Summary of Economic Doctoral dissertation: Relationship network, business model innovation and start-up performance of start-up firms in Vietnam

MINISTRY OF EDUCATION AND TRAINING
UNIVERSITY OF ECONOMICS HO CHI MINH CITY

TRAN NHA GHI

RELATIONSHIP NETWORK, BUSINESS MODEL
INNOVATION AND START-UP PERFORMANCE OF
START-UP FIRMS IN VIETNAM
Major : Business Administration
Code : 9340101
SUMMARY OF ECONOMIC DOCTORAL
DISSERTATION
Scientific instructors :
1. Assoc. Prof. Dr. Nguyen Quang Thu
2. Dr. Ngo Quang Huan

Ho Chi Minh City - 2019


These works are completed at

: University of Economics Ho Chi Minh City

Scientific instructor 1

: Assoc. Prof. Dr. Nguyen Quang Thu

Scientific instructor 2

: Dr. Ngo Quang Huan

Reviewer 1:...............................................................................................................................
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Reviewer 2:...............................................................................................................................
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Reviewer 3:...............................................................................................................................
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The dissertation will be defended in front of the Dissertation Evaluation Council at The
University of Economics Ho Chi Minh City at
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The dissertation can also be found at: ......................................................................................
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LIST OF THE AUTHOR’S PUBLICATIONS RELATED TO
THE DISSERTATION
Articles published on the Science Journals:
1. Nguyen Quang Thu, Ngo Quang Huan, & Tran Nha Ghi (2018). The relationship
between firm resources, dynamic capabilities and firm performance of start-up
firms in Ba Ria - Vung Tau province. Journal of Asian Business and Economic
Studies (JABES), 28 (12), 05–21.
2. Nguyen Quang Thu, Ngo Quang Huan, & Tran Nha Ghi (2018). Effect of relationship
quality on of business model innovation of start-up firms in Ba Ria - Vung Tau
province. Journal of Economics and Development (JED), 253(7), 59-69.
3. Nguyen Quang Thu, Ngo Quang Huan, & Tran Nha Ghi (2018). Effect of relationship
quality on start-up performance of start-up firms in Ba Ria - Vung Tau province.

Journal of Science Ho Chi Minh City Open University, 61(4), 67 – 79.
Articles published in the Scientific Conference:
4. Nguyen Quang Thu, Ngo Quang Huan, & Tran Nha Ghi (2016). The relationship
between firm resources, dynamic capabilities and business performance of
enterprises in Vung Tau City. Scientific conference of Entrepreneurship in
Vietnam: Opportunities and challenges in the period of integration, Tran Anh
Thanh Son (editor), University of Economics HCM City, 179-189.
5. Ngo Quang Huan, Bui Anh Tuan, & Tran Nha Ghi (2016). Research on the
relationship between the start-up environment and capability to the business
performance of small and medium enterprises in the Southern Vietnam. Scientific
conference of Entrepreneurship in Vietnam: Opportunities and challenges in the
period of integration, Tran Anh Thanh Son (editor), University of Economics
HCM City, 13-30.
6. Ngo Quang Huan, & Tran Nha Ghi (2018). Improving start-up performance through
business model innovation. Workshop of start-up science and small and mediumsized enterprise management in Vietnam in the context of the 4.0 revolution.
University Publishing House Ho Chi Minh City.


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CHAPTER 1: INTRODUCTION
1.1. The necessity of research problems
Derived from practical needs
In Vietnam, the private economic sector plays an important role in the economic development of the
country. Statistics show that about 97% of small and medium enterprises (SMEs) contribute 40% of the state
budget and create employment opportunities for 50% of the labor (Nguyen Trong Hoai, 2016). Start-up creates
new businesses and firms (Gartner, 1985). Therefore, start-up firms are the first step for the formation,
development and becoming mature firms and enterprises in later stages. According to GEM (2017), the rate of
maintaining business after starting up within the first 3.5 years accounted for 20.8%. Although this has been
improved when compared to 12.7% in 2016, the successful start-up rate is still very low.

The causes of the failure for start-up firms in the starting phase are very diverse such as: inappropriate
business strategy, lack of legal knowledge, "calling for capital" problems and administrative procedure barriers
(Y Nhi, 2017). Although start-up firms receive many priorities from the Government's development support
policies, the interest of society and the support of related parties. In fact, many start-up firms still have to face
many difficulties in accessing information and resources. Meanwhile, the information provided by state
agencies only partially meets the demand; there are many start-up firms without the initiative and sufficient
information. According to a survey by the Vietnam Chamber of Commerce and Industry (VCCI), the personal
relationships between firms and state agencies play an important role in the access to important information
and official documents in business activities.1
Trimi & Berbegal-Mirabent (2012) have studied the business model innovation (BMI) in the start-up
businesses; this new topic attracts increasing attention in scientific theory development. Each firm in an
industry has a different business model, built based on their available resources. Competitors can hardly imitate
or copy other business models to apply in their organizations (from resource point of view).
In summary, in the first phase, when start-up firms lack resources, implementing BMI to adapt to market
changes and improve operating performance requires external supporting resources. In this period, start-up
firms also need to receive the attention and support of the Government. Therefore, the question is how to access
the information and resources from individuals/organizations to supporting start-up activities? To answer the
above question, it is essential that the research issue on start-up firms' building relationship network with
government agencies and individuals/organizations to access information and resources, implement business
model innovation, improving performance is implemented in the current context.

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Derived from the theory gap
Foss & Saebi (2016) synthesized BMI studies in the period of 2000 - 2015 and proposed 4 future
research lines for BMI: (1) Building BMI concept and components of BMI; (2) Identify factors that are causes

