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Determinants among the Internet Startup Life Cycle
Dirk Jan Menkveld
Determinants among the Internet Startup Life Cycle
Master Thesis
Dirk Jan Menkveld
Master of Business Informatics StudentStudent number: 0364266
E-mail: [email protected]
Faculty of ScienceDepartment of Information and Computing Sciences
Utrecht University, Utrecht, The Netherlands
First advisor
Prof. Dr. S. Brinkkemper
Faculty of ScienceDepartment of Information and Computing Sciences
Utrecht University, Utrecht, The Netherlands
Second advisor
Dr. X. Franch
Faculty of InformaticsGroup of Software Engineering for information SystemsUniversitat Politècnica de Catalunya, Barcelona, Spain
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Abstract
Determinants among the Internet Startup Life Cycle
Internet startups are oftentimes seen as the solution to the much needed job growth in Western soci-eties. More importantly, it is successful startups that matter most. But, how do internet entrepreneursvalue the most important factors for success? This study determines what factors are important ineach stage in the internet startup life cycle. First, success and failure factors are identified througha literature review. Second, a conceptual internet startup framework is constructed in which thefactors are divided in the founding team, the startup capability, and the external environment. Third,interviews are held to validate the framework from which propositions are derived. And last, an on-line survey is conducted with 48 entrepreneurs in order to test the propositions and determine whatfactors are most important in each stage of the internet startup life cycle. The results showed us thata) the factors commitment, pivot / adaptability, and learning are significantly important in the dis-covery stage; b) no significant factors were found in the validation stage; c) the factors customers,commitment, and learning are significantly more important than other factors in the efficiency stage;and d) the factors pivot / adaptability and incubator / advisors showed significantly less importantthan the other ten factors. Besides this, the factor staffing becomes significantly more importantover time and the factor pivot / adaptability significantly less important over time. But, overall weconclude that commitment is most important for entrepreneurs. Furthermore, we present the epicstartup for today’s internet entrepreneurs which stands for engage, practice, interact and change.
keywords: internet startups, internet startup life cycle, factors, success/failure, entrepreneurs
Preface
When I started my master Business Informatics back in February 2007 I was determined to finish it
within two years. I was following three courses per period where two were advised, because I had
only one goal: graduate and show my skills in the world of practitioners.
Everything changed in the late fall of 2007. Together with Kevin Voges, Martijn de Kuijper and
Willem Spruijt we signed up for the course ICT Entrepreneurship and came up with a brilliant idea.
And this is where one adventure stagnated and another began. During the master program and the
course ICT Entrepreneurship we learned everything we needed to know how to build a software
product and how to start a software business.
Before I knew, we had build our own product, acquired customers, setup our own office, found a
CEO, managed two investment rounds, hired several employees, won several awards, and much
more. Our product was a social personal finance platform which we called Qash, and by launch we
changed it to Yunoo. Eventually it was acquired by AFAS, a software company. Today, it is known
as AFAS Personal and used by around 300,000 people in the Netherlands. After the acquisition, it
was time for me to finish what I had started back in February 2007, my master.
When I met Prof. Dr. Brinkkemper in the fall of 2011 I had absolutely no idea what I wanted
to write my thesis about. I agreed upon to visit Barcelona for a period of six months and work
on a project about Requirements Engeneering, as it was one of my tasks as a Product Manager at
Yunoo. After a few meetings with Dr. Franch, it didn’t feel right, I wanted to do something with
my own experience about internet startups. After brainstorming I came to the conclusion I wanted
to investigate what factors are most important for entrepreneurs in each stage of the internet startup
life cycle. And now, nine months later, this is the result. Enjoy.
Dirk Jan Menkveld
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Contents
1 Introduction 6
2 Method 9
2.1 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3 Research Question . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.4 Research Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.5 Scientific and Social Relevance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.6 Definitions and Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3 Literature 15
3.1 Systematic Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.2 Literature on Factors for Success . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.3 Identified Factors Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.4 Significant Identified Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.5 Significant Factors from Other Studies . . . . . . . . . . . . . . . . . . . . . . . . 34
3.6 Internet Startup Life Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
4 Conceptual Internet Startup Framework 39
4.1 CISF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.2 Factor Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.3 Predecessor of the CISF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5 Results 53
5.1 Startup Profile - Habitissimo.es . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
5.2 Startup Profile - GuideGuide.com . . . . . . . . . . . . . . . . . . . . . . . . . . 56
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5.3 Startup Profile - ChangeYourFlight.com . . . . . . . . . . . . . . . . . . . . . . . 58
5.4 Startup Profile - Teambox.com . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
5.5 Startup Profiles - Qualitative Analysis . . . . . . . . . . . . . . . . . . . . . . . . 63
5.6 Online Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.7 Most Important Factors Per Stage - Quantitative Analysis . . . . . . . . . . . . . . 69
5.7.1 Descriptive Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
5.7.2 Most Important Factors in the Discovery Stage . . . . . . . . . . . . . . . 71
5.7.3 Most Important Factors in the Validation Stage . . . . . . . . . . . . . . . 73
5.7.4 Most Important Factors in the Efficiency Stage . . . . . . . . . . . . . . . 75
5.7.5 Most Important Factors in the Scale Stage . . . . . . . . . . . . . . . . . . 77
5.7.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
5.8 Most Important Factors Over Time - Quantitative Analysis . . . . . . . . . . . . . 80
5.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.10 Most Important Factors vs. Startup Profile - Quantitative Analysis . . . . . . . . . 84
5.10.1 State vs. Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
5.10.2 Current Stage vs. Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5.10.3 Founding Team Size vs. Factors . . . . . . . . . . . . . . . . . . . . . . . 89
5.10.4 Founding Team Focus vs. Factors . . . . . . . . . . . . . . . . . . . . . . 90
5.10.5 Employees vs. Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.10.6 Target Focus vs. Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
5.10.7 Target Market vs. Factors . . . . . . . . . . . . . . . . . . . . . . . . . . 98
5.10.8 Startup Location vs. Factors . . . . . . . . . . . . . . . . . . . . . . . . . 99
5.10.9 Startup Age vs. Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
5.10.10 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
5.11 Most Important Factors vs. Profile of the Entrepreneur - Quantitative Analysis . . . 104
5.11.1 Gender vs. Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
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5.11.2 Age of the Entrepreneur vs. Factors . . . . . . . . . . . . . . . . . . . . . 105
5.11.3 Education vs. Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
5.11.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
6 Discussion 112
6.1 Most Important Factors per Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
6.2 Most Important Factors Over Time . . . . . . . . . . . . . . . . . . . . . . . . . . 114
6.3 Most Important Factors vs. Startup Profile . . . . . . . . . . . . . . . . . . . . . . 115
6.4 Most Important Factors vs. Profile of the Entrepreneur . . . . . . . . . . . . . . . 116
6.5 Research Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
7 Conclusion 119
7.1 Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
7.2 Implications for Entrepreneurs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
Acknowledgements 124
Appendix A Variable Names and Abbreviations 128
Appendix B Factors Found in Literature 130
Appendix C Interviews 134
C.1 Questions V1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
C.2 Questions V2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
C.3 Interview Transcript - Habitissimo.es . . . . . . . . . . . . . . . . . . . . . . . . . 137
C.4 Interview Transcript - GuideGuide.com . . . . . . . . . . . . . . . . . . . . . . . 147
C.5 Interview Transcript - ChangeYourFlight.com . . . . . . . . . . . . . . . . . . . . 158
C.6 Interview Transcript - Teambox.com . . . . . . . . . . . . . . . . . . . . . . . . . 167
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Appendix D Startup Profiles - Extended 177
Appendix E Online Survey 181
Appendix F Tables 193
F.1 Factors in Discovery - Paired Samples Test . . . . . . . . . . . . . . . . . . . . . 193
F.2 Factors in Validation - Paired Samples Test . . . . . . . . . . . . . . . . . . . . . 194
F.3 Factors in Efficiency - Paired Samples Test . . . . . . . . . . . . . . . . . . . . . . 200
F.4 Factors in Scale - Paired Samples Test . . . . . . . . . . . . . . . . . . . . . . . . 201
F.5 State vs. factors - Independent Samples Test . . . . . . . . . . . . . . . . . . . . . 207
F.6 Current stage vs. factors - Independent Samples Test . . . . . . . . . . . . . . . . 209
F.7 Founding team size vs. factors - Independent Samples Test . . . . . . . . . . . . . 211
F.8 Founding team focus vs. factors - Independent Samples Test . . . . . . . . . . . . 213
F.9 Employees vs. factors - Independent Samples Test . . . . . . . . . . . . . . . . . . 215
F.10 Target focus vs. factors - Independent Samples Test . . . . . . . . . . . . . . . . . 217
F.11 Target market vs. factors - Independent Samples Test . . . . . . . . . . . . . . . . 219
F.12 Startup age vs. factors - Independent Samples Test . . . . . . . . . . . . . . . . . 221
F.13 Age vs. factors - Independent Samples Test . . . . . . . . . . . . . . . . . . . . . 223
F.14 Education vs. factors - Independent Samples Test . . . . . . . . . . . . . . . . . . 225
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1 Introduction
The internet is driving economic growth and job creation. The Boston Consulting Group recently
evaluated the internet economy in the top 20 global economies to determine how online business
drives economic activity. By 2016, there will be 3 billion internet users globally - almost half the
world’s population. The internet economy will reach $4.2 trillion in the G-20 economies. The
internet is contributing up to 8 percent of GDP in some economies, powering growth, and creating
jobs. (Dean et al. 2012)
Today’s most valuable global brands are technology firms. The top 5 of Millward Brown’s index
of most valuable global brands consists of 4 technology firms, namely Apple (1), IBM (2), Google
(3), and Microsoft (5). Technology and telecom brands together comprised about 44 percent of the
value of the list, whereas they accounted for about one-third of the value in 2006. An upward trend
can be noted. internet firms like Google, Amazon.com, Facebook, Baidu, and eBay are prominently
present in Millward Brown’s index of most valuable global brands. (Campbell 2012)
Software businesses dramatically changed in the past few years. Whereas traditional products sales
and license fees have declined, product software firms revenues are shifting to services. With the
advent of free and open source software, and the welcoming of the internet, the trend accelerated and
still is rapidly growing. Since 2000, there are many enterprises and individual customers rebelling
against paying a lot of money for standardized or commodity-type product software. (Cusumano
2008)
Whereas the top internet firms are most successful and just a few ones in the world, more internet
firms want to go to the top. In this disruptive industry, starting an internet business is not an easy
task. Together with the failure rate, the risk is extremely high. In between 1991 and 2000 only
21.9 percent of the established new technology ventures (NTVs) in the United States survived after
5 years (Song et al. 2008). This is only one example of more studies conducted to identify the
survival rate in this emerging industry. With this new and immature industry, more research is
needed in order to identify critical factors for success or failure.
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Next to NTVs, the enclosed ecosystem is growing. Today, entrepreneurs are surrounded with a
lot of knowledge and experience through advisors, incubators, investors, fellow entrepreneurs, and
more. For example, science and technology incubators play an increasing role in contributing to
the entrepreneurial, venture and economic development (Wonglimpiyarat 2010). Besides this, in a
recent study, it has been stated the key technologies and developments evolved rapidly in only 30
years time (Oestreicher and Walton 2012). For example, the PC industry was born in the late 70’s
and today we’re walking around with smartphones in our pocket with access to internet.
The information and communication technology sector (ICT) becomes to shift from an emerging
industry to a major growth industry and occupies an important place in the contemporary knowledge
based economy. Implications for management practice are numerous and most economic actors,
such as venture capitalists, bankers, public authorities and local governments put high expectation
in the growth potential of ICT startups. (Lasch et al. 2007). The ICT sector has grown enormously,
a world without ICT has become unimaginable where ICT plays an important role in every industry.
Although failure rates are still high (82.9 percent), Silicon Valley research shows us that the technol-
ogy industry is still growing, but it has some year-specific and industry-mix effects (Luo and Mann
2011). Given the fact that most startup fails, it doesn’t stop (internet) entrepreneurs from trying.
This is because of the easiness to start a business, for example the startup costs are really low. The
only thing you need is an idea and you can enter or create a market.
If we talk about startups, we talk about entrepreneurs. Entrepreneurs are those who are willing
to risk everything to found something new. It’s been on the planet for ages. Most literature on
entrepreneurship has focused on successful ventures, so little is known about why ventures fail.
Even less is known about how they fail. We agree with Liao et al. (2008) that our understanding
of entrepreneurship will never be complete until we have a clear understanding of what causes its
discontinuation.
The internet startup life cycle (ISLC) of an startup (internet firm) is unbelievably fast (Drori et al.
2009). Theory shows that life cycle models exists of predetermined sequence of stages, and viewed
as a linear progression, while each stage exists of different factors that effect performance. Factors
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can be strategy, structure, decision-making, but also organizational, administrative, marketing is-
sues arise through the stages. A very recently published technical report of Berman et al. (2011)
show four stages that are best applicable to internet startups. Because, every internet startup can
benchmark itself against 17,000 startups spread over the world. In their report they adapt the four
steps of Blank (2007) and argue that the key difference is that Blank’s stages are company centric
than product centric. The stages consists of discovery, validation, efficiency, and scale. In discovery
a startup is trying to find its customer, in validation its startup to validate the business model, in
efficiency its trying to optimize the product and the business processes and in scale they’re ready to
conquer the market.
Keeping in mind that with the impact of the technology industry at the world economy and the
failure rate of NTVs, it can be said a lot can be accomplished in this research area. Therefore,
with this study we want to contribute to both scientific and practitioners world. Scientific research
has been done in different scientific areas like: computer science, information technology, business
venturing, management, product innovation, economics, entrepreneurship, and more. In several
papers it’s stated that there is a great discrepancy in literature as to which factors do in fact lead to
success or failure with results that are often controversial and fragmented (Cressy 1996; Sorensen
and Chang 2006; Lasch et al. 2007; Song et al. 2008; Lussier and Halabi 2010). In this study
different papers will be examined, evaluated and combined into a new conceptual internet startup
framework. We want to determine what factors are most important at the different stages of the
internet startup life cycle, so this is summarized in the following research question:
What are the most important factors among the stages of the internet startup life cycle?
The remainder of this thesis is organized as follows. The next section describes the research ap-
proach. Then, section 3 literature is reviewed to find out what is written about this subject. Next,
section 4, a conceptual internet startup framework is proposed to identify the most important factors
among the stages of the internet startup life cycle. Our new and exciting results are described in
section 5 and discussed in section 6. And finally, section 7 gives the conclusions.
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2 Method
2.1 Problem Definition
To become a successful internet startup, entrepreneurs need to follow an unwritten path. A path that
is certainly not straightforward for everyone and also not an easy task to perform. There are several
factors valued by entrepreneurs that play an important role to become successful. In successful
cases, factors are described as success factors, and in unsuccessful cases, factors are described as
failure factors.
There’s a great discrepancy in literature about success and failure factors (Cressy 1996; Sorensen
and Chang 2006; Lasch et al. 2007; Song et al. 2008; Lussier and Halabi 2010). Although ap-
proaches are original, results are often controversial and fragmented. An overlap can be found
between research approaches, but results differ.
As the growth of this technology industry is extremely high, we still know little. In most cases
internet startups fail whereas they could have survived if we knew more. Little research has been
done regarding to internet startups. The research field is relatively young and research is needed in
order to understand the success of internet startups.
2.2 Problem Statement
The right focus will help all entrepreneurs effectively in order to build an internet startup and deal
with problems that may occur at hand. Every entrepreneur is facing problems coming on their path
to success. Some are able to deal with it and some are not. So, the ones who are dealing with it,
probably become successful and others are fail and are unsuccessful.
These problems can be defined as critical factors that affect internet startups at certain stages of the
internet startup life cycle. These issues can be about business or development and will impact the
business at stages where entrepreneurs didn’t expect it to be. Mostly they’re unexpected. When
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entrepreneurs can prevent some issues from happening or when they identify it at the correct time,
they can consistently act on the issue at hand. Issues appear everywhere at anytime and it affects the
business vitality.
It’s important to consider these issues in order to help entrepreneurs building internet businesses
effectively and efficiently that eventually stimulate innovation. We can learn from both successful
and unsuccessful entrepreneurs in order to find out what factors are most critical for success, and
therefore entrepreneurs can benefit by focussing on these factors on their road to success.
2.3 Research Question
Based on the Introduction (section 1), Problem Definition (section 2.1) and the Problem Statement
(section 2.2), the following research question has been formulated:
What are the most important factors among the stages of the internet startup life cycle?
The goal is to determine what factors are valued as most important by entrepreneurs in becoming
successful. This will be done through a mixed method. Entrepreneurs of both successful and unsuc-
cessful internet startups will be surveyed about their experience and findings. The research question
also rises the following research subquestions:
1. What factors become more or less important when a startup matures?
2. What factors are valued differently based upon certain startup characteristics?
3. What factors are valued differently based upon characteristics of the entrepreneurs?
2.4 Research Approach
This thesis consists of four parts: a literature review, a conceptual internet startup framework, in-
terviews and an online survey. First, a literature review (a) will be performed in order to collect
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material about factors that play an important role by establishment of new firms. This means that an
investigation is done in order to find out what is written about this subject or similar topics in var-
ious articles, reports, and books from other researchers. Second, with the findings in the literature
a conceptual internet startup framework (b) will be constructed. The most important factors will
be grouped together in order to create an understandable framework. The goal of the conceptual
internet startup framework is answer the research question and its subquestions. Third, qualitative
feedback will be gathered through interviews in order (c) to validate the conceptual internet startup
framework from which propositions will derived. And fourth, an online survey (d) will be con-
ducted in order to test the propositions. With the results of the survey the research questions will be
answered.
This approach consists of gathering qualitative and quantitative data. Qualitative data is gathered
through the interviews and the quantitative data is gathered through the online survey. So, this
approach can be described as a mixed method.
a) Literature Review
A literature review will be conducted in order to find out what has been written about this subject
in literature. First, a systematic literature review (SLR) will be conducted to find relevant literature.
Besides this, more literature will be gathered from different research areas in order to understand
what has been researched in terms related to the subject. The selected papers will be thoroughly
discussed in order to understand what factors lead to firm success. (Section 3)
b) Conceptual Internet Startup Framework
After the selection and the review of the significant found factors of the literature review, they’ll be
grouped together into factor groups. The paper of Belassi and Tukel (1996) will be used in order to
construct a profound framework. This framework will be developed in a way that its applicable for
internet startups.
c) Interviews
The constructed framework will be validated with entrepreneurs from internet startups. With a in-
depth interview the researchers want to validate the framework by asking direct questions and let
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the entrepreneurs prioritize the factors for each factor groups. After the interview the framework
will be reviewed and improved based on the learnings.
d) Online Survey
After the validation of the framework with interviews, an online survey will be constructed in or-
der to find out what factors per stage of the internet startup life cycle (ISLC) are most important.
Questions will be constructed according to the Likert scale (Likert 1932), and are therefore easy to
answer for entrepreneurs. In this order a great number of surveys can be conducted.
2.5 Scientific and Social Relevance
Internet is relatively new and still immature considering the changes in technologies and software
that are innovated every day. The last decade showed us that internet startups rise and fall. So,
there’s a lot to learn of both successful and unsuccessful entrepreneurs that are challenging these
rapidly changing web technologies. Therefore sharing knowhow stimulates and motivates every-
body who has an idea and want to start their own business.
Scientific literature about this topic is still pretty scarce. There’s not a lot written about what fac-
tors are important for successes or failures of internet startups and also what factors are valued by
entrepreneurs as most important. This work will contribute to the scientific world for the following
reasons: it provides a real effort of real cases into the scientific world; together, with the experience
of the writers and other entrepreneurs it will help the scientific world in understanding what factors
are most important to entrepreneurs of internet startups in order to become successful.
Every entrepreneur struggles the same fight. Learnings can be defined in order to help the en-
trepreneurs starting up. It’s not about proving something new, no; it’s about helping these people
and internet startups building new companies, and therefore stimulate job growth. The research will
show what factors are most critical for entrepreneurs in the different stages of the internet startup
life cycle and present some clear implications for today’s internet entrepreneurs.
