Productivity Effects of Organizational Change:
Microeconometric Evidence
Joint with Irene Bertschek
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Abstract: This paper analyzes the relationship between investment in information
and communication technologies (ICT), non-ICT investment, labor productivity
and workplace reorganization. Firms are assumed to reorganize workplaces
if the productivity gains arising from workplace reorganization exceed the associated reorganization costs. Two different types of organizational change are
considered: introduction of group-work and flattening of hierarchies. Empirical
evidence is provided for a sample of 411 firms from the German business-related
services sector.
We develop and estimate a model for labor productivity and firms' decision to re-organize workplaces that allows workplace reorganization to affect any parameter
of the labor productivity equation. Our general and flexible methodology allows
to properly take account of strategic complementarities between the input factors
and workplace reorganization. The estimation results show that changes in human
resources practices do not significantly affect firms' output elasticities with
respect to information and communication technologies (ICT), non-ICT capital
and labor although most of the point estimates of the individual output elasticities
and of the control variables for observable firm heterogeneity are larger
if workplace reorganization is realized. We therefore apply Kernel density estimation
technique and demonstrate that for firms with organizational change
the entire labor productivity distribution shifts significantly out to the right if
workplace reorganization takes place, indicating that workplace reorganization
induces an increase in labor productivity that is attributable to complementarities
between the various input factors and workplace reorganization. By contrast,
firms without organizational change would not have realized significant productivity
gains if they had reorganized workplaces.
Keywords: workplace reorganization, ICT-investment, labor productivity, endogenous switching regression model, Kernel density estimation
JEL classification: C25; D24

Status: forthcoming in Management Science
Additional information:
- Click
here to download the software code we used (GAUSS)!
- Click
here to download Appendix A: the Maximum Likelihood function
- Click
here to download Appendix B: descriptive statistics of key variables
- Click
here to download Appendix C: Estimating productivity differentials
- Click
here to download Appendix D: estimation results for separation equations
- Click
here to download Appendix E: caveats