Content uploaded by Rana B. Madi Odeh
Author content
All content in this area was uploaded by Rana B. Madi Odeh on Feb 06, 2025
Content may be subject to copyright.
The moderating role of managerial
discretion: the impact of dynamic
managerial capabilities on
established firms’response strategies
to disruptive innovation
Rana Bassam Madi-Odeh
Faculty of Business and Law, The British University in Dubai, Dubai,
United Arab Emirates and Decision Support Department, Expert,
Dubai Municipality, Dubai, United Arab Emirates, and
Bader Yousef Obeidat
Department of Business Management, School of Business,
The University of Jordan, Amman, Jordan and Faculty of Business and Law,
The British University in Dubai, Dubai, United Arab Emirates
Abstract
Purpose –Using the upper echelons theory, this study aims to investigate the moderating effect of managerial
discretion (MD) on the impact of dynamic managerial capabilities (DMCs) on established firms’(EFs)
response strategies to disruptive innovation (RStDI).
Design/methodology/approach –A cross-sectional study was conducted using an online
questionnaire to collect data from senior management of sample firms, targeting the population of
professional service firms (PSFs) operating in the Emirate of Dubai. After receiving 491 responses,
data was analyzed using IBM packages (SPSS and Amos) through a covariance-based structural
equation modeling technique.
Findings –As proposed, the underpinnings of DMCs (managerial human capital, managerial social
capital and managerial cognitive perceptions) were associated with EFs’strategies for responding to DIs.
Surprisingly, despite theoretical predictions, MD did not moderate the relationship. These findings
provided support to the main propositions of the upper echelons theory, however, not for its contextual
moderator (MD).
Research limitations/implications –The cross-sectional approach to testing the research model limits the
identified significant effects that should be further investigated. The research sample was restricted to PSFs
operating in Dubai, UAE, thus limiting the generalizability of the findings to the examined context.
Practical implications –The findings of this investigation are valuable to managers and hiring teams. They
provide empirically supported insights on the critical role of managerial dynamic capabilities underpinnings
(human capital, social capital and cognitive perceptions) in facilitating organizational RStDI. The findings also
provide significant insights to policymakers, notably on the importance of innovative and well-crafted policies
and regulative frameworks that enhance MD.
Originality/value –This study provides one of the first empirical quantitative analysis to assess MD and test
its effects as a moderator, thus contributing significantly to the existing theoretical arguments on MD. To the
Conflictofinterest:On behalf of all authors, the corresponding author states that there is no conflict of interest.
International
Journal of
Innovation
Science
Received30 November 2023
Revised 11May 2024
11 June 2024
21 July 2024
Accepted29 July 2024
International Journal of Innovation
Science
© Emerald Publishing Limited
1757-2223
DOI 10.1108/IJIS-11-2023-0258
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1757-2223.htm
best of the authors’knowledge, this study is among the first to quantify the relationship between DMCs and
organizational RStDI.
Keywords Upper echelons theory, Dynamic managerial capabilities,
Response strategies to disruptive innovation, Managerial discretion, Professional service firms,
Emirate of Dubai
Paper type Research paper
1. Introduction
In the current digital age, marked by the evolution and advancement of super technologies
like artificial intelligence, big data and the Internet of things, the business environment is
witnessing unprecedented volatility caused by increased competition and rapidly evolving
trends enabled by technological advancements, which facilitated the emergence of countless
new businesses with disruptive business models (Fayad and El Ebrashi, 2022;Hartman and
Parilla, 2022). These disruptive business models swept the world in no time and challenged
the existence of established firms (EF), who did not anticipate such a disruption. This
dilemma was first discussed by Christensen (1997), who discussed the hard disk drive
industry and defined disruptive innovation (DI) as a process where small companies and
start-ups with fewer resources are capable of successfully challenging EF (Christensen et al.,
2015), mainly throughinnovative business models (Christensen, 2006;Chesbrough, 2010).
It is claimed that EF seldom responds effectively to DI (Christensen et al., 2015). As DI
does not seem competitive at its early stages (Teece, 2016), does not meet the requirements
of EF's mainstream customers (Martınez-Vergara and Valls-Pasola, 2020), and does not
comply with EF’s economic logic (Si and Chen, 2020). In this study, we challenge this claim
and aim to understand EF response strategies to DI (RStDI) in a complementary manner to
the existing literature, which focuses more on investigating this phenomenon from a
technological perspective (Sadiq et al., 2020) market characteristics, new markets and low-
end innovation perspectives (Nagy et al., 2016).
Recent studies have emphasized the importance of investigating the less explored
managerial perspective, which has a significantroleinmanagingandrespondingtoDI(
Ciampi
et al.,2021;Cortes and Kiss, 2023;Plöckinger et al.,2016;Sadiq et al.,2020). Hence, we
investigate the role of managers in formulating EF RStDI through their dynamic managerial
capabilities (DMCs) (Adner and Helfat, 2003), which are rooted in three main foundations:
•managerial human capital (MHC);
•managerial social capital (MSC); and
•managerial cognition (MC).
Where MHC refers to top executives' formal education, years of experience and training;
MSC refers to top executives’formal and informal networks of relations with the
government, business leaders and society; and MC refers to the cognitive abilities of
managers to observe events as threats or opportunities. This study sheds light on the role of
varying top executives DMC (MHC, MSC, MC) in shaping organizational behavior and how
they respond to disruption (RStDI).
To achieve the aim of this study, the upper echelons theoretical (UET) framework
(Hambrick and Mason, 1984) is used and tested among the professional service firms (PSFs)
operating in the Emirate of Dubai, in an endeavor to contribute to the literature of DI by
investigating the less explored service sector (Agarwal et al., 2016;Iyiola and Trafford,
2024). According to this theory, top executives’psychological attributes (like cognition and
IJIS
values) and other observable attributes (like age, experiences and education) are critical
determinants of top executives’decision-making, which shapes organizational behavior.
To improve the explanatory power of the UET, a crucial contextual moderator,
managerial discretion (MD), is introduced to the research model (Wangrow et al., 2014). MD
is defined as the “latitude of managerial actions”(Hambrick and Finkelstein, 1987, p. 371),
that is, the degree of freedom offered to decision-makers in a particular context, knowing that
each context has its specificities which mark it different from other contexts. According to
Liao and Zhang (2020), MD indicates how top executives impact firms' strategic decision-
making processes. MD, measured through a specific industry context variable, is essential in
determining the degree to which managerial traits and characteristics (i.e. DMC in this study)
will reflect on organizational outcomes (i.e. RStDI in this study). Figure 1 shows the study’s
high-level model.
Although we deductively investigate this phenomenon, this investigation is unique in
multiple ways.
First, it attempts to complement the previous literature on DI by focusing on the
disrupted side (i.e. EF) rather than the disruptors (i.e. the new entrants), which is
highlighted as an essential aspect of DI theory development (Christensen, 2006;
Christensen et al.,2018).
Second, it investigates the triggers of response to DI from within the organization (i.e.
managerial agency) rather than market and technological triggers, which are dominant in the
DI literature (Sadiq et al.,2020).
Third, this investigation provides empirical and quantitative evidence that the literature
lacks, hindering its theoretical generalizability, practical pertinency and its theorized
significance (Guo et al., 2020;Holzmayer and Schmidt, 2020;Heubeck and Meckl, 2022;
Liu et al., 2020;Mannor et al.,2016;Martınez-Vergara and Valls-Pasola, 2020;Mostafiz
et al., 2019;Pryor et al.,2019;Si and Chen, 2020).
Finally, this study is among the few investigations to incorporate the three underpinnings
of DMC (MHC, MSC and MC) in one model to predict organizational behavior (i.e.
response strategy to DI) (Helfat and Martin, 2015). Please refer to Appendix 1 for an
extension of the above.
Figure 1. Study’s high-level model
International
Journal of
Innovation
Science
This paper has six sections. Section 2 presents the theoretical framework and hypotheses
development, Section 3 describes the methods, Section 4 reports the results, and finally,
Sections 5 and 6 discuss the findings and state the concluding remarks, respectivley.
2. Theory and hypotheses
2.1 Dynamic managerial capabilities and response strategies to disruptive innovation
Researchers have been interested in explaining organizational behavior from an external and
environmental forces perspective since the 1970s (Mintzberg, 1978). However, it was only in
the early 1980s that organizational behavior was discussed in relation to managers’cognition
and perceptions. UET, which was developed based on the behavioral view of the firm (Cyert
and March, 1963;March and Simon, 1958), was first discussed by Hambrick and Mason
(1984) in response to the preceding efforts of researchers who described the organizations as
purposeful (Pfeffer and Salancik, 1978) or hapless (Hannan and Freeman, 1977). The upper
echelons describe decision-makers at the top of the organizational hierarchy (Finkelstein
et al., 2009). According to the theory, organizational behavior is perceived as a reflection of
its powerful actors' beliefs and cognitive bases. As such, top executives' differing
demographic and psychological characteristics are likely to influence their decisions, thus
resulting in different organizational strategies and performance levels (Liu and Ji, 2022).
This is attributed to top executives’characteristics and experience (i.e. DMC) that affect their
interpretation of the strategic environment and, therefore, influence their strategic choices,
shaping organizational behavior (i.e. RStDI).
According to the UET, and despite the prevailing claims that EF barely responds to DI
due to many internal and external factors (refer to Appendix 2 for a review of studies on
factors affecting EFs’nonresponse to disruption), we argue, in line with Tellis (2006),that
not all EF have this tendency. Moreover, we argue that their response strategy is greatly
determined by their top executives’DMC.
Helfat and Martin (2015) suggested that the DMC concept is discrete in its remarkable
emphasis on the managers’ability to influence strategic change. The theory contends that
organizations with managers owning DMC can adjust and adapt more effectively. In
addition, it has been argued that DMC is central in implementing strategic actions (e.g.
identifying opportunities) to attain stable organizational performance (Mostafizet al., 2019).
When facing an unexpected event such as disruption, managers should make a strategic
decision despite the situation's complexitythat goes beyond their ability to comprehend fully.
Managers need to bring their DMC, which is underpinned by their MHC (education,
experience and training), MSC (networks of formal and informal relations) and MC (ability
to perceive events as opportunities/threats), to analyze the situation and study the
possibilities. This process creates a filter through which they perceive the situation (Walsh,
1995). So, it is argued that the managers’field of vision is limited and selective (Prahalad and
Bettis, 1982;Vecchiato, 2017), thus posing limitations on their perception. Managers
perceive the disruptive event, each through his lens based on their set of DMC, and subject it
to their interpretation, followed by decision-making that resembles, in the first place, their
own capabilities and cognitive base, resulting in different strategic choices in the face of DI.
Thus, we argue that DMC will impact the RStDI that EF will adopt.
2.2 Response strategies to disruptive innovation
DI concept was triggered by the inability of earlier technological change theories to address
the hard disk drive anomaly (Yu and Hang, 2010). Competence enhancing and competence
destroying innovations classification (Tushman and Anderson, 1986) and architectural
innovation (Henderson and Clark, 1990) could not explain the hard disk industry EF failure
IJIS
in front of technological change waves that are not breakthrough nor architectural. The
theory explains how and why leading, well-managed, resource-plentiful, technologically
profound and customer-driven firms ignored DI and failed the competition.
DI is a process where small, less resourceful companies successfully contest against EF
(Christensen and Raynor, 2015). It is an innovation that redefines the rules of the game
(Charitou and Markides, 2003;Danneels, 2004). RStDI has been a hot topic of research. A
considerable number of researchers discussed these responses in relation to varying internal
and external factors. Appendix 3 summarizes some of these responses.
