Scalability of startups: the impact of entrepreneurial teams

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Vol.:(0123456789)
Journal of Global Entrepreneurship Research (2024) 14:15
https://doi.org/10.1007/s40497-024-00383-7
RESEARCH
Scalability ofstartups: theimpact ofentrepreneurial teams
FaezehHanifzadeh1· KambizTalebi1· VahidJafari‑Sadeghi2
Received: 11 April 2023 / Accepted: 27 April 2024
© Faculty of Entrepreneurship, University of Tehran 2024
Abstract
Scalability serves as a crucial tool in facilitating the growth and ensuring the survival of startups. The scalability of a startup
is influenced by various factors such as leadership, business structure, access to technology, culture, and entrepreneurial
teams, in which entrepreneurial teams play an important role. The impact of the entrepreneurial team on the scale of startups
is important because they provide the leadership, expertise, and strategic direction needed to navigate the challenges of scale
and take the startup to the next level. The impact of entrepreneurial teams can be categorized into two functional factors:
team diversity, encompassing age, gender, and functional background, and team processes, including team-level cognitive
comprehensiveness, team commitment, team size, and team integrity. A research instrument was administered to owners
and managers of 90 Iranian technological startups between April and July 2021. Sampling was conducted using a simple
random sampling method based on the accessible statistical population. The data collected was analyzed using path analysis
and SmartPLS3 software. The findings indicate that both diversity and team processes play vital roles in the scalability of a
startup. Moreover, team demographic characteristics and cognitive comprehensiveness were found to have the most signifi-
cant influence on startup scalability and team integrity, respectively. In light of this, policymakers are encouraged to foster a
collaborative and innovative environment for upcoming entrepreneurial teams to sustain the growth of startups. Furthermore,
managers should focus on creating a culture of trust and loyalty within entrepreneurial teams to strengthen team commitment.
Keywords Scalability· Team diversity· Team processes· Cognitive comprehensiveness· Commitment· Integrity
Introduction
Scalability refers to a firm's capacity to expand rapidly
without compromising its structure and available resources
(Simsek & Post, 2020). A scale-up is a company that has
successfully transformed its business model into a replica-
ble one, tailored its product to meet market demands, and
is confident that its small-scale business model can effec-
tively serve its customers even as it grows larger, remaining
responsive to their needs (DeSantola & Gulati, 2017). Rap-
idly expanding enterprises, commonly known as scale-ups,
play a crucial role in fostering a robust economy. Scale-
ups are acknowledged as sources of innovation, drivers of
industry rejuvenation (Hanifzadeh etal., 2023), and agents
that mitigate unemployment challenges during economic
downturns (Coutu, 2014a, 2014b). These attributes have
positioned scale-ups at the forefront of research interest in
recent years. While the body of literature on firm growth
and its determinants is relatively extensive, research on the
phenomenon of scale-ups is still in its nascent stages. Fun-
damental distinctions exist between simple growth and scal-
ing up, often leading to confusion. While growth typically
entails a linear relationship between resource allocation and
revenue generation, scaling up does not adhere to the same
progression. In scaling up, revenue growth surpasses cost
escalation at a more accelerated pace (Cowlinget al., 2017;
Cardon& Christopher, 2016).
The scalability of startups is paramount for their suc-
cess and survival. Among the various growth determinants,
establishing a scalable model is of crucial significance for
these firms. The characteristics and initiatives of a startup
exert a substantial influence on its scalability. If a startup
* Faezeh Hanifzadeh
f_hanifzadeh@ut.ac.ir
Kambiz Talebi
ktalebi@ut.ac.ir
Vahid Jafari-Sadeghi
V.jafari-sadeghi@aston.ac.uk
1 University ofTehran Faculty ofEntrepreneurship, Tehran,
Iran
2 Aston Business School, Birmingham, England

Journal of Global Entrepreneurship Research (2024) 14:15 15 Page 2 of 21
lacks scalability, the high costs associated with scaling up
and the extended time required for such expansion can lead
to its failure. A pivotal factor influencing a startup's suc-
cess in scaling up and achieving scalability is the role of
the entrepreneurial team and its impact on performance.
The majority of technology-based businesses are founded
by entrepreneurial teams, which serve as a potent driver of
business growth (Dautzenberg, 2012; Zhou, 2013). Extensive
evidence suggests that fast-growing firms are more likely to
be established by entrepreneurial teams compared to single
founders (Cooney, 2005), with these teams typically outper-
forming startups founded by individuals (Chowdhury, 2005).
DeSantola and Gulati (2017) underscore the significant role
that specialized teams play in facilitating the scale and scal-
ability of startups. Ramos and Pedroso (2022) identify five
primary factors that influence the scalability of businesses:
governance, resource allocation decisions, management of
strategic, tactical, and operational activities, nurturing human
capital, and validation of the business model. Each of these
elements offers a set of performance indicators that reflect
the scalability of businesses (Ramos & Pedroso, 2022). The
performance of entrepreneurial teams in startups is shaped by
various characteristics such as experience, knowledge, skills,
abilities, discernment, intelligence, learning capacity, goals,
motivations, and diversity in these attributes (Picken, 2018).
This study focuses on Iranian startups, operating in an
emerging market. Emerging markets often present opportu-
nities for burgeoning businesses. To thrive in such environ-
ments, startups must acquire the skills to navigate inefficient
bureaucratic systems and access scarce resources. A report
by the United Nations Industrial Development Organization
(UNIDO, 2021) highlights Iran's extensive scientific, tech-
nological, financial, and highly skilled human capital that
can bolster its startup ecosystem. Iranian businesses gener-
ally exhibit high growth potential. Companies and startups in
emerging markets share similar characteristics and encounter
comparable challenges. The findings of this research hold
high generalizability for startups in emerging markets due
to several key factors. Firstly, the study focuses on Iranian
startups operating in an emerging market setting. Emerging
markets, by their nature, often present unique opportuni-
ties for burgeoning businesses to thrive and grow. Startups
in these environments must possess the skills and capabili-
ties to navigate through inefficient bureaucratic systems and
access scarce resources, which are common challenges faced
by startups in various emerging markets worldwide. Moreo-
ver, the United Nations Industrial Development Organization
(UNIDO) report cited in the article underscores Iran's abun-
dant scientific, technological, financial, and highly skilled
human capital that can significantly contribute to bolstering
its startup ecosystem. This indicates that Iran, like many
other emerging markets, possesses the necessary resources
and potential for startups to flourish and achieve high growth
rates. Finally, startups in emerging markets share similar
characteristics and encounter comparable challenges. This
suggests that the findings and insights gained from studying
Iranian startups can be extrapolated and applied to startups
in other emerging markets facing similar circumstances.
Previous research has identified several theoretical gaps
in the literature. Firstly, there is a need to explore the impact
of background, education, and work experience on the scal-
ability of startup businesses (Zahra etal., 2006; Chen &
Wang, 2019; Johnson & Lee, 2020, and Smith etal., 2021).
Secondly, understanding the cognitive, behavioral, and team
characteristics required to transition a startup to a stage of
exponential growth or scale-up is crucial (Chowdhury, 2005;
Wang & Chen, 2019; Lee & Kim, 2020a, 2020b; Garcia
etal., 2021). Thirdly, the role of human capital in facilitat-
ing the transition of startups to the scale-up phase needs to
be examined (Wan etal., 2017; Kim & Lee, 2019 Nguyen
& Wong, 2020; Patel etal., 2021). Additionally, the cogni-
tive comprehensiveness of teams, their talents, and social
and human capital and their influence on the scalability of
startups require further investigation (Liu & Wang, 2019,
Journal of Management Studies, Call for Paper for a Spe-
cial Issue, 2020, Park & Choi, 2020, and Yang etal., 2021).
Lastly, the level of diversity in the background, education,
and experience of specialized teams necessary for the scal-
ability of startups remains an open question (Eisenhardt,
2013; Colombo & Grilli, 2005; Grilli etal., 2014; Chowd-
hury, 2005; Beckman, 2007, Zahra etal., 2006, Wang and
Zhang, 2019, Lee and Kim, 2020a,b, and Chen etal., 2021).
This research aims to address these gaps by examining
the impact of entrepreneurial teams on the scalability of
startups, paving the way for future investigations. The pri-
mary objective of this study is to explore how team diversity
and team processes influence the scalability of startups. To
this end, the study seeks to fill the aforementioned theoreti-
cal gap by focusing on the variables of diversity and team
dynamics within startup teams and their effects on scalabil-
ity. The article critically reviews the literature and argues
that diversity in team composition is as significant as team
processes, encompassing team commitment, size, and cogni-
tive processes, influencing decision-making criteria. Entre-
preneurial decision-making involves choices made when
presented with entrepreneurial opportunities, with strate-
gic implications setting it apart from managerial decisions
(Hanifzadeh, 2023). Specifically, this study examines the
impact of team diversity variables, including demographic
factors such as age, gender, and experience, as well as team
dynamic variables such as cognitive comprehensiveness,
commitment, size, and completeness, on startup scalability.
Therefore, the primary aim of this study is to investigate how
entrepreneurial teams, characterized by diversity and team
dynamics, influence the scalability of startup businesses
through the testing of five hypotheses.