and results of BMI; (3) Determine moderator variables between causes and results of BMI; (4): The marginal
impact of factors leading to BMI implementation and BMI results. However, until now, there has not been any
study to measure and verify the intermediary role of BMI between the network relationship and the start-up
performance of start-up firms.
1. The impact of BMI on start-up performance:
Studies on the effect of BMI on business performance of start-up firms are still limited. In addition, the
research results on this issue are different. For example, Zott & Amit (2008), Heij et al. (2014) and Anwar
(2018) found that BMI positively affected business performance. Meanwhile, Patzelt et al. (2008) proposed
there is no relationship between BMI and business performance. Halecker et al. (2014) found a negative
relationship between BMI and business performance. Therefore, this dissertation is conducted to test the
relationship between BMI and start-up performance of start-up firms in the transition economy. At the same
time, the dissertation will reaffirm the direction of impact of BMI on business performance.
2. The impact of relationship network on BMI:
There are few published studies about the influence of relationship network on BMI. Guo et al. (2013)
considered the impact of human capital and social capital on BMI, and Anwar & Shah (2018) assessed the
impact of financial relations, politics and business partnership networks on BMI. So far, there is no study on
the effect of relationship network on BMI for start-up firms published in Vietnam.
3. BMI concept approaches
BMI is approached by researchers in many different points of view. The approach of BMI from Zott &
Amit (2007) is most used by researchers for their studies. Some studies for this approach are of Guo et al.
(2013), Guo et al. (2015), Anwar & Shah (2018), etc. On the other hand, the study of Clauss (2017) applied
the BMI approach as a type II scale of Jarvis (2003), in which BMI is a model of result-cause scale. There are
few researchers applying this approach of BMI. Therefore, this dissertation will approach BMI according to
Clauss (2017).
To explain the formation of external resources for firms, previous studies such as Guo et al. (2013) and
Anwar & Shah (2018) used social network theory, social capital theory and innovation diffusion theory.
However, institutional theory has not been applied much in these studies. The institutional theory shows how
firms and businesses can increase the "acceptance" level of society. The higher the acceptance level of society
is, the more opportunities the firms will gain to access resources by their strategy.
In the initial phase, start-up firms enjoy preferential policies form the Government, support and concern

from relatives, friends and colleagues. So the research question is how do start-up firms access essential
information and resources? To answer this question, the dissertation uses institutional theory combined with


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the theory of social networks to explain the formation of external resources. This is a new explanation that
previous studies have not used. In this approach, the owners/senior managers play important roles in building
a network to help their firms access information and resources to implement BMI and improve business
performance.
In addition, according to the evaluation of GEM (2017) about Vietnam's business conditions, "the
environmental dynamism of domestic market" is ranked highest in the start-up ecosystem. Thus, it is very
necessary that the effect of the environmental dynamism on the relationship between BMI and the business
performance of firms in Vietnam to be verified.
Therefore, in order to examine the role of relationship network in conducting the current business model
innovation, contributing to improving the start-up performance of start-up firms, the research topic
“Relationship network, business model innovation and start-up performance of start-up firms in
Vietnam” is necessary to be implemented in the current context.
1.2. The general research framework of the dissertation
The implementation of BMI through relationship network will contribute to improving the start-up
performance of start-up firms, which is presented in the general research framework. Relationship network
directly affects start-up performance and indirectly affects start-up performance with BMI as an intermediate
variable. The environmental dynamism of the domestic market is considered to be the moderator of the
relationship between BMI and start-up performance of start-up firms.
Based on the general research framework, the dissertation concludes new research points that previous
studies have not mentioned as follows:
New point 1: The relationship between the relationship network, BMI and start-up performance of startup firms has not been verified in the transition economic market. Also, according to the latest review of the
author, this relationship has not been explored in the developed economic market.
New point 2: The combined approach of institutional theory and social network theory to explain the
formation of external resources to implement BMI of start-up firms has not been applied in previous studies.

New point 3: The approach of BMI scale according to Clauss (2017), which is a scale with the form of
hierarchical component models (HCMs) has not been widely tested.
1.3. Research objectives
General objective: The dissertation examines the relationship between the relationship network, BMI and the
start-up performance of start-up firms. From the achieved findings and results, the dissertation provides the
implications for management to enhance the development of relationship networks, promote the


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implementation of BMI, and contribute to the improvement of start-up performance of start-up firms in
Vietnam.
Detailed objectives: In order to achieve the general objective, the dissertation needs to fulfill the following
specific objectives:
1. Building a model of relationship between relationship network, BMI and start-up performance of
start-up firms;
2. Verifying the relationship between relationship network, BMI and start-up performance of start-up
firms;
3. Verifying the regulation of the environmental dynamism of the domestic market on the relationship
between BMI and start-up performance of start-up firms;
4. Suggesting managerial implications to improve start-up performance through the relationship
network and BMI implementation.
1.4. Research Methodology
1.4.1. Qualitative research methods
Interview method is used in qualitative research. The dissertation collected ideas and opinions of experts
who are experienced in the field of start-up activities. Qualitative research methods are implemented to
standardize theoretical models, explore research and adjust the scale. Implementation techniques are direct
individual interview with experts based on designed outline. Interview results will be aggregated in order to
form a draft scale to serve pilot study in quantitative research and formal quantitative research.
1.4.2. Quantitative research methods

Pilot study: After data entry, research data is tested for the reliability of scales with Cronbach’s Alpha
reliability coefficient. Next, exploratory factor analysis (EFA) is applied to check the convergence value and
distinctive value of observed variables in the scale. The purpose of this method is to preliminary assess the
scale of research concepts in theoretical models before conducting formal research.
Formal quantitative research: The scales will be tested with Cronbach’s Alpha coefficient and EFA
analysis again. Next, the scale will be evaluated by measurement model analysis and linear structure model
through PLS-SEM software.
1.5. Research objects and scope
Research objects: Research concepts such as relationship networks, BMI, start-up performance of start-up
firms and their relationships.
Subjects of the survey: The owners, the board of directors, the capital contributors, the founders and
representatives of start-up firms with operating time less than 5 years (according to Decision No. 844/QD- TTg).


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Research scope: the research is conducted with start-up firms in the area of Ho Chi Minh city, Ba Ria - Vung
Tau, Dong Nai, Binh Duong and some other provinces.
1.6. The significance of the research
1.6.1. Practical significances
For start-up firms: start-up firms recognize the importance of building a relationship network to
supplement information and resources in the early stages of operation. Start-up firms use various resources to
support BMI, increase start-up performance and minimize failure risks. At the same time, start-up firms realize
the importance of implementing BMI in order to adapt to the changing environment.
For policy makers: the research results suggest ideas to help policy makers issue effective and detailed
policies and solutions to support start-up firms. A number of official documents (Decisions, Decrees, Plans,
Laws, etc.) have been issued without specifically mentioning the practical detailed content to support business
model innovation. Therefore, the later documents need to supplement the content to support business model
innovation for start-up firms.
For start-up consultancies: Start-up consultancies realizes their missions in providing training services,

