Heterogeneity of innovation strategies and firms’ performance

[PAPER PRESENTED AND SELECTED FOR PUBLICATION AT THE 11TH INTERNATIONAL J.A. SCHUMPETER SOCIETY CONFERENCE ON “INNOVATION, COMPETITION AND GROWTH: SCHUMPETERIAN PERSPECTIVES”, NICE - SOPHIA ANTIPOLIS, 22-24 JUNE, 2006]

Giovanni Cerulli and Bianca Potì
CERIS - CNR
Via dei Taurini, 19
00185 Rome, Italy
g.cerulli@ceris.cnr.it; b.poti@ceris.cnr.it,

ABSTRACT. This work deals with two main issues: first, the possibility of identifying differences in firm economic returns (operating profit margins) for different groups of innovation strategy and second, the possibility of checking for factors explaining the probability of being within the best performers for each group of innovation strategy. It is an empirically based analysis using descriptive statistics (first part) and a probit econometric analysis (second part) where data are collected at firm level from two CIS surveys matched with economic accountability data for 902 Italian manufacturing firms for the period 1998-2000. The distribution analysis of profit margins by different populations of firms shows a better economic performance for groups characterized by more complex innovation strategies. Unexpectedly, the risk associated to economic returns is lower for groups where returns’ mean is higher. In this case skewness is higher too suggesting that reaching “excellence” is more difficult. The probit regressions account for the role played by different (market and firm) factors on the probability of being the best positioned for each firm population. This work gives two main messages: first, when studying the impact of R&D activity (both on firm productivity or competitiveness) it is worth to distinguish among different kinds of innovation strategy rather than limiting the analysis to aggregated results and second, it appears quite clear that competition awards more complex innovation strategies than simple R&D intra-muros activity.

KEYWORDS: profitability, strategic heterogeneity, R&D and innovation, probit regression

JEL CODES: L60, L10, O30, C25

ACKNOWLEDGEMENT. This paper has been realized within the ongoing Italian FIRB 2005-08 research project financed by the MIUR entitled “Modelli e strumenti per la valutazione dell’impatto, a breve e medio termine, degli investimenti in ricerca e innovazione delle imprese sul sistema produttivo del paese”, conducted by the Ceris-CNR in collaboration with ISTAT, Confindustria and Cilea. We wish to thank all the research’s members for their useful suggestions and in particular dr. Claudio Cozza for his effort and help in the dataset construction and assistance. We are also grateful to prof. Fabiano Schivardi for his reading and punctual comments on the paper.