This study examines how business unit reorganization affects innovation in 250 medical firms over 20 years. The researcher hypothesizes that the relationship between reorganization and innovation follows an inverted U-shape (Hypothesis 1A) or U-shape (Hypothesis 1B) as learning mediates this relationship. Results support Hypothesis 1B, showing that only current reorganization experiences positively impact future innovation in a U-shape, not past experiences. Additionally, highly active and larger firms that pursue acquisitions demonstrate more radical innovation. The researcher concludes reorganization can create value when firms learn from several experiences in a U-shape pattern over time.
3. Examines how business unit reorganization affects innovation
Explores how the learning Process may mediate this relationship
250 medical firms studied over a 20 year period
Theoretical support: dynamic capabilities and organizational learning
Degree of innovation (dependent variable)
Degree of reorganization (independent variable)
Learning (Mediating variable)
Control variables: firm level and industry level
4. Structural organization determines:
Resource allocations, use of internal routines and communication networks, flow
of information and tasks
Reorganization changes these circumstances
Creating a new environment for learning and the potential for resources to be
used in new combinations leading to innovation
Past findings suggest that firms are attempting to create value by realigning
units’ resources and activities within the firm
There is an underlying belief that reorganization is potentially beneficial
5. To determine if there are any innovative benefits of reorganization
Determine how learning occurs in the presence of unit-level structural change
To find whether firms learn immediately from a few reorganization attempts
If not, how many experiences are needed before there is learning?
6. Reorganization has been explored at the resource level, divisional level, and
activity level
No study has explored how business unit reorganization affects innovation
Research to date has revealed very little about the underlying structures and
processes by which firms actually achieve continuous innovation and ultimately,
change
7. Literature on Reorganization
Reorganization has been explored in various contexts
Chosen unit of analysis has varied between: resource, divisional and activity level
Innovation literature has addressed how new resource combinations or similar
resources combined in new ways (i.e., recombination) may result in innovation.
Brown and Eisenhardt (1997) theorize, based on complexity theory, that an
inverted U-shape relationship may exist between structural flexibility and
innovation
Eisenhardt and Brown (1999, p. 73) observe patching, “ the adding, deleting,
splitting, transferring, combining chunks of businesses,” as firms frequently
remap their divisional structures to react to changing market opportunities
8. Business Unit Reorganization and Innovation
Reorganization leads to grafting and cross functional teams which lead to new
opportunities and innovation as well as faster product development
Both dynamic capabilities and organization learning theories caution against too much
change or disorder.
Huber (1991, p. 103) warns that firms may experience information overload if “the
information to be interpreted exceeds the units’ capacity to process the information
adequately
Fiol and Lyles (1985, p. 806) predicted an inverted U-shape relationship between level
of change and level of learning, regardless of whether or not the intent for change was
thoughtful
As with general change and learning, excessive amounts of reorganization may lead to
disruption, inefficiency, and misinterpreted information that result in declining
innovative performance
9. Hypothesis 1A. Business unit reorganization
(within a given period) will have an inverted
U-shape impact on future innovation (in the
next period).
10. Learning as a Mediating Factor
learning how to reorganize alone may not be enough to innovate in a new product
market
Classic learning literature has focused on a model of learning-by-doing, exemplified
by the learning curve where the inputs needed per item of output decline at a
declining rate due to experiential learning (Arrow1962).
Experimental learning supports U shape relationship between change and
performance
Time affects learning because learning is built on memories, associations, and the
ability to recognize useful information (Huber 1991)
Learning is highly path dependent which can lead to competency trap
Haleblian and Finkelstein (1999) examined the effect of acquisition experience on
acquisition performance found it to be U-shaped
11. Based on these arguments, firms may not have success innovating after
reorganization until they have experienced several reorganization events and
practiced the appropriate application of what is learned to various circumstances
Hypothesis 1B. Business unit reorganization
(within a given period) will have a U-shape impact
on its future innovation (in the next period).
12. Data and Sample
Data gathered from several editions of ‘The Medical & Healthcare Marketplace
Guide’
Operating in US medical industry
250 medical firms studied over a 20 year period
Including their units and product markets
Pharmaceutical, health care service & medical device industry
Of 250 only 85 firms were still alive in 1977
866 business units and 1274 product lines
13. Dependent and Independent Variables
Degree of innovation( DV)
is a count variable that is calculated as the number of entries into new product
markets by the firm within a time period.
Degree of Reorganization( IV)
counts the number of unit boundary changes that occur in a firm within a time
period
Industry and firm level control variables
Firm level control variables include number of employees, medical sales, percent
medical sales, age, public status & foreign status.
Industry level variable includes category of pharmaceutical or healthcare services,
it is a dummy variable
Dummy variables are used to test the appropriateness of various models and
generate descriptive statistics
14. Poisson regression model for goodness of fit test
Time-varying lagged values of independent variables are used as the regression in
the estimated equations
Linear lagged model :
study is comprised of seven panels with six periods of data observed
Incorporating a two period lag the following four equations (at most) are observed
for each firm j:
observed for each firm j:
15. Hypothesis 1A not supported
Hypothesis 1B supported
Firms’ level of product activity and acquisition activity were significant
Major Findings
First; reorganization has a U-shape relationship with innovation
Second; only current reorganization experiences affect innovation, past
reorganization experiences do not affect future innovation
Third; Acquisition active firms innovate more than non- acquisition active firms
Other findings
Highly active in reorganization activity, larger firms, acquisition active firms
radically innovate more
16. Managerial Implications
Distinguish between reorganization events and be wary not to generalize
Learn from a cohort of several experiences
Increase the memory capacity; codify the past experience
Acquisition active managers should not neglect internal units
Limitations and Future Research
examined radical innovation only at the product level
Study includes only healthcare related organizations
Future studies should be more granular, incremental innovations
More accurate timings of events can provide more clear results
17. This research indicates that firms create value & pursue successful change when
there is a U shape relationship between reorganization & innovative performance,
where learning is a mediating factor.
My Analysis
Past experiences are as important as current experiences.
I think it is important that organizations to arrange training in change
management
Too much acquisition is not always good.
Concentrating on development of internal units in organizations is as important
as acquisition
Business unit reorganization is one way in managerial innovation