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Staying Power
The role of related experience and geographic
proximity for firm survival in tourism
Patrick Brouder & Rikard Eriksson
Department of Social & Economic Geography
Umeå University
Sweden
Setting the scene
• Area approx. the same size as Great Britain
but with a population of about 900,000
(2/3 in coastal areas)
• Public sector is chief employer in inland and
primary sector (mining, timber) are the
largest private employers
• Public sector has traditionally compensated
for relative underdevelopment but
emphasis is now shifting towards improving
market competitiveness
• Tourism employment up to 6% in some
municipalities
• “a residuum of leftover core activities”
(Anderson, 2000)
• “a Swedish pleasure periphery”
(Müller, 2008)
Theoretical framework
• Linking tourism and economic geography
(Ioannides, 2006, Tourism Geographies)
• Studies of entrepreneurs often focus on
individual characteristics
(Ateljevic & Doorne, 2000; Matlay & Fletcher, 2000; Russell & Faulkner,
2004; Timmermans, 2010; among others)
• Evolutionary approach has routines/skills as focus
(Boschma & Frenken, 2006, Journal of Economic Geography)
• Transfer of knowledge between firms and individuals
(Eriksson, 2011; Boschma, Eriksson & Lindgren, 2009)
• Reasoning from industrial cases to service cases?
• Beyond survival?
Data and variables
• Data: ASTRID: Longitudinal micro-database containing
matched annual data on all workers and workplaces in
Sweden
• 133 cases of new tourism entrepreneurs (1999-2001)
440 time points (richer analysis)
• Dependent variable: Firm failure over a 7 year period
• Key variables (dummies):
tourism related work experience (based on SIC-codes)
local experience (working in same municipality previously)
regional specialisation (many employed in tourism)
•
Controllers: employment previous year, education, gender, age, regional
roots, marital status, local unemployment, Gross Regional Product levels,
number of local micro-firms, number of local tourism firms, share of local
employees in micro-firms, overnight stays, non-tourism management
experience, and, level of benefits received before and at startup
Results I: Kaplan-Meier
(a) Overall survival
(c) Local experience
(b) Related experience
(d) Regional specialisation
Results II: Cox hazard models
Model 1
Model 2
Model 3
Model 4
Success factors
Related experience
56%*
56%*
(0.191)
(0.197)
Local experience
31%**
31%**
(0.166)
(0.164)
Regional specialization
Model score (Prob > Chi2)
0.096*
0.054*
96%
87%
(0.228)
(0.212)
0.264
0.047**
Notes: n=133; percentages in model are hazard ratios standard errors are in parentheses;
*=sig. at 0.1 level, **=sig. at 0.05 level
Note: Control variables omitted from table, only lodging was significant for survival.
Contribution to the local economy?
• 17% of new firms surviving after 7 years
• Median turnover of new firms increases
(from €35,000 to €180,000)
• Mean employees per new firm increases
(from 0.15 to 1.5 employees per firm)
• Performance of extant firms over seven years
(at higher levels but lower rates of increase)
• Smart thinking in entrepreneurial support can help to
optimise survival of new firms in tourism
(how to overcome the experience deficit?)