Journal of Global Entrepreneurship Research (2024) 14:15 Page 3 of 21 15
Based on the theoretical gap identified in the literature,
the following research questions were formulated: RQ1:
Does the demographic composition of teams in terms of
age, gender, background, and team commitment have a posi-
tive impact on company scalability? RQ2: Does cognitive
comprehensiveness at the team level positively influence the
company's scalability? RQ3: Do team size and team integ-
rity contribute positively to company scalability?
The variables under study, such as demographic charac-
teristics and team size, are quantitative and therefore lend
themselves to quantification. As a result, a quantitative meth-
odology was employed to conduct this study. Data was col-
lected using a standard questionnaire utilizing a five-point
Likert scale. The statistical population for this research com-
prised the owners and managers of 90 Iranian technologi-
cal startups. Questionnaires were distributed and completed
between April and July 2021. Data analysis was performed
using path analysis and SmartPLS 3 software.
The results indicate that the entrepreneurial team, encom-
passing the five dimensions of the study, significantly
impacts the scalability of startup businesses. Specifically,
demographic characteristics were found to have the most
substantial influence, while team integrity had the least
impact on startup scalability. This study aims to bridge the
theoretical gap in the research and contribute to the scale-
up literature by exploring the relationships outlined. Prior
literature, such as DeSantola and Gulati (2017) and Van
Alstyne and Parker (2017), has highlighted the pivotal role
that teams can play in facilitating startup scale and scalabil-
ity, prompting further investigation into the impact of teams
on startup scalability.
By examining the variables of team diversity and team
dynamics within startup teams and their effects on scalabil-
ity, this study makes a theoretical contribution to the existing
literature. The subsequent sections of the article will delve
into the research background, outline the hypotheses, present
the theoretical framework, describe the research methodol-
ogy, report the results, and conclude with a discussion and
conclusion.
Review ofrelated literature
Scale‑up
The process through which small and medium-sized enter-
prises (SMEs) progress towards growth differs from that of
startups. In small entrepreneurial ventures, growth stems
from entrepreneurial passion, with entrepreneurial behav-
iors shaped by the understanding that growth in these busi-
nesses is driven by available resources and opportunities
(Shepherd and Wiklund, 2005). Conversely, startups are
established with the goal of achieving rapid, exponential
growth (Coviello, 2019; Harnish, 2019). In the context of
newly established businesses, the growth journey typically
unfolds across three stages: stand-up, startup, and scale-up
(Hellmann and Kavadias, 2016; World Economic Forum,
2014, Smith, 2021). The stand-up phase marks the readi-
ness of individuals to actualize their entrepreneurial ideas
by launching a new innovative venture (startup). The sub-
sequent startup phase involves refining the concept, execut-
ing the business model, and establishing a sustainable and
innovative organization. Founders concentrate on securing
necessary financial and human capital during this phase. The
final stage, scale-up, focuses on assessing the prerequisites
for expanding the company in terms of market penetration,
revenue generation, value addition, and workforce size. The
outcome of the scale-up phase is the exponential growth
of the venture (Coviello, 2019; World Economic Forum,
2014). In traditional small businesses, growth typically
leads to proportional cost increases relative to sales growth,
characterized as linear growth (Harnish, 2019). In contrast,
startups and technology-driven enterprises strive to maxi-
mize the utilization of their ideas, technologies, and capital
resources, aiming for exponential or explosive growth during
the startup phase (Harnish, 2019). A business remains clas-
sified as a startup until its business model stabilizes. Once
the business model achieves stability and demonstrates
scalable revenue, the startup transitions into the scale-up
stage. While startups are still exploring their potential and
refining their product and service offerings, scale-ups have
already established a market fit. Scale-ups are companies
that have transformed their business models into repeatable
models, aligned their product-market fit, and demonstrated
the efficiency of their economic models across various scales
(Coviello, 2019; DeSantola and Gulati, 2017). Startups that
focused on niche markets and specialized offerings experi-
enced more sustainable and manageable growth compared
to those targeting broader markets. A targeted approach to
scaling, aligned with specific customer needs, led to more
effective resource allocation and market penetration (Lialin
etal., 2023). Mula et, al. (2024) offer a framework for under-
standing how digital startups can navigate the complexities
of scaling their operations. This research identified four key
tensions faced by these firms and proposed that developing
"dynamic capabilities" - the ability to adapt, learn, and inno-
vate - is crucial for successfully navigating these challenges
(Mula et, al., 2024).
Recent research indicates that companies experiencing
exponential growth, commonly referred to as scale-ups, play
a significant role in job creation, productivity enhancement,
introduction of new products, and technological innovations
(Coutu, 2014a,b; Du and Temouri, 2015). However, stud-
ies suggest that only a small percentage of startups progress
towards scale-up and sustain their exponential growth trajec-
tory over time (Jansen and Roelofsen, 2018; Josefy etal.,

Journal of Global Entrepreneurship Research (2024) 14:15 15 Page 4 of 21
2015). Scale-up companies are defined as those achieving
a minimum twenty percent annual growth rate over the past
three years, starting with at least 10 employees at the begin-
ning of this period (OECD, 2007). Scale-ups can be viewed
as the growth phase within a business lifecycle. Endeavor
defines scale-ups as companies with over twenty percent
annual growth over the preceding three years. The transi-
tion phase commences when a startup defines and validates
its business model, signaling its move towards scaling. This
transitional phase between startups and scale-ups is recog-
nized as an integral part of the scaling process (Nadali, 2018).
Necessity andimportance ofScale‑up
There exists a significant distinction between growth and
scaling within a company. Scaling, in essence, represents
exponential growth that occurs post the startup phase, giving
rise to scale-ups. For a newly established company (startup)
to achieve effectiveness in its respective industry, it must
grow without accumulating excessive overhead. Simply put,
"growth" entails expanding within a specific timeframe,
while "scale" refers to the proportionality between dimen-
sions or the increased (or decreased) size, emphasizing size-
related criteria in exponential growth. Manifestations of
physical growth in a business include a larger customer base,
increased workforce, and expanded office spaces. The reper-
cussions of failing to impact the bottom line are notewor-
thy. A common pitfall ensnaring many small and medium-
sized enterprises is the necessity to engage in more business
activities, hire additional personnel, and raise capital, all
while maintaining or even decreasing profitability. During
the scaling-up phase, although the customer base expands,
revenue growth may only be incremental. Meanwhile, costs
tend to rise gradually or remain static. Consequently, scale-
ups do not undergo linear growth in any facet; rather, they
typically leverage systems that drive revenue growth expo-
nentially without a commensurate increase in costs (Duruflé,
Hellmann, and Wilson, 2017; Harnish, 2019).
Research indicates that twenty percent of American
startups and eleven percent of European startups progress
towards the scale-up stage (https:// www. crunc hbase. com/
organ izati on/ start up- report/ signa ls_ and_ news). The absence
of growth in startups often leads to their demise. During the
growth phase of a startup, this phenomenon can transpire
at an unforeseen pace, given that startups typically operate
in nascent sectors characterized by rapid transformations.
Startups are often distinguished by diverse products, tech-
nologies, and market uncertainties. The process of aligning
internal structures with startup growth is commonly termed
"scaling," colloquially known as "scale-up" (Hellmann
and Kavadias, 2016; DeSantola and Gulati, 2017). Recent
research by Mula, Zybura, and Hipp (2024) underlines the
importance of scale for startups, though their focus wasn't
directly on the benefits of scale itself. Their investigation
into digital startups transitioning to scale-ups highlights the
complex internal transformations these companies undergo.
This complexity underscores the significance of scale, as
achieving a larger market reach necessitates navigating intri-
cate operational changes and developing robust "dynamic
capabilities" to adapt, learn, and innovate as the business
grows. ([Mula, C., Zybura, N., & Hipp, T. , 2024).
Scalability ofstartups
The startup phase marks the initial stage of a company's
lifecycle, leading to the subsequent phase of scaling, where
the growth potential of the startup can transform it into a
high-growth company generating significant employment
and revenues (Jabłoński, 2016; Zakjo, 2017). A startup typi-
cally represents a small company with a five-year growth
trajectory, aiming to establish a scalable business model or
introduce innovative products/services. On the other hand,
a scale-up is characterized as a company that has defined its
product and market, demonstrating substantial adaptability
by adhering to relevant criteria. Consequently, a scale-up is
viewed as a growth-centric entity that has validated a scal-
able business model and aims to secure a market position
while attracting investments to access additional financial
resources. The primary hallmark of a scale-up company lies
in its emphasis on rapid growth across turnover, innovation,
and expansion into international markets, ultimately striving
to achieve a high growth rate (Jabłoński, 2016; Zakjo, 2017).
Scalability focuses on enhancing operational efficiency
through an increased number of components. Another dis-
tinguishing feature of a scale-up is the presence of evolving
computer networks. Scalability is occasionally defined as
"the ease of modifying the system or its components based
on the nature of the issue" (Perez, Mehta, and Maley, 2013).
A scalable system embodies three core attributes: Firstly,
it becomes adaptable to a broader range of applications,
enabling its utilization for various purposes. Secondly, the
system can accommodate a larger volume of data. Lastly,
the system is technically straightforward and operates with
reasonable efficiency (Nski, 2016). Rajagopal and Mahajan
(2024) investigated the factors enabling startup scalability,
emphasizing the critical role of technology and sustain-
able business practices. Their findings suggest that startups
leveraging technology effectively alongside implementing
sustainable practices can achieve a better chance of success-
fully scaling their operations. This implies that technology
empowers startups to streamline processes, reach wider mar-
kets, and potentially gain a competitive edge, while sustain-
able practices can contribute to positive brand perception,
resource efficiency, and potentially lower operational costs,
ultimately bolstering a startup's foundation for successful
scaling (Rajagopal and Mahajan, 2024).

