1. INNOVATION AND DYNAMICS IN HIGH-TECH INDUSTRIES Isabel Almudí, Francisco Fatás-Villafranca, Luis R. Izquierdo Universidad de Zaragoza; Universidad de Burgos

2. Motivation I In certain times, in Science-based industries -chemicals, semiconductors, pharmaceuticals, medical devices or computer hardware and software- a few firms have managed to achieve commercial and technological leadership. (Malerba, 1985; Chandler, 1990; Nelson and Wright, 1992) These apparently solid leadership positions can be suddenly altered by processes of catch-up and surprising leadership shifts. (Amsden, 2001; Murmann, 2003).

3. Motivation II The economic and strategic importance of these industries has fostered a large amount of literature devoted to the study of the sources of industrial leadership in high- tech industries. These works have linked the emergence of industrial leadership with certain processes of co-evolution between strategic, technological and institutional factors (Nelson, 1992; Freeman, 2004)

4. Motivation III Recent empirical work has identified a number of robust statistical regularities in industrial dynamics such as : (a) persistence of heterogeneity at the micro-entities (firms) (b) continuous changes in market shares and profitability. (Dosi, 2007; Botazzi et al., 2008) These empirical findings, interpreted within the framework of Evolutionary Economics, suggest the existence of rich and complex dynamics of learning, competition and growth.

5. Motivation III Recent empirical work has identified a number of robust statistical regularities in industrial dynamics such as : (a) persistence of heterogeneity at the micro-entities (firms) (b) continuum changes in market shares and profitability. (Dosi, 2007; Botazzi et al., 2008) These empirical findings, interpreted within the framework of Evolutionary Economics, suggest the existence of rich and complex dynamics of learning, competition and growth. The main aim of this work is to understand the micro-foundations of some of these dynamics processes.

6. The Model-Outline 1.There are n-firms competing world-wide, in a high-tech sector. 2.Firms compete in price and product performance. Firms set prices according to their market share. Firms improve product performance by investing in R&D (firms decide how much to invest in R&D looking at the most profitable firm). 3.Demand-driven production. Each firm adapts its level of production to the level of demand. 4.Global demand and global capital remain constant over time. 5.Unit costs of production are constant and equal for all firms.

7. The Firms' Competitiveness We assume that firms fix prices by applying a mark-up over their unit cost. The mark-up is higher, the higher the market share of firm is.

8. Demand Transformation Consumers interact among them and diffuse information about prices and performances of the different products. There is a gradual process of demand transformation so that, consumers will avoid buying products from those firms which have higher prices and lower performance.

9. Production We assume, for simplicity, that all firms produce according to a given technology. We assume that each firm's rate of growth fits the growth rate of its demand.

10. R+D expending Firms spend in R&D activities a proportion, r it, of their profits. r it is a firm-specific operating routine. We consider that firms adapt this routine by trying to imitate the behavior of their most successful rival.

11. Product Innovation An innovation equation of the type of Nelson-Phelps (1966) extended by Benhabib y Spiegel (1994; 2002). R it is the R&D spending and z it is the R&D productivity. Phi, represents the degree of imitability u it represents the possibility of finding new innovations.

12. Demand Product Performance R&D over profits R&D expenditure Profits Competitiveness Market share Price Production Capital

13. Posible questions 1.Relation between product performance and profits. 2.Conditions for the emergence of a monopoly. 3.The impact of the random variables in the dynamic of the model. 4.The impact of the parameters in the dynamics of the model. 5.….

14. Simulation Results 1.The model has been implemented in Mathematica and in NetLogo. 2.Examples

15. MATHEMATICANETLOGO

16. MATHEMATICANETLOGO

17. THANK YOU! ialmudi@unizar.es