Emerald - Ambidextrous Leadership
Emerald - Ambidextrous Leadership
Emerald - Ambidextrous Leadership
www.emeraldinsight.com/0143-7739.htm
OSC as a
Ambidextrous leadership, moderator
entrepreneurial orientation,
and operational performance
Organizational social capital as a moderator 229
Abstract
Purpose – The purpose of this paper is to investigate the role of ambidextrous leadership in fostering
entrepreneurial orientation (EO) and operational performance. The research also seeks an insight into
the moderating role that organizational social capital (OSC) plays on the relationship between ambidextrous
leadership and EO.
Design/methodology/approach – The responses to the questionnaire survey were collected from
427 managers from software companies in Vietnam business context.
Findings – The data analysis verified the positive effect of ambidextrous leadership on EO, which was
positively moderated by OSC. The research results also shed light on the predictive role of EO for the
organization’s operational performance.
Originality/value – This research contributes to literature through identifying the convergence of
entrepreneurship and operations management research streams, and the moderation role of OSC for the
ambidextrous leadership-EO relationship.
Keywords Entrepreneurial orientation, Operational performance, Ambidextrous leadership, Vietnam,
Organizational social capital
Paper type Research paper
Introduction
Reflecting an external focus ( Johnson and Sirikit, 2002), sustainable competitive advantage
indicates an organization’s unique position relative to its competitors that enables it to
outperform them consistently (Porter, 1985). Sustainable competitive advantage thus emanates
from competitor-oriented operational performance, rather than from internally oriented
operational performance. Liu et al. (2013) also view operational performance as improvement in
an organization’s response to a changing environment in relation to its competitors. To create
operational performance with high responsiveness to competitive force, an organization should
have higher levels of proactiveness and innovativeness than its competitors in giving rise to
proactively innovative products or services. Entrepreneurial orientation (EO), which comprises
proactiveness, innovativeness, and risk taking (Covin and Slevin, 1989; Saeed et al., 2014), drives
employees to proactively seek novel ways to improve the value chain process, thereby
improving the components of operational performance including process flexibility, cost
efficiency, product or service quality, and delivery effectiveness (Devaraj et al., 2007).
Entrepreneurship literature has reported the relationship between EO and organizational
performance (Buttar and Kocak, 2011), especially financial performance (Poon et al., 2006), but
has not turned to the relationship between EO and competitor-oriented operational performance.
Entrepreneurship research has tended to suggest that managerial practitioners shape
Leadership & Organization
their leadership style into transformational leadership to activate entrepreneurial force in Development Journal
the organization (Ling et al., 2008; Engelen et al., 2014). Nonetheless, such a leadership Vol. 38 No. 2, 2017
pp. 229-253
fosters exploratory force only. Ambidextrous leadership, defined as the interaction between © Emerald Publishing Limited
0143-7739
the two complementary leadership behaviors – opening and closing – can foster both DOI 10.1108/LODJ-09-2015-0191
LODJ exploratory and exploitative forces (Rosing et al., 2011). The ambidexterity in this leadership
38,2 style engenders the emotional balancing of continuity and change (Huy, 2002), thereby
reducing employees’ fear of uncertainty and amplifying their self-efficacy to engage in
innovative and risk-taking actions. Besides, ambidextrous leaders use opening leadership
behaviors to encourage employees to proactively search for novel ideas and solutions,
then switch to closing leadership behaviors to encourage employees to implement them.
230 Therefore, ambidextrous leadership has a propensity to foster proactiveness,
innovativeness, and risk taking among employees.
Since the relationship between ambidextrous leadership and EO has not been
investigated, prior research has just focused on moderators for the relationship between
ambidexterity and performance such as environmental dynamism (Rothaermel and
Alexandre, 2009) and resource endowment (Cao et al., 2009). In an organization that has
sustainable relationships and goal harmony with its employees, employees are more
likely to take supportive actions toward entrepreneurial strategic posture that
ambidextrous leaders build. Organizational social capital (OSC) that reflects such trusting
relationships and goal congruence (Leana and Van Buren, 1999) may thus interact with
ambidextrous leadership in cultivating EO in the organization.
