The issue of “power” in the marketing channels for consumer products has received considerable attention in both academic and practitioner journals as well as in the popular press. Our objective in this paper is to provide an empirical method to measure the power of channel members and to understand the reasons (demand factors, cost factors, nature of channel interactions) for this power. We confine our analysis to pricing power in channels. We use methods from the game-theory literature in marketing on channel interactions to obtain the theoretical framework for our empirical model. This literature provides us a definition of power—one that is based on the proportion (or percentage) of channel profits that accrue to each of the channel members. There can be a variety of possible channel interactions between manufacturers and retailers in channels. The theoretical literature has examined some of these games. For example, Choi (1991) examines how channel profits for manufacturers and retailer vary if channel interactions are either vertical Nash, or if they are Stackelberg leaderfollower with either the manufacturer or the retailer being the price leader. Each of these three channel interaction games has different implications for profits made by manufacturers and retailers, and consequently for the relative power of the channel members. In contrast to the previous literature that has focused largely on the above three channel interaction games, our model extends the game-theoretic literature by allowing for a continuum of possible channel interactions between manufacturers and a retailer. Furthermore, for a given product market, we empirically estimate from the data where the channel interactions lie in this continuum. More critically, we obtain measures of how channel profits are divided between manufacturers and the retailer in the product market, where a higher share of channel profit is associated with higher channel power. We then examine how channel power is related to demand conditions facing various brands and cost parameters of various manufacturers. In going from game-theory-based theoretical models of channel interactions to empirical estimation, we use the “new empirical industrial organization” framework (Bresnahan 1988). As part of this structural modeling framework, we build retail-level demand functions for the various brands (manufacturer and private label) in a given product category. Given these demand functions, we obtain optimal pricing rules for manufacturers and the retailer. In determining their optimal prices, manufacturers and the retailer account for how all the players in the channel choose their optimal prices. That is, we account for dependencies in decision making across channel members. These dependencies are characterized by a set of “conduct parameters,” which are estimated from market data. The conduct parameters enable us to identify the nature of channel interactions between manufacturers and the retailer (along the continuum mentioned previously). In addition to the demand an...

The purchase timing decision is an important component of the dynamics of a household's purchase behavior. This decision is influenced by marketing and other variables, and the modeling of this dependence has recently received attention in the literature. In this paper, we build on previous studies and develop a comprehensive stochastic model that incorporates the major factors influencing interpurchase times. Specifically, we use a generalized version of Cox's proportional hazard model to test among competing probability distributions for the interpurchase times while incorporating effects due to marketing variables, observed household characteristics, and unobserved heterogeneity across households. The empirical finding from analyzing the IRI coffee data, suggests that the interpurchase times cannot be adequately described by probability distributions such as exponential, Erlang-2 or Weibull. The effects of unobserved heterogeneity are significant, and they impact the estimates of the effects of the covariates. We also find that a nonparametric procedure for estimating the effects of unobserved heterogeneity provides the best overall fit to the data and yields covariate estimates that are more consistent with prior expectations. Our model is validated by replicating the substantive empirical findings on an additional product category.hazard function, purchase timing, unobserved heterogeneity

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The equilibrium profit-maximizing advertising policies of firms operating in a dynamic duopoly are derived by linking in a single framework the econometric estimation of the market response function and the technique of differential games that characterizes dynamic competitive behavior. We use the Lanchester model of combat to represent the system dynamics that capture the competitive shifts due to investments in advertising by the two market rivals. We determine the equilibrium advertising levels using both closed- and open-loop policies. We also compare these equilibrium advertising policies for each firm to those obtained using an optimal control theory formulation wherein the advertising spending levels of the rival are assumed to be known. The empirical results obtained by analyzing the advertising rivalry between Coke and Pepsi for the period 1968--1981 under the above three alternative spending policies provide some interesting insights into the nature of competition between these two market rivals. A significant contribution of this paper is to extend the existing literature on advertising competition by integrating theoretical and empirical analyses.marketing, competitive strategy, advertising, games, noncooperative, differential

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Diagnosing the nature and magnitude of competitive interactions among firms is important for developing effective marketing strategies. In this paper, we formulate a game-theoretic model of firm interaction to analyze the dynamic price and advertising competition among firms in a given product market. Firm (or brand) level demand functions account for the contemporaneous and carry-over effects of these marketing activities, and also allow for the effects of competitor actions. Firms take into consideration the actions of their rivals, as well as their own demand and cost functions (both production and advertising) when determining the profit-maximizing price and advertising levels. Our formulation enables us to quantify not only the direction and magnitude of competitive reactions, but also to identify the underlying form of market conduct that generates the particular pattern of interaction. We specify and estimate a fully structural econometric model for three firms constituting a distinct sub-market within a personal-care product category. We estimate the demand and competitive interaction parameters, as well as the production and advertising cost functions for each firm. We then derive implications for competitive interactions and market structure. Interestingly, we find that while firms seem to compete on advertising, they price cooperatively, thereby enhancing their price-cost margins.competitive interactions, marketing mix, econometric estimation

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The authors use a continuous-time semi-Markov approach to analyze in a single framework the purchase-timing and brand-switching decisions of households for a frequently purchased product. The analysis provides more insights into the dynamics of household purchase behavior than could be obtained from conventional discrete choice models such as logit or probit. The authors find that the probability distribution of interpurchase times is not the same for various switching between brands, revealing extra information about the purchase-timing decisions. Further, they find that though the marketing mix and household demographic variables explain a large part of the variation in the brand-switching rates, they account for only a small part of the variation in the repeat purchase rates. Another finding from the analysis is that the rates of switching between brands due to promotional activities such as special displays and price reductions are in reverse order to the share of purchases of the various brands.