Decision-Making Strategies of Venture Capitalists for Risky Star.pdf

Section 1: Foundation of the Study

The U.S. economy is full of risk and uncertainty for venture capitalists (VCs)

seeking investment opportunities from innovative startups (Bhagat, 2014). Thomas

(2014) described an environment as turbulent when frequent and unpredictable markets

exist and technological changes occur. Risk and uncertainty make it difficult for VCs to

identify sustainable and profitable investment opportunities in innovative startups

(Gerasymenko & Arthurs, 2014). When VCs invest in sustainable and profitable

companies, their investment brings value to investors, entrepreneurs, and society

(Rosenbusch, Brinckmann, & Müller, 2013). Entrepreneurial, market, and economic

uncertainties might influence VCs to become risk averse toward innovative startups

(Smith & Cordina, 2014). Owing to the performance uncertainty of innovative startups,

VCs have trouble identifying startups that lead to sustainable economic growth (Lukas,

Mölls, & Welling, 2016). This research is an exploration of how VCs identify profitable

startups in the midst of risk and uncertainty.

Background of the Problem

The U.S. economy relies on entrepreneurs to spur economic growth through

innovation (Lee, Peng, & Song, 2013). Lee et al. argued that society should encourage

risk-taking and promote entrepreneurship through maximizing upside gains while

minimizing losses associated with entrepreneurial initiatives. The high-growth and high-

variance potential of entrepreneurial ventures could serve as a driver for economic

growth and a catalyst for new industry development (Lee et al., 2013). However, startups

require funding to pursue innovative opportunities (Van Rensburg, 2012). Some

entrepreneurs seeking innovative opportunities have risky business models that require

funding from VCs (Lee, Sameen, & Cowling, 2015). VCs tend to reject most of the

business plans from startup entrepreneurs (de Treville, Petty, & Wager, 2014). When

VCs reject a majority of business plans from startups, they may become an impediment

to spurring economic growth through innovation (de Treville et al., 2014).

A challenge regarding VCs’ willingness to invest in nascent entrepreneurs

includes the homogeneous decision-making approach of some VC firms throughout the

United States (Terjesen, Patel, Fiet, & D’Souze, 2013). Within the VC environment,

uncertainty avoidance attributes to low tolerances for risk-taking within investment

activities of formal institutions (Khavul & Deeds, 2016). Risk-averse investment

practices within the United States enable other fast-growing economies to gain on the

United States in terms of innovation (Hausman & Johnston, 2014). Therefore, to facilitate

improvements in identifying sustainable and profitable startup investments, VCs may

need better assessment strategies that could deviate from traditional decision-making

approaches.

Problem Statement

VCs face challenges in identifying entrepreneurial startups that lead to investor

return on investment (ROI) because of information asymmetry and environmental

uncertainty (Meglio, Mocciaro Li Destri, & Capasso, 2016). More than 50% of venture-

backed startups fail, whereas 85% of the investment returns come from only 10% of the

investee companies (Nanda & Rhodes-Kropf, 2013). The general business problem that I

addressed in this study was that many VCs invest in startups either fail or result in a little

ROI. The specific business problem that I addressed in this study was that VCs often

have limited strategies for determining which businesses would become profitable when

investing in startups.

Purpose Statement

The purpose of this qualitative multicase study was to explore strategies that VCs

use in determining which businesses would become profitable when investing in startups.

Eleven participants from eight VC firms located in the southeastern United States

participated in interviews to share their entrepreneur selection experiences. The findings

from this study may result in positive social change by illuminating VC strategies that

investors could use to lead startup businesses to profitability. Sustainable and profitable

startup businesses might contribute to positive social change by propelling the global

economy forward through job creation and investor ROI.

Nature of the Study

The qualitative method is appropriate for exploring a textual account of the

complex interaction between human beings and their environment (Erlingsson &

Brysiewicz, 2013). The qualitative method was suitable for this study because the

purpose of the research was to explore textual accounts of the complex interaction

between VCs and their environment as they identify startups that might lead to

sustainability, profitability, and investor ROI. Conversely, the quantitative method is

necessary when the research intent is to support or refute a hypothesis by establishing

testable relationships based on a statistical framework (Hanson, Balmer, & Giardino,

2011). Because the purpose of the study was not to test a hypothesis, the quantitative

method was not appropriate. The mixed-methods approach is useful for combining

qualitative and quantitative methods in a sequential or concurrent fashion to address

exploratory and confirmatory questions within the same research inquiry (Venkatesh,

Brown, & Bala, 2013). However, the framework of the research inquiry in this study was

focusing on addressing an exploratory question as opposed to addressing both

exploratory and confirmatory questions. Therefore, the mixed-methods approach was not

appropriate.

The case study is an empirical inquiry that is useful for addressing how and why

open-ended research questions that consitute a contemporary phenomenon within a

complex environment (Yin, 2014). According to Woolcock (2013), the application of

case studies is flexible enough to address a broad range of research inquiries within the

context of how and why questions. I selected a case study because the purpose of the

research was to explore how VCs identify startups that lead to profitability, sustainability,

investor ROI, and a successful VC exit as VCs interact with external and internal forces

within a complex environment. Conversely, ethnography is a research design for

capturing social meanings of individuals within their natural setting (Erlingsson &

Brysiewicz, 2012). Ethnography was an inappropriate design because my objective was

to address the research question by identifying strategies that VCs might use toward

investing in profitable startups, and not the cultural behaviors of individuals in their

natural settings. The narrative design includes storytelling the life of an individual based

on the individual’s perception of reality (Petty, 2016). The narrative design was

unsuitable for this research because the foundation of this study was a broad distribution

of VCs with different worldviews toward identifying profitable startups, and not on the

worldview of a single individual.

Grounded theory is a research design that includes an association of a

contemporary phenomenon to a theory (Ebrashi, 2013). The purpose of this doctoral

study was to explore strategies that VCs use in determining which businesses would

become profitable when investing in startups, and not associate a contemporary

phenomenon with a theory. Therefore, grounded theory was incompatible with this

research. Phenomenology is a research design that enables a deeper understanding of a

problem by describing human lived experiences around a phenomenon (Petty, Thomson,

& Stew, 2012). Phenomenology was an unfitting design because the goal of this research

was to explore strategies for identifying profitable startups, and not to address problems

relating to the lived experiences of individuals and failed startups.

Research Question

What strategies do VCs use to determine which startup businesses would become

profitable when investing in startups?

Interview Questions

Each participant responded to the following open-ended questions during the

interview process:

1. Why is it difficult for VCs to identify profitable startups?

2. How do you evaluate startups for initial investment?

3. How do you evaluate follow on investment options for startups?

4. How do you know when a startup will lead to a successful IPO or a successful

buyout?

5. How do you decide to manage a startup to an IPO or a buyout?

6. What techniques do you believe VCs should include when assessing startups?

7. What other information can you share concerning your experiences in investing in

startups?

Conceptual Framework

Myers first proposed the notion of real options theory (ROT) outside of the

financial industry domain in 1977 for addressing projects with high uncertainty (Zeng &

Zhang, 2011). Myers based ROT on the original works of Black and Scholes financial

options pricing from 1973 (Andalaft-Chacur, Ali, & Salazar, 2011). ROT means the right

but not the obligation of an investor to act on an investment option (Van Reedt Dortland,

Voordijk, & Dewulf, 2014). The application of ROT occurs in high-tech industries for

addressing risk and uncertainty during the investment evaluation phase of project

assessment (Van Reedt Dortland et al., 2014). Van Reedt Dortland et al. (2014) applied

ROT in a high-tech industry because of the inherent flexibility when making course

corrections to address uncertainty in changing environmental conditions. ROT could be

useful for decision-makers to implement course corrections as uncertainty reduces in time

(Baduns, 2013). ROT is useful for addressing investments with an uncertain outcome.

ROT is an applicable conceptual framework for studies involving decision-

making strategies of VCs (Lauterbach, Hass, & Schweizer, 2014). Zeng and Zhang

(2011) indicated that the broad application of ROT links to modern VC evaluation

practices. The foundation of ROT includes concepts aligning with decision-making

strategies VCs might use when investing in startups (Haeussler, Harhoff, & Meuller,

2014). Furthermore, Chung, Lee, Beamish, Southam, and Nam (2013) showed the

effectiveness of ROT in decision-making strategies that involve risk and uncertainty.

Cheng, Lo, and Lin (2011) conducted a study demonstrating how ROT extends beyond

the bounds of financial indicators into industries that use VC investments. VCs tend to

fund startups in high-tech industries, and they could use ROT to align investment

decisions to fund projects (Knockaert & Vanacker, 2013). As the conceptual framework,

contents of this study include ROT because ROT was appropriate for evaluating decision-

making strategies of VCs who operate in complex, risky, and uncertain environments.

Operational Definitions

Information asymmetry: Information asymmetry is a gap in information and

knowledge that exists between two or more parties (Smith & Cordina, 2014).

Real options: Real options represent a right, but not an obligation, to act on an

option (Van Reedt Dortland et al., 2014).

Uncertainty: Uncertainty is the lack of information due to the random nature of

environmental influences that create complexity in predicting the outcome of a situation

(Townsend & Busenitz, 2015).

Assumptions, Limitations, and Delimitations

Assumptions

In research, inferences based on the logical reasoning in the absence of conclusive

evidence are the basis for assumptions (Yin, 2014). I had five assumptions in this study.

The first assumption was that all participants had the sufficient industry experience to

provide insight into investment strategies that could contribute to the goal the study. The

second assumption was that participants would respond to the interview questions

honestly and accurately the best of their abilities. The third assumption was that ROT was

the most suitable theory for identifying decision-making strategies while dealing with

investment uncertainty. The fourth assumption was that entrepreneurial startups create

discontinuous innovations that might lead to job creation and investor ROI. The final

assumption was that data collected from at least five VC firms within the southeastern

United States would lead to themes and insights into investment strategies that could

benefit VCs, investors, and entrepreneurs.

Limitations

Limitations of the study are boundaries that are beyond the control of the

researcher and constrain the extent of generalization (Hyett, Kenny, & Dickson-Swift,

2014). There are three salient limitations in this study. The first limitation is that

responses from participants in the southeastern United States might not represent VCs in

other regions of the country. The second limitation is that the study does not show

detailed relationships with syndicates or other VC networks that could influence

decision-making strategies of VCs. The last limitation is that the short time limit for the

study may have imposed temporal constraints that otherwise are not prevalent in

longitudinal studies.

Delimitations

Delimitations are the constraints based on the researcher’s decisions that could

limit the extent of generalization of the study (Yin, 2014). The delimitation of the study

was an exploration of strategies that VCs need for identifying and investing in sustainable

and profitable startups bound by geographic location. The analysis of the data gathered

through interviewing VCs might enhance the understanding of common themes

surrounding profitable startups in the midst of risk and uncertainty. The delimitation of

this research focused on VC firms in the southeastern United States and the sole

application of ROT as the conceptual framework for the study.

Significance of the Study

Contribution to Venture Capital Assessment

Elevated levels of risk and uncertainty in entrepreneurial startups could cause

VCs to experience difficulty identifying sustainable and profitable companies that might

result in an ROI for investors. When VC-backed startups are sustainable and profitable,

value is created for investors and the economy (Terjesen et al., 2013). However, partly

owing to risk and uncertainty, VC firms fund only 0.5% to 1.0% of entrepreneur business

plans because most startup ventures fail (Nanda & Rhodes-Kropf, 2013). Of the VC-

backed startups, half of the companies exit with a non-zero value, and 85% of the returns

come from only 10% of the funded companies (Nanda & Rhodes-Kroft, 2013).

Consequently, if some VCs reject most entrepreneur business plans, yet the majority of

the funded startups have a high probability of failure, an opportunity exists for deeper

exploration in investigating this phenomenon (Xun, Hwee, Wilson, & Zhenyu, 2013).

The opportunity that I had in this study was to identify VC assessment strategies, which

might result in sustainable and profitable startups that eventually enable the VC to exit

successfully through an IPO or a buyout.

Some VC firms leverage syndication as a means of risk distribution (Khavul &

Deeds, 2016). Nonetheless, even with syndications the risk and uncertainty in startup

businesses continue to exist (Khavul & Deeds, 2016). Therefore, for syndicated and

nonsyndicated VCs, the outcome of this research might provide valuable contributions

toward identifying startup assessment strategies that result in sustainable and profitable

businesses, which could lead to a positive ROI for investors.

Value to Entrepreneurial Business Development

A rapidly changing world requires a new understanding of VCs’ evaluation,

selection, and monitoring tactics of entrepreneurial startups. Business leaders, large and

small, continually face the challenge of innovating toward a sustainable future (Soken &

Barnes, 2014). Through innovation, the integration of information and technology

continuously evolves (Nagy, Schuessler, & Dubinsky, 2016). In this evolution, new

opportunities surface for the astute entrepreneur (Jennings, Edwards, Jennings, &

Delbridge, 2015). However, alongside these opportunities for innovation, there exist risk

and uncertainty from multiple sources that threaten the viability of a startup (Autio,

Kenney, Mustar, Siegel, & Wright, 2014).

Like all companies, entrepreneurial businesses require funding to pursue

innovative opportunities (Henry, 2016). Some entrepreneurs pursue funding for high-risk

ventures from VCs. These VCs evaluate these fund-seeking entrepreneurs based on risk

assessment tactics as part of the VC’s entrepreneur selection strategy (Andrieu, 2013).

The idiosyncratic factors that influence these VC selection strategies include intuition,

industry experience, investment experience, and educational background (Woike,

Hoffrage, & Petty, 2015). Furthermore, King (2013) asserted that business models

change with time because of innovation. These innovation-based changes might derive

from the evolution of new ideas or the development and exploitation of new ideas

(Ostendorf, Mouzas, & Chakrabarti, 2014). Consequently, the traditional VC assessment

tactics used to evaluate modern business models might create impediments to

entrepreneurial innovation because of missed funding opportunities. These impediments

to entrepreneurial innovation could result in missed opportunities for investors, VCs, and

society because of unrealized ROI and job creation. Therefore, the outcome of this study

might provide insight for startup entrepreneurs as they prepare business models and

execution strategies that take advantage of future opportunities.

Implications for Social Change

The challenge for VCs is to identify investment opportunities that align with

investor goals and expectations (King, 2013). In 2010, small and medium-sized

enterprises (SMEs) constituted 99.7% of businesses that handled 64% of new private

sector jobs created in the United States (Organisation for Economic Cooperation and

Development, 2015). VC-backed startup and nascent entrepreneurs create SMEs (Li,

Cao, & Feng, 2016). The data compiled for this study could provide leaders with

strategies that enable VCs to increase the percentage of startups that lead to a successful

exit through an IPO or a buyout. The findings from this study may result in positive

social change by illuminating VC strategies that investment leaders could use to lead

startup businesses to profitability.

A Review of the Professional and Academic Literature

The exploration of the literature constitutes peer-reviewed articles, relevant

business books, and seminal works relating to the business problem of the study. The

sources of these reference materials come from various resources including, Google,

Google Scholar, Emerald Management Journals, Science Direct, ABI/Inform Complete,

Sage, and Business Source Complete. Various word and phrase combinations were useful

for identifying scholarly materials and seminal works for formulating the foundation of

the review of the literature. Keyword and phrase searches included nascent

entrepreneurs, entrepreneurs, real options, real options theory, venture capitalists,

venture capital, failed startups, business failure, venture capitalists assessment,

entrepreneur strategy, venture capital strategy, business models, entrepreneurial

innovation, competitive advantage, startup uncertainty, venture capital uncertainty,

evaluating uncertainty, and investment practices. The keyword and phrase searches in

varying combinations resulted in 129 references used throughout this review of the

literature. There were 126 peer-reviewed references (97.6%), three non-peer-reviewed

references (2.3%), and two business books (1.5%) included in this review of the

literature. Based on the number of references, 88% of the sources derive from references

between 2013 and 2017.

The purpose of this qualitative multicase study was to explore strategies that VCs

use when investing in profitable startups. The review of the literature includes

information that supports the underlying theme of VC assessment strategies. The three

main sections of the review of the literature include innovative nascent entrepreneurs, VC

firms, and ROT. The first section includes an overview of innovative nascent

entrepreneurs, triggers of entrepreneurial innovation, effect on society, challenges of

funding, funding sources, and determining factors that tend to lead entrepreneurs to

pursue VC funding. The second section concerning VC firms provides a scholarly-based

overview of the definition and types of VCs, purpose of VCs, investor relations, and

syndications.

The second section also includes an overview of VC assessment strategies

focusing on current assessment practices, success and failure statistics, signals, and the

effectiveness of accurately predicting profitable startups based on decision-making tactics

for evaluating startups. The third section in the review of the literature is on ROT. The

ROT section starts with a scholarly-based overview and history of ROT and the relevance

to financial theory. The ROT section extends into a discussion on the application of ROT

relating to VC decision-making strategies during the startup assessment process.

Following the conclusion of the ROT section, the formulation of a gap in the literature

will extend the collection of information presented throughout the three sections of the

review. The identification of a gap in the literature represented the basis for this research

study.

Innovative Nascent Entrepreneurs

Reasons that some individuals become motivated to start a business is to gain

independence, make money, and achieve job satisfaction (Albort-Morant & Oghazi,

2016). Businesses in the startup phase are highly complex and require significant

attention and support (Van Rensburg, 2012), and some entrepreneurs start businesses

with a “born-to-be-sold” strategy (Becker, Clement, & Nöth, 2016). Ehret, Kashyap, and

Wirtz (2013) indicated that experienced-backed entrepreneurs are poised to transform

uncertainty into value-adding and profitable business solutions. Furthermore, Cassar

(2014) indicated that entrepreneurial business experience increases the likelihood of a

profitable business venture that leads to a buyout or an IPO. Oe and Mitsuhashi (2013)

made a similar assertion when they indicated that the experience of founders led to a

faster break-even. Mayer-Haug, Read, Brinckmann, Dew, and Grichnik (2013) also

found that entrepreneurial talent has a strong link to business performance, particularly in

developing economies. Probert, Dissel, Farrukh, Mortara, Thorn, and Phaal (2013)

supported the value of an entrepreneur’s skills when they found that intangible

technologies, which relate to know-how or unrealized technologies, created a strong

business base when the technology is closer to the market. However, Kim and Longest

(2014) found that the greater the founder’s business experience, the less likely the

founder will involve others in startup efforts. However, DeTienne, McKelvie, and

Chandler (2015) found evidence linking industry experience to higher levels of IPO and

acquisition intentions. In a rapidly moving economy, motivators for starting a business

are insufficient without other essential skills for driving a profitable business (Vogel,

Puhan, Shehu, Kliger, & Beese, 2014). Fisher, Maritz, and Lobo (2014) described that an

entrepreneur’s success could attribute from the entrepreneur’s perspective on the business

opportunity. Success factors for innovative nascent entrepreneurs include motivation and

both tangible and intangible capabilities to drive the business.

Triggers of Innovation

The effect of entrepreneurial innovation influences the progression of society.

This influence comes from the notion that innovation can transform societal sustainability

issues into opportunities for entrepreneurial businesses that result in creating value for

societies (Spitzeck, Boechat, & Leão, 2013). Companies that commit to innovation and

customer knowledge play a dominant role in social capital and innovation performance

(Tsai, Joe, Ding, & Lin, 2013). Spitzeck et al. (2013) conducted a case study concerning

how Odebrecht, a company with a culture of social entrepreneurship, brought value into

societies in Santo Antonio in Porto Velho and Peru. Although Phillips, Tracey, and Karra

(2013) linked social entrepreneurs to individuals possessing characteristics of

benevolence and homophily thereby serving those in need. The intrinsic value of

entrepreneurial innovation resulted in building alliances and responding to the needs of

society members thereby having a positive influence on society. Furthermore, Meyskens

and Carsrud (2013) established a call for social innovators to align innovation towards a

globally sustainable market. Social innovation could be a catalyst for entrepreneurial

innovation.

Triggers of social innovation. The recognition of social innovation has become

prevalent in the social sciences (Cajaiba-Santana, 2014). Drucker (1987) explained that

social innovation has become the task of the manager. These managers are individuals

who are capable of aligning other people to a common purpose (Drucker, 1987). Drucker

indicated that less emphasis on social innovation should rest on science and technology,

and more emphasis should focus on management as an agent of social change. Phillips

(2011) used the term social change synonymously with social innovation. Phillips argued

that, to the detriment of society, social change is occurring faster than technological

innovation. Phillips reasoned that the slow-down of technological innovation is occurring

because of (a) various combinations of incentives that detract from innovation, (b)

continual use of obsolete business models in a changing world, and (c) changes in

political economies that reduce measures for funding innovation. Cajaiba-Santana (2014)

indicated that social innovation is an organic process with a dyadic relationship between

actor and structure. Cajaiba-Santana argued that individuals should develop analytic

skills, foster creativity, and encourage collaboration with others to drive social

innovation. Innovation has social properties that operate within a bricolage of complex

influences that could bring value to those who recognize and then take advantage of the

opportunity to drive innovation. The attributes of social innovation show some

similarities characteristic with entrepreneurial innovation.

Drivers of entrepreneurial innovation. Regarding entrepreneurship, there exist

drivers of innovation. Autio et al. (2014) indicated that drivers of innovation within the

national innovation system are research and development (R&D), technology, and

invention. The driver of innovation within entrepreneurship is entrepreneurial cognition,

learning, opportunity recognition, and creation (Autio et al., 2014). The driver of

innovation within entrepreneurial innovation is cocreation and evolution within the

ecosystem (Autio et al., 2014). Entrepreneurs might drive innovation by linking critical

milestones and capital needs to their underlying approach to manage risk and accelerate

value (Sammut, 2012). In addition, Day and Schoemaker (2011) indicated that timing is

an important component of driving innovation. In this context, drivers of innovation stem

from the timely recognition of an opportunity to improve value-adding products, services,

and situations.

Triggers of innovation through market opportunities. The recognition of

market opportunities might be a reason that individuals become nascent entrepreneurs

and pursue ventures. Franco, de Fátima Santos, Ramalho, and Nunes (2014) described

that entrepreneurs tend to take charge of the business and make all decision regarding

marketing. Edelman and Yli-Renko (2010), in a study of 114 entrepreneurs from the

National Panel Study of Entrepreneurial Dynamics, found that entrepreneurial perception

of market opportunity significantly relates to entrepreneurs’ efforts toward pursuing

ventures. Renko (2013), in a study of nascent entrepreneurs building companies with

socially beneficial intent, found that entrepreneurs who focus on creating imitative

products over innovative solutions are more likely to meet key milestones when building

an organization. In addition, Renko established that nascent entrepreneurs with

innovative ideas should focus on establishing legitimacy and stakeholder support early.

Innovation and market opportunities might trigger entrepreneurs to build startup

companies.

In contrast, according to Goel and Göktepe-Hultén (2013) identifying data sets

that focus on the nexus between nascent entrepreneurs and inventive activity is difficult.

Using survey data from Max Planck Society (MPS) in Germany, Goel and Göktepe-

Hultén study on nascent entrepreneurs found a positive and statistically significant effect

on inventive activities. The MPS dataset included 2,604 participants with a response rate

of 33.35%. Nascent entrepreneurs with a patent had a higher probability of procuring

equity-based financing than other nascent entrepreneurs (Goel & Göktepe-Hultén, 2013).

In addition, Goel and Göktepe-Hultén found a complex relationship in the nexus between

nascent entrepreneurs and invention because the direction of causality is not always clear.