Through the integration of new ambidextrous leadership theory (Rosing et al., 2011) into
entrepreneurship and operational performance streams, the current study fills the following
research gaps. The primary purpose of the study is to examine the predictive role of
ambidextrous leadership for EO (research gap 1). The second purpose of the study is to
assess the extent to which EO contributes to operational performance (research gap 2).
The third purpose of the study is to seek an insight into the moderating mechanism of OSC
for the ambidextrous leadership-EO linkage (research gap 3). The last research gap the
study attempts to fill is to test this research model, which is built on Western theories,
in Vietnam – an emerging market (Nguyen et al., 2015).
Following the depiction of the research aims in this introductory section, the paper
reviews the concepts and builds the hypotheses of the research model through the
discussion of the relationships among the concepts. The data were then analyzed to produce
theoretical and managerial implications.
Predictive and moderating effects of organizational size, organizational age, and ownership
According to Scherer (1980), smaller organizations were more likely to innovate than larger
ones. Small organizations need product innovation to survive in the market (Chaney et al., 1991).
On the contrary, large organizations may be slow in innovation pace, but when they are
threatened by new product development in the industry, the market expects them to respond to
the challenge (Scherer and Ross, 1990). The literature also indicates that larger organizations
may have the resources and skills necessary for entrepreneurial actions in domestic
(Porter, 1987) as well as international markets (Fujita, 1997b).
Besides the potential influence of organizational size on EO, organizational age has also
been found to be a significant factor in explaining organizational strategic behaviors
such as entrepreneurial strategic posture (Tang and Hull, 2012). The manner in which
younger and older organizations attempt to build new capabilities for EO may also differ
(Sapienza et al., 2006). New organizations are often created to introduce radically new
products or services by exploiting specific technological advances (Acs et al., 1997).
In contrast, the older an organization, the more bureaucratic and the less open it is to EO
(Luo et al., 2005). The older an organization is, normally the more hierarchy and inertia it
has; hence, the less it is motivated to change organizational directions through product or
LODJ service innovation (Huergo and Jaumandreu, 2004). Organizational age is especially
38,2 crucial in a transition economy, since older organizations that have been embedded in
the pre-reformed period are more risk averse and inertial for entrepreneurial strategic
posture (Yiu et al., 2007). Nonetheless, according to Sapienza et al. (2006), younger
organizations may be more willing than older ones to dynamically build the capabilities
required to effectively compete in new markets, but they may not be able to survive the
234 efforts necessary to do so. Fujita (1997a) also reported that older organizations, however,
were more likely to engage in entrepreneurial strategic posture to renew their operations.
Organizational age has been found to be a slightly significant predictor for EO (Wiklund
and Shepherd, 2005).
Moreover, ownership may also engender risk aversion and unwillingness to engage in
strategic change activities such as product or service innovation (George et al., 2005).
Fama and Jensen (1983) found the influence of ownership on the extent of engagement in
risky activities. Managers become risk averse as their ownership in the organization
increases (Denis et al., 1997). The concentrated nature of ownership hence puts state-owned
and domestic private organizations at a disadvantage in terms of risk taking and causes
strategic inertia (Schulze et al., 2002).
In addition, in state-owned organizations, since ownership is concentrated to a limited
group of governmental stakeholders, their owners may be more likely to unite around the
same values, interests and strategic practices (Goodstein and Boeker, 1991). This commitment
to the strategy tends to continue over time, leading to unwillingness to change the original
strategy (Kimberly and Bouchikhi, 1995). “Over time, owners may become insulated
from environmental and performance changes and fail to perceive and react to critical
environmental and organizational changes” (Goodstein and Boeker, 1991, p. 312). In Vietnam
context, while foreign-invested organizations tend to launch new products or new features and
applications of products and shape customer needs, state-owned and domestic private ones
tend to follow their foreign leaders in the market in terms of technological and product
innovations (Tran, 2003; Nguyen, 2015).
