Using diffusion models to forecast market size in emerging markets with applications to the Chinese car market

Abstract

Marketing managers have to forecast the market size and this forecast guides strategic decisions whether to continue exporting, open new factories or expand existing production operations. Forecasting sales and the market size is a challenging task; even more so in emerging markets where data is limited and the market demand is changeable. This research proposes a novel approach that applies diffusion models using car ownership data to forecast car sales. Car ownership data may be easier to access than sales data in emerging markets but marketing managers are more interested in the sales forecast. Researchers propose using diffusion models to forecast the adoption of new products or products which are new to consumers in a market. This research demonstrates that marketing managers can use diffusion models to predict car sales in China where cars are new products to most consumers in this market. Since the majority of car buyers in China are first time buyers, car manufacturers and retailers must also forecast when the market composition will change. This effectively means predicting when first time car buying will start to slow down and repeat/replacement purchase or second hand car purchase will become more important. To forecast both sales and market composition change, marketing managers must choose a robust model. Managers want insights from models that have been tested robustly especially in less stable market conditions. In this context, this study illustrates the value of using a rolling forecast instead of a fixed horizon approach when comparing and choosing which model to use to forecast both sales and market composition change for the Chinese car market.