Review of Industrial Organization 19: 305–328, 2001. © 2001 Kluwer Academic Publishers. Printed in the Netherlands. 305 The Determinants of Technology Adoption in Italian Manufacturing Industries ⋆ ELEONORA BARTOLONI National Institute of Statistics (ISTAT), Milano, Italy E-mail: Bartolon@Istat.it MAURIZIO BAUSSOLA ⋆⋆ Catholic University, Department of Economic and Social Sciences, Piacenza E-mail: Baussola@mi.unicatt.it 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. I. Introduction 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 technologies. 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.