The establishment mode choice of German multinational enterprises in Brazil: A comparative approach

We examine the drivers behind the establishment mode choice of German multinational enterprises (MNEs) in the sectors of Automotive, Chemicals and Mechanical Engineering in Brazil for the years 1993-2013 using a novel sample of primary data obtained directly from German MNEs. Based on prevalent theories found in the literature, we test the most common hypotheses on our sample. Firms with high R&D activities and firms with prior market knowledge in Brazil in from of previous sales offices are more likely to enter Brazil by a Greenfield investment. We also show that it is the specific private ownership of the German so-called hidden champions that drive those specific SMEs to enter Brazil by Greenfield, a sneaking suspicion that has been made before. Finally, we show that the establishment mode choice between Brazil and the USA only deviates to a low extent, with German MNEs preferring to enter Brazil by Greenfield and the USA by M&A. Thereby, we provide valuable insights for future research in this field.

How can clusters help in the product type choice? The case of a specialized retail store

This work project (WP) is a study about a clustering strategy for Sport Zone. The general cluster study’s objective is to create groups such that within each group the individuals are similar to each other, but should be different among groups. The clusters creation is a mix of common sense, trial and error and some statistical supporting techniques. Our particular objective is to support category managers to better define the product type to be displayed in the stores’ shelves by doing store clusters. This research was carried out for Sport Zone, and comprises an objective definition, a literature review, the clustering activity itself, some factor analysis and a discriminant analysis to better frame our work. Together with this quantitative part, a survey addressed to category managers to better understand their key drivers, for choosing the type of product of each store, was carried out. Based in a non-random sample of 65 stores with data referring to 2013, the final result was the choice of 6 store clusters (Figure 1) which were individually characterized as the main outcome of this work. In what relates to our selected variables, all were important for the distinction between clusters, which proves the adequacy of their choice. The interpretation of the results gives category managers a tool to understand which products best fit the clustered stores. Furthermore, as a side finding thanks to the clusterization, a STP (Segmentation, Targeting and Positioning) was initiated, being this WP the first steps of a continuous process.