Dynamic Advertising Research Articles

Cooperative Advertising in a Marketing Channel

This paper examines dynamic advertising and promotion strategies in a marketing channel where the retailer promotes the manufacturer product and the manufacturer spends on advertising to build a stock of goodwill. We assume that sales depend on goodwill and promotion activities and that there are decreasing marginal returns to goodwill. Two scenarios are studied. First, the manufacturer and retailer determine noncooperatively their respective strategies. Second, the game is played a la Stackelberg with the manufacturer as the leader who supports partially the cost of the promotion activities of the retailer. In both cases, stationary Markovian strategies are characterized. These scenarios are examined also in the absence of decreasing marginal effect of goodwill on sales. The results show that, whether or not the goodwill stock has a decreasing marginal effect on sales, the cooperative advertising program is a coordinating mechanism in the marketing channel, i.e., both players receive higher payoffs.

Oligopoly advertising strategies with market expansion

This study extends the literature of dynamic advertising competition by allowing oligopoly competition and market expansion that results from advertising. We find how advertising actions affect market development and how, conversely, market development influences advertising policies over time. Modelling the competition by a differential game, we solve for both time-variant closed-loop and time-invariant feedback Nash equilibrium strategies. The time-variant closed-loop strategy depends on a firm's own sales rates and the time-invariant feedback strategy depends on the growth of the market. We discuss the marketing implications of the results. Copyright © 1999 John Wiley & Sons, Ltd.

The World Wide Web: Exploring a New Advertising Environment

The World Wide Web currently boasts millions of users in the United States alone and is likely to continue to expand both as a marketplace and as an advertising environment. Three experiments explored advertising in the Web environment, in particular memory for ads as they appear in everyday use across the Web. Experiments 1 and 2 examined the effect of advertising repetition on the retention of familiar and less familiar brand names, respectively. Experiment 1 demonstrated that repetition of a banner ad within multiple web pages can improve recall of familiar brand names, and Experiment 2 demonstrated that repetition can improve recognition of less familiar brand names. Experiment 3 directly compared the retention of familiar and less familiar brand names that were promoted by static and dynamic ads and demonstrated that the use of dynamic advertising can increase brand name recall, though only for familiar brand names. This study also demonstrated that, in the Web environment, much as in other advertising environments, familiar brand names possess a mnemonic advantage not possessed by less familiar brand names. Finally, data regarding Web usage gathered from all experiments confirm reports that Web usage among males tends to exceed that among females.