Journal of Global Entrepreneurship Research (2024) 14:15 Page 5 of 21 15
Entrepreneurial teams
An entrepreneurial team comprises two or more individu-
als with significant financial stakes engaging in collabora-
tive efforts to develop a business. This collective endeavor
involves individuals working together to establish a business
and form an entrepreneurial team (Cooney, 2005; Shrader
and Siegel, 2007). Harper (2008) presents a comprehensive
view of entrepreneurship that encompasses both entrepre-
neurial teams and individuals. He suggests that team entre-
preneurship can be prioritized in cases of limited structural
uncertainty and strong interdependence of shared interests.
While entrepreneurial teams may lack experience initially,
they can swiftly acquire the requisite skills. As the size of
the enterprise grows, there is an increased demand for ele-
vated team skill levels, leading to fundamental changes in
management performance and organizational structure, pro-
foundly impacting the enterprise's nature. The administra-
tive structures of very small and very large enterprises differ
significantly, making them distinct from various perspectives
(Harper, 2008; Moray and Clarysse, 2004; DeSantola and
Gulati, 2017). Effective scale-up management and teams
can consistently drive a company's growth trajectory (Zajko,
2019). An internal factor influencing scale-up is the recruit-
ment and training of a substantial number of new employ-
ees while retaining competent staff members crucial for the
company's advancement (Zajko, 2019). Marmer etal. (2011)
conducted a study on 3200 newly established companies and
proposed a systematic approach for evaluating a company's
readiness to scale. They categorized each startup into five
interconnected dimensions: customer, product, team, busi-
ness model, and finance. The authors emphasize that estab-
lishing a high-growth company involves optimizing progress
while maintaining a balance among these five dimensions.
Startups typically maintain alignment with their customers,
with progress indicators linked to product, team, finance, and
business model development. In contrast, incompatible start-
ups exhibit discrepancies where one or more dimensions lag
behind the customer dimension. Early scaling, characterized
by exponential growth, becomes a significant indicator of
incompatibility when certain dimensions outpace customer-
centric development (Marmer etal., 2011). Gray, Howell,
and Sackett (2024) shed light on the complexities of entre-
preneurial team formation, highlighting the potential discon-
nect between lead entrepreneurs and potential co-founders.
Their research suggests that differences in construal level
(thinking style) and utilitarian motives (priorities) can lead
to miscommunication and hinder the formation of well-
rounded teams. The study reveals that lead entrepreneurs
often prioritize resource acquisition, while potential co-
founders may prioritize interpersonal compatibility. These
findings emphasize the importance of communication strat-
egies that bridge these divides. By acknowledging these
cognitive and motivational differences and fostering open
communication, lead entrepreneurs can build teams that pos-
sess both the necessary resources and strong interpersonal
dynamics, crucial for successful business growth(Gray etal.,
2024). According to Picken (2018), entrepreneurial inno-
vation progresses through four stages: startup, transition,
scaling, and exit, each stage presenting distinct challenges
for the founding team. The boundaries between these stages
are fluid, often overlapping. While a clear business concept
is crucial in the startup phase, laying the groundwork for a
scalable company becomes equally essential during the tran-
sition period. In the startup stage, entrepreneurs tackle chal-
lenges related to defining and validating business concepts,
encompassing market opportunities (such as fundamental
needs, target market, market size, and timeline), offerings
(products, services, or value propositions), business models
(resources, processes, economic patterns), and go-to-market
strategies aimed at ensuring reliable delivery and profitabil-
ity for the target customer (Picken, 2018).
The relationship betweenscalable structure
andteam composition
In startups, the focus on decision-making is narrow, with
limited time and resource commitment, and medium-level
economic risks. At the startup stage, the organization is typi-
cally informal with an open structure. The transition stage
commences when an entrepreneurial enterprise initiates its
market activities for the first time. Transition serves as a con-
nective bridge between the informal structure of a startup and
the structured form necessary for rapid scaling. The entre-
preneur's challenge is to upgrade and refine a value proposi-
tion, laying the foundation for rapid organization growth. The
acquisition of initial customers by a startup signals the need
for additional resources. Consequently, new capabilities must
be developed, leading to a significant increase in the range
and complexity of challenges faced by the founders' team.
During the scaling stage, entrepreneurs must infuse substan-
tial resources, participation, and streamlined processes into a
robust business framework and sustainable business model to
achieve growth (Pisoni and Onetti, 2016; Picken, 2018). This
growth propels the organization towards competitive scaling
and sustainable market leadership. Scaling necessitates a dis-
tinct organizational structure, processes, order, and discipline
compared to the startup or transition phases. As the company
expands, the fluid and flexible environment typical of startup
organizations becomes less conducive. Informal communica-
tion and decision-making processes lose effectiveness. In this
scenario, experts assume responsibilities to delineate general
matters, replace temporary decision-making with structured
processes and policies, and ensure continuous profitability to
provide returns for investors and secure financing for market
leadership. In some instances, a successful exit (via IPO, sale,

Journal of Global Entrepreneurship Research (2024) 14:15 15 Page 6 of 21
or integration) becomes imperative to realize the accumulated
investment value, thereby yielding profits for both the entre-
preneur and investors (Moro-Visconti, 2021). Transition occurs
when a startup evolves into a conventional business, marking
a pivotal phase in the new company's lifecycle. Within this
relatively brief period (typically lasting 18-36 months), the
founders' team must establish the groundwork for a reputa-
ble and legitimate business with accelerated growth, securing
essential resources for expansion. This stage fosters significant
development of the experience and skills required by the man-
agement team. Founders must concurrently focus on strategic
orientation, market positioning, team building, organizational
structure, resource accessibility, culture cultivation, and risk
mitigation. The heightened scope and complexity of these
activities necessitate adjustments in the leadership style and
management behaviors of the founders' team (Pisoni & Onetti,
2016; Picken, 2018; Moro-Visconti, 2021). Varga etal. (2024)
investigated how high-growth firms navigate the challenges
of scaling their business structure and team composition in a
turbulent environment. Their findings suggest that successful
scaling requires a balance between adaptability and stability.
While a degree of flexibility in structure allows high-growth
firms to respond to changing market conditions, a strong foun-
dation and well-defined roles are crucial for maintaining effi-
ciency and focus. The study emphasizes the importance of
building scalable teams. This may involve fostering a culture
of continuous learning and upskilling within the team, allow-
ing them to adapt their skillsets as the business grows and new
challenges arise (Varga etal., 2024).
Research has shown that the organizational structure
directly impacts its performance. A balanced structure is cru-
cial, as both too little and too much structure can be detri-
mental to a dynamic environment (Davis etal., 2009; Eisen-
hardt, 2013). Insufficient structure can open up a firm to a
wider range of unexpected opportunities but may also lead to
increased time consumption due to higher likelihood of mis-
takes and the need for more attention to tasks. Conversely, a
higher level of structure facilitates efficient execution of antic-
ipated opportunities, as inadequate structure can make goal
achievement challenging. Top management teams often spend
significant time deciphering tasks in the absence of adequate
structure, leading to errors. Conversely, excessive structure
may limit opportunities but can still enable effective exploita-
tion of certain opportunities (Eisenhardt, 2013). Davis etal.
(2009) assert that the relationship between structure and per-
formance varies across different environments. In predictable
markets, this relationship is linear, making it easier to manage
the balance between flexibility and business efficiency. Numer-
ous optimal structures exist under such conditions, allowing for
stable equilibrium. However, in unpredictable markets, achiev-
ing the optimal structure is difficult, with managing scale and
structure presenting challenges (Davis etal., 2009). Markets
characterized by rapid change offer abundant opportunities for
high performance, while ambiguous markets, akin to nascent
ones, heavily rely on luck, placing weaker management teams
at a disadvantage. Conversely, unambiguous markets favor
strong top management teams, where their management skills
are more likely to yield success (Eisenhardt, 2013). Organi-
zational scalability is a crucial factor enabling rapid growth
and profitability. Scalable organizations can expand swiftly
and generate profits or minimize losses (Gulati and DeSantola,
2016; Moro-Visconti, 2021; Gonçalvesa etal., 2022). Certain
top management teams are more adept at establishing success-
ful entrepreneurial ventures. These teams are typically large,
diverse in terms of age, skills, and expertise, with a history of
collaboration. In growing markets with low ambiguity, mod-
erate unpredictability, and rapid change, such strong teams
are more likely to lead highly performing firms (Davis etal.,
2009). The interaction between top management teams and
their corporate markets plays a pivotal role in organizational
success (Beckman etal., 2007).
Organizational scalability, a feature enabling rapid and
profitable growth, is distinct from technological scalability
seen in complex artifacts like computers and software code
(Bergin, 2001). A scalable organization is essential to har-
ness the economic benefits of scalable technology, highlight-
ing the interdependence between technological and organi-
zational scalability (Gonçalvesa etal., 2022).
The independent variables in this study encompass demo-
graphic characteristics such as heterogeneity, commitment,
cognitive comprehensiveness, and team size. Team diver-
sity, including heterogeneity, significantly impacts company
performance, yet research on demographic diversity within
entrepreneurial teams remains limited (Chowdhury, 2005;
Lopez Hernandezet al., 2018).
Demographic characteristics, commitment,
andcognitive comprehensiveness
The knowledge, skills, commitment, aspirations, and inter-
relationships among employees, both within the organiza-
tion and beyond its boundaries, are recognized as key com-
petitive advantages for fostering business growth (Amason
& Shrader, 2006; Beckmanet al.,2007; Hanifzadeh etal.,
2018; Meyer & Allen, 1984). A pro-growth working envi-
ronment fosters a culture that values diverse perspectives
and encourages knowledge sharing. This environment
benefits from a team with varied demographic characteris-
tics, potentially bringing a wider range of experiences and
ideas to the table. Additionally, a pro-growth environment
facilitates team commitment by fostering feelings of owner-
ship and purpose. Furthermore, such an environment may
encourage the development of cognitive comprehensiveness
within the team, as team members are empowered to learn
from each other and broaden their understanding of various
aspects of the business (Setiawan etal., 2024).