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2.6 Definitions and Scope
The scope of this research is based on entrepreneurs of both unsuccessful (failures) and successful
(success) internet firms in the ICT sector. Several definitions are and will be used during this study.
Here’s a summary of the most common words within the scope of this research.
Business model: a model that is developed in order to sustain a business. It needs to be defined at
the beginning and its purpose is to generate revenues.
Entrepreneur: a person who establishes, organizes and operates a (new) business under conditions
of extreme uncertainty, taking on greater than normal financial risks in order to do so.
Internet startup: is a starting (product) software company that provides a service via the internet
to people (users) to solve a certain problem. internet startups are innovative: they enter an existing
market or create a new market.
Internet startup life cycle: the stages that must be taken in order to become a mature internet firm
Factor: a circumstance, fact, or influence that contributes to success or failure
Founder: a person who establishes an institution or settlement (in this case an internet startup)
Funding: the amount of money needed in order to grow a sustainable business. Funding is used in
order to cover the costs. The costs can be divided into three main categories: marketing, personnel,
and technology costs.
Market: the B2C segmentation of people that are addressed as the potential users of the service the
internet startup provides. The B2B market consists of companies that are addressed as the potential
clients of the product or service the internet startup is providing.
Metrics: are the key indicators that give the impression of how the internet startup is doing and will
help to make proper business decisions.
Startup stage: a phase that internet startups go through during the startup life cycle
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Team size: is the size of the team that consists of persons that are fully employed and are running
the daily business
User: a person that uses the software product
Venture capital: provides capital for internet startups in exchange for shares
Terminology
Throughout this thesis we’ll use small letters for all words, e.g.: the words internet and startups will
always be written with small letters. Only names of persons or firms will be written with a capital
letter. Also titles of sections or sub sections will be written with a capital letter.
Variables
Variables are derived from the data that will be gathered through the interviews and the online sur-
vey. Both independent and dependent variables will be introduced in several sections. Throughout
this thesis tables will be used with abbreviations of the variables (used in SPSS) and therefore the
translations of the abbreviations can be found in the tables 61 62, and 63 in appendix A.
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3 Literature
First, a systematic literature review (SLR) has been conducted and is described in the first section.
Then, more literature has been reviewed in order to find out what is written about this subject.
After that, factor groups, significant identified factors, and significant factors from other studies are
presented in the following sections. And finally, the internet startup life cycle is described.
3.1 Systematic Literature Review
Background
The systematic literature review (SLR) has been proposed by Kitchenham. She adapted a system-
atic approach from the medicine discipline in order to conduct more thoroughly research. The goal
was to make it applicable for the domain of software engineering. In her report she states that a SLR
is a mean of identifying, evaluating and interpreting all available research relevant to a particular
research question, or topic area, or phenomenon of interest. In this study the goal is to find scientific
valuable papers about internet startups and their life cycles, entrepreneurs, factors, successes, fail-
ures, and lessons learned. The SLR consists of three main steps: planning the review, conducting
the review, and reporting the review. Conducting a SLR for this study is important, because of the
following reasons:
• to summarize the empirical evidence of the determinants (factors) startups are facing while
building a sustainable business
• to identify any gaps in current research in order to suggest areas for further investigation
• to provide a framework/background in order to appropriately position new research activities
The last two reasons were introduced by Kitchenham and are common for every SLR in the domain
of software engineering.
15
Review questions
In this review, the research question is mapped into the following review questions:
RQ1*: What is written about the success factors (key challenges) of startups?
RQ2 **: What cost and risk factors were identified by startups?
RQ3 **: What software development techniques are used by startups?
RQ4 **: Is there a relation between these techniques and business characteristics?
RQ5 **: How does a life cycle of a startup look like?
RQ6 **: Were software standards used during development?
*) the primary review question, RQ2-RQ6 are secondary review questions
**) these review questions were defined in the really early stage of this thesis
This study will search for recent developments regarding the proposed review questions. This is
done, because in a world where information technology is evolving rapidly, papers can’t be outdated.
Besides this, the goal of the thesis is to write implications for entrepreneurs in order to give them
advice. Therefore, that date is set to be 2007 or newer. Derived from the review questions, seven
keywords are taking into consideration and divided in about who and about what (table 1).
Table 1: Keywords
About who About whatInternet startup (web startup) Success factorsEntrepreneur Key challenges
Lessons learnedSoftware developmentLife cycleSoftware standard
16
The keywords from table 1 can be mapped into the following search string:
(internet startup OR web startup OR entrepreneur)
AND
(key challenges OR success factors OR lessons learned OR software development OR life cycle
OR software standard)
Data sources and search strategy
The search process will be a manual search of the specific conference proceedings and journal pa-
pers since 2007. In table 2 there’s a list of journals and conference proceedings that will be consulted
while conducting the SLR. The journals and proceedings are selected based on the best journals in
the areas of Software Engineering, Management, Entrepreneurship, Business, and Economics.
Study selection
The goal of the study selection is to test whether the papers are actually relevant for this study. So,
with a list of selection criteria primary studies are identified that provide direct evidence about the
research question. The following selection criteria will be used:
• papers must be published after 2007;
• papers must be written in English;
• papers must be available in electronic form (downloadable within the license of UPC or UU).
Study quality assessment
It’s hard to assess the "quality" of the primary studies. But, Kitchenham (2004) proposed that the
quality consists of the evidence that you’ve found. And, to understand the strength, it’s better to
build the literature on different types of study.
17
Table 2: List of journals and conference proceedings
Source(s) Acronym
Information and Software Technology IST
Journal of Systems and Software JSS
IEEE Transactions on Software Engineering TSE
IEEE Software IEEE SW
Communications of the ACM CACM
ACM Computer Surveys ACM Sur
ACM Transactions on Software Engineering and Methology TOSEM
Software Practice and Experience SPE
Empirical Software Engineering Journal EMSE
IET Software (formerly known as IEE Proceedings Software) IET SW
Proceedings International Conference on Software Engineering ICSE
International Workshop on Software Product Management IWSPM
Requirements Engineering: Foundation for Software Quality REFSQ
Requirement Engineering RE
Engineering Management Journal EMJ
Product Focused Software Process Improvement PROFES
MIS Quarterly MISQ
Strategic Management Journal SMJ
Journal of Management JOM
Journal of Development Entrepreneurship JDE
Journal of Accounting and Economic JAE
Journal of Business Venturing JBV
Small Business Economics SBE
18
Data extraction
The objective is to collect all the information needed to address the review questions and the study
quality criteria. The following data items can be addressed:
• author(s)
• title
• abstract
• number of citations
Results
At every search engine of the selected papers, the search string was entered into the available input
fields. Table 3 shows the results of the search. In total 12 search pages were consulted, where some
journals were searched more than once. It resulted in 1346 results, where 5 were selected as useful.
19
Table 3: Results
Search engine Includes journals Results Useful
sciencedirect.com IST, JSS, JAE, and JBV 66 papers 1 paper
computer.org TSE, IEEE SW 752 papers (only firstpage of 100available)
dl.acm.org CACM, ACM Sur, TOSEM 66 papers -
onlinelibrary.wiley.com SPE, SMJ 25 papers -
springer.com EMSE, REFSQ, PROFES - -
scitation.aip.org IET SW - -
ieeexplore.ieee.org ICSE, IWSPM , EMJ ( not included,no ISSN available)
412 papers 2 papers
digital-library.theiet.org REFSQ, not able to find in this paper - -
misq.org MISQ - -
jom.sagehub.com JOM 25 papers 2 papers
worldscinet.com JDE - -
springerlink.com SBE, unable to perform search withstring on website
- -
20
Table 4: Selected papers
Author(s) Title Abstract # of ci-tations
Franke, Gru-ber, Harhoff,and Henkel(2006)
What youare is whatyou like –similaritybiases inventurecapitalists’evaluationsof start-upteams
This paper extends recent research studying biases in venturecapitalist’s decision making. We contribute to this literatureby analyzing biases arising from similarities between a venturecapitalist and members of a venture team. We summarize thepsychological foundations of such similarity effects and derivea set of hypotheses regarding the impact of similarity on theassessment of team quality. Using data from a conjoint experi-ment with 51 respondents, we find that venture capitalists tendto favor teams that are similar to themselves in type of trainingand professional experience. Our results have important impli-cations for academics and practitioners alike.
96 cita-tions
Salah (2011) A Frame-work for theIntegrationof User Cen-tered Designand AgileSoftwareDevel-opmentProcesses
Agile and user centered design integration (AUCDI) is of sig-nificant interest to researchers who want to achieve syn- ergyand eliminate limitations of each. Currently, there are no clearprinciples or guidelines for practitioners to achieve successfulintegration. In addition, substantial differences exist betweenagile and UCD approaches which pose chal- lenges to integra-tion attempts. As a result, practitioners developed individualintegration strategies. However, suc- cess evaluation of cur-rent AUCDI attempts has been anec- dotal. Moreover, AUCDIattempts cannot be generalized to provide guidance and assis-tance to other projects or organi- zations with different needs.My thesis aims to provide a Software Process Improve- ment(SPI) framework for AUCDI by providing generic guide- linesand practices for organizations aspiring to achieve AUCDI inorder to address AUCDI challenges including: introducing sys-tematicity and structure into AUCDI, assessing AUCDI pro-cesses, and accommodating project and organizational charac-teristics.
no cita-tions
Erdogmus(2010)
Cost Ef-fectivenessAnalysis inSoftwareEngineering
The tutorial presented an approach that leverages well-knowneconomic and financial concepts for evaluating the cost ef-fectiveness of software development processes and techniques.Software engineering studies often report separately on thecosts and benefits of a phenomenon of interest, and rarely ad-equately address the combined bottom line implications. Inparticular, tensions between quality and productivity are hardto reconcile, making objective, high-level insights elusive. Toaddress this need, the tutorial focused on quantitative methodsfor synthesizing co-dependent cost-benefit effects and analyz-ing the resulting behaviors.
no cita-tions
21
Table 5: Selected papers
Ling, Zhao,and Baron(2007)
Influenceof Founder– CEOs’PersonalValues onFirm Per-formance:ModeratingEffects ofFirm Ageand Size?
The effects of two values held by founder-CEOs (collectivismand novelty) on companies’ postÐstart-up performance are in-vestigated. By integrating congruence and organizational life-cycle literatures, the authors hypothesized that the effects ofboth values are moderated by company age and size, suchthat collectivism exerts stronger beneficial effects in older andlarger firms, whereas novelty exerts stronger beneficial effectsin younger and smaller firms. Results based on 92 small- tomedium-sized enterprises offer support for most predictions,thus demonstrating the influence of founders’ values on newventure performance and highlighting the importance of con-sidering organizational lifecycle for the understanding of thisinfluence.
25 cita-tions
Shinkle(2012)
OrganizationalAspirations,ReferencePoints, andGoals :Building onthe Past andAiming forthe Future
Three distinct frameworks have been advanced by scholars toanalyze organizational aspirations: behavioral theory, Ansoff’sstrategic management view, and strategic reference point the-ory. These frameworks, or views, are grounded in different as-sumptions and mechanisms. This article reviews and synthe-sizes the three views, also drawing on literatures in economics,performance measurement, and psychology, to present a com-prehensive understanding of organizational aspirations. Thisreview shows the literature consists primarily of studies us-ing behavioral theory explanations, typically provides studiesof the consequences of theoretically inferred aspiration levels,is impoverished in terms of field measurement of aspirations,and lacks comparative or integrative studies of the three views.Drawing on this critique, the article identifies theoretical andempirical gaps and provides guidance for future research.
4 cita-tions
Conclusion
Table 4 show some divers results. There was no paper found that really matched our research topic.
The five papers were selected because they reflect really specific parts of startups. It needs to be
concluded that a SLR didn’t resulted in useful papers regarding this topic. So, we hope to find more
specific literature via other sources, like Google Scholar.
Besides this, it needs to be noticed that this SLR was conducted in the very early stage of this thesis.
Later on, the papers were defined as not useful where our research emerged to a more specific part
of our first intentions.
22
3.2 Literature on Factors for Success
As we’ve seen that the SLR didn’t showed us the results we were hoping to get. We started a more
flexible search on Google Scholar. Eventually, after thoroughly searching we were able to find
some interesting and useful papers. Although it’s not really about internet startups, it’s about factors
related to firm success in general from both entrepreneurial and business perspectives that can be
applicable in the case of internet startups .
Eventually, we selected nine papers that are useful for this research. These papers were selected
after reviewing the same data items as described in the SLR, namely the title, abstract, and number
of citations. In some cases it was more than others, but the most important is that these papers can
be easily bound to the subject of this research where we need it.
Several studies has been performed in different scientific areas in order to identify critical factors
that lead to success and failure of firms. Whereas it has been noted by several researchers, there’s
a great discrepancy in literature and results are often controversial and fragmented (Cressy 1996;
Sorensen and Chang 2006; Lasch et al. 2007; Song et al. 2008; Lussier and Halabi 2010), there’s
still a lot that can be accomplished.
Table 6 provides a summation of relevant papers to this subject. internet startups are not special,
they’re just like every other company with the same goal and that’s: attribute value and create a
sustainable business. The papers have been published between 1990 and 2011. So, when there
was no internet back in 1990, we can still learn of the findings of the paper of Duchesneau and
Gartner (1990). They investigated different types of factors related to the new venture success
and failure. In 1992, Bruno et al. investigated the evolution of new technology ventures over 20
years and examined patterns of failure, merger, and survival. Than, a few years later, Schutjens
and Wever (2000) addressed the determinants of success from a longitudinal perspective. And in
2006, it were van Gelderen et al. who estimated the relative importance of a variety of variables
in explaining startup success. In the same year Lee and Lee published a paper about failure factors
of new technology-based ventures according to the growth stages. This kind of research was also
conducted in 2007 by Lasch et al. where they seek to deal with growth determinants for ICT startups.
23
In 2008, Song et al. performed a meta-analysis of 31 studies and found 24 most widely researched
success factors. And in 2010, it were Lussier and Halabi trying to test the Lussier 15-variable
business success versus failure prediction model. And finally, in 2011, Cardon et al. explored
failure accounts that are attributed to mistakes made by entrepreneurs. These papers are based on
the entrepreneurial aspect of the factors and from a business perspective.
Summed up, these papers contribute to understand why entrepreneurs (or firms) succeed or fail.
Where these papers differ in context, they’ve a general purpose, and that’s to find out what factors
are important for success and failure. And therefore they can be used in order to learn from the
identified factors and find out whether they’re applicable for the success of internet startups.
24
Table 6: Key findings in 9 studies about key factors for success or failure
Author(s)context
Type of re-search
Data collection Summer of key finding(s)
Duchesneauand Gartner(1990)
Qualitativeand quan-titative
26 firms selected4-8 hour intervieww/ lead entrepreneurUSA
Field study conducted with both successful and un-successful entrepreneurs. They found that lead en-trepreneurs in successful firms were more likely tohave been raised by entrepreneurial parents, have hada border business and more prior startup experience,and believed they had less control of their success inbusiness. Effective startup or purchase required broadplanning efforts that considered all aspects of the in-dustry and firm. Nearly all purchased firms failed.Less successful firms were restricted to narrow mar-ket sectors consisting of smaller customers and thosemore difficult to service and therefore were typified byhigh products costs and unprofitable operations.
Bruno et al.(1992)
Qualitative 250 tech-based firms12 interviewsUSA
Studied 250 technology-based firms and a dozenfounders were interviewed that survived 20 years.They found that 50% failed, 32% had merged or beenacquired, and 18% had survived as independent busi-ness. Among the factors predicting failure were prod-uct/market problems, financial difficulties, and man-agerial/key employee problems. The interviews sug-gested that relations between founders, banking andcredit problems, attempted takeovers, and interna-tional expansion were among the key crises that hadto be overcome.
Schutjensand Wever(2000)
Quantitative 2,000 firmsliterature reviewThe Netherlands
They addressed the determinants of success from lon-gitudinal perspective and tested how new firm charac-teristics relate to firm growth in number of employeesusing a panel of nearly 2,000 firms. In addition to alarge firm size right from the start, good preparation,having a business partner, and some years in salariedemployment enhance firm growth.
Lee and Lee(2006)
Quantitative 2,052 tech firmsKorea
They investigated 2,052 technology-based Koreanfirms and identified 502 failed ones among them. Theydefined the failed firm as the one that stopped its busi-ness operations due to insolvency and financial prob-lem.The study observed that entrepreneurs of failedventures had significantly lower levels of education atall stages of growth. However, various factors had dif-ferent influences according to the stages of growth.
25
vanGelderenet al. (2006)
Qualitativeand quan-titative
517 entrepreneursEntrepreneurs fromUSA, Sweden, Nor-way, The Netherlands
In a 3-year period 517 nascent entrepreneurs were fol-lowed in order to estimate the relative importance of avariety of approaches and variables in explaining pre-startup success. They found that the importance ofperceived risk of the market as a predictor of gettingstarted versus abandoning the startup effort.
Lasch et al.(2007)
Qualitativeand quan-titative
220 ICT startupsFrance
They analyzed 220 ICT startups and verified the in-fluence of individual and organizational factors ongrowth. They found that human capital and workingexperience have no significant impact on the successof young ICT firms, whereas critical growth factors aremostly financing and customer related variables.
Song et al.(2008)
Qualitativeand quan-titative
11,259 NTVsMeta-analysis
An empirical study of 11,259 new technology ventures(NTVs) showed that after fours years 36 percent sur-vived and after five years, the survival rate fell to 21.9percent. They conducted a meta-analysis to analyzethe findings of 31 studies and identified the 24 mostwidely researched success factors for NTVs. Theyfound that 8 were homogeneous significant successfactors for NTVs, 5 were not significant, and 11 wereheterogeneous.
Lussierand Halabi(2010)
Quantitative 234 small businessUSA, Croatia, Chile
They tested the Lussier 15-variable business successversus failure prediction model in Chile with a sampleof 234 small business. The model has been test withsignificant results and will reliably predict a group ofbusinesses as failed or successful more accurately thanrandom guessing.
Cardon et al.(2011)
Quantitative 7 newspapersUSA
By examining reports of entrepreneurial failures thecollected data suggest that cultural sense making offailure varies by the geographical area where fail-ure occurs. In addition, failure has a large impacton the stigmatization of the entrepreneur and the en-trepreneurship within the local area, as well as on theindividual entrepreneur’s view of themselves follow-ing failure.
26
The nine papers are just a sample in literature where researches try to identify reasons for success
and failure, namely determinants. In general, it can be mapped in several scientific areas. For
example, in 2008, Fabriek et al. described an in depth analysis of successful and unsuccessful
offshore custom software development projects and therefore also investigated what factors lead to
success or failure. Just to be clear, the papers have been selected because there are closest to the
subject of this study.
The selected papers provide really interesting and significant findings and suggestions for further
research. Duchesneau and Gartner (1990) found more entrepreneurial characteristics that lead to
success and showed us that entrepreneurs can better start from the ground than to buy an existing
firms. They suggest that the nature and process of aggressive entry needs to be explored. And
in addition, in-depth field research would be useful for describing the complex process which en-
trepreneurs undertake to develop aggressive new ventures.
And Bruno et al. (1992) showed us that survival is tough and a lot crises need to be overcome and
were grouped in three factor groups, which we’ll see later. They’re suggesting how survival without
founders will be made possible.
The study of Schutjens and Wever (2000) showed us that experience, preparation, and starting with
a business partner enhance firm growth. Research on firm success that focusses exclusively on ei-
ther entrepreneurial aspect or firm aspects or firm aspects or external factors.
Lee and Lee (2006) showed that education is a significant factor in all stages of a startup life cyle.
Eventually they suggest common characteristics technology-based ventures among countries in the
world need to be identified.
van Gelderen et al. (2006) found that the market risk influences the startup abandoning and they
suggest that predictors of pre-startup performance need to be understood.
Lasch et al. (2007) found that financing and customer related variables are critical growth factors.
Regional effects on outcomes of new high tech ventures is a suggestion for further research. And
they argue that the distinction between the main branches of the ICT sector may give other insights.
Besides this, they also suggest a multiple level design to identify more detailed factors.
Song et al. (2008) found that out 24 researched success factors 11 were significant, which we’ll
27
present later. They suggest more research about the examination of opportunity dimensions as well
as search for moderators of the internationalization performance and the market growth rate perfor-
mance relationship.
