Advertising competition in the hierarchically structured market

Abstract

In a hierarchically structured market, marketers should make use of the market structure information for developing effective marketing strategies. This thesis presents a Lanchester-type advertising competition model for hierarchically structured and oligopolistic markets that incorporates the market structure information in Chapter 3. The model enables us to estimate the degree of competitive effects between brands within each submarket as well as that between submarkets. For an empirical illustration of the model, we use advertising and market share data of the automobile industry in a developing country and present the results in Chapter 4. Our model has potential to help marketers in several ways. First, we can use the model to confirm whether certain preconceived hierarchical competitive structure of the market is actually observed or not. Second, the model enables a firm selling several brands in a hierarchically structured market to allocate advertising budget more effectively. Third, it helps firms make better marketing decisions for firms competing not only with brands in its product market but also with other substitutable products. Fourth, it can give marketers important insights into the product positioning strategies. As an application of the main model, we analyze the model with game theoretic framework in Chapter 5. Each player in this game can make a decision on advertising budgeting for each product considering cannibalization, i.e. competition with the other products in their product line, as well as competition with other competing brands. We find a Nash solution for the advertising budgeting problem of a firm that manages a product line in that market. We compare the optimal advertising level of a firm that have a product line in the market with that of a firm that sells only one brand in the market. And we propose a method to measure the degree of cannibalization. We show the results of our findings empirically with the data from mobile com...