Team Leadership

Part 1: Team Leadership

Review attached academically reviewed articles on Team Leadership. Develop power presentation based on the articles. Support your presentation with appropriate references. Use APA format throughout.

Part 2: Discuss your learning outcomes:

present a discussion of your learning outcomes from the article review. Present your learning outcomes using power points.

Specific Instructions:

1. discuss requirements for Parts 1 and 2 above in 2 slides. references would be 3rd slide.

2. Use APA format throughout.

IMPACT OF TEAM LEADERSHIP HABITUAL DOMAINS
ON AMBIDEXTROUS INNOVATION

XINWEI YE, JUNWEN FENG, LEI MA, AND XIAOJING HUANG
Nanjing University of Science and Technology

We studied the formation of leaders’ habitual behaviors and the impact of leaders’ existing
and potential capabilities on ambidextrous (i.e., exploitative and exploratory) innovation
activities. Leadership habitual domain (LHD) theory was applied from an endogenous
perspective to analyze the impact mechanism of LHD on ambidextrous innovation via the
mediating role of dynamic capabilities. We used structural equation modeling to test data
collected from 205 team leaders in East China. Results showed that LHD was positively
associated with both exploitative and exploratory innovation, and that dynamic capabilities
mediated these relationships. Thus, team leaders should renew, reconfigure, and expand their
LHD by sensing and seizing opportunities when implementing ambidextrous innovation.

Keywords: team leadership, habitual domains, ambidextrous innovation, exploitative
innovation, exploratory innovation, dynamic capabilities.

In hypercompetitive environments, enterprises should establish a passive
adaptation mechanism to cope with external pressure, and should also form
a mechanism to innovate actively (Benner & Tushman, 2003). Jansen, Van
Den Bosch, and Volberda (2006) argued that companies need to apply
both exploitative and exploratory types of innovation, termed ambidextrous

SOCIAL BEHAVIOR AND PERSONALITY, 2018, 46(12), 1955–1966
© 2018 Scientific Journal Publishers Limited. All Rights Reserved.
https://doi.org/10.2224/sbp.7323

1955

Xinwei Ye, School of Economics and Management and Centre for Innovation and Development,
Nanjing University of Science and Technology; Junwen Feng, School of Economics and
Management, Nanjing University of Science and Technology; Lei Ma, School of Public Affairs and
Centre for Innovation and Development, Nanjing University of Science and Technology; Xiaojing
Huang, School of Intellectual Property and Centre for Innovation and Development, Nanjing
University of Science and Technology.
This work was supported by the Project of the National Natural Science Foundation of China
(71272164).
Correspondence concerning this article should be addressed to Lei Ma, School of Public Affairs,
Nanjing University of Science and Technology, Xiaolingwei 200, Nanjing, Jiangsu 210094, People’s
Republic of China. Email: maryma208@sina.com

TEAM LEADERSHIP AND AMBIDEXTROUS INNOVATION1956

innovation, to obtain a long-term competitive advantage. O’Reilly and Tushman
(2011, 2013) described the ability to sense and seize new opportunities as a
key leadership challenge. Teams are playing an increasingly important role in
organizational management, and the amount of research on team leadership
reflects this trend (Braun, Peus, Weisweiler, & Frey, 2013; Hoch & Kozlowski,
2014; Morgeson, DeRue, & Karam, 2010). Rosing, Frese, and Bausch (2011)
proposed the concept of ambidextrous leadership, that is, integration of opening
and closing leader behaviors—which increase and reduce variance in follower
behaviors, respectively—and suggested switching between the two to deal with
the changing requirements of innovation. However, there has been little research
into the formation of leaders’ habitual behaviors and the impact of existing
and potential capabilities on innovation activities. In team leadership habitual
domains (LHD; Ma, Hu, Ye, & Wang, 2014) theory a new research perspective
has been put forward that addresses the leaders’ habitual behaviors and their
potential abilities on the basis of their experience, knowledge, and capabilities.