Planning Media Schedules in the Presence of Dynamic Advertising Quality

A key task of advertising media planners is to determine the best media schedule of advertising exposures for a certain budget. Conceptually, the planner could choose to do continuous advertising (i.e., schedule ad exposures evenly over all weeks) or follow a strategy of pulsing (i.e., advertise in some weeks of the year and not at other times). Previous theoretical analyses have shown that continuous advertising is optimal for nearly all situations. However, pulsing schedules are very common in practice. Either the practice of pulsing is inappropriate or extant models have not adequately conceptualized the effects of advertising spending over time. This paper offers a model that shows pulsing strategies can generate greater total awareness than the continuous advertising when the effectiveness of advertisement (i.e., ad quality) varies over time. Specifically, ad quality declines because of advertising wearout during periods of continuous advertising and it restores, due to forgetting effects, during periods of no advertising. Such dynamics make it worth-while for advertisers to stop advertising when ad quality becomes very low and wait for ad quality to restore before starting the next “burst” again, as is common in practice. Based on the extensive behavioral research on advertising repetition and advertising wearout, we extend the classical Nerlove and Arrow (1962) model by incorporating the notions of repetition wearout, copy wearout, and ad quality restoration. Repetition wearout is a result of excessive frequency because ad viewers perceive that there is nothing new to be gained from processing the ad, they withdraw their attention, or they become unmotivated to react to advertising information. Copy wearout refers to the decline in ad quality due to passage of time independent of the level of frequency. Ad quality restoration is the enhancement of ad quality during media hiatus as a consequence of viewers forgetting the details of the advertised messages, thus making ads appear “like new” when reintroduced later. The proposed model has the property that, when wearout effects are present, a strategy of pulsing is superior to continuous advertising even when the advertising response function is concave. This is illustrated by a numerical example that compares the total awareness generated by a single concentrated pulse of varying duration (blitz schedules) and continuous advertising (the even schedule). This property can be explained by the tension between the pressure to spend the fixed media budget quickly to avoid copy wearout and the opposing pressure to spread out the media spending over time to mitigate repetition wearout. The proposed model is empirically tested by using brand-level data from two advertising awareness tracking studies that also include the actual spending schedules. The first data set is for a major cereal brand, while the other is for a brand of milk chocolate. Such advertising tracking studies are now a common and popular means for evaluating advertising effectiveness in many markets (e.g., Millward Brown, MarketMind). In the empirical tests, the model parameters are estimated by using the Kalman filter procedure, which is eminently suited for dynamic models because it attends to the intertemporal dependencies in awareness build-up and decay via the use of conditional densities. The estimated parameters are statistically significant, have the expected signs, and are meaningful from both theoretical and managerial viewpoints. The proposed model fits both the data sets rather well and better than several well-known advertising models, namely, the Vidale-Wolfe, Brandaid, Litmus, and Tracker models, but not decisively better than the Nerlove-Arrow model. However, unlike the Nerlove-Arrow model, the proposed model yields different total awareness for different strategies of spending the same fixed budget, thus allowing media planners to discriminate among several media schedules. Given the empirical support for the model, the paper presents an implementable approach for utilizing it to evaluate large numbers of alternative media schedules and determine the best set of media schedules for consideration in media planning. This approach is based on an algorithm that combines a genetic algorithm with the Kalman filter procedure. The paper presents the results of applying this approach in the case studies of the cereal and milk chocolate brands. The form of the best advertising spending strategies in each case was a pulsing strategy, and there were many schedules that were an improvement over the media schedule actually used in each campaign.

Note: Dynamic Conjectural Variations in a Lanchester Oligopoly

An approach based on dynamic conjectural variations is advanced for developing dynamic advertising strategies in a Lanchester oligopoly differential game. The approach allows competitors to anticipate rival reactions to market-share state variables, and maintains the computational advantage of open-loop Nash equilibrium strategies. In an empirical application to the ready-to-eat cereal industry, it is shown that advertising strategies based on dynamic conjectural variations can better explain the advertising of the cereal competitors than can open- loop advertising strategies.

Marketing investment decisions in a dynamic duopoly: A model and empirical analysis

Determining the levels of profit-maximizing investments in marketing mix activities such as advertising, detailing and sales promotion in a dynamic competitive environment is an important, but difficult managerial task. In this paper, we model the marketing rivalry over time between two competing firms as a differential game and derive expressions for the equilibrium investment decisions using closed-loop policies. We apply the analytical results derived from our model to examine empirically the dynamic advertising and detailing policies of two competing brands of a prescription drug. Our empirical results show that each firm takes into consideration the actions of its rival when determining its advertising and detailing expenditures. We also find that a firm could be misallocating resources between the different marketing mix instruments, even though the actual total expenditures may be close to the equilibrium levels. This suggests that when firms use multiple marketing mix investments as competitive tools, it could be misleading to model them as a single promotional variable.

Empirical Analysis of Closed-Loop Duopoly Advertising Strategies

Closed-loop (perfect) equilibria in a Lanchester duopoly differential game of advertising competition are used as the basis for empirical investigation. Two systems of simultaneous nonlinear equations are formed, one from a general Lanchester model and one from a constrained model. Two empirical applications are conducted. In one involving Coca-Cola and Pepsi-Cola, a formal statistical testing procedure is used to detect whether closed-loop equilibrium advertising strategies are used by the competitors rather than open-loop strategies. In the second application, involving Anheuser-Busch and Miller, the general model is estimated. Results indicate that closed-loop equilibria better explain dynamic advertising competition than do open-loop equilibria. Also, closed-loop equilibrium advertising strategies implied by model estimates show that competitive advertising levels may or may not be monotonic in market share.