Christensen (2006) acknowledged that disruption is a business model problem (P. 48).
Chesbrough (2010) argued that any innovation's economic value is only materialized by
commercializing it through a business model. Thus, we adopt in this study the Osiyevskyy
and Dewald (2015) response strategies in terms of business model innovation. The
researchers argued that EF responds in one of two ways: adaptiveresponse strategies through
either strengthening their existing business model (exploitative adoption) or adopting the
new disruptive business model (explorative adoption) or defiant resistant response strategies
(resisting the adoption of DI). We argue that EF's response strategy is determined by their top
executives DMC.
2.3 Dynamic managerial capabilities
The success/failure of firms is not determined only by their competitive structures and
diversification patterns. Instead, it is mainly determined by the top management's evolution
and the ability to acquire new skills (Augier and Teece, 2009;Martin, 2011;Van de Ven, 2017).
Adner and Helfat (2003) presented DMC and defined it as “the capabilities with which
managers build, integrate and reconfigure organizational resources and competencies”
(p. 1012). They found that corporate managers in different firms, yet operating within the same
industry, responded to the same external environmental changes differently and made
strategically different decisions. They attributed this to the various sets of capabilities
managers own. These capabilities are underpinned by three foundations: MHC, MSC and MC.
2.3.1 Managerial human capital. Becker (1964) in Adner and Helfat (2003) defined
human capital as “learned skills that require some investment in education, training, or
learning more generally”(p. 1020) [1]. Managers exploit these learned skills to sharpen their
expertise and enhance their knowledge. Despite the wide range of human capital definitions,
the essential components of tacit knowledge measured via education and explicit knowledge
measured via experience and training are very prominent among relevant research
(Davidsson and Honig, 2003;Geletkanycz and Boyd, 2011;Khanna et al.,2014;Wright
et al., 2014); thus, it has been adopted in our investigation.
MHC is socially complex, rare and inimitable. Managers with higher levels of MHC are
expected to generate higher rents for their organizations (Carpenter et al., 2001;Koroglu and
Eceral, 2015;Prajogo and Oke, 2016). MHC is linked to the capacity of managers to integrate
and consume new knowledge from professional work experience, which decreases the
ambiguity of events and offers managers extra related and precise information about their
context (Cassar, 2014). Thus, it is suggested that organizations directed by well-educated and
experienced managers have higher-order capabilities to absorb outside knowledge (Kato, 2019).
Managers who own higher levels of MHC have higher absorptive capacity and a higher
tendency to invest in R&D, thus stimulating external knowledge sourcing that is expected to
influence the organizational propensity to adopt strategic change initiatives (Kato, 2019).
They are also better positioned to deal with complicated problems while leveraging their
knowledge and experience to obtain the resources necessary for identifying and exploiting
business opportunities (Ucbasaran et al., 2008). Finally, they have better logical problem-
International
Journal of
Innovation
Science
solving techniques, so they are more expected to be able to treat high risks and ambiguity,
which are intrinsic features of DI, superiorly (Kato and Honjo, 2015).
Managers’prior knowledge gained through education, working experience and
continuous training forms the base for acquiring new knowledge, improving experience and
enhancing individual skills (Ambrosini and Altintas, 2019;Helfat and Martin, 2015;
Mostafizet al., 2019). Managers usually build on their education, experience and knowledge
to sense and seize opportunities, avoid or mitigate threats and reconfigure resources in
response to dynamic environments, thus playing a crucial role in strategic change.
Nonetheless, as managers vary in their MHC, which shapes their decision-making rationale,
they usually differ in their absorptive capacity and abilities to sense and seize opportunities
and reconfigure accordingly (Adner and Helfat, 2003;Helfat and Martin, 2015). Managers
with higher levels of MHC have higher levels of absorptive capacity and, thus, are inclined
towards engaging in external knowledge sourcing (Debrulle et al.,2014;Kato, 2019;Zahra
and George, 2002), and consequently, they are more receptive to change. Based on that, we
hypothesize that:
H1. Higher levels of MHC positively impact adaptive RStDI.
2.3.2 Managerial social capital. The social capital concept was first introduced by the
French sociologist Pierre Bourdieu as: “the aggregate of the actual or potential resources
which are linked to possession of a durable network of more or less institutionalized
relationships of mutual acquaintance or recognition”(Bourdieu, 1985, p. 248) [2]. Adler and
Kwon (2002) argued that social capital definitions adopt one of two views: external relations
and internal relations. This investigation considers external relations as they form the conduit
to the external environment for transmitting and receiving information, resources and
opportunities, which is expected to improve managers' ability to respond and adjust in
dynamic environments (Acquaah, 2007).
It has been argued that managers' social ties and networks positively impact
organizational ambidexterity, where firms can vigorously explore and exploit strategic
activities (Cao et al., 2010). Managers' advice-seeking through their social ties and networks
reduces their doubts about their strategic beliefs and nurtures confidence through affirming
advice, positively affecting strategic change (McDonald and Westphal, 2003).
MSC positively impacts strategic change (Ambrosini and Altintas, 2019). MSC represented
in external, formal and informal work relations provides managers with supplementary and
diverse information which facilitates scanning the external environment and allows sparking
new ideas that are essential to innovations, thus better enabling sensing opportunities and
reconfiguring assets (Geletkanycz and Boyd, 2011;Helfat and Martin, 2015;Helfat and Martin,
2016;Martin and Bachrach, 2018). MSC facilitates managers’access to external resources and
information about practices in other firms required to seize opportunities, thus broadening their
field of vision, better enabling environmental scanning through networks of relations, and
supporting decision-making in favor of strategic change (Adner and Helfat, 2003;Helfat and
Martin, 2016;Prashantham and Dhanaraj, 2010). Thus, we hypothesize that:
H2. Higher levels of MSC positively impact adaptive RStDI.
2.3.3 Managerial cognition. MC is defined as “managerial beliefs and mental models that
serve as a basis for decision making”(Adner and Helfat, 2003, p. 1021) [3] and includes
mental processes and emotions (Helfat and Martin, 2015). It is shaped mainly by historical
experience rather than current knowledge and events; this fact explains why even top
IJIS
managers cannot adapt their mental models in dynamic and fast-changing environments
(Tripsas and Gavetti, 2000).
MC plays a significant role in framing responses to new emerging technologies (Benner
and Tripsas, 2012;Sirén et al.,2018). The literature provided mixed results on the impact of
cognition on strategic change. Nonetheless, it is essential to study cognitive capabilities in
terms of their type (flexible versus rigid mental structures) or (opportunity vs threat framing
and perceptions). It has been supported that the flexibility of managerial mental models
improved the degree of flexibility in the interpretation process of strategic resource allocation
decisions and the relevant available options, thus positively impacting response to strategic
change (Ambrosini and Altintas, 2019;Martin and Bachrach, 2018), whereas rigid cognitive
frames negatively impacted the ability to sense, seize opportunities and adjust accordingly
(Rosenbloom, 2000;Vecchiato, 2017).
MC is essential for scanning the environment selectively, assessing events, categorizing
them and understanding their consequences to prepare for responding (Walsh, 1995).
Dewald and Bowen (2010) argued that managerial decision-making is primarily driven by
managers' cognitive perception of events as a threat or an opportunity. This perception plays
a significant role in framing responses to new emerging technologies (Benner and Tripsas,
2012;Tripsas and Gavetti, 2000). According to the issues interpretation school of situation
framing (Dutton and Jackson, 1987), it is expected that threat cognitive perception (COTH)
will drive risk-averse response, whereas opportunity cognitive perception (COOP) will drive
risk-seeking behavior. The flexibility of managerial mental models and thinking structures is
expected to improve the degree of flexibility in the interpretation and the process of strategic
resource allocation decisions and, thus, the type of response the organization might opt for.
Based on the above, it is hypothesized that:
H3a. COTH positively impacts resistant RStDI.
H3b. COOP positively impacts adaptive RStDI.
2.4 Managerial discretion
MD was first discussed as an essential moderator to the UET by Hambrick and Finkelstein
(1987), who defined it as: “The latitude of managerial action”offered to the decision-makers
(e.g. managers, top executives […] etc.) in a particular situation. MD bridges the
environmental context and the organizational strategic choice (Hambrick and Finkelstein,
1987, p. 371). According to UET, MD is a manager's influence on a firm's strategic decision-
making and execution processes; that is, the degree of freedom in establishing goals and
acting. It reflects the room and scope for senior leaders to make strategic decisions. When
managers have more freedom to make and execute decisions within their firms, they can
create new opportunities, absorb and adapt to changes, take challenges and exploit
opportunities to enhance their organizational contribution and behavior (Amir et al.,2022).
MD explains the influence of leaders on organizational behavior and outcomes. As
managers are considered members of the organizational structure, they reside under many
constraints brought to them by internal and external factors such as governmental policies,
trade unions, business shocks and disruption (Liao and Zhang, 2020). Thus, the success of
implementing any reforms or actions attempting to respond to disruption initiated by the
managers themselves is contingent on the degree of their authority within the organization
(Crossland and Hambrick, 2011).
Low MD restricts managers, allowing limited strategic options; thus, leaders' roles
become less critical as firms adopt established strategies (Crossland and Hambrick, 2011;
International
Journal of
Innovation
Science
Liao and Zhang, 2020;Lin et al.,2020). On the other hand, higher levels of MD allow for
more potential strategic options (Wan g et al.,2021); thus, leaders' role becomes more critical
and provide them with the opportunity to use their education, skills, cognitive perceptions
and experience to shape organizational behavior and yield a substantial impact on
organizational results (Shen and Cho, 2005).
MD, discussed in this study at the environmental level (Boyd and Gove, 2006)[4].
Moreover, MD measured through (the degree of regulations, capital intensity, degree of
product differentiation and level of demand growth) is an essential factor in determining the
degree to which managerial traits and characteristics shaped by their MHC, MSC and MC
will reflect on organizational RStDI, and thus, its outcomes. In other words, the higher the
MD, the more freedom managers will enjoy, and the better managerial traits and
characteristics will reflect on organizational outcomes. On the contrary, as the degree of
regulation increases, capital requirements intensify, product differentiation and demand
growth lessens, MD levels decrease and managers become more constrained by other
contextual variables, thus leaving little room for managerial traits and characteristics to
reflect on organizational outcomes. Based on the above, it is hypothesized that:
H4. MD has a significant moderating impact on the relationship between DMC and
RStDI.
Figure 2 presents the study’s conceptual model.
3. Research methodology
3.1 Research context
The context of PSF in Dubai provides an excellent setting for studying and understanding
such a relationship for a few reasons. First, Dubai is an active host of PSF (+50,000 PSF
operating in the Emirate during 2022), where empirical research on the service industry and
PSF in particular is being called for (Agarwal et al.,2016;Amir et al., 2022;Jaworski and
Patel, 2020;Skjolsvik et al.,2017). Moreover, the United Arab Emirates is classified as a
secondary emerging economy in the Financial Times Stock Exchange Emerging Market
indices (FTSE_Rusell, 2022). Earlier research called for more studies in emerging
economies, and this research extends the investigation of such a relationship, which, to the
knowledge of the researchers, has not been investigated before, into a new unexplored
emerging economy context that is considered crucial for the theoretical and practical
significance of the theory (Agarwal et al., 2016;Christensen et al., 2018;Guo et al., 2020;
Lin et al., 2020;Liu et al., 2020;Magerakis, 2022). Besides, Dubai is increasingly becoming
a global role model for many emerging economies through its sincere endeavors to maintain
a welcoming and friendly business context (The World Bank, 2020). Thus, it becomes more
important to investigate its context and provide insights to the concerned.