Toft-Kehler, Wennberg, and Kim (2014) described a perspective that nascent

entrepreneurs with industry experience could have greater challenges in venture

performance owing to their lack of founder experience. However, recognition of

opportunities can influence individuals to become nascent entrepreneurs. Legitimacy and

stakeholder support early with prototypes can increase the likelihood of procuring

funding for the venture. Kazadi, Lievens, and Mahr (2016) confirmed this assertion by

indicating that stakeholders are playing an active role in the value creation activities of

organizations. Creating innovative solutions include managing people towards working

together to create innovation (Liedtka, 2014). However, in a competitive environment, a

nascent entrepreneur might need a high-caliber management team to create an attractive

business model for equity-based financing.

Innovation and entrepreneurial team. In a competitive industry, the

management team of the nascent entrepreneurs influences the success or failure of the

venture. Dubocage and Galindo (2014) mentioned that the condition of a company’s

distress extends beyond the management skills of the founder-CEO, but into the

execution skills of the management team and dynamics of the market conditions.

Although Liao, Lu, and Wang (2013) indicated that agency problems that cause company

distress relate to conflicts of interest between the company’s management team and

investors. However, Townsend and Busenitz (2015) showed that capabilities of the

management team influence equity-based funding decisions. Townsend and Busenitz

(2015) also found that high-quality management teams are essential to early-stage

ventures in overcoming challenges of market innovation and navigating the competitive

industry. The capabilities of the entrepreneur and the management team are necessary for

creating a sustainable and profitable business (Kremljak & Tekavcic, 2014). However,

the reliance on the sole capabilities of the entrepreneur and the management team is not

sufficient for creating a profitable business (Colombo & Dawid, 2016). Early-stage and

startup-stage ventures require capital funding to establish a position in the market and

create a competitive organization.

Financing innovations. Entrepreneurs often face challenges procuring equity-

based funding to finance high-risk ventures. These challenges are prevalent because most

equity-based startup ventures fail, or fail to meet, expected returns (Nanda & Rhodes-

Kropf, 2013). In general, entrepreneurs have greater challenges compared with

established companies in terms of combining activities for acquiring resources in an

effective and efficient manner that creates a sustainable company (Malmström, 2014).

For this reason, entrepreneurs face the challenge of convincing VCs that the

entrepreneur’s project is worthy of equity-based financing. Some VCs recognize that

some entrepreneurs continue to commit financial resources towards investments that

might result in failure because of the entrepreneur’s emotional connection to the venture

(Brundin & Gustafsson, 2013). Although Staniewski, Szopiński, and Awruk (2016) found

that entrepreneurs who invest significant amounts of personal funds into a venture send a

positive signal that helps convince VCs of the viability of the prospect for financing. The

positive signal from the entrepreneur is because of the notion of sharing risk between the

investor and the founder who commits capital (Miettinen & Niskanen, 2015). Conversely,

Henry (2016) suggested that entrepreneurs who come across shy or introvertive

negatively affect the VCs’ judgment to fund the innovation. Furthermore, Mollick (2014)

indicated that entrepreneur’s preparedness increases the chances of funding. Therefore,

the task for VCs is to distinguish between risky and worse investments (Nanda &

Rhodes-Kropf, 2013). From this vantage point, the entrepreneur’s task of convincing VCs

to invest into the startup includes but also extends beyond boundaries of the

entrepreneur’s control.

There are controllable and uncontrollable forces that influence entrepreneurs and

these forces can create funding challenges and dampen the opportunities for equity-based

funding. Nanda and Rhodes-Kropf (2013) found a higher probability of company failure

when firms receive funding during hot markets; however, companies can also result in

higher returns if profitable and sustainable. The consideration of market dynamics

influences the decision-making strategies of VCs in emerging markets that are risky

(Nanda & Rhodes-Kropf, 2013). Li, Tan, Wilson, and Wu (2013) found that the limiting

factor of funding risky ventures is the VC’s level of risk aversion. Townsend and

Busenitz (2015) indicated that information asymmetry provides the basis of VC risk

aversion. Information asymmetry directly relates to risk and results in higher costs of

raising capital (Miettinen & Niskanen, 2015). Information asymmetry creates resource

allocation challenges for VCs (Lahr & Mina, 2016). However, Muzychenko and Liesch

(2015) suggested self-efficacy could reduce information asymmetry between the

entrepreneur and the investor. Market conditions and risk aversion can influence the

funding decisions of VCs.

In the wake of the financial crisis, innovation is important towards ensuring

economic resilience and recovery (Hausman & Johnston, 2014). Hausman and Johnston

performed an analysis of the effect of innovation on the United States following the

global financial crisis. According to Hausman and Johnston, innovation (a) positively

relates to job creation, (b) positively relates to increased profitability, (c) positively

relates to discontinuous innovation through economic stability, and (d) provides a method

for recovery during the economic downturn. Hausman and Johnston found that since the

global financial crisis, there is a negative slope of technological innovation deriving from

the United States. As such, the global financial crisis results in an increase in risk

aversion and a decrease of innovation in the United States. Market uncertainty and

investor expectations contribute to risk averse attributes that might influence the

decisions of VCs to invest in risky startups. These decisions reside in a complicated

domain of analysis. Li et al. (2013) reflected on complexities in entrepreneurial finance

that complicated decision-making activities characterized by the assessor’s inability to

describe the complex phenomenon in a linear model. However, Franklin and Diallo

(2013) found evidence of using geometric Brownian motion, Poisson decay process, and

real options to model investment decisions with uncertainty in a regulated industry. The

affect of complexities surrounding the decision-making tactics of VCs are partly a result

of the global financial crisis. For this reason, VCs attempt to have as much information as

possible before making investment decisions. When the information available to the VC

is asymmetric from the information of the investee, then risk increases.

Essence of innovation. The essence of innovation is discovering value-creating

opportunities that internal and external influences on the organization triggered. There is

a complex interconnection between innovation, technology, and business models (Baden-

Fuller & Haefliger, 2013). Owing to this complex interconnection, pursuers of innovation

must exercise creativity to establish a competitive advantage (Baden-Fuller & Haefliger,

2013). Regarding creativity, discovery and creation are modes of model development that

drive how entrepreneurs pursue innovative ventures (Edelman & Yli-Renko, 2010). King

(2013) supported these modes of innovative pursuit by identifying a tinker management

style that supports making constant course adjustments and thrives in volatile, risky, and

uncertain environments. Dorner, Fryges, and Schopen (2017) found that startups that use

R&D to create innovation improve their prospective earnings. Creativity is a trigger of

innovation in entrepreneurial business model development (Baden-Fuller & Morgan,

2010). Liedtka (2014) indicated that a problem-solving approach similar to design-

thinking concepts could lead to innovation. Innovative entrepreneurs are creative

individuals capable of building business models pursuant to their innovative goals.

Impediments to VCs funding innovations. Although innovative entrepreneurs

are creative individuals, information asymmetry has implications on the decision of VCs

investing in entrepreneurial ventures. There are important issues and challenges that

entrepreneurs face in financing a business. The notion of information asymmetry relates

to some of the challenges of entrepreneurial financing. Information asymmetry occurs

when there exist disconnects between the knowledge of the investee and the knowledge

of the investor (Tong & Crosno, 2016). Information asymmetry increases the cost for

new ventures to raise external funding because lenders tend to pursue higher interest rates

or greater equity to compensate for the risk (Miettinen & Niskanen, 2015). Information

asymmetry between the investee and the investor increases uncertainty and risk, which

results in a higher cost of capital. Smith and Cordina (2014) found that essential elements

for reducing information asymmetry derive from an evaluation of the personal qualities

of the management team and their experience of bringing a venture to market. In

addition, Smith and Cordina (2014) indicated that some VCs use documents including

financial statements, business plans, executive summaries, and any disclosures about

future expectations as a method for reducing information asymmetry. Although, Goel and

Göktepe-Hultén (2013) indicated a patent and a product prototype reduces information

asymmetry by resolving the problem of uncertainty about the outcome of the venture.

These signals are useful for reducing information asymmetry (Goel & Göktepe-Hultén,

2013). Butler and Goktan (2013) suggested that smaller companies and inexperienced

VCs might work together to obtain better information. In essence, entrepreneurs face

challenges in obtaining equity-based financing and must manage the perception of risk

and uncertainty through decreasing information asymmetry between the entrepreneur and

VC.

Minimizing information asymmetry between the entrepreneur and the VC does

not ensure that the VC will approve the equity-based funding opportunity. Other factors

could trigger a VC to reject the entrepreneurial funding opportunity. Bengtsson and

Wang (2010) indicated that a misalignment in the expectations between the entrepreneur

and the VC could result in VC rejection. Henry (2016) highlighted a consequence of a

startup with the wrong entrepreneurial management team could result in high risk for the

VC with low benefit from the startup. De Treville et al. (2014) mentioned that VC

resource limitations or internal resource constraints might result in a rejection of equity-

based funding opportunities. Heughebaert and Manigart (2012) found that VC rejection

could be indicative of a strategic misalignment between the entrepreneur and the VC.

When VCs reject the funding request of an entrepreneur, then the entrepreneur must seek

alternative sources of financing for the venture. Therefore, understanding alternative

funding options for entrepreneurs is important for VCs and entrepreneurs (Staniewski et

al., 2016). Understanding alternative financing options provide a richer perspective

concerning strategies that VCs might use to identify profitable startups. Identifying

financing options available to entrepreneurs may lead to VCs understanding when and

why an entrepreneur would pursue equity financing.

Entrepreneur Financing Options

There is an array of funding sources and options available to entrepreneurs.

Rupeika-Apoga (2014) defined finance types that include (a) formal equity, (b) formal

loan, (c) informal investment, (d) overdraft, and (e) grants. In addition, Rupeika-Apoga

mentioned that sources of startup financing include (a) VCs, (b) personal funds, (c)

business partners, (d) loan guarantee, (e) banks, (f) family and friends, and (g) grants.

Rupeika-Apoga’s references to the types and sources of funding are not all encompassing

of available funding options. Sometimes, depending on the type and stage of the business,

entrepreneurs might elect to finance a startup business through personal financing: These

methods include bootstrap methods, debt financing, crowdfunding, or equity financing.

Croce, D’Adda, and Ughetto (2015) found that VC firms provide better support for

entrepreneurs while bank-affiliated firms have fewer constraints regarding additional

rounds of funding. Malmström (2014) discussed that bootstrapping is another method for

funding ventures. The bootstrapping method involves using creativity and imagination to

garner or control resources that benefit the business (Belleflamme, Lambert, &

Schwiendbacher, 2014). The creative and imaginative methods of bootstrap financing

include family, friends, arrangements for delayed payments to suppliers, or advanced

payment from customers (Malmström, 2014). According to Malmström, risk is the most

important motivating factor of bootstrap finance. Zheng, Li, Wu, and Xu (2014) provided

another alternative method of funding businesses through crowdfunding. Crowdfunding

is an Internet-based method for obtaining capital to fund a project or business (Zheng et

al., 2014). Crowdfunding is a newer concept for obtaining capital and use social networks

of individuals who contribute small amounts of money to the venture (Zheng et al.,

2014). Crowdfunding is not a replacement for VCs because the funding method does not

provide the magnitude of capital compared to VC funding (Zheng et al., 2014). Also,

Autio et al. (2014) discussed funding programs that the United States government uses to

spur innovation from entrepreneurs. These programs include the Small Business

Administration (SBA), Small Business Innovation Research (SBIR), and Small Business

Technology Transfer (STTR). These government programs are available for providing

funding for seed-stage and early-stage startups. These various funding options are

available to entrepreneurs for financing their business venture.

Financially literate entrepreneurs. Alternative funding methods could reduce

the need for the entrepreneur to pursue funding options that might result in elevated costs

of capital. However, regardless of the viability of a project, entrepreneurs face a plethora

of challenges starting a business and one of the greatest challenges for entrepreneurs is

capital procurement. Entrepreneurs who are literate in funding options are poised to make

suitable choices regarding financing ventures. Depending on the venture, some sources of

funding are more appropriate than other sources of funding options. Dahmen &

Rodríguez (2014) found that financially literate entrepreneurs perform better than

entrepreneurs who are not financially literate. Dahmen and Rodríguez indicated that

financial literacy contributes to generating higher levels of cash flow management from a

broader spectrum of funding sources. Understanding the sources of capital funding is an

essential criterion for entrepreneurs (Staniewski et al., 2016). However, since the overall

scope of this research is on the decision-making strategies of VCs, then the focus of most

of the review of the literature will center on VCs. The focus is specific types of

entrepreneurs who require equity-based funding from VCs as a criterion for business

development (Colombo & Dawid, 2016).

VCs finance entrepreneurial innovations. The assessment strategies for funding

risky ventures could influence the interaction between VCs and entrepreneurs. Innovation

is vital to the success and sustainability of organizations. Typically, entrepreneurs in the

United States who are seeking VC funding are pursuing high-tech and innovative

ventures (Knockaert & Vanacker, 2013). For this reason, sustainable companies must

constantly innovate to remain relevant (Hausman & Johnston, 2014). Conversely, nascent

entrepreneurs must innovate to become relevant (Renko, 2013). The concept of

innovation goes beyond the state of the moment and includes the process of change

(Cajaiba-Santana, 2014). Innovation brings new ideas and a different way of thinking

(Cajaiba-Santana, 2014). Innovation can also derive from the interaction with others

(Wang & Hsu, 2014). Sustainable businesses exist because these businesses continually

meet the changing needs of the customer by providing value-adding solutions through

innovation (Choi & Majumdar, 2014). Consequently, meeting the needs of customers

infer an interaction with others to create new value. For this reason, innovation can

happen regardless of economic conditions; however, the financial crisis tends to make

investors of innovation more risk averse.

A role of the VC includes managing the funding and relationship with the

entrepreneur and managing relationships with investors who might be risk averse. The

goal of the VC includes obtaining a successful exit within an acceptable cost and

timeframe (Eldridge, Van Iwaarden, Van Der Wiele, & Williams, 2013). High-tech

innovation ventures are, by nature, risky and uncertain (Knockaert & Vanacker, 2013).

Risk relates to uncertainty, which results from information asymmetry among all parties

(Townsend & Busenitz, 2015). As indicated earlier, innovation results from creating

value for those who take advantage of the innovation and the opportunity to be

innovative. Some entrepreneurs might pursue VC funding to help finance an innovation

(Goel & Göktepe-Hultén, 2013). However, funding an innovation does not always result

in a positive return for investors or entrepreneur (Turan, 2015). Therefore, VCs may have

a challenge in determining suitable investments into entrepreneurial businesses that are

acceptable for the risk tolerance of investors. VCs might need to balance their

entrepreneurial business assessment strategies with the risk tolerance of the investors.

Entrepreneurial Business Models

Entrepreneurial business models should align with the business environment that

the model applies (Huarng, 2013). DaSilva and Trkman (2014) described the role of a

business model is to synchronize company resources with customer transactions to create

value for both customers and the organization. An entrepreneurial business model is

important because the model (a) captures components of the business plan, (b) depicts

what the business does and method for generating profit, and (c) shows how the business

will create wealth (Huarng, 2013). However, the concept of one-size-fits-all models is an

ineffective entrepreneurial business model in complex and risky business environments

(Ehret et al., 2013). To create competitive advantage, the design of an effective

entrepreneurial business model will establish links between technology, development,

and business performance while accounting for market dynamics (Baden-Fuller &

Haefliger, 2013). Entrepreneurs should develop a logical progression of salient success

factors while demonstrating the linkage using a project plan that links activities,

resources, and required funding to the goals of the business (Sammut, 2012). Therefore,

entrepreneurs must remain alert to recognize and take advantage of rising opportunities

and adjust their business strategy to the opportunity (Jennings et al., 2015). Through this

alertness, entrepreneurs can meet the needs of customers through innovation while

achieving competitive advantage in the market (Probert et al., 2013). In addition, through

alertness, entrepreneurs can recognize and respond to the changing conditions of the

environment. Correctly aligning entrepreneurial models with the relevant business

environment is essential for competitive advantage.

Regarding innovation and funding, the pace of change creates opportunities for

evaluating and understanding VC evaluation, selection, and monitoring tactics of

entrepreneurial startups. Business leaders, large and small, continually face the challenge

of innovating towards a sustainable future (Soken & Barnes, 2014). Through innovation,

the integration of information and technology constantly evolves. In this evolution, new

opportunities surface for the astute entrepreneur (Jennings et al., 2015). Adjacent to these

opportunities for innovation are elements of risk and uncertainty from multiple sources

that threaten the viability of a startup (Lee et al., 2013). Consequently, entrepreneurs need

funding to pursue innovative opportunities (Colombo & Dawid, 2016). Entrepreneurs

who are pursuing high-risk ventures might decide to leverage VCs for funding

innovations (Eldridge et al., 2013).

Venture Capital Firms

VCs are equity investors with access to pools of capital to invest in companies

with high growth potential within a limited timeframe (Gordon, 2014). VC firms in the

United States have a positive contribution towards economic development, job creation,

and innovation. VC firms contributed to over 12 million jobs in 2004 and $2.9 trillion in

revenue (Andrieu, 2013). The United States has the largest and most successful VC

presence in the world (Tykvová & Schertler, 2014). In 2014, VCs invested $87 billion in

startup companies; 58 percent more than 2013 (Lukas et al., 2016). High-risk technology-

based industries are typical for VC investors (Lehoux, Daudelin, Williams-Jones, Denis,

& Longo, 2014). Thus, VC contribution permeates into the domains of economic

development, job creation, and innovation by investing in companies through providing

funding and other services that increase the likelihood of a successful VC exit. Many

scholars define a successful VC exit as a merger and acquisition (M&A), Initial Public

Offering (IPO), or buyout (Cassar, 2014; Gerasymenko & Arthurs, 2014; Liao et al.,

2013, Nanda & Rhodes-Kropf, 2013; Rosenbush, Brinckmann & Müller, 2013). The

strategies and discussions used in this research will adopt similar VC success criteria

regarding an IPO and buyout.

VCs are investment brokers. VCs are individuals who invest capital funds and

other resources in investee companies. Wonglimpiyarat (2013) provided a model linking

capital providers to investees brokered through the VC firm. In this model, VC firms

establish general partner relationships with capital fund providers in the form of limited

partnership relationships (Wonglimpiyarat, 2013). These limited partners represent

pension funds, banks, individuals, corporations, and insurance companies

(Wonglimpiyarat, 2013). Limited partners provide capital funds to the VC firm that in

turn invests the capital in (a) seed capital, (b) startup capital, (c) early-stage capital, (d)

expansion-stage startup, or (e) late-stage entrepreneurial companies (Khavul & Deeds,

2016). In exchange for capital investment, the entrepreneurial company will relinquish a

percentage of ownership of the company to a VC firm in the form of equity-based

ownership (Galloway, Miller, Sahaym, & Arthurs, 2017). The VC retains this equity-

based ownership until the time of exit (Wonglimpiyarat, 2013). While the VC retains

ownership, a member representing the VC interests might sit on the Board of Directors of

the VC-backed company. The compensation for VCs includes a percentage of the capital

funds to manage the investment capital (Wonglimpiyarat, 2013). Compensation of

independent VC (IVC) comes from fixed management fees (e.g., 2% of investment

capital) and performance fees (e.g., 20% of profits; Heughebaert & Manigart, 2012). The

type of VC firms has an influence on the type of ventures the VC will pursue.

Types of VCs. VC firms have an important function towards propelling

entrepreneurs towards success. VCs are important towards creating sustainable startups

(Liao et al., 2013). Li et al. (2016) indicated that a VC is an essential component of

innovation and entrepreneurship. However, all VC firms are not created equal.

Differences in VC type could have an effect on the funding opportunity extended to an

entrepreneur. As such, there are differences in the strategic objectives of a VC depending

on VC type. Andrieu (2013) identified different types of VC firms that include (a)

independent VC firms, (b) bank affiliated VC firms, and (c) corporate VC firms. When

Heughebaert and Manigart (2012) studied the types of VC investors and bargaining

power, they included the types of VC firms as (a) corporate VC, (b) University VC, (c)

government VC, and (d) independent VC. Although Bertoni, Colombo, and Grilli (2013)

identified independent venture capitalists (IVC) and corporate venture capitalists (CVC)

as relevant for technology-based firms. The common types of VC that persist throughout

many studies are IVCs and CVCs. The type of VC firms is characteristic of the

investment strategies that they might pursue. IVC investors prefer larger firms than CVC

investors (Bertoni et al., 2013). Both IVC and CVC investments have a long-term

positive effect on the growth rate of technology-based firms (Bertoni et al., 2013). Also,

both IVC and CVC investments increase the employment growth following the first

round VC financing (Bertoni et al., 2013). IVC firms tend to leverage outsourcing in

substitution of hiring a large number of employees to support sales growth (Bertoni et al.,

2013). IVC investors have an incentive to grandstand to spur sales growth of the

portfolio, particularly when the IVC is young and needs to build a positive reputation

with investors (Bertoni et al., 2013). The grandstanding results from investors relying on

VC track record when making an investment decision to commit funds (Kollmann,

Kuckertz, & Middelberg, 2014). Bartkus, Hassan, and Ngene (2013) made a similar

assertion when they found that inexperienced VCs might bring a company to IPO quicker

than experienced VCs to build a reputation. Conversely, CVC requires no grandstanding

as a means of facilitating reputation building because CVC tends to invest in ventures

that strategically align with the parent organization (Bertoni et al., 2013). For this reason,

differences in types of VC organizations have different incentives for fueling growth

through startup development and funding opportunities.

Purpose of VCs

The purpose of VCs is to create value for investment shareholders by financing

high-growth, high-potential companies that result in ROI for both VC and investment

shareholders (De Treville et al., 2014). VCs will distribute resources and management

activities across a portfolio of investee companies with the intent of generating ROI. In

the distribution of these VC resources, Tykvová and Schertler (2014) indicated that the

geographic location of the investee company in the proximity of the VC is important

towards investment decisions and performance. Manigart and Wright (2013) concurred

with Tykvová and Schertler when they indicated that VC investment strategies might lead

to (a) restricted industry, (b) geographic niche, (c) range of portfolio companies, and (d)

investment approach. Hsu (2013) made a similar conclusion after indicating that young

firms in high-tech industries are more likely to receive VC financing in locations like

California or Massachusetts. Butler and Goktan (2013) indicated that cultural distance

might have a statistically significant negative effect on company performance.

Ultimately, VCs invest in companies hoping for a favorable exit (Ozmel, Robinson, &

Stuart, 2013). To achieve the goal of a favorable exit, VCs have a leading role in equity-

based financing for early-stage startups (Galloway et al., 2017). Also, VCs use bargaining

power to negotiate higher equity from entrepreneurial startups to generate higher returns

(Heughebaert & Manigart, 2012). This bargaining power includes the value that the VC

brings to the relationship. The value that VCs bring to the relationship with the startup

include (a) screening, (b) advising, (c) monitoring, (d) certification, and (e) exercise

control (Flor & Grell, 2013). Heughebaert and Manigart (2012) supported this position

when they indicated that reputable VCs might attribute better entrepreneurial companies

to better VC screening mechanisms. Entrepreneurs’ preference is to associate themselves

with reputable investors (Heughebaert & Manigart, 2012). Entrepreneurial success is a

result of meeting the objectives of the shareholders (Gomezelj & Kuace, 2013). This

frontend relationship between the VC and the entrepreneur must also align with the

performance expectations in the backend relationship between the VC and investors.

