convex response function.     

Dynamic bidding strategies in search-based advertising

Search-based advertising allows the advertisers to run special campaigns targeted to different groups of potential consumers at low costs. Google, Yahoo and Microsoft advertising programs allow the advertisers to bid for an ad position on the result page of a user’s query when the user searches for a keyword that the advertiser relates to its products or services. The expected revenue generated by the ad depends on the ad position, and the ad positions of the advertisers are concurrently determined after an instantaneous auction based on the bids of the advertisers. The advertisers are charged only when their ads are clicked by the users. To avoid excessive ad expenditures due to sudden surges in the keyword-search activities, each advertiser reserves a fixed finite daily budget, and the ads are not shown in the remainder of the day when the budget is depleted. Arrival times of keyword-search instances, ad positions, ad selections, and sales generated by the ads are random. Therefore, an advertiser faces a dynamic stochastic total net revenue optimization problem subject to a strict budget constraint. Here we formulate and solve this problem using dynamic programming. We show that there is always an optimal dynamic bidding policy. We describe an iterative numerical approximation algorithm that uniformly converges to the optimal solution at an exponential rate of the number of iterations. We illustrate the algorithm on numerical examples. Because dynamic programing calculations of the optimal bidding policies are computationally demanding, we also propose both static and dynamic alternative bidding policies. We numerically compare the performances of optimal and alternative bidding policies by systematically changing each input parameter. The relative percentage total net revenue losses of the alternative bidding policies increases with the budget loading, but were never more than 3.5 % of maximum expected total net revenue. The best alternative to the optimal bidding policy turned out to be a static greedy bidding policy. Finally, statistical estimation of the model parameters is visited.     

Optimal Multi-Period Advertising Budget Allocation within a Competitive Environment

A mathematical model approach is developed for the purpose of aiding advertising and marketing executives in advertising budget allocation decision-making in the face of a competitive environment. Two alternative model formulations are examined to study the dynamic market response to advertising expenditures. These embody numerous realistic characteristics of the advertising phenomenon including carry-over of past expenditures, diminishing returns and saturation effects, response decay in the absence of advertising and product diffusion effects. Through mathematical programming, the model determines the optimal advertising expenditures over a predetermined planning horizon under alternative constraint options (including competitive advertising assumptions). Illustrations of model applications are also presented.     

Coordinating advertising and pricing in a manufacturer–retailer channel

Cooperative advertising is a practice that a manufacturer pays retailers a portion of the local advertising cost in order to induce sales. Cooperative advertising plays a significant role in marketing programs of channel members. Nevertheless, most studies to date on cooperative advertising have assumed that the market demand is only influenced by advertising expenditures but not by retail price. This paper addresses channel coordination by seeking optimal cooperative advertising strategies and equilibrium pricing in a two-member distribution channel. We establish and compare two models: a non-cooperative, leader–follower game and a cooperative game. We develop propositions and insights from the comparison of these models. The cooperative model achieves better coordination by generating higher channel-wide profits than the non-cooperative model with these features: (a) the retailer price is lower to consumers; and (b) the advertising efforts are higher for all channel members. We identify the feasible solutions to a bargaining problem where the channel members can determine how to divide the extra profits.     

Dynamical analysis of a nonlinear competitive model with generic and brand advertising efforts

In this paper, a new four-dimensional map is proposed to model the dynamical advertising efforts, where both the generic and brand effects for advertisement are taken into account in the model. The marginal profit adapting strategy is used to reflect the interaction among the firms that strive for the optimal profit. When the generic advertising bears a large effectiveness coefficient, the generic advertising efforts will exhibit chaos, which leads to a chaotic dynamics for brand advertising efforts. In this case, we analyze the some properties of steady trajectories that imply rough profiles of the advertising strategies evolution. Furthermore, by rigorous dynamical analysis and numerical simulations, we obtain the feasible set outlining the influence of initial conditions on the global dynamic properties. We first deal with the symmetric system, and then extend the obtained results to more general case, namely, the asymmetric model. For the symmetric model, two firms’ brand advertising expenditures behave synchronization, but the dynamics of generic advertising efforts are dependent upon initial conditions. Meanwhile, for the heterogeneous case, the domain firm in the market needs to contribute all generic advertising expenditures. Our results can have a practical impact on the market evolution, and are therefore beneficial to decision maker.