Review of Industrial Organization 19: 305–328, 2001.
© 2001 Kluwer Academic Publishers. Printed in the Netherlands.
The Determinants of Technology Adoption in
Italian Manufacturing Industries
National Institute of Statistics (ISTAT), Milano, Italy
Catholic University, Department of Economic and Social Sciences, Piacenza
Abstract. The adoption of new technologies in Italian manufacturing industries is analysed using
data for 13,334 ﬁrms selected from the 1990–92 Community Innovation Survey. The determinants
of technology adoption are analysed in an econometric framework (logit model) which is a general
test of different theoretical explanations of technological diffusion. We particularly refer to the rank,
epidemic and information effects which signiﬁcantly affect the use of new technology in Italian
manufacturing industries. We use a set of explanatory variables which enables us to set up a well
speciﬁed empirical model and to use odds ratios to determine the effect of their changes on the
adoption probability, thus giving a more precise picture of the determinants of technology adoption.
Key words: Innovation, logit models, technological diffusion.
JEL Classiﬁcations: O30, O40.
The empirical analysis of technological diffusion has concentrated on general tests
concerning the impact of different explanatory variables on the adoption decision
of ﬁrms. The debate has emphasized the role of market structure and ﬁrm size,
following the seminal analysis by Schumpeter (1942). In addition, the economic
analysis of technological change has been further improved by different analyt-
ical approaches, i.e., game theory, the economics of information and integrated
models focusing on both demand and supply factors affecting the diffusion of new
However, these improvements on theoretical grounds did not bring about new
empirical investigations trying to test the relevance and signiﬁcance of these hetero-
geneous approaches. There is therefore a need for testing by empirical investigation
We would like to thank two anonymous referees for their helpful comments on an earlier draft
of this paper. Needless to say the usual disclaimer applies.
Financial support from CNR is gratefully acknowledged.