information support on laws and tax policies, especially consulting in planing and building appropriate
business model, in order to help start-up firms improve management skills, professional skills and select
appropriate business models for their start-up businesses.
1.6.2. Theoretical significances
Firstly, the dissertation has synthesized institutional theory, social network theory, innovation theory
and VARIM theory. In addition, the dissertation has systematized the relationships between the theories to
build the strategy of start-up firms in the transition economy.
Secondly, the proposed research model is combined from background theories and tested in Vietnam
market with the following results:
- Relationship network consists of 3 components (relations with government officials, social relations
and business partnerships) that positively affect BMI and the start-up performance of start-up firms.
- BMI is a concept with a high-level structure, a scale of decentralized factor model (results - causes
scale), which is inherited from the study of Clauss (2017). The results of verification in the Vietnamese market
show that BMI reaches the permitted value and has a positive impact on start-up performance of start-up firms.
- Researchers can make a general assessment of the relationships between the theories mentioned and
re-test the above relationships in other areas (space, specific occupations).
Finally, the dissertation has adjusted, supplemented and tested the research scale and developed a
particular set of observed variables for specific scales of start-up activities in Vietnam.


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CHAPTER 2: LITERATURE REVIEW AND RESEARCH MODEL
2.1. Institutional theory
North (1990) defined institutions as "social playing rules", which are human-made rules and restrictions
that guide and regulate what an individual should and should not do in some certain cases. It is a regulatory
framework for human interaction. Scott (1995) defined institutions including constraints and actions that
belong to cognition, norms and laws to create stability and meaning of social behavior.
The view of institutional theory in economics and sociology is that every business that adheres to
institutional constraints will be accepted by society (legitimacy). When accepted, businesses are more likely

to "survive". "Acceptance of society" becomes the key concept in institutional theory. Aldrich and Fiol (1994)
pointed out two types of acceptance. Acceptance in awareness: awareness of entities (businesses / industries)
or practices (systems, management policies) can be spread. Socio-political acceptance: the extent to which
society (stakeholders, the public, officials) considers an entity/practice to be consistent with social and legal
standards.
2.2. Social network theory
The relationship network of start-up firms is mentioned including: formal networks and informal
networks. In particular, formal networks are the network of official relations with banks, Government agencies,
lawyers, etc. and informal networks are those with family, friends and colleagues. In the first phase of
operation, start-up firms are more interested in informal relationship networks than formal networks (Peng,
2000, p. 158).
2.3. Theory of Innovation
Business model innovation (BMI): Baden-Fuller & Mangematin (2013), Zott & Amit (2013) and
Spieth et al. (2014) have presented three components of a business model: value creation, value proposition
and value capture. BMI is innovating and renewing the above three components.
Clauss (2017) developed the measurement of BMI concept to ensure reliability and validity. The
results show that the compositions of BMI include value creation innovation, value proposition innovation
and value capture innovation. Value creation innovation has 4 components including new capabilities, new
technology/equipment, new partners, and new processes/structures. In value proposition innovation, there are
4 components including new offerings, new markets, new distribution channels, new customer relationships.
Value capture innovation has 2 components including new revenue model and new cost structure.
2.4. VARIM theory
VARIM theory consists of 5 components.
Value: The business model provides benefits that customers perceive to be valuable to them. It is
measured through satisfaction and loyalty, market share, benefits provided to customers compared to
competitors' offerings, reputation/image in customers' perceptions.


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Adaptability: Can the business model be reformatted to provide the benefits that customers find valuable
to them? It is measured through the number and variety of new benefits provided by the business, the level of
improvement that customers perceive, revenue from new products, flexibility of valuable competencies.
Rareness: Is business unique when it provides this benefit to customers? It is measured through the
number of competitors or businesses with alternative products, the level of benefits compared to competitors.
Inimitability: Is the customer benefits difficult for competitors to imitate or replace? It is measured
through number of imitated objects, inimitable resources, inimitable scope of activities.
Monetization: Does the business make money from providing benefits to customers? Measurements
include ROS, ROE, reasonable price, importance and value of additional assets.
2.6. Research models and hypotheses
Relationship with Government officials, BMI and start-up performance of start-up firms:
Officials at all levels of government have considerable power in approving projects and allocating
resources (Walder, 1995). Relationship with government officials is recognized as useful in emerging markets,
because it provides operational performance for venture projects (Kotabe et al., 2017; Li & Zhang, 2007).
Research by Du & co (2016) shows that in China, venture business projects rely on the network of political
relationship to survive and develop. Therefore, firms should create relationships with government officials
because it affects their performance (Peng, 1997).
According to the results of some previous studies, relationship with government officials will simplify
procedures for government and banking institutions (Peng & Luo, 2000; McMillan & Woodruff, 1999; Meyer
& Nguyen, 2005). Start-up firms with strong relationship with Government officials will approach many
donations, aid and government support programs. Firms will be supported with training to improve their
capacity (knowledge/expertise, capacity to meet environmental changes, etc.), improving and developing
technology. Start-up firms are also introduced to business partners, investors, support funding for testing,
making sample products and changing the process accordingly.
In addition, relationship with Government officials helps firms and businesses access Governmentfunded projects or customers (Le et al., 2006). Start-up firms will be supported in developing new
products/services, intensive training on construction and product development, market testing, accessing to
foreign markets, participating in available distribution channels and connecting customers.
Start-up firms builds relationships with Government officials to help reduce transaction costs in
registration and business activities, such as access to information, land, and other operating licenses (Meyer &
Nguyen, 2005). In a transitional economy, the costs for these barriers are very significant and sometimes very

high for private enterprises (Tenev et al., 2003). Finally, start-up firms will be supported in commercialization
of the scientific research results, exploitation and intellectual property development in order to generate more
revenue for start-up firms.