Lussier and Halabi (2010) showed that a set of factors in a model can reliably predict success or
failure, and is therefore useful. They argue that research is needed to develop a theory of success
/ failure. Besides this, they suggest to develop cultural control variables and these how they affect
business success and failure.
And finally, Cardon et al. (2011) showed that misfortune or mistakes are caused by several factors
and can be avoided and is therefore also useful. For further research they suggest to study failure
situation from multiple perspectives, study attributions among countries, and evaluate long-term
effects of venture failure.
Whereas the studies differ in approach, they found some significant factors that matter. So, com-
bined together, the nine papers form a solid foundation for the conceptual internet startup frame-
work, which will be proposed in section 4. First, let’s elaborate more on the identified factors groups
consisting of the individual factors that influence success or failure.
28
3.3 Identified Factors Groups
In total 157 factors were identified and grouped together in each paper, that can be seen in table 7.
The naming of the groups show some resemblances and differences. Some resemblances can be
notified, like factors related to the entrepreneur. It can be assumed that is a logical consequence,
because the entrepreneur is the founder of the firm and the center of attention within each firm.
Also more central are the firm and the resources. And besides this, groups are formulated through
activities or consequences. Differences are more dimension based, for example in pre- and post
activities vs. the just named factor groups.
As the factor groups point out, the factors are mainly divided in three groups can be found: the
entrepreneur, the firm (capability), and the resources (external). In the next section we’ll come back
to this remark. Lee and Lee (2006) is the only study that looks at the influence of the factors over
time in different growth stages. Lasch et al. (2007) did almost the same, but the difference is Lasch
et al. already defined pre- and post- startup activities, whereas it may be that some factors can be
influential in both stages.
Although most of the authors are indicating that there’s a discrepancy in the literature and the results
are often controversial and fragmented (Cressy 1996; Sorensen and Chang 2006; Lasch et al. 2007;
Song et al. 2008; Lussier and Halabi 2010), approaches are original and an overlap can be found in
between the research approaches, namely the identified factor groups and the factors. Let’s take a
look at the results.
29
Table 7: Identified factor groups
Author(s) Factor groups (number of factors)
Duchesneau and Gartner (1990) The lead entrepreneurs (4)Startup behaviors (8)Firm behaviors and strategy (8)
Bruno et al. (1992) Product/market (5)Financial (3)Managerial/key employee (2)
Schutjens and Wever (2000) Entrepreneur-associated factors (12)Firm-associated factors (6)External factors (2)
Lee and Lee (2006) Traits of entrepreneur (5)Strategy and resource capabilities (7)Environmental conditions (5)
van Gelderen et al. (2006) Individual (8)Process (2)Environment (4)Intended organization (5)
Lasch et al. (2007) Human capital and working experience (8)Pre- start-up activities (5)Post- start-up activities (8)
Song et al. (2008) Market and opportunity (9)Entrepreneurial team (4)Resources (11)
Lussier and Halabi (2010) Success and failure variables (15)
Cardon et al. (2011) Misfortunes (5)Mistakes (6)
30
3.4 Significant Identified Factors
The studies show some remarkable results. Table 8 gives an overview of all significant found factors.
The papers of Duchesneau and Gartner (1990), Bruno et al. (1992), Cardon et al. (2011) were left
out of table where had a different approach and showed no direct significant factors. From this point
on we’ll present the most important findings of each paper.
In the first study conducted by Duchesneau and Gartner (1990) they examined three factor groups
with factors that have been adapted in a previous research of the author. Factors were correlated
between failure and success firms (and therefore not added to the table). The most interesting find-
ings are that successful entrepreneurs are more likely have a broad range of previous (a) managerial
experience, (b) seek to reduce risk, (c) identify a business idea that is clear and broad, (d) use a
procedural and comprehensive planning process, (e) spend more time planning, (f) undertake mar-
ket research, (g) seek professional advice, (h) encourage participative decision making at strategic
and operational levels, (i) emphasize high levels of communication, (j) started at high levels of
capitalization, and (k) strategies of aggressive entry into broad markets.
The second study, conducted by Bruno et al. (1992), showed us that in 78% of surviving firms still
had one or more of the original founders in place. Failure was predicted by product/market prob-
lems, such as product timing difficulties, problems of product design, or inappropriate distribution
channels; financial difficulties such as initial undercapitalization or problems with the center capital
relationship; and managerial/key employee problems such as imbalance in the management team
or succumbing to the trappings of success. In the research they also looked at merger/acquisition
rates, relational aspects of surviving firms, and motives for founding the businesses. There were
no significant analyses performed in this research. It should be noted that the surviving founders
learned five things: 1) know yourself, 2) love your product, 3) honor your customer, 4) treat your
people well, 5) keep your integrity. As this is a wise lesson to pass on.
31
Table 8: Significant factors for success
Author(s) Factor groups Significant factors
Schutjens and Wever(2000)
Entrepreneur-associated factors
Firm-associated factorsExternal factors
Preparation (p<.05)Employment history (p<.05)Business partners (p<.05)-
Lee and Lee (2006) Traits of entrepreneur
Strategy and resource capabili-tiesEnvironmental conditions
Educational level (p<.05)Risk taking propensity (p<.05)Need for achievement (p < .10)Technology driven (p < .10, p < .01)Market driven (p < .10)Supports from Gov. (p<.05)Supports from Non Gov. (p<.05)
van Gelderen et al.(2006)
IndividualProcessEnvironment
Intended organization
--Industry experience (p<.05)Risk of the market (p<.05)Start out part- or full-time (p<.05)Industry type (p<.05)
Lasch et al. (2007) Human capital and working experi-encePre- start-up activities
Post- start-up activities
-
Existing clients at startup (p<.05)Startup capital (p < .10)Firmsize at startup (p<.05)Founding team (p<.05)New capital (p < .10)Type of clients (p<.05)Evolution of numbers of clients (p <
.01)International market (p < .10)
Song et al. (2008) Market and opportunity
Entrepreneurial team
Market scope (p < .001)Product innovation (p < .001)Industry experience (p<.05)Marketing experience (p<.05)
32
Resources Financial resources (p < .01)Firm age (p < .001)Firm size (p < .01)Firm type (p < .001)Patent protection (p<.05)R&D Alliances (p < .001)Supply chain integration (p < .001)
Lussier and Halabi(2010)
Success and failure variables Capital (desc.)Record keeping and financial control(desc.)Management experience (desc.)Planning (desc.)Professional advisors (desc.)Education (desc.)Marketing (desc.)
In the study of Schutjens and Wever (2000) they found preparation, employment history, and busi-
ness partners significantly relate to firm growth (measured in number of employees). These factors
all contribute to growth in terms of reducing risk and uncertainty. They found that firms with more
personnel and a higher turnover over time had a better preparation, more experience, and business
partner is very important to succeed.
Lee and Lee (2006) found that the following factors were significant: educational level, risk taking
propensity, need for achievement, technology driven, market driven, supports from Government,
and supports from non Government. The educational level was significant in all growth stages
identified by Lee and Lee. The other factors differ among the stages and are important at different
moments of the internet startup life cycle (ISLC).
No individual factors were found in the study of van Gelderen et al. (2006), but more environmental
and organizational factors. Industry experience, risk of the market, start out part- or full-time, and
industry type are factors that made a significant difference for success of a startup over time. The
only remarkable is that part- or full-time appeared to be significantly, because setting up a business
part-time may be a disadvantage because there isn’t a single focus on the business.
Lasch et al. (2007) found 7 significant factors that lead to growth of ICT startups. The most striking
33
part of their research is that human capital and working experience had no significant impact on the
success of young ICT firms. The paper showed that growth factors mostly exists of financing and
customer related variables, whereas there were identified at predefined stages of the startup, like the
defined activities in the pre- and post-startup stages.
Song et al. (2008) performed a empirical study among a lot of NTVs. They found 11 significant
factors all amongst the factor groups they defined. These findings are not remarkable, because the
factors consisted of previous researched factors. They corrected artifacts, and defined 24 factors
that were of relevance. The results are encouraging and therefore used by other papers.
This is the only paper where they didn’t group the factors. Lussier and Halabi (2010) had a slightly
different approach and constructed a model in order to predict success or failure. They found that
the prediction model is reliable and applicable in different countries. The most interesting part is the
identified factors. They found that 7 of 15 variables, identified in an earlier study, are (descriptively)
significant for success.
The paper of Cardon et al. (2011) was enclosed, because of a different approach. Although they
didn’t performed statistical analyses, they gathered practical information about failure reasons in
major US newspapers. The identified factors therefore can be used to learn from failure, and know
what factors (misfortunes or mistakes) lead to failure.
3.5 Significant Factors from Other Studies
Beside the selected studies as described earlier, more significant factors were identified in other
studies. In 1996, Cressy found that human capital (specific: experience, education, vocational
qualifications, prior employment status, and most recent type of occupation) is a true determinant of
survival, whereas they found that the correlation between financial capital and survival was spurious.
Like other researchers as stated before, they also conclude that the divergence of empirical results
in the area may be the failure to test a sufficiently rich empirical model.
Baum et al. (2000) investigated the impact of variation in startup’s alliance network composition
34
on their early performance in the biotechnology industry. They found that firm age and size influ-
ence performance, especially it produced significant differences in early performance. Implications
for managers are also discussed, where ’Don’t go it alone.’ is the most important one, because al-
liances is a valuable asset for early growth. Second, they argue that managers must consider rival as
partners.
Three factors were identified by Chang (2004) as to influence a firm’s initial public offering (IPO), an
indicator for internet startup performance. The better the reputation of participating venture capital
firms and strategic alliances partners were, the more money a startup raised, and the larger was the
size of a startup’s network of strategic alliances led to a shorter time to IPO. For entrepreneurs,
they argue that capital should be found from respectable venture capital firms, which can provide
needed funds and repetitional benefits. Second, strategic alliances with prominent partners should
be developed in order to access social, technical, and commercial resources that normally take years
to accumulate.
In a study of Sorensen and Chang (2006) determinants on the entrepreneurship side of startup were
reviewed. They found that education, industry experience, managerial experience and prior en-
trepreneurial experience are positively associated with venture performance. Although it should be
noted that the results should be treated with caution, their conclusions can be used for the develop-
ment of the framework.
In 2008, Bekker et al. (2008) researched the influence of situational factors in software product
management (SPM). The presence of SPM plays an important role in internet startup. The solution
of a real life problem will be offered via software, and therefore managing the software product
development is really important. They found defined several factor groups, namely business unit,
customer, market, product, and stakeholder characteristics. The customer characteristics were the
most influential one.
Li et al. (2010) examined firms who failed or survived the software industry in between 1995 and
2007. In their work they focus on capabilities like marketing (MK), research & development (RD),
and operations (OP) capabilities and found that OP capability has the strongest positive impact, and
35
MK and RD capability have a significant but lower degree of impact on firm survival. In practice,
they argue that OP is crucial for firm survival in the software industry.
The effects of human capital of founders and access to venture capital (VC) were analyzed of 439
Italian new technology-based firms (NTBFs) in a study by Colombo and Grilli (2010). They found
two important factors. First, there’s a direct positive effect of founders’ human capital on the growth
of NTBFs from the indirect effect mediated through access to VC financing. And second, the VC
status has a impact on the NTBF growth.
In the last paper, Cope (2010) found that failed entrepreneurs learn much not only about them-
selves and the demise of their ventures but also about the nature of networks and relationships and
the "pressure points" of venture management. The article also provides evidence that these pow-
erful learning outcomes are future-oriented, increasing the entrepreneur’s level of entrepreneurial
preparedness for further enterprising activities.
Summed up, these 8 papers were published by researchers from different disciplines and gave
insights of factors for success and failure. Together the researchers showed that human capital,
business partners, capital (with prominent status), experience, operational capability, network and
learning may influence the startup performance and therefore survival. Again, these findings can be
divided into factor groups like the entrepreneur, the firm (capability), and the resources (external).
3.6 Internet Startup Life Cycle
Every firm started somewhere and went through different stages, which is called the internet startup
life cyle (ISLC). Each stage in the ISLC is different and comes with different learnings. Drori
et al. (2009) states that a startup life cycle of an internet firm is rapid. Theory shows that life
cycle models exists of predetermined sequence of stages, and viewed as a linear progression, while
each stage exists of different factors that influence performance. Factors can be strategy, structure,
decision-making, but also organizational, administrative, marketing issues arise through the stages.
Drori et al. (2009) argued that we know little about the rapid SLC of the internet firm.
36
Table 9 shows previous research of identified life cycle stages of technology-based firms. It has
been researched in the 80’s, 90’s, 00’s, and still is begin researched. The first two columns show
scientific articles of Kazanjian and Kim and Ha, the identified stages in third column comes from
Blank, a Silicon Valley-based retired serial entrepreneur that founded 8 startup firms.
Table 9: Life cycle stages identified in 4 studies
Stage Kazanjian (1988) Kim and Ha (1999) Blank (2007) Berman et al. (2011)1. Conception and De-
velopmentStartup Customer Discovery Discovery
2. Commercialization Early Growth Customer Validation Validation3. Growth High Growth Customer Creation Efficiency4. Stabilty Mature Company Building Scale
The last column shows the stages of a very recently published technical report of Berman et al.
whom are specializing in internet startups. Every internet startup can benchmark itself against
17,000 startups in the world. With their data they can analyze the most important factors that lead to
success or failure. In their report they adapt the four steps of Blank and argue that the key difference
is that Blank’s stages are company centric than product centric.
Kazanjian (1988) investigated growth patterns and identified four stages. In the first stage, concep-
tion and development, it’s about resources acquisition and technology development, problems at this
stage include contraction of a product prototype and selling the business idea to financial backers.
The second stage, given financial backing, it’s about production related startup, so the focus is on
developing the product or technology for commercialization. At the third stage, if the product is
feasible and archives market acceptance, a period of high growth will typically result, building a
efficient task system is necessary to deal with problems. And finally, stability is reached when the
growth rate slows to a level consistent with market growth, the challenge is to maintain growth and
the market position.
Kim and Ha (1999) modified the described model of Kazanjian (1988) and adapted it to Korean
ventures and categorized progression into four stages. At startup, firms start their business and
37
develop a prototype of a product or service. At the second stage, early growth, those firms sell and
distribute the product or service in the market. Than, in the third stage, firms have multiple lines of
product and high growth rates of sales volume. And finally, firms become mature in the fourth stage
and succeed to IPO and stand on a leading position in an industry.
Blank (2007) defined the four steps to the epiphany in his customer development model. The cus-
tomer plays a centric role and therefore separates it’s activities to the early stage of a firm, and
designed four easy-to-understand steps. At the beginning, with custom discovery is meant to find
out who your customers are and whether the problem you’re solving is important to them. In the
second stage, customer validation, the goal is to build a repeatable sales road map for the sales and
marketing teams that will follow later. Than, in customer creation, the firm builds success on the
initial sales and the goal is to create end-user demand and drive that demand into the company’s
sales channel. And finally, in company building, all learnings will be made formal into different
departments in order to exploit the firm’s early market success.
As been said, the stages according to Berman et al. (2011) are adapted from Blank and shifted from
company to product centric. In their report they covered these four stages by defining each stages’
purpose, typical events, and duration. They also defined two more steps, not covered in their report,
but called profit maximization and renewal or decline. In the next chapter we’ll elaborate more on
these stages.
With the precursors of Kazanjian and Kim and Ha on Blank and Berman et al. there’s a solid mix
between the stages that are identified by different influential people. In general the first stage is
for everyone the same, it’s about building your first version of your product or service and try to
validate your customer’s need. Than, if the need has been verified, it’s important to see whether the
constructed business model will work and therefore will be tested in the second stage as we have
seen in all models. The third stage is about growth and efficiency, because we know the need is
there and sales can be accomplished, it’s time to be as efficient as possible in order to service the
customer. When this stage is over, the startup becomes formal and matures, and can therefore scale
and grow with the market and guard it’s position.
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4 Conceptual Internet Startup Framework
As we have seen in literature many studies have been performed to understand what factors influence
success or failure. It’s important, because it contributes to our research question. Now, we will
construct a conceptual internet startup framework (CISF) in order to combine the findings and find
out what factors are most important in the stages of the internet startup life cycle (ISLC).
This conceptual internet startup framework was derived from an earlier version of the CISF. Whereas
our goal shifted throughout this thesis project, the earlier work was more detailed and covered most
parts of the internet startup domain. At some point the predecessor of the CISF was getting to com-
plex and unfounded to investigate. So, we decided to focus on the factors related to the stages of the
ISLC and do a profound literature study before constructing the framework. With this focus we had
a more clearer research goal. The predecessor of the CISF can be found in section 4.3.
4.1 CISF
Covered in the previous section factors and factors groups have been identified in different studies
about success and failure factors. As described before in sections 3.3 and 3.5 the entrepreneur, the
firm (capability), and the resources (external) are defined as factor groups throughout all research
that has been done. These factor groups influence the different stages of the internet startup life
cycle (figure 1). The startup is set up by the entrepreneur and therefore the most important. Now,
a startup is often founded by more than one entrepreneur and therfore we call it the founding team.
Next to it, there are a lot of factors related to the firm, in this framework we call it the startup
capability with which we mean the state in which it operates and in which it can accelerate through
different factors. Available resources are needed to execute and solve problems, the resources are
provided by the external environment. Summed up, each factor may influence each stage in the
ISLC, namely discovery, validation, efficiency and scale.
Each factor group consists of a set of factors. In sections 3.4 and 3.5 we described a lot of significant
influential factors for success and failure. We summarized the findings and found the following
39
related significant factors for the factors groups identified in the previous section:
• Founding team: Working experience, commitment, learning *, pivot / adaptability *
• Startup capability: Business model / plan, network, business partners, staffing *
• External environment: Financial capital, market / competitors, customers *, incubator / advi-
sors *
The * resembles the fact that no significant effect on success have been found in literature. Still, we
argue that these factors may be more, less, or equally important in each of the stages of the ISLC.
The factors with a star were proven significantly influential on the startup performance.
Figure 1: Conceptual Internet Startup Framework
Startup
External environmentFinancial capitalMarket / competitorsCustomers *Incubator / advisors *
Founding teamWorking experienceCommitmentLearning *Pivot / adaptability *
Startup capabilityBusiness model / planNetworkBusiness partnersStaffing *
Startup life cycle
Discovery Validation Efficiency Scale
H1 H2 H3 H4
First, we’ll discuss each factor and later on we’ll present our definition of the factors.
40
Founding team
The team consists of one or more entrepreneurs who founded the firm and form the heart of the
internet startup. In several papers the characteristics of the entrepreneur highly influence the perfor-
mance of the startup (Cressy 1996; Lee and Lee 2006; van Gelderen et al. 2006; Song et al. 2008;
Colombo and Grilli 2010).
The working experience consists of industry experience, marketing experience, and management ex-
perience. The industry experience is identified in four papers, showed in two papers (van Gelderen
et al. 2006; Song et al. 2008) a significant difference and therefore adapted into the CISF and may
influence the founding team at different stages of the startup. The marketing experience showed to
be significant in the study performed by Lussier and Halabi (2010) as a critical factor for success-
ful firms and is therefore adapted into the CISF. This factor may be important in all startup stages.
Next, the management experience has been investigated by several papers (Duchesneau and Gartner
1990; Schutjens and Wever 2000; van Gelderen et al. 2006; Sorensen and Chang 2006; Lasch et al.
2007; Lussier and Halabi 2010; Cardon et al. 2011) and was only found significant in two papers of
Sorensen and Chang and Lussier and Halabi. It has been depicted as an avoidable error to prevent
failure by Cardon et al. and therefore interesting to investigate. Summed up, working experience
can be best described as general knowledge of the industry and previously working experience.
van Gelderen et al. (2006) tested the influence of part- vs. full-time and found it has a significant
influence on success. Bruno et al. (1992) found that an ineffective team is more likely to lead to
failure. Based on these two papers, we want to know in what stages commitment is important for
the success on an internet startup. Summed up, commitment resembles the state of being dedicated
to the startup.