Relationship between VC and investor. Investors are an important component

of the VC process for funding entrepreneurial companies. Also, investors may exert

pressure on VCs to invest capital (Lauterbach et al., 2014). Investors provide the capital

funding to VCs who in turn manage and distribute the funds to portfolio companies

(Wonglimpiyarat, 2013). VCs aim to protect their investment with trade secrets and

patents (Castellaneta et al., 2016). Nunes, Gomes Santana, and Pacheco Pires (2014)

indicated that one of the most important criteria for evaluating entrepreneurs include

honesty, integrity, and a long-term vision. However, investors can extend beyond the

bounds of capital funding. Lehoux et al. (2014) found interrelationships between

technology design and business model development when involving investors, which

could compete with visions of the stakeholders and shareholders. In support of competing

visions, Knockaert and Vanacker (2013) indicated that financial investors are confident in

selecting ventures but have less influence on the value adding activities. However, when

investors monitor VC performance, then the perception of the investor matters. From the

perspective of the investor, VC performance has a positive influence on the VC

reputation (Manigart & Wright, 2013). The investor’s perception of the VC can trigger

VC behavior towards pursuing an IPO or a faster exit (Bertoni et al., 2013).

Parhankangas and Ehrlich (2014) discussed impression management between nascent

entrepreneurs and angel investors, and the notion of impression management might

extend into VC and investor. Although, Dutta and Folta (2016) found that VCs tend to

offer superior value-added services to the investment when compared to angel investors.

VCs act as a broker between investors and portfolio companies. To meet the timely return

on the investment goals of investors, VCs might pursue high-risk, high-return ventures

while attempting to minimize financial loss resulting from pursuing risky ventures.

Relationship between VC and entrepreneur. VC firms can provide a source of

funding for risky entrepreneurial companies. VCs often use proprietary procedures for

discovering and managing entrepreneurs (Khanin & Mahto, 2013). Andrieu (2013) stated

that VCs mostly specialize in seeding and development stages of the business

development cycle. Manigart and Wright (2013) noted the homogeneous effects of VC

selection of startups in high-risk industries. Croce et al. (2015) found that VC firms might

offer better deals to entrepreneurs for high-risk technology ventures that have no

tangibles. As venture uncertainty increases, VCs are likely to provide more frequent

funding with a lesser dollar amount based on the entrepreneur meeting milestones

(Andrieu, 2013). In this context, there exist multiple dimensions of risk regarding VC

investment. Risk might include risk related to the liability of newness, risky industry,

risky technology, and risky markets. Risk relates to information asymmetry.

As mentioned earlier, information asymmetry is the discontinuity between the

knowledge of the investee and the knowledge of the VC investor. However, information

asymmetry extends into other domains beyond investee-VC relationships. VCs must

consider the complexity of these other domains while evaluating startup companies.

Information asymmetry increases the risk of the VC and entrepreneur failing to obtain the

anticipated ROI. Hausman and Johnston (2014) inferred a need for new measures to

account for innovation in risky environments. This new measure comes following the

global financial crisis that created impediments to US-based innovation because of an

unbalanced focus on short-term financial results over the long-term consequences

(Hausman & Johnston, 2014). Nanda and Rhodes-Kropf (2013) studied the times that VC

investors are willing to invest in novel companies with greater risk during hot periods in

the market. Nanda and Rhodes-Kropf go on to clarify the distinction between risky and

worse investments. In this context, risk can be acceptable regarding an anticipation of an

ROI. This risk-acceptance becomes clear when Nanda and Rhodes-Kropf revealed that

risky firms could result in greater ROI if the company becomes profitable through an

acquisition or an IPO. VCs do not invest in gamblers; VCs will invest in individuals

knowledgeable of the market and capable of managing or minimizing risk (Pollack &

Bosse, 2014; Fisher, Kuratko, Bloodgood, & Hornsby, 2017). Furthermore, Li et al.

(2013) attempted to define a mathematical formulation linking the volatility of the market

and investee performance to a point in time to sell the investee company. Given the

complex dynamics that VCs face while investing in companies, VCs might distribute risk

and reduce negative financial effect through the act of syndication.

VC syndicates. Forming a syndicate is a means for VC and capital investors to

reduce the effect of loss resulting from risk and uncertainty. Khavul and Deeds (2016)

indicated that the most pervasive reason that syndicates exist is that syndicates are an

efficient way to share risk among VC partners, as well as an effective screening process.

VCs might use syndicates and portfolio of investment firms to spread risk and to reduce

uncertainty (Terjesen et al., 2013). However, even with syndicates, risk and uncertainty

in startup businesses continue to exist (Khavul & Deeds). Also, Khavul and Deeds

rationalized that the VC, who is the lead in the syndicate, provides the majority of the

financing. For this reason, to hedge against the risk related to uncertainty, VCs leverage

diversification and syndication in their investment portfolio (Rosenbusch et al., 2013).

Exercising syndication is another channel for risk distribution among other VCs and

investors to reduce the effect of loss to a single VC. Syndicates are not only a means for

risk reduction and diversification, but also syndicates are useful for bringing value to

investment partners.

VC syndicates can have influences on the VC’s entrepreneurial assessment

activities. Heughebaert and Manigart (2012) indicated that young VCs might establish

themselves with a syndicate to build themselves in the market. Furthermore, Terjesen et

al. (2013) indicated that VCs who belong to syndicates and other social associations tend

to exhibit homogeneous decision-making behaviors. For this reason, syndicates have an

influence on common evaluation behaviors and expectations of VC performance.

Through these behaviors and expectations, Khavul and Deeds (2016) indicated that

syndicates have a greater demand for due diligence, monitoring, and information. Li,

Vertinsky, and Li (2014) found that the VC’s past success and the VC’s association with

a syndicate could improve the success rate of investors. The social interaction of VCs

with syndications can improve the success rate of investee companies while distributing

risk across all the syndicated VC partners. Although distributing the risk of investment

across all VC collaborates through syndication reduces the positive returns to the primary

investors. Therefore, VCs must identify the best investment method for their strategic

objectives.

Challenges of VCs assessing entrepreneurs. Distinguishing between good

entrepreneurial investments and poor entrepreneurial investments is difficult for VCs.

Flor and Grell (2013) outlined the difficulty in assessing entrepreneurial investments

because the VC does not fully determine an entrepreneur's intent until post investment. Li

et al. (2016) found that VCs invest in entrepreneurs who are proven high quality during

the first stage output when a reduction in uncertainty and a reduction in information

asymmetry exist. Furthermore, Muzychenko and Liesch (2015) suggested that

entrepreneur self-efficacy has a positive influence on signaling the execution of business

opportunities. Muzychenko and Liesch inferred that entrepreneurs with high self-efficacy

had high confidence in paying back the debt. Wood, Bradley, and Artz (2015) made a

similar finding when they indicated that entrepreneurs who exhibit optimism could lead

to business growth. Therefore, entrepreneur self-efficacy in debt financing synthesizes

into the notion that entrepreneurs with high self-efficacy have high confidence of success

and passion in the venture. Henry (2016) suggested that an entrepreneur’s preparedness

supersedes the entrepreneur’s passion in terms of the funding decision-making tactics of

VCs. Brundin and Gustafsson (2013) argued that positive emotions from the entrepreneur

increase the propensity for the VC to invest in the entrepreneur when uncertainty is high.

Conversely, Monika and Sharma (2015) described some challenges with the VC

decision-making process that includes bias and heuristics. Therefore, subjective displays

of entrepreneurial preparedness, passion, and emotion might suggest the challenge of

computerizing all VC decision-making initiatives. Consequently, entrepreneurs having

strong emotional ties to their venture could have an unwillingness to terminate the

continuation of poor investments. For this reason, given the notion of preparedness,

passion, emotions, and self-efficacy, none of these attributes illuminates any specific

patterns that VCs might link into strategies for identifying profitable ventures. VCs must

develop strategies for assessing entrepreneurial companies in complex environments to

identify those with the highest probability of success.

When VCs have all the necessary information, then they can make the best

decision to identify and invest in successful startups (Rosenbusch et al., 2013). The

definition of a successful startup includes a VC exit through an IPO or a buyout (Nanda

& Rhodes-Kropf, 2013; Cassar, 2014). However, because of information asymmetry,

VCs must operate in a world of less than ideal conditions when making decisions to

invest in startups (Vogel et al., 2014). Information asymmetry creates risk and

uncertainty that could affect decisions of the VC to invest in entrepreneurial startups (De

Treville et al. , 2014). Information asymmetry and interaction between the VC and

investors, combined with the interaction between the VC and the entrepreneur influences

investment decisions of the VC (De Treville et al., 2014). Endogenous and exogenous

factors also influence the assessment strategies of VCs (Li et al., 2016). Some factors

directly influence the assessment strategies of VCs, while other factors are beyond VC

control (Tykvová & Schertler, 2014). Exogenous factors like market conditions, location,

and econometric indicators integrate into the decision of the VC to invest in a startup

(Tykvová & Schertler, 2014). Endogenous limitations, capabilities, and timing of the VC

firm influence the decision to invest in a startup (De Treville et al., 2014). These factors

coincide in a manner that could drive the VC to decide to accept or to reject the

entrepreneurial investment opportunity. VCs must regularly make assessment decisions

about startups based on incomplete information that stems from a world of less than ideal

conditions (Trigeorgis, 1996). Most often, the decision to invest in a startup results in a

company that fails to meet the expectation of shareholders (Nanda & Rhodes-Kropf,

2013). Investigating the pervasive nature of these factors above alongside the interactions

between the VC and the entrepreneur requires a deeper understanding of decision-making

strategies of VCs. Understanding the decision-making strategies of VCs roots with the

goal of identifying how VCs identify profitable startups in the southeastern United States.

Holistically, the interaction between VCs and entrepreneurs centers on the

assessment strategies of funding risky ventures. Typically, entrepreneurs in the United

States seeking VC funding are pursuing innovative high-tech ventures (Knockaert &

Vanacker, 2013). High-tech innovation ventures are risky and uncertain (Knockaert &

Vanacker, 2013). Risk relates to uncertainty because of information asymmetry among

VCs and entrepreneurs.

VCs prefer to invest in startups that have members representing diverse

backgrounds and skills (Kakarika, 2013). Also, VCs invest more time in businesses that

they feel might result in a higher likelihood of an IPO (Gerasymenko & Arthurs, 2014).

Therefore, continuous monitoring of the startup is essential to the VC (Hirsch & Walz,

2013). For startups, negative outcomes of conflict stemming from excessive diversity

lead to unrecoverable conflicts and impediments to progression (Kakarika, 2013). Too

little diversity leads to a business that fails to innovate because of the narrow focus

among the team members (Kakarika, 2013). For this reason, extremely high and

extremely low levels of diverse opinions are destructive to a startup (Kakarika, 2013).

Entrepreneurial team diversity includes (a) diversity of opinion, (b) diversity of expertise,

and (c) diversity of power (Kakarika, 2013). The author suggests that business founders

should build teams of maximum diversity while minimizing maximum power (Kakarika,

2013). There must be a balance between diversity and similarity in team members

(Kakarika, 2013). VCs evaluate these entrepreneurs and include risk assessment tactics as

part of their entrepreneur selection strategy (Andrieu, 2013). Conversely, Guinn (2013)

found that methods for evaluating good people could include systems for measuring

thinking skills, team orientation, adaptability, leadership, and change management

capabilities. However, generally accepted business assessment and monitoring tactics that

were sufficient in the past might not remain tolerant for future organizational

performance and design (DaSilva & Trkman, 2014). However, regardless of the type of

VC, monitoring is essential (Hirsch & Walz, 2013). For this reason, traditional VC

entrepreneurial assessment tactics that might have an inclination to protect shareholder

interests through risk aversion might present roadblocks that stifle entrepreneurial

innovation. The consequence of these roadblocks might have a rippling effect because of

unrealized or missed opportunities for shareholders, VCs, entrepreneurs, and society

through unrealized ROI and job creation. The manner in which VCs assess entrepreneurs

becomes essential for identifying the most promising companies that could lead to a

successful IPO or a successful buyout exit.

Many VCs tend to leverage methods for evaluating entrepreneurial startups by

using tactics similar to corporate project evaluation practices (Zeng & Zhang, 2011). Net

Present Value (NPV) and Discounted Cash Flow (DCF) are popular financial instruments

for determining whether the project or venture, is worthy of investment (Zeng & Zhang,

2011). The basic premise for the NPV calculation derives from the sign of the result; if

the sign is positive, then the project or venture is worthy of investment. Conversely, if the

sign of NPV is negative, then the venture is not worthy of investment. However, Zeng

and Zhang (2011) indicated that NPV could lead to the wrong investment decisions

because of the mantra accept or never accept criteria underlying the foundation of the

method. Also, Zeng and Zhang mentioned the limitations and misuse of DCF because of

assessors’ assumptions of estimated future cash flows deriving from certainties while not

accounting for an uncertain future. A shortcoming of traditional DCF methods is the

inability to recognize the value of active management in adapting to changing market

conditions (Trigeorgis, 1996). These shortcomings become clear upon the inspection of

failure rate statistics of VC-backed companies.

High levels of risk and uncertainty in entrepreneurial startups could cause VCs to

have a difficult time identifying sustainable and profitable companies that might result in

a strong ROI. When VC-backed startups are sustainable and profitable, then the results

include creating value for investors and the economy (Terjesen et al., 2013). However,

partly due to risk and uncertainty, VC firms fund only 0.5% to 1.0% of entrepreneurial

business plans because most startup ventures fail (Nanda & Rhodes-Kropf, 2013).

Conversely, Vogel et al. (2014) studied the decision-making tactics of VCs investing in

seed-stage startups. They mentioned that 20% of business proposals continued beyond

the assessment of the VC investors. De Treville et al. (2014) indicated that VCs spend

about 33% of their time on the entrepreneur evaluation and assessment process. Chen and

Chang (2013) indicated that VCs reject 9% of entrepreneur startups because of the lack of

VC resource capacity to evaluate each company. However, out of the VC-funded

startups, half of the companies exit with a non-zero value, and 85% of the returns come

from only10% of the funded companies (Nanda & Rhodes-Kropf, 2013). Additionally,

Nanda and Rhodes-Kropf (2013) in a study of VCs experimenting with riskier than usual

investments found a 27% probability of bankruptcy in risky industries that include

biotechnology, healthcare, and financial services. Arcot (2014) pointed that VCs on

average owns 36.6% of the firm before the IPO. In a study of VC-backed companies

from 23 French VCs, 10% of the companies resulted in an IPO, while 64% of the

companies resulted in a sale and 24% was some other exit type (Gerasymenko & Arthurs,

2014). Since some VCs reject high percentages of entrepreneurial business plans while

most of the 1% of the funded startups have a high probability of failure, then there exist

an opportunity for further inquiry. Soken and Barnes (2014) corroborated this statement

when they indicated that the results of a McKinsey survey showed that 65% of executives

are disappointed in their ability to promote innovation. The situation of disappointing

returns becomes exasperated because, since the dot-com era, there are fewer IPOs and

many VCs are transitioning towards mergers and acquisitions as an alternative to IPO

(Waite & Jamison, 2013).

VCs experience the challenges of evaluating entrepreneurs with limited

information. This limited information is information asymmetry (He & Wan, 2013). As a

method of evaluating investment startups, VCs use signals as part of the assessment

practices. Guinn (2013) indicated that some strategies that VCs might use to evaluate an

entrepreneur are by observing signals that could identify whether or not the entrepreneur

might be a good candidate for investment. However, Flor and Grell (2013) mentioned the

difficulty of differentiating between a good and a bad entrepreneur occurs following the

initial investment. Eldridge et al. (2013) cautioned that in environments of high

uncertainty, signals are unreliable in predicting technological and market behaviors.

Although, Goel and Göktepe-Hultén (2013) suggested that patents and prototypes could

send a positive signal to VCs in the same markets. Haeussler et al. (2014) drew a similar

conclusion when they indicated that companies that demonstrate a larger set of

technological capabilities receive VC financing faster.

Influence of signals in making investment decisions. Signals are useful for

informing the market by extending the notion of VC assessment into environmental

dynamics. In this context, the investment market might use signals to base the decision of

a forthcoming IPO. Spitzeck et al. (2013) indicated that organizations should establish

signals of sustainability to attract an IPO or a buyout. Also, Arcot (2014) discussed

signals that VCs send to the market when converting stocks. Ecer and Khalid (2013)

postulated that VCs with high industry experience tend to increase their investments the

most when the public markets’ signals are favorable. Vogel et al. (2014) cautioned the

use of signals for VCs investing in foreign cultures that might not persist in the United

States cultures. Inmaculada and Francisco (2013) supported a similar perspective when

they indicated that some country cultural values led to higher entrepreneurial intention.

Signals could mislead investors regarding entrepreneurial performance in market

dynamics. Therefore, VCs tend to leverage decision-making strategies as a means to base

decisions to invest in entrepreneurial companies (Nanda & Rhodes-Kropf, 2013). There

exist salient strategies that VCs might use to assess entrepreneurial startups (Hsu, 2013).

As mentioned earlier, Terjesen et al. (2013) indicated a homogeneous decision-making

effect that occurs with VCs affiliated with a syndicate. Kremljak and Tekavcic (2014)

presented a decision-making support system based on real options theory – a discussion

of real options theory would come later in the review of the literature. The Kremljak and

Tekavcic’s model incorporates risk management and uncertainty. Although, Kremljak

and Tekavcic also indicated that corporate politics influences the execution of decision-

making strategies. Daming et al. (2014) conducted a decision-making analysis that

described a corporation’s decision to innovate when confronted with the challenges of

uncertainty. Simón-Moya and Revuelto-Taboada (2016) used a mathematical model that

identifies entrepreneurs’ characteristics relating to education, experience, and motivation

as important factors to firm survival. Daming et al. (2014) created a model that identified

innovative technological trajectories leading to the entrepreneurial decision to invest in a

venture. These models above may synthesize to decisions that VCs might use when

assessing an entrepreneurial company. However, Li et al. (2013) reflected on the

complexities of equity-based entrepreneurial financing which creates decision-making

challenges because of an inability to describe the complex phenomenon in a linear model.

Pauwels et al. (2013) indicated that there are too many parameters lost in the translation

of the variables to derive real-world knowledge into well-defined information structure.

The loss in translation is because humans with multiple perspectives are unable to

calculate all possible actions in which economists assume because the complexities of the

world, the volume of information, and the cognitive abilities of humans are too limited to

allow (Rodríguez, Martínez, & Herrera, 2013). From an accounting practice perspective,

Smith and Cordina (2014) evaluated the effectiveness of accounting practices in high-

tech investment. Smith and Cordina indicated that some VCs use financial statements as a

starting point while other VCs do not consider financial statements a major component of

the entrepreneur assessment process. Smith and Cordina continued by mentioning that

some VCs use various documents including financial statements, business plans,

executive summaries, and any disclosures about future expectations as a method of

assessment before investment. Also, Smith and Cordina found that important

characteristics that VCs use to evaluate entrepreneurial ventures include the personal

qualities of the team or management and the experience in bringing projects to market.

Smith and Cordina reflected on the absence of an explicit formula that can determine the

value of an investment. As such, the literature provides little reflection on a holistically

viable collection of decision-making strategies that VCs use that result in identifying

profitable startups.

Complexities of VC investment decisions. Since VCs are typically unable to

rely on syndicates, innovation trajectory models, traditional finance theories, financial

statements, nor any other explicit formula holistically to identify profitable investments,

then some VCs might base their investment decisions on the human capital of the

investee company (Smith & Cordina, 2014). Internal factors of human capital from the

entrepreneur and the entrepreneurial team could affect the assessment of the VC funding

decision and the effectiveness of establishing a competitive business (Townsend &

Busenitz, 2015). Probert et al. (2013) indicated that know-how creates a strong business

base, particularly when the underlying technology is closer to the market. Huarng (2013)

described the effectiveness of the entrepreneur’s business model when operating a

profitable business. For this reason, the business model and internal factors of human

capital that make up the talents and skills of the entrepreneurial team are important to

VCs for meeting the goals of finding a profitable startup and mitigating risk. However, in

changing environments of high-risk and uncertainty, VCs need methods and strategies for

assessing and better identifying startups that will likely result in a successful VC exit.

Real Options Theory

ROT was the conceptual framework for this study. Trigeorgis (1996), described,

all things being equal, the average investor is risk averse while operating in a world of

business where the existence of risk and uncertainty is unavoidable. Management teams

use methods like NPV and diversification to manage risk (Trigeorgis, 1996). Traditional

NPV results in a decision to either invest or abandon a project (Trigeorgis, 1996).

Diversification spreads risk in an offsetting manner across the portfolio (Trigeorgis,

1996). However, diversification does not directly address the shortcomings of traditional

NPV methods because the result of NPV is the decision to either invest or not invest in a

project. The real options theory is a framework for connecting diversification with

hedging against risk and uncertainty.

History of ROT. ROT started in the financial investment industry. However,

ROT has advantages in other industries where investors and stakeholders must address

risk and uncertainty. Black and Sholes (1973) derived a mathematical formulation within

the investment industry for modeling and addressing risk and uncertainty. The

formulation represents a set of differential equations for aiding investors in hedging

against risk and uncertainty within a portfolio of investments (Black & Sholes, 1973).

The hedging occurs by presenting investors with an option to buy or sell a security within

a specified timeframe (Black & Sholes, 1973). The Black and Sholes differential

equations for hedging against risk and uncertainty are real options (Fernandes, Cunha, &

Ferreira, 2011). ROT derives from the Black and Scholes differential equations and

relates to a decision-tree analysis that supports decision-making strategies of investors by

allowing course adjustments as uncertainty reduces over time (Baduns, 2013). Real

options have applications that extend beyond the investment industry and into a broad

scope of other industries where investors must make investment decisions with risk and

uncertainty (Trigeorgis, 1996; Mun, 2006; Cheng et al., 2011; Peng, Lee, & Hong, 2014).

The advantage of real options over traditional assessment methods is that real options

provides investors the option to continue, abandon, or switch an investment (Fernandes,

Cunha, & Ferreira, 2011). The real options theory is useful for assessing ventures that

have uncertainty (Cheng et al., 2011). The nature of entrepreneurial startups is risky and

uncertain because of information asymmetry between the entrepreneur and the VC.

Therefore, the real options theory could provide a suitable conceptual framework for

describing some strategies that VCs might use when investing in profitable startups.

Flexibility of ROT. The use of ROT provides a VC the option to assess and

reassess the value of the venture throughout a finite lifespan of the investment. Therefore,

ROT is the right, but not the obligation to invest or continue investing (Cheng et al.,

2011). The option to invest in a venture provides an advantage over traditional financial

assessment tactics that consist of all or nothing investment mentality (Cheng et al., 2011).

Decision-makers have the option to make course corrections as information asymmetry

and uncertainty reduces over time (Mun, 2006). Mun (2006) described several types of

options that include the option to (a) switch, (b) abandon, (c) expand, and (d) contract.

Options provide an investor the ability to make profitable decisions in the midst of risk,

uncertainty, and information asymmetry.

Through the lens of ROT, the conceptual framework of this study for VCs

assessing entrepreneurial startups in uncertain and risky environmental and market

conditions exist. The application of ROT has advantages of optimizing investment

decisions to increase the likelihood of venture success. Mun (2006) described that real

options are useful for identifying and navigating investment decision pathways and

strategic decision pathways in the midst of uncertainty. Mun also indicated that real

options are appropriate for prioritizing and timing the execution of investment decisions

to increase the likelihood of venture success.