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Thus, start-up firms’ strong relationship with government officials will affect the business model (Gao
et al., 2017; Wu, 2011). From the above-mentioned backgrounds, the dissertation proposes hypotheses H1a,
H1b, H1c and H1d are proposed as follows:
Hypothesis H1a: Strong relationship of start-up firms with government officials has a positive impact
on start-up performance of start-up firms;
Hypothesis H1b: Strong relationship of start-up firms with government officials has a positive impact
on BMI's value creation innovation;
Hypothesis H1c: Strong relationship of start-up firms with government officials has a positive impact
on BMI's value proposition innovation;
Hypothesis H1d: Strong relationship of start-up firms with government officials has a positive impact
on BMI's value capture innovation;
Social relations, BMI and start-up performance of start-up firms:
For many small firms with limited resources, business performance depends on the ability to obtain
external resources (Partanen et al., 2011). Some studies have confirmed that close-kit networks can increase
solid returns (Aldrich et al., 1987), enterprise development (Shaw, 2006) and sales growth (Antončič, 2002a;
Tuli, 2006).
When start-up firms connect with start-up associations/clubs, they will be supported free training courses
and start-up coaching courses to improve and develop new capabilities. Start-up firms will get legal support,
join a common work-space to experience and learn from the experts in the field (process innovation). Start-up
associations/clubs supports cooperation, connecting members with each other, with start-up ecosystems and
other start-up associations/clubs (new partners). Firms with strong relationships will have many opportunities
to interact and connect with the desired business partners (Wong & Ellis, 2002).
When participating in start-up associations/clubs, start-up firms will be connected with consultants,

investors, entrepreneurs, start-up support organizations, and policy makers to create bridges and spreading
support solutions for start-up communities (product development, distribution channels and relationships with
new customers). In addition, start-up associations/clubs have links with the surrounding provinces and other
provinces to expand the market of start-up products (developing new markets). Thus, through the relationship
network, managers of firms recognize business opportunities (Ma et al., 2011; Tang, 2010), access to external
information and resources (Peng & Luo, 2000). Firms with strong relationships will successfully persuade
stakeholders to accept and promote support for new business models (Guo et al., 2013).
According to Birley (1985), in the early stages of business development, informal contacts with business
associates, family members and friends will provide the sources of labor and material facilities for businesses.
Start-up clubs shares business opportunities, cross-selling among members of the club, and guaranteeing large
orders (developing new revenue models). Start-up club builds a start-up fund contributed by members to


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support capital. In addition, the relationship of start-up firms with relatives, friends and colleagues will help
businesses raise capital quickly, simple procedures, low costs (developing new cost structures). , the
hypotheses H2a, H2b, H2c and H2d are stated as follows:
Hypothesis H2a: Strong social relations of start-up firms have a positive impact on start-up performance
of start-up firms;
Hypothesis H2b: Strong social relations of start-up firms have a positive impact on BMI's value creation
innovation;
Hypothesis H2c: Strong social relations of start-up firms have a positive impact on BMI's value
proposition innovation;
Hypothesis H2d: Strong social relations of start-up firms have a positive impact on BMI's value capture
innovation;
Relationship with business partners, BMI and start-up performance of start-up firms:
Good business relationship with suppliers can offer quality materials, good service and timely delivery.
Similarly, good relationships with buyers can promote buyers' loyalty, sales volume and reliable payment.
Moreover, good relationships with executives from competitors can facilitate internal cooperation and implicit

collusion, minimizing uncertainty (Peng & Luo, 2000). These relationships are seen as opportunities or as a
lubricant to reduce transaction costs (Williamson, 2010). Firms with strong relationships with reputable
partners will have access to other resources (Stinchcombe, 1965; Stuart, 2000), such as the high quality of
labor, financial resources, technology and support of Government. These resources are very important for the
growth of start-up firms.
Anwar & Shah (2018) argued that firms communicating well with business partners will get new ideas,
new business opportunities, capture customer needs, new knowledge and technology. Newly established
businesses with good relationship with managers of mature enterprises will easily access new information,
resources and new knowledge (Li & et al., 2015), which will affect the innovation of business (Breuer &
Ludeke-Freund, 2017). DePropris (2002) argued that process innovation is related to cooperation with
suppliers. Businesses' increased customer relations will positively impact product innovation activities (Gao
et al., 2017; Wu, 2011). When connecting with other partners and businesses, start-up firms often have
advantages in reducing costs.
The relationship of senior managers will promote BMI activities of enterprises (Guo et al., 2013). The
design of a new business model requires businesses to have a lot of information about customers, suppliers
and competitors (Timmers, 1998), and must know how to develop, share and reformat resources. On that basis,
the hypothesis H3a, H3b, H3c and H3d are proposed:
Hypothesis H3a: Strong relationship of start-up firms with business partners has a positive impact on
start-up performance of start-up firms;


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Hypothesis H3b: Strong relationship of start-up firms with business partners has a positive impact on
BMI's value creation innovation;
Hypothesis H3c: Strong relationship of start-up firms with business partners has a positive impact on
BMI's value proposition innovation;
Hypothesis H3d: Strong relationship of start-up firms with business partners has a positive impact on
BMI's value capture innovation;
The relationship between BMI and start-up performance of start-up firms

Capability innovation has a direct impact on the performance of businesses (Alam, 2013). Reichert &
Zawislak (2014) argued that technology capability has a positive impact on business performance. Atalay et al
(2013) stated that process innovation directly impacts on business performance. Corporate profits are improved
from product innovation, distribution channels and new markets which have not been served. The reality shows
that the profits of enterprises mainly come from existing customers (Nguyen Dinh Tho & Nguyen Thi Mai
Trang, 2009).
BMI allows businesses to regain position and profit in the current market (Johnson et al., 2008). The
new business model has a strong impact on performance compared to the old model (Nunes & Breene, 2011).
In addition to securing profits in the current market, BMI helps businesses expand their reach by penetrating
new markets. The components of the new business model focus on targeted customers who are not yet served
(Aspara et al., 2010) and create new markets (Zott & Amit, 2007). Exploiting new opportunities can help
businesses maintain performance (Velu & Stiles, 2013).
Firms renew revenue models to create long-term revenue and independent of existing revenue. In the
early stages, start-up firms have incurred many costs for fixed investment and investment activities. The
structure of costs determines the performance of the business. Extend the cost structure to determine the types
of operational costs related to the business at the lowest level. Foss & Saebi (2016) stated BMI will reduce
costs.
BMI provides productivity, return on revenue, market value (Andreini & Bettinelli, 2016) and financial
performance for businesses (Pedersen et al., 2016). BMI provides significant financial performance in a
developing economy (Gerdoçi et al., 2017). Business model is an important factor to improve business
performance (Dunford et al., 2010). From the above mentioned bases, the proposed H4 H5, H6 hypotheses are
proposed:
Hypothesis H4: BMI's value creation innovation has a positive impact on start-up performance of startup firms;
Hypothesis H5: BMI's value proposition innovation has a positive impact on start-up performance of
start-up firms;


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Hypothesis H6: BMI's value capture innovation has a positive impact on start-up performance of startup firms;

