Cross - National Learning Effects in Global Diffusion Patterns: An Exploratory Investigation
To compete effectively in the global marketplace, marketing managers require insight into how a product gets adopted in different countries. For example, can international marketers identify specific cultural traits that may help them to forecast how quickly a new product will be adopted in a particular country or in a group of somehow related countries? Similarly, can they identify factors that suggest why the adoption process differs among countries? Although these diffusion-related questions address critical issues for international marketing managers, only a few studies have explored cross-national diffusion. To help fill this gap, V. Kumar, Jaishankar Ganesh, and Raj Echambadi present the results of a study that replicates and extends the findings of three previously published studies of cross-national diffusion. Their research aims to replicate four findings from the previous studies: the role of country-specific effects in explaining differences in diffusion parameters, the presence of a lead-lag effect, the use of cultural variables to explain systematically the diffusion patterns across countries, and the merit of country segmentation schemes based on diffusion parameters. They extend the previous research by integrating cross-sectional and time lag variables into a single framework, and they demonstrate how managers can apply this integrated framework for forecasting the diffusion of new products. They replicate the findings from the previous studies by using annual sales data for five product categories (VCRs, microwave ovens, cellular phones, home computers, and CD players) in the following countries: Austria, Belgium, Denmark, Finland, France, Germany, Italy, The Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, and the UK. The product categories and time periods covered differ from the ones in the previous studies; some overlap exists among the countries in this study and the ones in the previous studies. The findings in this study suggest that country-specific characteristics (for example, cosmopolitanism, mobility, percentage of women in the labor force) are useful for identifying the differences in diffusion patterns across countries and innovations. This study also suggests that the lead-lag effect helps to explain differences in diffusion across countries. Factors that this study identifies as possibly influencing the clustering of countries with similar diffusion patterns include timing of entry, geographical proximity, and cultural or economic similarity.