Applications of ROT. The notion of real options has existed in the academic

literature for decades (Zeng & Zhang, 2011). Zeng and Zhang (2011) indicated that the

concept of real options dated back to Myers in 1977 in relation to the similarities between

real options and financial options. However, Nobel Prize laureates Merton, Myron, and

Black identified that the formula for financial investment options applies to real options

(Haeussler et al., 2014). Therefore, the concept of ROT has roots in financial call options.

Financial call options center on the notion that investors have the right to buy or sell an

asset at a pre-specified price for a pre-specified length of time (Fernandes et al., 2011).

The idea of ROT is to give managers the flexibility to decide to invest in an asset today

with the option to abandon or continue with the investment in the future (Fernandes et al.,

2011). Chung et al. (2013) indicated that although ROT was historically criticized for

perceived lack of real world applicability, ROT was comparable to risk diversification

theory. For this reason, the basis of financial options creates the underlying pattern to

transition the same concept of financial options into other applications.

Some scholars described the effectiveness of ROT (Fernandes et al., 2011; Chung

et al., 2013). ROT provides a decision-making mechanism for investing in a venture that

would otherwise result in investment rejection when using traditional NPV and DCF

financial evaluation methods as the determinant. When demand is uncertain, then there is

an opportunity cost for deciding to invest with the risk of losing the option as new

information becomes available (Bertoni et al., 2013). ROT is a method for addressing

uncertainty in changing conditions (Podoynitsyna, Song, Van Der Bij, & Weggeman,

2013). ROT is a method for expanding on traditional financial instruments as a means of

evaluating risky ventures. Through ROT, VCs can assess entrepreneurial startups in the

midst of uncertain conditions.

In the context of finance, ROT has advantages over traditional assessment

methods. Zeng and Zhang (2011) discussed the advantage of real options over the

traditional NPV and DCF instruments. Fernandes et al. (2011) supported this position

when they referred to a study of renewable energy sources (RES) where ROT provided

superior performance although DCF was negative. For this reason, limitations and misuse

of DCF come from the assessors’ assumptions of estimated future cash flows deriving

from certainties that do not account for an uncertain future (Zeng & Zhang, 2011).

However, Mun (2006) explained that real options are not a substitute for NPV and DCF;

real options complement NPV and DCF because NPV is for seeding the binomial lattice.

Also, Zeng and Zhang (2011) showed a robust flow of literature history describing the

broad application of real options in various industry segments. Real options provide a

suitable method for managing uncertainty in high-risk projects (Zeng & Zhang, 2011).

ROT provides a method for VCs to base decision-making strategies of entrepreneurs in

high-risk ventures.

Decision-making systems that support a ROT framework provide a means for

evaluating entrepreneurial startups. Kremljak and Tekavcic (2014) created a model for

supporting a decision-making support system based on ROT. Kremljak and Tekavcic

found that when organizations buy options for the future, coinciding with the greater the

uncertainty of the business, then the greater the organizational system gains. De

Magalhães Ozorio, de Lamare Bastian-Pinto, Nanda Baidya, and Teixeira Brandão

(2013) submitted that ROT is an adequate tool when making decisions with high

uncertainty. Fernandes et al. (2011) showed methods of application of ROT in terms of

partial differential equation approach, dynamic programming, and simulation to support

the option to invest. The basic premise of the partial differential equation approach is to

express the value of an option in mathematical terms with boundary conditions

(Fernandes et al., 2011). The partial differential equation approach is useful for

developing a model for determining the optimal time to invest in technologies and for

identifying key parameters that could affect the investment decision (Fernandes et al.,

2011). Applying ROT using a method of dynamic programming is useful for optimizing

decisions on future payoffs (Fernandes et al., 2011). Applying ROT through Monte Carlo

simulations is effective for modeling real life scenarios with complex relationships

between variables and complicated business rules (Fernandes et al., 2011). However,

from the perspective of computer simulations, Trigeorgis (1996) noted that although

investors and managers can adapt to changing conditions, computer-simulated models do

not adapt to changing conditions in the same manner. For this reason, decision-making

strategies in industries of high uncertainty, as seen through the eyes of scholars, suggest

that real options are a means for addressing the high uncertainty that accompanies risky

ventures.

From a strategic approach, ROT provides a decision-making mechanism for

investing in a venture that would otherwise be rejected using traditional financial

evaluation methods as determinant in NPV and DCF instruments. ROT is a method for

expanding on traditional financial instruments as a means of evaluating and predicting

entrepreneurs’ performance. Through the framework of ROT, VCs can assess

entrepreneurial startups in the midst of uncertain conditions. Fernandes et al. (2011)

argued that ROT is useful for evaluating ventures with high initial costs, high financial

risk, and uncertainties. Considering the uncertainty that accompanies high-risk ventures,

in addition to the shortcomings of pure NPV and DCF represents an opportunity for

further inquiry. The assessment strategies that VCs could use to evaluate risky ventures

while predicting profitable ventures become the focus of this research.

ROT and game theory. A supporting theory to ROT is game theory. Game

theory is the study of strategic decision-making patterns in competitive and risky

environments (Azevedo & Paxson, 2014). Some scholars use game theory and ROT to

explain decision-making patterns of investors who operate in competitive environments

of risk, uncertainty, and information asymmetry (Azevedo & Paxson, 2014; Daming et

al., 2014). Daming et al. (2014), in a quantitative study, described a mathematical model

that incorporated Poisson, ROT, and game theory to predict trajectories of innovation in

risky and competitive markets. The mathematical model could be a strategic tool for VCs

to identify profitable startups by aiding in predicting the market dynamics of innovations.

Azevedo & Paxon (2014) combined the concepts of ROT and game theory to create a

model of investment analysis that is suitable for addressing risk and uncertainty in a

competitive environment. According to Azevedo and Paxon, their model provided

advantages over classical investment evaluation methods that derive from unrealistic

assumptions. Also, ROT may be limited in addressing the external influences of

competition that could trigger changes in market dynamics through discontinuous

innovations. The use of game theory could provide an alternative conceptual framework

for describing how VCs identify profitable startups. The game theory could include

information that highlights the competitive dimension of VCs in identifying profitable

startups in a manner that supports ROT.

Alternative explanations to ROT. There may be alternative explanations to

ROT that could provide contrasting conceptual frameworks in the study of VC strategies

for identifying profitable startups. Contrasting explanations to ROT include investors

making risky investment decisions within the domain of economic theory. Virlics (2013)

used economic theory to describe the behavior of VCs in making investment decisions

that include risk, uncertainty, and information asymmetry. Virlics observed that VC

investment decisions are subjective, and influences of VC decisions include past

performance, the perception of risk, expected cost of investment, while not devoid of

emotional responses of VC behavior. In addition, Brundin and Gustafsson (2013) found

that uncertainty is a strong moderator in the relationship between emotions and the

propensity to continue investing in projects. The economic theory contrasts ROT by

illuminating the subjective and the emotional components of VC investment strategies

within a conceptual framework that might be less prevalent in the application of ROT. In

particular, the application of ROT shows less emphasis on the emotional attributes of VC

behavior whereas economic theory could incorporate VC emotional attributes as a critical

component in evaluating risky investments. The subjective and emotional responses of

VCs could influence investment decisions that lead to identifying profitable startups.

Another alternative explanation that could explain the influence of VC strategies

in identifying profitable startups is behavioral and legitimacy theories. Petkova, Wadhwa,

Yao, and Jain (2014) applied behavioral and legitimacy theories to study the role of VC

reputation when evaluating investments that include risk, uncertainty, and information

asymmetry. Petkova et al. found that VC firms with higher reputations tend to emphasize

risk reduction strategies to maintain a high reputation and legitimacy among investors.

Renko (2013) offered a parallel view of legitimacy from the perspective of entrepreneurs.

Renko indicated that nascent entrepreneurs should focus on establishing legitimacy with

VCs early to decrease the perception of risk and uncertainty. Establishing and

maintaining VC reputation and legitimacy among investors could influence VC selection

strategies of risky ventures. Based on the conceptual framework of behavioral and

legitimacy theories, VCs might place greater emphasis on maintaining a high reputation

and legitimacy with investors over the merits of the investee firm. Therefore, VC

reputation and legitimacy could be a modulator to an investment strategy as oppose to the

result of an investment strategy. Behavioral and legitimacy theories might provide a

viable alternative to ROT regarding VC investment strategies for identifying profitable

startups.

The collection of resources that constitutes this review of the literature shows a

broad array of ideas regarding strategies that VCs use for identifying startups that could

result in a successful VC exit. Some scholars demonstrate decision-making complexities

in human interactions in a manner that might generalize to identifying profitable startups

(Rodríguez et al., 2013). Other scholars believe that under certain conditions, there is the

possibility of identifying profitable startups through mathematical modeling techniques

(Kremljak & Tekavcic, 2014; Fernandes et al., 2011). Still, some scholars have indicated

that signals from various sources are useful for identifying profitable startups (Guinn,

2013; Spitzeck et al., 2013). Still, other scholars assert that the experience of the VC and

the entrepreneur are key factors for identifying profitable startups (Ecer & Khalid, 2013;

Smith & Cordina, 2014). Considering the various scholarly perspectives, ROT was a

suitable conceptual framework that enables the convergence of the different VC

assessment strategies toward consistent themes of identifying profitable startups. Based

on the information in the review of the literature, there were no clear strategies emerging

that identify reliable methods for assessing startup entrepreneurs in a manner that predicts

a successful VC exit. The previous assertion is evident in the high number VC-backed

companies that fail to meet investment performance expectations (Nanda & Rhodes-

Kropf, 2013). For this reason, there is an opportunity to begin addressing a gap in the

literature by qualitatively exploring the techniques that VCs use in assessing startups in

the southeastern United States. Based on the qualitative study, concepts became clear that

could provide direction for both inexperienced VCs and experienced VCs operating in the

domain of funding high-risk, high-return entrepreneurial startup companies. Also, the

results of the qualitative study could illuminate strategies for nascent entrepreneurs to

make better decisions regarding ideas of novelty. The results of this study could lead to

positive social change by enabling better supply-side and demand-side investment

decisions from both VCs and startup entrepreneurs.

Transition

Section 1 was an introduction to the framework of the research. The framework of

the research includes the problem statement, the purpose statement, the research question,

the nature of the study, the conceptual framework, the operational definitions, the

significance of the study, and the review of the literature. Section 1 also included

information highlighting the focus of the study by centering on the challenges that VCs

face when evaluating startups that could result in a successful VC exit. The challenges of

risk and uncertainty that VCs face set the context of the research question and the

foundation for selecting ROT as the basis for the conceptual framework.

Section 2 includes the role of the researcher, the method for identifying

participants, the selection of qualitative methodology, the selection of a case study design

strategy, the focus on conducting ethical research, the focus on validity and reliability, the

data collection method, the method for analyzing the data, and the organization of the

data. Section 3 contains the presentation of the findings derived from the research data.

The presentation of the findings includes an application to professional practice, the

implications for social change, recommendations for action, recommendations for further

study, and reflection.

Section 2: The Project

The purpose of Section 2 is to provide a description of the research design

strategy and the rationale for the design selection. This research study was a qualitative

method using a case study design strategy. Section 2 includes discussion on the (a)

purpose statement, (b) role of the researcher, (c) participant selection, (d) research

method, (e) research design, (f) population and sampling, (g) ethical research, (h) data

collection instrument, (i) data collection technique, (j) data organization techniques, and

(k) reliability and validity. Section 2 also includes a description of the tactical approach

to addressing the research question, which centers on strategies that VCs could use for

identifying and investing in profitable startups.

Purpose Statement

The purpose of this qualitative multicase study was to explore strategies that VCs

use in determining which businesses would become profitable when investing in startups.

Eleven VCs from eight firms located in the southeastern United States participated in

interviews to share their entrepreneur selection experiences. The findings from this study

may result in a positive social change by illuminating VC strategies that investors could

use to lead startup businesses to profitability. Sustainable and profitable startup

businesses might contribute to positive social change by propelling the global economy

forward through job creation and investor ROI.

Role of the Researcher

The role of the researcher includes conducting an honest study with the highest

ethical standards while striving for ensuring credibility and accepting responsibility for

the research work (Yin, 2014). As the researcher, my role in the data collection process

included conducting interviews with VC participants while triangulating findings with

archival documents, field notes, and reflexive journal entries using methodological

triangulation. Qu and Dumay (2011) indicated that interviewers try to remain open to

new ideas during participant interviews while avoiding imposing the interviewer’s

preconceived notions. As the researcher, I focused on each participant’s interview

question responses and remained open and receptive to new ideas while adhering to the

ethical standards of the university.

Twining, Heller, Nussbaum, and Tsai (2016) described how epistemological and

ontological views integrate with the researcher-participant experiences to richly describe

a phenomenon and contribute to the validity of the research. Vogel et al. (2014) showed

that members of a VC firm possessing diverse experience in fields including

management, engineering, and information technology are capable of identifying

profitable startups. I brought more than 20 years of practitioner experience from the fields

of management, engineering, and information technology into this research. My only

interaction with VCs related to pursuing startup capital for a biotechnology venture in

early 2000. Therefore, I had neither personal nor professional contact with VCs who

participated in this study.

Ensuring ethical integrity includes integrating principals outlined in the Belmont

Report protocol under the authority of the U.S. Department of Health and Human

Services as a strategy for ethical compliance (U.S. Department of Health and Human

Services, 1979). I completed the Protecting Human Research Participant training by the

National Institutes of Health (NIH) Office of Extramural Research (Certification No.

1322814). Using the Belmont Report and NIH training, I proactively anticipated and

addressed any potential ethical issues that could compromise the confidentiality of the

participants and their organization.

Mitigating biases in research include being sensitive to alternative explanations

from participants (Yin, 2014). To mitigate researcher bias, I established confirmability by

implementing techniques of auditing, triangulation, member checking, and reflexive

journaling for data collection. Lincoln and Guba (1985) asserted that auditing,

triangulation, member checking, and reflexive journals are techniques for mitigating

researcher bias while supporting the notion of viewing the data through a personal lens.

The design of this qualitative research included semistructured interviews as part

of the data collection strategy. Moustakas (1994) indicated that conducting research on

humans requires a method that is systematic, orderly, disciplined, and executed with care

and rigor. Lincoln and Guba (1985) mentioned that interviewers should follow

established steps and guidelines executed in a systematic manner when interviewing

participants. An interview protocol is useful for guiding the interaction with participants

in a systematic and orderly manner (Kokka, 2016). Therefore, I used an interview

protocol (Appendix A) that included the interview questions, the procedure for executing

the interview, and scripts used before, during, and after the interview with each

participant. The integration of the interview protocol within the case study design

establishes the foundation for a credible study (Yin, 2014).

Participants

VCs are a specialized group of professionals with unique knowledge and

experience evaluating, investing, and supporting startup ventures (Monika & Sharma,

2015). Bartkus et al. (2013) indicated that an identifier of VC experience includes

working in a VC firm. Hsu (2013) mentioned that experienced VCs who finance startups

are more likely to exit with an IPO. However, Khanin and Mahto (2013) cautioned that

VCs with at least 5 years’ experience could become ineffective in evaluating startups

because they might lose the learner’s mindset from their portfolio of companies. The

criteria for participant eligibility included at least 5 years of VC experience evaluating

funding rounds for startups. The selection of participants with at least 5 years VC

experience may ensure that each participant has sufficient experience to address the

research question.

The source for identifying participants for this study was the Dow Jones

VentureSource database. VentureSource is a semipublic database that is accessible

through a user subscription (Nanda & Rhodes-Kropf, 2013). Townsend and Busenitz

(2015) indicated that VentureSource is a major database for identifying the performance

profile and locations of VC firms. Lutz, Bender, Achleitner, and Kaserer (2013)

established that VentureSource is largely unbiased from the perspective of industry and

performance of VCs. Furthermore, Nanda and Rhodes-Kropf (2013) asserted that

VentureSource is a popular database for many academic papers on VCs. Therefore, data

from the VentureSource database was useful for identifying VC firms that meet the

performance criteria and the geographic location of the case study population.

Following access to the VentureSource database, I searched for VC firms meeting

the IPO performance criteria. Using VentureSource, the search criteria for identifying VC

firms having an IPO within the past 5 years include:

1. Select the investment round type option as IPO.

2. Set the finance completion-date range between January 2012 and January 2016.

3. Set the investor type option to VC.

4. Select southeastern United States as the investor region.

The search results included a list of investee companies with an IPO within the

past five years. A review of each investee company from the search results showed the

investor VC firm located within the southeastern United States meeting the search

criteria. Selecting the option for additional information showed demographic information

including the name, address, email, and phone number of a representative of the investing

VC firm.

An additional type of search from VentureSource™ was appropriate for

identifying VC firms in the southeastern United States having an investee buyout within

the past five years. The search criteria for identifying VC firms having an investee buyout

within the past five years include:

1. Select the investor type option as VC.

2. Set the round preference option to buyout.

3. Set the finance completion-date range between January 2012 and January 2016.

4. Select southeastern United States as the investor region.

Using the search results for identifying investee buyouts, the steps for accessing

the VC firm contact information from the IPO procedure also apply to the buyout

procedure. The combination of the IPO search results and the buyout search results

provided the list of VC firms that are eligible for the study. The final list included eligible

VC firms in alphabetical order with duplicate firms removed from the list. The list of VC

firms contained the information to send an introduction email letter and a request for

participation form to an authorized representative of each VC firm.

Gaining access and establishing a working relationship with participants included

sending an email to an authorized representative of the VC firm. After identifying eligible

VC firms and contacts, I sent an introduction email containing the letter of cooperation

and the consent form to an authorized representative of the firm. Orser, Elliott, and Leck

(2011) used a combination of email distribution and purposive selection to identify

participants to engage in an interview-based study. Leonard et al. (2014) showed how

email distribution provides a conduit for identifying and engaging knowledgeable

participants who are relevant for a specific purpose. Moreover, Khanin and Mahto (2013)

leveraged email distribution for identifying and recruiting VCs to participate in a study

that reflected on biases of VCs continuing to invest in follow-on funding. Furthermore,

Hadidi, Lindquist, Treat-Jacobson, and Swanson (2013) indicated that an interactive

consent process, which might include emails, could prevent or resolve issues of

participant withdrawal. Email distribution is an appropriate method for identifying and

inviting participants suitable for addressing the research question (Orser, Elliot, & Leck,

2011).

The emailed introduction letter, Letter of Cooperation, and Consent Form

included my name, affiliation with Walden University, and the purpose of the study. If

the authorized representative did not respond to the initial request for participation email

within seven calendar days, then I sent a second follow-up email. Following Orser, Elliot,

and Leck (2011), if there was no response to the second follow-up email within another

seven calendar days, then I sent a final email. The removal of the candidate VC firm from

further consideration occurred if there was no contact with a firm representative after

seven days following the third follow-up email. Table 1 shows the distribution and

response dynamics of the initial email and follow-up emails sent to VC firms throughout

the southeastern United States.

Table 1

Email Request for Study Participation

Description Number of

emails sent

Number of

email replies

Number of

no response

Request for

conversation

interview

Decline

interview

Initial email 94 8 86 1 1 7

Follow-up 1 86 33 53 6 7 26

Follow-up 2 53 2 51 0 0 2

Final follow-up

51 0 0 0 0 51

The number of emails sent column shows the count of emails sent to each VC

firm. The number of email replies column shows the number of responses received from

a VC firm. The number of no response column shows the number of emails that had no

response or a failed delivery message from the mail server. The request for conversation

column shows the number of VC firm representatives requesting phone conversations to

gain a better understanding of the research as well as to introduce eligible participants

from the firm. These introductory phone conversations provided an opportunity to

elaborate on the study as well as build a working relationship and rapport with potential

participants of the study. The accept interview column shows the number of VC firms

with participants willing to participate in the study. The decline interview column shows

the number of VC firms with representatives who chose not to participate in the study.

Research Method and Design

Investigating strategies that VCs could use toward identifying profitable startups

was a qualitative case study. Muijs (2011) suggested that researchers whose worldview

underlies subjectivists or pragmatism use the qualitative framework in social science

studies. Hanson et al.(2011) indicated that the qualitative case study is appropriate for

describing unexplored complex behaviors, processes, and systems. Furthermore, the case

study is a research design associated with qualitative methodology (Yin, 2014). Yin

(2013) described case study design as suitable for evaluating a phenomenon with

complex relationships or complexity in intention. The case study design was appropriate

for deepening the understanding of the complex phenomenon that tends to influence

VCs’ strategies for identifying profitable startups (Gerasymenko & Arthurs, 2014). This

research was a study of how complex phenomena may influence strategies that result in

sustainable startups.

Research Method

Quantitative, qualitative, and mixed methods approach are approaches for

conducting a research study (Yin, 2014). The selection of a suitable methodology derives

from the goal of the research and not the researcher’s preferences (Jaffe, 2014; Boblin,

Ireland, Kirkpatrick, & Robertson, 2013; Yin, 2014). The researcher should identify a

suitable methodological approach that addresses the research question while considering

the exogenous and the endogenous factors that limit the scope of the study (Robinson,

2014; Sànchez-Algarra & Anguera, 2013).

Mixed methods research includes the methodological combination of quantitative

and qualitative methods in a manner that addresses the research question from multiple

worldviews (Venkatesh et al., 2013). Muijs (2011) indicated that mixed methods

approach is suitable for evaluating both breadth and depth, or causality and meaning of a

phenomenon. The mixed methods approach combines the strengths of qualitative and

quantitative approach and increases the overall strength of the study conclusions

(Östlund, Kidd, Wengström, & Rowa-Dewar, 2011). Practitioners of the mixed methods

approach, either sequentially or concurrently, leverage the combination of quantitative

and qualitative to meet the goal of the research and reduce mono-method variance

(Venkatesh et al., 2013). Practitioners use the mixed methods approach to complement,

expand, corroborate, compensate, diversify, develop, and complete the findings from the

other research method (Venkatesh et al., 2013). Fuhse and Mützel (2011) indicated that

qualitative research could enrich quantitative analysis in mixed methods designs.

Integrating quantitative and qualitative philosophies enable researchers to consider

aspects of the natural world, the conceptual effect of quantitative research, the influence

of human experience, and the conceptual focus of qualitative research integrated together

to formulate inferential conclusions (Östlund et al., 2011). Venkatesh et al. (2013)

recommended selecting the mixed methods approach when the intent of the research is to

provide a holistic understanding of a phenomenon for which existing research is

incomplete. Therefore, selecting the mixed methods approach depends principally on the

research question (Petticrew et al., 2013). Venkatesh et al. (2013) showed that the mixed

methods approach is appropriate when the goal of the research is to address both

confirmatory and exploratory research questions within the same inquiry. In this study,

the central focus of the research question was to explore how VCs evaluate startups in a

complex environment, which does not include the causality of VC strategies in a

confirmatory manner. Therefore, the mixed methods approach was inappropriate for

addressing the research question in this study.

Practitioners of quantitative research tend to work towards linking concepts of

integrated human experiences with processes by gathering, validating, and numerically

analyzing data (Polit & Beck, 2010). Quantitative research is an empirical analysis of

observable phenomena built on a mathematical foundation with intent to discover,

validate, or identify symmetrical or asymmetrical relationships among concepts derived

from a theoretical framework to support or refute a hypothesis (Hanson et al., 2011). The

notion of quantitative research emphasizes objective techniques that include extracting

measurements through mathematical, statistical, or numerical analysis through data

collection instruments including polls, surveys, questionnaires, or pre-existing statistical

data using computational techniques (Jaffe, 2014). The quantitative research is suitable

for establishing relationships between measurable quantities and variables in a deductive

manner (Baduns, 2013). Exploring participants’ perspective within a complex

environment that has unknown variables is not testable within a mathematical context

(Hanson et al., 2011). Therefore, the quantitative research method was inappropriate

because the exploratory nature of this study indicated a population of unknown variables

as new themes and concepts became exposed throughout the research inquiry.