Learnings were not directly investigated in the selected papers of section 3. But, in other literature
it has been stated by Cope (2010) that entrepreneurs learn from failure and entrepreneurs are more
prepared when they start again. We want to investigate whether entrepreneurial learning is already
important throughout the startup stages. Summed up, learning is about the acquisition of knowledge
or skills through experience and the ability to apply it.
And the last factor that hasn’t been investigated in any of the literature we saw, is pivot / adapt-
ability. It can be said it’s about decision-making (investigated by Duchesneau and Gartner (1990)),
41
but it’s about the ability to change at every stage of the internet startup life cycle where its needed.
Summed up, pivot / adaptability, the ability to change to a new direction.
Startup capability
The startup capability resembles the power of the internet startup (the firm) and the ability to change
the world. Its about the capability of solving problems and managing the execution. The defined
factors are related to the firm, the idea, and the ability to be innovative.
First, the business model / plan consists of the business plan (=planning) and model and has been
investigated in four papers (Duchesneau and Gartner 1990; Lussier and Halabi 2010; Cardon et al.
2011). Lussier and Halabi (2010) found that planning has a significant effect at successful firms,
and Cardon et al. (2011) found that a bad business model/plan is more likely to fail than a good one.
Therefore it will be interesting at what stages the business model / plan is mostly influential. Besides
this, strategy is part of it and is discovered as an influential factor on success in research.Lee and Lee
(2006) found that technology driven and market driven strategies lead to a higher chance of survival
in different stages. Song et al. (2008) found that low-cost strategy had no effect and (Duchesneau
and Gartner 1990) researched firm behaviors and strategy in general, and Li et al. (2010) found that
OP capability has a strong positive impact on firm survival and can be seen strategy. Summed up,
strategy is important factor related to the startup capability and therefore will be tested. Summed
up, the usiness model / plan consist of the way how the startup creates, delivers, and captures value.
Second, each firm have a (large) network that can influence performance. van Gelderen et al. (2006)
found that industry experience had a significant effect and they grouped this factors under network
(environment). Network can be influential at every stage of the internet life cycle and therefore is
interesting to investigate. Network can help starting firms to accelerate and is best described as a
group or system of interconnected people or things that surrounding the startup.
Third, the influence of business partners have been researched in several papers (Baum et al. 2000;
Schutjens and Wever 2000; Chang 2004; Song et al. 2008; Lussier and Halabi 2010) and found
significant important. According to Baum et al. (2000) it’s better to start with a business partner
for acceleration. Chang (2004) found that strategic alliances lead to a faster IPO. Schutjens and
42
Wever (2000) found that partnering leads to a high turnover and employee growth. And finally,
according to Song et al. (2008) R&D alliances have a heterogeneous situational effect. Based on
these findings business partners have been added to startup capability. Summed up, business partner
is a commercial entity with which you can form of alliance.
And last, staffing has been investigated Lussier and Halabi (2010) and showed no effect for success.
Although it showed no effect, we state that it plays in some internet startup stages an important role
for success. It’s important what definition of network will be used. So, staffing can be seen as the
process of hiring people (who and why).
External environment
Resources are needed in order to perform and execute, they are covered in the CISF as an external
environment factor group. This group consists of external factors that are important in relation to
the startup’s performance at the different stages of the internet startup life cycle.
Financial capital consists of startup capital, third-party capital or external capital. Startup capital
has been found of significant importance in one paper (Lasch et al. 2007) and had no effect in two
papers (Schutjens and Wever 2000; van Gelderen et al. 2006). Lasch et al. (2007) it contributed to
growth in terms of employee growth, although it most stated that the amount of capital was higher
than e75,000,-. It will be more likely be of influence at the beginning of the ISLC, than the last
stage. Third-party capital or external capital can be named financial capital and comes from ven-
ture capitalists. This factor has been researched in several papers (Duchesneau and Gartner 1990;
Bruno et al. 1992; Chang 2004; Lussier and Halabi 2010; Colombo and Grilli 2010). Duchesneau
and Gartner (1990) found that new ventures with higher levels of capitalization were more likely
to succeed. Bruno et al. (1992) found that undercapitalization and a bad relationship with the VC
leads to failure. Chang (2004) found that the reputation of VC and the more money a startup raised,
a startup’s time to IPO is shorter. And, Duchesneau and Gartner (1990) found that raised financial
capital has been found more at successful firms. And finally, Colombo and Grilli (2010) found that
the VC status has a impact on the NTBF growth. Summarized, it can’t me missed to include this
factor into the CISF, and should be interesting where entrepreneurs find this factor to be most im-
portant.
43
Different aspects of the market have been researched as factors in different studies (Duchesneau and
Gartner 1990; Bruno et al. 1992; van Gelderen et al. 2006; Lasch et al. 2007; Song et al. 2008). van
Gelderen et al. (2006) found that the risk of the market has a significant effect on a startups success.
Lasch et al. (2007) found that international market orientation leads to startup success based on the
employee’s growth performance indicator. And, Song et al. (2008) found that the market scope had
a scope homogenous positive effect for success. Three of the five papers showed a significant effect
and therefore this factor will be interesting to investigate. Only in this study it will be denominated
in one factor: the market. Market / competitors are grouped together and form a combined place of
different entities whereby parties engage in exchange.
Remarkably, only in one study Bekker et al. (2008) the influence of customers has been researched.
Although the context on the paper is slightly different, it has a high impact on the product or service
that is provided as a solution in an internet startup. We argue that the customers are crucial in some
on the stages on the ISLC. Customers refer to the people or firms that use the product or service.
And finally, the influence of the incubator has not been studied before, where rhe effect of the
factor advisors was only researched in the paper of Lussier and Halabi (2010), the descriptive
analysis showed a significant influence in successful firms. The role of an advisor is important
because in some cases there’s entrepreneurs lack experience in some cases and advisors can be
used as a startup’s reflection. Besides this, we argue that today’s incubators gained more knowl-
edge (knowhow) over the years and matured. Therefore they know what to offer, for example the
right facilities, a proper network, and a energetic environment that provide a good start for every
entrepreneur. Lots of internet success stories come out of incubators. Together, incubator / advisors
they can be formulated as support from an instance or people in order to accelerate.
The stages of the ISLC
The literature showed different studies that identified several stages of a firm. In section 3.6 the
ISLC has been described. It showed us that there’s an identifiable overlap between the different
studies. For example, the first stage is in general the same, you start building your first version
of your product or service and try to validate your customer’s need. The rest of the stages are
described in that section. Figure 1 shows that the factor groups influence the stages of the SLC. The
44
stages discovery, validation, efficiency, and scale are adapted from the tech report of Berman et al.
(2011). This recent work, existing of a huge benchmark, perfectly mirrors the current condition
of the internet startup ecosystem. Discovery can be best described as finding the customer. In
this stage startups are trying to find out who your customer is. This means answering the question
whether your solution is solving a real life problem. Besides this, they create a founding team,
conduct customer interviews, find value proposition, build a minimal viable product, join incubator,
first advisors on board, and finance it by themselves. Validation can be described as validating the
business model. In this stage startup are validating whether your users are willing to pay for your
product or service. This means developing your business model. Besides this, they are refining
core features, initiate user growth, implement metrics and analytics, get seed funding, hire first
employee, and find your product market fit. Efficiency can be best described as optimizing product
and processes. In this stage startups are optimizing the business processes and the product / service
(customer experience). This includes improving the user acquisition process. Besides this, they
refine the value proposition, improve the user experience, optimize conversion funnels, achieve
viral growth, find repeatable sales process and scalable user acquisition channels. Scale can be best
described as conquering the market. In this stage startups are accelerating very rapidly in order to
create growth aggressively. Besides this, they get a large round, start massive customer acquisition,
improve back-end scalability, hire first executive, implement processes, and establish departments.
45
4.2 Factor Definitions
Now, we have seen why its interesting to investigate these factors among the Internet Startup Life
Cycle, we need to define the factors before we continue. The factors that have been presented in the
CISF (figure 1) are described here.
Table 10: Definition of the factors used in the conceptual internet startup framework
CISF Factor DefinitionWorking experience General knowledge of the industry and previously working expe-
rienceCommitment The state of being dedicated to the startupLearning The acquisition of knowledge or skills through experience and
apply itPivot / adaptability The ability to change to a new directionBusiness model / plan The way how the startup creates, delivers, and captures valueNetwork A group or system of interconnected people or things that sur-
rounding the startupBusiness partners A commercial entity with which you can form of allianceStaffing The process of hiring people (who and why)Financial capital The amount of money raised through third-party firms (VC’s and
investors)Market / competitors A combined place of different entities whereby parties engage in
exchangeCustomers The people or firms that use the product or serviceIncubator / advisors Support from an instance or people in order to accelerate
These definitions are a collection of multiple angles. We used the papers in the reference, the
internet, and our own experience in describing each presented factor.
46
4.3 Predecessor of the CISF
As we’ve seen the CISF as it is, it was derived from an earlier constructed conceptual internet startup
framework, which is described in this section. In 1996, Belassi and Tukel (1996) developed a new
framework for determining critical success/failure factors in projects. It varied in scope and purpose.
They emphasized to the grouping of success factors and explaining the interaction between them,
rather than the identification of individual factors. After that, he conducted an empirical study to
test the practicality of the framework.
In this case we looked at a startup from a different perspective, we can say that it can be seen as a
project. Where a project normally ends, a startup continuous. And that’s where we can say that a
startup probably consists of multiple projects. You can also say it’s going into another stage of the
life cycle where other factors are important.
Belassi and Tukel (1996) developed a framework for determining critical success/failure factors in
projects (figure 2). In this thesis we’ll adapt the framework of Belassi and Tukel (1996) and map
it into the ecosystem of an internet startup in order to identify the determinants of the success of
internet startups.
Belassi grouped the factors he collected from literature into four areas: factors related to the project,
factors related to the project manager and the team members, factors related to the organization, and
factors related to the external organization. As can be seen in figure 1, these factors are interrelated.
Which means a factor in one group can influence a factor in another group, and a combination of
several factors from various groups might lead to project success or failure. Also Belassi talks about
factors vary over the different stages of the project life. Whereas for startups the same life cycle
can be depicted, it will be interesting to find out what whether factors will vary over the stages of a
startup. Now, let’s extend Belassi’s framework with the factors that influence the performance of an
internet startup (figure 2).
47
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Startup life cycle
The startup framework of Belassi’s has been extended with the startup life cycle of Steve Blanks’
Four Steps to Epiphany and is called Customer Development. It can be seen on the left side of the
framework. The four steps are:
1. Customer Discovery
2. Customer Validation
3. Company Creation
4. Company Building
Customer development is a four-step framework to discover and validate that entrepreneurs have
identified the market for their product, built the right product features that solve customers’ needs,
tested the correct methods for acquiring and converting customers, and deployed the right resources
to scale the business. The goal of step 1, Customer Discovery, is to find who the customers are and
test whether the product solves the problem for these users. The goal of step 2, Customer Validation,
is to set the sales & marketing road map and check that the market is saleable and large enough for a
viable business. The goal of step 3, Company Creation, is to build on the successes of the sales and
scale to the roadmap that has been set in the previous step. And the goal of the last step, Company
Building, is to transform into departments and operational processes are created to support scale.
On every stage of this four-step framework it’s interesting to investigate which factors are critical
for success of this stages. In this way entrepreneurs can focus on the key factors to go from stage to
stage and grow a sustainable business.
Factors related to the investors
Whereas ’Capital’ describers the amount of money that an investors brings to you, ’Resources (e.g.
Network)’ describes the secondary need of a startup, and ’Knowledge’ describes the knowhow of
the investor vs. the startup and its industry.
49
Factors related to the founders
The factor ’Compentence’ describes that a founder need a certain set of skills with which he or she
can solve any problem that occurs at hand. ’Commitment & motivation’ is a not to be missed factor
and described as the drive to keep you going and that you’ll be there when the startup needs you.
And then, ’Vision’ resembles the higher goal of the startup and is needed to lead the startup and
its team. ’Work experience’ is what is says, its the familiarity with the industry can be important.
’Constraints’ are there to be solved which describes a founder needs to be able to solve it. ’Technical
background’ describes the history of the founder with its industry. ’Decision making’ describes the
ability to make decisions where its necessary. And finally, ’Pivot / adaptability’ describes the way a
founder is able to change strategy.
Factors related to the startup
’Intellectual capital’ describes the knowhow of startup and a ’Business plan’ influences the way
in which the founder(s) see the business. It’s an initial document to help the entrepreneur answer
questions how to solve the most important parts of starting a business. Second, in this document a
’Mission & vision’ statement will be described. This must be the guidance and the goal throughout
the life cycle of the startup. Besides this, ’Strategy’ will be determined in order how to execute the
plan. Together with a solid ’Business model’ which describes the way the startup makes the money,
it are important factors for the startup. ’Market knowledge’ helps the startup with knowledge about
the people who are using your product, but also about the competitors. In order to grow, eventually,
founders need to expand their network, develop a proof-of-concept, and expand their business plan
in order to raise money. This money will be used to grow a sustainable business. ’Cooperation’
is a typical factor that is really important. You really need to get along with each other in order
to build a business. Teams with a high synergy are more likely to succeed. ’Monetization’ is
a factor that is really important and basically means how money is made with your product or
service. Entrepreneurs can build an awesome product, but eventually, a business model needs to be
in place in order to monetize it. Besides building the product, building a ’Network’ is also important,
because you need to let everybody know that you’re making this and you’ll have to communicate
your intentions, thus your vision & mission. The factor ’Costs’ the way in how a startup is spending
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money and finally ’Tools’ describes the set of hardware and software you need.
Factors related to the organization
One of the most important factors for the organization is the incubator. Mainly internet startups
consist of young people with a lack of experience and therefore incubators can couch these people
in order to build a company. Besides this, advisors surround startups in order to coach the startup.
It’s recommended for startups to find and point advisors. They’ll help you to reflect your startup
and put both legs on the ground again. Besides money, investors should also provide knowledge to
the startup, or any other kind of support. Because, this really could help startups grow. And the last
point, the organizational structure, is can be a critical factor because it shows how decision-making
is been done. If it sometimes goes to slowly, investors (or advisors) can reflect the organization
structure and start commenting it should be done differently. So, these four factors related to the
organization can all be critical factors for the success of failure of an internet startup.
Factors related to the facilitators
Whereas ’Experience’ describers the knowhow of startups and all things around it, ’Resources (e.g.
Network)’ describes the entrances to advisors, investors, etc. that a facilitators can offer, and ’Fa-
cilities’ describes the materials a startup needs in order to execute, for example an office with an
internet connection.
Factors related to the external environment
This last group consists of factors that are external to the startup, but still can have a significant
impact on the success or failure of a startup. Political, economical, social, and technological factors
can affect the progress of an internet startup at any given moment. ’Competitors’ describe what is
says and can also be either seen from a supportive view or unsupportive. Supportive in the way of
market growth, and unsupportive as in blocking you in every way they can. ’Partners’ can also be
of influence in the success or failure. Because, e.g. in some cases it’s really important to use their
product combined with your idea to create a new innovative business. And finally, ’Media attention
(e.g. Blogs)’ describe the way in which media pay attention to you and are willing to write about
you.
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Factors related to the Customert
Users (customers) are an important factor group in this framework. ’User satisfaction’ resembles the
happiness of the customer with the product or service. And ’Knowledge’ describes the knowledge
one customer has about your product or service. The ’Need’ reflects to the way the customer really
needs the product or service. And ’Contracting’ explains the way how the customer can sign up for
the product or service. And, eventually, the ’Network’ of the customer describes the way in which
the customer is about to promote the product or service to other customers.
Hypotheses
All hypotheses depicted in figure 2 are interpreted as follow: the combination of the factors in
the factor group positively influences the startup performance (the third column). E.g. the first
hypothesis (H1) states that the combination of all factors related to the investors positively influences
the founders performance. Hypotheses H2 to H14 are formulated according to these rules. Then,
the hypotheses H15 to H18 state that the combination of the factors in the group is high, the startup
is more likely to succeed.
Summary
Summed up, there are a lot of factors that can influence the success or failure rate of an internet
startup. If it’s not in this framework, we’ll have to find out in the interview whether these factors
are applicable for internet startups. This framework describes the factors and shows their relations
between each other. And, the system response shows us the effects of the factors that will lead to
success or failure.
Conclusion and further steps taken from here
Based on this work and its description we conclude that the complexity of this framework was get-
ting to high. Therefore, we decided to focus on small part of the framework with simple and already
proven factors for success and test it with entrepreneurs. The new framework (section 4.1) was based
on the experience of this framework, the interviews held with this framework (section 5), a solid
foundation of literature (section 3), and therefore a more solid thoroughly study was conducted.
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5 Results
In this section we’ll present the analyses and results. First, the interviews will be presented that were
held to validate the first framework. We’ll talk about the startup itself, the factor groups related to the
different entities and the impact of each factor, the most important factors per stage of the internet
startup life cycle, the performance of the startup, the hypotheses, and a final summation. Next, we’ll
analyze the results of the survey with descriptive statistics. Followed by the most important factors
overall and per stage. And finally, we’ll present the results of the relation between the factors and
the startup and the relation between the factors and the entrepreneur.
The interviews were held with the predecessor of the CISF where thoroughly the most important fac-
tors per factors groups and the startup performance (hypotheses in the framework) were discussed.
In this final version of the thesis, we moved these parts to the appendix (appendix D), because its
outside the scope of the current research questions.
5.1 Startup Profile - Habitissimo.es
The Founder
Before co-founding and leading the Spanish internet startup Habitissimo, Jordi Ber finished degrees
in Civil Engineering and Management. He studied Civil Engineering at the Universitat Politècnica
de Catalunya in Barcelona. Before approaching the end of first study, he had the opportunity to
study Management in Paris, where he spent three years. In the second year, he specialized in
Entrepeneurship, which was a great experience. When he came back in Barcelona he finished
Civil Engineering. And then, he tried to start something at that time, but it didn’t work out. He
decided to get a job at a construction company for some work experience. But, at some point, he
noticed that it wasn’t the job for him. By browsing the web for a career movement, he noticed there
was hardly no information on construction, and he sensed an opportunity to build some kind of a
knowledge network for this industry. He started to build something on his own. In between, he had
an opportunity to go the Massachusetts Institute of Technology for a year, where he learned more
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about IT Management. After he came back to Spain he decided to start something. He continued
working on some of his ideas, which was Construmatica, he co-founded it with the help of Grupo
Intercom. It’s a kind of wikipedia for the construction industry. The experience of Construmatica
was the school of Entrepeneurship for Jordi. Habitissimo is his second startup.
The Product
Habitissimo is an online platform that connects homeowners with prescreened and customer-rated
residential contractors, architects and interior designers. It operates in Spain with market leader
position, Italy, and Brazil and it’s expanding to other markets in Europe and Latina America. The
business model consists of companies paying for leads.
The Internet Startup Life Cycle
At the end of 2008 he co-founded Habitissimo with a partner. Because it was for him a must to find
a technical guy to found the company with. First, they did a small side project in order to get to
know each other. After successful completion they continued with their own startup, because Jordi
mentioned you actually "marry" your co-founder. Together they formed a balanced team with Jordi
as the business guy and the partner as the IT guy. With their own savings they started the adventure.
They decided to participate on the SeedRocket program. SeedRocket is a Barcelona based incubator.
In 2009, they won the first prize, got some media exposure, and got their first round of investment.
Some months later they launched their public version of the website. At this point, they survived by
bootstrapping and they were operating like the Lean Startup methodology. Meanwhile, more users
were visiting the website, they got their first paying customer, and got more media attention. By
2010 they managed to get an investment of a well known Spanish investment company. And, they
launched an Italian website to get some traction on that website. A lot was going on, but they were
struggling to really escalate the business. They tried different business models and pivot several
times. But, in 2011, they found their working business model and now they’re growing really fast.
Recently, they managed a get new investment round.
Most Important Factors per Stage
Table 11 show the factors that are really important per stage of the startup life cycle according to
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Jordi. In the beginning, it’s the customer need that is important, whereas competence is important
in the validation stage, and customer satisfaction becomes important in the efficiency stage, finally
the network of the customer helps to scale the product.