The regulation of the environmental dynamism of domestic market on the relationship between BMI
and start-up performance of start-up firms
In a dynamic market, implementing BMI is necessary to replace the existing business model (McGrath,
2010) to address threats to the current business model, creating a fit for the new environment. (Giessen et al.,
2010) and pursuing a solid existence (Hamel & Välikangas, 2003). Therefore, in dynamic environments, BMI
has a stronger impact on business performance than in less dynamic environments. Because, in dynamic
environments, businesses have to deal with more threats to the existing business model (Heij et al., 2014).
Therefore, in dynamic environments, the implementation of BMI is expected to have a stronger impact on
performance than in the less dynamic environment. Therefore, in the dynamic market of Vietnam today, the
hypotheses H7a, H7b and H7c are stated:
Hypothesis H7a: The environmental dynamism has a regulation impact on the relationship between
BMI's value creation innovation and start-up performance of start-up firms;
Hypothesis H7b: The environmental dynamism has a regulation impact on the relationship between
BMI's value proposition innovation and start-up performance of start-up firms;
Hypothesis H7c: The environmental dynamism has a regulation impact on the relationship between
BMI's value capture innovation and start-up performance of start-up firms;


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H1a (+)

H1b (+)

Relationship with
Government officials

H1c (+)

H2b (+)

BMI: value
creation innovation
H4 (+)

H1d (+)

Social relations

H2c(+)

BMI: value
proposition innovation

Start-up
performance

H5 (+)

H7a (+)
H3b (+)

H6 (+)
H3c (+)

H2a (+)

Relationship with
business partners

H2d (+)

BMI: value capture
innovation

H3d (+)

H3a (+)

Figure 2.1. Proposed research model
Source: Author's proposal

H7c (+)

H7b (+)


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CHAPTER 3: RESEARCH METHODOLOGY
3.1. Research process
This research was conducted in two main stages: (1) preliminary research by preliminary qualitative
methods and quantitative pilot study, (2) formal research by quantitative methods.
Preliminary research: Preliminary qualitative research: From the research objectives, the dissertation
synthesizes relevant theoretical foundations (background theory, research concepts and previous studies). On
that basis, the research model, the hypotheses and the observed variables to measure scales of the research
concepts are formed. Through qualitative method of interviews with experts, the research model is evaluated
to standardize theoretical models, appear new factors and adjust/supplement the scale for clarity and relevance
in research context. Quantitative pilot study: The scale is used to test the sample of 50 start-up firms by
convenient sampling method and verify Cronbach’s Alpha reliability and EFA analysis before conducting

formal research.
Formal research: The purpose of this method is to assess the suitability of the measurement model and
structural model using the PLS-SEM method. Evaluating the measurement model: the scales are tested by
composite reliability, convergent validity, uni-directional and discriminant validity. Evaluating the
decentralized factor model by "Repeated Indicators Approach" through two stages. Evaluating the structural
model with Bootstrapping (N = 5000): determination coefficient (R2), predictive relevance (Q2), effect size
(f2).

3.2. Results of qualitative research
3.2.1. Results of theoretical model adjustment
The research data of interviews and research theory show that:
(1) The relationships between research concepts (relationship network, BMI and start-up performance of startup firms) are confirmed. The components of relationship network (relationships with government officials,
social relations and relationships with business partners) are clearly affirmed. The components of BMI are
complete, specific and consistent with the business model of start-up firms in Vietnam.
(2) The important roles of owners/senior managers are confirmed in building a network of relationship with
related parties to implement BMI and contribute to improving start-up performance. This shows that there is
an interaction between the relationship network, BMI and the start-up performance of start-up firms. Moreover,
the environmental dynamism of Vietnam market is highly appreciated so its role in promoting BMI to improve
start-up performance is necessary to be examined and verified.
In conclusion, the theoretical model is evaluated to be consistent with the reality and research context of
Vietnam market.
3.2.2. Results of scale adjustment


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From the suggestions to adjust the scale, the author summarizes and adjusts the scales of research concepts:
Table 3.1. The scale of relationship network
Name

Scale

No. of
observation

Relationship network
Tiesgov
Relationship with Government
officials
Soties
Social relations

3
4

Tiesmanager

Relationship with business
partners
Source: Adjusted results from the original scales

4

Sources

Peng & Luo (2000)
Le et al. (2006), qualitative research
results
Peng & Luo (2000), qualitative
research results

Table 3.2. BMI scale
Name

Scale

No. of
observation

Value creation innovation (VCI)
CAP
New capabilities
TEC
New technology
PART
New partners
PRO
New processes
Value proposition innovation (VPI)
OFF
New offerings
MARK
New markets
CHAL
New distribution channels
REL
New customer relationships
Value capture innovation (VCIN)
REV
New revenue model

COST
New cost structure
Source: Adjusted results from the scale of Clauss (2017)

Sources

3
3
4
3

Clauss (2017)
Clauss (2017)
Clauss (2017)
Clauss (2017)

3
3
3
3

Clauss (2017)
Clauss (2017)
Clauss (2017)
Clauss (2017)

4
3

Clauss (2017)

Clauss (2017)

Table 3.3. The scales of environmental dynamism and start-up performance
Name

Scale

ENVIRDYNA Environmental dynamism
STARTPERF Start-up performance

No. of
observation
3
3

Sources
Jansen et al. (2006)
VARIM theory, Ju et al. (2019),
qualitative research results

Source: Adjusted results from the original scales
3.3. Quantitative research method
Data collection method: To collect data, the dissertation mainly sends online survey via email and
social networks (Facebook and Zalo) with Microsoft Forms tool. The survey was sent to start-up