3.2 Sample
The target population is PSF operating in Dubai, counting (10,871) firms. According to
Grawe et al. (2009), restricting the population targeted to a single business sector enhances
the research's internal validity. To avoid selection bias, we adopted VonNordenflycht’s
(2010) taxonomy of PSFs: classic PSFs, technology developers, neo-PSFs and professional
campuses.
The sampling frame was retrieved from an open-access governmental platform
(dubaipulse.gov.ae), which records all registered PSFs in Dubai. Probability simple random
sampling technique was employed to meet the representativeness requirement, which would,
IJIS
in turn, support the generalizability of findings, making it possible to extract inferences from
the sample about the population to answer the research question (Sekaran and Bougie, 2016).
Targeting (384) complete responses, as per Cochran's formula at a 95% confidence interval,
with an expected response rate of 20%, a total of 2000 cases were randomly selected using
their corresponding serial number in the sampling frame. A total of 491 responses were
received, marking a response rate of 24.55%.
This research collects data from top executives/managers in the selected firms as the unit
of observation. This choice of observation is essential due to two main reasons. First, this
research aims at understanding the impact of DMC on organizational RStDI, where these
capabilities reside at the senior management level; second, CEOs and senior managers are
better informed about the firm's capabilities and its operations, and their statement is more
reliable and valid than those provided by lower-level management and can be as valid and
reliable as multiple informants (Weerawardena et al., 2020;Zahra and Covin, 1993).
3.3 Instrument and measures
The research instrument (available in Appendix 7) used prevalidated scales to measure the
research variables on a six-point Likert scale (e.g. 1 –strongly disagree to 6 –strongly
agree). Six points are better than a five-point scale to measure opinions and attitudes,
producing better reliability and validity (Chomeya, 2010;Nunnally, 1978).
Figure 2. Study’s conceptual model
International
Journal of
Innovation
Science
Using Davidsson and Honig's (2003) five-item scale, MHC was measured through tacit
and explicit knowledge. MSC was measured via two dimensions (MSC from relations with
government and community leaders and MSC from relations with top managers at other
firms) via Acquaah's (2007) nine-item scale. MC was measured through two dimensions
(COOP and COTH) using Dewald and Bowen's (2010) scale of six items.
RStDI variables (defiant resistant and adaptive) measures were adapted from Osiyevskyy
and Dewald (2015,2018), who developed the scale to measure RStDI in the brokerage
industry. Thus, a minor change in the wording was performed to meet the PSF industry with
the help of a panel of four academic experts. Then, the scale was subjected to a pretest by 12
individual raters (experts, business managers and peers) (Nevo, 1985) before it was deployed
for pilot testing. MD's four-item measure was adopted from Hambrick and Finkelstein
(1987).
3.4 Procedures
A random sample of (2,000) cases was retrieved from the sampling frame based on their
corresponding serial number in the sampling frame. Random numbers were generated by an
online true random number generator tool (https://www.random.org/). The sampling frame
provided details of the firms (e.g. name, trade license number, activity type and status) along
with the firm's contact details.
An email/message briefly outlining the research purpose, clarifying the participants' roles
and assuring anonymity and confidentiality was communicated with the sample firm's senior
management through the identified communication channel (e-mail, LinkedIn, social media
and direct mobile numbers) or as otherwise requested by the contacts.
First, a sample of 400 cases was contacted for a pilot study, which lasted for eight weeks.
We received 102 responses, marking a response rate of 25.5%. Responses were retrieved
from the online questionnaire platform via an Excel sheet. Data were analyzed using the IBM
package (SPSS and Amos). A reliability test of Cronbach's alpha was applied, and all
variables revealed a value greater than 0.7, indicating an excellent reliability level. The
researchers conducted an exploratory factor analysis (EFA) to confirm the scales' reliability
and fit for analysis. No amendments were made to the instrument. Later, the study continued
distributing the questionnaire among the rest of the selected cases from the sampling frame
1,600, and it took an additional 14 weeks to accumulate the total number of 491 responses,
marking a 24.55% response rate. The final study’s data was analyzed using SPSS V.26 and
AMOS V.23.
4. Analyses and results
4.1 Descriptive statistics and correlations
The study's sample demographics are availablein Appendix 8.
Table 1 represents the means, standard deviations and correlations among all research
variables examined. There is no evidence of range restriction in the data set, as standard deviation
(SD) for all variables (except human capital (HC) [5]) represents an accepted spread of the
responses around the mean. Most research study variables are found to be significantly correlated.
4.2 Reliability and validity of constructs
Scale reliability was assessed through internal consistency measures of the scales using
Cronbach’s coefficient alpha (α) and EFA. As shown in Table 2, all αvalues exceeded the
recommended threshold value of 0.7 (Pallant, 2007). As this research uses a single data
collection tool, with self-report data on both dependent and independent variables from the
same source, we tested statistically for common method bias through Harman’s one-factor
IJIS
test (Podsakoff et al., 2003). Harman's one-factor test result showed no such single factor
emerged and the first factor accounted for 15.79% of the 71.04% explained variance, which
is way below the threshold of 50%. In addition, EFA results supported the previous findings
of scale reliability, with the Kaiser–Meyer–Olkin measure of sampling adequacy value of
0.814, much greater than the recommended value of 0.5 (Field, 2018), supporting a pattern of
correlations in the data. Bartlett's test of sphericity was statistically significant at the (p<
0.000) level, indicating clusters of items are correlated. Commonalities exceeded the
threshold of 0.5 (Field, 2018). Hence, all the scales used in this study were proven reliable
due to the good internalconsistency among their items.
In addition, confirmatory factor nalysis (CFA) was used using AMOS graphics. As shown in
Figure 3, all the standardized estimates (factor loadings) exceeded the required minimum of 0.50
(Hair et al.,2014), showing that all the measured variables significantly represent the constructs.
Table 1. Descriptive statistics and correlations
Variables (1) HC (2) SCa (3) SCb (4) COOP (5) COTH (6) MD (7) DR (8) Adaptive
Mean 16.2732 3.3757 4.1139 3.8818 3.3787 4.1065 3.0783 3.6524
SD 11.88875 1.41220 1.07887 0.77403 1.27061 0.90533 1.41490 0.51737
1 1 0.163** 0.076 0.052 −0.075 0.077 −0.031 0.124**
2 1 0.347** 0.106* 0.057 0.277** 0.226** 0.141
3 1 0.191** 0.010 0.101* −0.022 0.288**
4 1 0.120** 0.240** −0.010 0.362**
5 1 0.035 0.135** 0.092
6 1 0.256** 0.307**
7 1 −0.057
8 1
Notes: **Correlation is significant at the 0.01 level (two-tailed); *Correlation is significant at the 0.05 level
(two-tailed); HC = managerial human capital; SCa = managerial social capital from government and
community leaders; SCb = managerial social capital from managers in other business firms; COOP =
opportunity cognitive perception; COTH = threat cognitive perception; MD = managerial discretion; DR =
defiant resistant
Source: Authors’own creation retrieved from AMOS
Table 2. Reliability of constructs, KMO and Bartlett’s test of sphericity
Scale α
SCa Managerial social capital from government and community leaders 0.908
SCb Managerial social capital from managers in other business firms 0.869
COOP Opportunity cognitive perception 0.783
COTH Threat cognitive perception 0.920
MD Managerial discretion 0.904
DR Defiant resistant 0.902
Adaptive Adaptive 0.850
KMO Kaiser–Meyer–Olkin 0.814
/ Bartlett’s test of sphericity P< 0.000
Source: Authors’own creation
International
Journal of
Innovation
Science
Figure 3. Measurement model
IJIS
The most cited model fit assessed the overall measurement model fit. Those indices are
minimum discrepancy (CMIN/df), goodness of fit index (GFI), adjusted goodness of fit index
(AGFI), normed fit index, Tucker–Lewis index, comparative fit index, root mean square residual
approximation and p-value (Awang, 2012). As shown in Table 3, all the fitness indices are within
the acceptable range of values except for the GFI and the AGFI, which almost achieved the cutoff
value and were considered accepted as the other stringent model fit indices were met.
4.3 Hypotheses testing using SEM
Correlational and regression analysis was conducted to understand the effect of DMC
(MHC, MSC and COOP and COTH) on RStDI. With respect to correlational analysis and
based on Table 1, results show that each of the MHC, MSC from relations with top managers
at other business firms (SCb) and managerial cognitive perceptions of opportunity (COOP) is
correlated with adaptive RStDI (adaptive). In contrast, MSC from relations with government
and community leaders (SCa) and managerial cognitive perceptions of threat (COTH) are
correlated with defiant resistant RStDI (DR).
Moreover, the results of regression analysis, based on the path model which was
developed based on the imputed variables from the measurement model using AMOS, as it
appears in Figure 4, show that each of the MHC, MSC from relations with top managers at
other business firms (SCb), and managerial cognitive perceptions of opportunity (COOP) is
positively related to adaptive RStDI (adaptive) with values (β= 0.004, t-values = 2.253, p=
0.024), (β= 0.104, t-values = 4.885, p< 0.001), (β= 0.205, t-values = 7.283, p< 0.001),
respectively, managerial cognitive perceptions of threat (COTH) is positively related to
defiant resistant RStDI (DR) (β= 0.134, t-values = 2.721, p= 0.007), whereas MSC from
relations with government and community leaders (SCa) was not significantly related with
adaptive RStDI (adaptive) as hypothesized (β= 0.005, t-values = 0.327, p= 0.744).
However, we found it positively related to defiant resistant RStDI [6] (DR) (β= 0.269,
t-values = 5.683, p< 0.001). Thus, based on the above results, we find support for accepting
H1 and H3 of this study and partial acceptance of H2.
4.3.1 Test of moderation effects. In addition to the linear aspects of the model, the
moderating effects (H4) of MD were tested through regression analysis with interaction
terms, using the SPSS software package to estimate the interactions and AMOS to produce
the moderated path analysis, as shown in Figure 5.
Interaction terms were calculated using standardized scores to reduce the potential multi-
collinearity problems among the main and interaction variables (Collier, 2020). As shown in
Table 3. Measurement model fit indices
Name of index Results Comments
CMIN/DF 2.477 The required level is achieved
CFI 0.943 The required level is achieved
NFI 0.909 The required level is achieved
TLI 0.934 The required level is achieved
GFI 0.89 The required level is almost achieved
AGFI 0.862 The required level is almost achieved
SRMR 0.052 The required level is achieved
RMSEA 0.055 The required level is achieved
PClose >0.05 The required level is achieved
Source: Authors’own creation
International
Journal of
Innovation
Science
Table 4, the interaction model for the moderating effect was insignificant. The interaction
terms were also insignificant. Therefore, MD did not moderate the relationship between
DMC (MHC, social capital and cognitive perceptions of opportunity and threat) and RStDI.
In other words, rejecting H4.
Table 5 summarizes the study results.
5. Discussion and implications
The central assumption of this study is that EF can respond adaptively to DI using their top
executives’dynamic capabilities (DMC), in contrast to the common assumption of their
failure in the face of disruption. This study provides the needed extension to the previous
literature, which has not empirically modeled the role of DMC in predicting organizational
behavior such as RStDI. It additionally provides exciting insights into the role of MD as an
essential moderator to the model of the upper echelonstheory.
The previous section showed that DMC underpinnings (MHC, MSC and MC) are not
identical in their effects on organizational behavior. Although it has been long theorized that
the three DMC underpinnings are essential and significant in supporting organizational
coping with shifting environments (Helfat and Martin, 2015;Mostafizet al., 2019;Peteraf
and Reed, 2007;Salvato, 2009), each capability should be considered at a finer level to
understand its impact.