The qualitative method is an inductive bottom-up design approach that illuminates

on textual accounts of the participant’s experiences (Erlingsson & Brysiewicz, 2013).

The qualitative method is appropriate for understanding human being behaviors as they

interact with one another within their environment (Sànchez-Algarra & Anguera, 2013).

Through the lens of qualitative research, the researcher seeks an understanding of true

reality from a perspective beyond their worldview (Erlingsson & Brysiewicz, 2013). The

qualitative method is useful for describing complex interactions that can affect outcomes

that are not easily explainable or identified through mathematical derivation (Petticrew et

al., 2013). Sànchez-Algarra and Anguera (2013) indicated that the qualitative method is a

rigorous contextual description of a phenomenon that represents an account of the

complexity of humans interacting with their environment where multiple forces can

influence decisions. Hanson et al. (2011) mentioned that qualitative method is useful for

understanding a phenomenon based on the evidence within the data as oppose to using

models or theories to predict dynamics of the data. Also, Hanson et al. (2011) showed the

inherent flexibility of qualitative method to accommodate unanticipated, yet important,

findings that might emerge throughout the research inquiry. Therefore, a qualitative

framework was useful for exploring complex interactions between VCs and their

environment where resonating themes could emerge that explains tradeoffs and options

that VCs use to identify profitable startups (Vilkkumaa, Salo, Liesiö, & Siddiqui, 2015).

Research Design

Qualitative methodological research holistically supports a vast array of research

design strategies (Petty et al., 2012). The five commonly used qualitative research

designs are (a) case study, (b) ethnography, (c) grounded theory, (d) narrative, and (e)

phenomenology (Petty et al., 2012). Yin (2013) indicated that the case study design is

appropriate for addressing complex scenarios. The case study design includes a

framework in a real-world scenario to extrapolate rich contextual information suitable for

the exploratory nature of the design (Yin, 2014). Maine, Soh, and Santos (2015) used the

case study design to explore complexities in decisions to invest and pursue ventures with

high risk and high uncertainty. Similar to Maine et al., this research included the case

study design to establish a foundation for exploring the complex decision-making

strategies of VCs when pursuing ventures with high risk and high uncertainty.

There are two main distinctions between case study designs, which are single-case

study and multiple-case study (Yin, 2014). The single-case study is analogous to a single

experiment that focuses on a critical, unusual, common, revelatory, or longitudinal case

(Yin, 2014). Multiple-case study establishes the mechanism to compare and contrast

views on multiple cases (Yin, 2014). Multiple-case study is useful for comparing similar

results among cases or comparing contrasting results for anticipated reasons among cases

(Yin, 2014). Orser et al. (2011) used a multiple-case design to explore the complex nature

of successful feminist entrepreneurs. Probert et al. (2013) selected a multiple-case design

to explore the complexities associated with marketing and consultative selling for

persuading investment into new technologies. I selected a multiple-case design for this

research because of the complex interactions that may exist among VCs, investors, and

entrepreneurs. These complex interactions among VCs and entrepreneurs within the

investment environment could illuminate themes that lead to common strategies for

identifying and investing in profitable startups.

Ethnography is a strategy of inquiry for the researcher to understand the behavior

of a culture in a natural setting (Liberati et al., 2015). Ethnography is the study of a group

through the examination of shared behaviors that influence culture (Petty et al., 2012).

Erlingsson and Brysiewicz (2012) described ethnography as a means to capture

participants’ social meanings in a natural setting. The focus of this study was not the

cultural behavior of people. Instead, this study was exploratory based on the complex and

the dynamic influences from various conditions that might influence salient strategies of

VC assessment practices. For this reason, ethnography was inappropriate for this study.

Grounded theory includes the formulation of an inquiry linked to the derivation of

a theory. The grounded theory includes data based on the interaction between the

participant and the phenomenon to develop a theory associated with a social concept

(Petty et al., 2012). Hanson et al. (2011) described how researchers immerse themselves

into the data to create a testable theory. Ebrashi (2013) used grounded theory to link the

behavior and intention of social entrepreneurs to behavioral theory. The purpose of this

study was to explore strategies that VCs use in determining which businesses would

become profitable when investing in startups; not to bind VC strategies to a theory.

Therefore, grounded theory was inappropriate for this study.

Narrative research is a study method of telling the story of the life of an individual

or a small group of people (Petty et al., 2012). Petty (2016) described narrative research

as an ordered description of an individual’s experiences in the form of storytelling.

Stephens and Breheny (2013) mentioned that narrative research has particular value in

research areas of health and family where participants interact with complex constructs

that include physical, moral, and cultural influences. The study of VC assessment

strategies did not focus on the storytelling of a single individual or the storytelling of a

small group of individuals. Instead, the study of VC assessment strategies was on

exploring salient characteristics among VCs to understand how they identify profitable

startups. Therefore, the narrative research was inappropriate for this study.

Phenomenology is a strategy of inquiry that describes the human essence of a

phenomenon through lived experiences. Moustakas (1994) described phenomenology as

the study of things themselves. Phenomenology is the study method that describes human

lived experiences around a phenomenon to gain deeper insight into a problem (Petty et

al., 2012). Hanson et al. (2011) described phenomenology as the goal to understand

someone’s experience. Phenomenology was inappropriate because the objective of the

study was to understand VC assessment strategies of startups and not the transcendental

understanding of individuals’ lived experiences in a VC environment.

Data saturation occurs when the analysis of the data provides no new discovery or

revelation, and any additional analysis becomes counter-productive (Mason, 2010). Elo et

al. (2014) indicated that data saturation becomes easier to recognize when the collection

and the analysis of the data are done at the same time. O’Reilly and Parker (2012)

mentioned that data saturation is a quality indicator that identifies the limits of the study.

Furthermore, O’Reilly and Parker noted that a study that does not meet full saturation

does not suggest an invalid study but that the phenomenon has not been fully explored.

For this study, data saturation occurred following the rigorous analysis and re-analysis of

the collected data until no new ideas or themes emerged. Massey, Chaboyer, and Aitken

(2014) achieved data saturation by using an inductive approach that involved two levels

of data interpretation. The first level of data interpretation included the continuous review

of the data to discover new and emerging themes (Massey et al., 2014). The second level

data interpretation included the repeated immersion of analyzing the data alongside the

preliminary themes until each theme converged into a single concept (Massey et al.,

2014). Massey et al. (2014) indicated data saturation occurred when no new themes

emerged following the rigorous analysis of data. Following Massey et al., this study

included a similar inductive approach. Following member checking with each participant,

I became immersed in the data to discover new and emerging themes. Data saturation

was met after interviewing 10 participants. However, I interviewed 11 participants to

ensure no new information was discovered. I continuously reinterpreted the themes with

broad and descriptive names to capture salient ideas from each participant. Afterward, I

repeated the analysis of the data with the preliminary themes until each theme converged

into a single concept. Interviews continued until participants no longer provide any new

information.

Population and Sampling

The sample population was derived from a purposive selection of VCs with

experience assessing startup ventures. Purposive selection is a method for identifying and

selecting potential participants that could best illuminate the propositions of the study

(Yin, 2014). Some scholars use the term purposive sampling to define the same purposive

selection method for identifying participants suitable for illuminating the propositions of

the study (Williams, Burton, & Rycroft-Malone, 2013; Orser et al., 2011; Parlalis, 2011).

However, Yin (2014) indicated that the term sampling could mislead readers into

believing that the purposive sampling of participants has a statistical connotation taken

from a larger population of case studies. Therefore, this study included purposive

selection.

Purposive selection is suitable for qualitative studies when the objective includes

using informants with the best knowledge to address the research question (Elo et al.,

2014). Williams et al. (2013) used purposive selection to identify professionals with

relevant skills and organizational responsibilities appropriate for addressing the research

question. Petty et al. (2012) indicated that purposive selection is effective for gaining a

deeper understanding of the phenomenon, and purposive selection is effective for seeking

out variations among participants. Parlalis (2011) used purposive selection because the

study required individuals with in-depth knowledge of practices relevant to the study.

Parlalis (2011) rationalized that purposive selection is necessary for identifying industry

professionals with the appropriate knowledge to aid in the investigation. Purposive

selection limits the generalizability of findings to a specific group of participants (Orser

et al., 2011). To address the overarching research question for this study, purposive

selection was the method for identifying VCs with the knowledge and the experience in

startup assessment strategies.

VCs with experience assessing startup firms are suitable for addressing research

questions that focus on initial startup investment opportunities (Bartkus et al., 2013).

Monika and Sharma (2015) mentioned that many studies on VC decision-making

techniques for assessing startups use interviews as a method of data collection. The

sampling universe for this study was the southeastern United States. The criteria for VC

firm selection were firms having either a successful IPO or a successful buyout within the

last five years. This study comprised of 11 participants from eight VC firms located in the

southeastern United States. The data collection started with interviewing at least 10

participants from at least five VC firms. Although data saturation occurred following 10

interviews, 11 participants were interviewed to ensure no new information became

apparent. This minimum quota sampling technique ensures inclusion of key participants

while providing flexibility for achieving data saturation (Robinson, 2014). Although at

least 10 interviews from at least five VC firms was an arbitrary starting point for this

exploratory study, Galvin (2015) indicated that 8 to 17 interviews are most common for

exploratory studies. Robinson (2014) mentioned that 3 to 16 interviews are common for

achieving data saturation in exploratory case studies. Moreover, Hanson et al. (2011)

indicated that a range of 10 to 20 participants could illuminate themes in qualitative

studies. Furthermore, Schenkel, Corhran, Carter-Thomas, Churchman, and Linton (2013)

selected 11 VC participants between the United States and China to explore perceptions

of necessary management skills that lead to successful exits. Also, Haeussler et al. (2014)

achieved data saturation using five interviews with VCs to complement a study on

understanding the influence of patents on the VC’s decision to invest in startups.

Therefore, using past scholarly studies of similar nature as a starting point, this study

began with the goal of interviewing at least 10 participants from at least five VC firms.

Following each interview, a rigorous evaluation of the data provided the means for

identifying the recurrence of existing themes and the emergence of new themes. After

interviewing 11 participants from eight VC firms, no new themes emerged following a

rigorous analysis of the data.

Data saturation occurs when there is no new discovery or revelation resulting

from analyzing the information collected from interviews (O’Reilly & Parker, 2012).

Furthermore, data saturation occurs when continuous analysis of the data provides no

new discovery or revelation (Mason, 2010). Also, Fusch and Ness (2015) supports the

notion that there is no one size fits all concept of data saturation, and many scholars have

different views on the interpretation of data saturation. Polit and Beck (2010) cautioned

against prematurely closing the study because of revelation or convenience rather than

the attainment of data saturation. In alignment with the perspective of Elo et al. (2014) in

recognizing data saturation, the analysis of the data around the time of data collection

enables easier recognition of data saturation. Therefore, as interviews with the

participants were completed then the timely analysis of the data collected during the

interviews improved the identification of common themes and the recognition of data

saturation. Also, Galvin (2015) indicated that an insufficient exploration of the research

question exists if there is at least one unique idea or theme from at least one participant in

comparison to all other participants. I assumed the attainment of data saturation when no

new themes, ideas, or revelations occurred after analyzing the data. No new themes,

ideas, or revelations occurred following data collection from 11 participants with eight

VC firms. Data saturation occurred with 10 participants, however, as a confirmatory

method of no new themes, ideas, or revelations, I interviewed 11 participants from eight

VC firms. O’Reilly and Parker (2012) supports the notion that data saturation is never

fully attained because life constantly changes. However, Galvin (2015) noted that many

qualitative studies use the exhaustion of themes from the participants as a strategy for

recognizing data saturation. Following 11 interviews, the manifestation of no new ideas

or themes was apparent. Therefore, data saturation for this study occurred with 11

participant interviews from eight VC firms.

For this study, VentureSource™ database was the instrument for identifying firms

that meet the VC firm selection criteria. Following the identification of suitable VC firms

as well as the attainment of the letter of cooperation from each firm’s representative, then

I proceeded with selecting participants to interview. Using Yin’s one-phase approach,

participants participated in an independent interview from VC firms. A criterion for

participation included each participant must possess experience assessing early-stage

startups. Yin (2014) described the one-phase approach as a screening procedure that

consists of querying people who are knowledgeable about the skills of the interview

candidate. Furthermore, Yin indicated that the one-phase approach is suitable for a small

number of cases. Stern and Chur-Hansen (2013) indicated that screening is important for

not only ensuring consent for study participation but also to ensure that the participant is

appropriate for addressing the research question. Furthermore, Befort et al. (2014)

showed that screening is useful for ensuring a minimum quota sampling for a qualitative

study. This study included leveraging Yin’s one-phase approach for screening and

selecting participants suitable for addressing the research question. This study included

11 participant face-to-face interviews.

Face-to-face interviews with participants were on-premise at each firm in an

environment free from noise and distraction. Williams et al. (2013) found that face-to-

face onsite interviews obtained richer contextual information through direct interaction

with the participants than telephone interviews. Dubocage and Galindo (2014) observed

that onsite semistructured interviews were effective for understanding critical reasons

VCs replace founder-CEOs. Erlingsson and Brysiewicz (2013) indicated that face-to-face

interviews are vehicles for data extrapolation from the participants of the study. Yin

(2014) mentioned that the salient value of the case study is in the interaction with

participants within the context of their environment. Conversely, Musteen (2016) found

phone interviews an effective method for data collection when participants are in

disparate locations. Shirazipour, Latimer-Cheung, and Arbour-Nicitopoulos (2015)

indicated that phone interviews enable researchers to accommodate participants'

schedules better. Furthermore, the mitigation of phone-interview limitations occurs with

the careful selection of participants with relevant knowledge of the subject (Hahn &

Gold, 2014). However, Yu, Abdullah, and Saat (2014) argued the importance of

responding to the unique context of the study and the research environment to provide a

complete investigation of the research question. The objective of this study was to

address the research question by engaging with participants concerning their experiences

assessing startups. Face-to-face interviews provide closer engagement with participants

than phone interviews. Therefore, face-to-face interviews were the technique for

collecting data to address the research question.

Interviews are useful to the researcher for obtaining information about the

participant’s feelings, thoughts, and experiences (Hanson et al., 2011). Information from

each participant flowed from open-ended questions using a semistructured interview

format. Therefore, the development of rapport between the participant and the

interviewer becomes important to encourage the free flow of information (Qu & Dumay,

2011). Furthermore, Williams et al. (2013) described the effectiveness of onsite

interviews for extrapolating contextual information from participants. However,

Shirazipour et al. (2015) also indicated that phone interviews could be an effective

technique for the free flow of information because participants might talk more freely due

to increased anonymity and privacy. For this study, all interviews were face-to-face

within the environment of the VC firm. A casual introduction is appropriate for building

trust, informing the participant about the purpose of the interview, and for building

rapport (Qu & Dumay, 2011). The strategy for establishing a working relationship with

the participant was to start each interview with a casual introduction, an explanation of

the purpose of the study, and an explanation concerning the importance of the study.

Selecting participants that meet the eligibility criteria ensures alignment with the

overarching research question (Paradkar, Knight, & Hansen, 2015).

Each participant provided feedback from onsite semistructured interviews in a

conversational manner. Semistructured interviews facilitate interview questions based on

a pre-established theme that elicit feedback from the participant (Qu & Dumay, 2011).

Semistructured interviews with open-ended questions provide formative inquiry into the

complex interaction between the participant and their environment (Suddaby, Bruton, &

Si, 2015). Singh, Corner, and Pavlovich (2015) used semistructured interviews with

open-ended questions to gain an in-depth understanding of venture failures. Therefore, an

onsite semistructured interview with each participant using open-ended questions

maximized an understanding of the complex decision-making strategies that VCs use to

identify profitable startups. Purposive selection and semistructured onsite interviews were

suitable for eliciting elaborate responses from participants for addressing the research

question. Interviews with each VC participant provide a rich source of information for

describing the participant’s interaction with their environment (Erlingsson & Brysiewicz,

2013). Purposive sampling was the tool for identifying eligible participants for this study.

Eleven participants with at least five years’ experience assessing startups participated in

face-to-face interviews. These interviews occurred using a semistructured interview

format with open-ended questions.

Ethical Research

Walden University’s Institutional Review Board (IRB) procedures were the

guidelines for this study. These IRB guidelines include the informed consent process that

conforms to all ethical and legal requirements of the University standards for ensuring the

protection of all participants (Atwater, Mumford, Schriesheim, & Yammarino, 2014).

The informed consent process included the requirement that all participants must sign a

consent form. The consent form includes full disclosure of the nature of the study,

purpose, participant rights, and the request for participation (Moustakas, 1994). Before

pursuing any interaction with participants, I obtained an approval number from the IRB

to proceed with the study. After receiving the IRB approval number 04-01-16-0376053, I

proceeded by sending the consent form and the request for participation form to VC firms

with participants eligible to participate in the study. Scheduling of an interview occurred

after I receive a signed copy of the completed consent form from the participant. The

consent form included the written authorization for audio recording the interview.

Interviewers should inform participants their rights to withdraw from the study

(Qu & Dumay, 2011). Once member checking was complete, participants had an

opportunity to withdraw from the study without penalty by notifying me via email.

Participants did not receive incentives for participating in this study.

Ethical research is the obligation of the researcher to behave in a manner that

emphasizes human rights, and the principles of protecting participants of the study from

exposure to any harm (Qu & Dumay, 2011). Hanson et al. (2011) indicated the

importance of qualitative researchers to be aware of any ethical concerns that might occur

as the researcher interacts with participants. Concerns include acknowledging bias,

building rapport, respecting individual’s privacy and confidentiality, and avoiding

exploitation (Hanson et al., 2011). Therefore, measures are necessary to remove any

personal identifiers linking the participant and the VC firm to the research and to ensure

the confidentiality of each participant throughout the research (Moustakas, 1994). Some

measures included avoiding disclosure of any data that could lead to identifying the

participants of the study and avoiding disclosure of trade secrets or knowingly falsifying

data. The research data remained securely in my possession to protect the confidentiality

of the participants. Furthermore, a professional transcription service transcribed the

audio-recorded interviews into text. Burton, Halpern-Felsher, Rehm, Rankin, and

Humphreys (2013) used a professional transcriptionist, under a confidentiality agreement,

to maintain the protection of participants for a qualitative study. The transcriptionist

service signed a confidentiality agreement (Appendix B) before transcribing the interview

recordings. The confidentiality agreement included additional measures to assure that the

ethical protection of the participants was adequate. Unique identifiers replaced

participants’ names and VC firms’ names as a strategy for masking identity. Gerdtz, et al.

(2013) ensured anonymity of participants by replacing participant names with unique

identifiers.

The confidentiality of each participant will persist for the life of the research and

follow the destruction of the research data after a 5-year period. Atwater et al. (2014)

described the importance for scholarly authors to follow the American Psychological

Association (APA) 5-year data retention policy to mitigate the risk of refraction. To

ensure the confidentiality of each participant, the collection of study data remains in my

possession within a fireproof lockbox throughout the 5-year lifecycle of the research.

Data Collection Instruments

Sànchez-Algarra and Anguera (2013) indicated that qualitative research method is

appropriate for describing human behavior in complex surroundings. Through the lens of

qualitative research method, the human instrument is a data collection tool that has an

advantage over nonhuman data collection tools (Lincoln & Guba, 1985). Human

instruments are useful in qualitative research because humans are highly adaptive to

changes in the environment that might lead to addressing the research question (Lincoln

& Guba, 1985). This adaptiveness enables the human instrument to be effective in

responding to unanticipated and complex responses from the interviewee during the data

collection phase of the research (Lincoln & Guba, 1985). Conversely, nonhuman data

collection tools found in quantitative studies has an inherent cause and effect relationship,

which are less suitable for complex studies with undefined variables (Muijs, 2011). Since

this qualitative study was an exploration of strategies that VCs use to identify profitable

startups, a data collection instrument that is flexible enough to accommodate

unanticipated and complex responses from the interviewee was appropriate. Regarding a

human instrument, I was the primary data collection instrument for this study.

Case study designs include participant interviews as a technique for data

collection. Da Mota Pedrosa, Näslund, and Jasmand (2011) found that many case studies

include some form of participant interview strategy. Dubocage and Galindo (2014) used

semistructured interviews in a case study design to facilitate a deeper understanding of

why VCs replace founder-CEOs. Schenkel et al. (2013) incorporated semistructured

interviews in a case study design to identify salient management characteristics that VCs

look for in entrepreneurs. Khanin and Mahto (2013) selected semistructured interviews to

identify biases of VCs towards continuing to invest in ventures. This research was a study

of VCs’ behaviors within complex environments as they implement strategies for

identifying profitable startups. Therefore, the semistructured interview was an

appropriate data collection technique for understanding VCs’ behaviors in complex

environments. A semistructured interview was the data collection instrument for this

study because the instrument aligns with other scholarly sources within a similar context

of inquiry. Semistructured interviews provide a means for making additional inquiries as

the interview unfolds for deeper exploration of the phenomenon under investigation

(Moustakas, 1994). Also, semistructured interviews provide a robust data collection

instrument for addressing the research question (Lincoln & Guba, 1985).

Open-ended questions in a semistructured interview format can provide a robust

structure for ensuring that participants answer interview questions relevant to the central

research question (Hanson et al., 2011). Furthermore, integrating open-ended questions in

a semistructured interview format within an interview protocol could amplify the findings

from the study (Windler, Jüttner, Michel, Maklan, & Macdonald, 2017). Therefore, the

data collection instrument for this case study was an interview protocol with open-ended

questions in a semistructured interview format.

De Ceunynck, Kusumastuti, Hannes, Janssens, and Wets (2013) described the

interview protocol as a technique for eliciting participant’s unique perspectives of the

phenomenon under investigation. Shapka, Domene, Khan, and Yang (2016) found the

effectiveness of using an interview protocol to extract more detail from participant

interviews than without an interview protocol. Also, an interview protocol is useful for

providing consistency in the interaction between the interviewer and participant

(Ramthum & Matkin, 2014). Therefore, an interview protocol was the method for

guiding the interviews in the exploration of strategies that VCs might use to invest in

startups. Using the interview protocol as the guide, the participants responded to seven

open-ended interview questions (see Appendix C). The interview protocol was the guide

to ensure all participant interviews occurred in a consistent manner.

Interviews with subject matter experts provided the process for capturing

participants’ perceptions of strategies that VCs use toward identifying profitable startups.

Twining et al. (2016) described that experience derives from one’s interaction with the

environment whereas knowledge deals with various aspects that experience describes.

Lincoln and Guba (1985) established that human instruments in an indeterminate

situation use interviews, archival documents, notes, member checking, and other cues as

a manner of addressing the research question. Capturing the full richness of data by

applying multiple and diverse methods can improve data collection from multiple

sources, and result in a richer understanding of humans in complex surroundings

(Twining et al., 2016). The illumination of concepts and themes from the data collection

instrument derive from the quality of textual data, experiences of participants, and the

interpretation of the data collected from the participants (Yin, 2014). A review of archival

documents provided augmentation and triangulation of data collected from interviews.