Journal of Global Entrepreneurship Research (2024) 14:15 Page 7 of 21 15
Chowdhury (2005) delves into the significance of demo-
graphic diversity within entrepreneurial teams and its influ-
ence on team effectiveness. He posits that effective entre-
preneurial teams are characterized by responsible members
who leverage diverse perspectives and resources to tackle
challenges. Therefore, fostering an environment of trust and
loyalty within entrepreneurial teams is essential to enhance
team commitment. Entrepreneurs are advised to collabora-
tively establish a cohesive team framework that encourages
each member to contribute their individual approaches and
perspectives for comparison and evaluation against various
options and procedures (Chowdhury, 2005).
Research suggests that overlapping team members are
likely to communicate more efficiently and share a common
frame of reference, particularly when they have previously
collaborated on new projects (Beckman etal., 2007; Eisen-
hardt and Schoonhoven, 1990). It appears that founding team
members with prior collaborative experiences exhibit higher
effectiveness and mutual trust (Eisenhardt and Schoonhoven,
1990), with trust being a fundamental component of social
capital. These shared work experiences can lead to shared
priorities and a common language among team members.
Moreover, everyday experiences have been shown to shape
shared beliefs and cultures. Affiliation overlap signals com-
petence to investors and enables teams to act swiftly and
efficiently. Therefore, both affiliation diversity and overlap
within both the top management team (TMT) and founding
team can facilitate companies in reaching their milestones
for various reasons (Beckman etal., 2007). The study by
Patel etal. (2021) explores the critical role of human capi-
tal in facilitating the transition of start-ups to the scale-up
phase. The research highlights the significance of talent
acquisition, leadership development, and organizational
culture in driving sustainable growth during the scale-up
process (Patel etal., 2021).
When considering the aspect of "relationship," the rela-
tionship between prior affiliations and organizational dynam-
ics may be indirect. Prior affiliations establish a set of norms
and expectations regarding organizational structure for indi-
viduals without shared everyday experiences in a company.
Social capital pertains to a shared understanding stemming
from social structures rather than direct social connections.
Previous joint affiliations can foster trust, while diverse prior
affiliations can lead to new contacts and insights. Conse-
quently, other factors may be influenced or interconnected,
highlighting the nuanced interplay within organizational
teams (Beckman etal., 2007).
Demographic heterogeneity
Characteristics of a team, instead of focusing on the struc-
ture of individual roles, primarily center on the background
and experiences of the individuals fulfilling those roles.
Individuals within an organization engage in considerations
such as product development, market analysis, risk assess-
ment, and managing uncertainty to chart the organization's
course (DeSantola and Gulati, 2017). Smith etal. (2021) in
their study highlight the significance of team educational
backgrounds in influencing the scalability of start-up busi-
nesses. The research suggests that founders and teams with
specialized education in business or entrepreneurship are
more likely to successfully scale their ventures compared to
those with non-business backgrounds (Smith etal., 2021).
Also, Johnson and Lee (2020) underscore the role of prior
work experience in shaping the scalability potential of start-
ups. The study found that founders with industry-specific
work experience were better equipped to navigate challenges
related to scaling, leading to more sustainable growth tra-
jectories for their businesses. The demographic makeup of
a team influences its information processing capabilities,
thereby impacting the performance of a startup. The breadth
of access to diverse information and varied past experiences
within a team, known as performance diversity, directly
influences the level of business performance and growth
(Amason & Shrader, 2006).
The functional background of team members reflects their
collective experiences. Chowdhury (2005) demonstrates
that teams characterized by diversity in terms of age, gen-
der, specialization, and past performance tend to be more
dynamic and effective. Entrepreneurial scholars emphasize
the importance of the quality of the team's prior experiences
for the company's success. To operationalize these insights
within a demographic framework, it is crucial to consider
diversity in the types of human capital experiences present
within the team (Beckman etal., 2007, Huang etal., 2021).
Beckman etal. (2007) illustrate in their study on the demo-
graphic compositions of top management teams in young
high-tech firms that functional diversity, represented by a
range of previous experiences, and interdependencies stem-
ming from past work engagements, lead to enhanced infor-
mation access.
Building on previous research, Beckman etal. (2007)
establish that top management teams, whether founding or
early-stage, characterized by diverse functional backgrounds
and relevant human capital, achieve entrepreneurial mile-
stones more rapidly than less diverse and less experienced
teams. They further contend that performance diversity and
prior executive experience generally contribute to team suc-
cess. Business team members accrue valuable experience
and networks from past business endeavors that can prove
advantageous for a new venture. An underlying aspect that
has received scant attention is the notion of dependence
within a team's demographic composition (Beckman etal.,
2007).
Research indicates that variations in age, educational
attainment, and experience positively impact startup sales

Journal of Global Entrepreneurship Research (2024) 14:15 15 Page 8 of 21
growth. Moreover, diversity within a team in terms of age,
gender, and expertise can influence the growth trajectory of
startups (Klotz etal., 2014; Wong and Hong, 2005; Huang
etal., 2021). This study, drawing on the works of Beckman
(2007), Chowdhury (2005), and Eisenhardt (2013), consid-
ers age, gender, operational background, specialization,
qualifications, and startup history to measure the demo-
graphic diversity of team members.
Startups with higher levels of demographic heterogene-
ity in their teams were more likely to successfully reach the
scale-up stage. The diverse perspectives and experiences
brought by team members from different demographic
backgrounds contributed to enhanced creativity, problem-
solving, and adaptability, key factors for scaling up a startup
(Johnson etal., 2022). Also, startups with a balanced demo-
graphic composition in their teams, including gender, age,
and cultural diversity, exhibited higher levels of innovation
and resilience during the scale-up process. The ability to lev-
erage diverse perspectives and approaches within the team
positively influenced the startup's growth trajectory (Garcia
and Patel, 2023).
Given the aforementioned rationale, it is anticipated that
demographic diversity within teams plays a vital role in the
scalability of startups. Consequently, based on Research
Question 1 (RQ1), the first hypothesis is proposed:
Hypothesis 1. There is a significant positive relationship
between demographic diversity in terms of age, gender,
functional background, and firm scalability.
Team commitment
In the organizational context, a team is defined as a small
group of individuals with specific performance objectives
and a shared commitment to a common goal and approach
to their responsibilities (Harvey, Millet, and Smith, 1998). A
crucial distinction between teams and groups lies in the level
of commitment to a shared goal. While group members may
pursue a common objective, team members not only seek a
common goal but are also deeply committed to achieving it.
The primary aim of a team is to outperform other teams in
a specialized domain, with team goals being internalized by
members who invest significant time in their development.
Teams and groups utilize goals to guide and advance their
members, while also striving towards broader objectives
such as creating meaning, emotional energy in activities,
and fostering a sense of commitment (Rezaian, 2007).
Transitioning from a group to a team requires strong
leadership, with all members dedicated to a singular pur-
pose, assuming responsibility for that purpose, and adept at
problem-solving when challenges arise (Janutaite, 2015). In
a management team, members operate in roles designated by
the team leader, while entrepreneurial team members exhibit
commitment to one another and the future of the business.
The motivations of entrepreneurial team members often
revolve around leveraging their human capital to enhance
organizational performance (Tihula, Huovinen, and Fink,
2009).
Lencioni (2006) highlights in his book "The Five Dys-
functions of a Team" that genuine teamwork is challenging
in many organizations due to five common dysfunctions:
lack of trust, fear of conflict, lack of commitment, avoid-
ance of accountability, and inattention to results. Overcom-
ing these behavioral barriers is essential for transforming an
ineffective team into a cohesive one (Lencioni, 2006). Drex-
leret al. (1988) propose a comprehensive model of team
performance outlining predictable stages of team formation
and sustainability across seven areas: orientation, trust build-
ing, goal clarification, commitment, implementation, high
performance, and renewal (Drexleret al., 1988).
Recent research conducted by Smith (2021), and John-
son and Lee (2022) found that team commitment signifi-
cantly influences the success of a startup in reaching the
scale-up stage. They highlighted that high levels of com-
mitment among team members were positively associated
with improved collaboration, communication, and overall
performance, which are crucial for navigating the chal-
lenges of scaling up a startup. Also, Johnson and Lee (2022)
emphasized that teams with strong commitment were more
likely to stay motivated, resilient, and focused on achieving
long-term goals. This dedication was found to help start-
ups overcome setbacks, adapt to changes, and maintain a
positive work culture that fosters innovation and growth.
Furthermore, the research indicated that team commitment
positively impacted investor confidence, customer trust,
and stakeholder relationships, all of which are essential for
securing funding, expanding market reach, and building a
sustainable business model (Smith, 2021, and Johnson and
Lee, 2022).
According to Katzenbach and Smith (2015), a team is
described as "a small group of individuals with complemen-
tary skills, committed to performance goals and a shared
approach to mutual accountability for those goals" (Katzen-
bach and Smith, 2015). Commitment within a team signifies
a high level of dedication among team members to each
other and the team, fostered by an environment of trust and
loyalty (Shapiro & Varian, 1999). High-growth startups tend
to have more committed employees, with the knowledge,
experience, skills, and commitment of employees, along
with their relationships internally and externally, serving
as a competitive advantage for business growth (Meyer &
Allen, 1984). Picken (2018) suggests that building commit-
ment within the startup team is a key challenge in transition-
ing from startup to scale-up stages (Picken, 2018).
In this study, based on the research of Katzenbach and
Smith (2015), Drexleret al. (1988), and Chowdhury (2005),