Furthermore, organizational size, organizational age, and ownership may further
influence the effectiveness of EO in leveraging operational performance. Organizational size
and organizational age have apparently received little scholarly attention as moderating
effects in previous EO studies (Hamilton, 2012). Organizational size was reported to
influence the relationship between EO and performance (Rauch et al., 2009). Wiklund and
Shepherd (2005) view organizational size and organizational age as levers of the success of
EO. Entrepreneurial strategic posture tends to be more successfully implemented in older
and larger organizations than younger and smaller ones since the former have more
experience (Ismail and Jenatabadi, 2014) and resources (Sapienza et al., 2006; Porter, 1987;
Fujita, 1997b) than the latter. Foreign-invested organizations also may have more resources
and experience in implementing entrepreneurial strategy than state-owned and domestic
private ones in developing countries like Vietnam. Additionally, foreign-invested
organizations tend to have entrepreneurial values in their core values when they have
gone global and to some extent infuse these values into local employees. Thus, when
entrepreneurial strategic posture is built in overseas subsidiaries in local contexts, their
local employees are more likely to support this strategic posture to catalyze the conversion
of EO into operational performance than those in state-owned and domestic private ones.
The above discussion leads to the ensuing hypotheses:
H4a. Organizational size, organizational age, and ownership type are predictors of EO.
H4b. Organizational size, organizational age, and ownership type moderate the
relationship between EO and operational performance.
Figure 1 recaps the relationships among the constructs in the research model.
Ambidextrous H1 (+) H3 (+)
OSC as a
Operational
leadership
Entrepreneurial
orientation performance moderator
H2a H2b
H4a H4b
Organizational
social capital
Organizational size
Trust 235
Organizational age
Goal congruence Figure 1.
Ownership Research model
Research methodology
Research context
Emerging economies are experiencing unprecedented transition and fundamental
changes in their infrastructures which, combined with their fast growth, engender
challenges to companies operating in such environments (Marino et al., 2008). Companies
operating in emerging economies must thus respond to ongoing changes in market
conditions. As a growing emerging economy, Vietnam is transitioning to a market economy
(Malesky and Taussig, 2009; Nguyen et al., 2015). So as to respond to the shifting
competitive landscape, Vietnam-based companies have been forced to transform, making
Vietnam a natural setting for empirically testing our model of EO and operational
performance. To offset for the unpredictability, volatility, and deficiencies in the external
environment of emerging markets, leaders have a propensity to pay greater heed to their
company’ internal resources (Tan and See, 2004) including leadership (Walker, 2010).
Sampling
Respondents came from software companies in Vietnam business context. Software
companies were selected for the current research as they typify a knowledge-based industry
(Murthy and Abeysekera, 2008), engage in producing innovations, and have a growing
importance to the Vietnamese economy (Nguyen, 2015). Companies in knowledge-based
industries have a propensity to create dynamic capabilities through their knowledge as
unique resources, which produce innovations and heighten operational performance
(Murthy and Abeysekera, 2008). Furthermore, software industry is characterized by a high
competitive intensity, especially market pressure from foreign-invested software
companies (Nguyen, 2015). Meanwhile, domestic software companies tend to be slow in
technological and managerial innovation (Nguyen, 2015). There also remains resistance to
innovations in numerous software companies in Vietnam (Nguyen, 2015). Therefore,
understanding mechanisms promoting operational performance helps software companies,
especially domestic ones, enhance its responsiveness to changes in the environment and
sustain its competitiveness.
Since companies should be sufficiently large to ensure that organizational variables apply
(Miller, 1987), 121 companies which had at least 100 employees working were selected from
the 2014 Vietnam Trade Directory. Yet, the final company sample included 64 companies that
had at least three managers participating in the survey (Coombes et al., 2011). Together with
such criteria, small companies were designated as having 100-249 employees, companies
with 250-499 employees were designated as medium sized, and large companies as those with
500 employees or more (Gulbro et al., 2000). Meanwhile, the mean of organizational age
“21 years” was used as the cut-off point to define older and younger companies (Anderson and
Eshima, 2013). Companies with less than 21 years are dubbed younger companies
LODJ and companies aged 21 years and older are known as higher age companies. The description
38,2 of the company sample in terms of organizational size, organizational age, and ownership is
presented in Table I.
