Servitization strategy as a driver of performance: interpreting empirical evidence

Supino Enrico, Tenucci Andrea

Worldwide there has been a significant change in the economic output structure during the last decades. Services are dominating in the traditionally industrialized world (USA and Europe), accounting for over 70% of gross domestic product and continue to grow (WTO, 2010). While service industry in these countries is thriving, manufacturing firms are facing substantial challenges. Manufacturers might enhance their competitive position starting to rely also on service offerings, a process which has been termed “servitization”. Servitization is a trend in which “more and more corporations throughout the world are adding value to their core corporate offerings through services” (Vandermerwe and Rada, 1988). Literature on service (Gebauer et al., 2005) highlights the “service paradox” where substantial investment in extending the service business leads to increased service offerings and higher costs but does not generate the expected correspondingly higher returns. More services doesn’t autoatically mean more revenues and profits. The paper aims at verifying the relationship between servitization and financial performance (service paradox) analysing some variables affecting financial performance. The paper uses a wider service classification and different financial performance measures compared to previous studies. The empirical analysis is performed on firms belonging to manufacturing industries related to machinery, computer and electronic products, electrical equipment, appliance and components, transportation equipment, furniture and related products. After a first selection, the data on 10.995 companies were collected from the ORBIS database, and then the paper focusses on a dataset of 572 companies. The analyses performed consider the provenance of firms and distinguish between EU 15 versus the BRIC countries. In order to better describe the different servitization approaches we use an exploratory multivariate data analysis technique, Multiple Correspondence Analysis.

Key-Words: Misurazione e valutazione delle performance