In terms of MHC, the findings of this investigation have underscored its role in endorsing
organizational tendency to adapt to turbulent environments marked with disruption. MHC has
been discussed as a critical success factor of innovations (Koroglu and Eceral, 2015;Lynsk ey,
2004;Prajogo and Oke, 2016), enabler of sensing, seizing and exploiting opportunities
(Davidsson and Honig, 2003) and thus improving the capability of coping with change
(Carpenter et al.,2001). Managers with relatively high prior experience are gifted with the
knowledge and skills required to integrate and exploit external knowledge (Kato, 2019)and
Figure 4. Path model
IJIS
work experience plays a role in decreasing the volume of unknowns and assumptions, giving
managers more pertinent and accurate information about their surroundings (Cassar, 2014),
thus, enhance the capacity to adapt with change. Although other researchers foundcontrasting
results (Brinckmann et al.,2019;Marvel and Lumpkin, 2007;Parker, 2006), where higher
levels of MHC have a role in limiting strategic flexibility, nevertheless this investigation came
to emphasize the pivotal role of MHC in adapting to change.
In terms of MSC, which has been cited as an essential factor in improving the capacity to
seize opportunities and redeploy resources, facilitating managers' environmental scanning
through their networks of relations (Helfat and Martin, 2016), allowing better detection of
new opportunities and asset reconfiguration (Helfat and Martin, 2015); and cited as a channel
for valuable information on the environmental change insights, strategic and organizational
Figure 5. Moderated path model
International
Journal of
Innovation
Science
substitutes and decision-making methods (Geletkanycz and Boyd, 2011), still, the findings of
our investigation revealed exciting distinction in the MSC concept. Although MSC from
relations with top managers at other firms had a significant impact on adaptive RStDI, the
other managerial ties (MSC from relations with government and community leaders) had no
impact on adaptive RStDI. This finding further motivated us to explore the non-hypothesized
relations (i.e. MSC from relations with government and community leaders on defiant
resistant RStDI), where we found a significant positive impact. Supported by the findings of
Hauser et al. (2007), who found that the social capital concept is distinguished into several
dimensions that are independent of each other, a potential explanation can be that MSC from
relations with top managers at other firms provides the managers with resources, diversified
and valuable information and up to date knowledge, which are used to alleviate
vulnerabilities, ignite the organizational ambidexterity and improve their abilities to respond
appropriately to change (Cao et al., 2010;Dyer and Nobeoka, 2000;Park and Luo, 2001;
Peng and Luo, 2000). It offers managers more diversified information to aid in a more
efficient scan of the external environment.
Table 4. Moderation test results
The relation Estimate SE CR pStatus
DRi << MDi 0.5 0.385 1.298 0.194 Not significant
Adaptivei << MDi 0.225 0.131 1.719 0.086 Not significant
DRi << ZMD × HC −0.701 0.376 −1.862 0.063 No moderation
Adaptivei << ZMD × HC −0.017 0.128 −0.131 0.896 No moderation
Adaptivei << ZMD × SCa 0.393 0.125 3.133 0.201 No moderation
Adaptivei << ZMD × COTH −0.095 0.105 −0.902 0.367 No moderation
DRi << ZMD × COTH −0.175 0.309 −0.567 0.571 No moderation
Adaptivei << ZMD × COOP −0.069 0.145 −0.48 0.631 No moderation
DRi << ZMD × COOP 0.012 0.426 0.028 0.978 No moderation
Adaptivei << ZMD × SCb −0.226 0.14 −1.615 0.106 No moderation
DRi << ZMD × SCb 0.081 0.413 0.197 0.844 No moderation
DRi << ZMD × SCa 0.174 0.369 0.472 0.637 No moderation
Source: Authors’own creation
Table 5. Results’summary
Hypothesis Result
H1 Higher levels of managerial human capital positively impact adaptive
response strategies to DI
Supported
H2 Higher levels of managerial social capital positively impact adaptive RStDI Partially supported
H3a Managerial cognitive perception of threats positively impacts resistant
adaptive response strategies to DI
Supported
H3b Managerial cognitive perception of opportunities positively impacts
adaptive response strategies to DI
Supported
H4 Managerial discretion has a significant moderating impact on the
relationship between DMC and response strategies to DI
Not supported
Source: Authors’own creation
IJIS
On the other hand, MSC from relations with government and community leaders might
play a critical role in resisting change by granting managers the power to control resources,
people and structures (Adner and Helfat, 2003), in addition to the easy access to exclusive
updates on new and pending regulations and policies that might impact the organizational
operations, industry and social arrangements (Acquaah, 2007), providing them with an early
opportunity to lobby against any disruption or try to affect the policymaking process in their
favor (Granovetter, 1985) and make proactive efforts to adjust legislation to protect existing
business models (Dewald and Bowen, 2010).
Regarding MC, we found that managerial cognitive perception of threats has significantly
and positively impacted defiant resistant RStDI. In contrast, managerial cognitive perception
of opportunities has significantly and positively impacted adaptive RStDI, confirming
similar findings in the literature. This can be related to the proposition that threat perception
drives risk-averse decisions and actions (Dewald and Bowen, 2010) and makes managers
less keen to change with the new rules of the game and more willing to invest in their current
business to enforce it in the face of DI (Charitou and Markides, 2003). These managers may
need to be made aware of the ramifications of disruptive technologies as their belief systems
are firmly ingrained and heavily influenced by their prior experiences with technologies and
markets (Vecchiato, 2017). On the other hand, managers with a cognitive perception of
opportunities are more open to exploring new possibilities within the new disruptive
business model (Dewald and Bowen, 2010). These managers perceive the rewarding results
of adopting the new disruptive business model, such as being an early adopter, even if it
might necessitate significant resource restructuring (Lavie, 2006). These findings correspond
with entrepreneurship research, stating that opportunity identification and recognition trigger
strategic change. However, they contradict the findings of other researchers who identified
contrasting results (Dutton and Jackson, 1987;Gilbert, 2005).
In relation to MD as a moderator, this research provides an exciting and important insight
into the UET theoretical framework, which has proposed an essential role for MD as a
moderator (Hambrick and Finkelstein, 1987). The findings of the investigation found no
significant moderating effect of MD in terms of Dubai’s business environment degree of
regulation, business capital intensity, availability of differentiable products and rate of demand
growth (Hambrick and Finkelstein, 1987) on the direct relation between DMC and RStDI. This
finding is in contrast with the findings of other researchers who found support for the role of MD
(Sirén et al.,2018;Wang et al.,2021;Amir et al.,2022) in similar relationships.
The nonsignificance of MD in our study might be attributed to Dubai's serious endeavors
to maintain a benevolent business environment as part of its bigger competitive approach to
economic development. Dubai has crafted innovative policies, regulations and strategies to
enable the economic transformation of the country by leveraging the national competitive
advantage through becoming more knowledge-based and innovative, supporting value-
creation sectors and providing a fully supported business environment for organizations to
operate (Federal_Competitiviness_and_Statistics_Authority, 2020). It seems that these
innovative initiatives are reflecting the freedom allowed for managers to make decisions and
take actions, thus eroding the effect of high and low MD on the proposed model, as the
country is maintaining flexible regulative structures and elastic policies that allow freedom to
decision-makers while making their mind. In addition, firm size has been cited as an essential
factor to MD (Dalton et al., 1999), where smaller firms, which form the majority of this
investigation’s sample, representing the population of Dubai’sfirms, enhance the internal
MD and dilute the environmental MD effect (Cortes and Kiss, 2023;Finkelstein and
Hambrick, 1996). Managers of small firms are less constrained by environmental structures,
systems and forces (Dalton et al., 1999); as such, they better adapt to their ecological
International
Journal of
Innovation
Science
structures and institutions, thus facilitating the reflection of their traits and characteristics on
their organizations without the moderatingimpact of the environmental MD.
These findings have a few theoretical and practical vital implications for researchers,
academics, practitioners and policymakers.
Theoretically, this study contributes to the DI literature by providing an integrative
research model for enabling organizational adaptive response strategies from within firms,
other than external drivers like technology and market characteristics. This investigation is
the first attempt in the literature to empirically investigate the impact of the three
underpinnings of DMC on RStDI. Besides, this study contributes well to the social capital
theory by providing finer empirical evidence on the role ofsocial capital in enabling strategic
change (i.e. adaptive RStDI). In this regard, this study refutes the assumptions of previous
studies, which viewed social capital as a social liability that inhibits firm strategic change
initiatives (Alguezaui and Filieri, 2010), or the other view which tackles social capital at the
aggregate level as a pure catalyst for strategic change (Ambrosini and Altintas, 2019;Helfat
and Martin, 2015;Martin and Bachrach, 2018).
In addition, this study investigates the moderating effect of the MD on the direct relation
between DMC and RStDI. This relationship has not been measured previously in the
literature on DMC and DI. It also contributes to the literature on MD that needs more
statistical quantification of the concept. Although the research revealed no moderation effect,
it contributes to the academic endeavors in measuring this phenomenon in a new unexplored
context and a new industry.
In addition to the scholarly contributions, there are also important practical and
managerial implications. Generally, this study provides managers with insights to capitalize
on their DMC and achieve an adaptive response strategy to DI, a critical success factor for
organizations' sustained competitive advantage and survival (Teece, 2016). First, managers
and practitioners are now equipped with empirical evidence that MHC contributes to
organizational flexibility and adaptability to change, refuting some previous literature
findings on MHC as a strategic change counterforce. Second, itis essential to understand that
MSC dimensions have different outcomes. Thus, it becomescrucial for managers to leverage
the required social capability to attain the competitive advantage that endorses strategic
flexibility to adopt DI, which is the ties with other market players. This finding can also be
necessary for hiring teams, especially MNEs, who might need to consider attracting local
executives enjoying well-established relations within the local market rather than attracting
foreign executives if they wish for more strategic flexibility. Third, managers can understand
now that cognitive perception might be unconsciously biased while making strategic
decisions, which they should strive to avoid. At the same time, they assess a phenomenon,
considering that threat-rigidity might paralyze the efforts to respond strategically adequately
(Shimizu, 2007).
Furthermore, the research findings provide good insights for hiring teams within
organizations, as they indicate how managers would behave in the light of their DMC, thus
supporting the ability to hire executives accordingly. Besides, the insights created by this
research assist top executives in predicting other competitor organizations' moves in the face
of disruption based on their management teams' profiles. Finally, the insights this
investigation provides on the erosion of the MD effect can also be attractive to policymakers.
As discussed earlier throughout this section, policymakers may conclude that pursuing well-
thought, flexible and innovative policies can aid in achieving a business-friendly
environment, which provides managers and executives with enough freedom and latitude of
action necessary to manage their businesses according to their views, with minimum
regulatory and policy constraints to achieve sustained success.
IJIS
6. Conclusion
This study has investigated the impact of DMC underpinnings (MHC, MSC and MC) on
organizational behavior in terms of RStDI under the moderating effect of MD. Using the
UET framework, the empirical findings of this investigation, based on data collected from a
random sample of (491) senior managers in PSF operating in Dubai, supported the
propositions of the UET. MHC, MSC and MC directly impacted RStDI (adaptive and
resistant), as we hypothesized. However, MD, an essential moderator to the model of UET,
did not exert any significant moderation effect.
Despite this study's significant and valuable contributions, it has limitations. First, this
study used a mono method, a cross-sectional survey,as a data collection tool, which was used
and analyzed to test research hypotheses; this limitation imposes a limitation on the identified
significant effects that should be further investigated. Future research can address this
limitation by considering longitudinal studies. Second, MD has been subjectively evaluated
and assessed by senior management; other studies can use other objective indicators as
proxies of industry MD. Third, the study sample was restricted to PSFs operating in Dubai,
UAE, thus limiting the generalizability of the findings to the examined context. The future
research venue would be conducting replication studies in other contexts and industries.