No. of companies %
Organizational size
100-249 employees 9 14.06
250-499 employees 34 53.13
500 employees or more 21 32.81
Organizational age
Older organizations (over 21 years) 38 59.38
Younger organizations (21 years or under) 26 40.63
Organizational ownership
State-owned 15 23.44
Table I. Domestic private 22 34.38
Description of the Joint-venture 9 14.06
company sample 100% foreign-invested 18 28.13
In the first-wave survey, out of the 1,805 questionnaires, 647 responses were returned from OSC as a
managers, among which 68 (10.51 percent) contained missing data. From Hair et al.’s moderator
(2006, p. 55) perspective, “missing data under 10% for an individual case or observation
can generally be ignored”; therefore, though the data are missing at random
(Little MCAR test: χ2 ¼ 537.42, df ¼ 162, sig ¼ 0.214), responses with missing data rate
higher than 10 percent were removed, resulting in 579 responses apposite for analysis
(Hair et al., 2006), at a usable response rate of 32.08 percent. The comparison of early and 237
late responses through Armstrong and Overton’s (1977) extrapolation method revealed no
significant divergence, which reduces concerns that the data suffers from non-response
bias and amplifies the credibility to make generalizations about the population.
Since 16 managers left their organizations, T2 survey questionnaires were sent to
563 managers. However, merely 491 responses without missing data (3.16 percent missing
data) were garnered (27.20 percent). In the third-wave survey, due to the further leaving of
nine managers, only 482 questionnaires were relayed to managers. In total, 427 complete
responses (23.66 percent) were returned (4.69 percent missing data), building the
final sample of 427 managers.
Out of the managers, 30.91 percent were female, their average age was 38.6 years
(SD ¼ 9.2), they had an average job tenure of 12.4 years (SD ¼ 2.7), and they were employed
as chief accountants (11.01 percent), operations managers (48.02 percent), marketing
managers (18.03 percent), and sales managers (22.95 percent).
Measures
Respondents indicated their perceptions on scale items measuring ambidextrous leadership,
EO, OSC, and operational performance. Items were gauged on a five-point Likert scale
anchored by “strongly disagree” (1) to “strongly agree” (5) unless otherwise stated.
Ambidextrous leadership. Respondents were invited to assess their supervisors’
ambidextrous leadership through Zacher and Rosing’s (2015) 14-item scale, based on
Rosing et al.’s (2011) ambidextrous leadership theory. The scale comprises seven opening
leadership behaviors (e.g. “My supervisor encourages experimentation with different
ideas,” “My supervisor has motives to take risks”) and seven closing leadership behaviors
e.g. “My supervisor monitors and controls goal attainment,” “My supervisor takes
corrective action”).
EO. This construct was assessed using Covin and Slevin’s (1989) eight-item scale, which
comprises the three dimensions: proactiveness consisting of two items (e.g. “Our organization
is very often the first to introduce new products or services, administrative systems, methods
of production, etc.”); innovativeness consisting of three items (e.g. “Our organization has
introduced a lot of new products or services in the past 5 years”); and risk taking consisting of
three items (e.g. “Our organization has a strong propensity toward getting involved in high
risk projects (with a chance for high yield)”).
OSC. Relational (trust) and cognitive (goal congruence) facets of OSC were gauged
through six items each from Leana and Pil (2006). Respondents assessed OSC of the
organization as a whole instead of individual employees. Sample items for trust and goal
congruence, respectively, are “There is no ‘team spirit’ among employees in this company”
(reverse-coded) and “Employees share the same ambitions and vision for the company.”
Operational performance. Operational performance was assessed along the
dimensions of cost, quality, flexibility, and delivery in Devaraj et al.’s (2004) eight-item
five-point Likert scale (1 ¼ not very good, 5 ¼ very good).
Organizational size was measured by the number of full-time employees and
organizational age in years since foundation (Brettel et al., 2011). Ownership type was
coded as 1 ¼ domestic (state-owned and private) and 2 ¼ foreign invested (Luu, 2012a).
LODJ Results
38,2 Reliability and validity
The data analysis was conducted through LISREL 8.8 ( Jöreskog and Sörbom, 2006).
The scales’ reliability was potentially enhanced through the use of multiple-item scales
(Neuman, 2000). The reliability of each construct and its specific dimensions was further
assessed through composite construct reliability coefficients. As Table II exhibits,
238 the composite reliability of each research variable ranged from 0.73 to 0.86, above
0.6 according to Fornell and Larcker (1981) and Bagozzi and Yi (1988). Convergent validity
was also achieved because the resulting average variance extracted for each scale ranged
from 0.532 to 0.657, above 0.5 as Fornell and Larcker (1981) suggest. In addition, as shown
on the diagonal in Table II, the square root of the average variance extracted for each
construct exceeded the standardized correlation between the construct and each of the other
constructs, which denotes the Fornell and Larcker’s (1981) test is met for all pairs of
constructs or discriminant validity was attained.