An effective leader needs to foster both exploitation and exploration, and
switch flexibly between them (Rosing et al., 2011). Dynamic capabilities are
rooted in both exploratory and exploitative activities (Benner & Tushman,
2003). In combination with good strategic leadership, dynamic capabilities
allow companies to produce the right products for the right market to satisfy
consumers’ needs, and gain promising technologies and a competitive advantage
(Teece, 2012). Researchers have explored the impact of leadership preferences
on ambidextrous innovation, but neglected to examine whether leaders can
change their existing abilities to satisfy a changing environment (Chang &
Hughes, 2012; Jansen, Vera, & Crossan, 2009; Lin & McDonough, 2011; Zacher
& Rosing, 2015). As flexibility is one characteristic of LHD (Ma et al., 2014),
we introduced the mediator of dynamic capabilities to explore how team leaders’
LHD affects ambidextrous innovation, thereby allowing companies to obtain a
long-term competitive advantage in a complex and changing environment.

Literature Review and Development of Hypotheses

Leadership Habitual Domains Theory
Yu (1980, 1991) stated that each person has a unique set of behaviors rooted

in his or her ways of thinking, forming memories, judging, responding, and
handling problems, and that these behaviors tend to stabilize within a certain
domain over time. This collection of habitual behaviors, along with its formation,
dynamics, and the basis of experience and knowledge, is called one’s habitual
domain. Therefore, leadership habitual domains (LHD) refer to an absence
of stimuli causing a leader’s knowledge and experience to gradually stabilize
within a certain domain, forming a pattern of habitual behavior over a period

TEAM LEADERSHIP AND AMBIDEXTROUS INNOVATION 1957

of time. In addition, leaders’ knowledge and experience constitute a potential
capability to deal with environmental change (Ma et al., 2014), whereas activated
or focused knowledge and experience constitute one’s existing capabilities and
form observable habitual behaviors. Leaders can expand or reform their LHD by
habitual perception, learning, reflection, and practice; pursuing new leadership
skills until they reach a relatively stable state of LHD; and switching between
different leader behaviors as needed.

Specific LHD, which guide leaders’ decision making and determine their
different leadership styles and leadership behaviors, are formed from individual
leaders’ heterogeneous knowledge and experience. For example, Ma Yun, the
chief founder of Alibaba Group, originally engaged in translation work and
wanted to establish an e-commerce company in China only after realizing the
market potential of e-commerce, an idea that changed his LHD. Other Chinese
entrepreneurs were not stimulated by the new concept of e-commerce, so it did
not become part of their LHD, leading to their making different decisions. Thus,
people who have the same leadership style do not necessarily have the same
LHD. Leadership style is defined as the habitual behavior that leaders use when
influencing subordinates, and is gradually formed through long-term leadership
experience and practice. Thus, leadership style is the behavior model of leaders,
reflecting and providing a way to understand LHD, whereas LHD comprise a
leader’s own attributes.

LHD have three characteristics: flexibility, demonstration, and coadaptation
(Ma et al., 2014). Flexibility means that when the internal or external environment
changes, a team leader can make a quick response and an effective decision to
deal with the change, then return to the original stability. Demonstration refers
to the stability of the leader’s behavior often being learned and imitated by their
subordinates, with proactive behavior being oriented toward team members.
Coadaptation refers to the fact that, because habitual domains vary among team
members and between team members and leaders, leaders absorb knowledge and
experience from an uncertain external environment, then influence and adapt
with team members mutually, constantly improving their own LHD and team
members’ habitual domains.

Leadership Habitual Domains and Ambidextrous Innovation
Exploitative innovation and exploratory innovation are significant features

of an ambidextrous organization (Jansen et al., 2006). Exploitative innovation
is aimed at meeting the existing market and customer needs, and enhancing the
organization’s existing skills, processes, and structure on the basis of existing
knowledge. It leads to a slight improvement in quality and performance in
products and processes, mainly affects the organization’s short-term gains, and
makes the organization more competitive (Colombelli, Krafft, & Quatraro,

TEAM LEADERSHIP AND AMBIDEXTROUS INNOVATION1958

2014). In contrast, exploratory innovation is aimed at meeting the emerging
market and customer needs, carrying out new designs, developing new markets,
or opening up new distribution channels relying on new knowledge. It broadens
the breadth of knowledge, produces a series of product and process innovations,
and improves the flexibility and diversity of the organization. Exploratory
innovation may not be effective in the short term, and the results are not easily
predictable (March, 1991). In the process of ambidextrous innovation, leaders
should be able to weigh up the conflicts between exploitative and exploratory
innovation, and constantly adjust their leadership style to match the required
management activities (Jansen et al., 2006; O’Reilly & Tushman, 2011).