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communities in localities (Ho Chi Minh City, Ba Ria - Vung Tau, Dong Nai, Binh Duong, etc.), SIYB startup clubs (promoting start-up business), and Vietnamese start-up community.
Sampling method: Due to time constraints, the dissertation uses convenient sampling method. Start-up

firms are classified according to criteria such as size (number of employees), type and industry of operation.
Data analysis method: The process of data analysis is conducted through two stages in quantitative
research:
Stage 1: Preliminary quantitative research with sample size n = 50; Cronbach's Alpha reliability
coefficient testing and EFA analysis.
Stage 2: Formal quantitative research with sample size N = 150:
Step 1: Evaluate Cronbach’s Alpha reliability coefficient and EFA analysis.
Step 2: Evaluate the measurement model: composite reliability, convergent validity, discriminant
validity, multicollinearity, relevance of the model.
Step 3: Evaluate the Hierarchical Compositional Models (HCMs): apply the technique of "Repeated
Indicators Approach".
Step 4: Evaluate the internal model/structure: determination coefficient R2, assess the effect size (f2),
estimate the path coefficient, assess the predictive relevance (Q2).
3.4. Preliminary evaluation of the scale
After a small sample test of 50 start-up firms with SPSS 23 software, most of the scales mentioned in
the theoretical model meet the requirements of reliability, convergent validity and discriminant validity. The
variable soties4 “Firm has relationships with universities and research institutes” are excluded from the social
relations scale. However, due to limitations of small samples, this observed variable is retained in the official
survey questionnaire for consideration.
3.5. Official research sample
The research sample is officially selected by convenient method, online survey via Microsoft Forms.
Due to limitations on the time of the dissertation, the results of online surveys are set to the time taken from
the beginning of April 20, 2019 to the ending date of May 25, 2019.
Hair et al. (2010) suggested that the sample size must be at least 100 to 150. Therefore, based on the
statement of Hair et al. (2010), the dissertation decided to use the research sample size of 150 start-up firms
for official quantitative research.


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CHAPTER 4: RESEARCH FINDINGS
4.1. Characteristics of research samples
Type of operation: The start-up firms operate mainly in the form of private enterprises (accounting for
42.7%) and limited liability companies (accounting for 43.3%). Scope of activities: The start-up firms operate
mainly in the service sector (accounting for 49.3%) and trading and commerce (accounting for 30%). Labor
size: The number of labor of start-up firms is mainly under 10 employees (accounting for 43.3%) and from 10
to 30 people (accounting for 41.3%). Location: Due to the random data collection method, the number of startup firms has not been evenly distributed among provinces. The most surveyed start-up firms are in Ba Ria Vung Tau province (accounting for 54%).
4.2. Scale testing
Cronbach's Alpha reliability coefficient testing of scales: relationship network (relationship with
government officials, social relations, relationship with business partners), BMI (value creation innovation,
value proposition innovation, value capture innovation), environmental dynamism, start-up performance of
start-up firms. The results show that all scales are reliable because they have Cronbach’s Alpha coefficient>
0.6 and the total correlation coefficient> 0.3. In the scale of new cost structure, the variable cost4 has this
coefficient<0.3 and is eliminated. Therefore, the scales ensure reliability and eligibility for EFA analysis.
The results of EFA analysis performed in each group show that all scales ensure permissible value:
KMO value> 0.5 and <1; Sig value of Barlett test < 0.05; total variance extracted > 50% and load factor > 0.5.
Therefore, the scales reach convergent validity and discriminant validity.
4.3. Evaluation of the measurement model
The results show that the scales have composite reliability (CR) > 0.7; The lowest CR value is 0.903
and the highest CR value is 0.919. The scales are reliable. The value of variance extract (AVE) of scale > 0.5.
The matrix coefficient Fornell - Larcker shows that the top coefficients are larger than the coefficients in the
same column. Therefore, the scales are differentiated. The VIF value of the observed variables is < 5, so the
model does not have multicollinearity phenomenon. The results show that the SRMR of the critical model and
the estimated model are < 0.12. Thus, the estimated model meets the requirement of survey data compatibility
compared with market data.
4.4. Evaluation of Structural Equation Model
4.4.1. Evaluation of adjusted coefficient of determination (R2adj)
The level of explanation of network relationship on BMI (VCI, VPI, VCIN) is 0.379, 0.322 and 0.199
respectively. The results show that the explanation level of R2adj is moderate (range from 0.25 to 0.5, except
R2adj of VCIN = 0.199 < 0.25). The network relationship and BMI have a simultaneous level of explanation on

the start-up performance of start-up firms with R2adj = 0.814. The adjusted coefficient of determination R2adj =
0.814 > 0.75 is considered to be significant (Hair et al., 2017, p.206).


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Table 4.1. Results of Structural Equation Modeling
Estimation
Standard
t
VIF
P
β
B (Bootstrap) deviation
Relationship with Government officials --->BMI and start-up performance of start-up firms
TIESGOV -> VCI
0,483
0,485***
0,061
7,895
1,169
0,000
TIESGOV -> VPI
0,317
0,319***
0,069
4,633
1,169
0,000
TIESGOV -> VCIN

0,375
0,377***
0,070
5,326
1,169
0,000
TIESGOV -> STARTPERF
0,115
0,113***
0,047
2,473
1,635
0,008
Social relations ---> BMI and start-up performance of start-up firms
SOTIES -> VCI
0,125
0,129ns
0,078
1,601
1,318
0,109
SOTIES -> VPI
0,276
0,278***
0,071
3,880
1,318
0,000
SOTIES -> VCIN
0,072

0,074ns
0,079
0,914
1,318
0,361
SOTIES -> STARTPERF
0,119
0,117**
0,050
2,373
1,480
0,018
Relationship with business partners --> BMI and start-up performance of start-up firms
TIESMANAGER -> VCI
0,175
0,179**
0,075
2,328
1,282
0,020
TIESMANAGER -> VPI
0,165
0,170**
0,068
2,415
1,282
0,016
TIESMANAGER -> VCIN
0,123
0,127ns

0,090
1,376
1,282
0,169
TIESMANAGER -> STARTPERF
0,101
0,099**
0,042
2,416
1,391
0,016
BMI ---> Start-up performance of start-up firms
VCI -> STARTPERF
0,358
0,362***
0,059
6,061
2,415
0,000
VPI -> STARTPERF
0,255
0,256***
0,049
5,175
2,132
0,000
VCIN -> STARTPERF
0,230
0,226***
0,054

4,215
1,772
0,000
Moderator variables
ENVIRDYNA -> STARTPERF
0,061
0,062
0,045
1,375
1,429
0,169
VCI*ENVIRDYNA -> STARTPERF
-0,065
-0,068ns
0,054
1,205
2,197
0,228
VPI*ENVIRDYNA -> STARTPERF
-0,063
-0,059ns
0,048
1,304
1,499
0,192
VCIN*ENVIRDYNA -> STARTPERF
0,056
0,054ns
0,046
1,210

