Empirical Taxonomy of Start-Up Firm Growth Trajectories

1. Université catholique de Louvain Empirical Taxonomy of Start-Up Firm Growth Trajectories Mahamadou Biga D., D. François, B. Gailly, M. Verleysen, V. Wertz Centre for Research in Change, Innovation and Strategy Louvain School of Management www.crecis.be Machine Learning Group Engineering Faculty www.ucl.ac.be/mlg

2. How do “promising” firms grow and develop over time? Do typical growth trajectories exist? What are the key characteristics of these growth trajectories? “Promising” firms generate significant wealth and jobs OECD; Audretsch & Turik,; Storey; Birsch… Knowledge about new & small firm growth remains scattered Wiklund & Shepherd; Delmar et al; Davidsson & Wiklund… Longitudinal approaches generate methodological challenges Garnsey & Heffernan, Garnsey et al. ; Davidsson & Wiklund… Motivation

3. Use of multiple economic data (10 indicators) Focus on growth trajectories Analysis across multiple sectors Proposed approach Growth is a multidimensional process Wiklund, 2004; Delmar & et al., 2003; Dess & Lumpkin, 2001; Weinzimmer et al., 1998; Lumpkin & Dess, 1996; Birley & Westhed, 1990; Cameron, 1978. Growth is a longitudinal process Garnsey et al., 2006; Busenitz et al., 2003; Chandler & Lyon, 2001; Pettigrew et al., 2001; Davidsson & Wiklund, 2000;… Growth is an ubiquitous phenomenon Delmar & Davidsson, 1998; Delmar et al.,2003

4. Methodology 1/2: « Promising firms » Sales Employment Assets 10 years Excluded firms Sample of 741 “promising” firms with complete trajectory, out of 17,168 firms created between 1992 and 2002 in Belgium. “Promising” firms Threshold of micro-firm size Firm age

5. Employment (above 9) 50% 5% 1% 2% Assets (above 2M€) Sales (above 2M€) 33% 3% 8% Importance of using multidimensional approach Share of firms growing beyond micro-firm level based upon criteria selected to measure growth. (n=741)

6. Ubiquity of ‘‘promising firms’’ Sector distribution High-tech vs. low-tech distribution

7. ●● ●●●● ● ● ●●● ●●●●● ● ●●●● ●●● ● ● ● ● ●● ●● ● ● ● ●● ●●●●● ● ● ● ●● ●●● ●● ● ●● ●● ●●●● ● ●● ●●● ●●●●●●●●●●●●●●●●●●●●●●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●●●● ●●●●● ●● ●●●● ●● ●● ●●● ● ●● ● ● ● 2 ●● ●●●● ● ● ●●● ●●●●● ● ●●●● ●●● ● ● ● ● ●● ●● ● ● ● ●● ●●●●● ● ● ● ●● ●●● ●● ● ●● ●● ●●●● ● ●● ●●● ●●●●●●●●●●●●●●●●●●●●●●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●●●● ●●●●● ●● ●●●● ●● ●● ●●● ● ●● ● ● ● ----- ----- 21234 ----- ----- ----- 1 4 3 Clustering and discretization Sequence analysis Methodology 2/2: Discretization ●● ●●●● ● ● ●●● ●●●●● ● ●●●● ●●● ● ● ● ● ●● ●● ● ● ● ●● ●●●●● ● ● ● ●● ●●● ●● ● ●● ●● ●●●● ● ●● ●●● ●●●●●●●●●●●●●●●●●●●●●●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●●●● ●●●●● ●● ●●●● ●● ●● ●●● ● ●● ● ● ● Multidimensional representation of growth trajectories

8. 7 Typical growth trajectories identified • Grow as a question mark • Grow as a start-up • Grow as a star • Grow as a boutique • Grow from start-up to question mark • Grow from start-up to boutique • Grow from start-up to star vii ii iv v vi i iii Span (years) 4 5 6 n 602 521 431 Share of firms adopting one of 7 58 % 50 % 42 %

9. Conclusions & Further Work • Original empirical approach based on systematic clustering and classification • Relevance of longitudinal and multidimensional approach based on economic data • Identification of several possible growth trajectories beyond classical “start-ups” profiles Further interpretation could rely upon international sample, in-depth case studies or use of more complete data (business model, entrepreneur’s motivation, competitive environment….)