Journal of Global Entrepreneurship Research (2024) 14:15 Page 9 of 21 15
team commitment is assessed through three factors: 1) the
extent of members' loyalty, 2) their expectation of remaining
with the team long-term, and 3) their trust in the team. Each
entrepreneur evaluated their team on these criteria using a
five-point scale ranging from very high to very low.
Building on this rationale, it is anticipated that team com-
mitment plays a significant role in the scalability of startups.
Therefore, based on Research Question 1 (RQ1), the second
hypothesis is proposed:
Hypothesis 2. There is a significant positive relationship
between team commitment and firm scalability.
Team‑level cognitive comprehensiveness
Although the entrepreneurship literature has traditionally
focused on the individual entrepreneur's role, contempo-
rary innovative enterprises are predominantly established
by teams rather than individuals. Harrison and Klein
(2007)have noted that high-growth large enterprises are
typically founded by teams. Moreover, research suggests that
companies founded by teams tend to be more successful than
those established by individual founders. Teamwork among
individuals with diverse academic backgrounds exposes
them to a broader range of knowledge, ideas, and perspec-
tives (Harrison and Klein, 2007). These interactions can
foster the generation of creative ideas and stimulate novel
combinations of knowledge, creativity, and innovation. The
study by Garcia etal. (2021) delves into the cognitive factors
that impact the transition of start-ups to a stage of expo-
nential growth. The research highlights the importance of
entrepreneurial mindset and strategic thinking in driving
scalable growth trajectories for early-stage ventures (Garcia
etal., 2021).
When analyzing the growth of startups created by teams,
it is essential to consider not only the characteristics of indi-
viduals but also the dynamics and composition of the team.
Team composition plays a crucial role as it involves various
considerations to achieve the optimal mix of attributes such
as knowledge, skills, and competencies. The formation of
teams is particularly significant as it can impact the suc-
cess of a startup. Team heterogeneity, which encompasses a
variety of skills and competency levels within the team, has
been shown to have a positive effect on sales growth and the
long-term success of new ventures.
The study of Chen and Gupta (2023) revealed that teams
with a high level of cognitive diversity and comprehensive-
ness, encompassing a wide range of knowledge, expertise,
and problem-solving approaches, were more likely to effec-
tively navigate the challenges of scaling up. Team-level
cognitive comprehensiveness was associated with enhanced
decision-making, innovation, and adaptability, which are
critical for driving growth in startups (Chen & Gupta, 2023).
Also, The research of Patel and Kim (2022), demonstrated
that startups with cognitively diverse teams, characterized by
a broad spectrum of knowledge and perspectives, were bet-
ter equipped to drive innovation, make strategic decisions,
and sustain growth during the scale-up phase. Team-level
cognitive comprehensiveness was found to positively influ-
ence problem-solving capabilities, creativity, and overall
performance, leading to increased success in reaching the
scale-up stage (Patel & Kim, 2022).
Research suggests a positive relationship between cohe-
sion and growth, as cohesion expedites decision-making
processes and startup growth. Beckman etal. (2007) notes
that members with shared backgrounds and experiences can
communicate effectively and perform tasks efficiently. Net-
work activity should involve all team members, as indicated
by Neergaard etal. (2005), and the communication network
evolves based on the organization's evolving needs. The
literature reviewed above highlights several critical entre-
preneurial attributes that influence venture growth. Studies
have extensively explored human resources and strategic
planning to understand the relationship between organiza-
tional members' characteristics and venture growth patterns.
As leading a new venture is increasingly viewed as a col-
laborative effort, team composition at the upper organiza-
tional levels of a new venture has garnered special attention.
Existing team members may undergo transformations, and
new members may join the upper teams as the organiza-
tion grows. The characteristics and diversity of upper
team representatives can evolve based on the rationale and
method of hiring new members with professional expertise,
enabling the organization to gain external experiences for
smoother growth.
Cognitive comprehensiveness within a team is deemed
essential for complex and innovative decision-making pro-
cesses. Studies by Perez and Mehta, Maley (2013), DeSan-
tola and Gulati (2017), and Chowdhury (2005) emphasize
the significance of cognitive comprehensiveness in fostering
effective decision-making. To measure cognitive compre-
hensiveness, Wrona and Ladwig (2015) developed a tool
designed for team effectiveness. Data on team-level cogni-
tive comprehensiveness are collected based on four items:
the team's perspective on an existing problem, the number
of potential solutions to a problem, the generation of inno-
vative ideas, and criteria for evaluating potential solutions.
Cognitive comprehensiveness facilitates comprehensive
decision-making processes and the development of strate-
gies that incorporate diverse perspectives, potential solu-
tions, and evaluation criteria for addressing complex and
innovative decisions.
A five-point agree/disagree scale is utilized to gather data
on these four items. Given the aforementioned rationale,
team-level cognitive comprehensiveness is expected to play
a significant role in the scalability of startups.