Table 11: Most important factors per stage
Discovery Validation Efficiency Scale1. Customer need 1. Competence 1. Customer satisfaction 1. Network of cust.2. Strategy 2. Business model 2. Monetization 2. Vision3. Commitment 3. Pivot / adaptability 3. Costs 3. Costs
Tips of the Founder
Jordi’s definition of success is to have a purpose and succeed in it, give back to the society, and to
be happy. And not learning anything, and being selfish leads to failure he says. The best advice he
ever got was: "Do what you think it’s right for you, not what others think is right for you. Live your
own life, be yourself." He would like to pass the following tips for other internet entrepreneurs:
• Do something you’re passionate about
• Have a purpose
• Be humble and try to learn every day to be a better entrepreneur, manager, person
Summary
Currently, Jordi places his startup in between the third and the fourth stage of the internet startup
life cycle. His startup is learning everyday and is getting more mature. The expansions to Italy and
Brazil were some wise lessons, and they realized that they had to optimize their business model and
create traction in the market. Although it was not easy to find their business model, they found it.
With new money, they’re able to accelerate more and conquer the market.
One mistake they made is surviving without selling. Customers don’t fall from the sky, you really
have to create a good value proposition. Implementing KPI’s from the start help to keep on track,
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and also talk to customers as soon as possible. Commitment is also critical to a startup and was one
of the things he learned, because you need to be committed in order to succeed.
5.2 Startup Profile - GuideGuide.com
The Founder
Christof Damian is from Germany. After finishing high school he started studying computer science
at the university, this was in 1995. At that time there was no internet, but he noticed a trend in which
he wanted to participate. His study was very theoretical, it was more about mathematics and physics
instead of programming, what he wanted to do and was doing in his spare time. He decided to stop
his study, and one or two years later he had the opportunity to go to London to help a friend with
his web agency. At that time they were not happy with their project based assignments and decided
they wanted to make a product which they can sell. With his friend as the business guy and Christof
as the IT guy, they founded GuideGuide.com in 1999.
The Product
GuideGuide helps restaurants and other companies to build a website and attract new customers via
the internet. They’re targeting the German market. Restaurants pay a setup fee and a monthly fee to
host their website. Besides this, a portal of all restaurants was created and sponsored by a company
related that sold goods to restaurants.
The Internet Startup Life Cycle
In 1999 they started the development of the product. After a couple of months, they allowed some
restaurants to test their product via their network. Slowly they acquired more restaurants to the
portal. After a year the portal was sponsored by a company that sold goods to restaurants. During
this period, the startup was financed by own savings, friends, and family. The development was
done in the UK, and a secondary office was setup in Germany for Sales, Marketing, and Customer
Support. They stayed in London for development, because they believed the knowledge was better
in London and designers and developers were better skilled and more easy to find. Most of the
money came in from the sponsorship, and they decided to target other markets like barbershops and
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construction companies where big consumer product companies could sponsor. In a few years, they
grew to 18 developers in London and 60 people in Germany. Around 2003, the bubble exploded,
the business collapsed, people were fired, and they shrank from 80 to 25 people in a short period.
There was a big distrust in the internet and companies were holding back on internet investments.
In the UK firing people was easy, but in Germany employees had better arrangements and it cost
GuideGuide a lot of money for to fire the people. During that time, they hired a new CEO, but soon
they realized it didn’t worked and he left. After that, his partner left the company and the father of
the partner took over. They company was in maintenance mode, there was no new development. By
2004, there were no employees left in London and they closed the office. Before the company went
bankrupt in 2006, Christof left the company and moved to Barcelona. The company was bought by
another company without debts and is still running today.
Most Important Factors per Stage
Christof prioritized the most important factors per stage (table 12). In the beginning, the vision
is most important. Christof really believes that you can accomplish anything with a good vision.
Then, commitment becomes important, and with capital you can grow and scale.
Table 12: Most important factors per stage
Discovery Validation Efficiency Scale1. Vision 1. Commitment 1. Capital 1. Capital2. Motivation 2. Soc. & tech. environ. 2. Motivation 2. Business model3. Network 3. Network 3. User satisfaction 3. Tech. background
Tips of the Founder
According to Chrstiof, success is defined as continuous growth of the company. And failure is when
the company shrinks or when you can’t implement your business model. The best thing you can do
is to try to start the company without investment money, e.g. start with a bank loan. Besides this,
Christof wants to say the following tips for other internet entrepreneurs:
• Don’t get investment money
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• Don’t plan too far in the future
• Don’t care about the competition
Summary
GuideGuide.com was born at the beginning of the internet era. A lot of people and companies saw
huge opportunities with the internet and companies rise very rapidly before the bubble exploded.
GuideGuide is one example that went bankrupt. Where everything was going fine, and money was
easily found, they couldn’t survive the crash due to sticky contracts of the employees in Germany.
Although it was not easy for Christof, he learned a lot during this period. The most important thing
is the vision and motivation of the founders. Everything else doesn’t really matter. If you really
want something, you can do it. Whereas most people see possibilities in terms of money, according
to Christof it isn’t about money, it’s all about the vision.
5.3 Startup Profile - ChangeYourFlight.com
The Founder
Jose Luis Vilar is 31 years old and co-founder of ChangeYourFlight.com. After completing his study
in Industrial Engineering, he switched to Design. He did a Post Graduate and Master in Design.
First, he worked as a engineer, and later he worked as business consultant and gained experience
in disciplines like marketing, innovation, management consulting and strategy. For some time he
worked for Renault in Paris, and later he worked in Barcelona for a big consultancy company.
The Product
ChangeYourFlight.com is an online platform allowing air travelers to recover part of the money
spent on a ticket that they will not be using to fly. Users get a voucher of the same airline to spent
another time. At the point of transaction, ChangeYourFlight gets a small commission.
The Internet Startup Life Cycle
Jose Luis and his co-founder met each other in Paris and they were brainstorming about several
ideas. After splitting up, they organized a meet up in Paris and suffered a problem. Everything
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was arranged, but suddenly some friends had to cancel a week before, and they ended up together,
and this was where the idea was born. The basic idea was getting rid of the ticket and getting part
of the money back. At first it was a side project by developing the idea. They invested a lot of
time and a year later, in 2010, Jose Luis quit his job and they incorporate the company. At some
point a third founder decided not to go along. So, it was up to Jose Luis and his partner to start up.
Getting to know the airline industry and building a network were the first primary tasks they had to
do. In the first year they worked on confidence and credibility towards the airlines and build a solid
network. Getting influential people of the industry on board was their strategy in order to build such
a network. In the first year it was not clear what the business model was, and with some changes
and advice they managed to find it. The key success of the business model was finding added value
for both the passenger and the airline company. At the beginning they financed the startup their self
in order to develop the commercial pitch, develop mockups, building the network, etc. The first
development was outsourced, but unfortunately it didn’t work. So, they learned from their mistake
and they decided to do it in-house and hired an IT guy. But, he was not motivated and involved
enough, so, this also didn’t work out. After a while they decided to really invest and found a CTO
and at the end of 2011 they engaged him in the company. In between, at the beginning of 2011, they
managed to get a bank loan, they joined Barcelona Activa, and the first airline engaged. Recently,
they managed to get a new investment in order to accelerate.
Most Important Factors per Stage
Table 13 show the factors that are really important per stage of the startup life cycle according to
Jose Luis. In the beginning, the customer need is most important, then then the ability to pivot
becomes important, and finally you’ll need capital to optimize processes and scale.
Table 13: Most important factors per stage
Discovery Validation Efficiency Scale1. Customer need 1. Pivot / adaptability 1. Capital 1. Capital2. Network 2. Customer satisfaction 2. Network 2. Vision3. Pivot / adaptability 3. Media attention 3. Market knowledge 3. Network of cost.
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Tips of the Founder
Jose Luis definition of success is "reaching your objectives". His definition of failure has multiple
angles, namely "attempt, not focus or when you quit". The best advice he ever got was "Think as a
rich man, spend as a poor man". If he would do it again, he would focus and execute rapidly. He
would like to pass the following tips to other internet entrepreneurs:
• Impossible is nothing, there are a lot of things you don’t know but only a few you cannot
learn
• Fail, but fail fast and learn from the past mistakes
• There is no plan B (side projects or secure jobs) just do it!
Summary
ChangeYourFlight is solving a real life problem as they discovered it on their own. They were
moving slowly in order to validate their customer and their business model. Next to it, they were
unfamiliar with the industry, they read some books, and were constantly networking until they got
more body. It was their strategy to create an advisory board. It’s remarkable that they were capable
of convincing people with a sheet of paper, because in the beginning they had no working prototype,
mockups that did the trick.
The hardest struggle they had to overcome was to hire the right IT guy. As they were strong and
complementary on the business side, they missed another co-founder. Eventually, they invested in
finding the right guy by engaging him in the company. They found it hard to find support in terms
of IT of the facilitators, now its easy for developers to find support on how to start a business, but
for business guys its not easy to find support in order to create an application.
In the end, they managed to do it, and with new money on board they’re able to accelerate. And in
the end its all about conniving the other guy.
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5.4 Startup Profile - Teambox.com
The Founder
Pablo is 26 years old and the founder of teambox.com. He studied Aerospace Engineering in
Madrid. He starting coding when he was 15, he got inspired by his father to start building his
own game and he thought: "Why not?". During his studies he developed a platform for students
to prepare themselves for exams and it helped a lot of students, and some point he sold it. After
that, he started some other companies, but it didn’t really worked out. At some point, he had the
opportunity to go to the USA, and when he came back he joined Barcelona Activa to start working
on his own project, Teambox.com.
The Product
Teambox is a collaboration platform in the cloud. They enable users to collaborate, share files and
manage tasks. They are changing the way people work by making it easier and fun to get things
done. From 5 users or more, people or companies pay for the service.
The Internet Startup Life Cycle
In the end of 2008 Pablo started working on his on project, a collaboration tool. Then, in 2009,
he got some advice of an acquaintance about the product which he welcomed and it even led to an
initial investment (seed money). From this point on Pablo started full-time developing on Teambox.
Nine months later he was ready to launch his product, meanwhile he got some media attention and
grew from no users to a couple of thousand users. In September 2011 he brought in a CEO from
the United States, because he simply wanted to focus oo the product, and not being busy with other
stuff. They made some changes, like the pricing model and the positioning in the market, and now
they’re really accelerating their business.
Most Important Factors per Stage
Table 14 show the factors that are really important per stage of the startup life cycle according to
Pablo. In the beginning, the customer need is most important, then capital becomes important, and
then you start to monetize, and again you’ll need capital to scale.
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Table 14: Most important factors per stage
Discovery Validation Efficiency Scale1. Customer need 1. Capital 1. Monetization 1. Capital2. Business model 2. Complementary team 2. Partnerships 2. Work experience3. Experience of fac. 3. User satisfaction 3. Competitors 3. Media attention
Tips of the Founder
Pablo’s definition of success is "creating a product that is self sustainable, profitable, and innovative
in some sector". His definition of failure is "falling to grow because of some threshold". has multiple
angles, namely "attempt, not focus or when you quit". Next to implementing metrics in the early
stages, he would like to pass the tips to fellow internet entrepreneurs:
• Start today
• Hire slow, and fire fast
• No one knows better than you
Summary
Pablo is a real entrepreneur and a product minded guy. He founded teambox on his own and the
startup is becoming the leader in terms of collaboration software worldwide. In a couple of years
he established a great startup with focus. His DNA can be found throughout the company.
With his 3rd startup he keeps on learning everyday. The smartest thing he did, was hiring the CEO
and focus on the product. He’s open for every suggestion to get better and grow.
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5.5 Startup Profiles - Qualitative Analysis
In order to determine the most important factors in the startup life cycle, qualitative data has been
gathered from four interviews (sections 5.1, 5.2, 5.3, and 5.4). The interviewees were asked to
prioritize the most important factors (independent variables) in each of the startup life cycle stages
from which we can derive propositions that can be tested with a larger population. The interviews
were held with the predecessor of the conceptual internet startup framework (first) from which we
derived the conceptual internet startup framework (second). So, in order to derive the propositions,
we need to map the factors from the first to the second framework in order to derive propositions
with the most important factors per stage. The mapping is shown in table 15.
Table 15: Mapping of factors to the CISF
Case 1: Habitisimo.esDiscovery Validation Efficiency Scale
factors depicted in the predecessor of the CISF (figure 2)1. Customer need2. Strategy3. Commitment
1. Competence2. Business model3. Pivot / adaptability
1. Customer satisfaction2. Monetization3. Costs
1. Network (customer)2. Vision3. Costs
factors depicted in the CISF (figure 1)1. Customers2. Business model / plan3. Commitment
1. Pivot / adaptability2. Business model / plan3. Working experience
1. Customers2. Business model / plan3. Financial capital
1. Customers2. Business model / plan3. Financial capital
Case 2: GuideGuide.comDiscovery Validation Efficiency Scale
factors depicted in the predecessor of the CISF (figure 2)1. Vision2. Motivation3. Network
1. Commitment2. Soc. & tech. environ.3. Network
1. Capital2. Motivation3. User satisfaction
1. Capital2. Business model3. Tech. background
factors depicted in the CISF (figure 1)1. Business model / plan2. Commitment3. Network
1. Commitment2. Market / competitors3. Network
1. Financial capital2. Commitment3. Customers
1. Financial capital2. Business model / plan3. Work experience
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Case 3: ChangeYourFlight.comDiscovery Validation Efficiency Scale
factors depicted in the predecessor of the CISF (figure 2)1. Customer need2. Network3. Pivot / adaptability
1. Pivot / adaptability2. Customer satisfaction3. Media exposure
1. Capital2. Network3. Market knowledge
1. Capital2. Vision3. Awareness
factors depicted in the CISF (figure 1)1. Customers2. Network3. Pivot / adaptability
1. Pivot / adaptability2. Customers3. Network
1. Financial capital2. Network3. Market / competitors
1. Financial capital2. Business model / plan3. Customers
Case 4: Teamwork.comDiscovery Validation Efficiency Scale
factors depicted in the predecessor of the CISF (figure 2)1. Customer need2. Business model3. Exp. of facilitator
1. Capital2. Complementary team3. User satisfaction
1. Monetization2. Partnerships3. Competitors
1. Capital2. Work experience3. Media attention
factors depicted in the CISF (figure 1)1. Customers2. Business model / plan3. Incubator / advisors
1. Financial capital2. Commitment3. Customers
1. Business model / planBusiness partners3. Competitors
1. Financial capital2. Work experience3. Network
The mapping needed to be done in order to distinguish the most important factors according to the
interviewees and construct a proper online survey. They had the opportunity to choose from all
factors presented in the predecessor of the conceptual internet startup framework (figure 2). Then,
we mapped these into the conceptual internet startup framework (figure 1), which has been done in
table 15. The numbers depicted in the figure can be explained as: 1 stands for the most important
factor, 2 stands for the second most important factor, and 3 stands for the third most important
factor. Now, we are going to weight each factor with values, the most important factor (#1) gets 3
points, the second most important factor (#2) gets 3 points, and the third most important factor (#3)
gets 1 point. Then, we add up the numbers and the scores are depicted in table 16. Now, with these
findings we can formulate propositions and test these with an online survey.
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Table 16: Total scores of all factors in all stages (n=4)
Discovery Validation Efficiency ScaleWorking experience 0 1 0 3Commitment 3 5 2 0Learning 0 0 0 0Pivot / adaptability 0 6 * 0 0Business model / plan 8 2 5 6Network 3 2 2 1Business partners 0 0 2 0Staffing 0 0 0 0Financial capital 0 3 7 * 10 *Market / competitors 0 2 2 0Customers 9 * 3 4 4Incubator / advisors 1 0 0 0
*) highest score
The table tells us that in the discovery stage the factor customers is most important, in the validation
stage the factor pivot / adaptability is most important, in the efficiency stage the factor financial
capital is most important, and in the scale stage also the factor financial capital is important. Now,
we introduce the following propositions:
Proposition 1a: The factor customers is most important in the discovery stage
This relates to the need of the customers which was mentioned often by the interviewees. When
you’re solving a problem, it’s important to connect the need of the customer to the solution. We’ve
to say that this factor was closely followed by the factor business model / plan which includes the
vision, strategy, and more. Because, it was often said that you need a clear vision, an outlined
strategy, and a solid business model in order to start your business.
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Proposition 1b: The factor pivot / adaptability is most important in the validation stage
Whereas the factor pivot / adaptability has the highest score, it is closely followed by the factor
commitment. One of the interviewees was following the Lean Startup methodology at this stage,
where its common to pivot in order to find a working business model. Commitment comes second
and is also mentioned often in the interviews.
Proposition 1c: The factor financial capital is most important in the efficiency stage
In the stage of optimizing your product and processes it’s about all about money. The interviewees
told us that capital is needed when you want to grow, because in most cases they had a proven
concept with a working business model, the only way to accelerate is to get a large investment
round.
Proposition 1d: The factor financial capital is most important in the scale stage
With scaling the entrepreneurs want to grow and establish a real company. It doesn’t surprise us
that the factor financial capital is prioritized as the most important one. You need capital to hire the
best people, start large marketing campaigns, and so on.
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5.6 Online Survey
With the validation of the conceptual internet startup framework we derived four propositions to test
and in order to answer our research question we conducted an online survey to test the propositions
of the previous section. The survey was created with QuestionPro (www.questionpro.com), an on-
line survey facilitator. The overall questionnaire included both open and multiple choice questions
and existed of six parts (appendix E), namely:
1. Discovery - finding the customer
2. Validation - validation the business model
3. Efficiency - optimizing product and processes
4. Scale - conquering the market
5. Startup profile
6. Profile of the entrepreneur
In the first four parts of the survey a rating scale was used to determine what the most important
factors in each of the stages. On a Likert scale from 1-5 entrepreneurs had to value each factor as 1)
unimportant to 5) very important in the relation to the stage. This scale was chosen in order to create
a survey that was a) understandable, b) easy to fill out and c) that could be done within a reasonable
time. We’ll perform a quantitative analysis in order to test what the most important factors are in
each stage (section 5.7).
Another thing we want to analyze are how the factors differ over time which relates to answering
the first research subquestion (section 2.3). Do they become more important or less important?
Therefore, in section 5.8 we’ll analyze differences between factors over time.
The fifth part was constructed in order to create several startup profiles based on different charac-
teristics. Entrepreneurs were asked a) if they could define their startup as a success, failure, or still
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undecided; b) at what stage of the startup life cycle they were in; c) how large the founding team
was; d) if the founding team more business centric or more technical centric was; e) how many
employees the startup has; f) if the product was targeting a consumer or an enterprise market; g) if
the product is targeting a local, regional, national, or international market; h) where the startup is
located; and finally i) when the startup was founded. Later on, we’ll analyze the survey and identify
differences in between the factors and the characteristics of the startup (ssection 5.10).
And, the last part of the survey consisted of the profile of the entrepreneur where a) the gender of
the entrepreneur was asked, b) the age of the entrepreneur was asked, and c) what the highest level
of education was achieved. We’ll analyze the results and try to identify differences in between the
factors and the characteristics of the entrepreneur (section 5.11).
The survey has been spread through e-mail to 55 entrepreneurs in our personal network. Also, eleven
incubators were formerly approached by e-mail and asked to send an e-mail to all entrepreneurs.
Two of the incubators were located in Barcelona and two were located in Utrecht, namely Nether-
ware and UtrechtInc. Next to this, 57 startups were dropped an ’cold’ e-mail at their info@[name-
of-the-startup.ext] address with a formal approach whether they could help us. And finally, we
approached entrepreneurs through five online groups that consisted of internet entrepreneurs.
Statistics of QuestionPro showed that the survey had been viewed by 432 people, of whom 172
people started, and of whom 48 people completed the survey. This resulted in 124 drop outs (after
starting) and a completion rate of 27.91%. The average time to complete the survey was 10 minutes.
