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8/3/2019 Analysing and Measuring Business Growth
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Warwick Business School
Analysing and measuring
business growth
12 October, 2011
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Warwick Business School
Key learning objectives
Understand six different approaches to
business growth
Be able to compare and contrast these different
approaches to business growth
Begin to develop your own opinions on fast-
growth businesses
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Six approaches to business growth
1. Evolutionary approaches to growth
2. Social network approaches to business growth
3. Resource-based views and learning approaches
4. Managerial approaches
5. Economic approaches
6. Stochastic approaches
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Do individual firms follow an organic
pattern of development?
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Issues with stage theories
Closure rather than growth is the norm
One-size-fits-all approach: heterogeneity in the
business population
Growth is unidirectional but reality is much morespotty
Number of stages and crises?
Importance of informal managerial interactions Intuitively appealing but little conceptual or
empirical reliability
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Evolutionary approaches: population
ecology
Tends to study demographic dynamics within firm
populations (operationalised as sectors or
industries). Focus tends to be on founding (business
entry) and mortality (disbanding) not why (some)firms grow
Legitimation, environmental resources (richness of
inputs and demand for products/services) and
competition between firms determines outcomes
This shows three patterns in industries:
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Victorian Railways
0
50
100
150
200
250
300
No. of Companies Sanctioned Capital Authorised (m)
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The population dynamics of automotives, tyres,
television and penicillin
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Growth and population ecology
Firms may grow because they overcome the liability
of newness (legitimation effects) and liability of
smallness
Entrants can also supplant existing players becausethey have new organizational routines that overcome
the structural inertia of existing firms (theory
assumes that most firms stick to the routines they
developed when they were relatively new and asthese routines age, they are less and less suited to
the environment)
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Growth and population ecology
Growth firms are those that are have a superior fit
with the environment and/or there is little
competition in the resource environment
Existing firms can seek to reconfigure their approache.g. specialist (focus on a narrow niche) and
generalist strategies (focus on wider niche) (web
browser wars between Netscape Navigator/Firefox &
Internet Explorer)
Criticism is that it gives little weight to the activities
of individuals/firms
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Social network approaches: Version 1
networks
Focus on individuals:
a set of actors (individuals or organizations) and aset of linkages between the actors (Hoang andAntoncic, 2003: 168). Environmental resource andcompetition determines outcomes
Or on businesses:
a firms set of relationships with other organisations(Perez and Sanchez, 2002: 261)
Growth associated with trust, the nature ofrelationships (strong and weak ties) and tacitknowledge
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Three network approaches
1. Network magnitude (entrepreneur needs to
network widely to grow)
2. Network closure (entrepreneur relies on smallnumber of strong ties)
3. Network position (entrepreneur acts as a
gatekeeper between networks)
http://www.google.co.uk/imgres?imgurl=http://thesituationist.files.wordpress.com/2008/03/istock-social-network.jpg&imgrefurl=http://thesituationist.wordpress.com/2008/03/03/social-networks/&usg=__2q1lc73_Qe8pq9fabUHvojV1Exs=&h=387&w=310&sz=39&hl=en&start=4&zoom=1&um=1&itbs=1&tbnid=reNdF88wHnogvM:&tbnh=123&tbnw=99&prev=/images?q=networks&um=1&hl=en&rlz=1I7GZEZ_en-GB&tbs=isch:18/3/2019 Analysing and Measuring Business Growth
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Issues with networking
Difficult to measure association between
networking and growth (definitional issues and
hindsight bias)
Trust is a two-way street: may not be
beneficial
Limited evidence to support influence of
networking (non-linear association?)
Networking is important but showing its
influence has proved elusive
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Basis of cluster approach
Marshalls (1890) agglomeration thesis looks at
the benefits of being located close to other
businesses
Access to specialist pools of labour
Saves on costs (e.g. lower transportation costs)
Potential for knowledge spillover effects (know how
and know who) Cluster analysis essentially based upon this but
emphasises knowledge spillovers
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Cluster approach
Porter (2003) defines it as: a geographically proximate group of
interconnected companies, suppliers, service
providers and associated institutions in a particular
field, linked by externalities of various types (p.562).
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Boston life science cluster
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Evidence for clusters
Delgado, Porter and Stern (2010) suggest using USdata that:
Strong clusters more likely to see stronger growth rates instart ups
Strong clusters enhance the employment in new small firms
Strong clusters enhance employment growth of existingfirms
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Martin and Sunleys (2003) critique
Not a new approach: just old wine in new bottles
Vague and elastic definition
Difficult to empirically verify
Heterogeneity and idiosyncratic businesses andregions
Hermetically sealed
Economic not spillover effects are more important
Represent a one-way bet
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3. Resource-based views and
learning approaches to growth
RBV is based on Rumelts (1991) finding that
what a business does is more important to its
performance than external conditions
Basis of approach:
Businesses as bundles of resources
Resources are heterogeneous and idiosyncratic
Resources are immobile
Resources are path dependent
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RBV approach
Valuable, rare, imperfectly immobile and non-
substitutable (VRIN attributes)
Growing businesses have VRIN attributes
Resources (physical resources) is important but moreso is capabilities (being smart)
Linked to dynamic capabilities (ability to reconfigure
business) and absorptive capacity (ability and limitsof learning)
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Issues with approach
Tautological
How do businesses know they have the
capabilities? How come researchers can work it
out but not competitors?
Assumes (continuous) returns to learning
whereas growth is spotty
Hindsight bias of entrepreneurs?
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4. Entrepreneurial management
approaches
Trait-based approach
Management style
Intentions and entrepreneurial orientation
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Trait-based approach
Assumes that entrepreneurs have the right stuff in
their psychological make up (e.g. risk behaviour,
locus of control, tolerance of ambiguity)
Has proved to be a bit of a dead end (Gartner, 1988) Stronger version is Shane et al (2010) who examined
twins and found that 2 of the big 5 personality
traits are associated with being self-employed
(extraversion and openness to experience but not
agreeableness, conscientiousness or emotional
stability)
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Scott and Bruces (1987) managerial
styles
Like stage models, appealing but conceptually
and empirically weak
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Intentions
Some evidence that intentions are linked to
growth (Hakim, 1989)
Wiklund and Shepherd (2003) suggest that the
relationship is likely to be indirect
Rely on self-report measures
Sufficient but not necessary condition?
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Entrepreneurial orientation (EO)
Focus on the orientation of business (e.g.
innovation, risk taking, aggressiveness)
Some evidence to support EO but not all factors
equally supported
People do business: wrong unit of analysis?
Overall some evidence with this approach of an
indirect impact on business growth
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5. Economic approaches
Wide variety of approaches from the simple
(neo-classical) to evolutionary economics
Shared interest with other approaches
(e.g. learning, dynamic capabilities)
Share, therefore, similar frailties
Economic approaches still more likely to
emphasise cost
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6. Stochastic approaches: Version 1
Jovanovic (1982)
Dont know entrepreneurial talent before entry
but if have talent more likely to grow
afterwards
Random because high (low) talent individuals
may get unlucky (lucky) draws
Emphasis is on passive learning by
entrepreneur of their talent
May be modified to make them active learners
(links to RBV)
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Stochastic approach: Version 2
lottery effects
Entrepreneurs are those with the winning ticket
No good asking them they are faulty guides
Growth isnt serially correlated
Older and bigger businesses dont have
stronger growth outcomes
Coads (2007) review of growth studies show
that they can explain only 15 per cent: other 85
per cent is random
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Conclusions
Spectrum of explanations from the more
deterministic to the random
Each have advantages and disadvantages
Your task is to critically evaluate each of these
approaches