An Evaluation Cost Model of Consideration Sets

Abstract If utility (net of price) varies by consumption occasion, the consideration set of a rational consumer will represent trade-offs between decision costs and the incremental benefits of choosing from a larger set of brands. If evaluating a brand decreases biases and uncertainty in perceived utility, the decision to evaluate a brand for inclusion in a consideration set is different from the decision to consider an evaluated brand. The decision to consume is, in turn, different from the decision to consider. This article provides analytical expressions for these decision criteria and presents four aggregate implications of the model: (1 ) distributions of consideration set sizes, (2) order-of-entry penalties, (3) dynamic advertising response, and (4) competitive promotion intensity.

Competitive dynamic advertising: A modification of the Case game

In this paper, we consider a modified version of the advertising differential game of Case (1979). We derive non-cooperative Nash equilibria for open-loop controls as well as for feedback strategies. We consider finite and infinite planning horizons. The feedback equilibrium is shown to be robust against stochastic disturbances of the state equation.

Dynamic Advertising Strategies of Competing Durable Good Producers

This work develops a diffusion model which incorporates word-of-mouth and advertising effects for two firms introducing competing brands of a new durable product. The competition between the two firms is formulated as a two-player, nonzero sum Markovian game. The firms are assumed to behave noncooperatively in choosing their advertising strategies and the solution concept is a Nash noncooperative equilibrium. Optimal advertising policies for this stochastic closed-loop control problem are obtained via dynamic programming. Our results indicate that both firms will start with high advertising outlays which will get reduced as the number of adopters increases. This is similar to the result obtained previously for a monopolist. Further, we find that there is a significant value in being the first brand to the market, and the greater the intensity of word-of-mouth effects, the greater the value in being first. The first entrant advantage is due to the goodwill generated by its stock of previous adopters. This first entrant advantage can only be overcome if the second entrant enters with a superior brand which is more enthusiastically endorsed by its adopters.

Consumer buying behavior and optimal advertising strategy: The quadratic profit function case

Nicosia's consumer buyer behavior model for a finite advertising campaign duration and a quadratic profit function, which represents the advertising effectiveness measure, is considered. The optimal dynamic advertising strategy is the solution to a quadratic, two-boundary point, optimal control problem with two control constraints. The closed form solutions of optimal advertising paths are obtained and estimation of the parameters is treated. A numerical example illustrates the methodology and provides a comparison with a constant advertising path. The feasibility of applying constrained dynamic optimization to obtain the optimal advertising path in a more realistic environment is demonstrated.

Technical Note—Advertising Models, Stochastic Games and Myopic Strategies

This paper analyzes dynamic advertising models. We present conditions that imply that the payoffs under myopic strategies are linear in the state variable, which represents the number of customers for each firm. These conditions, which determine a subclass of stochastic games, are satisfied by several dynamic advertising models. We give a criterion to check whether this model contains an equilibrium point within the class of myopic strategies that is also an equilibrium point with regard to all strategies.

Dynamic advertising and pricing in an oligopology A Nash equilibrium approach

A general dynamic oligopolistic price-advertising model is formulated and open-loop Nash solutions are derived. As a main result a generalisation of the well known Dorfman — Steiner — Theorem to heterogenous oligopoly markets is presented. Furthermore a detailed discussion of long run equilibrium solutions is given. For an important special case of the general model formulation it is shown that the optimal advertising policies are constant over time and constitute degenerated feedback solutions.

Optimal dynamic advertising policies for hereditary processes

In this paper, the Nerlove-Arrow model of optimal dynamic advertising policies is generalized by assuming a general probability distribution of the “forgetting time,” rather than the exponential one. A control problem with integrodifferential equations of motion is defined for which the transitory and steady-state properties of the optimal advertising policy are examined. The effects of assumptions like IHR-distributions and DHR-distributions, the existence of an upper bound for the forgetting time, etc., are explained. It is shown that there are two (in the case of an exponential distribution even three) different current-value adjoint functions associated with the problem, and relations between the two (three) are established. Also provided is a sensitivity analysis.