Researchers have explored the factors that influence ambidextrous innovation
from the perspective of leadership. For example, Jansen et al. (2009) indicated
that transformational leadership behaviors contribute significantly to exploratory
innovation, whereas transactional leadership behaviors are associated with
exploitative innovation. However, Lin and McDonough (2011) argued that the
relationship between leadership and innovation is complex. Chang and Hughes
(2012) found that risk-taking managers tend toward exploratory innovation and
risk-intolerant managers tend toward exploitative innovation, and Zacher and
Rosing (2015) verified that team leaders need to engage in both opening and
closing behaviors to produce high levels of innovation. Therefore, we proposed
the following hypotheses:
Hypothesis 1: Leadership habitual domains will have a significantly positive
impact on exploratory innovation.
Hypothesis 2: Leadership habitual domains will have a significantly positive
impact on exploitative innovation.

Leadership Habitual Domains and Dynamic Capabilities
Dynamic capabilities (DC) allow a firm to sense and seize opportunities or

threats, and integrate, build, and reconfigure internal and external resources
and routines to address rapidly changing environments (Barreto, 2010). DC are
rooted in high-level routines and analytical methodologies that determine the
speed and degree of aligning particular resources to modify or even transform
continuously what the enterprise is doing, in order to match the requirements
of the business environment (Teece, 2012; Winter, 2003). Essentially, DC are
an adaptation mechanism that enables enterprises to acclimate to dynamic and
complex circumstances.

Researchers have pointed out that DC purposely change basic resources
under managers’ leadership (Helfat et al., 2007; Teece, 2016). Teece (2016)
stated that DC are reliant on the organization’s values, culture, and collective
ability, which mainly result from past management efforts and are embedded
in the organization’s habitual domains. Unlike ordinary capabilities, DC may

TEAM LEADERSHIP AND AMBIDEXTROUS INNOVATION 1959

be based on the skills and knowledge of leaders rather than on organizational
routines. Accordingly, leadership skills are required to sustain DC (Teece, 2012).
Improving and expanding LHD can enhance the flexibility of the enterprise to
adapt to a changing environment (Ma, Zhang, & Han, 2002), which can also
improve DC. Thus, we proposed the following hypothesis:
Hypothesis 3: Leadership habitual domains will have a significantly positive
impact on dynamic capabilities.

Dynamic Capabilities and Ambidextrous Innovation
Strong DC are the key to success, especially when an innovative company

needs to develop new markets or new products (Teece, 2012). Taking the
initiative to mobilize resource allocation, DC allow organizations to broaden
existing knowledge boundaries and technical capabilities, and carry out creative
searching activities in relation to new market boundaries, thereby permitting
organizations to discover new business opportunities or markets (Pandza &
Thorpe, 2009), which supports exploratory innovation. Meanwhile, DC can
facilitate the communication, diffusion, and integration of existing knowledge
and resources, thus reinforcing organizations’ existing technologies, processes,
and products (Helfat & Eisenhardt, 2004), so as to promote exploitative
innovation.

Castiaux (2007) found that large-scale enterprises can promote the use of
existing knowledge and the development of new knowledge by linking with
network members. Ellonen, Wikström, and Jantunen (2009) also found that
DC can effectively improve the competitive means in existing markets and the
development of new markets. Sheng (2017) stated that successful ambidextrous
innovation requires a combination of DC and organizational sense-making,
the process by which an organization senses and acts decisively to respond to
opportunities and threats. Thus, we proposed the following hypotheses:
Hypothesis 4: Dynamic capabilities will have a significantly positive impact on
exploratory innovation.
Hypothesis 5: Dynamic capabilities will have a significantly positive impact on
exploitative innovation.

