Mapping the Dynamics of Management Styles —Evidence from German Survey Data

Abstract

We study how firms adjust the bundles of management practices they adopt overtime, using repeated survey data collected in Germany from 2012 to 2018. By employingunsupervised machine learning, we leverage high-dimensional data on human resourcepolicies to describe clusters of management practices (management styles). Our resultssuggest that twomanagementstyles exist, one of which employs many and highlystructured practices, while the other lacks these practices but retains training measures.We document sizeable differences in styles across German firms, which can (only)partially be explained by firm characteristics. Further, we show that management ishighly persistent over time, in part because newly adopted practices are discontinuedafter a short time. We suggest miscalculations of cots-benefit trade-offs and non-fittingcorporate culture as potential hindrances of adopting structured management. In light ofprevious findings that structured management increases firm performance, our findingshave important policy implications since they show that firms which are managed in anunstructured way fail to catch up and will continue to underperform.