GLOBELICS ACADEMY 2004 May 25 – June 3, LISBON, PORTUGAL INCUBATION POLICY :

1. GLOBELICS ACADEMY 2004 May 25 – June 3, LISBON, PORTUGAL INCUBATION POLICY : SUPPORTING THE NEEDS OF HIGH TECHNOLOGY BASED FIRMS Danny P. Soetanto Faculty of Technology Policy and Management Delft University of Technology, Delft, the Netherlands

2. Structure of the presentation • Aim of the research • Introduction to the research problems • Problems in the study • Theoretical perspective • Literature review (S&T Parks definition and performance measurement) and empirical studies on the obstacles faced by new high technology firms. • Conclusion

3. Aim of the research(preliminary) To identify design rules of incubation policy to support the growth of new technology-based firms under certain condition (e.g. national innovation system, culture)

4. Introduction to the problem • Competitive advantage of the region determined by their level of innovativeness. • One of the best policies adapted by many regions in the world, is endorsing the development of small high tech firms. • Why do small high-tech firms need support? • They face many obstacles compared with other types of firms • They face a high risk • They are often in the dilemma of exploring new market (innovative) or exploiting the existing market.

5. Introduction to the problem The type of support provided by incubation policy • Selection process • Supply of • Financial support • Cheap and flexible space • Shared services • Courses and training • Access to knowledge at university • Monitoring activity

6. Problems in the study Three fundamental questions in the early stage of my research (year 1): • What is the definition of incubator? S&T Park? Technology Park? • How to evaluate the performance of incubator, S&T Park, etc? • What are the major obstacles faced by new technology based firms? Methods used to answer the question • Literature review • Experiment with Meta analysis Rough set / cluster and Survey / in depth interview

7. Park Launch Size (ha) Academic link Stakeholders Supply Innotech Budapest (Hungary) 1987 0.9 Technical university of Budapest Collaboration of university, local and national government Estate, maintenance, business support service (incubator) Ideon Science Park (Sweden) 1983 14.8 Lund university Collaboration of private, local government, university Estate, maintenance, laboratory & workshop, commercial service Surrey research park (United Kingdom) 1984 28.3 University of Surrey University of Surrey Estate, maintenance, laboratory & workshop, commercial service Singapore science park (Singapore) 1984 115 None Owned by government but privatized in 1990 Estate, maintenance, no business support service (incubator) Research Triangle Park (US) 1959 2712 Six universities in North Carolina region Research triangle foundation – private, non profit Estate (sold), maintenance A wide diversity of S&T Parks

8. Assets Growth Reversal Growth Reinforcement Generate Resources Stability Mobilize Resources Failure Access Resources Time Theoretical Perspective • Resource-based theory (Penrose, 1959) Adapted from Reid and Garnsey (1998)

9. Theoretical Perspective Spin offs subject to incubation policy Viable firms as output Initial resources Admission criteria Additional resources

10. Stakeholders Role of real-estate development Role of attracting outside firms Type of linkage with university Availability of incubation facility Types of activities Classification of S&T Parks • Literature study

11. Classification of S&T Parks Industrial Parks • Major actors : government and a mix of actors including real estate development agencies. • Goal : attracting firms from outside the region (often FDI). Research Parks • Major actors : combination of actors (local government, university, real estate developers). • Goal : to attract R&D activities. Incubation Parks • Major actors : university and local government • Goal : to provide incubation facilities to support new firms development

12. Previous studies in measuring the performance of S & T Parks Methodology : • Longitudinal approach versus one point in time approach. • Micro approach (firm) versus macro approach (regional). • Process approach (e.q. quality of the management of the parks) versus output approach (e.q. number of firms established). • Comparing with control group (on-site firms and off-site firms) versus analysis of the performance of the park itself. • Direct impact versus indirect impact (multiplier effect).

13. Previous studies in measuring the performance of S & T Parks • The most common indicator : on-site job creation. • Few authors measure impact at a longer timescale in a comprehensive way. • The most common indicator : regional economic. • Few authors use specific performance indicators, like mutual links between S&T Parks residents and university and quality of the management team.

14. Performance indicators Policymakers Researchers T - test Mean Std Mean Std Patents per 1000 habitants 1.40 0.60 0.69 0.85 0.009* University spin off companies 1.65 0.75 1.92 0.28 0.217 Spin-off and startup growth 1.80 0.41 1.46 0.52 0.045* PhD's working in business and industry 1.00 0.79 1.61 0.65 0.027* R&D driven companies 1.95 0.22 1.54 0.77 0.032* Differences in perception of performance measurement * Significant at .05 level

15. Characteristics of TU Delft spin offs • Age of the firm < 3 years (39.5 %) 3-5 year (32.5 %)  6 year (27.9 %) • Innovative level ‘New to the sector’ 45.2 % Not ‘new to the sector 54.8 % ‘Breakthrough’ 39.5 % Not a ‘breakthrough’ 60.5 % • R & D activity Firms with own R&D activity 85.4 % Firms without R&D activity 14.6 %

16. Results of Descriptive Statistics • The major obstacles to grow : Marketing 14.5% 1 Uncertainty 13.8% 2/3 Cash flow 13.8% 2/3 Sales skills 12.3% 4 Management 10.1% 5

17. Results of Regression Analysis The factors that determine the growth of the firms (measured by the job growth) are : Number of the founders Age of the firms Internal support External support Lack of marketing knowledge * Dealing with uncertainty * * Significant at .05 level

18. Obstacles < 3 years 3-5 years  6 years Market-related 15 7 8 Financial 16 4 3 Management-related 13 8 3 Totals obstacles (incl. others obstacles) 55 21 15 Total firms 17 14 12 Average number of obstacles / firm 3.24 1.50 1.25 Obstacles per age category

19. Obstacles per age category

20. Statistical test • Result : • Age category and market related obstacles : .569 • Age category and financial obstacles : .024 * • Age category and management obstacles : .046* * Significant at .05 level • Preliminary interpretation : • The financial and management obstacles are declining over time • The market related obstacles are not declining over time

21. Obstacles over time 56.9 % 93.5 %

22. Preliminary Conclusion • The typology of S&T Parks (industrial parks, research parks, incubator parks) • The performance of policies to foster new technology firms through S&T Parks is difficult to measure through conventional methods. We prefer to introduce a new method using the participation of different stakeholders. • Highly innovative firms face a somewhat higher level of obstacles in the beginning compared to all spin offs. • The problem incidence among highly innovate firms, however decreases at a much higher rate (by 94%).

23. Research question • What are the types of obstacles that influence the growth of new technology-based firms? In which stage of the firm’s development do the obstacles appear? And what factors cause the obstacles? • What strategies of technology incubator are effective in supporting new technology-based firms to overcome their obstacles? • In applying those strategies, what management model of technology incubators is appropriate? What requirements are needed for those strategies? • Obstacles : market related obstacles

24. Phases I Preparation Exploring the incubation process & incubators’ performance evaluation Phase II Overview Empirical analysis of incubators’ performance Research on firm’s critical junctures Initial hypotheses Case study Selection Phase III Case studies (International Comparison) Case study analysis International comparison Hypotheses Reformulation Model of incubation process Phase IV Designing rules Testing on expert opinion Model of incubation process Phase V Conclusion Conclusion – Writing dissertation Research Design

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