Journal of Global Entrepreneurship Research (2024) 14:15 15 Page 10 of 21
Building on this rationale, it is anticipated that team-level
cognitive comprehensiveness plays a significant role in the
scalability of startups. Therefore, based on Research Ques-
tion 2 (RQ2), the third hypothesis is proposed:
Hypothesis 3. There is a significant positive relationship
between team-level cognitive comprehensiveness and
firm scalability.
Team size
Team size was considered as another independent variable in
this study. The size of the participating team was measured
as the total number of active partners in the team who are
shareholders of the company. Respondents cited the number
of active partners, not just investors and shareholders.
Eisenhardt (2013) argues in his research that large and
diverse teams, in terms of age, experience, and expertise,
with a history of previous collaboration are more likely to
succeed. This impact is especially strong when operating
in high-growth markets. In his research, Eisenhardt evalu-
ated performance through annual revenue growth, and the
strategy was evaluated in terms of the extent to which the
company was involved with advanced innovations. He con-
cluded that teams that were larger in size, more diverse in
age and experience, and had a history of working together
in the past, had a significant impact on the success of their
entrepreneurial companies (Eisenhardt, 2013). Kock and
Galkina in their research showed that changing the size of
the team and the arrival of people with new skills affect the
capabilities and skills of the business (Kock and Galkina,
2008). Herre (2010) divides the team into three levels: 1-
Individual factors including skills, personality, and 2- Group
factors including structure, size, and 3- Environmental fac-
tors including work, stress, reward. Accordingly, group
behavior influenced by the group factors affects the results
of the business. For example, team size is directly related to
business success (Herre, 2010). Robins etal. (2013) divide
the factors affecting the success and effectiveness of the
team into three categories of factors, which include: 1- Basic
factors including sufficient resources, leadership, structure,
trust, performance appraisal, and reward system, 2- Team
composition including team members' ability, personality,
role recognition, diversity, team size, members' flexibility,
and preferences, and 3- The process includes a common mis-
sion, specific goals, team efficiency, and levels of conflict.
Accordingly, increasing the size of the team increases the
probability of success and effectiveness of the team (Rob-
ins etal., 2013). Accordingly, with increasing team size,
interactions related to teamwork increase, and as a result,
the possibility of creativity increases. Creativity leads to
constant innovation in the changing environment, which
makes it possible for businesses to be more successful in
scale (Davidsson & Honig,2000;Shalley & Smith, 2008).
Recent research suggests there's a optimal spot for team
size when a startup transitions into a scale-up. Startups with
teams that are not too small and not too large seem to have a
better chance of successfully scaling their operations. This
in-between zone allows for the agility and close collabora-
tion characteristic of startups while having enough structure
and resources to handle the growth demands of a scale-up
phase (Piaskowska etal., 2021).
Building on this rationale, it is anticipated that team
size plays a significant role in the scalability of startups.
Therefore, based on Research Question 3 (RQ3), the fourth
hypothesis is proposed:
Hypothesis 4. There is a significant positive relationship
between team size and firm scalability.
Team completeness
Team completeness, as the last independent variable in this
study, was examined for its effect on scalability. It indicates
that for each key business position, there is a specific and
distinct individual (Beckman etal., 2007). Functional het-
erogeneity affects company performance due to its diver-
sity in functional backgrounds, skills, and abilities (Randel
&Jaussi, 2003). Colombo and Grilli (2005) have presented
evidence of the supplementary capabilities of the synergic
effect of the founders' team. Their findings support the belief
that new investment growth is influenced by the founders'
education duration in the areas of economics and knowledge
management. Barringer and Neubaum (2005) emphasize the
importance of founders' education. They compared a sample
of 50 rapidly growing companies with a sample of 50 slowly
growing companies and found that the academic education
of founders is essential for acquiring the skills required
to start a new venture and facilitate its growth. Roure and
Keeley (1990) demonstrate in their research that team com-
pleteness is the degree to which key positions are filled by
members of the founding team. Diverse functional experi-
ence within the team also attracts the attention of foreign
stakeholders and investors. Some experts also believe that
team completeness should include essential expertise in a
new venture (Stevens, 2016).
The study of Kim and Patel (2022) found that teams
with a diverse set of skills and expertise, representing a
high level of completeness, were more likely to effectively
tackle the challenges of scaling up. Team completeness was
associated with enhanced problem-solving abilities, crea-
tivity, and adaptability, which are crucial for navigating the
complexities of growth in startups (Kim and Patel, 2022).
Also, Garcia and Wong (2021) demonstrated that startups
with well-rounded teams, encompassing a diverse range of
skills, experiences, and perspectives, were better equipped

Journal of Global Entrepreneurship Research (2024) 14:15 Page 11 of 21 15
to innovate, adapt to market changes, and sustain growth
during the scale-up phase. Team completeness was found
to positively impact decision-making processes, resource
allocation, and overall performance, leading to increased
chances of success in reaching the scale-up stage (Garcia
and Wong, 2021).
Based on the above rationale, it is anticipated that team
completeness plays an important role in the scalability of
startups. Therefore, based on RQ3, the fifth hypothesis is
presented:
Hypothesis 5. There is a significant positive relationship
between team completeness and firm scalability.
Theoretical Framework
Based on a comprehensive review of the literature and the
aforementioned considerations, this research comprises
five hypotheses. In these hypotheses, business scalability is
treated as the dependent variable, with variables pertaining
to team diversity and processes considered as independent
variables. These ideas were empirically tested through an
examination of a sample of 90 technological startups in Iran.
The firms included in the sample were established for
over 5 years and had a workforce of more than 10 employees
at the outset. Data regarding the impact of team roles on the
scalability of startups was collected through a questionnaire.
To develop the questionnaire, a mixed methods approach
was employed in this research. It involved the utilization
of Chowdhury's research questionnaire (2005) and a pilot
study for certain questions. The pilot study questions were
reviewed by two experts to ensure the validity of the ques-
tionnaire in addressing the research inquiries.
The online questionnaire was distributed to the founders
and managers of Iranian technological startups via LinkedIn.
Out of the 362 questionnaires sent, 90 completed responses
were received. Among the participants, 27% were female
and 73% were male. The average age of the participants was
31 years, with an average of 4.5 years of prior work experi-
ence. Furthermore, 63.6% of the participants held a master's
degree, 22.4% held a bachelor's degree, and the remaining
participants had a PhD.
Method
Sample anddata
Participants in this study comprised founders and managers
of ninety technological startups in Iran. 362 questionnaires
were distributed to eligible LinkedIn members (managers
and founders of Iranian technological start-ups and other
conditions mentioned below) to gather information about
the team's role in scaling startups, of which 90 completed
questionnaires were returned. Questionnaires were randomly
distributed among the accessible community. The online
questionnaire was sent to participants via LinkedIn and
was designed to be completed online, with responses being
automatically recorded upon completion. Participants were
assured of the confidentiality of their responses. These 90
valid questionnaires that were answered show a response
rate of approximately twenty-five percent.
The research aimed to assess the scalability of startups
(Piaskowska, Tippmann, & Monaghan, 2021). Criteria
indicating that the firms were in the scale-up stage included
being operational for over 5 years, having a stable business
model, fixed or linearly growing expenses, and exponen-
tially growing revenues (DeSantola & Gulati, 2017). Over a
three-year period, the average sales had increased by twenty
percent annually and the firms had at least 10 employees at
the start of the period (Simsek & Post, 2020). Additionally,
the firms operated in the IT industry.
Among the participants, 24 were female and 66 were
male, with seventy-three percent being male. The average
age and years of education were 31 and 4.5, respectively.
Twenty respondents held bachelor's degrees, 57 possessed
master's degrees, and 11 held Ph.D.s. Thirty-five percent of
respondents had 10 to 20 years of work experience, while
6% had over 20 years, and the rest had 5 to 10 years of expe-
rience. All startups examined in this research were techno-
logical and operated in the electronic commerce industry.
Seventy-five startups were founded by a team, while 15 were
individually launched. The questionnaire was completed in
2021.
This study, the first of its kind in Iran, aimed to enhance
understanding of the team factors influencing the scalability
of startups. The firms in the sample were operational for
more than 5 years and had over 10 employees at the outset.
According to a report by UNIDO (2021), Iran possesses
extensive scientific, technological, financial, and highly
skilled human capital to bolster its startup sector. However,
there is a need for mechanisms to engage key stakehold-
ers, such as access to funding and relevant advisory sup-
port. Knowledge-based entrepreneurship plays a crucial
role in generating employment opportunities, facilitating
the integration of young professionals into the labor mar-
ket, and driving the knowledge-based development of Iran's
economy.
Iran's startup ecosystem is in its nascent stages but dis-
plays promising growth potential. According to the survey
conducted by Jafari (2019), 32.2 percent of participants
indicated that their startups were between 6 months and a
year old. Additionally, 27.2 percent reported their startups
were less than 6 months old, while 28.2 percent stated their
companies were between one and three years old. Only 8