1,830
0,226
2
2
2
2
2
R
=
0,379;
R
=
0,322;
R
=
0,199;
R
=0,814
R adj
VCI
VPI
VCIN
STARTPERF
f2SOTIES->STARTPERF = 0,056; f2TIESGOV->STARTPERF = 0,047; f2TIESMANGER2
2
>STARTPERF = 0,042; f VCI->STARTPERF = 0,307; f VCIN->STARTPERF = 0,173;
f2VPI->STARTPERF = 0,176;
Effect size f2
f2TIESGOV->VCI = 0,329; f2TIESMANGER->VCI = 0,039
f2TIESGOV->VCIN = 0,153

f2SOTIES->VPI = 0,087; f2TIESGOV->VPI = 0,130; f2TIESMANGER->VPI = 0,032
Relationship

Note: *, **, *** corresponds to 10%, 5% and 1% significance levels; ns (non-significant): not statistically significant

Source: Processing results from the author's survey data


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Figure 4.1. Measurement model at stage 2
Source: Processing results from the author's survey data
4.4.2. Evaluate the multicollinearity
Based on Table 4.1, the VIF value is lower than the allowed threshold (< 5). Therefore, the estimated
structure model does not have multicollinearity. The level of explanation of the independent variables on the
dependent variables is reliable.
4.4.3. Evaluate the effect size (f2)
Evaluate the effect of relationship network on BMI:
▪ The effect size of relationship with government officials on BMI: the relationship with government
officials has strongest and greatest effect value to VCI (f2 = 0.329 <0.35); followed by moderate effect to VCIN
(f2TIESGOV-> VCIN = 0.153 > 0.15); and finally, moderate and lowest effect to VPI (f2TIESGOV-> VPI = 0.130 < 0.15).
▪ The effect size of relationship with business partners on BMI: The effect size is assessed as weak (f2
<0.15). In particular, relationship with business partners weakly affect VCI (f 2 = 0.039 < 0.15), and the effect
has the lowest value to VPI (f2TIESGOV-> VPI = 0.032 < 0.15).
▪ The effect size of social relations on VPI is low (f2SOTIES-> VPI = 0.087 < 0.15).
Evaluate the effect of relationship network on start-up performance of start-up firms:
In relationship network, social relations have the greatest effect on the start-up performance of start-up
firms, followed by relationship with government officials in second place. Finally, relationship with business
partners has the lowest effect on start-up performance of start-up firms.
Evaluate the effect of BMI on start-up performance of start-up firms:

The effect size of BMI on the start-up performance of start-up firms is moderate (f2 <0.35). In which,
the effect of VCI on start-up performance has the highest value of f2VCI-> STARTPERF = 0.307 < 0.35; next is VPI
with the value of f2VPI-> STARTPERF = 0.176 > 0.15; and finally is VCIN with f2VCIN-> STARTPERF = 0.173 > 0.15.


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4.4.4. Estimate the path coefficients and confidence intervals
The results show that the difference between Bootstrapping (N = 5000) and the original weight is very
small. The path coefficient is within the confidence range from 2.5% to 97.5%. Therefore, estimating the path
coefficient is reliable.
4.4.5. Evaluate the predictive relevance Q2 by Blindfolding
The predictive relevance of relationship network and BMI to start-up performance of start-up firms are
very strong (Q2 = 0.532 > 0.35). Relationship with government officials and relationship with business partners
have a moderate predictive relevance level (Q2 = 0.151 < 0.35) to VCI. Relationship with government officials
has predictive relevance to VCIN at a moderate level (Q2 = 0.168 > 0.15). Relationship with government
officials, social relations and relationships with business partners have predictive relevance to VPI at a
moderate level (Q2 = 0.102 < 0.15).
4.4.6. Research hypotheses testing
Based on the P-value from the estimated model structure results, the results of hypothesis testing are
concluded and summarized. The dissertation proposed 18 hypotheses. The research findings have supported
12 accepted hypotheses and 6 hypotheses are rejected.
4.5. Discussing research findings
4.5.1. Comparing the research findings of the dissertation with the background theories
Research findings of the dissertation show that the owners/senior managers of start-up firms building a
relationship network with government officials, social relations and business partners will promote BMI (VCI,
VPI, VCIN). Research results are consistent with the views of institutional theory and social network theory.
The dissertation used the innovation theory and VARIM theory to explain the relationship between BMI and
start-up performance of start-up firms. Firms' implementation of BMI will contribute to improving business
performance (Morris et al., 2015; Amit & Zott, 2012, etc.). The research results of the dissertation show that

the implementation of BMI contributes to increase start-up performance of start-up firms. The results are
consistent with the innovation theory of Schumpeter (1943) and VARIM theory.
4.5.2. Comparing the research findings of the dissertation with previous studies
1) The impact of relationship with government officials on BMI and start-up performance of start-up firms:
Hypothesis H1a stated that strong relationship with government officials will have a positive impact on
the start-up performance of start-up firms. The estimated results show that this hypothesis is accepted (β =
0.113, p = 0.008 <0.01). Research results are similar to previous studies in the world such as Peng (1997), Du
et al. (2016), Kotabe et al. (2017). Relationship with government officials will have a positive impact on BMI
(VCI, VPI, VCIN) which are shown in the hypotheses H1b, H1c and H1d. The estimation results show that
the above hypotheses are accepted (H1b: β = 0.485, p = 0,000 <0.01; H1c: β = 0.319, p = 0.000 <0.01 and
H1d: β = 0.377, p = 0,000 <0.01). Research results are similar to previous studies. For example, research by
Wu (2011), Guo et al. (2017), Anwar & Shah (2018), Tan & Litsschert (1994).
2) The impact of social relations on BMI and start-up performance of start-up firms:


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Hypothesis H2a about strong social relations of start-up firms have a positive impact on start-up
performance. This hypothesis is accepted (H2a: β = 0.117, p = 0.018 <0.05). There have not been many studies
examining this relationship. In hypothesis H2c, strong social relations of start-up firms have a positive impact
on BMI's VPI. Test results show that this hypothesis is accepted (H2c: β = 0.278, p = 0.000 <0.01). Because
no previous research has examined this relationship, the research results emphasize the role of social relations
in value proposition innovation of BMI. With the data of this study, hypothesis H2b and H2d are rejected
(H2b: β = 0.129, p = 0.109> 0.1; H2d: β = 0.074, p = 0.361> 0.1). Research results show that social relations
of start-up firms do not impact VCI.
3) The impact of relationship with business partners on BMI and start-up performance of start-up firms:
Hypothesis H3a stated that strong relationship of start-up firms with business partners has a positive
impact on start-up performance of start-up firms. The estimation results show that this hypothesis is accepted
(H3a: β = 0.099, p = 0.006 <0.05). Research results are similar to previous studies such as Peng & Luo (2000),
Su et al. (2013). Test results show that the hypotheses H3b and H3c are accepted (H3b: β = 0.179, p = 0.020

