On the Predictive Power of Market Share Attraction Models

Abstract

The authors test Naert and Weverbergh's empirical finding that attraction-type specifications are characterized by a predictive power greater than that of their nonrobust counterparts. The empirical results, obtained by use of data on the German cigarette market, do not support the conclusions of Naert and Weverbergh.

There Is No Aggregation Bias: Why Macro Logit Models Work

“…Surprisingly, studies have shown (see Leeflang and Reuyl 1984) that the three models perform similarly in practice, despite the severe restrictions that the independence of irrelevant alternatives (IIA) property of the logit model imposes on the data. In addition, practitioners find that the logit model, which was developed for micro-level data, performs well with aggregate-market-share data.…”

Analyzing the effects of a brand introduction on competitive structure using a market share attraction model

“…We choose to analyze market shares and to measure the effectiveness of marketing instruments of different brands using the familiar market share attraction model (Bronnenberg, Mahajan, & Vanhonacker, 2000;Cooper & Nakanishi, 1988;Leeflang & Reuyl, 1984;Naert & Weverbergh, 1981). An advantage of using market shares is that these are in general not influenced by category expansion or contraction.…”

On Inferences Concerning Market Shares

“…The large literature on the determinants of market shares (see, for example, Batsell and Polking 1985, Brodie and de Kluyver 1984, Ghosh, Neslin and Shoemaker 1984, Leeflang and Reuyl 1984, Kamakura and Srivastava 1984, Karnani 1985, and references therein) is indicative of the importance often attached to relative market performance, in addition to (or, occasionally, in place of) absolute performance. Instances abound in which, for example, firms consider that a declining market share is cause for concern, even when dollar sales and profits are increasing.…”