Journal of Global Entrepreneurship Research (2024) 14:15 15 Page 12 of 21
percent of the companies included in the study were estab-
lished more than three years ago (Jafari, 2019). Nearly half
of Iranian startups (49 percent) are currently in the market
entry stage. Among these, 23.4 percent are in the growth
phase and generating income, 15.6 percent have developed
a prototype or minimum viable product (MVP), 11.5 percent
are exploring new markets, and 0.5 percent have reached
maturity. An established organizational structure, a reliable
source of income, and sustainable growth are indicative of
a startup's progress (Jafari, 2019).
Furthermore, Jafari's study (2019) revealed that 51.4 per-
cent of Iranian startups target the entire country, while 39.5
percent focus on provincial markets and 7.3 percent cater
to local markets. Interestingly, only 1.1 percent of startups
aim at the regional market, with a mere 0.6 percent targeting
the international market. Challenges such as international
sanctions and difficulties related to financial transactions
often compel Iranian companies to operate within domestic
boundaries. Despite these obstacles, some companies have
effectively expanded into international markets while oper-
ating locally. In certain cases, these companies establish
branches in European countries to facilitate international
money transfers.
The Iranian market, being an emerging market, presents
unique opportunities for growth. Emerging markets are
typically viewed as appealing regions for business expan-
sion (Ferreira & Ferreira, 2018). Yang (2018) suggests that
firms in emerging markets must develop the necessary skills
to navigate challenging institutional environments. This
includes adapting to inefficient bureaucratic systems, secur-
ing limited resources, and combating corruption through
avoidance and resistance. Acquiring these capabilities to
thrive in a challenging environment can confer a distinct
competitive edge. Institutional advantages, such as adeptness
in dealing with bureaucratic inefficiencies, resource scarcity,
and corruption control, are commonly observed in startups
operating in emerging markets (Landon etal., 2019). Con-
sequently, companies and startups in such environments
often exhibit similar characteristics. Moreover, the allure of
emerging markets for startup scalability is well-documented
(Ferreira & Ferreira, 2018). Therefore, the findings of this
research can be extrapolated to other startups situated in
emerging markets, highlighting the relevance and applicabil-
ity of the study's results beyond the Iranian context.
In this study, the criteria established by Katzenbach and
Smith (2015) and Chowdhury (2005), which were developed
based on the work of Drexleret al. (1988), were utilized
to evaluate the research variables. The questionnaire was
translated from English to Persian by a proficient English
language specialist. To ensure the fidelity of the original
meanings, two Persian language experts in the United States,
specializing in this field, validated the translation of con-
cepts between the English and Persian questions.
The research team monitored the independent variables
using a questionnaire derived from existing literature. These
variables, along with their corresponding literature, encom-
passed demographic diversity in terms of age, gender, and
functional background (Beckman, 2007, Eisenhardt, 2013;
Chowdhury, 2005; Huang etal., 2021), team commitment
(Katzenbach & Smith, 2015; Drexleret al., 1988; Chowd-
hury, 2005), with references to Shapiro and Kirkman (1999)
team-level cognitive comprehensiveness (Chowdhury,
2005; DeSantola & Gulati, 2017; Stevens, 2016), drawing
on Miller etal. (1998) and Simons etal. (1999), team size
controlled for team completeness (Beckman etal., 2007)
originally by Roure and Keeley (1990), and team complete-
ness (Stevens, 2016; Neubaum, 2005; Beckman etal., 2007).
The data collection instrument employed in this study
was a standardized questionnaire utilizing a five-point Likert
scale. Table1 provides a detailed overview of the tool used
to measure the research variables. The statistical population
under investigation consisted of representatives and manag-
ers of entrepreneurial teams within Iranian startups. Through
the stratified random sampling method, a sample size of 90
members from these entrepreneurial teams was selected.
In this research, the criteria established by Katzenbach
and Smith (2015) and Chowdhury (2005), based on Drex-
leret al. (1988), were employed to assess the research vari-
ables, which encompassed demographic diversity in terms
of age, gender, and functional background, team commit-
ment, team-level cognitive comprehensiveness, team size,
and team completeness.
We utilized the structural equation modeling technique
with the partial least squares method (PLS-SEM) and Smart
PLS software to analyze the questionnaire data for this study.
SEM is commonly employed in research to confirm a study
design rather than to explore or explain a phenomenon. The
primary objective of structural equation modeling (SEM) is
to establish a theoretical causal model comprising a series
of predicted covariances between variables and subsequently
assess its plausibility against the observed data.
SEM analysis serves various purposes, including testing
the strength of relationships within the model. The structural
equation modeling framework comprises two key compo-
nents: the measurement model and the structural model.
Model variables are categorized into hidden and explicit
variables, with hidden variables operating at different levels
within the model. The measurement model segment entails
the examination of the questions associated with each fac-
tor, as well as the relationships between the questions and
the factor. In contrast, the structural model segment encom-
passes all structures outlined in the primary research model,
evaluating the extent of correlation and relationships among
them (Kline, 2015).
To ensure the validity of the instruments used in this
study, we conducted instrument validation procedures

Journal of Global Entrepreneurship Research (2024) 14:15 Page 13 of 21 15
using Smart PLS software. Key indicators such as CR, AVE,
Alpha, and factor load coefficients were employed for valida-
tion purposes, as presented in Table2.
The questionnaire items were assessed using the AVE
(Average Variance Extracted) method and by compar-
ing AVE values and correlations between variables. To
evaluate reliability, Cronbach's alpha coefficient and com-
posite reliability were employed. In this study, a stringent
factor-confirmatory analysis approach was adopted, leading
to the elimination of questions with a factor loading below
0.4. In factor-confirmatory analysis, the t-statistic is also
calculated, with a threshold value of greater than 1.96 con-
sidered essential (Davari and Rezazadeh, 2015).
The instrument demonstrated strong reliability, with α
exceeding 0.7. Average Variance Extracted (AVE) indicates
the level of correlation within a structure and its attributes,
Table 1 Components of the Research Instrument
Variable Measurement Index Reference
Demographic characteristics of teams in
terms of age, gender and background
(DD)
age (Chowdhury 2005)
gender
education
Field of study and orientation
Position in the team
Professional work experience
Managerial work experience
Background and field of activity of the company
Your company activity background
Team size Team size in beginning (Eisenhardt 2013)
Current team size
Team completeness For which key business position is there a spe-
cific and distinct individual?
(Beckman, Burton, and O'Reilly 2007)
Team commitment Team members feel very loyal to the business (Chowdhury 2005) (they used: Shapiro and Var-
ian 1999)
I expect to stay with this company for next five
years
I feel this team is very trustworthy
Team-level cognitive comprehensiveness There are a variety of perspectives on the prob-
lem at hand when facing a problem
Chowdhury (2005) They used (Miller etal. 1998;
Simons etal. 1999).
Team members turn to various trainings and
resources to find solutions when facing a
problem
There is a variety of different specialties in our
business team
We have a variety of criteria for evaluating pos-
sible solutions to problems ahead
Firm Scalability The current structure will be responsive to this
volume of production if the volume (commod-
ity/service) triples next year.
(Bergin 2001; Koren 2010; Lafou etal. 2015;
Nunez, Artta and Truex 2004, Gonçalvesa etal,
2022).)
The current processes will be responsive to this
volume of production if the volume (commod-
ity/service) triples next year.
The company will be responsive to this volume
of production if the demand (commodity/ser-
vice) triples next year.
The company will not incur unreasonable costs
if the demand (commodity/service) triples next
year.
Reevaluating our company's processes for
sudden increase in production will not Couse
much cost.
Our company can redesign its structures to take
advantages of 3 to 4 times more demand at
little cost.

Journal of Global Entrepreneurship Research (2024) 14:15 15 Page 14 of 21
with higher correlations indicating better model fit. The results
presented in Table2 show that the AVE values for all constructs
exceed 0.5, confirming convergent validity and model fit.
Another crucial indicator examined for model validation
was the factor load coefficient. To assess the factor load coef-
ficient, all item factor loadings should surpass 0.4. If any item's
factor loading falls below 0.4, it is recommended for removal,
necessitating a re-evaluation of the model. Table3 displays the
outcomes of factor load coefficients and t-values. As depicted
in the table, all item factor loadings exceed 0.4, indicating that
no questions need to be eliminated from the model.
Analysis ofvariables andtheir validation
Part of the factor-confirmation analysis is to examine the
validity of the model. As can be seen in Table2, the mean
coefficients of variance taken or AVE and the values of the
path coefficient C and the statistic T are at an acceptable
level. The cumulative variance percentage is also acceptable.
Therefore, the main dimensions of the model are significant.
Also in the reliability section, Cronbach's alpha coefficient
and reliability coefficient have a combination higher than 0.7
and is acceptable. Evaluation of the overall fit of the model
According to Maydeu-Olivares and Montaño (2013), the
GOF index is between 0 and 1. Values close to one indicate
the proper quality of the model. GOF can be obtained by
calculating the geometric mean of the common mean and
R2. The overall fit of the model is calculated by the GOF
criterion using the following method:
com
the sign is the average of the common values of each
structure and R2 is the mean of the mean values. The higher
the R2 of the endogenous structures of the model, the better
the fit of the model. Davari and Rezazadeh (2015) intro-
duced three values of 0.01, 0.25, and 0.36 as weak, medium,
and strong values for GOF respectively. In this study, a value
of 0.752 for GOF indicates a general and strong fit of the
model (Davari & Rezazadeh, 2015) Based on this, the model
of this research is fit.
GOF
=
�
com ×R2=
√
0.818 ×0.692 =
0.752
Results
The majority of participants reported having 10 to 20 years
of professional experience, with twenty-one percent being
the most frequently reported figure. Additionally, twenty-
seven percent of subjects reported having 10 to 20 years of
managerial experience.
Structural equation modeling was employed to explore
the relationships between variables, with results presented
in terms of significance levels and path coefficients. Initially,
the bootstrapping function in the PLS software was utilized
to validate the research hypotheses, yielding p-values as
depicted in Fig.1. A p-value exceeding 1.96 or falling below
-1.96 signifies the significance of variables, thereby confirm-
ing the related hypotheses. In Fig.2, all p-values are below
1.96, indicating the confirmation of all hypotheses.
The study examined the causal relationships between var-
iables by assessing path coefficients following significance
evaluation. Path coefficients represent the extent of influ-
ence that variables exert on each other, with the outcomes
displayed in the accompanying figure.
Test ofhypotheses
The study hypotheses are summarized in Table4. Hypoth-
esis 1, with a t-value of 13.5 and a path coefficient of 0.515,
supports RQ1. Similarly, Hypotheses 2, 3, 4, and 5, with
t-values of 4.81, 11.43, 2.89, and 2.22, and path coefficients
of 0.20, 0.44, 0.10, and 0.08, respectively, support their cor-
responding research questions (RQ1, RQ2, RQ3).
Two very important outputs in SmartPLS3 software are
the value of the t statistics and path coefficients (C) or factor
Table 2 Results of validating the model OR Results of Model Valida-
tion
Variables items Alpha CR AVE
Entrepreneurial Team DD 9 0.89 0.85 0.505
Tcommit 3 0.85 0.657
TLCC 4 0.82 0.538
TS 2 0.85 0.741
Tcomplet 1 1.00 1.00
FS 6 0.78 0.84 0.580
Table 3 Results of factor load coefficients
Q FL Q FL
1 Q1 0.645 4 Q10 0.887
Q2 0.621 Q11 0.834
Q3 0.701 5 Q12 1.000
Q4 0.559 6 Q20 0.714
Q5 0.666 Q21 0.721
Q6 0.718 Q22 0.694
Q7 0.627 Q23 0.721
Q8 0.648 Q24 0.676
Q9 0.516 Q25 0.634
2 Q13 0.847 1.DD
2.Tcommit
3.TLCC
4.TS
5.Tcomplet
6. FS
Q14 0.786
Q15 0.799
3Q16 0.775
Q17 0.751
Q18 0.750
Q19 0.655

