Erc progress feb2015 v7. oksana koryak

DISENTANGLING THE
ANTECEDENTS OF AMBIDEXTERITY:
EXPLORATION AND EXPLOITATION
11 February 2015
Andy Lockett, James Hayton, Oksana
Koryak, Deniz Ucbasaran & Kevin Mole
Warwick Business School
Enterprise Research Centre

Motivation
 Ambidexterity is important for a number of organizational
outcomes, including growth, both in the short run and long run.
 Ambidexterity, however, is a difficult capability for firms to
develop because its components (exploration and exploitation)
require substantially different structures, processes, strategies
and capabilities (Benner & Tushman, 2003; Katila & Ahuja,
2002; McGrath, 2001; Siggelkow & Levinthal, 2003).
 Exploration is associated with organic structures, improvisation and
autonomy (Katila & Ahuja, 2002; Rosenkopf & Nerkar, 2001); whereas
 Exploitation is associated with mechanistic structures, path dependence
and routinization (Beckman et al., 2004; Benner & Tushman, 2003;
March, 1991).

Motivation
 A major stream of research on ambidexterity has focused its
antecedents, however, this work has taken ambidexterity as an
aggregate construct.
 The position is surprising given that exploration and exploitation may
require substantially different structures, processes, strategies and
capabilities
 Following the lead of Beckman (2006) we disaggregate
ambidexterity and examine whether or not its antecedents have
differential effects on the exploration and exploitation, and in
doing so identify some of the fundamental tensions in becoming
an ambidextrous firm.
 Research question: How do antecedents of Exploration and
Exploitation capabilities differ?

Modelling strategy
 Drawing on the attention based view (Ocasio, 1997; 2011) and
cognitive approaches to strategic management (Gavetti &
Levinthal, 2000) we view the development of explorative and
exploitative capacity to be a consequence of the focus of
managerial attention.
 We examine three antecedent factors that reflect the three key
principles of the attention-based view (Ocasio, 1997):
 Attention is selective – different factors drive attention to different targets
 Attention is situated – the social context and organizational
communications are important channels for steering attention
 Attention is distributed – culture and behavioural controls impact attention
throughout the organization

Modelling strategy
 In SMEs contextual ambidexterity (as opposed to structural) is
most relevant due to the small size.
 The situated nature of the attentional process:
 TMT composition: heterogeneity and size (Alexiev et al., 2010;
Nielsen & Nielsen, 2013; Nielsen, 2010).
 The impact of communication channels on attention:
 Vision (Pearce & Ensley, 2004).
 The selective nature of organizational attention:
 Extent to which attention is focused on explorative (R&D intensity)
and exploitative (continuous improvement) learning activities
(Rothaermel & Alexandre, 2009) .

TMT composition
 TMT Heterogeneity provides TMTs with different types of
knowledge and decision-making styles and a greater variety of
professional perspectives:
 Broadens the scope of the information & stimulates differences in the
interpretation (Knight et al., 1999; Pitcher & Smith, 2001),
 Facilitates team reflexivity leading to learning (Schippers et al., 2003).
 Helps to counteract team-level biases and errors in decision making
(Schippers et al., 2014).
 TMT heterogeneity, however, may also lead to the emergence
of conflict:
 Task conflict facilitates the exchange of information and the
development of shared understanding (Amason & Sapienza, 1997;
Bantel & Jackson, 1989).
 Emotional conflict may have a detrimental effect on group functioning
(Pelled et al., 1999; Van Knippenberg & Schippers, 2007) and team
performance (Jehn, 1995).

TMT composition and exploration
 The impact of TMT heterogeneity on the determinants of
ambidexterity, however, will be contingent on firm size.
 The size of a TMT, providing a larger pool of managerial
resources, will magnify the effects of diversity:
 Larger heterogeneous TMTs will have more resources facilitating team
performance (Kozlowski & Bell, 2003).
 Larger heterogeneous TMTs are better adept at dealing with more
complex problems and operating in more difficult environmental
conditions (Hill, 1982).
 H1a: TMT heterogeneity will have a positive impact on a
firm’s exploration capability, and the relationship will be
positively moderated by team size.