Construct validity was established on confirmatory factor analyses (CFA). Table II
depicts correlations among the latent constructs in the CFA. χ2 statistics and three fit indices
were used to assess the acceptability of the measurement model. Indices such as
non-normed fit index (NNFI), Tucker-Lewis coefficient (TLI), comparative-fit index (CFI),
and root mean square error of approximation (RMSEA) were used to estimate the model.
The fit indices including NNFI ¼ 0.95, TLI ¼ 0.95, CFI ¼ 0.96, which surpassed the 0.90
cut-off value (Tabachnick and Fidell, 2001; Hu and Bentler, 1995), indicate that the data
fitted the model. The level of misfit was also tolerable, with RMSEA ¼ 0.04, under the
relevant benchmark of 0.08 (Hu and Bentler, 1999). Besides, model fit was further reinforced
through χ2/df ¼ 281.58/162 ¼ 1.74, which is below 2 (Carmines and McIver, 1981).
Hypothesis tests
The effect of ambidextrous leadership on operational performance through EO.
The hypotheses were tested through hierarchical multiple regression analysis following
Cohen et al.’s (2003) procedures. The testing process commenced with the estimation of a
model with simple effects (without the OSC interaction effects) (Model 1 in Table III).
The hypothesized model (Model 2 in Table III), which incorporated the OSC interaction
effects, was then estimated. The addition of the hypothesized interaction significantly
improved model fit (Satorra-Bentler scaled χ2 difference test (Satorra and Bentler, 2001):
Dw2SB ¼ 14.096, po 0.01). The R2 values also unveiled that the model accounted for large
proportions of variance in the endogenous variables (31.7 percent of variance in EO and
Constructs Mean SD 1 2 3 4 5 6 7 8 CCR AVE
a
1. Organizational size 5.48 0.65 –
2. Organizational age 21.7 9.3 0.06 –
3. Ownership type 1.42 0.36 0.05 0.03 –
4. Ambidextrous leadership 3.48 0.46 0.12 0.07 0.14* (0.77) 0.81 0.588
5. EO 3.62 0.57 0.16* 0.11 0.18* 0.54*** (0.78) 0.84 0.609
6. Trust 3.27 0.34 0.01 0.04 0.02 0.29** 0.41** (0.73) 0.82 0.532
7. Goal congruence 3.36 0.39 0.03 0.06 0.05 0.15* 0.24* 0.12* (0.81) 0.73 0.657
8. Operational performance 3.47 0.41 0.14* 0.08 0.16* 0.18* 0.48** 0.14* 0.11* (0.79) 0.86 0.624
Notes: CCR, composite construct reliability; AVE, average variance extracted. Values in parentheses display the square root of the average variance extracted. aValue is
the natural logarithm. Standardized correlations reported *p < 0.05; **p < 0.01; ***p < 0.001
moderator
239
OSC as a
Operational performance
Ambidextrous leadership – – 0.162*
Entrepreneurial orientation 0.462** 0.459** 0.458**
Entrepreneurial orientation × Organizational size – 0.196* 0.196*
240 Entrepreneurial orientation × Organizational age – 0.139 0.137
Entrepreneurial orientation × Ownership type – 0.208* 0.208*
Entrepreneurial orientation
Ambidextrous leadership 0.674*** 0.672*** 0.672***
Trust 0.405** 0.404** 0.402**
Goal congruence 0.225* 0.225* 0.224*
Organizational size 0.153* 0.152* 0.152*
Organizational age 0.111 0.109 0.110
Ownership type 0.175* 0.175* 0.174*
Ambidextrous leadership × Trust – 0.366** 0.366**
Ambidextrous leadership × Goal congruence – 0.257* 0.257*
Model characteristics
Log-likelihood −10,017.215 −10,021.552 −10,020.636
Table III. Scaling factor 1.248 1.246 1.246
Standardized path Free parameters 165 162 162
coefficients Notes: *po 0.05; **p o0.01; ***p o0.001 (two-tailed)
High trust
1.5
Low trust
1.0
Entrepreneurial orientation
0.5
0.0
–0.5
–1.0
Figure 3.