In addition to the previously mentioned future research suggested to overcome some of
the study's mentioned limitations, future studies can dedicate more focus to investigating
each of the dynamic capabilities' underpinnings (MHC, MSC and MC) at a finer level (e.g.
the social capital construct which has played a mixed role at the dimension level) and
investigate its impact on organizational behavior. This will further enrich the theory of DMC
with deeper insights into its role as a catalyst for change. Another opportunity for future
research arises from deeper investigations of the adaptive RStDI (explorative and
exploitative) to understand the precise effect of each DMC underpinning each of these two
responses. Another avenueof future research is to focus more on managers who can perceive
both opportunity and threat simultaneously and demonstrate a level of cognitive resilience
that can lead to competitive advantage (55% of the respondents of this investigation). Hence,
although seemingly opposite to opportunity, the threat can also lead to strategic decision-
making related to business model change. Future research can use this concept to understand
better the role of cognitive resilience in similar or similar relations.
Notes
1. Appendix 4 provides a range of definitions of the human capital concept.
2. Appendix 5 provides a range of definitions of the concept of social capital.
3. Appendix 6 provides additional definitions of cognition.
4. MD can be found in the literature at different levels (individual, organizational and
environmental). This study focuses on the task environment concerned with the industry-level
managerial discretion.
5. Human capital is considered a formative measure (Diamantopoulos and Siguaw, 2006). It consists
of several indicators (experience measured in years, education measured in educational level
coded in values from 1 to 6 and training measured in the number of sessions in the past three
years). These indicators are objective and not expected to correlate, so they were not included in
the EFA and CFA analyses. The MHC index was inserted as an observed variable directly in the
path model.
6. This relationship was not hypothesized during the hypotheses development. It is an insight
retrieved during data analysis.
International
Journal of
Innovation
Science
References
Acquaah, M. (2007), “Managerial social capital, strategic orientation, and organizational performance
in an emerging economy”,Strategic Management Journal, Vol. 28 No. 12, pp. 1235-1255.
Adler, P. and Kwon, S. (2002), “Social capital: prospects for a new concept”,The Academy of
Management Review, Vol. 27 No. 1, pp. 17-40.
Adner, R. and Helfat, C. (2003),“Corporate effects and dynamic managerial capabilities”,Strategic
Management Journal, Vol. 24 No. 10, pp. 1011-1025.
Adner, R. and Snow, D. (2010), “Old technology responses to new technology threats: demand heterogeneity
and technology retreats”,Industrial and Corporate Change, Vol. 19 No. 5, pp. 1655-1675.
Agarwal, R. and Helfat, C. (2009), “Strategic renewal of organizations”,Organization Science, Vol. 20
No. 2, pp. 281-293.
Agarwal, N., Grottke, M., Mishra, S. and Brem, A. (2016), “A systematic literature review of constraint-
based innovations: state of the art and future perspectives”,IEEE Transactions on Engineering
Management, Vol. 64 No. 1, pp. 3-15.
Alguezaui, S. and Filieri, R. (2010), “Investigating the role of social capital in innovation: sparse versus
dense network”,Journal of Knowledge Management, Vol. 14 No. 6, pp. 891-909.
Ambrosini, V. and Altintas, G. (2019), “Dynamic managerial capabilities”,Oxford Research
Encyclopedia of Business and Management, Oxford University Press, Oxford, doi: 10.1093/
acrefore/9780190224851.013.20).
Amir, M., Siddique, M. and Ali, K. (2022), “Responsible leadership and business sustainability:
exploring the role of corporate social responsibility and managerial discretion”,Business and
Society Review, Vol. 127 No. 3, pp. 701-724.
Ansari, S. and Krop, P. (2012), “Incumbent performance in the face ofa radical innovation: towards a
framework for incumbent challenger dynamics”,Research Policy, Vol. 41 No. 8, pp. 1357-1374.
Augier, M. and Teece, D. (2009), “Dynamic capabilities and the role of managers in business strategy
and economic performance”,Organization Science, Vol. 20 No. 2, pp. 410-421.
Awang, Z. (2012), A Handbook on SEM: Structural Equation Modelling, Universiti Teknologi MARA,
Kelantan.
Becker, G. (1964), Human Capital, Columbia University Press, : New York, NY.
Benner, M. and Tripsas, M. (2012), “The influence of prior industry affiliation on framing in nascent industries:
the evolution of digital cameras”,Strategic Management Journal, Vol. 33 No. 3, pp. 277-302.
Bourdieu, P. (1985), “The social space and the genesis of groups”,Theory and Society, Vol. 14 No. 6,
pp. 723-744.
Boyd, B.K. and Gove, S. (2006), “Managerial constraint: the intersection between organizational task
environment and discretion”,Research Methodology in Strategy and Management, Vol. 3 No. 1,
pp. 57-95.
Brinckmann, J., Villanueva, J., Grichnik, D. and Singh, L. (2019), “Sources of strategic flexibility in
new ventures: an analysis of the role of resource leveraging practices”,Strategic
Entrepreneurship Journal, Vol. 13 No. 2, pp. 154-178.
Cao, Q., Simsek, Z. and Zhang, H. (2010), “Modelling the joint impact of the CEO and the TMTon
organizational ambidexterity”,Journal of Management Studies, Vol. 47 No. 7, pp. 1272-1296.
Carpenter, M.,Sanders, W. and Gregersen, H. (2001), “Bundling human capital with organizational
context: the impact of international assignment experience on multinational firm performance
and CEO pay”,Academy of Management Journal, Vol. 44 No. 3, pp. 493-511.
Cassar, G. (2014), “Industry and startup experience on entrepreneur forecast performance in new firms”,
Journal of Business Venturing, Vol. 29 No. 1, pp. 137-151.
Charitou, C. and Markides, C. (2003), “Responsesto disruptive strategic innovation”,MIT Sloan
Management Review, Vol. 44 No. 2, pp. 55-63.
IJIS
Chesbrough, H. (2010), “Business model innovation: opportunities and barriers”,Long Range
Planning, Vol. 43 Nos 2/3, pp. 354-363.
Chomeya, R. (2010), “Qualityof psychology test between Likert scale 5 and 6 points”,Journal of
Social Sciences, Vol. 6 No. 3, pp. 399-403.
Christensen, C.M. (1997), The Innovator's Dilemma: When New Technologies Cause Great Firms to
Fail, Harvard Business Review Press, Boston, MA.
Christensen, C.M. (2000), The Innovator’s Dilemma. When New Technologies Cause Great Firms to
Fail, Harvard Business School Press, Boston, MA.
Christensen, C.M. (2006), “The ongoing process of building a theory of disruption”,Journal of Product
Innovation Management, Vol. 23 No. 1, pp. 39-55.
Christensen, C.M. and Bower, J.L. (1996), “Customer power, strategic investment, and the failure of
leading firms”,Strategic Management Journal, Vol. 17 No. 3, pp. 197-218.
Christensen, C.M. and Raynor, M. (2015), “What is disruptive innovation?”Harvard Business Review,
Vol. 93 No. 12, pp. 44-53.
Christensen, C., Raynor, M. and Mcdonald, R. (2015), “The big idea: what is disruptive innovation?”
Harvard Business Review, Vol. 93 No. 12, pp. 44-53.
Christensen, C.M., Alton, R., Rising, C. and Waldeck, A. (2011), “The new M&A playbook”,Harvard
Business, Vol. 89 No. 1, pp. 48-57.
Christensen, C.M.,McDonald, R., Altman, E.J. and Palmer, J.E. (2018), “Disruptive innovation: an
intellectual history and directions for future research”,Journal of Management Studies, Vol. 55
No. 7, doi: 10.1111/joms.12349.
Ciampi, F., Demi, S., Magrini, A., Marzi, G. and Papa, A. (2021), “Exploring the impact of big data
analytics capabilities on business modelinnovation: the mediating role of entrepreneurial
orientation”,Journal of Business Research, Vol. 123, pp. 1-13.
Collier, J. (2020), Applied Structural EquationModeling Using AMOS: Basic toAdvanced Techniques,
Routledge, New York, NY.
Cortes, A.F. and Kiss, A.N. (2023), “Is managerial discretion high in small firms? A theoretical
framework”,Small Bus Econ, Vol. 60 No. 1, pp. 157-172.
Crossland, C. and Hambrick, D.C. (2011), “Differences in managerial discretion across countries: how
nation-level institutions affect the degree to which CEOs matter”,Strategic Management
Journal, Vol. 32 No. 8, pp. 797-819.
Cyert, R. and March, J. (1963), A Behavioral Theory of the Firm, Prentice-Hall, Englewood Cliffs.
Dalton, D., Daily, C., Johnson, J. and Ellstrand, A. (1999), “Number of directors and financial
performance: a meta-analysis”,Academy of Management Journal, Vol. 42 No. 6, pp. 674-686.
Danneels, E. (2004), “Disruptive technology reconsidered: a critiqueand research agenda”,Journal of
Product Innovation Management, Vol. 21 No. 4, pp. 246-258.
Davidsson, P. andHonig, B. (2003), “The role of social and human capital among nascent
entrepreneurs”,Journal of Business Venturing, Vol. 18 No. 3, pp. 301-331.
Debrulle, J., Maes, J. and Sels, L. (2014), “Start-up absorptive capacity: does the owner's human and
social capital matter?”International Small Business Journal: Researching Entrepreneurship,
Vol. 32 No. 7, pp. 777-801.
Dewald, J. and Bowen,F. (2010), “Storm clouds and silver linings: responding to disruptive innovations
through cognitive resilience”,Entrepreneurship Theory and Practice, Vol. 34 No. 1,
pp. 197-218.
Dutton, J.E. and Jackson, S.E. (1987), “Categorizing strategic issues: links to organizational action”,
The Academy of Management Review, Vol. 12 No. 1, pp. 76-90.
Dyer, J. and Nobeoka, K. (2000), “Creating and managing ahigh-performance knowledge-sharing
network: the Toyota case”,Strategic Management Journal, Vol. 21 No.3, pp. 345-367.
International
Journal of
Innovation
Science
Fayad, Y. and El Ebrashi, R. (2022), “Social capital and corporate entrepreneurship: therole of
absorptive capacity in emerging markets”,Management Decision, Vol. 60 No. 9.
Federal_Competitiviness_and_Statistics_Authority (2020), “Competitiveness story”, available at: https://
fcsa.gov.ae/en-us/Pages/Competitiveness/Competitiveness-Story.aspx (accessed 3 February 2020).
Field, A. (2018), Discovering Statistics Using IBM SPSS Statistics, 4th ed. Sage, London.
Finkelstein, S. and Hambrick, D. (1996), Strategic Leadership: Top Executives and Their Effects on
Organizations, West Publishing Company, St. Paul, Minneapolis.
Finkelstein, S., Hambrick, D.C. and Cannella, A.A. (2009), Strategic Leadership: Theory and Research
on Executives, Top Management Teams, and Boards, Oxford University Press, New York, NY.
FTSE_Rusell (2022), FTSE Equity Country Classification Annual Announcement, FTSE International
Limited, Canary Wharf, September.
Geletkanycz, M. and Boyd, B. (2011), “CEO outside directorships and firm performance: a
reconciliation of agency and embeddedness views”,Academy of Management Journal, Vol. 54
No. 2, pp. 335-352.
Gilbert, C.G. (2005), “Unbundling the structure of inertia: resource versus routine rigidity”,Academy of
Management Journal, Vol. 48 No. 5, pp. 741-763.