TMT composition and exploitation
 Although TMT heterogeneity may be advantageous for
exploitation, in terms of enhancing the flow of information for
decision making, its effects may be decreased in larger teams
as problems arise.
 Larger heterogeneous TMTs may begin to exert a negative influence
over tasks that require high focus and alignment.
 Larger heterogeneous TMTs might experience problems related to
dispersion of responsibility (Sheppard, 1993) and coordination (Latane
et al., 1979), which are important in the execution of more routine
tasks.
 H1b: TMT heterogeneity will have a positive impact on a
firm’s exploitation capability, but the relationship will be
negatively moderated by team size.

Vision and exploration/exploitation
 Vision has been identified as an important antecedent of
ambidexterity (O'Reilly & Tushman, 2008; O Reilly & Tushman,
2004), and has been identified as important for firm growth
(Baum & Locke, 2004; Baum et al., 1998; Naffziger et al.,
1994).
 Articulating a clear vision for an organization inspires action
(Avolio & Bass, 1995; Pieterse et al., 2010).
 Vision is an important component of entrepreneurial
leadership (Gupta et al., 2004).
 Vision reflects a communications channel, which is an
important mechanism through which attention is focused and
control exerted throughout the organization (Ocasio &
Wohlgezogen, 2010).

Vision and exploration/exploitation
 Vision communicates the rules of the game, influencing
attention by shaping the situation in terms of defining context,
participants, and resources (Ocasio & Wohlgezogen, 2010).
 Vision is likely to be particularly relevant for activities that focus on
promoting efficiency by regularizing decision making (Ocasio &
Wohlgezogen, 2010).
 In contrast, a focus on clearly defined actions might hamper
exploration activities reliant on creativity and experimentation
 H2a: Written vision will be negatively related to exploration.
 H2b: Written vision will be positively related to exploitation.

R&D intensity and exploration
 R&D intensity is positively related to innovation activity
(Cardinal & Hatfield, 2000; Hall et al., 1986; Pakes & Griliches,
1984) through enhanced internal development of new
discoveries as well as the flow of new information into the
firm.
 However, there are diminishing returns from R&D in terms of
performance and firm value (Ho et al., 2004; Mank & Nystrom,
2001; Zenger, 1994).
 May be related to the fact that firms switch from exploration to
exploitation and vice versa (Mudambi & Swift, 2001, 2014).
 H3a: R&D intensity will be positively related to exploration
capability, however, the relationship will be subject to
diminishing returns

R&D intensity and exploration
 The systematic and deliberate investment in R&D will raise the
cost base of the firm, and restrict firms’ ability to raise debt
and increases the cost thereof (Williamson, 1988).
 Firms with high levels of R&D intensity run the risk of overly
engaging in the exploration of new opportunities at the
expense of being able to generate complementary assets and
processes to exploit them.
 May reduce the value that can be extracted from the strategic assets
created through already-funded R&D projects (Dierickx & Cool, 1989).
 In addition to financial investment, higher levels of R&D
intensity may reflect TMT members selective decisions about
the focus of attention in terms of their cognitive investments.
 H3b: R&D intensity will be negatively related to exploitation

Continuous improvement exploration
 Continuous improvement is defined as “a company-wide
process of focused and continuous incremental innovation”
(Besant et al., 1994).
 Practices such as six-sigma, kaizen and the ‘lead toolbox’
focuses attention throughout the organization by
programming step by step behavioural control.
 CI is explicitly focused on the elimination of waste across
the organization, in its systems and processes.
 The selective and limited nature of organizational attention
(Ocasio, 1997) implies that a positive focus on CI will promote
more routine and exploitative activities to the detriment of
longer term explorative activities.
 H4a: A focus on continuous improvement will be negatively
related to exploration capability
 H4b: A focus on continuous improvement will be positively
related to exploitation capability

Data and analysis
 Sample frame based on Fame database to link survey data to
financial information.
 Main data collected using phone survey data, complemented
by objective information from Fame.
 Initial questionnaire was pre-tested on 25 firms.
 Scales are based on existing literature with minor
modifications where necessary to suit the context.
 Current analysis is based on cross-sectional data.
 Regression analysis is based on a sample of 378 firms.

