Musings on Growth. Dimo Dimov presentation.ERC Understanding Small Business Growth Conference 2015

1. Musings on growth:
Schrodinger’s Cat, Wicked Problems and
Entrepreneurial Opportunities
Dimo Dimov
University of Bath
ERC Conference
Understanding Small Business Growth
11 February 2015

3. Replication and partitioning
• Multiple observations need to be aggregated
• Observations are, literally, not identical
• Major judgments to be made:
– Which observations are identical? (replication)
– Which observations are different? (partitioning)
• Such decisions are arbitrary and tentative
3
McGrath (1982)

4. Time
Effort 1
Effort 2
Effort 3
Non-partitioned observation space
Observation space partitioned for variance
Non-partitioned observation space
McMullen and Dimov (2013)

5. What are firms?

6. Time
Time
Effort 1
Effort 2
Effort 3
Observation space partitioned for variance
Effort 1
Effort 2
Effort 3
Effort 1
Effort 2
Effort 3
Effort 1
Effort 2
Effort 3
Effort 1
Effort 2
Effort 3
Variable 1 Variable 2 Variable 3 Variable 4 Outcome
Effort 1
Observation space partitioned for process
Partitioning for variance explanation
McMullen and Dimov (2013)

7. Two conceptions of time
• A source of noise to the enactment of
regularities
vs.
• Incessant change between past and future

8. Time
Effort 3Effort 3 Effort 3 Effort 3 Effort 3
Time
Effort 1
Effort 2
Effort 3
Observation space partitioned for process
Partitioning for process explanation
McMullen and Dimov (2013)

9. Partitioning the time dimension
• Public (clock) time
– Continuous vs. discrete (days, months, years)
– Objectively vs. subjectively identical intervals
• Ordered increments of transformation
– Not equal in terms of calendar ‘slots’
– A year is not the same time for every firm (individual)
9
Brumbaugh (1966)

10. Partitioning for increments of
transformation
10
Junction 1
Junction 2
Junction 3
Junction 4
Junction n
Growth
Stasis
Decline

11. Implications
• After each transformation, the firm (effort)
is not the same any more
• Zoom in on the transformation as focus /
unit of analysis

12. New logic of explanation
• From nomothetic: searching for regularities
between factors and outcomes
• To generative: specifying mechanisms that can
help reconstruct the process
– Abductive / retroductive inference
– Computational modeling, “a third way of doing
science” (Axelrod, 1997)
Cederman (2005)

13. Zooming even further
• Each transformation is unique ….
– In content
– In outcomes
• But is there a general structure?

15. There are no future facts
• The “adjacent possible” changes with each step
(Kauffman, 2008)
• The truth of propositions with future time
reference is fractional. Present possibilities
have some ontological status (Brumbaugh, 1966)

16. Entrepreneurship as design
Engineering, medicine, business, architecture, and
painting are concerned
• not with the necessary
• not with how things are
• but with the contingent,
• but with how they might
be
Simon (1996: xii)
in short, with design.

17. Transformations as wicked problems
• No definitive formulation
• No stopping rule
• Solutions are not right or wrong (but good or bad)
• Every problem is novel and unique
• Every solution is a “one-shot operation”
• No enumerable set of potential solutions
17
Rittel and Webber (1973)

18. What next?
• Mission: creation of preferred futures
– Driven by real-world problems
– From ‘independent’ to ‘participant’ observer
– Solution orientation
• Output: solution concepts
– Design propositions
– Pragmatic validity
Van Aken & Romme (2012)