Granovetter, M. (1985), “Economic action and social structure: the problem of embeddedness”,
American Journal of Sociology, Vol. 91 No. 3, pp. 481-510.
Grawe, S.J., Chen, H.and Daugherty, P.J. (2009), “The relationship between strategic orientation,
service innovation, and performance”,International Journal of Physical Distribution and
Logistics Management, Vol. 39 No. 4, pp. 282-300.
Guo, D., Huang, H., Jiang, K. and Xu, C. (2020),“Disruptive innovation and R&D ownership structures
of the firm”, available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3628181
(accessed 27 November 2020).
Hair, J.F., Black,W.C.,Babin, B.J. and Anderson, R.E. (2014), Multivariate Data Analysis, 7th ed.
Pearson Education, Essex.
Hambrick, D. (2007), “Upper echelons theory: an update”,Academy of Management Review, Vol. 32
No. 2, pp. 334-343.
Hambrick, D. and Finkelstein, S. (1987), “Managerial discretion: a bridge between polar views of
organizational outcomes”,Research in Organizational Behavior, Vol. 9 No. 1, pp. 369-406.
Hambrick, D. and Mason,P. (1984), “Upper echelons: the organization as a reflection of its top
managers”,The Academy of Management Review, Vol. 9 No. 2, pp. 193-206.
Hannan, M.T. and Freeman,J. (1977), “The population ecology of organizations”,American Journal of
Sociology, Vol. 82 No. 5, pp. 929-964.
Hartman, J. and Parilla, J. (2022), “Microbusinesses flourished during the pandemic. Now, we must tap
into their full potential”, available at: www.brookings.edu/blog/the-avenue/2022/01/04/
microbusinesses-flourished-during-the-pandemic-now-we-must-tap-into-their-full-potential/
(accessed 18 September 2022).
Hauser, C., Tappeiner, G. and Walde, J. (2007), “The learning region: the impact of social capital and
weak ties on innovation”,Regional Studies, Vol. 41 No. 1, pp. 75-88.
Helfat, C. and Martin, J. (2015), “Dynamic managerial capabilities: review and assessment of
managerial impact on strategic change”,Journal of Management, Vol. 41No. 5, pp. 1281-1312.
Helfat,C.andMartin,J.(2016),“Dynamic managerial capabilities: a perspective on the relationship between
managers, creativity, and innovation in organizations”, in Shalley, C., Hitt, M. and Zhou, J. (Eds), The
Oxford Handbook of Creativity, Innovation, and Entrepreneurship, Oxford University Press, Oxford.
Henderson, R.M. and Clark, K.B. (1990), “Architectural innovation: the reconfiguration of existing
product technologies and the failure of established firms”,Administrative Science Quarterly,
Vol. 35 No. 1, pp. 9-30.
IJIS
Heubeck, T. and Meckl, R. (2022), “More capable, more innovative? An empirical inquiry into the
effects of dynamic managerial capabilitieson digital firms' innovativeness”,European Journal of
Innovation Management, Vol. 25 No. 6, pp. 892-915.
Holzmayer, F. and Schmidt, S. (2020), “Dynamic managerial capabilities, firm resources, and related
business diversification –evidence from the English premier league”,Journal of Business
Research, Vol. 117 No. 1, pp. 132-143.
Iyiola, B. and Trafford, R. (2024),“Measuring industry managerial discretion:a comparative study in
the UK”,Journal of Accounting and Organizational Change, Vol. 20 No. 2, pp. 228-247.
Jaworski, B. and Patel, A. (2020), “Reinventing professional service firms: the migration to a client-
facing, talent-on-demand platform”,AMS Review, Vol. 10 Nos 1/2, pp. 135-144.
Kato, M. (2019), “Founders’human capital and external knowledge sourcing: exploring the absorptive
capacity of start-up firms”,Economics of Innovation and New Technology, Vol. 29 No. 2, doi:
10.1080/10438599.2019.1598670.
Kato, M. and Honjo, Y. (2015), “Entrepreneurial human capital and the survival of new firms in high-
and low-tech sectors”,Journal of Evolutionary Economics, Vol. 25 No. 5, pp. 925-957.
Khanna, P., Jones, C. and Boivie, S. (2014), “Director human capital, information processing demands,
and board effectiveness”,Journal of Management, Vol. 40 No.2, pp. 557-585.
King, A. and Baatartogtokh, B. (2015), “How useful is the theory of disruptive innovation?”MIT Sloan
Management Review, Vol. 57 No. 1, pp. 77-90.
Koroglu, B. and Eceral, T. (2015), “Human capital and innovation capacity of firms in the defense and
aviation industry in Ankara”,Procedia - Social and Behavioral Sciences, Vol. 195 No. 1,
pp. 1583-1592.
Lavie, D. (2006), “Capability reconfiguration: an analysis of incumbent responses to technological
change”,Academy of Management Review, Vol. 31 No. 1, pp. 153-174.
Liao, Z. and Zhang, M. (2020), “The influence of responsible leadership on environmental innovation
and environmental performance: the moderating role of managerial discretion”,Corporate
Social Responsibility and Environmental Management, Vol. 27 No. 5, doi: 10.1002/csr.1942.
Lin, R., Li, F. and Olawoyin, A. (2020), “CEO overconfidence and firm internationalization: the
moderating role of experience and managerial discretion”,Nankai Business Review
International, Vol. 11 No. 4, pp. 597-616.
Liu, M. and Ji, D. (2022), “An overview of the literature on upper echelons”,Accounting Perspectives,
Vol. 21 No. 2, pp. 331-386.
Liu, W., Liu, R., Chen, H.and Mboga, J. (2020), “Perspectives on disruptive technology and innovation:
exploring conflicts, characteristics in emerging economies”,International Journal of Conflict
Management, Vol. 31 No. 3, pp. 313-331.
Lynskey, M. (2004), “Determinants of innovative activity in Japanese technology-based start-up firms”,
International Small Business Journal: Researching Entrepreneurship, Vol. 22 No. 2, pp. 159-196.
McDonald, M.L. and Westphal, J.D. (2003), “Getting by with the advice of their friends: CEOs' advice
networks and firms' strategic responses to poor performance”,Administrative Science Quarterly,
Vol. 48 No. 1, pp. 1-32.
Magerakis, E. (2022), “The importance of managerial discretion on managerial ability–firm cash
holding nexus”,Management Decision, Vol. 60 No. 12, pp. 3275-3303.
Mannor, M.J., Wowak, A.J., Bartkus, V.O. and Gomez-Mejia, L.R. (2016), “Heavy lies the crown? How
job anxiety affects top executive decision-making in gain and loss contexts”,Strategic
Management Journal, Vol. 37 No. 9, pp. 1968-1989.
March, J. and Simon, H. (1958), Organizations, Wiley, New York, NY.
Markides, C. (2006), “Disruptive innovation: in need of better theory”,Journal of Product Innovation
Management, Vol. 23 No. 1, pp. 19-25.
International
Journal of
Innovation
Science
Martin, J.A. (2011), “Dynamic managerial capabilities and the multibusiness team: the role of episodic
teams in executive leadership groups”,Organization Science, Vol. 22 No. 1, pp. 118-140.
Martin, J. and Bachrach, D. (2018), “A relational perspective of the micro-foundations of dynamic
managerial capabilities and transactive memory systems”,Industrial Marketing Management,
Vol. 74 No. 1, pp. 27-38.
Martınez-Vergara, S. and Valls-Pasola, J. (2020), “Clarifying the disruptive innovation puzzle: a critical review”,
European Journal of Innovation Management, Vol. 24 No. 3, doi: 10.1108/EJIM-07-2019-019.
Marvel, M.R. and Lumpkin, G. (2007), “Technology entrepreneurs’human capital and its effects on
innovation radicalness”,Entrepreneurship Theory and Practice, Vol. 31 No. 6, pp. 807-828.
Marx, M., Gans, J.S. and Hsu, D.H. (2014), “Dynamic commercialization strategies for disruptive
technologies: evidence from the speech recognition industry”,Management Science, Vol. 60
No. 12, pp. 3103-3123.
Mintzberg, H. (1978), “Patterns in strategy formation”,Management Science, Vol. 24 No. 9, pp. 934-948.
Mostafiz, M., Sambasivan, M. and Goh, S. (2019), “Impacts of dynamic managerial capability and
international opportunity identification on firm performance”,Multinational Business Review,
Vol. 27 No. 4, pp. 339-363.
Nagy, D.,Schuessler, J. and Dubinsky, A. (2016), “Defining and identifying disruptive innovations”,
Industrial Marketing Management, Vol. 57, pp. 119-126.
Nevo, B. (1985), “Face validity revisited”,Journal of Educational Measurement,Vol.22No.4,pp.287-293.
Nunnally, J.C. (1978), Psychometric Theory, McGraw-Hill Book, New York, NY.
O’Reilly, C.A., III and Tushman, M.L. (2016), Lead and Disrupt: How to Solve the Innovator’s
Dilemma, Stanford University Press, Stanford.
Osiyevskyy, O. and Dewald, J. (2015), “Explorative versus exploitative business model change: the
cognitive antecedents of firm-level responses to disruptive innovation”,Strategic
Entrepreneurship Journal, Vol. 9 No. 1, pp. 58-78.
Osiyevskyy, O. and Dewald, J. (2018), “The pressure cooker: when crisis stimulates explorative
business model change intentions”,Long Range Planning, Vol. 51 No. 4, pp. 540-560.
Paap, J. and Katz, R. (2004), “Anticipating disruptive innovation”,Research-Technology Management,
Vol. 47 No. 5, pp. 13-22.
Pallant, J. (2007), SPSS Survival Manual: A Step-by-Step Guide to Data Analysis Using SPSS Version
15, McGraw Hill, Nova Iorque.
Park, S. and Luo, Y. (2001), “Guanxi and organizational dynamics: organizational networking in
Chinese firms”,Strategic Management Journal, Vol. 22 No. 5, pp.455-477.
Parker, S.C. (2006), “Entrepreneurship, self-employment, and the labour market”, in Al, M.C. (Ed.),
Handbook of Entrepreneurship, Oxford University Press, Oxford.
Peng, M. and Luo, Y. (2000), “Managerial ties and firm performance in a transition economy: the nature
of a micro-macro link”,Academy of Management Journal, Vol. 43 No. 3, pp.486-501.
Peteraf, M. and Reed, R. (2007), “Change, managerial discretion, and internal alignment are under
regulatory constraints and change”,Strategic Management Journal, Vol. 28 No. 11,
pp. 1089-1112.
Petzold, N., Landinez, L. and Baaken, T. (2019), “Disruptive innovation from a process view: a systematic
literature review”,Creativity and Innovation Management, Vol. 28 No. 2, pp. 157-174.
Pfeffer, J.and Salancik, G.R. (1978), The External Control of Organizations: A Resource Dependence
Perspective, Harperand Row, NewYork, NY.
Plöckinger, M.,Aschauer, E.,Hiebl, M.R.W. and Rohatschek, R. (2016), “The influence of individual
executives on corporate financial reporting: a review and outlook from the perspective of upper
echelons theory”,Journal of Accounting Literature, Vol. 37 No. 1, pp. 55-75.
IJIS
Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. andPodsakoff, N.P. (2003), “Common method biases in
behavioral research: a critical review of the literature and recommended remedies”,Journal of
Applied Psychology, Vol. 88 No. 5, p. 879.
Prahalad, C.K. and Bettis, R.A. (1982), “The dominant logic: a new linkage between diversity and
performance”,Strategic Management Journal, Vol. 7 No.6, pp. 485-501.
