1. The Elixir or Burden of Youth? Exploring differences among start- ups and established firms in innovation behaviour in the UK Paola Criscuolo, Nicos Nicolau and Ammon Salter * * Advanced Institute of Management Research

2. Objectives Utilise the improved information on CIS 4 about date of birth of new firm Analyse the innovative activities, the appropriability and search strategies of start-ups Compare the behaviour of start-ups vs. established firms Examine patterns in comparison to internal corporate ventures (start-ups that are part of group)

3. Start-ups and innovation Strengths –Not burdened by history –Strong entrepreneurial spirit – risk taking –Informal and personal culture – organic Weaknesses –Lack of resources – finance, people and technology –Liabilities of newness and smallness –Lack of complementary assets –Underdeveloped relationships with suppliers and customers

4. Data Question 4 NOYES Question 1 YES NO Start-up (1,619) 9.8% Corporate Venture (798) 4.8% Established firm

5. Size differences across firm types and sectors

7. Sectoral and geographical distribution 10% of start-ups are in construction and hotel & restaurant sectors and 19% are in the other business activities sector, which includes: –Business & management consulting, legal & account activities, architectural & engineering consulting, advertising, recruiting agencies Start-ups are concentrated in the South-West & the Midlands, while corporate ventures are mostly found in the South-East, North-West & London

8. Innovative Performance

10. Information sources

11. Innovation sources

12. Protection methods

14. Matching estimator D = 1 if a firms is a new firm (treatment) Yi (1) outcome of the treated: the likelihood of introducing a new product that would be observed if the firm was a new firm Yi (0) outcome of the non-treated: the likelihood of introducing a new product for the same firm if it were not a new firm The sample average treatment effect on the treated (SATT): –SATT=E[Yi(1) -Yi (0)|D=1]=E(Yi(1) |D=1)-E(Yi (0)|D=1) The SATT provides an answer to this questions: –How does being a new firm change the likelihood that a firm will be innovative compared to what it would have experienced if it had not been a new firm?

15. Matching estimator (2) We can estimate E(Yi(1) |D=1) BUT we cannot estimate E(Yi (0)|D=1) The matching estimator uses the average outcome of some similar firms in some observable characteristics (X) who were not exposed to the treatment to estimate E(Yi (0)|D=1) Conditioning on a set of covariates (X): –SATT=E(Yi(1) |D=1, X)-E(Yi (0)|D=1, X)

16. Advantages of the matching estimator over regression analysis Non-parametric method thus it does not require a functional form specification (i.e. innovation function) Regression analysis is not concerned with how similar treated and un-treated groups are in the distribution of the covariates

17. Covariates used to match firms

18. Outcome variables

19. Effects of being a new firm in manufacturing

20. Effects of being a new firm in services

21. Results New firms differ from established firms: –New firms are more innovative in services BUT not in manufacturing –New firms are more open to use draw knowledge from external sources and to adopt new organisational and managerial practices –New firms are more likely to use appropriability methods in services –New firms are no different from established firms in their pattern of collaboration

22. Policy Implications Distinguishing between new and established firms and not only between SMEs and large firms Policy should target new firms in manufacturing where the liabilities of newness may be stronger Encourage established firms to become more open to external knowledge sources

23. Limitations We only analysed the innovative behaviour of young firms with more than 10 employees We cannot compare firms with exactly the same age