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5.7 Most Important Factors Per Stage - Quantitative Analysis
5.7.1 Descriptive Statistics
Now, we will examine the results of the online survey. Let us first define the independent variables:
• Independent variables: Working experience, Commitment, Learning, Pivot / adaptability,
Business model / plan, Network, Business partners, Staffing, Financial capital, Market / com-
petitors, Customers, Incubator / advisors
The interviews gave us insight of the factors that were most important in the stages of the startup
life cycle. With the results, we derived four propositions (Section 5.5) that we want to test with the
results of our survey. First, we translate these formulated propositions into the following hypotheses:
H1: The factor customers is among the most important factors in the discovery stage
H2: The factor pivot / adaptability is among most important factors in the validation stage
H3: The factor financial capital is among most important factors in the efficiency stage
H4: The factor financial capital is among most important factors in the scale stage
In the first four parts of the survey we asked respondents to estimate each factor in terms of impor-
tance in each stage of the internet startup life cycle. Table 17 show the descriptive statistics of the
factors in each stage. The mean and the standard deviation are shown.
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Table 17: Descriptive statistics (n=48)
DiscoveryMean (S.D.)
ValidationMean (S.D.)
EfficiencyMean (S.D.)
ScaleMean (S.D.)
Working experience 3.15 (.90) 3.52 (.77) 3.77 (.69) 4.19 (.73)Commitment 4.56 (.54) * 4.46 (.68) * 4.44 (.68) 4.50 (.68)Learning 4.40 (.80) 4.27 (.74) 4.27 (.77) 3.94 (.81)Pivot / adaptability 4.44 (.62) 4.08 (.90) 3.73 (.96) 3.27 (1.05)Business model / plan 3.10 (.97) 3.67 (1.08) 3.46 (.94) 3.83 (.95)Network 3.85 (.80) 3.87 (.82) 3.62 (.96) 4.15 (.90)Business partners 3.13 (1.02) 3.56 (1.07) 3.75 (.91) 4.33 (.88)Staffing 2.75 (1.21) 3.38 (1.00) 3.79 (.90) 4.44 (.62)Financial capital 2.71 (1.27) 3.15 (.95) 3.44 (.85) 4.58 (.61) *Market / competitors 2.90 (1.04) 3.50 (.90) 3.54 (.92) 3.67 (.75)Customers 3.79 (1.11) 4.19 (.96) 4.52 (.62) * 4.19 (.82)Incubator / advisors 2.77 (.93) 3.19 (.92) 3.06 (.89) 2.85 (1.07)
*) highest mean
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Commitment seems to be the most important factor in the discovery and the validation stage. In the
efficiency stage, the factor customers seems to be the most important one. And in the last stage, the
factor financial capital seems to be the most important one. We use a Paired Samples Test in order
to test the significance of the differences on the mean scores. Before we continue, we performed a
Reliability Analysis with the data of table 17 and the 48 items showed us a alpha coefficient of .820,
suggesting that the items have relatively high internal consistency.
Now, we’re going to look at the four hypothesis (Hx) in which we state that each stage has a factor
that is among the important factors in that stage. If this factor also has the highest mean we continue
to test this hypothesis. If not, we take the factor with the highest mean and derive a new hypothesis
(Hx’) and start testing whether this factor is significantly higher than all other factors. If so, we can
conclude that this factor is the most important in that stage and accept the hypothesis. If not, than
we’ll do further analysis and we’ll grab the first two factors with the highest means and derive a new
hypothesis (Hx”) and test this hypothesis and see whether these two factors are significantly higher
than all other factors. If true, the hypothesis is accepted and we conclude that these two factors
are significant important in this stage. If not, we continue, but now we take the first three factors
with the highest means and derive a new hypothesis (Hx”’) and test whether these three factors are
significantly higher than all other factors. If true, we accept the hypothesis and conclude that these
three factors are the most important in that stage. If not, we continue this approach until we find
the most important factors. In the case if we’ve to reject all (derived) hypothesis, than it needs to be
concluded that there are no significant factors in that stage.
When this approach has ended, we take a look back at the first hypothesis that we formulated at the
beginning and see if this factor is among the most important factors. If so, we conclude that this
hypothesis (Hx) can be accepted. If not, the hypothesis needs to be rejected.
5.7.2 Most Important Factors in the Discovery Stage
In the discovery stage it has been noticed that the factor commitment seems to be the more important
than the factor customers, but still we can’t reject H1. Because of the higher mean we derive a new
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hypothesis:
H1’: The factor commitment is among the most important factors in the discovery stage
Now, we are going to test if the factor commitment is significantly higher than all other factors. The
Paired Samples Test is used to compare the means between the factor commitment and all other
factors. The results are depicted in table 18.
Table 18: Paired Samples Test for the factor commitment with all factors in the discovery stage(n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. A_COMMIT-A_WOREXP 1.417 .919 .133 10.684 47 .000Pair 2. A_COMMIT-A_LEARNN .167 .859 .124 1.345 47 .185Pair 3. A_COMMIT-A_PIVOTA .125 .789 .114 1.098 47 .278Pair 4. A_COMMIT-A_BMOPLN 1.458 1.091 .157 9.263 47 .000Pair 5. A_COMMIT-A_NETWRK .708 1.051 .152 4.669 47 .000Pair 6. A_COMMIT-A_BUSPAR 1.438 1.201 .173 8.291 47 .000Pair 7. A_COMMIT-A_STAFFN 1.813 1.214 .175 10.341 47 .000Pair 8. A_COMMIT-A_FINCAP 1.854 1.271 .184 10.103 47 .000Pair 9. A_COMMIT-A_MARKET 1.667 1.226 .177 9.417 47 .000Pair 10. A_COMMIT-A_CUSTOM .771 1.242 .179 4.301 47 .000Pair 11. A_COMMIT-A_INCUBA 1.792 1.010 .146 12.294 47 .000
From the statistical results, the factor commitment is not significantly higher than all other factors
with p<.05, the factors learning and pivot / adaptability didn’t show a significant difference. There-
fore we reject reject H1’ and we grab the first two factors with the highest means from table 17 and
test whether these two factors are significantly higher than the other factors. The factors commit-
ment and pivot / adaptability are the factors with the highest means with respectively 4.56 and 4.44.
Now, we derive the following hypothesis:
H1”: The factors commitment and pivot / adaptability are among the most important factors
in the discovery stage
The statistical results show that the factors commitment and pivot / adaptability are not higher than
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all other factors with p<0.05, the factor learning didn’t show a significant difference (table 18 and
table 65 in appendix F.1). Therefore we reject H1” and continue, but now we grab the first three
factors with the highest means from table 17 and test whether these three factors are significantly
higher than the other factors. The factors commitment, pivot / adaptability, and learning are the
factors with the highest means with respectively 4.56, 4.44, and 4.40. Now, we derive the following
hypothesis:
H1”’: The factors commitment, pivot / adaptability, and learning are among the most impor-
tant factors in the discovery stage
The statistical results show that the factors commitment, pivot / adaptability, and learning are higher
than all other factors with p<0.05, therefore we accept H1”’ and it can be concluded that these
factors are the most important factors in the discovery stage. Our original hypothesis states that the
factor customers is among the most important factors, we just found that its not, so we reject H1.
5.7.3 Most Important Factors in the Validation Stage
In the validation stage it has been noticed that the factor commitment seems to be the more important
than the factor pivot / adaptability, but still we can’t reject H2. Because of the higher mean we derive
a new hypothesis:
H2’: The factor commitment is among the most important factors in the validation stage
Now, we are going to test if the factor commitment is significantly higher than all other factors. The
Paired Samples Test is used to compare the means between the factor commitment and all other
factors. The results are depicted in table 19.
From the statistical results, the factor commitment is not significantly higher than all other factors
with p<0.05, the factors learning and customers didn’t show a significant difference. Therefore, we
reject H2’ and grab the firs two factors with the highest means from table 17 and test whether these
two factors are significantly higher than the other factors. The factors commitment and learning are
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Table 19: Paired Samples Test for the most important factor in the validation stage (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1 - B_COMMIT-B_WOREXP .937 .976 .141 6.652 47 .000Pair 2 - B_COMMIT-B_LEARNN .188 .816 .118 1.592 47 .118Pair 3 - B_COMMIT-B_PIVOTA .375 .959 .138 2.708 47 .009Pair 4 - B_COMMIT-B_BMOPLN .792 1.320 .191 4.155 47 .000Pair 5 - B_COMMIT-B_NETWRK .583 1.108 .160 3.649 47 .001Pair 6 - B_COMMIT-B_BUSPAR .896 1.292 .187 4.803 47 .000Pair 7 - B_COMMIT-B_STAFFN 1.083 1.069 .154 7.024 47 .000Pair 8 - B_COMMIT-B_FINCAP 1.312 1.095 .158 8.037 47 .000Pair 9 - B_COMMIT-B_MARKET .958 1.220 .176 5.444 47 .000Pair 10 - B_COMMIT-B_CUSTOM .271 1.180 .170 1.590 47 .119Pair 11 - B_COMMIT-B_INCUBA 1.271 1.125 .162 7.827 47 .000
the factors with the highest means with respectively 4.46 and 4.27. Now, we derive the following
hypothesis:
H2”: The factors commitment and learning are among the most important factors in the
validation stage
The statistical results show that the factors commitment and learning are not higher than all other
factors with p<0.05, the factors customers and pivot / adaptability didn’t show a significant differ-
ence (table 19; table 67 in appendix F.2). Therefore we reject H2” and continue, but now we grab
the first three factors with the highest means from table 17 and test whether these three factors are
significantly higher than the other factors. The factors commitment, learning, and customers are the
factors with the highest means with respectively 4.46, 4.27, and 4.19. Now, we derive the following
hypothesis:
H2”’: The factors commitment, learning, and customers are among the most important fac-
tors in the validation stage
The statistical results show that the factors commitment, learning and customers are not higher than
all other factors with p<0.05, the factor pivot / adaptability didn’t show a significant difference
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(table 19; tables 67 and 68 in appendix F.2). Therefore we reject H2”’ and continue, but now we
grab the first four factors with the highest means from table 17 and test whether these four factors
are significantly higher than the other factors. The factors commitment, learning, customers, and
pivot / adaptability are the factors with the highest means with respectively 4.46, 4.27, 4.19, and
4.08. Now, we derive the following hypothesis:
H2””: The factors commitment, learning, customers, and pivot / adaptability are among the
most important factors in the validation stage
The statistical results show that the factors commitment, learning, customers, and pivot / adaptabil-
ity are not higher than all other factors with p<0.05, (table 19; tables 67, 68 and 69 in appendix F.2),
therefore we reject H2””. From this point, we continued analyzing and found that all factors are sig-
nificantly important (tables 70, 71, 72, 73, 74, 75, 76 and 77 in appendix F.2). There’s no significant
factor that is most important, therefore we reject H2 and conclude that are no significant factors that
are most important.
5.7.4 Most Important Factors in the Efficiency Stage
In the efficiency stage it has been noticed that the factor customers seems to be the more important
than the factor financial capital and therefore, but still we can’t reject H3. Because of the higher
mean we derive a new hypothesis:
H3’: The factor customers is among the most important factors in the efficiency stage
Now, we are going to test if the factor customers is significantly higher than all other factors. The
Paired Samples Test is used to compare the means between the factor customers and all other factors.
The results are depicted in Table 20.
From the statistical results, the factor customers is not significantly higher than all other factors
with p<0.05, the factors commitment and learning didn’t show a significant difference. Therefore
we reject H3’ and we grab the first two factors with the highest means from table 17 and test
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Table 20: Paired Samples Test for the most important factor in the efficiency stage (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1 - C_CUSTOM-C_WOREXP .750 .887 .128 5.856 47 .000Pair 2 - C_CUSTOM-C_COMMIT .083 .871 .126 .663 47 .511Pair 3 - C_CUSTOM-C_LEARNN .250 .957 .138 1.811 47 .077Pair 4 - C_CUSTOM-C_PIVOTA .792 1.166 .168 4.703 47 .000Pair 5 - C_CUSTOM-C_BMOPLN 1.062 1.119 .161 6.581 47 .000Pair 6 - C_CUSTOM-C_NETWRK .896 .951 .137 6.528 47 .000Pair 7 - C_CUSTOM-C_BUSPAR .771 .928 .134 5.755 47 .000Pair 8 - C_CUSTOM-C_STAFFN .729 1.047 .151 4.827 47 .000Pair 9 - C_CUSTOM-C_FINCAP 1.083 .942 .136 7.971 47 .000Pair 10 - C_CUSTOM-C_MARKET .979 .887 .128 7.468 47 .000Pair 11 - C_CUSTOM-C_INCUBA 1.458 .849 .123 11.894 47 .000
whether these two factors are significantly higher than the other factors. The factors customers and
commitment are the factors with the highest means with respectively 4.52 and 4.44. Now, we derive
the following hypothesis:
H3”: The factors customers and commitment are among the most important factors in the
efficiency stage
The statistical results show that the factors customers and commitment are not higher than all other
factors with p<0.05, the factor learning didn’t show a significant difference (table 20; table 78
in appendix F.3). Therefore we reject H3” and we grab the first three factors with the highest
means from table 17 and test whether these three factors are significantly higher than the other
factors. The factors customers, commitment, and learning are the factors with the highest means
with respectively 4.52, 4.44, and 4.27. Now, we derive the following hypothesis:
H3”’: The factors customers, commitment, and learning are among the most important fac-
tors in the efficiency stage
The statistical results show that the factors customers, commitment, and learning are higher than
all other factors with p<0.05 (table 20; table 78 and 79 in appendix F.3), therefore we accept H3”’
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and it can be concluded that these factors are the most important factors in the efficiency stage. Our
original hypothesis states that the factor financial capital is among the most important factors, we
just found that its not, so we reject H3.
5.7.5 Most Important Factors in the Scale Stage
In the scale stage it has been noticed that the factor financial capital seems to be most important.
But, still we can not accept hypothesis H4. First, we are going to test if the factor financial capital
is significantly higher than all other factors. The Paired Samples Test is used to compare the means
between the factor financial capital and all other factors. The results are depicted in Table 21.
Table 21: Paired Samples Test for the most important factor in the efficiency stage (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1 - D_FINCAP-D_WOREXP .396 .939 .136 2.919 47 .005Pair 2 - D_FINCAP-D_COMMIT .083 .767 .111 .753 47 .455Pair 3 - D_FINCAP-D_LEARNN .646 .934 .135 4.792 47 .000Pair 4 - D_FINCAP-D_PIVOTA 1.312 1.114 .161 8.164 47 .000Pair 5 - D_FINCAP-D_BMOPLN .750 1.062 .153 4.893 47 .000Pair 6 - D_FINCAP-D_NETWRK .438 1.029 .149 2.944 47 .005Pair 7 - D_FINCAP-D_BUSPAR .250 1.042 .150 1.663 47 .103Pair 8 - D_FINCAP-D_STAFFN .146 .799 .115 1.265 47 .212Pair 9 - D_FINCAP-D_MARKET .917 .964 .139 6.589 47 .000Pair 10 - D_FINCAP-D_CUSTOM .396 .869 .125 3.156 47 .003Pair 11 - D_FINCAP-D_INCUBA 1.729 1.086 .157 11.027 47 .000
From the statistical results, the factor financial capital is not significantly higher than all other fac-
tors with p<0.05, the factors commitment, business partners and staffing didn’t show a significant
difference. Therefore we reject H4 and we grab the first two factors with the highest means from
table 17 and test whether these two factors are significantly higher than the other factors. The factors
financial capital and commitment are the factors with the highest means with respectively 4.58 and
4.50. Now, we derive the following hypothesis:
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H4’: The factors financial capital and commitment are among the most important factors in
the scale stage
The statistical results show that the factors financial and commitment are not higher than all other
factors with p<0.05, the factor learning didn’t show a significant difference (table 21; table 80 in
appendix F.4). Therefore we reject H4’ and we grab the first three factors with the highest means
from table 17 and test whether these three factors are significantly higher than the other factors.
The factors financial capital, commitment, and staffing are the factors with the highest means with
respectively 4.58, 4.50, and 4.44. Now, we derive the following hypothesis:
H4”: The factors financial capital, commitment, and staffing are among the most important
factors in the scale stage
The statistical results show that the factors financial, commitment, and staffing are not higher than
all other factors with p<0.05, the factors working experience network, and business partners didn’t
show a significant difference with these factors (table 21; tables 80 and 81 in appendix F.4). There-
fore we reject H4” and we grab the first four factors with the highest means from table 17 and
test whether these fours factors are significantly higher than the other factors. The factors financial
capital, commitment, staffing, and business partners are the factors with the highest means with
respectively 4.58, 4.50, 4.44, and 4.33. Now, we derive the following hypothesis:
H4”’: The factors financial capital, commitment, staffing, and business partners are among
the most important factors in the scale stage
The statistical results show that the factors financial capital, commitment, staffing, and business
partners are not higher than all other factors with p<0.05 (table 21; table 80, 81, and 82 in ap-
pendix F.4), therefore we reject H4”’. From this point, we continued analyzing and found that all
factors are significantly important (tables 83, 84, 85, 86, 87, and 88 in appendix F.4), expect the
factors pivot / adaptability (table 89) and incubator / advisors (table 90). These last two factors
also showed a significant different, so, it can be concluded that the factor incubator / advisors is
least important, then the factor pivot / adaptability is least important and the other ten factors are
equally important. Therefore we can accept H4 and conclude that financial capital is among the
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most important factors in the scale stage.
5.7.6 Summary
The research question (section 2.3) can now be answered based on the analysis of the previous
sections. The research question was:
What are the most important factors among the stages of the internet startup life cycle?
From the interviews four propositions were derived and translated into hypothesis and quantitatively
tested with the online survey. Respondents were asked to value each factor on a 1-5 point Likert
scale in each stage of the startup life cycle.
H1: The factor customers is among the most important factors in the discovery stage
H2: The factor pivot / adaptability is among most important factors in the validation stage
H3: The factor financial capital is among most important factors in the efficiency stage
H4 The factor financial capital is among most important factors in the scale stage
Whereas H1, H2, and H3 were rejected, only H4 was accepted. Further analyses showed other
significant important factors among the stages and the findings are depicted in table 22 and answers
our main research question.
Table 22: Most important factors per stage
Discovery Validation Efficiency ScaleCommitmentPivot / adaptabilityLearning
No significant factors CustomersCommitmentLearning
Pivot / adaptability andincubator / advisorswere significant lessimportant than the otherten factors
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5.8 Most Important Factors Over Time - Quantitative Analysis
Figure 3 show the descriptive statistics of section 17 in graphical way from which we can derive the
following:
• The factors business partners, working experience, staffing, and financial capital show a re-
markable trend upwards over time
• The factor pivot / adaptability show a remarkable trend line downwards over time
• All other factors remain more or less the same
In order to find out whether factors are significantly becoming more or less important over time
we conduct paired sample tests between the stages. So, three tests are needed to find out whether
a factor differs over time. We perform these test between the discovery and the validation stage,
between the validation and the efficiency stage, and between the efficiency and the scale stage.
When all tests are proven significantly different, we state that this factor differs over time.
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Figure 3: Factors over time
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Table 23: Factors Over Time - Paired Samples Test (n=48)
Discovery > Validation Validation > Efficiency Efficiency > ScaleMean Sig. (2-tailed) Mean Sig. (2-tailed) Mean Sig. (2-tailed)
Working experience -.375 .003 -.250 .077 -.417 .000Commitment .104 .302 .021 .837 -.063 .411Learning .125 .224 .000 1.000 .333 .014Pivot / adaptability * .354 .008 .354 .031 .458 .001Business model / plan -.563 .000 .208 .168 -.375 .008Network -.021 .890 .250 .103 -.521 .002Business partners -.021 .001 -.188 .316 -.583 .000Staffing * -.625 .000 -.417 .004 -.646 .000Financial capital -.438 .007 -.292 .075 -1.146 .000Market / competitors -.604 .000 -.042 .781 -.125 .371Customers * -.396 .027 -.333 .028 .333 .006Incubator / advisors -.417 .001 .125 .243 .208 .124
*) significantly different in all stages
Table 23 tells us that the factors pivot / adaptability, staffing and incubator / advisors do significantly
(p<.05) differ between the stages. It needs to be noted that pivot / adaptability shows a downward
trend as been assumed. The factor staffing shows a significant (p<.05) upward trend over time
as assumed. The most remarkable factor that differs in between stages is customers, this factor
shows an upward trend until the third stage, efficiency, and then becomes significantly less important
(p<.05).