Prajogo, D. and Oke, A. (2016), “Human capital, service innovation advantage, and business performance”,
International Journal of Operations and Production Management, Vol. 36 No. 9, pp. 974-994.
Prashantham, S. and Dhanaraj, C. (2010), “The dynamic influence of social capital on the international
growth of new ventures”,Journal of Management Studies, Vol. 47 No. 6, pp. 967-994.
Pryor, C., Holmes, R.M., Webb, J.W. and Liguori, E.W. (2019), “Top executive goal orientations’
effects on environmental scanning and performance: differences between founders and
nonfounders”,Journal of Management, Vol. 45 No. 5, pp. 1958-1986.
Raffaelli, R. (2019), “Technology re-emergence: evidence from Swiss mechanical watchmaking, 1970-
2008”,Administrative Science Quarterly, Vol. 64 No. 3, pp. 576-618.
Rosenbloom, R.S. (2000), “Leadership, capabilities, and technological change: the transformation of
NCR in the electronic era”,Strategic Management Journal, Vol. 21 Nos 10/11, pp. 1083-1103.
Roy, R. and Cohen, S. (2015), “Disruption in the US machine tool industry: the role of in-house users
and pre-disruption component experience in firm response”,Research Policy, Vol. 44 No. 8,
pp. 1555-1565.
Sadiq, F., Hussain, T. and Naseem, A. (2020), “Managers' disruptive innovation activities: the construct,
measurement, and validity”,Management Decision, Vol. 59 No. 2, pp. 153-174.
Salvato, C. (2009), “Capabilities unveiled: the role of ordinary activities in the evolution of product
development processes”,Organization Science, Vol. 20 No. 2, pp. 384-409.
Sandström, C., Magnusson, M. and Jörnmark, J. (2009), “Exploring factors influencing incumbents'
response to disruptive innovation”,Creativity and Innovation Management, Vol. 18 No. 1, pp. 8-15.
Schmidt, G.M. and Druehl, C.T. (2008), “When is a disruptive innovation disruptive?”Journal of
Product Innovation Management, Vol. 25 No. 4, pp. 347-369.
Sekaran, U. and Bougie, R. (2016), Research Methods for Business: A Skill Building Approach,John
Wiley and Sons, NJ.
Shen, W. and Cho, T.S. (2005), “Exploring involuntaryexecutive turnover through a managerial
discretion framework”,Academy of Management Review, Vol. 30 No. 4, pp. 843-854.
Shimizu, K. (2007), “Prospect theory, behavioral theory, and the threat-rigidity thesis: combinative
effects on organizational decisions to divest formerly acquired units”,Academy of Management
Journal, Vol. 50 No. 6, pp. 1495-1514.
Si, S. and Chen, H. (2020), “A literature review of disruptive innovation: whatit is, how it works and
where it goes”,Journal of Engineering and Technology Management, Vol. 56 No. 1, doi:
10.1016/j.jengtecman.2020.101568.
Sirén, C., Patel, P., Örtqvist, D. and Wincent, J. (2018), “CEO burnout, managerial discretion, and firm
performance: the role of CEO locus of control, structural power, and organizational factors”,
Long Range Planning, Vol. 51 No. 6, pp. 953-971.
Skjolsvik, T., Pemer, F. and Lowendahl, B.R.(2017), “Strategic management of professional service
firms: reviewing ABS journals and identifying key research themes”,Journal of Professions and
Organization, Vol. 4 No. 2,pp. 203-239.
Teece, D. (2016), “Dynamic capabilities and entrepreneurial management in large organizations: toward
a theory of the (entrepreneurial) firm”,European Economic Review, Vol. 86 No. 1, pp. 202-216.
Tellis, G.J. (2006), “Disruptive technology or visionary leadership?”Journal of Product Innovation
Management, Vol. 23 No. 1, pp. 34-38.
The World Bank (2020), Ease of Doing Business Report, The World Bank Group, Washington, DC.
International
Journal of
Innovation
Science
Tripsas, M. and Gavetti, G. (2000), “Capabilities, cognition, and inertia: evidence from digital
imaging”,Strategic Management Journal, Vol. 21 Nos 10/11, pp. 1147-1161.
Tushman, M. and Anderson, P. (1986), “Technological discontinuities and organizational
environments”,Administrative Science Quarterly, Vol. 31 No. 3, pp. 439-465.
Ucbasaran, D., Westhead, P. and Wright, M. (2008), “Opportunity identification and pursuit: does an
entrepreneur’s human capital matter?”Small Business Economics, Vol. 30 No. 2, pp. 153-173.
Van de Ven, A.H. (2017), “The innovation journey: you can't control it, but you can learn to maneuver
it”,Innovation, Vol. 19 No. 1, pp. 39-42.
Vecchiato, R. (2017), “Disruptive innovation, managerial cognition, and technology competition
outcomes”,Technological Forecasting and Social Change, Vol. 116 No. 1, pp. 116-128.
VonNordenflycht, A. (2010), “What is a professional service firm? Toward a theory and taxonomy of
knowledge-intensive firms”,Academy of Management Review, Vol. 35 No.1, pp. 155-174.
Walsh, J.P. (1995), “Managerialand organizational cognition: notes from a trip down memory lane”,
Organization Science, Vol. 6 No. 3, pp. 280-321.
Wang, L., Jiang, W. and Ma, X. (2021), “The effect of CEO entrepreneurial orientation on firm strategic
change: the moderating roles of managerial discretion”,Journal of Engineering and Technology
Management, Vol. 59, p. 101616.
Wangrow, D.B., Schepker, D.J. and Barker, V.L. (2014), “Managerial discretion”,Journal of
Management, Vol. 41 No. 1, pp. 99-135.
Weerawardena, S.S., Knight, G., Mort, G.S. and Liesch, P.W. (2020), “The learning subsystem interplay
in service innovation in born global service firm internationalization”,Industrial Marketing
Management, Vol. 89 No. 1, pp. 181-195.
Wright, P., Coff, R. and Moliterno, T. (2014), “Strategic human capital: crossing the great divide”,
Journal of Management, Vol. 40 No. 2, pp. 353-370.
Yu, D. and Hang, C.C. (2010), “Areflective review of disruptive innovation theory”,International
Journal of Management Reviews, Vol. 12 No. 4, pp. 435-452.
Zahra, S. and Covin, J. (1993), “Business strategy, technology policy, and firm performance”,Strategic
Management Journal, Vol. 14 No. 6, pp. 451-478.
Zahra, S. and George, G. (2002), “Absorptive capacity: a review,reconceptualization,and extension”,
The Academy of Management Review, Vol. 27 No. 2, pp. 185-203.
Zhanglan, Y., Awino, Z.B., Yabs, J. and Wainaina, G. (2021), “Top management team characteristics
and managerial discretion on sustainable competitive advantage: an empirical investigation”,
Academic Journal of Business and Management, Vol. 3 No. 7, pp. 50-57.
Further reading
Cooper, D. and Schindler, P. (2008), Business Research Methods International Edition, McGraw Hill
Publications, New York, NY.
Creswell, J.W. and Creswell, J.D. (2018), Research Design Qualitative, Quantitative and Mixed
Methods Approaches, 5th ed. Sage Publications Ltd, London.
Galbraith, J. (1973), Designing Complex Organizations, Addison-Wesley, Reading, MA.
Haleblian, J. and Finkelstein, S. (1993), “Top management team size, CEO dominance, and firm
performance: the moderating roles of environmental turbulence and discretion”,Academy of
Management Journal, Vol. 36 No. 4, pp. 844-863.
Malhotra, N. (2007), Marketing Research, 5th ed. Pearson, NJ.
IJIS
Appendix 1
Table A1. Recent research this study has reviewed, synthesized, challenged and built on
Previous research Topic and purpose This research
Iyiola and Trafford
(2024)
A comparative study to establish
whether the measurement of managerial
discretion is constant between the two
similar societal corporate frameworks
of the UK- and the USA-listed markets
Complementing insights about MD
in new context and industry (PSF);
providing empirical findings on
subjective measurement of MD
indicators
Cortes and Kiss
(2023)
Build a theoretical framework that
explains how some key firm
characteristics shape executives’
perceptions of strategic choice
availability (latitude of actions) and
strategy implementation ability
(latitude of objectives), thus providing a
more nuanced perspective on the
relationship between firm size and
managerial discretion
Responding to the call of
incorporating perceptions of
managerial discretion in research
exploring opportunity recognition,
entrepreneurial orientation and
strategy formation and
implementation in small firms
Amir et al. (2022) The study constructs a comprehensive
framework on responsible leadership,
corporate social responsibility and
managerial discretion to provide the
guideline for business sustainability.
Managerial discretion was measured at
firm level
Complement the findings of prev.
research by providing insights in
small firms context and service
industry –as being called for;
providing additional insights on the
role of MD as a moderator in upper
echelons theory
Magerakis (2022) This paper examines the role of
managerial discretion in the relation
between managerial ability on the level
of corporate cash. With managerial
discretion being measured by firm-level
indicators (past research and
development over sales, employees to
sales, change in total revenue, selling
…etc.)
Responding to the call of
investigating the manager’s
education in terms of impact on
organizational behavior; expand
the investigation in new context to
provide a comparative analysis
within different institutional
contexts
Wang et al. (2021) Examines the relationship between
CEO entrepreneurial orientation and the
magnitude of strategic change initiated
by the firm being moderated by
managerial discretion as a measure four
industry indicators (e.g. environmental
munificence; market concentration …
etc.)
Challenge the finding that the MD
facilitated the impact of CEO
entrepreneurial orientation and the
magnitude of strategic change, as
we revealed a similar finding with
no role of MD as a moderator
Zhanglan et al. (2021) The study assesses the influence of top
management teams (TMT)
characteristics and managerial
discretion on sustainable competitive
advantage of Chinese Multinational
Corporations in Kenya. With
managerial discretion measured at the
organizational level via indicators like
The prev. study focused on
measuring the TMT influence,
which is one of the three distinct
levels of analysis according to
UET: the board of directors, the
CEO and TMT. Our study on the
other hand focuses on CEOs. TMT
influence has been criticized with
(continued)
International
Journal of
Innovation
Science
Table A1. Continued
Previous research Topic and purpose This research
(managerial discretion given by your
mother company to me/my TMT
characteristics meets the dynamic
environment; Managerial discretion
allows managers to serve their own
interests rather than company’s
objectives; …etc.)
bias, as some members within
these TMTs exerts more power on
others, as many TMTs “often
consist of semiautonomous
‘barons’having little to do with
each other and hardly constituting a
team”(Hambrick, 2007, p. 336)
Liao and Zhang
(2020)
The study investigates the relationships
between responsible leadership,
managerial discretion, environmental
innovation and firm-environmental-
performance. Managerial discretion
was measured at firm level
Challenge the finding of positive
moderating effect of (MD); and
provide an insight on the
measurement of MD at the industry
level, rather than firm level;
expanding the sample to cover
other industry and context
Lin et al. (2020) The study investigates the impact of
CEO’overconfidence ‘as a
psychological factor’on the
international expansion of companies
under the moderating role of CEO’s
overseas experience, CEO duality and
ownership as individual managerial
discretion measures
Our study adds to the prev. one by
investigating other psychological
& cognitive aspects of managers.