<0.05; H3c: β = 0.170, p = 0.006 <0.05). These relationships have not been verified from previous studies, but
some previous studies have shown a positive impact of relationship with business partners on BMI, such as
Anwar & Shah (2018), Gao et al. (2017), Partanen et al. (2011). Hypothesis H3d stated that relationship with
business partners will affect the same direction on VCIN. Test results show that this hypothesis is not
statistically significant (H3d: β = 0.127, p = 0.169> 0.1). This relationship has not been verified from previous
studies.
4) The impact of BMI on start-up performance of start-up firms:
Hypotheses H4, H5 and H6 suggested that BMI (VCI, VPI, VCIN) will have positive impacts on the
start-up performance of start-up firms. Test results show that the above hypotheses are accepted (H4: β = 0,362,
p = 0,000 <0,001; H5: β = 0,256, p = 0,000 <0,001; H6: β = 0,226, p = 0,000 <0.001). Research results of the
dissertation contribute and affirm the positive impact of BMI on the start-up performance of start-up firms in
this perspective.
5) The regulation of the environmental dynamism of domestic market on the relationship between BMI and
start-up performance of start-up firms:
Hypotheses H7a, H7b and H7c stated the regulation of environmental dynamism of domestic market on
the relationship between BMI (VCI, VPI, and VCIN) and start-up performance of start-up firms. By the
research data of the dissertation, the test results show that the above hypotheses are rejected (H7a: β = -0.068;
p = 0.228> 0.1; H7b: β = -0,059; p = 0.192; H7c: β = 0.054; p = 0.226). This study has not verified (or
demonstrated) the regulatory role of environmental dynamism to the relationship between BMI and start-up
performance. Thus, in the dynamic market, BMI does not increase the start-up performance of start-up firms.
These findings are similar to previous researches. For example, the study of Heij et al. (2014) showed that the
environmental dynamism of the market does not affect the relationship between BMI and business
performance in a developed economy (Netherlands).


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CHAPTER 5: CONCLUSIONS AND MANAGERIAL IMPLICATIONS
5.1. Conclusions
5.1.1. Measurement model

The dissertation's seven research concepts consist of 4 unidirectional concepts with result-form scale
(relationship with Government officials, social relations, relationship with business partners and start-up
performance of start-up firms) and 3 concepts of BMI with high-level structure, decentralized factor model in
result-cause form (value creation innovation, value proposition innovation and value capture innovation). The
above scales are revised and supplemented, evaluated by Cronbach’s Alpha reliability test, EFA analysis and
re-testing by measurement model (CFA in SEM). The results show that the scales are reliable (Cronbach’s
Alpha reliability test and aggregated), satisfying the allowable value (unidirectional, convergent validity and
discriminant validity).
5.1.2. Theoretical model
Test results show that the theoretical model is consistent with market data. The research hypotheses
include 18 hypotheses, of which 12 are accepted and have important implications for related subjects. They
are start-up firms operating in many industries, local start-up support organizations and researchers in start-up
fields.
Theoretical model of relationship network, BMI and start-up performance of start-up firms has added to
the theoretical framework in the start-up field. Researchers can refer to the research model for their research
in other areas. In different areas, building a network of relationships will lead to innovation and operating
performance in different ways. Therefore, the scales in this study must be evaluated for reliability and
measurement validity before being applied in other research contexts.
5.2. New contributions of the dissertation
Discover new relationships:
Research results show that the new relationship appears from 3 factors above:
1. Relationship with Government officials has a positive impact on BMI (VCI, VPI, VCIN);
2. Social relations have a positive impact on BMI (VPI);
3. Relationship with business partners has a positive impact on BMI (VCI, VPI);
4. BMI (VCI, VPI, VCIN) has a positive impact on start-up performance of start-up firms.
Add new observation variables to old variables
By qualitative research methods by the interview technique with experts in field, the dissertation has
adjusted and added a number of new observed variables to suit the research context. New observed variables
have been tested for reliability and content value and satisfy the required criteria.
Discover intermediate variable (BMI)

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Until now, the author has not found any publication on the intermediate role of BMI between the
relationship network and the start-up performance. The author realized that there should be intermediate
actions between relationship network and start-up performance. For example, Jin et al. (2019) stated the
resources obtained from relationship network will help improve business performance. Thus, "resource
acquisition" acts as an intermediary between the relationship network and the business performance. When
start-up firm gets benefits from the relationship network, it will promote innovation activities, thereby leading
to start-up performance. Therefore, BMI plays an intermediary role between the relationship network and the
start-up performance of start-up firms. The dissertation found that relationship network indirectly impacts the
start-up performance of start-up firms through an intermediary role BMI, which is a new point and contribution
of this research.
New research context
Some previous studies have demonstrated the importance of a relationship network in a market economy
(Peng & Luo, 2000; Xin & Pearce, 1996). The above studies only mention firms in general and new firms (e.g.
Li & Zhang, 2007). The survey objects of start-up firms have not been specifically studied. Compared to startup firms in developed economies, the start-up firms in transition economies face many difficulties in terms of
start-up resources due to the institutional environment and undeveloped input market. The new contribution of
this dissertation is proving the role of management resources affecting BMI and start-up performance of startup firms. At the same time, the dissertation has provided evidence for institutional influence on the role of
management resources for innovation and start-up performance of start-up firms in transition economies like
Vietnam's.
5.3. Managerial implications
5.3.1. Strengthen relationship networks with related parties
In order to increase the social acceptance of firm's practical activities, the important strategy of start-up
firms in the transition economy is to build a relationship network with related parties. Then, the role of the
owners/senior managers in start-up firms is emphasized and makes an important contribution to the access to
useful information and resources for BMI, increasing start-up performance of start-up firms.
Building relationships with Government officials:
According to the social network theory, a strong/weak relationship is measured by the criteria such as

the time for the relationship and the frequency of communication between the network members. Thus, the
role of the owners/senior managers is very important in building relationships and negotiating transactions
with government officials and authorities. Owners/managers know how to lobby will gain information, policies
and decisions that benefit their businesses in the framework of the law.
Building social relations:
Start-up firms should actively participate in local start-up associations/clubs. Start-up firms can invest
time or membership fees to take part in activities of start-up associations/clubs. In addition, start-up firms can
connect with SVF for laboratory support, product improvement, research and technology development of startup projects.