Data and analysis
 We adopt EU’s definition of small and medium firms (as per
Recommendation 2003/361/EC adopted on 1st January 2005):
 The final sample is approximately equally distributed across
the size brackets, in terms of the number of employees (10-
49; 50-99, 100-249).
 Geographical distribution of the sample closely resembles that
of the population (NI excluded in line with similar UK studies).
 Northern Ireland is often omitted from UK-wide enterprise surveys due
to some idiosyncratic factors affecting firm performance in this region
that are difficult to control for within the scope of smaller surveys.
 The sample is drawn from a broad variety of sectors.
Category Headcount Turnover Total Assets
Medium < 250 € 50 million = +/- £42.5m € 43 million = +/-£36.5m
Small < 50 € 10 million = +/-£8.5m € 10 million = +/- 8.5m

Measures
 Dependent variables:
 Exploration & exploitation (Lubatkin et al., 2006).
 Independent variables:
 TMT heterogeneity (Van Doorn et al., 2013) and TMT size.
 Vision (based on: Baum & Locke, 2004).
 R&D intensity (Rothaermel & Alexandre, 2009).
 Continuous improvement (Peng et al., 2008).
 Controls:
 Firm age, firm size and substantive capabilities (Marketing, HR and
Financial management capabilities based on (Vorhies and Morgan
(2005) measure of marketing implementation scale).
 Industry: industry category dummies (manufacturing, high tech
services and other) as well as environmental dynamism, munificence,
the latter two as per Castrogiovanni (2002), calculated over 5-year
interval (2008-2012) on the basis of Annual Business Survey 2012
(Office for National Statistics).

Measures
 Scale-based measures show good internal reliability:
 We have performed a CFA to confirm discriminant validity of
the model
 The results of the CFAs suggested that our seven-factor measurement
model fit the data well (2 /df = 1.398, TLI = .969, CFI = 0.972 and
RMSEA .032). Thus, CFAs supported the discriminant validity of our
measures.
Construct Cronbach alpha # items
Exploration 0.79 4
Exploitation 0.84 6
Marketing capability 0.88 4
HR capability 0.90 4
Financial capability 0.93 4
Continuous improvement 0.81 5
TMT Heterogeneity 0.78 4

Results – Exploration (OLS)
VARIABLES Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Controls H1a H2a H3a H4a Full model
Age 0.063 0.071 0.062 0.043 0.088 0.070
Size (employees) 0.053 0.019 0.041 0.081 0.010 0.012
Manufacturing 0.440*** 0.432*** 0.432*** 0.394*** 0.427*** 0.386***
Knowledge intensive services 0.498** 0.474** 0.480** 0.311* 0.484*** 0.328**
Market Dynamism 0.020 -0.005 0.019 0.011 0.021 -0.009
Munificence -0.862 -0.597 -0.830 -0.910 -0.542 -0.466
Marketing capability 0.181** 0.160** 0.177** 0.152* 0.111* 0.095†
HR capability 0.176** 0.150** 0.166** 0.167** 0.071 0.075
Financial management capability -0.098† -0.132* -0.103† -0.075 -0.121* -0.119*
TMT Heterogeneity 0.170** 0.072
TMT size 0.042* 0.044*
TMT Heterogeneity x TMT size 0.055*** 0.048***
Vision 0.061 -0.006
R&D Intensity 0.059*** 0.043***
R&D Intensity squared -0.001*** -0.000**
Continuous improvement capability 0.380*** 0.307***
Constant -0.850† -0.619 -0.837† -0.969* -0.734† -0.650
Observations 378 378 378 378 378 378
R-squared 0.128 0.180 0.131 0.225 0.243 0.327
Adjusted R-squared 0.107 0.153 0.107 0.201 0.223 0.297
F test 7.243 12.07 6.687 10.64 14.17 14.93
Robust standard errors in parentheses
*** p<0.001, ** p<0.01, * p<0.05, † p<0.1

Results – Exploitation (OLS)
Controls H1b H2b H3b H4b Full Model
Age -0.059 -0.037 -0.064 -0.055 -0.033 -0.018
Size (employees) 0.122 0.115 0.084 0.109 0.078 0.031
Manufacturing -0.093 -0.069 -0.119 -0.088 -0.106 -0.099
Knowledge intensive services -0.211 -0.240† -0.271† -0.150 -0.224 -0.189
Market Dynamism -0.052 -0.042 -0.055 -0.047 -0.051† -0.034
Munificence 1.135* 1.173* 1.243* 1.176* 1.461** 1.592**
Marketing capability 0.216** 0.192** 0.206** 0.217** 0.146* 0.126*
HR capability 0.174** 0.125* 0.138* 0.182** 0.066 0.024
Financial management capability 0.104 0.104 0.090 0.093 0.080 0.057
TMT Heterogeneity 0.205** 0.128*
TMT size -0.012 -0.014
TMT Heterogeneity x TMT size -0.048*** -0.041**
Vision 0.205** 0.154**
R&D Intensity -0.011 -0.018*
Continuous improvement capability 0.387*** 0.372**
Constant 0.210 0.125 0.251 0.231 0.328 0.301
Observations 378 378 378 378 378 378
R-squared 0.184 0.227 0.215 0.194 0.302 0.367
F test 10.15 10.16 11.83 9.564 16.47 15.21
*** p<0.001, ** p<0.01, * p<0.05, † p<0.1