The Mediating Role of Dynamic Capabilities
According to Morgeson et al. (2010), team leadership has 15 functions, such as

training and developing the team, sense-making, solving problems, and providing
resources. For the team to be fully functioning, leaders need to mobilize their
skills and resources to satisfy the team’s needs (O’Reilly & Tushman, 2008).
During this process, leaders need to know each member’s habitual domains and
have flexible LHD to use different leadership tactics for different members of
the team (Ma et al., 2014). In addition, the critical tasks leaders need to perform

TEAM LEADERSHIP AND AMBIDEXTROUS INNOVATION1960

are sensing opportunities and threats, seizing opportunities, and managing
threats/transforming, which can effectuate better resource allocation in times of
uncertainty (Teece, 2016), and enable firms to reconfigure existing assets and
learn new ways to perform ambidextrous innovation (O’Reilly & Tushman,
2008, 2011). Thus, we proposed the following hypothesis:
Hypothesis 6: Dynamic capabilities will mediate the relationship between
leadership habitual domains and ambidextrous innovation.

Method

Participants and Procedure
Participants were team leaders in Chinese companies that were located in

Jiangsu, Guangxi, Guangdong, and Shandong Provinces. All study procedures
were conducted in accordance with the ethical standards of our institutional
research committee and with the 1964 Declaration of Helsinki and its later
amendments. We sent our survey forms to 309 team leaders, and 224 of them
responded (response rate = 72.49%). After excluding 19 invalid responses, the
final sample consisted of 205 respondents (valid response rate = 66.34%). Table
1 shows the demographic profiles of the respondents and their teams.

Table 1. Participants’ Demographic Characteristics

Characteristics Frequency Percentage (%)

Gender Male 119 58.0
Female 86 42.0
Level of education High school graduate 19 9.3
College graduate 49 23.9
Bachelor’s degree 94 45.8
Master’s degree 43 21.0
Age (years) Under 30 39 19.1
30–39 57 27.8
40–49 62 30.2
50–59 47 22.9
Team size 10 or fewer 125 61.0
11–20 42 20.5
21–30 8 3.9
31–40 13 6.3
41 or more 17 8.3

Measures
Leadership habitual domains. LHD were measured using the 17-item scale

developed by Ma et al. (2014), which comprises three dimensions: flexibility
(e.g., “I make plans in advance to deal with problems that may arise in future
work”), demonstration (e.g., “My behavior in my work can be imitated and

TEAM LEADERSHIP AND AMBIDEXTROUS INNOVATION 1961

studied by team members”), and coadaptation (e.g., “I am able to effectively
resolve team conflicts, coordinate relationships, and encourage team members
to get along well”). Responses were rated on a 5-point Likert-type scale ranging
from 1 (strongly disagree) to 5 (strongly agree).

Dynamic capabilities. DC were measured using a 14-item scale developed
by Feng (2012), which consists of three dimensions: sensing capability (e.g.,
“We have various ways get to know the development status and trends of the
industry”), integrating capability (e.g., “Information about the industry or market
can be widely disseminated within the enterprise”), and reconfiguring capability
(e.g., “We can adjust in a timely manner our internal and external networks and
network communication”). Reponses were rated on a 5-point Likert-type scale
ranging from 1 (strongly disagree) to 5 (strongly agree).

Ambidextrous innovation. We measured exploratory innovation and
exploitative innovation using the 12-item scale developed by Jansen et al.
(2006). As the original scales were developed in English, we conducted back-
translation to ensure the equivalence of the Chinese version. A bilingual scholar
and three postgraduate students with a management background were asked to
read through the items and comment on the clarity of expression. A sample item
for exploratory innovation is “Our company accepts demands that go beyond
existing products and services,” and a sample item for exploitative innovation
is “We frequently refine the provision of existing products and services.”
Responses were rated on a 5-point Likert-type scale ranging from 1 (strongly
disagree) to 5 (strongly agree).