We provide more insights on the
role of MHC, MCS and MC on the
organizational behavior;
responding to the call of other
context investigation; challenge
their finding on MD
Ambrosini and
Altintas (2019)
A review on the role of DMC in
refreshing and transforming the
resource base of the firm so that it
maintains and develops its competitive
advantage and performance
Adopt the view of DMC role in
achieving competitive advantage
through an empirical articulation of
their role in adapting with strategic
change
Mostafizet al. (2019) The study investigates Impacts of
dynamic managerial capability and
international opportunity identification
on firm performance
Respond to the call of more
investigation to bridge the gap of
empirical evidence on the effect of
DMC on strategic change
initiatives
Kato (2019) The study highlights the importance of
founders’human capital on firms’
absorptive capacity for explaining the
external knowledge sourcing in start-up
firms, Japan
Adopt and extend the supported
views of the prev. study to propose
that MHC is a determinant of
adaptive RStDI, because of
external knowledge sourcing and
improved absorbative capacity
Siren et al. (2018) Examines the influence of CEO burnout
on firm performance and the
moderating roles of the individual
(CEO locus of control), structural
power (CEO duality and CEO tenure)
and organizational characteristics (size,
age and resource availability) related to
managerial discretion (firm + individual
levels)
Further validated the assumption of
the importance of “cognitive
endeavours”where CEOs actively
engage in seeking, developing and
exploiting strategic opportunities
by orchestrating, combining and
leveraging a diverse range of
resources; respond to a call of
measuring MD at industry level
(continued)
IJIS
Table A1. Continued
Previous research Topic and purpose This research
Vecchiato (2017) Explore why incumbent firms fail to
identify new markets in the face of
disruptive technologies. Explore how
managerial cognition influences the
market choices of organizations and
thereby affects their long-term
performance in the face of disruptive
technologies
Respond to the call of crossing
research on disruptive innovation
with research on managerial
cognition since we still know “…
very little about the impact of
managers’mental models on the
strategic responses of established
firms to disruptive technologies”
(p. 117)
Plöckinger et al.
(2016)
Investigates the influence of individual
executives on corporate financial
reporting and use upper echelons theory
as an organizing framework
Respond to the call of additional
research in the field to clarify the
influence of unexamined upper
echelon characteristics (other than
demographics) and important
moderator variables (MD in this
study)
Helfat and Martin
(2015)
DMC concept is discrete in its
remarkable emphasis on the managers’
ability to influence strategic change;
DMC has a central role in
implementing strategic actions
Adopted the concept of DMC and
used it in an empirical manner for
testing
Osiyevskyy and
Dewald (2015)
Develop a typology of incumbent
adaptations to emerging disruptive
business model innovations, based on
two generic strategies: explorative
adoption of a disruptive business model
and exploitative strengthening of the
existing business model
Adopt the developed typologies of
response strategies to DI that has
been derived in a brokerage
industry and test it in a PSF context
Source: Authors’own creation
International
Journal of
Innovation
Science
Appendix 2
Table A2. Factors affecting established firms’nonresponse to disruption
Factors Internal/External Research
Resource allocation Internal Christensen (1997),Christensen and
Bower (1996),Christensen and Raynor
(2015),Yu and Hang (2010)
Organizational Inertia Internal Paap and Katz (2004),Gilbert (2005),
Ansari and Krop (2012),Roy and
Cohen (2015)
Visionary leadership Internal Tellis (2006)
Quick rate of DI growth External Markides (2006)
Short term nondisruptive nature of DI External Schmidt and Druehl (2008)
Human resources, structure and culture Internal Yu and Hang (2010),King and
Baatartogtokh (2015)
Marketing competence Internal Vecchiato (2017),Christensen (2000)
Source: Authors’own creation
IJIS
Appendix 3
Table A3. Response strategies to DI
Research Response strategy to DI
Charitou and Markides (2003) Response One: Focus on and Invest in Traditional Business (P. 58)
Response Two: Ignore the Innovation –It’s Not Your Business
(P 59)
Response Three: Attack Back –Disrupt the Disruption (P. 60)
Response Four: Adopt the Innovation by Playing Both Games at
Once (P. 60)
Response Five: Embrace the innovation completely and Scale it Up
(P. 62)
Lavie (2006) Capability reconfiguration to eliminate the capabilities gap:
Capability substitution
Capability evolution; and
Capability transformation
Markides (2006) Adopt the new business model under certain situations
Invest in a neighboring market
Take the current business model to international level
Agarwal and Helfat (2009) Strategic renewal
Adner and Snow (2010) Exploiting the old technologies in a niche or a new market
Marx et al (2014) Partnering with or licensing a new entrant
Christensen et al. (2011)
Sandström et al. (2009)
Mergers and acquisitions
Christensen and Raynor (2015) Separate organizational unit to focus on disruption
Osiyevskyy and Dewald (2015) The defiant resistance
The pure exploration
The pure exploitation
O’Reilly and Tushman (2016) Organizational ambidexterity
Petzold et al. (2019) Co-opt new entrants with DI
Raffaelli (2019) Redefining the boundaries of the market they compete in
(re-emergence)
Martınez-Vergara and
Valls-Pasola (2020)
EFs’RStDI should resort to identifying the context of inside
market, assess the identified impact of DI, strive to maintain and
improve its control on market share to mitigate the impacts of DI
and establishing an internal specialized R&D unit
Source: Authors’own creation
International
Journal of
Innovation
Science
Appendix 4
Table A4. Reviewed human capital definitions
Research Definitions
Becker (1964)inAdner and
Helfat (2003, P1020)
“Learned skills that require some investment in education,
training, or learning more generally”
Weatherly (2003) Defined HC in terms of a collection of elements: knowledge,
innovation, and creativity, in addition to energy, that individuals
use it in their work
O'Sullivan and Sheffrin (2003) The skills and knowledge stock personified in workers to enhance
their ability to perform tasks and produce economic value
Frank and Bemanke (2007) A combination of elements such as education, knowledge,
training, experience, intellect, energy, work conducts, honesty, and
ingenuity which impact the workers’products' value
Rodriguez and Loomis (2007) The knowledge, competencies, skills and qualities of people which
enable their abilities of creating personal, social and economic
well-being
Stevens (2010) The thing that is brought to the organization by employees and
workers and helps it in achieving its goals and objectives
Poteliene and
Tamasauskiene (2014)
The knowledge and skills owned and deployed by people, or as the
set of abilities and skills employed by workers
Prajogo and Oke (2016, p. 975) “Comprising the level of creativity, knowledge, and idea
development skills residing within and utilized by individuals in
organizations”
Kato (2019) HC as being composed of their prior knowledge and accumulated
skills
Davidsson and Honig (2003)
Mostafizet al. (2019)
Defined HC “based on educational qualification, experience, and
training that facilitates managers to reconfigure organizational
resources and competencies”
Source: Authors’own creation
IJIS
Appendix 5
Table A5. Reviewed social capital definitions
Research Definitions
Coleman (1988, p. S98) “A variety of entities with two elements in common: They all
consist of some aspect of social structures, and they facilitate
certain action of actors whether persons or corporate actors within
the structure”
Baker (1990, p. 619) “A resource that actors derive from specific social structures and
then use to pursue their interests; it is created by changes in the
relationship among actors”
Schiff (1992, p. 161) “The set of elements of the social structure that affects relations
among people and are inputs or arguments of the production and/
or utility function”
Burt (1992, p. 9) “Friends, colleagues, and more general contacts through whom
you receive opportunities to use your financial and human capital”
Portes (1998, p. 6) “The ability of actors to secure benefits by virtue of membership
in social networks or other social structures”
Adler and Kwon (2002,P.23) “The goodwill available to individuals or groups. Its source lies in
the structure and content of the actor's social relations. Its effects
flow from the information, influence, and solidarity it makes
available to the actor”
Acquaah (2007, P. 1238) “The sum of resources, actual or virtual, that accrue to an
individual or an organization as a result of the development of
personal and social networking relationships”
Mostafizet al. (2019) “The relationship with business partners, alliances, government
officials and other union leaders, which facilitates them to have
better managerial control, influence and power”
Source: Authors’own creation
International
Journal of
Innovation
Science
Appendix 6
Table A6. Reviewed cognition definitions
Research Definition
Prahalad and Bettis (1982, p. 490) Dominant general management logic is defined as “the way in
which managers conceptualize the business and make critical
resource allocation decisions-be it in technologies, product
development, distribution, advertising, or in human resource
management”
Adner and Helfat (2003, p. 1021) “Managerial beliefs and mental models that serve as a basis for
decision making”
Laamanen and Wallin (2009, p. 954) “Forward-looking form of intelligence that is premised on an
actor’s belief about the linkage between the choice of actions and
the subsequent impact of those actions on outcomes”
Helfat and Peteraf (2015, p. 835) “The capacity of an individual manager to perform one or more of
the mental activities that comprise cognition …activities, such as
those involving attention, perception, and problem solving”
Source: Authors’own creation
IJIS
Appendix 7
Table A7. The research instrument
Human capital
1 Overall experience (yrs.)
2 Managerial experience (yrs.)
3 Entrepreneurial experience (yrs.)
4 Training sessions during the last three years
5 Highest academic qualification
Social capital
Rate the personal relationship level you have as a manager with:
6 Leaders in the federal government
7 Leaders in the local government
8Officials in regulatory and supporting organizations
9Officials in industrial and investment institutions
10 Local leaders and/or their representatives
11 Religious leaders
12 Managers at buyer firms (customer firms)
13 Managers at supplier firms
14 Managers at competitor firms
Cognition
a. Opportunity cognitive perception
Express your agreement to the following:
15 Disruptive business models are a new opportunity for our business
16 Customers are more interested in innovative service delivery
17 Customers are more interested in taking a role in service delivery
b. Threat cognitive perception
Express your agreement to the following:
18 Disruptive business models are a threat to the existing industry
19 In the next five years, our profits will shrink due to the success of the disruptive business models
20 In the coming years, disruptive business models will dominate the market
Response to disruptive innovation
a. Explorative adoption to the disruptive business model
In response to the introduction of a new disruptive business model in the market, we will consider (or) already
considered:
21 Changing the structure of our services to adopt the new model
22 Offering new services to our clients
23 Introducing discounted fees to meet market demand
24 Abandoning our existing ways of doing business
b. Exploitative adoption to the disruptive business model
In response to the introduction of a new disruptive business model in the market, we will consider (or) already
considered:
25 Adding new value-adding services to our existing set of services
26 Building expertise in providing additional services that are complementary to ours
27 Increasing customer value, without compromising our conventional services
c. Defiant resistant
In response to the introduction of a new disruptive business model in the market…
28 We will lobby (or) already lobbied the authorities, regulatory bodies and industry bureaus to ensure that the
industry is protected from the disruption of any unexpected newcomers or new offerings
29 We will focus (or) already focused our efforts on our businesswithout any alterations
Managerial discretion
How do you evaluate your business environment in terms of?
30 Degree of regulation
31 Capital intensity
32 Availability of differentiable product and services
33 Demand growth
Source: As indicated in Section 3.3 (Instrument and Measures)
International
Journal of
Innovation
Science
Appendix 8
Corresponding author
Rana Bassam Madi-Odeh can be contacted at: ranaodeh1982@gmail.com
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
Or contact us for further details: permissions@emeraldinsight.com
Job Title
Job Title Senior
Manager
CEO Founder General
Manager
Manager Managing
Director
Managing
Partner
Other Managerial
Role
%7.84 14.11 7.68 4.98 22.2 9.96 5.39 27.84
Gender
Gender Female Male
%14.52 85.48
Age Category
Age Category 25<35 35< 45 45<55 55<65 +65
%24.9 36.51 25.93 10.3 2.36
Education Level
Education
Level
PhD MA BA Diploma Less than Diploma
% 5.39 51.45 33.4 6.02 3.74
Years of Experience
Years 0<5 5<10 10<15 15<20 20+
%4.4 35.3 39 17.2 4.1
Source: Authors own creation
Table A8. Study’s high-level model
IJIS