Results – Ambidexterity (OLS)
Age 0.005 0.034 -0.003 -0.020 0.056 0.048
Size (employees) 0.174 0.134 0.125 0.189† 0.089 0.045
Manufacturing 0.347* 0.363* 0.313† 0.283† 0.321* 0.279*
Knowledge intensive services 0.287* 0.234 0.209 0.136 0.260* 0.131
Market Dynamism -0.032 -0.048 -0.036 -0.033 -0.029 -0.042
Munificence 0.273 0.577 0.412 0.302 0.919 1.126†
Marketing capability 0.397*** 0.351*** 0.383*** 0.351*** 0.257*** 0.216***
HR capability 0.350*** 0.275*** 0.304*** 0.356*** 0.137* 0.105
Financial management
capability 0.005 -0.028 -0.013 0.014 -0.041 -0.062
TMT Heterogeneity 0.375** 0.198**
TMT size 0.030 0.029
TMT Heterogeneity x TMT size 0.007 0.007
Vision 0.265*** 0.142*
R&D Intensity 0.069*** 0.034**
R&D Intensity squared -0.001*** -0.001***
Continuous improvement
capability 0.767*** 0.671***
Constant -0.640 -0.494 -0.586 -0.782 -0.406 -0.376
Observations 378 378 378 378 378 378
R-squared 0.224 0.288 0.251 0.282 0.463 0.512
F test 11.49 11.76 13.41 14.18 29.49 25.22
*** p<0.001, ** p<0.01, * p<0.05, † p<0.1

Summary of the results
 We find strong evidence of the differential effect of the
antecedents of ambidexterity on exploration and exploitation,
with potentially contradictory outcomes.
Antecedent Exploration Exploitation Ambidexterity
TMT heterogeneity x
size
H1a
(+)
H1b
(-)
+ for only the direct
effect of heterogeneity
Vision H2a
(n.s.)
H2b
(+)
+
R&D intensity H3a
(+ diminishing returns)
H3b
(n.s.)
+
but diminishing returns
Continuous
improvement
H4a
(+ opposite effect)
H4b
(+)
+

Discussion
 Antecedents of exploration and exploitation differ in
important and sometimes contradictory ways
 TMT composition: The interaction effect between
heterogeneity and size has opposite effects for exploration
and exploitation
 The positive effect of TMT heterogeneity on exploration increases with
TMT size
 The positive effect of TMT heterogeneity on exploration decreases
with TMT size
 Vision: Has a positive effect on exploitation but no real
influence on exploration.
 Appears to influence firm’s ability to develop exploitation skills,
through focusing the attentions of staff towards executing a developed
strategy.
 In contrast, vision appears to be unrelated to exploration, potentially
due to difficulties of managing a creative process and the problems of
creating cognitive boundaries

Discussion
 R&D intensity has a differential and contradictory effect on
exploration and exploitation.
 R&D intensity has a positive effect on firm’s exploration activities,
albeit with diminishing returns
 In contrast, R&D intensity has a negative effect on a firm’s exploitation
activities.
 Continuous Improvement has a consistent and positive effect
on exploration and exploitation
 Contrary to expectation, continuous improvement matters for
exploration as well as exploitation

Discussion
 The differential effect on TMT composition on exploration and
exploitation may reflect how the effect of team dynamics are
shaped by the nature of the task at hand.
 These results are largely consistent with the Attention Based
View and suggest that:
 Attention is selective and that factors that support attention to one
dimension can directly undermine attention to the other (e.g., TMT
heterogeneity)
 Attention is situated, and that social context (e.g., TMT) behavioural and
cultural control mechanisms (e.g., CI), and communication channels
(Vision), each exert an influence
 Attention is distributed so that factors beyond TMT matter for
organizational attention on both exploration and exploitation
 The unanticipated positive association between CI and
exploration may be because different parts of the organization
are activated to support exploration and exploitation
 Attention is distributed, selective, but does not need to be uniformly
focused throughout the organization

Limitations and future research
 At present our work is cross sectional, which we need to link
into Fame data to track the performance of our companies
over time.
 To avoid the practical “so what question”, however, we can
link the determinants of ambidexterity into specific types of
firm growth, albeit in a cross sectional manner.
 Running path models with different growth outcomes as the
final variable we find:
 Exploration is positively related to the % of sales generated from new
products and services and the % of sales generated from exports
 Exploitation is positively related to turnover growth (as measured by
CAGR).