Reviewing archival documents is a method for augmenting the data collected

from participants, which results in adding precision to the information gathered during

participant interviews (Sutheewasinnon, Hoque, & Nyamori, 2016). Feldman and Lowe

(2015) added that reviewing archival documents could lead to a detailed and a contextual

understanding of the data, which could substantiate the researcher’s interpretation of

information gathered from participant interviews. Jennings et al. (2015) described sources

of archival documents include publicly available materials about the company or

industry, excerpts from books, and industry specific periodicals. For this study, types of

archival documents were VentureSource™ database, VC firm website, startup website,

and startup brochures. Following Feldman and Lowe (2015), I used the information

gathered from archival documents to substantiate the interpretation of findings during

each interview and to gain a contextual understanding of the data.

The data collection process included member checking as a technique for

enhancing the validity and reliability of the study data. Lincoln and Guba (1985)

indicated that member checking following the interview is appropriate for ensuring the

validity of the study. Petty et al. (2012) included member checking as a strategy for

objectivity and neutrality as well as establishing the validity of the study. Furthermore,

Erlingsson and Brysiewicz (2013) showed that member checking is useful for securing

the trustworthiness and the validity of the study data. The technique of member checking

includes post-interview verification of data collected for determining the accuracy of the

researcher’s interpretation of the data (Bromley, 2014). Member checking was part of the

interview protocol (see Appendix A). Member checking included sending an emailed

copy of a synopsis of my interpretation of the interview question responses to each

participant. After the participants had received an emailed copy of the synopsis, then they

made additional annotations, edits, elaborations, and any other feedback they felt was

appropriate. If the participant replied to the email with additional feedback, then another

synopsis of my interpretation that integrates the participant’s feedback was sent in an

email to the participant. This iterative process between the participant and the researcher

continued until the participant signified that the researcher had correctly interpreted the

responses to the interview questions. Once member checking was complete, then data

analysis continued until data saturation was met. Data saturation occurs when no new

information emerges after spending time immersed in the phenomena (Houghton et al.,

2013). I recognized data saturation when no new themes or ideas emerged from the

member-checked synopsis after constantly reviewing and then coding the themes and

ideas into Nvivo™.

Data Collection Technique

This study included multiple techniques of data collection to address the research

question. Using an interview protocol, techniques for data collection included audio-

recorded participant interviews, personal field notes, reflexive journal entries, reviewing

the VentureSource™ database, reviewing the VC firm’s website, reviewing the startup’s

website, and reviewing the startup’s brochures. Using a combination of multiple data

collection techniques assisted in capturing rich contextual information between the

participant and the researcher, which led to addressing the research question. Lincoln and

Guba (1985) described how multiple techniques of data collection might help establish an

audit trail that simultaneously improves the dependability and the confirmability of a

study. Erlingsson and Brysiewicz (2013) indicated that multiple techniques like

interviews and field notes are vehicles for extrapolating rich contextual data from

participants. Hanson et al. (2011) mentioned that various techniques including interviews,

field notes, and transcribed audio recordings are useful for exploring complex behaviors,

processes, relationships, settings, and systems. Therefore, using multiple data collection

techniques established a suitable framework for understanding how VCs interact within

complex environments to identify profitable startups.

The steps for the data collection technique included conducting semistructured

interviews with 11 VC participants from eight VC firms. Paradka et al. (2015) found that

interviewing multiple participants for each case was effective in gaining a richer

description of how access to multiple types of resources lead to startup success. Ramthun

and Matkin (2014) used semistructured interviews with subject matter experts to gain

unique perceptions and interpretations to understand the dynamics of leadership in

stressful situations. Yin (2014) indicated that participant interviews serve as a catalyst for

obtaining insights, views, perceptions, and meaning toward the case study topic. An

advantage of conducting participant interviews includes using targeted questions to solicit

participant feedback in a manner designed to address the research question (Singh et al.,

2015). A disadvantage of conducting participant interviews includes receiving inaccurate

participant feedback due to poor recollection (Yin, 2014).

Paradkar et al. (2015) found that interviewing multiple participants from a firm

was effective in gaining a multidimensional perspective on the success of an

organization. In an exploratory case study, Sjoerdsma and van Weele (2015) interviewed

multiple experts within a company to capture a broader scope of data from functional

areas to gain a holistic perspective of a phenomenon. Szajnfarber (2014) interviewed

multiple experts within an organization to understand complex factors that lead to

decisions of transitioning from exploitative innovations to explorative innovations. To

capture a broad scope of data, a maximum of two participants from each VC firm

participated in separate interviews. Interviews continued until data saturation occurred.

No new themes or ideas occurred after interviewing 10 participants. However, 11

participants were interviewed to confirm the discovery of no new themes or ideas in

compliance with the study design.

All interviews were onsite and face-to-face. Paradka et al. (2015) used onsite

interviews as a technique for capturing additional data through visual cues, expressions,

and non-verbal feedback throughout the interview process. Gerasymenko and Arthurs

(2014) used their physical presence at VC firms to capture additional data concerning

how VC’s time-to-exit strategies affect their decision-making tactics for startups.

Christner and Strömsten (2015) used face-to-face interviews to trace the link between

accounting practices and technology innovations for VC-backed companies. Furthermore,

an advantage of conducting onsite interviews included an opportunity to observe non-

verbal cues that might remain elusive in an offsite or remote setting (Paradkar et al.,

2015). However, a disadvantage of conducting onsite interviews is the presence of the

interviewer could trigger various cues to the participant, which might result in

interviewer bias (Nielsen, Kines, Pedersen, Andersen, & Andersen, 2015). For this study,

each participant interview was an onsite face-to-face interview.

An interview protocol (Appendix A), which contains open-ended questions, was

the instrument for conducting each interview. Darawsheh (2014) described an interview

protocol as a guide for directing and managing the interview process with each

participant. Brown et al. (2013) found that an interview protocol is effective for obtaining

accurate participant responses from a wide range of questions. Boardman and

Ponomariov (2014) demonstrated an interview protocol is effective for maintaining

consistency throughout each interview, while flexible enough to explore tangential ideas

based on participant’s responses to open-ended questions. An advantage of an interview

protocol includes systematically establishing a tempo for interviewing each participant

and ensuring each interview aligns with the goals of the research (Darawsheh, 2014). A

disadvantage of an interview protocol includes the risk of inflexibility to adjust for

unexpected responses as participants provide feedback that might deviate from the

interview protocol. The interview protocol included (a) a script for starting the interview,

(b) the list of interview questions, and (c) a closing script.

The interviews with the VC participants were audio recorded. Audio recording the

interviews is the technique for capturing verbatim the participant’s responses to the

interview questions (Jennings et al., 2015). A transcribed audio recording of the interview

between the researcher and the participant is an effective technique for accurately

capturing raw data (Lincoln & Guba, 1985). Audio-recorded interviews create high

fidelity in the sense that the researcher can reproduce the data in an exact form for later

inspection (Lincoln & Guba, 1985). Transcribing audio recordings is a process of

converting audio information into text for textual analysis (Yin, 2014). An audio-

recorded interview is an effective auditing tool to ensure the researcher captures exactly

what the participant meant to articulate (Lincoln & Guba, 1985). A disadvantage of

audio-recorded interviews is that some participants are reluctant to be recorded with an

audio device (Lincoln & Guba, 1985). Another disadvantage of audio-recorded

interviews is problems with the recording device could interfere with the interview

(Lincoln & Guba, 1985). However, a transcribed audio recording of the interview is an

effective technique for capturing data from each participant without the risk of losing

salient points from the participant (Lincoln & Guba, 1985). An audio recording of each

interview occurred by using the audio-recording feature of a tablet computer and freely

available audio-recording software called Audacity™.

Following the completion of the interviews, a professional transcription firm

transcribed the audio recordings into an electronically formatted text file. Gordon (2014)

showed that transcribing audio data into electronically formatted text was an effective

technique for analyzing information captured during semistructured interviews with

open-ended questions. The transcriptionist from the transcription firm signed a

confidentiality agreement before starting the transcription work (see Appendix B).

Dubocage and Galindo (2014) used transcribed interviews to understand why VCs

replace founder-CEOs. Gordon (2014) used transcribed interviews to extrapolate critical

themes of successful entrepreneurs engaging in venture philanthropy activities. An

advantage of transcribing interviews includes converting audio data into textual data for

detailed analysis (Yin, 2014). A disadvantage of transcribed interviews is the participant

may become uncomfortable during member checking (Lincoln & Guba, 1985). After the

each transcription was complete, I reread the transcripts and listened to the audio

recordings to ensure the accuracy of the transcription service. A method for member

checking included sending each participant a synopsis of my interpretation of the

interview questions for review. Participants had an opportunity to provide edits and

comments on the synopsis to ensure accurate interpretation of responses to interview

questions. After each participant had an opportunity to review the synopsis and provide

any feedback, then an analysis of the data and the participant’s feedback continued by

combining information from other data collection instruments, which included field

notes.

Field notes are a data collection technique for the researcher to record his

thoughts and insights as part of the verbal and nonverbal interaction with the participant

(Lincoln & Guba, 1985). Field notes help the researcher stay engaged and responsive

during the data collection process (Lincoln & Guba, 1985). Furthermore, field notes are

useful for refreshing the memory of the researcher and the participant (Lincoln & Guba,

1985). Bocken (2015) showed that field notes are useful for corroborating and

augmenting data collected from other sources. The field notes captured during the

interviews included a unique identifier to ensure that the notes aligned with the correct

participant. I maintained possession of all field notes to ensure the confidentiality of the

participant and the VC firm. The field notes included visual observations and important

points during each participant’s response to each interview question. An advantage of

using field notes includes documenting salient points, ideas, and themes that emerge

during the interview (Jennings et al., 2015). Lincoln and Guba (1985) described a

disadvantage of field notes is the difficulty of recollection for the researcher if the

handwriting is illegible. Lincoln and Guba discussed another disadvantage of field notes

is the influence on the participant to slow the tempo if the researcher is busy or distracted

while taking notes (Lincoln & Guba, 1985). If the participant slows the tempo, then there

is a risk that the participant could lose the train of thought (Lincoln & Guba, 1985).

However, field notes are useful because notes enable the researcher to highlight

important points for later recall (Lincoln & Guba, 1985). Therefore, while listening to the

participant’s responses and observing visual or verbal cues during the interviews, creating

researcher field notes created an opportunity for additional data collection.

In addition to field notes, a review of archival documents was another technique

for data collection and data triangulation. Feldman and Lowe (2015) described the

collection of archival documents from sources including company websites, public

sources, and quasi-public sources. Jennings et al. (2015) used different sources of

archival documents that include book excerpts, media, and industry specific periodicals

to augment and triangulate data collected from interviews. Sutheewasinnon et al. (2016)

leveraged interviews and archival documents to triangulate interviewee comments with

archival evidence from the company for adding precision to a study of governmental

policy change. Company brochures are another form of archival documents (Sepulveda &

Gabrielsson, 2013). Sepulveda and Gabrielsson used a brochure from the study firm as an

additional data collection source and data triangulation for understanding how successful

firms with global networks grow in complex environments. Yin (2014) indicated that

sources of evidence for case studies could derive from multiple sources including

company brochures. Company brochures provided an additional source of information

useful for complementing and triangulating other archival documents. Therefore, an

advantage of using an array of archival documents includes providing additional evidence

that might support or refute the data collected from the interviews (Jennings et al., 2015).

Denzin (2009) asserted that archival documents are an applicable data collection

technique for methodological triangulation and enhancing the validity of a study. A

disadvantage of historical archival documents is a point in time record that may no longer

represent the current environment the participant operates (Feldman & Lowe, 2015). For

this study, archival documents included source data from (a) VC websites, (b) investee

company website, (c) search engine results about the VC firm, (d) company brochure,

and (e) journal articles about VCs. Also, before leaving the VC firm, I requested any

brochures the participant felt comfortable sharing. The brochures included information

for gaining an additional perspective on the types of services that members of the VC

firm provide to startups.

Reflexive journal entries were useful for preparing for participant interviews.

Lincoln and Guba (1985) indicated that reflexive journal entries are appropriate for (a)

maintaining a daily schedule and documenting logistics of the study, (b) maintaining a

personal diary for evaluating self throughout the research process, and (c) writing down

the rationale for making methodological decisions. Furthermore, Lincoln and Guba

(1985) mentioned that reflexive journal entries are appropriate for establishing

credibility, transferability, dependability, and confirmability within a study. Petty et al.

(2012) showed that reflexive journal entries are a strategy for protecting against

researcher bias and for increasing the reliability and validity of the study. Houghton,

Casey, Shaw, and Murphy (2013) described an advantage of reflexive journals includes

establishing the basis for research transparency while considering the researcher’s

history, experience, interests, and biases. Houghton et al. (2013) inferred a disadvantage

of reflexive journaling is the requirement for researchers to be objectively aware of their

thoughts and feelings to record accurate journal entries. Before arriving at each VC firm,

a review of the firm’s website provided insight into the business model and the services

offered to startups. During the VC website review, creating reflexive journal entries

concerning any perceptions, opinions, and potential biases that could distort an objective

view of the firm or the participants supported research transparency. For the study, I used

reflexive journal entries while reviewing brochures, field notes, and archival documents

that pertain to the VC firm and startup.

Member checking was useful for establishing accuracy in data interpretation of

the participant’s responses to the research questions. Lincoln and Guba (1985) indicated

that member checking enables participants an opportunity to confirm that the researcher

accurately captures and interprets the interview responses from the participant. Member

checking is critical for establishing credibility (Lincoln & Guba, 1985). Erlingsson and

Brysiewicz (2013) indicated that member checking is useful for confirming the

authenticity of the information captured from the participant. Each participant received an

emailed packet containing a synopsis of the researcher’s interpretation of the interview

responses. The email included directions requesting each participant to review the

synopsis. Each participant replied to the email with any edits, clarifications, or

elaborations the participant feels was appropriate for ensuring an accurate interpretation

of the responses. The iterative process of clarifying the interpretation of the interview

responses between the participant and researcher continued until the participant signified

a correct interpretation of interview question responses. The participant feedback

provided a technique for member checking, which led to ensuring an accurate

interpretation of the data collected from the participants.

Data Organization Technique

Collecting data for case study research results in an accumulation of many

documents relevant to the study that requires a large amount of storage space (Yin, 2014).

Denzin (2009) described how individual cases become significant following the

organization and the classification of data in a manner that reveal patterns and themes.

Therefore, a documentation indexing strategy is appropriate for organizing documents for

later inspection, perusal, transparency, or cross-referencing with other materials relevant

to the study (O’Reilly & Parker, 2012). A database solution is effective for indexing,

organizing, and managing data and other materials relevant to the study including field

notes, transcripts, archival documents, and reflexive journal entries (Feldman & Lowe,

2015). Lincoln and Guba (1985) discussed that a data management system is appropriate

for creating an audit trail to increase the confirmability and dependability of the study.

Moustakes (1994) mentioned that the organization of study data should be systematic

based on textual descriptions and themes. Therefore, a case study database was the

instrument for organizing and tracking data throughout the research process.

For this case study research, I used an indexing strategy to link the data

classification, file type, and evidence to a searchable and orderly key. This indexing

strategy for managing the data classification, file type, and evidence is called the case

study database system (Yin, 2014). The case study database system included a

combination of NVivo™, Excel spreadsheet, an organization of files within an electronic

medium, and organization of files based on naming convention. Lincoln and Guba (1985)

described a research database system includes an indexing strategy that contains an

organization method based on data classification, file type, and evidence. Also, Yin

(2014) indicated that the case study database should be an orderly compilation of data

from the study. Furthermore, Edwards (2017) noted that a case study database system

supports thematic content analysis and increases the study’s reliability. The evidence, in

the form of raw data, included the audio file from each interview, transcription of the

audio file, field notes, reflexive journal entries, and archival documentation.

An external hard drive was the storage device for the collection of data during the

study, and NVivo™ was the tool for coding and analyzing the data. NVivo™ is useful for

evidence management, coding, and theme extrapolation and analysis (Erlingsson &

Brysiewicz, 2013). Houghton et al. (2013) showed that a combination of a file storage

strategy and NVivo™ are effective in identifying patterns and themes and for ensuring a

rigorous case study research. Meyskens and Carsrud (2013) found that NVivo™ was

effective for analyzing, coding, and tracking variables in the data. Orser et al. (2011) used

NVivo™ to import and analyze participant interviews for thematic analysis. Using codes

to illuminate patterns and themes required a method for identifying and tracking data.

The arrangement and organization of raw evidence in this research included

uniquely identifying data associated with each case using a folder-subfolder labeling

strategy. Ramthun and Matkin (2014) used a numeric-based labeling strategy for unique

identification and data tracking in a case study that explains dynamics of leadership

during dangerous situations. Maine et al. (2015) leveraged a prefix and letter labeling

strategy to track participant data in a case study about decision-making modes of founder

entrepreneurs. Paradkar et al. (2015) numerically labeled each case and the role of the

participant as a strategy for identifying and tracking research data. For this study, the

organization of each parent folder label was correlated to each participating VC firm as

VC1, VC2, VC3, VC4, VC5, VC6, VC7, and VC8 respectively. Within each parent

folder, there were two subfolders called I1 and I2. The I1 and I2 subfolders included

evidence about each interview within the VC firm. Included in each parent folder was a

copy of archival documents, field notes, and reflexive journal entries. The pattern of the

naming convention for each file was file name-name_data-

classification_MMDDYYYY.txt. A spreadsheet located in the root directory of the external

hard-drive included the index of all files contained within each parent folder and the

corresponding subfolders. The spreadsheet was useful for cataloging and labeling

evidence in the case study database. Each file from the folders and subfolders was

imported into NVivo™ for coding and analysis. All evidence from the study will remain

on an external hard-drive, and the external hard-drive will remain in a locked container

for 5 years.

Data Analysis

This case study included methodological triangulation as the technique for data

analysis. Methodological triangulation involves using multiple methods to gather data

(Denzin, 2009). Methodological triangulation is useful for ensuring a reliable and a valid

study (Tsolou & Margaritis, 2013; Tuncel & Bahtiyar, 2015). Ruiz-Lòpez et al. (2015)

indicated that establishing methodological triangulation is appropriate during the research

design phase of the study to develop data collection strategies suitable for the goals of the

research. Koc and Boz (2014) described triangulation as a strategy for providing stronger

evidence to draw better conclusions in the research. Therefore, multiple data collection

techniques provided a framework that led to addressing the reliability and the validity of

the case study.

Methodological triangulation was a suitable technique for interrogating data in

complex environments. Denzin (2009) indicated that methodological triangulation is

appropriate for a broad range of tasks including participant interviews and self-reflection.

Tuan (2012) used methodological triangulation by employing multiple methods of data

capture through interviews, site visits, and analysis of documents for augmenting the

study of high-performance hospitals operating in complex environments. Feldman and

Lowe (2015) used methodological triangulation by combining interviews and archival

documents to map temporal dynamics of documents to study the effect of entrepreneurial

success over time within a localized region. This research study included methodological

triangulation to explore strategies that VCs might use to identify profitable startups.

The process for data analysis included a rigorous review of data collected from

participant interviews from each VC firm. Denzin (2009) mentioned that a strategy for

methodological triangulation includes triangulating information between participants

within the same environment. Christner and Strömsten (2015) interviewed multiple

participants within the same environment to understand the role of accounting on

decision-making strategies that effect scientists’ and VCs’ ability to innovate. Paradkar,

et al. (2015) included a strategy for analyzing data from multiple participants from startup

firms to explore how different types of resources influence the success of early-stage

startups. The process of analyzing the data included the analysis of data from participants

from each VC firm using NVivo™ to identify themes.

I used NVivo™ for coding and theme extrapolation of the evidence collected

during the research. NVivo™ is useful for analyzing data from interviews (Orser et al.,

2011). NVivo™ is also appropriate for the content analysis of data and useful for coding

and tracking themes (Meyskens & Carsrud, 2013). Gordon (2014) suggested that

NVivo™ might provide the support for the coding and the theme extrapolation process

that will integrate within the conceptual framework. Therefore, the process for using

NVivo™ for theme extrapolation included importing the data from each interview into

NVivo™. Data entered into NVivo™ provide a method for remaining close to the data

(Parlalis, 2011). NVivo™ includes features for querying the data and extrapolating

themes from narrative-based data (Orser et al., 2011). Furthermore, NVivo™ supports a

method for uploading raw data from transcribed interviews for coding and cross-

referencing to facilitate organizing the data in an easily retrievable format (Erlingsson &

Brysiewicz, 2012). After importing the participant data into NVivo™, an analysis of the

data included identifying common words, ideas, and phrases. Methodological

triangulation was incorporated into the data analysis by importing field notes, reflexive

journal entries, and archival documents into NVivo™. The archival documents included

information from the VC website, investee company website, information from

VentureSource™, and brochures collected from the participants. Following the

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importation of field notes, journal entries, and archival documents, an analysis of the

documents continued with the identification of common words, themes, and phrases.

The conceptual plan included a bottom-up approach starting with the analysis of

participants from each VC firm using NVivo™ for identifying themes. Smith and

Cordina (2014) used a bottom-up approach for conducting data analysis when exploring

the effectiveness of accounting practices in high-tech VC investments. Pardkar et al.

(2015) described a bottom-up data analysis approach when they identified themes among

multiple startups within a case study. Huang and Wilkinson (2013) incorporated a

bottom-up approach to explore the dynamics and evolution of trust in business relations

within a complex environment. Therefore, after analyzing the data from participants

within the each VC firm, another level of analyzing the data occurred between the

populations of participants across all participating VC firms. The intent of analyzing data

across all participants was to identify common themes that might emerge across the entire

population of VC firms.

Coding Process

Using NVivo™, an open coding method was used to identify key themes during

data analysis. The open coding method is useful for analyzing qualitative data and for

identifying emergent themes based on frequencies of occurrence from the interview

(Soykan, Gunduz, & Tezer, 2015). In a qualitative study, Ozcan and Kotek (2015) used

an open coding method to integrate similar ideas into major themes. Furthermore,

Witkamp, Droger, Janssens, Van Zuylen, and Van Der Heide (2016) used an open coding

method to code data across all interview questions from multiple interview participants.

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In this qualitative study, the open coding method was appropriate for coding the feedback

from VC participants to identify major themes.

Erlingsson and Brysiewicz (2013) indicated that NVivo™ could aid in compiling

data captured as part of the study design and provide easy access to important

information. Meyskens and Carsrud (2013) used NVivo™ to perform content analysis,

coding, and tracking of variables in a study of understanding the complex and diverse

influences of nascent green technology ventures. Orser et al. (2011) used NVivo™ to

analyze transcribed audio-recorded interviews in a case study to gain a deeper

understanding of feminist entrepreneurs operating in complex environments. Therefore,

using NVivo™, common words, ideas, and phrases were identified with the same code.

Also, a color-coding scheme highlighted red (important), green (possibly important), and

blue (not important) to facilitate a hierarchal structure. Themes that were identified in the

study and reflected in the literature had a unique code. STRAT was the code for strategies

for identifying profitable startups. BVI was the code for successful buyouts versus

successful IPO. INFL was the code for salient influences of VC success. TECHQ was the

code for techniques for driving successful exits. RSUC was the code for recurrence of

VC success. Since the nature of this study was exploratory, then new codes emerged

during the coding while looking for relationships among data categories. Following the

completion of the coding process across the entire population of participants, themes

emerged through the rigorous data interrogation process.