Data Analysis
We used SPSS version 22.0 to generate the descriptive statistics and the

means, standard deviations, correlations, and reliability results for the study
variables. Then we used Amos version 21.0 to perform the confirmatory factor
analysis. We conducted structural equation modeling to explore the relationships
between LHD, DC, and ambidextrous innovation because this method allowed
us to assess the relationships among the latent variables simultaneously, while
ensuring statistical efficiency (Blunch, 2008). Finally, we performed mediation
analysis using PROCESS version 3.0.

Results

The means, standard errors, reliability coefficients, and correlations among the
study variables are presented in Table 2. We adopted Cronbach’s  coefficients
to measure the internal consistency reliability of the scales, and all were greater
than .80, indicating that the measures had a high level of reliability.

TEAM LEADERSHIP AND AMBIDEXTROUS INNOVATION1962

Table 2. Means, Standard Deviations, and Correlations for Study Variables

Variables M SD 1 2 3 4

1. Leadership habitual domain 4.09 0.71 (.92)
2. Dynamic capabilities 3.99 0.83 .82** (.93)
3. Exploratory innovation 3.90 0.83 .33* .70** (.87)
4. Exploitative innovation 3.94 0.80 .63** .56** .87** (.88)

Note. N = 205. Cronbach’s alpha values are shown in parentheses.
* p < .05, ** p < .01.

The confirmatory factor analysis results are shown in Table 3. The goodness-
of-fit index did not reach but was close to the ideal value, and the other fit indices
all exceeded the recommended minimums; thus, we believe that this model
supports the distinctiveness of the constructs.

Table 3. Fit Indices for Confirmatory Factor Analysis Results

Fit indicator 2 df 2/df GFI CFI IFI TLI RMR RMSEA

Proposed model 236.736 130 1.821 .889 .963 .964 .957 .035 .063
Fit guideline – – < 3.0 > .90 > .90 > .90 > .90 < .08 < .08

Note. N = 205. GFI = goodness-of-fit index, CFI = comparative fit index, IFI = incremental fit index,
TLI = Tucker–Lewis index, RMR = root mean square residual, RMSEA = root mean square error of
approximation.

We conducted structural equation modeling to test the hypotheses. First, we
tested the main effect of the independent variable (LHD) on the dependent
variable (ambidextrous innovation). The results show that LHD had a positive
influence on both exploratory innovation ( = .83, p < .001) and exploitative innovation ( = .86, p < .001). Thus, Hypotheses 1 and 2 were supported.

Second, we tested the correlations between the independent variable (LHD)
and the mediator (DC), and between the mediator (DC) and the dependent
variable (ambidextrous innovation). Results show that LHD was positively
and significantly associated with DC ( = .82, p < .001). Thus, Hypothesis 3 was supported. In addition, DC had a significantly positive correlation with exploratory innovation ( = .93, p < .001) and with exploitative innovation ( = .80, p < .001). Thus, Hypotheses 4 and 5 were supported.

Third, we used bootstrapping to examine the mediating effects, following
Preacher and Hayes’ (2004) recommendation. Bootstrap estimates (based on
5,000 resamples) indicated that the indirect effect of LHD on exploratory
innovation through DC was significant (p < .05), with a point estimate of 0.74 and a 95% confidence interval (CI) excluding zero [0.61, 0.87], and the direct effect of LHD on exploratory innovation after controlling for DC also had a 95% CI excluding zero [0.01, 0.29]. These results indicate that DC mediated the

TEAM LEADERSHIP AND AMBIDEXTROUS INNOVATION 1963

relationship between LHD and exploratory innovation. Furthermore, the indirect
effect of LHD on exploitative innovation through DC was significant (p < .001), with a point estimate of 0.63 and a 95% CI interval excluding zero [0.46, 0.78], and the direct effect of LHD on exploitative innovation after controlling for DC also had a 95% CI excluding zero [0.12, 0.40]. These results indicate that DC mediated the relationship between LHD and exploitative innovation. Thus, Hypothesis 6 was supported.