Contributions and Conclusion
 Our research demonstrates that decisions taken about
achieving ambidexterity may simultaneously enhance one
dimension of it whilst diminishing the other.
 Hence, firms need to be clear about the nature of the balance they
wish to achieve at any given point in time and given their particular
internal and environmental conditions.
 Optimal combination of exploration and exploitation will depend on
the firms chosen growth path.
 There is a need to balance investment in dynamic and
substantive capabilities (Winter, 2003).
 Firms might not dedicate enough attention to further developing the
opportunities they have identified and explored.
 Overall, problems in achieving ambidexterity may relate to
different antecedents of its key components. These are
difficult to resolve in the context of SMEs.

Size distribution
29
29.8%
36.8%
33.4%
10-49 50-99 100-250
Approximately equal distribution across the size brackets, in terms
of the number of employees

Geographical distribution
88.8%
4.0% 7.3%
89.6%
3.6% 6.8%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
England Wales Scotland
Population Survey
Geographical distribution of the sample
closely resembles that of the population
(NI excluded)

Interviews by sector
31
4%
20%
2%
10%
35%
7%
11%
11%
20, 21, 26-29 High Tech
manufacturing
C (exc 20, 21, 26-29) other
manufacturing
BDE Primary
F Construction
GHI TRAD
J
Information/communicatio
ns

3%
1%
6%
19%
11%
13%4%
2%
25%
6%
10%
A (Agriculture, Forestry &
Fishing)
BD,E (Mining & Quarrying;
Electricity, Gas & Water)
C (Manufacturing)
F (Construction)
G (Wholesale & Retail)
H&J (Transportation,
Storage, Communications)
I (Accomodation & Food
Service)
K (Financial & Insurance)
L,M&N (Real Estate,
Professional Services)
P&Q (Education & Health)
Population by Sector (all
UK): Source ONS

Descriptives and correlations
Mean S.D. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1 Ambidexterity 0.00 1.41
2 Exploration 0.00 1.00 .707
**
3 Exploitation 0.00 1.00 .707
**
0.000
4 Firm Age 2.94 0.80 0.009 0.012 0.000
5 Firm Size 4.22 0.64 0.047 0.019 0.047 -0.003
6 Manuf dummy 0.25 0.43 0.052 .103
*
-0.030 .099
*
0.016
7 Market dynamism 9.73 1.84 0.008 0.069 -0.057 0.049 -0.056 .140
**
8 Munificence 0.02 0.08 0.033 -0.027 0.074 -0.051 -0.001 -.128
**
.169
**
9 Marketing 0.00 1.00 .398
**
.223
**
.335
**
0.067 0.016 -0.077 -0.003 0.070
10 HR 0.00 1.00 .343
**
.200
**
.285
**
0.084 0.022 -0.027 0.013 0.051 .403
**
11 Financial Mgmt 0.00 1.00 .224
**
0.065 .251
**
0.020 -0.091 0.021 -0.040 -0.007 .450
**
.442
**
12 TMT heterogeneity 0.00 1.00 .367
**
.254
**
.268
**
-0.063 -0.004 -0.054 -0.009 -0.021 .240
**
.273
**
.201
**
13 TMT size 3.41 2.27 0.050 0.085 -0.014 0.001 .181
**
-0.007 .112
*
0.039 0.008 0.001 -0.045 -0.030
14 Written vision 0.50 0.50 .248
**
.113
*
.238
**
-0.002 .120
**
0.037 0.032 0.010 .174
**
.209
**
.161
**
.112
*
.107
*
15 R&D Intensity 4.78 11.19 .140
**
.249
**
-0.054 -0.025 -0.035 -0.045 .136
**
0.089 0.007 0.046 -0.011 0.078 -0.012 0.049
16 Cont improvement 0.00 1.00 .607
**
.409
**
.443
**
-0.024 0.071 -0.004 -0.012 -0.050 .326
**
.370
**
.267
**
.336
**
-0.027 .201
**
.142
**
* Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).

Erc progress feb2015 v7. oksana koryak

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