Journal of Global Entrepreneurship Research (2024) 14:15 Page 15 of 21 15
loads. In this study, according to Table3, the factor load
between all the questions of the questionnaire and the latent
variables is more than 0.4, which means that the construct
used has measured the latent variable well. The value of
the t statistic is also the property of confirming or rejecting
hypotheses. If this value is more than 1.96, 1.64, and 2.58
respectively. The hypothesis, therefore, is confirmed at the
95, 90, and ninety-nine percent levels. Also, if the value of
the path coefficient between the independent latent variable
and the latent dependent variable is positive, we will see an
increase in the dependent variable by increasing the inde-
pendent variable, and conversely. If the value of the path
coefficient between the independent and dependent variables
is negative, we will see a decrease in the dependent variable
by increasing the independent variable. Surveys showed the
demographic characteristics of teams in terms of age, gender
and background, team commitment, cognitive comprehen-
siveness at the team level, team size, and team integrity they
have a positive and significant effect on the scalability of
the company, and the hypotheses are confirmed at the level
of ninety-nine percent (Table4). Also, respectively demo-
graphic characteristics and cognitive comprehensiveness at
the team level have the strongest relationship with the scal-
ability of the company Fig.3.
Fig. 1 Conceptual framework of
the study
Demograp
hic
diversity
in terms
Team
completeness

Journal of Global Entrepreneurship Research (2024) 14:15 15 Page 16 of 21
The results of the the study hypotheses are summarized
in the Table4. Based on this t-value of the hypothesis 1 is
13.5 and it’s path coefficient is 0.515, so to address RQ1
hepatitis 1 is supported. T-value of the hypothesis 2 is 4.81
and it’s path coefficient is 0.20, so to address RQ1 hepatitis
2 is supported. T-value of the hypothesis 3 is 11.43 and it’s
path coefficient is 0.44, so to address RQ2 hepatitis 3 is sup-
ported. T-value of the hypothesis 4 is 2.89 and it’s path coef-
ficient is 0.10, so to address RQ3 hepatitis 4 is supported.
T-value of the hypothesis 5 is 2.22 and it’s path coefficient
is 0.08, so to address RQ3 hepatitis 5 is supported.
According to Fornell and Larcker (1987), divergent
validity is examined by using the correlation matrix, that
one component, compared with other components, should
have more distinction and distinction among its observable
(questions) then can be said that the component in question
has high divergent validity. In divergent validity, we seek
to answer this question: A factor compared to external fac-
tors, how irrelevant and uncalculated can explain the col-
lection variance of the questions? According to Table5, if
a factor has the highest amount of variance of questions,
and it shows less correlation with unrelated factors, it has
Fig. 2 Model drawing in the significant t-value conditions
Table 4 The results of the hypotheses tests
hypotheses p-values Path coefficients Test results
H1. There is a significant positive relationship between Demographic diversity in terms of age, gender
functional background, and Firm Scalability.
13.5 0.515 confirmed
H2. There is a significant positive relationship between Team commitment, and Firm Scalability. 4.81 0.20 confirmed
H3. There is a significant positive relationship between Team-level cognitive comprehensiveness, and
Firm Scalability.
11.43 0.44 confirmed
H4. There is a significant positive relationship between Team Size, and Firm Scalability. 2.89 0.10 confirmed
H5. There is a significant positive relationship between Team completeness, and Firm Scalability. 2.22 0.08 confirmed

Journal of Global Entrepreneurship Research (2024) 14:15 Page 17 of 21 15
divergent validity. In other words, the convergent validity
tide of each component is greater than the maximum cor-
relation of that component with other components. In other
words, the square root of the convergent validity of each
component is greater than the maximum correlation of that
component with other components (Numbers on the diam-
eter of Table5) (Fornell & Larcker, 1987).
The numbers in Table5 indicate the appropriate diver-
gence validity based on the Fornell and Larcker methods.
According to the results in the table above, the convergent
validity of variance average is shared between each construct
with its own indexes. By Fornell and Larcker (1987) conver-
gent validity above 0.5 was considered acceptable but Mag-
ner (1996) believed that 0.4 and higher is enough (Davari &
Rezazadeh, 2015). Therefore, the convergent validity of all
variables has a favorable coefficient.
Fig. 3 model execution in the path coefficients conditions
Table 5 Correlation matrix and
the convergent and divergent
validities of Fornell and Larcker
Number Variables Con-
vergent
validity
123456
1 Demographic diversity (DD) 0.598 0.773
2 Team Size (TS) 0.689 0.504 0.83
3 Team completeness(Tcomplet) 0.579 0.35 0.093 0.761
4 Team commitment (Tcommit) 0.479 0.479 0.462 0.444 0.692
5 Team-level cognitive compre-
hensiveness (TLCC)
0.591 0.453 0.448 0.279 0.442 0.769
6 Firm Scalability(FS) 0.783 0.308 0.332 0.307 0.314 0.342 0.885

Journal of Global Entrepreneurship Research (2024) 14:15 15 Page 18 of 21
Discussion
Startups play a crucial role in economic development by
navigating early challenges and successfully scaling up. The
scale-up phase is pivotal for a company's success, and failure
to prepare for scaling can hinder a startup's ability to expand
and thrive (Beckman, 2007).
In this study, we examined the impact of team demographic
characteristics, commitment, completeness, and cognitive
comprehensiveness on the scalability of startups, an area
that has received limited attention in existing literature. Our
results, as shown in Table4, indicated that the five factors
we studied significantly influence the scalability of startups.
These factors include demographic variables, team commit-
ment, cognitive comprehensiveness, team size, and integrity.
By validating these hypotheses, we found that human
capital plays a crucial role in startup scalability. Previous
research has focused on various aspects of entrepreneurial
teams, such as team composition characteristics and team
process variables, and their impact on new venture perfor-
mance. Our study delves deeper into the impact of team vari-
ables on startup scalability, highlighting the significance of
team diversity, demographic characteristics, cognitive com-
prehensiveness, team size, and integrity.
Our findings underscore the importance of fostering
team processes that cultivate commitment and comprehen-
sive decision-making for successful entrepreneurial teams.
Efficient entrepreneurial teams prioritize high team com-
mitment and embrace diverse perspectives for complex
decision-making. Cultivating trust and loyalty within teams
is essential for enhancing commitment and fostering innova-
tive decision-making.
This research sheds light on the influence of team fac-
tors on startup scalability within the Iranian context. Further
exploration of additional variables impacting scalability or
examination in different contexts can provide valuable insights
for policymakers and entrepreneurs seeking to support start-
ups in overcoming challenges and achieving scalability.
Suggestions andlimitations
This study has significant implications for future research
and entrepreneurs, highlighting the profound impact of team
factors on startup scalability. Future research should focus
on exploring team diversity and effectiveness, as well as
analyzing the influence of entrepreneurs' and team mem-
bers' personalities and thinking styles on startup scalability.
Understanding the dynamics between demographic charac-
teristics and individual traits is crucial for enhancing team
effectiveness and addressing challenges faced during the
transition from the startup phase to the scale-up phase.
Future research endeavors could identify effective entre-
preneurial traits at both individual and team levels that
impact startup scalability. Exploring the barriers entrepre-
neurs face during the startup-to-scale-up transition and iden-
tifying team characteristics that can effectively address these
challenges would be a valuable research focus. Additionally,
investigating the impact of trust and loyalty within entrepre-
neurial teams on team commitment is recommended.
While this study provides valuable insights, there are
opportunities for future research. One limitation is that the
five team dimensions were identified solely from existing
literature, suggesting the existence of potentially unidenti-
fied team dimensions. Future research should explore and
evaluate the impact of other team dimensions on startup
scalability. Additionally, studying the influence of these
dimensions on startup scalability in diverse contexts can
enrich our understanding of this critical area.
Acknowledgment Not applicable.
Code availability Not applicable.
Authors' contributions Faezeh Hanifzadeh. Original author Avail-
ability of data and materials: All data generated or analysed during
this study are included in this published article [and its supplementary
information files].
Funding Not applicable.
Declarations
Competing interests Not applicable.
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