5.9 Summary
Now, we can answer the first research subquestion:
1. What factors become more or less important when a startup matures?
In the previous paragraph we found that a) the factor staffing becomes more important over time, b)
the factor pivot / adaptability becomes less important over time, and c) the factor customers becomes
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more important over time till the third stage and in the last stage its significantly less important than
the third stage.
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5.10 Most Important Factors vs. Startup Profile - Quantitative Analysis
In this section we will analyze differences between the most important factors of each stage in the
startup life cycle versus the startup characteristics. In section 5.7 we mentioned nine questions that
were asked to the entrepreneurs in order to create an startup profile. Now, we will analyze the
differences between the factors and the startup characteristics. First, we define the independent and
the dependent variables:
• Independent variables: Working experience, Commitment, Learning, Pivot / adaptability,
Business model / plan, Network, Business partners, Staffing, Financial capital, Market / com-
petitors, Customers, Incubator / advisors
• Dependent variable: State (Succes, Failure, Still undecided)
• Dependent variable: Current stage (Discovery, Validation, Efficiency, Scale)
• Dependent variable: Founding team size (1, 2, 3, 4, 5, 6, 7 or more)
• Dependent variable: Founding team focus (Business centric, Technical centric, Balanced)
• Dependent variable: Employees (0, 1-5, 6-10, 11-20, 21-50, 51-100, 101 or more)
• Dependent variable: Target focus (Consumer market, Enterprise market, Both)
• Dependent variable: Target market (Local, Regional, National, International)
• Dependent variable: Startup location (Chile, Germany, Spain, The Netherlands, United King-
dom) *
• Dependent variable: Startup age (0, 1, 2, 3, 4, 5, 6, 7) *
*) derived from answers
Second, we need to know how the results are distributed between the groups of each dependent
variable. The total number of respondents was 48. Therefore we look at the frequencies of the
dependent variables which are depicted in table 24.
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Table 24: Frequencies of the dependent variables of the startup profile (n=48)
Success Failure UndecidedState 17 6 25
Discovery Validation Efficiency ScaleCur. stage 9 15 14 10
1 2 3 4 5 6 7 =>
Team size 6 10 12 17 2 0 1
Business Technical BalancedTeam focus 16 11 21
0 1-5 6-10 11-20 21-50 51-100 101 =>
Employees 14 20 6 4 0 2 2
Consumer Enterprise BothTarget foc. 13 21 14
Local Regional National InternationalTarget mar. 3 1 21 23
Chile Germany Spain Netherlands UKStartup loc. 1 1 3 42 1
0 1 2 3 4 5 6 7Startup age 11 3 13 5 9 4 2 1
Now, the above table tells us that the frequencies of all dependent variables are to low to perform
a tangible analysis. Therefore, we are going to reduce the groups of each dependent variable to
two groups, where the frequencies become larger and the analysis becomes more reliable. E.g.,
the distribution of 48 respondents among two groups (=24) is higher than the distribution among
four groups (=12), therefore the analysis is more solid when we introduce two groups. Now, we’ll
analyze each dependent variable.
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5.10.1 State vs. Factors
This dependent variable has three groups, namely success with 17 respondents, failure with 6 re-
spondents, and undecided with 25 respondents. In order to reduce this into two groups we combine
success with failure, because in these cases the entrepreneurs knew their (end) state, which was
success or failure. The other entrepreneurs don’t know their end state yet, so we assume that it
will result in differences among the most important factors in each of the stages. This leads to the
following:
• Dependent variable: State (Decided, Undecided)
In order to find differences, the Independent Samples Test is used and the results are depicted in
Table 25.
Table 25: State vs. factors in discovery - Independent Samples Test (n=48)
Decided (n=23) Undecided (n=25)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -1.759 .085 -1.781 .082Commitment -.496 .623 -.498 .621Learning -.764 .449 -.767 .447Pivot / adaptabiitly -1.454 .153 -1.464 .150Business model / plan 1.381 .174 1.385 .173Network .127 .900 .127 .900Business partners .035 .972 .035 .972Staffing .892 .377 .891 .378Financial capital 1.072 .289 1.074 .288Market / competitors -.167 .868 -.167 .868Customers -1.645 .107 -1.656 .104Incubator / advisors .083 .934 .083 .934
There are no significant differences among the factors in the discovery stage between the decided
and undecided state of the startup. The other stages also didn’t show differences between the decided
and undecided state of the startup (tables 91, 92, and 93 in appendix F.5).
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Explained
After this question, an open question was presented to explain the answer. Reasons like user growth,
profitable, market leader were mostly mentioned as indicators for success. Not being committed,
business model not working, no customer match were mentioned as indicators for failure. And,
about the undecided group couldn’t really answer, because they were simply to young as a startup
to give a proper answer.
5.10.2 Current Stage vs. Factors
This dependent variable has four groups, namely discovery with 9 respondents, validation with 15
respondents, efficiency with 14 respondents and scale with 10 respondents. In order to reduce this
into two groups we combine discovery with validation, because in these cases the startup is still
starting and finding its solution and a valid business model where its still unmature. On the other
side we combine efficiency and scale and name it more mature startups, they validated the business
model and now are trying to optimize the product / service and conquer the market. We assume that
there will be difference with the less mature startups vs. the more mature startups. This leads to the
following:
• Dependent variable: Current stage (Less mature, More mature)
In order to find differences, the Independent Samples Test is used and the results are depicted in
table 26.
The factor customers is valued significantly different between less mature and more mature startups
in the discovery stage (p<.01). In order to analyze this difference we need to look at the answers of
this question, therefore we created a cross tab depicted in table 27.
From this table we derive that less mature startups value customers in discovery more than more ma-
ture startups (p<.01). The other stages didn’t show significant differences between the less mature
and more mature startups (tables 94, 95, and 96 in appendix F.6).
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Table 26: Current stage vs. factors in discovery - Independent Samples Test (n=48)
Less mature (n=23) More mature (n=25)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .800 .428 .800 .428Commitment -.796 .430 -.796 .430Learning .910 .368 .910 .368Pivot / adaptabiitly .232 .818 .232 .818Business model / plan -1.039 .304 -1.039 .304Network -.538 .593 -.538 .593Business partners .279 .781 .279 .781Staffing .473 .639 .473 .639Financial capital .000 1.000 .000 1.000Market / competitors 1.555 .127 1.555 .127Customers 3.114 .003 3.114 .003Incubator / advisors -.154 .878 -.154 .878
Table 27: Customer in discovery - Crosstab (n=48)
Less mature (n=24) More mature (n=24) TotalCustomers Unimportant 0 0 0
Of little importance 1 8 9Moderately important 4 4 8Important 7 8 15Very important 12 4 16
Total 24 24 48
88
5.10.3 Founding Team Size vs. Factors
This dependent variable has seven groups. In order to reduce this into two groups we combine
founding team size 1, 2, 3 with each other and name it small founding teams and 4, 5, 6, 7 or more
with each and name it large founding teams. Now, we compare the small founding teams vs. large
founding teams and seek for differences and assume that small founding teams value other factors
than large founding teams. This leads to the following:
• Dependent variable: Founding team size (Small, Large)
In order to find differences, the Independent Samples Test is used and the results are depicted in
table 28.
Table 28: Founding team size vs. factors in discovery - Independent Samples Test (n=48)
Small (n=20) Large (n=28)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .620 .538 .591 .558Commitment -.401 .690 -.411 .683Learning .705 .485 .721 .475Pivot / adaptability .353 .725 .357 .723Business model / plan -1.499 .141 -1.463 .152Network -.333 .741 -.352 .726Business partners 1.001 .322 1.008 .319Staffing .000 1.000 .000 1.000Financial capital .726 .472 .747 .459Market / competitors -.584 .562 -.596 .554Customers 1.011 .317 .979 .334Incubator / advisors .443 .660 .461 .647
There are no significant differences among the factors in the discovery stage between the small and
large founding teams. The other stages also didn’t show significant differences between the small
and large founding teams (tables 97, 98, and 99 in appendix F.7).
89
5.10.4 Founding Team Focus vs. Factors
The founding team variable had three options where the respondents could choose from. In order
to reduce this into two groups we combine business centric with technical centric and name it
unbalanced. Now, we compare the balanced teams with the unbalanced teams and assume that
balanced team make value other factors than unbalanced teams. This leads to the following:
• Dependent variable: Founding team focus (Balanced, Unbalanced)
In order to find differences, the Independent Samples Test is used and the results are depicted in
table 29.
Table 29: Founding team focus vs. factors in discovery - Independent Samples Test (n=48)
Balanced (n=21) Unbalanced (n=27)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.020 .984 -.020 .984Commitment .100 .921 .101 .920Learning 2.170 .035 2.236 .030Pivot / adaptability .380 .705 .383 .703Business model / plan -.650 .519 -.671 .506Network -.702 .486 -.722 .474Business partners -.176 .861 -.167 .869Staffing -1.913 .062 -1.904 .064Financial capital -2.643 .011 -2.658 .011Market / competitors -1.970 .055 -1.899 .066Customers -.162 .872 -.165 .870Incubator / advisors -.682 .499 -.676 .502
There are two significant differences among the factors in the discovery stage between the balanced
and unbalanced founding teams, namely the factors learning and financial capital. Also the factor
network in the validation stage showed a significant difference. The other stages also didn’t show
differences between the small and large founding teams (tables 100, 101, and 102 in appendix F.8).
90
In order to analyze these difference we need to look at the answers of the questions, therefore we
created cross tabs which are depicted in tables 30, 31, and 32.
Table 30: Learning in discovery - Crosstab (n=48)
Balanced (n=21) Unbalanced (n=27) TotalLearning Unimportant 0 0 0
Of little importance 0 1 1Moderately important 2 4 6Important 3 11 14Very important 16 11 27
Total 24 24 48
Table 31: Financial capital in discovery - Crosstab (n=48)
Balanced (n=21) Unbalanced (n=27) TotalFinancial capital Unimportant 7 2 9
Of little importance 7 7 14Moderately important 4 9 13Important 2 4 6Very important 1 5 6
Total 24 24 48
From tables 30, 31, and 32 we derive the following:
• Balanced teams value learning in discovery more than unbalanced teams (p<.05)
• Unbalanced teams value financial capital more than balanced teams (p<.05)
• Unbalanced teams value network in validation more than balanced teams (p<.05)
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Table 32: Network in validation - Crosstab (n=48)
Balanced (n=21) Unbalanced (n=27) TotalNetwork Unimportant 1 0 0
Of little importance 1 0 9Moderately important 6 4 8Important 11 16 15Very important 2 7 16
Total 24 24 48
5.10.5 Employees vs. Factors
The number of employees has been divided into seven groups. We reduce this into two groups as
follow: no employees and employees. So, the last six groups are combined into one group. We as-
sume that startups with employees value factors more importantly than startups with no employees.
This leads to the following:
• Dependent variable: Employees (Employees, No employees)
In order to find differences, the Independent Samples Test is used and the results are depicted in
table 33.
This table shows one significant difference (p<.05), namely the factor customers. The other stages
also showed significant differences, in validation the factors learning and market / competitors
showed a significant difference (p<.05), in efficiency the factor business model / plan showed a
significant difference (p<.05), and in scale the factor pivot / adaptability showed a significant differ-
ence (p<.05) (tables 103, 104, and 105 in appendix F.9). In order to analyze this difference we need
to look at the answers of the questions, therefore we created cross tabs depicted in tables 34, 35,
36, 37, and 38.
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Table 33: Numbers of employees vs. factors in discovery - Independent Samples Test (n=48)
Employees (n=34) No employees (n=14)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.335 .739 -.360 .722Commitment .508 .614 .455 .654Learning -1.401 .168 -1.572 .126Pivot / adaptability -.966 .339 -1.068 .294Business model / plan -.175 .862 -.170 .866Network 1.181 .244 1.071 .297Business partners .230 .819 .235 .816Staffing .130 .897 .135 .893Financial capital .227 .822 .241 .811Market / competitors -2.045 .047 -2.038 .053Customers -2.719 .009 -2.886 .007Incubator / advisors .268 .790 .272 .788
Table 34: Customers in discovery - Crosstab (n=48)
Employees (n=34) No employees (n=14) TotalCustomers Unimportant 0 0 0
Of little importance 8 1 9Moderately important 7 1 8Important 12 3 15Very important 7 9 16
Total 34 14 48
Table 35: Learning in validation - Crosstab (n=48)
Employees (n=34) No employees (n=14) TotalLearning Unimportant 0 0 0
Of little importance 0 0 0Moderately important 7 1 8Important 16 3 19Very important 11 10 21
Total 34 14 48
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Table 36: Market / competitors in validation - Crosstab (n=48)
Employees (n=34) No employees (n=14) TotalMarket / competitors Unimportant 1 0 1
Of little importance 3 0 3Moderately important 17 5 22Important 10 5 15Very important 3 4 7
Total 34 14 48
Table 37: Business model / plan in efficieny - Crosstab (n=48)
Employees (n=34) No employees (n=14) TotalBusiness model / plan Unimportant 0 0 0
Of little importance 6 2 8Moderately important 16 1 17Important 9 7 16Very important 3 4 7
Total 34 14 48
Table 38: Pivot / adaptability in scale - Crosstab (n=48)
Employees (n=34) No employees (n=14) TotalPivot / adaptability Unimportant 2 0 2
Of little importance 4 5 9Moderately important 11 6 17Important 11 3 14Very important 6 0 0
Total 34 14 48
94
From the above tables we derive the following:
• Startups without employees value customers in discovery more than startup with employees
(p<.01)
• Startups without employees value learning in validation more than startup with employees
(p<.05)
• Startups without employees value market / competitors in validation more than startup with
employees (p<.05)
• Startups without employees value business model / plan in efficiency more than startup with
employees (p<.05)
• Startups with employees value pivot / adaptability in scale more than startup without employ-
ees (p<.05)
5.10.6 Target Focus vs. Factors
The score of the three groups are more or less equally divided, therefore its difficult to reduce it to
two groups. In this case we’ll analyze differences among the three groups. We assume that the three
groups value the factors differently. In order to find differences, the K Independent Samples Test is
used and the results are depicted in table 39.
This table shows two significant differences (p<.05), namely the factors business model / plan and
financial capital. The other stages also showed significant differences, in validation the factors pivot /
adaptability and customers showed a significant difference (p<.05), efficiency showed no significant
differences, and in scale the factor network showed a significant difference (p<.05) (tables 106, 107,
and 108 in appendix F.10). In order to analyze this difference we need to look at the answers of the
questions, therefore we created cross tabs depicted in tables 40, 41, 42, 43, and 44.
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Table 39: Target focus vs. factors in discovery - Independent Samples Test (n=48)
Consumer market (n=13), Enterprise market (n=21), Both (n=14)Chi-Square Asymp. Sig.
Working experience 2.814 .245Commitment .867 .648Learning 2.160 .340Pivot adaptability 4.562 .102Business model / plan 7.466 .024Network .291 .865Business partners 1.990 .370Staffing 3.349 .187Financial capital 6.229 .044Market / competitors .640 .726Customers 3.996 .136Incubator / advisors 1.245 .537
Table 40: Business model / plan in discovery - Crosstab (n=48)
Consumer (n=13) Enterprise (n=21) Both (n=14) TotalBusiness model / plan Unimportant 1 0 1 9
Of little importance 4 1 5 14Moderately important 4 11 6 13Important 3 6 2 6Very important 1 3 0 6
Total 13 21 14 48
Table 41: Financial capital in discovery - Crosstab (n=48)
Consumer (n=13) Enterprise (n=21) Both (n=14) TotalFinancial capital Unimportant 0 0 0 0
Of little importance 2 1 1 4Moderately important 2 3 0 5Important 7 15 3 22Very important 2 5 10 17
Total 13 21 14 48
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Table 42: Pivot / adaptability in validation - Crosstab (n=48)
Consumer (n=13) Enterprise (n=21) Both (n=14) TotalPivot / adaptability Unimportant 1 0 0 1
Of little importance 1 0 0 1Moderately important 4 3 2 9Important 4 6 4 14Very important 3 12 8 23
Total 13 21 14 48
Table 43: Customers in validation - Crosstab (n=48)
Consumer (n=13) Enterprise (n=21) Both (n=14) TotalCustomers Unimportant 0 0 0 0
Of little importance 0 1 2 3Moderately important 2 1 4 7Important 8 6 4 18Very important 3 13 4 20
Total 13 21 14 48
Table 44: Business model / plan in scale - Crosstab (n=48)
Consumer (n=13) Enterprise (n=21) Both (n=14) TotalNetwork Unimportant 1 0 1 2
Of little importance 4 1 5 10Moderately important 4 11 6 21Important 3 6 2 11Very important 1 3 0 4
Total 13 21 14 48
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From the above tables we derive the following:
• Startups with a enterprise product value business model / plan in discovery more than star-
tups with consumer products or startups with a product that focus on both consumers and
enterprises (p<.05)
• Startups with a product that focus on both consumers and enterprises value financial capital
in discovery more than startups with consumer products and startups with enterprise products
(p<.05)
• Startups with a enterprise product and startups with a product that focus on both consumers
and enterprises value pivot / adaptability in validation more than startups with consumer prod-
ucts (p<.01)
• Startups with a enterprise product value customers in validation more than startups with
consumer products or startups with a product that focus on both consumers and enterprises
(p<.05)
• Startups with a enterprise product value network in scale more than startups with consumer
products or startups with a product that focus on both consumers and enterprises (p<.05)
5.10.7 Target Market vs. Factors
The startup could choose four options by this question. The groups national and international show
the highest scores, therefore we are going to compare these two groups. We add the local and
regional options to the national market. We assume that startups that target nationally value factors
differently than startup who target internationally. This leads to the following:
• Dependent variable: Target market (National, International)
In order to find differences, the Independent Samples Test is used and the results are depicted in
table 45.
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Table 45: Target market vs. factors in discovery - Independent Samples Test (n=48)
National (n=25) International (n=23)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.848 .401 -.847 .402Commitment -.033 .974 -.033 .974Learning -.324 .748 -.324 .747Pivot / adaptability -.908 .369 -.910 .367Business model / plan -.178 .860 -.177 .860Network -.486 .629 -.484 .631Business partners -.880 .383 -.884 .381Staffing .532 .597 .533 .596Financial capital -.159 .874 -.159 .874Market / competitors .443 .660 .441 .661Customers .571 .571 .569 .572Incubator / advisors .225 .823 .224 .824
This tables shows us no significant differences (p<.05) in discovery. The tables (tables 109, 110,
and 111 in appendix F.11) of the other stages also showed no significant difference (p<.05). There-
fore it can be said that no differences between startups target nationally or internationally.
5.10.8 Startup Location vs. Factors
From the answers five groups were derived. The frequencies of the groups (table 24) show us
no opportunity to reduce it to two groups, therefore we are unable to analyze differences among
countries.
5.10.9 Startup Age vs. Factors
This dependent variable has eight groups. In order to reduce this into two groups as follow: young
startups and older startups. So, the startups with an age of two years or younger are grouped and
named younger startups. And, the startups with an age of three years or older are grouped and
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named older startups. This leads to the following:
• Dependent variable: Startup age (Younger startups, Older startups)
In order to find differences, the Independent Samples Test is used and the results are depicted in
table 46.
Table 46: Startup age vs. factors in discovery - Independent Samples Test (n=48)
Younger startups (n=27) Older startups (n=21)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .664 .510 .643 .524Commitment -.633 .530 -.646 .522Learning .847 .401 .882 .382Pivot / adaptability -.380 .705 -.383 .703Business model plan -1.144 .259 -1.121 .269Network .338 .737 .338 .737Business partners -.105 .916 -.106 .916Staffing .417 .679 .422 .675Financial capital .198 .844 .201 .841Market / competitors .505 .616 .506 .615Customers 2.067 .044 2.046 .047Incubator / advisors .369 .714 .363 .719
This table shows one significant difference (p<.05), namely the factor customers. The factor work-
ing experience in scale also showed a significant difference ( p <.05), the other two stages didn’t
show significance differences (tables 112, 113, and 114 in appendix F.12). In order to analyze this
difference we need to look at the answers of the questions, therefore we created cross tabs depicted
in tables 47 and 48.