Discussion

In this study we found that LHD had a positive effect on DC, exploitative
innovation, and exploratory innovation, and that DC mediated the effect of LHD
on both types of innovation. Moreover, DC was found to be positively related to
both exploitative innovation and exploratory innovation.

Theoretical and Practical Implications
First, we found that LHD had a positive effect on both exploitative innovation

and exploratory innovation, which supports previous research findings on the
relationship between LHD and ambidextrous innovation (Ma et al., 2014; Tang,
Ye, Chen, & Feng, 2004; Ye, Feng, & Ma, 2016). Whereas Ye et al. (2016)
provided a framework to explore the relationship between firms’ technology
habitual domains and innovation strategies, in this study we moved to a personal
perspective by focusing on team leaders who are responsible for satisfying team
members’ needs and achieving team goals (Morgeson et al., 2010). Leaders’
habitual behaviors, which reflect LHD, are formed by stabilized knowledge and
experience that accumulate over time, and LHD contribute to leaders’ existing
and potential capabilities. Meanwhile, the inertia of LHD supports exploitative
innovation by refining existing products and gaining efficiency, but when a leader
is stimulated by new information, LHD becomes unstable and is reconfigured or
even transformed to a new domain, thus supporting exploratory innovation (Ye
et al., 2016). Our analysis of the antecedents of ambidextrous innovation from
an endogenous viewpoint has filled a gap in the existing research and enriched
HD theory by providing a new perspective with which to study leadership theory.

Second, our results confirm that DC mediates the relationship between LHD
and ambidextrous innovation, which supplements existing knowledge of this
influence process. According to the innovation dynamics framework proposed
by Yu and Chen (2012), firms need to consider how to solve a set of problems
by using existing or acquired competencies, and also need to create value. By
introducing the mediator of DC, we revealed the influence mechanism of firms’
strategic renewal and transformation of existing knowledge and competencies in
LHD to satisfy the need for ambidextrous innovation.

TEAM LEADERSHIP AND AMBIDEXTROUS INNOVATION1964

Moreover, we found that LHD can affect DC. As coadaptation is a characteristic
of LHD, LHD can affect leaders’ ability to adapt to the environment (Ma et
al., 2014). Combined with the heterogeneous knowledge, experience, and
capabilities provided by LHD, specific LHD give enterprises their distinct DC to
respond to turbulence. As high-level competencies, DC determine the speed and
degree of aligning particular resources to match the requirements of the business
environment (Teece, 2012). As we also verified that DC are positively related
to ambidextrous innovation, which is consistent with existing research findings
(Castiaux, 2007; Ellonen et al., 2009; Sheng, 2017), our results also explain
the differences in developing and executing innovation strategies between
enterprises through LHD theory.

In addition, although habitual domain theory has been applied to various
research areas (e.g., decision making, innovation management), there is still a
shortage of empirical studies using this theory. In this study we applied structural
equation modeling to analyze the effect of LHD on ambidextrous innovation,
providing objective and reliable results and enriching the extant literature on
habitual domain theory.

Practically, we can conclude from our results that team leaders need to broaden
the depth and width of leadership knowledge and experience, because the more
they are stabilized in LHD, the more likely the firm is to succeed in ambidextrous
innovation. In addition, to avoid the rigidity of LHD, leaders need to constantly
renew, reconfigure, and transform their existing capabilities, structures, and
processes, to maintain efficiency in the short term by using exploitative
innovation and pursue profit in the long term through exploratory innovation.

Limitations and Future Research Directions
This study has certain limitations. First, we adopted a horizontal data collection

method, which may not be able to reveal accurately the dynamic changing impact
of LHD on DC and ambidextrous innovation. Therefore, future researchers
could apply longitudinal analysis to trace the relationships between LHD, DC,
and ambidextrous innovation. Second, some variables may have been strongly
correlated owing to the relatively small sample size in this empirical study.
Future researchers could increase the sample size to avoid multicollinearity.
Third, we focused only on one mediator in the relationship between LHD and
ambidextrous innovation. Future researchers could include more mediators and/
or moderators, to improve interpretation of the model.

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