Geography Reference
In-Depth Information
time of entry, which shapes long-term performance. This competence is acquired from
i rms in related industries and prior entrants in the same industry.
The stock of incumbents and i rms in related industries in a region determines the
entry rate and post-entry performance of i rms in this particular industry. The dif erences
in entry by region are not necessarily determined by dif erential distance to buyers and
suppliers, thick labour markets, or to spill-overs between i rms (more likely to be within
i rms, with employees spinning out afterwards). They explain the market conditions con-
ducive to spin-of s, the types of i rm that spawn spin-of s, and the relationship of spin-
of s to their parents. The model is tested using detailed data on entrants in industries like
automobiles (Boschma and Wenting, 2007; Carroll et al., 1996; Klepper, 2002, 2007),
tyres (Buenstorf and Klepper, 2009), television receivers (Klepper and Simons, 2000),
lasers (Klepper and Sleeper, 2005; Buenstorf, 2007), semiconductors (Moore and Davis,
2004), law i rms (Phillips, 2002), accounting (Wezel et al., 2006), footwear (Sorenson
and Audia 2000), fashion design (Wenting, 2008), and software (Buenstorf and Fornahl,
2009). Their i ndings support the basic premise of the model that spin-of s inherit knowl-
edge from their parents that shapes their nature at birth and their survival chances.
Industry structure
New i rm formation across regions can be explained by dif erences in the regional com-
position of industries and by dif erences in one particular industry in specii c regions.
The latter would indicate that there are context-specii c dif erences af ecting entrepre-
neurship rates, while the former would indicate that the explanation should largely be
sought in the specii c industry structure of the region. The industry structure of a region
af ects the overall new i rm formation rates in a region, as industries dif er in their degree
of contestability (entry barriers) and the extent to which entrepreneurial opportunities
emerge (e.g. many in business services and few in mining).
Sometimes both the industry structure and the regional context are favourable for new
i rm formation in a region; this can for example be found in the south-east of the UK,
which has both a favourable industry mix (especially construction, service, and i nance
and related sectors) and favourable local conditions. In contrast, regions like Northern
Ireland, Scotland and Wales suf er from a combination of both an unfavourable industry
mix and unfavourable local conditions for new i rm formation. Often the industry mix
component dominates the local conditions component in statistical analyses of determi-
nants of regional i rm formation rates (Fotopoulos and Spence, 2001).
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Several mechanisms related to the industry structure can be at work in a region, to
produce something that academics and policymakers like to call a cluster (Martin and
Sunley, 2003). Two important concepts connected to clusters are localization econo-
mies and related variety. The i rst concept has a long history in the academic literature
(Chinitz, 1961; Hoover, 1948; Malmberg and Maskell, 2002; Marshall, 1890), while the
second one is only recently recognized in evolutionary economics (Frenken et al., 2007)
and organizational ecology (Audia et al., 2006).
Localization economies involve agglomeration economies resulting from the concen-
tration of the same or similar activities: for example, benei ts resulting from the local
access to a specialized work force or the specialized reputation of a locality, while related
variety emphasizes the positive ef ects (on entrepreneurship, innovation) of the co-
presence of dif erent but related industries or organizational populations. Regions that