Deterministic and stochastic optimization of a dynamic advertising model

AbstractThis paper considers a variation of the Vidale‐Wolfe advertising model for which the maximum value of the objective function and the form of the optimal feedback advertising control are identical in both a deterministic and a stochastic environment. The stochastic environment is due to a white noise disturbance introduced in the deterministic sales‐advertising dynamics.

Dynamic Advertising Effects in A Generalised Firm

Optimal advertising expenditures in static models of the firm generally satisfy the well-known Dorfman-Steiner conditions (Dorfman and Steiner) under a variety of objective functions (see Peel), including that of the « Illyrian » labour-managed firm as perceived by Meade and Vanek, (see Ireland and Law). If advertising has dynamic effects then the generalisation of such results as that of Nerlove and Arrow to firms with objectives other than pure profit maximisation is considered doubtful by at least one writer (Peel). The purpose of the present note is to argue that there is unlikely to be any fundamental difference in advertising policy between a « generalised » firm such as a labour-managed firm and a traditional profit-maximising firrn after provision has been made to adjust for scale differences (factor input levels).Peel contrasts Nerlove and Arrow’s result for the profit-maximising firm with the result for the same model but with an objective function of maximising the discounted stream of profits per worker or income per worker.

Optimal dynamic advertising policies in the presence of continuously distributed time lags

The Nerlove-Arrow model of optimal dynamic advertising policies is generalized by incorporating a continuously distributed lag between advertising expenditures and increases in the stock of goodwill. This leads to a control problem where the equation of motion is given by an integro-differential equation. The transitory and steady-state properties of the optimal policies are examined, both for a general lag function and for a gamma distributed lag. The dependence of the steady-state solution on the parameters of the gamma distribution is also investigated. An example is given using specific demand and cost functions.

Canadian Cases in Marketing

problems is delineated in the early chapters to aid the reader in placing scientific decision making in perspective. Standard basic quantitative techniques are then presented. Included in the review are outcome arrays, the idea of utility and payoff tables, evaluation criteria, and sensitivity analysis. Most importantly, the author depends primarily on basic techniques and their implicit assumptions. Thus, the difficulties in using these techniques are discussed. The second half of the text presents the role of models in the functional areas of marketing. An understanding of the models requires a knowledge of algebra and elementary calculus. Most of the essential material draws only on algebra while the more specialized material requires calculus. This latter area is presented in technical notes where it does not upset the flow of the book. Unfortunately, the author does not include the application of computer sciences to marketing problems. However, this is the only major exclusion of this text, and the area is covered in other monographs. Product decisions are centered on the selection and development of new products. The use of factor utility arrays and probability matrices in new product selection permits the author to synthesize much of the qualitative work that has been reported. Network theory is then used to guide the product through the various development stages. Market analysis and test marketing a product are covered in the traditional manner. Purchasing decisions are considered under conditions of certainty and risk. In addition, both the static and dynamic price situations are included. Since the material in this chapter depends quite heavily on calculus, the technical note presented enables the reader who is unfamiliar with the mathematics used to grasp the meaning of the material covered. Pricing decisions are initially presented via the economist model approach. The section on the use of decision trees in arriving at a price introduces the more practical techniques to solve the problem of setting a price. Competitive bidding strategies, including the use of decision trees, are discussed as a conclusion to this chapter. Two chapters are devoted to exploring the quantitative approach to advertising and promotion decisions. The standard topics of allocation of funds, measuring effectiveness, and competitive strategies are included. Of special note are the sections devoted to the estimation of the parameters of the dynamic advertising model and the use of Markov processes in promotion. Channel of distribution decisions is the concluding topic of the text. In this chapter, transportation and allocation techniques are used to solve problems arising in physical distribution. In summary, this book is useful as a text in an introductory quantitative marketing course and for the practitioner interested in reviewing basic scientific techniques applied to marketing. EARNEST B. UHR State University of New York at Albany