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Themes

The open coding method was used to identify and correlate key themes with

archival documents, field notes, and reflexive journal entries. In a case study, Yildirim

and Dinçer (2016) used an open coding method with NVivo™ to identify themes in

addressing the complex debate between corporate social responsibility and strategic

corporate intent. Erlingsson and Brysiewicz (2013) mentioned that one role of the

researcher is to immerse himself in the data and to code sections of the text in a way that

results in categories and themes. Researchers should remain open and flexible throughout

the data analysis and coding process to discover themes from the study that might

otherwise remain elusive (Hanson et al., 2011). Maine et al. (2015) used a coding process

to identify key themes related to entrepreneurial decision-making strategies during

opportunity recognition. Jennings et al. (2015) incorporated a coding process to identify

key themes relating to the influence of emotions on entrepreneurial outcomes. This study

pertained to decision-making patterns of VCs in the southeastern United States.

Therefore, a continuous review and importation of archival documents from recent

scholarly sources on VC behaviors into NVivo™ provided additional insight into the

decision-making strategies of VCs. After importing new scholarly sources into NVivo™,

key themes from scholarly sources were correlated to key themes that emerge during the

data analysis and coding process. Salient themes emerged that show critical strategies

that VCs need for investing in startups in the southeastern United States. Similar to

Bocken (2015), themes also emerged from the study that include (a) entrepreneurial

business model innovation, (b) collaboration between startup and VC, and (c) a strong

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business case. An identification of key themes linked into the conceptual framework of

the study.

Framework

The conceptual framework of this study was ROT. ROT is an entitlement that

indicates the right, but not the obligation to invest or to continue investing in a project

(Zeng & Zhang, 2011). This entitlement could provide the flexibility for VCs to identify

profitable startups. Vilkkumaa et al. (2015) based a mathematical model using a ROT

framework to map an optimal funding decision-making strategy to identify successful

products. Haeussler et al. (2014) used a ROT framework to explore VC assessment

strategies of entrepreneurs. Mun (2006) indicated that ROT is useful for VCs to identify

successful investee companies. Using ROT as the conceptual framework provides a

method for risk management and uncertainty management in changing conditions that are

facilitated through lifelong learning and experiences of VCs (Kremljak & Tekavcic,

2014). These lifelong learning and experiences from assessing investee companies

influence the decision-making strategies of VCs (Kremljak & Tekavcic, 2014). Linking

themes into the ROT conceptual framework illuminated how VCs might decide to either

abandon a startup after the initial investment or continue investing into the startup. The

results of the study could provide VCs in the southeastern United States with key

strategies necessary for identifying and investing in startups that might lead to higher

probability of success. This higher probability of success is regarding a VC ROI and a

sustainable startup that results in an IPO or a buyout.

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Reliability and Validity

Reliability

Reliability is a precondition for research validity because a study has to be

reliable to be valid (Lincoln & Guba, 1985). A study is reliable when the conclusions

drawn from the study include quality attributes of consistency, dependability, and

predictability (Lincoln & Guba, 1985). These quality attributes are necessary for building

a framework of research rigor that leads to the trustworthiness of the study (Petty et al.,

2012). Furthermore, a study is trustworthy when the reader has confidence in the research

findings (Petty et al., 2012). Lincoln and Guba (1985) described the criteria for

establishing the trustworthiness of the study as dependability, creditability,

transferability, and confirmability. Reliability derives from the rigorous processes

designed to test the merits of the qualitative research (Erlingsson & Brysiewicz, 2012).

Creating a reliable study includes a focus on building a trustworthy study (Lincoln &

Guba, 1985). This section includes the steps taken to increase the reliability and the

validity of the research by building a trustworthy study. These steps include a pragmatic

approach to addressing the four criteria of trustworthiness. This section concludes with

the description of the steps taken to outline how data saturation occurred.

Dependability. Moon et al. (2013) described dependability as the extent to which

the reader can ascertain the consistency between the interpretations of the findings and

the data collected for the study. The responsibility is on the researcher to provide enough

detail in the study so readers can determine the extent that the interpretations of the

findings are consistent with the data collected (Moon et al., 2013). Strategies for

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achieving dependability include creating an audit trail of processes and procedures, and

the implementation of triangulation techniques (Petty et al., 2012). Houghton et al. (2013)

increased dependability using NVivo™ for managing data and for creating an audit trail

throughout the research process. Another strategy for ensuring the dependability of the

study is through member checking (Jennings et al., 2015). Yin (2014) indicated that a

strategy for increasing the reliability of the study includes using a case study protocol that

comprises of processes and procedures for executing the study. A case study protocol,

which comprises of an interview protocol, increased the reliability and the dependability

of the study. The case study protocol included guidelines for creating an audit trail of

processes and procedures. Following Yin (2014), the case study protocol included (a) the

overview of the case study, (b) the data collection procedures, (c) the interview protocol,

and (d) the guide for the case study report. Furthermore, the incorporation of member

checking addressed the dependability of this study. Harvey (2015) indicated that member

checking is important for ensuring participants verify the accuracy of data interpretation.

Houghton et al. (2013) mentioned that member checking should occur after transcription

and before data analysis. Jennings et al. (2015) found that member checking was

effective for supporting an explanation for their research model. For this study, member

checking included emailing the participants a synopsis of the interview question

responses. Each participant had an opportunity to reply to the email with any edits,

expansions, omissions, elaborations, or agreements with the interpretation of the

information before data analysis. The combination of the participant’s feedback, field

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notes, and reflexive journal entries were instruments for guiding the interpretation of the

data.

Validity

Establishing the validity of research is necessary for determining the

trustworthiness of a study (Lincoln & Guba, 1985). For a study to be valid, Ebrashi

(2013) indicated that data collected from various research sources should derive from the

same perspective of the overall study. Erlingsson and Brysiewicz (2013) elaborated on

validity by indicating that qualitative studies must have consistent data collection

methods administered to participants to be valid and establish trustworthiness. This

section includes the steps taken to increase the validity of the research to establish a

trustworthy study. This section includes the approach used to ensure the creditability,

transferability, confirmability, and data saturation of the research.

Credibility. Moon et al. (2013) described credibility as the extent to which the

findings of the study are trustworthy and believable by the participants. Lincoln and Guba

(1985) indicated two criteria for a credible study include executing the research in a

manner that produces credible results and having confirmation of results by individuals

who provide input to the study. Petty et al. (2012) listed some strategies for achieving the

credibility of a study that include member checking and triangulation. The execution of

member checking includes engaging closely with the participants during the interview to

ensure the interpretation of their responses accurately reflects the participant’s intended

meaning (Moon et al., 2013). The same technique of member checking described in the

dependability section also increased the credibility of the study. Also, reviewing the

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transcripts from the transcription service while listening to the audio recording to ensure

the transcriptionist accurately transcribed the recording was a method for addressing the

credibility of the study. Adams, Bailey, Anderson, and Thygeson (2013) ensured the

accuracy of a qualitative study by enabling a researcher to verify the transcripts with the

audio-recorded interview. Dionne-Odom, Willis, Bakitas, Crandall, and Grace (2015)

independently verified the accuracy of a professional transcriptionist before importing

text into a data analysis package to ensure the credibility of their study. Turner,

Brownstein, Cole, Karasz, and Kirchhoff (2015) demonstrated the effectiveness of

verifying transcribed interviews before thematic analysis to increase the credibility of the

study.

Denzin (2009) mentioned that a study is credible when the triangulation of

independent sources of evidence corroborates the assertions of the study. Yin (2013)

indicated that triangulation strengthens the validity and credibility of case studies. Tuan

(2012) indicated that methodological triangulation includes using several methods to

triangulate the data. These methods of capturing data include interviews and archival

documents (Tuan, 2012). Importing data from interviews, archival documents, field

notes, and reflexive journal entries into NVivo™ and analyzing the data using multiple

methods was a technique of methodological triangulation. This methodological

triangulation technique was appropriate for addressing the credibility of the study.

Following the importation of the data into NVivo™, I conducted a thematic analysis of

the data to identify themes that were appropriate for addressing the research question.

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Transferability. Tsang (2014) indicated that the ontological and epistemological

perspective of the researcher influences the generalization and transferability of a study.

Moon et al. (2013) described transferability in terms of the extent that the findings from

the research are useful in similar contextual situations. Transferability is contingent on

credibility (Petty et al., 2012). Lincoln and Guba (1985) mentioned that transferability is

the responsibility of the reader to decide whether the results of the study fit into a given

context. Lincoln and Guba also mentioned the responsibility of the researcher to ensure

that a rich description of the data provides sufficient information to the reader for making

a proper assessment concerning the transferability of the results. Moon et al. (2013)

agreed with Lincoln and Guba when they indicated that the researcher should provide

sufficient information so that the reader might determine if the interpretations of the

findings are consistent with the data. Petty et al. (2012) suggested strategies for meeting

transferability includes purposive selection, reflexive journal entries, and thick

descriptions. Lincoln and Guba (1985) said that the researcher should maintain a database

so that judgments concerning transferability are available. Yin (2014) agreed with

Lincoln and Guba by highlighting that a case study database is suitable for organizing

data to support the reliability and the validity of the study, which aligns with the

transferability of the study. Purposive selection, as described in the Population and

Sampling section of this dissertation, provided a method for addressing the transferability

of this study. Furthermore, this study included a rich description of themes that emerged

during the data analysis process in a manner that supports the transferability of the study.

Also, a participant labeling strategy that abstracts away any participant identifiers in a

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manner that does not jeopardize any ethical boundaries of the participants supported the

transferability of the study. Finally, highlighting the limitations and boundaries of this

study provided direction for possible applications of the study findings for VCs,

investors, and entrepreneurs as well as provided possible avenues for future studies.

Confirmability. Moon et al. (2013) described confirmability as the extent to

which the results of the study are neutral and free from researcher bias. Lincoln and Guba

(1985) indicated that researchers could achieve confirmability through auditing,

triangulation, and reflexive journal entries. Petty et al. (2012) listed strategies of

confirmability that include an audit trail, triangulation, member checking, and reflexive

journal entries. Creating an audit trail includes defining a systematic procedure for

mapping the course of the research (Erlingsson & Brysiewicz, 2013). Houghton et al.

(2013) showed that audit trails and reflexivity are strategies for confirmability. Moon et

al. (2013) described how the process of reflexivity could ensure the researcher disclose

any potential biases that could influence the confirmability of the study. Using techniques

of an audit trail, triangulation, member checking, and reflexive journal entries addressed

the confirmability of the study. The case study protocol was included to establish the

standard for an audit trail of activities for the study. In addition, methodological

triangulation for triangulating data from other sources established a technique for

supporting or refuting any themes that led to addressing the research question. Exercising

member checking with each participant after the interview supported study

confirmability. I used reflexive journal entries to ensure an objective and neutral

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perspective by disclosing any potential biases throughout the research process and by

documenting the rationale for making decisions concerning the research.

Data Saturation. O’Reilly and Parker (2012) described the debate within the

scholarly community concerning the evolving definition of data saturation. However,

Houghton et al. (2013) said data saturation is evident when no new information emerges

after spending sufficient time immersed in the phenomena. Lincoln and Guba (1985)

mentioned that in qualitative research, the researcher should sample data continually until

information redundancy occurs. Elo et al. (2014) indicated that data saturation becomes

easier to recognize when data collection and data analysis occur at the same time. Massy

et al. (2014) described a pragmatic inductive approach for achieving data saturation.

Following Massey et al., this study leveraged an inductive approach involving two levels

of data evaluation to achieve data saturation. The study design included the solicitation of

at least 10 participants from at least five VC firms to participate in interviews. However,

11 participants from eight VC firms participated in interviews for this study. Following

member checking, NVivo™ was the tool for importing and analyzing data from the

interviews, field notes, reflexive journal entries, and archival documents. NVivo™ was

appropriate for coding and identifying new themes, and emerging themes based on

interviews. Also, NVivo™ was helpful for triangulating themes from the interviews to

field notes, archival documents, and reflexive journal entries. If at least one new idea

existed in at least one participant, then data saturation had not occurred for this study.

After 11 participant interviews, no further solicitation of additional participants from a

new VC firm was necessary. No new ideas or themes emerged from the population of

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interviewees. For this study, the convergence of ideas and themes existed when at least

one participant did not have a unique idea or theme when compared to all other

participants. Therefore, identifying repetitive themes from successive participants

warranted the conclusion of interview activity. The second stage of this inductive

approach was the continuous reinterpretation of themes with broad and descriptive names

for capturing salient ideas from each participant. A repetitive analysis of the data with the

preliminary themes continued until each theme converged into a single concept. Concepts

identified in this study formed the basis for addressing the research question concerning

strategies that VCs might use to identify successful startups.

Transition and Summary

Section 2 included the review of the research method and the study design as well

as the rationale for selecting the qualitative method with a case study design over

alternative methods. Data collection techniques and data organization techniques

included using open-ended questions with a semistructured interview format and

NVivo™ as part of the methods of collecting and organizing data within the study. The

information in Section 2 disclosed detail identifying the primary data collection

instrument and the role of the researcher. Furthermore, Section 2 included decisions

highlighting the participant selection process and the population sample size. Using

purposive selection techniques, these highlights included 11 participants from eight VC

firms participated in the study. Section 2 included information that described the plan for

ensuring the study maintains high standards of ethics and ensuring the participants are

safe and assurances of participant confidentiality. Section 2 also showed measures for

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ensuring reliability and validity through rigorous analysis of the data, triangulation,

member checking, and a method for ensuring data saturation, auditing, and using an

interview protocol. The goal of these previously mentioned points was to produce a

research study that is acceptable in the academic community.

Section 3 includes a report on the findings and the results of the study. Section 3

also includes the presentation of the findings that reflect on salient themes from the data

analysis and other materials from the study. Following the identification of themes,

Section 3 shows information about the application of the results of professional practice,

implications for social change, recommendations for action, recommendations for further

research, and reflection. At the conclusion of Section 3, the intent is to provide VCs,

entrepreneurs, and investors with a clear understanding of strategies that VCs might use

to identify profitable startups.

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Section 3: Application to Professional Practice and Implications for Change

Introduction

The purpose of this qualitative multicase study was to explore strategies that VCs

use in determining which businesses would become profitable when investing in startups.

Using purposive selection, 11 VC participants from eight firms located in the

southeastern United States participated in semistructured interviews to share their

entrepreneur selection experiences. The findings of the study were a result of analyzing

and triangulating interviews and archival documents. The analysis of archival documents

included the VentureSource database, VC firm website, startup website, and VC firm

brochures. I used field notes and reflexive journal entries to ensure researcher bias did not

interfere with the findings of the research.

The findings of the study centered on eight themes. The first theme is due

diligence and investor involvement. The second theme is reduction of information

asymmetry. The third theme is human capital management. The fourth theme is

environmental and market forces. The fifth theme is startup experience matching investor

strategy. The sixth theme is building trust. The seventh theme is investment timing. The

last theme is VC market dynamics.

Presentation of the Findings

This study had one overarching research question: What strategies do VCs use to

determine which startup businesses would become profitable when investing in startups?

Investment motives for VCs center on their exit strategy (Ozmel et al., 2013). The

findings of this study are a result of interview responses from 11 participants within eight

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VC firms in the southeastern United States. Although data saturation occurred after

interviewing 10 participants, 11 participants were interviewed to ensure no new data

became apparent. In this study, nine participants participated in the assessment of startups

that led to a success VC exit through a buyout. Two participants participated in the

assessment of startups that led to a success VC exit through an IPO. Table 2 shows the

distribution of participant interviews to VC firm. This study included a maximum of two

VC participants interviews per VC firm. The first participant interviewee and the second

interviewee from each firm are denoted by Interview A and Interview B, respectively. In

cases of one participant interview from a VC firm, Table 1 shows the column for

Interview A populated with the relevant interview participant number. As denoted in

Table 1, three VC firms included two participant interviews, and five VC firms included

one participant interview. There was no difference in triangulating data from firms with

two participant interviews and firms that included one participant interview. Data

triangulated across all participant interviews, which led to consistent themes among the

population of participants.

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Table 2

Distribution of Participants to Venture Capital Firm

VC firm Interview A Interview B

VC1 I1 I2

VC2 I3 I4

VC3 I5

VC4 I6

VC5 I7

VC6 I8

VC7 I9 I10

VC8 I11

Note. VC, venture capital.

Each participant interview included seven interview questions. The member-

checked summary of the responses to the interview questions was coded in NVivo™

using an open coding method. Witkamp et al. (2016) described the effectiveness an open

coding method for theme extrapolation when multiple participants respond to interview

questions. Furthermore, Soykan et al. (2015) mentioned the open coding method uses

frequencies of occurrence from interview question responses to aid in illuminating

themes.

Archival documents include the VentureSource database, VC firm website,

startup website, and VC brochures were triangulated with responses to the interview

questions. Before visiting each firm, I reviewed the VC firm’s website and noted

products and services offered by the VC firm. I also reviewed the VC firm “About Us”

page and noted important points about the leadership team, partners, and customers. Also,

I reviewed the “About Us” page on the startups’ websites and noted important points

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about the leadership team and investors. I imported my notes from the VC firm website

and startup website into NVivo™. The VC firms that were able to provide a brochure, I

reviewed the brochure and noted important points about the VC firm’s products and

services. My notes from the VC firm’s brochure were imported into NVivo™ for further

analysis and triangulation with participant interviews.

The findings from this study related to the conceptual framework of real options

theory. Assessment strategies expressed by participants was options for continued

investment or options to abandon the venture in alignment with the VC’s objectives.

These investment and abandonment options were the basis for minimizing information

asymmetry for VCs to make better strategic decisions about the startup. Furthermore,

participants described concepts of real options in how their strategic options might

change as the startup’s market environment changes. Changing strategic options was

mentioned by Baduns (2013), who described that businesses might use a real options

framework to hedge against risk due to uncertain climatic conditions in the market.

Therefore, based on participant responses to interview questions, option identification

and recognition were part of VC’s startup assessment and analysis. In this study, VC

participants used investment or abandonment options to decide whether to continue

investing in the startup and whether to pursue an IPO or buyout at the most suitable time.

The themes from this study attribute to strategies that VCs use to determine which

startups will become profitable. Derivation of these themes was triangulated and

supported with the review of archival documents. The themes of this study included (a)

due diligence and investor involvement, (b) reduction of information asymmetry, (c)

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human capital management, (d) environmental and market forces, (e) startup experience

matching investor strategy, (f) trust building, (g) investment timing, and (h) VC market

dynamics. Derivation of these aforementioned themes was triangulated and supported

with the review of archival documents. The themes relate to the finding of the study. The

findings of the study were used to address the overarching research question.

Theme 1: Due Diligence and Investor Involvement

Due diligence is a process that VCs use to prepare, plan, analyze, and monitor an

investment (Gerasymenko & Arthurs, 2014). Strategically preparing and planning

business activities are important to VCs for identifying companies that lead to

profitability and a successful investor exit (Teker & Teker, 2016). Monika and Sharma

(2015) emphasized that VCs spend time monitoring their investment portfolio of investee

companies and making course adjustments throughout the investment process to

maximize VC success rate. Maximizing VC success rate includes various criteria for

making investment decisions (Monika & Sharma, 2015). Consistent with Monika and

Sharma, the interview participants highlighted various criteria they use while making

investment decisions when describing strategies for identifying profitable startups.

However, regardless of the investment criteria or strategies VCs discussed, the

participants converged on a similar theme: due diligence and investor involvement are

important for identifying profitable startups and a successful investor exit. Table 3 shows

the questions and the frequency of participants discussing strategies that include due

diligence and investor involvement with the entrepreneur leads to profitable companies

and a successful VC exit. I used the archival documents, which include imported data

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from VC websites, entrepreneur websites, and VC brochures, to triangulate with

participant responses to illuminate the theme of due diligence and investor involvement.

Table 3

Due Diligence and Investor Involvement (Frequency)

Participant Interview

questions

Total number

of references

I1 2, 4, 5, 6 7

I2 2, 6, 7 5

I3 2, 3, 4, 5 7

I4 2, 3, 5 4

I5 2, 4, 6, 7 5

I6 3, 4, 7 4

I7 2, 3, 6, 7 8

I8 4, 7 3

I9 2, 4, 6, 7 6

I10 3, 5, 6, 7 6

I11 2, 3, 7 4

Pursuing buyout versus IPO. Six participants (55%) described the rationale for

buyers to invest in a startup may include (a) generating additional revenue for the buyer’s

business or (b) integrating a technology difficult to develop in-house. However, four

participants (36%) indicated that managing a business strictly toward an IPO is rare. IPO

is costly for VCs to pursue (Arcot, 2014). Three participants (27%) highlighted that

unless an IPO is important to the entrepreneur, CEO, and the management team, very few

companies explicitly focus on an IPO. Eleven participants (100%) made an assertion that

managing a startup to an IPO or a buyout starts with preparation and a long-term vision.

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Four participants (36%) described the long-term vision includes leveraging the

investment in a manner that drives success and knowing that following a period,

favorable options exist. Nunes et al. (2014) indicated that one of the most important

criteria that VCs use to evaluate entrepreneurs relates to not only a long-term vision but

also honesty and integrity. Nine participants (82%) discussed evaluating a startup as a

formidable investment vehicle to become attractive to buyers or lead to an IPO requires

preparation in support of the long-term vision.

Assessing investee companies. Three participants (27%) indicated that

identifying profitability from a startup is a straightforward process. However, the initial

assessment of the startup can be difficult; overcoming this difficulty requires preparation.

Seven participants (64%) made similar assertions when indicating that preparation

comprises of elements of due diligence that VCs might use when assessing startups.

Gerasymenko and Arthurs (2014) said that VCs predict the performance of the

investment by analyzing the business plan, technology, and management team during the

due diligence process. VCs may conduct a detailed analysis of the startup to ensure the

business is a viable investment. Five participants (45%) indicated that due diligence is

operational in nature and includes a detailed review of sales, legal status, customer

information, contracts, business model, industry, and internal/external forces. However,

Sammut (2012) said that due diligence is more an art than a science. Conducting due

diligence includes leveraging people with expertise in specific areas who can quickly

assess if the investment is the correct path for meeting the goals and objectives of the VC

(Kollmann et al., 2014).

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Ten participants (91%) emphasized that to minimize risk, preparing for

investment might include the entrepreneur and VC conducting all the quality work

upfront. Eight participants (73%) indicated that the entrepreneur, VC, and any other

investment stakeholders require a plan, template, and an approach suitable for all

investment participants. Three participants (27%) indicated that preparation should be

conducive with how the startup business is structured. Seven participants (64%)

suggested that preparing a plan is important but equally important is following the plan

through moments when the business performance may be under stress. VCs prefer

entrepreneurs who demonstrate capabilities of managing risk and preparing for things

that might not go according to plan (Khavul & Deeds, 2016). Two participants (18%)

indicated that failure sometimes occurs when people deviate from their plan and start to

move away from how they made money in the past and how they managed risk in the

past.

Ten participants (91%) indicated that preparing and provisioning for a buyout are

easier than preparing for an IPO. Eight participants (73%) elaborated on provisioning for

a buyout. These eight participants (73%) indicated that strategically preparing for a

buyout does not exclude the need for conducting market analysis and competitor analysis

because there is a rare situation when someone might attack a market never seen before

by any entrepreneur. Eight participants (73%) indicated that startups with a clear value

proposition are attractive to the market. Five participants (45%) described that market

attractiveness provides feedback signals by the number of people looking at the company

from a buyer’s perspective. These signals, according to three participants (27%), could

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include inquiries from investor bankers or other companies interested in acquiring or

expanding into the technologies the startup possess. Four participants (36%) talked about

positive investment signals that trigger a buyout because of market traction from the

investee company. When startups gain traction in the marketplace, then people might be

interested in the startup’s activities. Two participants (18%) indicated that market interest

could attract upper bench buyers and creates a buzz in the marketplace centering on the

startup.