–1.5 Moderating effect
Low ambidextrous High ambidextrous of trust
leadership leadership
LODJ High goal congruence
1.5
38,2 Low goal congruence
1.0
Entrepreneurial orientation
0.5
242
0.0
–0.5
–1.0
Figure 4.
Moderating effect –1.5
of goal congruence Low ambidextrous High ambidextrous
leadership leadership
organizations with smaller size. Likewise, the results supported our hypothesis that
ownership is a moderator for the relationship between EO and operational performance
( β ¼ 0.208, p o0.05), indicating that the effect of EO on operational performance in
organizations that have foreign-invested ownership is stronger than that in organizations
with other ownership types. Nonetheless, the results do not corroborate the
role of organizational age in moderating the EO-operational performance relationship
( β ¼ 0.137, p W0.10).
To test differences in terms of organizational size, organizational age, and ownership
type, the critical ratio (CR) test ( W±1.96, p o0.05) is employed to achieve the CR
statistics for the differences among regression weights of larger- and smaller-size subjects,
higher- and lower-age subjects, and foreign-invested and other ownership subjects
(Ho, 2006). According to Arbuckle (2010), the CR of an estimate pair is utilized to confirm the
equality of the two parameters. As the results in Table IV reflect, there were significant
differences in the relationship between EO and operational performance in larger and
smaller organizational size, and in foreign-invested type and other ownership types, but no
significant difference in the relationship between EO and operational performance in
higher and lower organizational age. Thus, these findings support that organizational
size and ownership act as moderators for the EO-operational performance relationship in
our research model.
Managerial implications
The research results indicate that the improvement in operational performance may not be
produced without soft change factors such as EO. Organizational leaders therefore should
not build operational performance initiatives through their complete reliance on hard factors
such as technology transfer, but should balance between technology transfer and the
cultivation of entrepreneurial values among employees. This is reflected in Lattuch and
Seifert’s (2015) change management perspective. Leaders should design training programs
that not merely increase employees’ knowledge of new technologies or quality management
approaches to be adopted in the organization, but also infuse entrepreneurial values into
their mindsets. Leaders should not adopt new technologies and coerce their employees to
follow, but rather using opening leadership behaviors to inspire their openness to new OSC as a
technologies or quality management approaches, as well as using closing leadership moderator
behaviors to refreeze entrepreneurial values. In addition, leaders should use
opening behaviors to inspire employees to contribute initiatives to ongoing technological
and managerial improvements of the organization, and engage more employees in its
exploratory change. They should also use closing behaviors to encourage employees
with low adaptability to exploit all their competencies in an incremental operational 245
change process.
Furthermore, since OSC plays a moderating role for the influence of ambidextrous
leadership on EO, leaders should create the harmony between the goals and interests of
employees and the organization by formulating strategies through both top-down and
bottom-up approaches (Pascale and Sternin, 2005). They should elicit the contribution of
ideas to strategies from employees but in the direction of the organizational vision. Leaders
should further communicate and translate entrepreneurial strategic posture into goals and
roles for teams, as well as role-model their commitment to entrepreneurial goals, thereby
fostering goal congruence among employees. As Kotter (1995) suggests, the organization
also needs to establish a guiding coalition, consisting of change agents who role-model their
commitment to team goals and nurture goal congruence among their team members.
Moreover, leaders should be cognizant that trust – a crucial component of OSC,
which strongly interacts with goal congruence (Leana and Van Buren, 1999) – should be
built to reinforce the relationship between ambidextrous leadership and EO. Trust will
augment employees’ response to opening behaviors of the ambidextrous leader as well as
reduce their resistance to exploratory change, thereby catalyzing their shift from
incremental adaptation to exploratory change in operational performance. Trust should be
fostered through fair practices, especially understanding employee resistance to
entrepreneurial posture as a sign of leaders’ ineffective communication and inculcation of
entrepreneurial values into employees as well as avoiding the use of this resistance to isolate
or ostracize them from change activities.
Further reading
Schulze, W.S., Lubatkin, M.H. and Dino, R.N. (2003), “Toward a theory of agency and altruism in family
firms”, Journal of Business Venturing, Vol. 18 No. 4, pp. 473-490.
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