Nine participants (82%) indicated that risk-averse entrepreneurs and VCs should

perform a rigorous analysis of the competition to understand why the competition might

not attack the market. Furthermore, five participants (45%) indicated that evaluating a

startup’s idea from the perspective of why other players who have been in the industry

for a number of years can see the same idea but they are not attacking the market.

According to these five participants (45%), fundamental competitive and market analysis

can address such questions. Three participants (27%) elaborated on market analysis by

indicating some competitors might have capital constraints, too much leverage, or a focus

on a different strategy. The competitive analysis may lead to an understanding of why the

timing may be suitable for the entrepreneur to enter the market. Eldridge et al. (2013)

discussed the complexities of developing and delivering products better, quicker, and

cheaper than the competition. Three participants (27%) indicated that some people view

entrepreneurs as wildcatters who prefer to take the risk. However, six participants (55%)

explained that good quality entrepreneurs focus on managing risk. They indicated that

preparation derives from the market analysis so that when the entrepreneur is ready to

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attack a market with the VC investment, then the entrepreneur and other stakeholders feel

confident about the startup’s position. Therefore, strategic techniques for assessing

startups include analyzing the startup’s capabilities and the startup’s preparation through

rigorous upfront analysis of the market and the competition.

Eight participants (73%) indicated that the VC’s and entrepreneur’s ability to

recognize the potential future market is important for planning. Five participants (45%)

suggested that this planning coupled with the ability to maximize profits becomes a

driver for a successful business. Mayer-Haug et al. (2013) found that planning and profit

are not as strong as the link between network and profit or experience and profit.

However, Ecer and Khalid (2013) found that VCs support the growth of startups with

hands-on involvement that includes management, marketing, and planning activities.

Furthermore, seven participants (64%) highlighted some factors for determining the most

suitable course of action might include recognizing the potential for expanding the

business into other continents, or the need for outsourcing. These factors influence the

assessment activities, planning, preparation, and the decision to manage the investment

business to profitability and a successful VC exit.

Eight participants (73%) discussed planning the business execution path includes

evaluating and assessing the transferability of the product. This transferability is to

determine whether the product is highly customized for a unique client base or if the

product is transferable and scalable to a general population of clients. Five participants

(45%) described this assessment should include understanding the extent and effort for

additional product modifications to enable the product to become multitenant and capable

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of servicing a broader scope of clients. Eight participants (73%) discussed selling a

product, and how VCs strategically evaluate how the product generates revenue. Five

participants (45%) discussed selling products based on a licensing structure, which

becomes difficult to grow revenue on a consistent basis when startups sell licenses. Three

participants (27%) mentioned an attractive long-term revenue-generating model is to sell

products as a service comprising of monthly fees with long-term contracts. VCs should

plan and analyze how the startup’s product links into the financial objective and

performance of the company to determine if the financial performance aligns with the

expectations of the VC (Lahr & Mina, 2016).

Six participants (55%) indicated during early phases of the business, uncertainty

in the market and market forces could affect the business and create difficulty in knowing

whether a VC should cash out or make a multimillion-dollar investment and continue

growing the company. However, two participants (18%) noted that although some VCs

prefer a buyout in today’s market, there are certain elements that could make a business

more IPO-able versus being a private sale. Four participants (36%) highlighted that some

VCs may plan a dual track option while filing for an IPO. According to these

participants, a dual track option could elicit buyer interest. The VC, entrepreneur, and the

startup team may be satisfied going public if the opportunity presents itself. However,

with the dual track option, the option is to weigh going public with the inbound interest

from potential buyers of the business. With a dual-track option, decision makers become

indifferent to either outcome of an IPO or a buyout. Therefore, according to six

participants (55%), if the VC and entrepreneur get a great offer to sell the business, then

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the business is sold. Five participants (45%) suggested that if little buyer interest exists,

then taking the business public and continue growing the company is an alternative

option for a profitable VC exit. Leveraging strategies for pursuing an IPO or a buyout

depends on entrepreneurial orientation.

Entrepreneurial orientation. The entrepreneurial orientation creates strategic

VC options in the midst of market and economic uncertainty. These strategic options help

the VC and the entrepreneur determine suitable action plans for competitive strategies

and performance expectations. Linton and Kask (2017) characterized entrepreneurial

orientation as (a) business being proactive, (b) containing traits of risk-taking, and (c)

being innovative. Ten participants (91%) indicated that VCs and entrepreneurs

strategically map the structure of the company within the market, and they determine how

this structure might change over time. Seven participants (64%) described the need to

understand how customers view the startup’s products and the sustainability of labor

requirements aligned with production output. Ten participants (91%) indicated that

deciding to manage a startup to a successful VC exit includes strategically evaluating the

sustainability of the product, market size, and customers in alignment with the

entrepreneurial orientation. Seven participants (64%) highlighted that when someone

considers buying the startup, assessors may evaluate forecast models, budget,

profitability, and human capital. Three participants (27%) indicated the purpose of this

evaluation is to determine the requirements to achieve the next strategic milestone or

stage of the company. One participant (9%) further elaborated by indicating if some of

these business components are weak, then there is the option to share the risk through

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partnerships for the next few years. According to this participant (9%), if the partnership

is successful, then the startup and buyer might fully integrate through a merger or buyout.

All participants (100%) agreed that entrepreneurs should understand the

reasonable growth in the market as well as their business model. Nine participants (82%)

indicated that this understanding should include a multiyear plan that effectively

describes how the company will lead to a successful VC exit. Evaluating the reasonability

of the entrepreneurial business model constitutes a series of metrics and performance

indicators that are measurable, understandable, reasonable, and rational (Rosenbusch et

al., 2013). Parlalis (2011) described how some business models from early-stage startups

take a top-down approach. One participant (9%) indicated when an entrepreneur is

attacking an industrial area the entrepreneur must have real operations and knowledge to

understand the factory floor. The consensus from all participants (100%) is entrepreneurs

must understand the team, the product, the market, customers, and possess necessary

strategic and tactical skills to design a business model capable of meeting milestones and

moving the business towards profitability.

All participants (100%) agreed that meeting milestones are critical for follow-on

investment options and profitability because, during each stage of the business lifecycle,

such milestones provide validation of the business model and the team’s ability to

execute. Therefore, ongoing monitoring of early-stage startups is essential for a

successful VC exit (Hirsch & Walz, 2013). Sammut (2012) found that entrepreneurs

should link critical milestones and capital needs to the underlying approach to managing

risk and accelerate value. All participants (100%) indicated that as the entrepreneurial the

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team meeting business milestones, and the justification for continuous investment into

subsequent rounds of funding becomes merited. These milestones might include metrics

for monitoring the startup (Hausman & Johnston, 2014). Metrics are useful for

monitoring (a) the performance of the company, (b) changes in the market, and (c) the

dynamics of the industry (Hausman & Johnston, 2014). Three participants (27%)

indicated the importance of using metrics when they noted significant market fluctuations

might damage the startup’s ability to continue investing alongside the VC when the

company loses money. According to these three participants (27%), high market

variability might signal caution for startups because if there are insufficient funds to

continue investing in the company through a turbulent market, then follow-on investment

options could lead to the option for the VC to strategically abandon the venture.

Follow-on investment. Six participants (55%) discussed how forces outside of

market conditions could affect VC follow-on investment options. According to these six

(55%) participants, forces include the direct or indirect influence of regulatory and

government decisions on the industry, market, or entrepreneurial business. Lee et al.

(2013) corroborate the influence of governmental involvement with entrepreneurial

performance. Ehret (2013) described the unpredictability of external forces acting on a

business or an industry in a manner that influences performance. These external forces

are sometimes hidden and could influence the performance of the investment, and these

forces might delay investment yields (Ehret, 2013). External forces could influence not

only the initial investment but also follow-on investment options (Ehret, 2013).

Therefore, actionable strategies for evaluating follow-on investment for profitable

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startups includes understanding the entrepreneurial business expansion plan while

operating in the existing market context and contending against real or perceived

headwinds that might derive from external and unpredictable forces.

Nine participants (82%) discussed actionable techniques for assessing profitable

startups include seeking the truth behind the startup business. Four participants (36%)

explicitly discussed the notion of truth regarding looking beyond the flashiness of the

presentation into evaluating the reality of the startup’s operations. These four participants

(36%) indicated the VC might seek to have a clear and concise perspective on the

financial state of the company. They described that VCs could thoroughly evaluate the

operational performance, run rate, liabilities, expenses, company issues, and how the

startup uses their finances to create value in the market. Fisher et al. (2014) linked

successful entrepreneurs to monetary performance that result from their decisions and

actions. Also, VCs may evaluate the assets at the startup’s disposal (Smith & Cordina,

2014). These assets are both tangible and intangible, which includes intellectual property,

human capital, software, expertise, and trade secrets (Castellaneta et al., 2016).

Six participants (55%) indicated that before and during the follow-on investment

stage of the investment cycle, startups have an opportunity to execute on the initial

investment. According to these participants, how startups execute on VC investment

provides signals to the investor. Rosenbusch et al. (2013) described measuring firm

performance derives from monitoring capital usage and financial indicators that include

profitability, growth, and market performance. Therefore, strategically evaluating a

company for follow-on, or second round investment, includes determining the quality of

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the startup’s execution abilities (Rosenbusch et al., 2013). Six participants (55%)

indicated that a strategy for identifying profitable startups include the VC assessor

reviewing the financial objectives of the company in the language of revenues and

profits. VCs might evaluate the controls in place to ensure the company is meeting

margin targets (Khanin & Mahto, 2013). The VC might review the company from an

operational performance perspective, and determine traction in the marketplace (Manigart

& Wright, 2013). This marketplace traction might derive from on-target product

launches, quality of customer service, customer loyalty, and recurring customers

(Manigart & Wright, 2013). Given the outcome of this evaluation, a determination could

become evident to the VC whether to leverage the option to make a full investment or the

option to abandon the investment and pull out.

Ten participants (91%) indicated that VCs are risk averse and tend to avoid

unnecessarily high-risk investments. Also, VCs face entrepreneurial investment

challenges characterized by high risk and strong information asymmetries (Lahr & Mina,

2016). In response to these challenges, three participants (27%) suggested that startups

might start on the lower scale and gradually progress based on addressing a distinct need

in the market while remaining cognizant of changes in the environment, financial

commitment, government regulations, state laws, and how these influences can effect

profit. One participant (9%) noted that risk-averse VCs should consider investing in

companies for the right reasons. Ten participants (91%) discussed reasons for investment

should link into generating an ROI for the VC through business growth and profitability.

Two participants (18%) suggested that VCs may avoid investing in companies for

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reasons relating to building a portfolio of investee companies for client lists or investing

to mimic the behaviors of other competitors in the market for market share. These two

participants (18%) agreed that when VCs invest in startups for client lists or for

mimicking the behavior of competitors, then there exist risk relating to potentially

investing in a company that does not meet the financial expectations of the VC. Failing to

meet financial expectations might occur when insufficient preparation, due diligence, and

analysis of the startup occur (Gerasymenko & Arthurs, 2014). One participant (9%)

shared a result of investing in client lists or mimicking competitors could lead to

investing in a company that might be highly leveraged, or the company may depend on a

small group of customers that provide the majority of the company’s revenue with little

opportunity to expand the customer base. Therefore, according to six participants (55%),

when investors make the decision to invest in a company, the decision should be rational

and explainable. Three participants (27%) indicated that if investors cannot explain their

rationale for investing in the company, then the investor becomes at risk of investing in

something that might not result in a profitable startup.

VC and entrepreneur objectives. Four participants (36%) discussed a

dependency of the investor’s objectives and the entrepreneur’s objectives in the business

when assessing a startup for an IPO or buyout. Gomezelj and Kuace (2013) established

that entrepreneurial success lies in meeting the objectives of shareholders. Four

participants (36%) indicated that the entrepreneur achieving revenue and profitability

milestones within a finite timeframe might trigger the point when it is time to sell the

company or pursue an IPO. Furthermore, three participants (27%) described the

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recognition of profitable opportunities if strategic buyers decide to buy the startup and the

buyer can increase the size of the business by some magnitude. These participants

suggested that these buyers may recognize the value of the startup and want to capitalize

on it, and they may become willing to pay for it. One participant (9%) discussed a

company might require a hundred million in revenue before it can become relevant to a

sector and a proof point the company is a sustainable business. Therefore, according to

three participants (27%), recognizing if a company will lead to a successful buyout or

IPO is case specific although the monetization component usually is not. Two

participants (18%) indicated that if the startup has a good idea, a good market, and a good

team, then the monetization piece usually works itself out.

Six participants (55%) indicated, from a buyout perspective, VCs might assess the

strategic effect the startup might have on competitors thus becoming an attractive

investment opportunity for an industry leader to acquire the startup. According to one

participant (9%), this situation is a great buyout scenario to consider while building a

company. Therefore, strategically, entrepreneurs and VCs should try to recognize the

window of opportunity and the point when the startup is most valuable to buyers. One

participant (9%) described that if the entrepreneur goes beyond a critical inflection point,

then the startup becomes less valuable to the buyers because of the point where the

startup builds something that the buyer might have to unbuild. Gordon (2014) indicated

that VC exits occur when the investors reach an acceptable increase in share value. VCs

bet on the management team, and the team’s ability to deliver a plan that generates a

positive ROI and a successful VC exit (Townsend & Busenitz, 2015). Therefore, a

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strategic indicator of a buyout or an IPO is the startup’s ability to become profitable

through a timely and strategic execution of the business plan.

After reviewing participant responses and archival documents, strategies VCs use

for identifying profitable startups include due diligence and investor involvement. Due

diligence includes a combination of preparation, planning, and monitoring. In addition to

due diligence, investor involvement with the investee company is important for building

a profitable investee company. Therefore, both due diligence and investor involvement

could enable VCs to identify profitable startups and lead to a successful VC exit.

Theme 2: Reduction of Information Asymmetry

Van Rensburg (2012) indicated that the entrepreneur and VC relationship could

reduce information asymmetry thereby improving the performance of the business.

Information asymmetry between the entrepreneur and the VC increases the risk of failing

to create a profitable venture (Townsend & Busenitz, 2014). Based on participant

feedback, another overarching theme in this study is knowledge and information are

important for reducing information asymmetry thereby creating strategic value for

identifying profitable startups. Table 4 shows the questions and frequency of participants

discussing the reduction of information asymmetry. I used the archival documents, which

include imported data from VC websites, entrepreneur websites, and VC brochures, to

triangulate with participant responses to illuminate the theme of reducing information

asymmetry.

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Table 4

Reduction of Information Asymmetry (Frequency)

Participant Interview

questions

Total number

of references

I1 2, 6 3

I2 1, 2 4

I3 1, 6, 7 8

I4 1, 2, 6, 7 6

I5 2, 6 3

I6 6 2

I7 1, 2, 7 5

I8 2, 6, 7 4

I9 1, 7 2

I10 1, 2, 6, 7 5

I11 1, 6, 7 3

Six participants (55%) described their top-down approach for assessing startups.

These six participants (55%) discussed their approach for identifying large segments of

the economy open to disruption while providing less consideration on whether the market

segment a startup pursues makes an initial profit. According to these participants,

focusing on large segments of the economy requires VCs and entrepreneurs to

understand, through information sharing, how the startup fits into the economy. Four

participants (45%) described the importance of information sharing because of their

mentality of investing money as quickly as possible into the startup. These four

participants (45%) indicated they evaluate entrepreneurial business plans to determine the

feasibility of faster growth in a shorter timeframe. According to the four participants

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(45%), if the business plan does not provide information concerning how to achieve

faster growth then information asymmetry between the VC and entrepreneur exists, and

the business plan is often rejected. Four participants (45%) highlighted the importance of

reducing information asymmetry and the investment timeline since VCs work to

maximize their ROI as quickly as possible. Therefore, reducing information asymmetry

as quickly as possible becomes important for a strategic VC investment. Four participants

(45%) described the reduction of information asymmetry when making startup

investment decisions. However, Hsu (2013) suggested that VC exit decisions depend on

industry-specific levels of technological changes and the timing of an IPO relates to the

incubation period; information asymmetry between the VC and startup effects the

incubation period. Whether the VC’s approach for profitable exits derives from economic

disruption, rapid ROI, technological changes, or incubation period, the correct

information made available at the correct time is critical for the VC to make the best

decisions (He & Wan, 2013).

According to nine participants (82%), difficulty identifying profitable startups

includes the lack of information available to the VC during the time of assessment.

Townsend and Busenitz (2014) found that information asymmetry provides the basis of

risk aversion in investors. Nine participants (82%) indicated that identifying profitable

startups require several dimensions of analysis for reducing information asymmetry.

Although, according to the nine participants (82%), these dimensions of analysis create

complexity in identifying profitable startups. These dimensions of analysis include the

VC, entrepreneur, business, technology, and market (Gerasymenko & Arthurs, 2014).

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Monika and Sharma (2015) made a similar assertion after indicating the VC decision-

making process includes market potential, management, competition, and product. Six

participants (55%) described the interaction of information and knowledge within the

domains of VC, startup, technology, and market relates to enhancing the understanding

between the entrepreneur and VC to lead to a profitable business. According to eight

participants (73%), although identifying profitability in a company might be a

straightforward process, the initial assessment of startups is difficult because of

information asymmetry. Therefore, reducing information asymmetry between the VC and

entrepreneur enables the VC to make a better investment decision, which enables startups

to achieve timely profitability and leads to a successful VC exit.

Eleven participants (100%) indicated evaluating startups for initial investment

begins with an understanding of the market, the market opportunity, and the

entrepreneur’s value proposition. Huarng (2013) corroborates this assertion by indicating

that important elements of entrepreneurship include an analysis of the market along with

the application of innovation, products and services, strategies, and competitive

dynamics. Six participants (55%) indicated a good entrepreneurial business plan should

include such information (i.e., market opportunity capable of supporting hundreds of

millions or billions of dollars annually). Five participants (45%) expounded on the

investor’s understanding of the market reduces information asymmetry between the

investor and the startup as well as positions the investor to make better evaluation

decisions. Furthermore, six participants (55%) indicated the VC’s understanding of the

market reduces the risk of investing in a company that misaligns with the true needs of

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the market. This understanding includes looking beyond the existing client base of the

startup and into the problem facing the majority of clients in the market (Kollmann et al.,

2014). Part of understanding the market includes understanding the localized competition

through competitor analysis (Huarng, 2013). Four participants (36%) indicated high

market entry barriers to new entrants are strategically important to VCs because entry

barriers might protect market share. Entry barriers might include intellectual property

designed to protect trade secrets, knowledge, or technology from replication (Castellaneta

et al., 2016). Intellectual property may ensure the protection of the VC’s investment for

future use. Castellaneta et al. (2016) described how VCs in some states that support

Inevitable Disclosure Doctrine (IDD) for trade secret protection increases investment per

startup by approximately 27%. Furthermore, eight participants (73%) indicated VCs

might need to assess who else is attacking the same opportunity. Therefore, according to

these participants, VCs should strategically evaluate the problem within the market that

the startup seeks to solve. Entrepreneurs and VCs could reduce information asymmetry

by understanding the market and customer segment.

Challenges exist for VCs because of the lack of information available to the

entrepreneur and the VC during the time of assessment (Van Rensburg, 2012). Ten

participants (91%) suggested information asymmetry presents an inherent risk in

identifying profitable startups because VCs tend to fill in gaps in information with

assumptions. Seven participants (64%) described how some VCs reduce information

asymmetry by relying on other individuals or sources of information about the startup

company; information may relate to opportunity, technology, or market. These seven

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participants (64%) indicated the source of information might derive from bankers,

financial individuals, or other companies familiar with the market. Although information

asymmetry creates challenges for VCs, Peng et al. (2014) found that information

asymmetry could create value for entrepreneurs when they can lower searching and

monitoring cost through the exploitation of information asymmetry. Conversely, Van

Rensburg (2012) indicated that when entrepreneurs establish relationships with VCs, then

this relationship could reduce information asymmetry. Wang and Hsu (2014) supported

this assertion when they found that the VC and entrepreneur relationships could create

mutual benefit for knowledge gain thereby reducing information asymmetry. Four

participants (36%) noted the challenge and difficulty that VCs experience when

identifying profitable startups includes relying on others to provide critical and authentic

information suitable for making decisions. Although VCs cannot eliminate risk, they do

manage risk within the boundaries of their risk tolerance levels (Andrieu, 2013). Four

participants (36%) indicated VCs experience the risk of knowing if the startup created

something ahead of its time, created a niche market, or created something flashy that

sounds good but brings little value to the market. These areas of analysis represent

challenges for VCs identifying profitable startups.

Five participants (45%) indicated another challenge identifying profitable startups

could be attributable to the lack of knowledge that entrepreneurs might possess

concerning their available options when pursuing capital for businesses. Colombo and

Dawid (2016) showed that successful business discoveries include the ability of the

entrepreneur to leverage knowledge and alertness to search and exploit opportunities.

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Entrepreneurs without the requisite knowledge of financing options for capital

procurement might focus on conventional avenues that include personal finances, credit,

and loans (Gomezelj & Kuace, 2013). Two participants (18%) indicated this situation

further exasperates the challenge of assessing startups when entrepreneurs mix business

expenses, assets, and income with personal finances. According to these two participants

(18%), this mixing expenses situation creates impediments when entrepreneurs are

unable to raise sufficient capital needed for their startup and create missed opportunities

for the VC that might otherwise result in a positive ROI and profitability. Although,

Staniewski et al. (2016) inferred that entrepreneurs who invest heavy personal funds into

the venture send positive signals that help convince investors of the commitment of the

entrepreneur through shared risk. Entrepreneurs with experience, knowledge of the

market, and understanding of financial options can reduce information asymmetry

thereby create a profitable business (Franco et al., 2014).

Three participants (27%) highlighted that for first-time entrepreneurs, the VC

should ensure the entrepreneur understands what it means to get 5% of the market, and

includes the startup’s plan for obtaining the initial customer to a large enough customer

base to achieve profitability. One participant (9%) indicated less knowledgeable and

inexperienced entrepreneurs begin to breakdown at this point of evaluation. Kim and

Longest (2014) suggested that nascent entrepreneurs are at a greater disadvantage

because of the lack of startup experience. According to two participants (18%), less

experienced entrepreneurs have a good idea, and they think they know where the

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opportunities exist in the market, but these entrepreneurs do not understand the difficulty

of penetrating the market or scaling distribution because of lack of knowledge.

Ten participants (91%) indicated VCs choose to invest in markets large enough to

support a meaningful business. The VC’s understanding of the market is important in

identifying profitable startups (Monika & Sharma, 2015). Four participants (36%)

indicated VCs with little market understanding is at risk of startups with flashy

presentations or serves a small portion of the market triggering an investment response

that might elevate investment risk and fail to produce a positive ROI. Therefore,

according to these four participants (36%), the evaluation of the startup should align with

the VC’s area of interest and core knowledge. Six participants (55%) agree that the VC’s

area of interest includes the market size, anticipated ROI, and assurances that the

startup’s pitch aligns with the VC’s goals. The VC’s goals and interests should include

the VC’s exit strategy (Ozmel et al., 2013). Capitalizing on investor and investee

knowledge reduces information asymmetry and leads to profitable startup and successful

investor exits.

Theme 3: Human Capital Management

Eleven participants (100%) agree VCs must have a keen eye for people to identify

which startups will become profitable. The VC must understand people, their

motivations, and their strengths and weaknesses (Arcot, 2014). Table 5 shows the

questions and frequency of participants discussing people as important factors for a

profitable startup. I used archival documents that comprised of imported data from VC

Decision-Making Strategies of Venture Capitalists for Risky Star.pdf

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