100
Table 47: Customers in discovery - Crosstab (n=48)
Younger startups (n=34) Older startups (n=21) TotalCustomers Unimportant 0 0 0
Of little importance 3 6 9Moderately important 4 4 8Important 8 7 15Very important 12 4 16
Total 27 21 48
Table 48: Working experience in scale - Crosstab (n=48)
Younger startups (n=34) Older startups (n=21) TotalWorking experience Unimportant 0 0 0
Of little importance 0 0 0Moderately important 8 1 9Important 11 10 21Very important 8 10 18
Total 27 21 48
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From tables 47 and 48 we derive the following:
• Younger startups value customers in discovery more than older startups (p<.05)
• Older startups value working experience in scale more than younger startups (p<.05)
5.10.10 Summary
In this section we performed statistical analysis in order to find differences among the startup profile
vs. the factors. With the analysis we can answer our second research subquestion:
2. What factors are valued differently between certain startup characteristics?
In the previous paragraphs we analyzed nine different startups characteristics. With almost all de-
pendent variables (the characteristics) we had to reduce the predefined groups into two different
groups in order to perform a more reliable test. Now, we summed up the results in table 49.
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Table 49: Summary - Most Important Factors vs. Startup Profile
Dependent variable Differences Sig.State No differences found between decided and undecided startups -Current stage Less mature startups value customers in discovery more than more ma-
ture startupsp<.01
Founding team size No differences found between small and large founding teams -Founding team fo-cus
Balanced teams value learning in discovery more than unbalancedteamsUnbalanced teams value financial capital in discovery more than bal-anced teamsUnbalanced teams value network in validation more than balancedteams
p<.05
p<.05
p<.05
Employees Startups without employees value customers in discovery more thanstartup with employeesStartups without employees value learning in validation more thanstartup with employeesStartups without employees value market / competitors in validationmore than startup with employeesStartups without employees value business model / plan in efficiencymore than startup with employeesStartups with employees value pivot / adaptability in scale more thanstartup without employees
p<.01
p<.05
p<.05
p<.05
p<.05
Target focus Startups with a enterprise product value business model / plan in dis-covery more than startups with consumer products or startups with aproduct that focus on both consumers and enterprisesStartups with a product that focus on both consumers and enterprisesvalue financial capital in discovery more than startups with consumerproducts and startups with enterprise productsStartups with a enterprise product and startups with a product that focuson both consumers and enterprises value pivot / adaptability in valida-tion more than startups with consumer productsStartups with a enterprise product value customers in validation morethan startups with consumer products or startups with a product thatfocus on both consumers and enterprisesStartups with a enterprise product value network in scale more thanstartups with consumer products or startups with a product that focuson both consumers and enterprises
p<.05
p<.05
p<.01
p<.05
p<.05
Target market No differences found between startups that target nationally or interna-tionally
-
Startup location Insufficient data in order to perform statistical analysis -Startup age Younger startups value customers in discovery more than older startups
Older startups value working experience in scale more than youngerstartups
p<.05p<.05
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5.11 Most Important Factors vs. Profile of the Entrepreneur - Quantitative Analysis
In this section we will analyze differences between the most important factors of each stage in the
startup life cycle versus the characteristics of the entrepreneur. In section 5.7 we mentioned three
questions that were asked to the entrepreneurs in order to create a profile of the entrepreneur. Now,
we will analyze the differences between the factors and the characteristics of the entrepreneurs.
First, we define the independent and the dependent variables:
• Independent variables: Working experience, Commitment, Learning, Pivot / adaptability,
Business model / plan, Network, Business partners, Staffing, Financial capital, Market / com-
petitors, Customers, Incubator / advisors
• Dependent variable: Gender (Male, Female)
• Dependent variable: Age of the entrepreneur (24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 36,
37, 38, 41, 43, 44) *
• Dependent variable: Education (Didn’t graduate high school, High School / GED, Some
college, Associates degree, Bachelors degree, Masters degree, Doctorate degree, Professional
degree)
*) derived from answers
Second, we need to know how the results are distributed between the groups of each dependent
variable. The total number of respondents was 48. Therefore we look at the frequencies of the
dependent variables which are depicted in table 50.
5.11.1 Gender vs. Factors
For gender there are only two possible options, male or female. The frequencies of the groups
(table 50) show us no opportunity to analyze, because there were only two females and 46 males.
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Table 50: Frequencies of the dependent variables of the profile of the entrepreneur
Male FemaleGender 46 2
24 25 26 27 28 29 30 31 32 33 34 36 37 38 41 43 44Age 1 4 3 8 7 1 4 5 4 2 2 1 2 1 1 1 1
No HS / GED SC AD BA MA DR PDEducation 0 1 0 1 17 26 2 1
5.11.2 Age of the Entrepreneur vs. Factors
The frequencies of the age tells us that we can reduce the groups into two groups. We introduce
young entrepreneurs and older entrepreneurs. The young entrepreneurs are 29 years old or younger
and the older entrepreneurs are 30 years or above. We assume that young entrepreneurs value factors
differently than older entrepreneurs. This leads to the following:
• Dependent variable: Age of the entrepreneur (< 30, 30 =>)
In order to find differences, the Independent Samples Test is used and the results are depicted in
table 51.
This table shows a significant difference (p<.05) for the factor financial capital. Also, the factor
customers showed a significant difference (p<.01) in the efficiency stage and the factors business
model / plan and pivot / adaptability showed a significant difference (p<.05) in the scale stage,
validation showed no significant differences (tables 115, 116, and 117 in appendix F.13). In order to
analyze this difference we need to look at the answers of the questions, therefore we created cross
tabs depicted in tables 52, 53, 54, and 55.
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Table 51: Age of the entrepreneur vs. factors in discovery - Independent Samples Test (n=48)
< 30 (n=24) 30 >= (n=24)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.800 .428 -.800 .428Commitment .796 .430 .796 .430Learning .910 .368 .910 .368Pivot / adaptability .232 .818 .232 .818Business model / plan -.147 .884 -.147 .884Network -.179 .859 -.179 .859Business partners -1.131 .264 -1.131 .264Staffing -1.701 .096 -1.701 .096Financial capital -2.382 .021 -2.382 .022Market / competitors -.974 .335 -.974 .335Customers -.516 .608 -.516 .608Incubator / advisors -1.091 .281 -1.091 .281
Table 52: Financial capital in discovery - Crosstab (n=48)
< 30 (n=24) 30 >= (n=24) TotalFinancial capital Unimportant 5 4 9
Of little importance 11 3 14Moderately important 5 8 13Important 2 4 6Very important 1 5 6
Total 24 24 48
Table 53: Customers in efficiency - Crosstab (n=48)
< 30 (n=24) 30 >= (n=24) TotalCustomers Unimportant 0 0 0
Of little importance 0 0 0Moderately important 3 0 3Important 12 5 7Very important 9 19 28
Total 24 24 48
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Table 54: Business model / plan in scale - Crosstab (n=48)
< 30 (n=24) 30 >= (n=24) TotalBusiness model / plan Unimportant 0 0 0
Of little importance 6 1 7Moderately important 4 1 5Important 10 15 25Very important 4 7 11
Total 24 24 48
Table 55: Pivot / adaptability in scale - Crosstab (n=48)
< 30 (n=24) 30 >= (n=24) TotalPivot / adaptability Unimportant 1 1 2
Of little importance 4 5 9Moderately important 14 3 17Important 5 9 14Very important 0 6 6
Total 24 24 48
107
From the tables 52, 53, 54, and 55 we derive the following:
• Older entrepreneurs value financial capital in discovery more than younger entrepreneurs
(p<.05)
• Older entrepreneurs value customers in efficiency more than younger entrepreneurs (p<.01)
• Older entrepreneurs value business model / plan in scale more than younger entrepreneurs
(p<.05)
• Older entrepreneurs value pivot / adaptability in scale more than younger entrepreneurs (p<.05)
5.11.3 Education vs. Factors
The frequencies of the education variables tells us that we can reduce the groups into two groups.
We introduce a bachelor and a master group. The groups on the left of the bachelor are added to the
bachelor and the groups on the right are added to the master group. We assume that entrepreneurs
with a Bachelor degree or less value factors differently than entrepreneurs with a Master degree or
better. This leads to the following:
• Dependent variable: Education (< Bachelor, Master >)
In order to find differences, the Independent Samples Test is used and the results are depicted in
table 56.
This table shows no significant differences (p<.05). But, the factors learning and business partners
showed a significant difference (p<.01, p<.05) in the efficiency, the other two stages didn’t show
significance differences (tables 118, 119, and 120 in appendix F.14). In order to analyze this dif-
ference we need to look at the answers of the questions, therefore we created cross tabs depicted in
tables 57 and 58.
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Table 56: Education vs. factors in discovery - Independent Samples Test (n=48)
< Bachelor (n=19) Master > (n=29)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.251 .803 -.254 .801Commitment .711 .481 .733 .467Learning .547 .587 .571 .571Pivot / adaptability -1.111 .272 -1.076 .290Business model / plan .006 .995 .006 .995Network .650 .519 .657 .515Business partners -.973 .336 -.972 .337Staffing -.060 .952 -.062 .951Financial capital .124 .901 .133 .895Market / competitors .560 .579 .628 .533Customers .252 .802 .249 .805Incubator / advisors -.203 .840 -.208 .836
Table 57: Learning in efficiency - Crosstab (n=48)
< Bachelor (n=19) Master > (n=29) TotalLearning Unimportant 0 0 0
Of little importance 0 0 0Moderately important 6 3 9Important 9 8 17Very important 4 18 22
Total 19 29 48
Table 58: Business partners in efficiency - Crosstab (n=48)
< Bachelor (n=19) Master > (n=29) TotalBusiness partners Unimportant 0 0 0
Of little importance 2 3 5Moderately important 7 5 12Important 10 11 21Very important 0 10 10
Total 19 29 48
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From tables 57 and 58 we derive the following:
• Entrepreneurs with a master degree or higher value learning in efficiency more than en-
trepreneurs with a bachelor degree or lower (p<.01)
• Entrepreneurs with a master degree or higher value business partners in efficiency more than
entrepreneurs with a bachelor degree or lower (p<.05)
5.11.4 Summary
In this section we performed statistical analysis to find differences among the profile of the en-
trepreneur vs. the factors. Now, we can answer our third research subquestion:
3. What factors are valued differently based upon characteristics of the entrepreneurs?
In the previous paragraphs we analyzed three different characteristics of the entrepreneur vs. the
factors. With almost all dependent variables (the characteristics) we had to reduce the predefined
groups into two different groups in order to perform a more reliable test. Now, we summed up the
results in table 59.
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Table 59: Summary - Most Important Factors vs. Profile of the Entrepreneur
Dependent variable Differences Sig.Gender Insufficient data in order to perform statistical analysis -Age of the en-trepreneur
Older entrepreneurs value financial capital in discovery more thanyounger entrepreneursOlder entrepreneurs value customers in efficiency more than youngerentrepreneursOlder entrepreneurs value business model / plan in scale more thanyounger entrepreneursOlder entrepreneurs value pivot / adaptability in scale more thanyounger entrepreneurs
p<.05
p<.01
p<.05
p<.05
Education Entrepreneurs with a master degree or higher value learning in effi-ciency more than entrepreneurs with a bachelor degree or lowerEntrepreneurs with a master degree or higher value business partnersin efficiency more than entrepreneurs with a bachelor degree or lower
p<.01
p<.05
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6 Discussion
The goal of this study is clear: the determination of important factors among the stages of the
internet startup life cycle. After conducting interviews, four propositions were defined and tested
with an online survey where 48 respondents were found to fill out our survey. Section 5 (results)
begun with the elaboration of the interviews, followed by the derivation of four propositions which
consisted of the factors with the highest scores among each stage of the internet startup life cycle.
These propositions were translated into hypotheses and statistically analyzed. This systematic way
helped us to construct a thoroughly survey that was understandable, easy to fill out and could be
done within reasonable time. It also helped us answering the research question and its subquestions.
6.1 Most Important Factors per Stage
At first, we thought that the research question was easy to answer, whereas we assumed - before
conducting this research - that in each stage at least one of the factors would be found as signifi-
cantly most important. Analysis showed us differently and the research question "What are the most
important factors among the stages of the internet startup life cycle?" is answered by table 60. We’ll
share some thoughts on the found answers that relate to practice.
Table 60: Most important factors per stage
Discovery Validation Efficiency ScaleCommitmentPivot / adaptabilityLearning
No significant factors CustomersCommitmentLearning
Pivot / adaptability andincubator / advisorswere significant lessimportant than the otherten factors
Most Important Factors in Discovery
The factors commitment, pivot / adaptability, and learning are significantly most important than the
other factors in this stage. In advance it seems logical that these factors are most important, but we
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miss two factors that we thought were important too, namely the factors business model / plan and
customers. Because, the first stage discovery is about the process of starting up where a business
model / plan comes in handful. Also, startups are focussing on finding the customer, where you
would expect that the customer would be central. We believe that the results tell us that its all about
the founding team in this stage, because the significant found factors are all related to the founding
team. The key for success in this stage is the founding team.
Most Important Factors in Validation
While performing the analysis we were determined to find significant factors based on the descrip-
tive statistics of this stage, but we stagnated by the fourth derivation of the hypothesis which meant
there were no significant factors to be found. Otherwise, the first three factors, namely commitment,
learning, and customers would be significantly higher than the other factors. As the validation stage
is closely related to the discovery stage, it seemed logical that these factors were the most important
ones. But, in this stage its about finding the business model, and that was not even among the top
three highest valued factors which surprised us.
Most Important Factors in Efficiency
The factors customers, commitment, and learning are significantly most important in this stage. The
factor customers can be explained, because in the efficiency stage its about optimizing the product
or service where it can be assumed that the customers play a central role. Startups are interacting
with the customer in order to improve its product or service. And the factor learning is important
where each startup learns everyday and should be able to translate learnings into actions to - e.g.
- optimize the business processes. Commitment stays important, because all hands on deck are
needed in order to survive each stage.
Most Important Factors in Scale
This stage showed no top three of significantly found factors, but it showed us that two factors were
significantly less important than the others, namely the factors pivot / adaptability and incubator /
advisors. This can be assumed as pretty logical, because at this point startups already found their
business model, revenues are showing a slightly upward trend, so therefore they became independent
113
enough to stand on their own where the factors pivot / adaptability and incubators / advisor become
irrelevant. Although the derived hypothesis (H4) states that financial capital is among the most
important factors is true, we thought it would be within the top three. Backed up with the interviews,
the factor financial capital shows to be most important, because money is needed to establish growth.
6.2 Most Important Factors Over Time
We didn’t assume anything for this subquestion. Analysis showed us new insights of the factors
over time and the research subquestion "What factors become more or less important when a startup
matures?" showed the following results (section 5.9):
• Staffing becomes more important over time
• Pivot / adaptability becomes less important over time
• Customers become more important over time till the third stage
Staffing
One of the interviewees gave the following tip: "Hire slow, and fire fast" which can be interpreted as
find the best people (takes long) and show the door to those who are performing badly (fire directly).
This is confirmed by our own experience, a startup should only hire the best available people. At
the beginning of the startup cycle everything is managed by the founding team, but when you start
to grow, you can not do everything on your own, and you need people to do that for you. So, staffing
becomes important, and only the best people can really help you accelerate.
Pivot / adaptability
This factor significantly becomes less important over time. This is assumed as logical, where pivot
/ adaptability is important at the beginning, because you’re more likely to change your product
or service when finding your customer. While validating your business model this factor stays
important, but significantly less important than in the first stage. And, the last stages this factor
becomes more or less irrelevant.
114
Customers
This factor is quiet remarkable, because it behaves significantly different among the stages. The
importance increases in the first three stages and then it decreases. Its remarkable, because in
the first two stages you’re trying to find your customer and validate your business model where
you expect it would equally important. In the third stage its even more important where it sounds
logical, because you’re optimizing your product or service where the customers play a central role.
And, in the last stage it decreases where we think its because of other factors that were valued more
or less equally important.
6.3 Most Important Factors vs. Startup Profile
Before performing the analysis we also didn’t assume anything. At this point we really need to
be careful about what we are going to say about the significantly found differences among the
most important factors vs. the startup characteristics which were formulated in the second research
subquestion: "What factors are valued differently based upon certain startup characteristics?".
If we want to answer this question giving the survey it could be done in different ways. Where most
questions were formulated as multiple choice questions and some had more than seven options,
you can assume you’ll need a lot of respondents in order to say something statistically meaningful.
Giving this assumption we had no choice with the 48 respondents, but to reduce it to two groups.
From this we derived some uncommon groups and found sixteen significant differences (p<.05,
p<.01). As been said, you need more data to perform more reliable analysis. So, we’re going to
discuss those differences who are significantly strong at a .01 level and neglect those who are at a
significant level .05. Three differences at the significant level of .01 were found (section 5.10.10):
• Less mature startups value customers in discovery more than more mature startups
• Startups without employees value customers in discovery more than startup with employees
• Startups with a enterprise product and startups with a product that focus on both consumers
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and enterprises value pivot / adaptability in validation more than startups with consumer prod-
ucts
Customers in discovery
Both less mature startups and startups without employees value customers in discovery more than
more mature startups and startups with employees. The term maturity has been derived from the
current stage in which the startup finds itself in and the term employees has been derived from the
number of employees a startup has. Although we didn’t analyzed it, we assume these dependent
variables are closely related to each other, because a startup that has just been born is more likely
to have no employees. Now, we believe that the difference comes of the naivety of the first group,
because the startups are still trying to find their customer and validate their business model, that’s
why they believe this factor is more important than others, where the second group is more mature
and believes other factors were probably more important than others.
Pivot / adaptability in validation
We are going to turn this difference around and say: startups with a consumer product value pivot
/ adaptability less than startups with an enterprise product and startups with a product that focus
on both consumers and enterprises. This is more or less remarkable and we think this is due to the
fact of the vision and mission of the entrepreneur and its startup. We believe that startups with a
consumer product have a higher and more abstract vision and mission than the other groups.
6.4 Most Important Factors vs. Profile of the Entrepreneur
Again, we didn’t had any expectations for this analysis. The third research subquestion, namely
"What factors are valued differently based upon characteristics of the entrepreneurs?" showed six
significantly found differences among the characteristics of the entrepreneurs vs. the factors (sec-
tion 5.11.4). In the previous paragraph we neglect those findings who were at a significant level of
.05 and discussed those with a significant level of .01. Now, we’re going to do the same with these
findings, and we’re going to discuss the following two:
116
• Older entrepreneurs value financial capital in discovery more than younger entrepreneurs
• Entrepreneurs with a master degree or higher value learning in efficiency more than en-
trepreneurs with a bachelor degree or lower
Financial capital in discovery
We believe that older entrepreneurs come to the conclusion that financial capital is more important
at the beginning where they learn as they develop their business. We assume that these entrepreneurs
have less problems accepting third-party money in exchange for shares in order to accelerate faster
where results can be booked sooner. Younger entrepreneurs value this factor less, because they’re
probably focussing on other aspects and forget they need money at some point and .
Learning in efficiency
As we have seen that learning is significantly among the most important factors in the efficiency, now
it shows us that entrepreneurs with a master degree or higher value learning more than entrepreneur
with a bachelor degree or lower. We think that this is because better educated entrepreneurs are
more wise and analytical and value everything in terms of learning. We believe that they are better
trained to act of these learning and therefore value this factor more.
6.5 Research Limitations
Throughout this study, certain limitations were encountered that need to be mentioned. The first
drawback was the time of the entrepreneurs. Where lots of entrepreneurs were approached to in-
terview, only four responded and participated. Next to this, the survey resulted in a small sample
size where 48 entrepreneurs filled out our survey. Although reliable (a=.820), the last two in-depth
analysis where factors were plotted against the startup profile and the profile of the entrepreneur are
less reliable. It need to be noted that more respondents are needed for a more reliable analysis.
Another thing that need to be mentioned was the profile of the entrepreneurs. Entrepreneurs were
approaches through several channels. Although it delivered us enough respondents, the profile of
117
the entrepreneur was really broad where it divert from startups with a consumer product and a large
founding team vs. startups with an enterprise product and a solo founding team.
It also need to be mentioned that the survey was more or less opinion-based - normative analysis -
instead of positive analysis. Hard numbers like startups costs, revenues, etc. of startups were not
investigated. Questions like "How important is..", "What do you consider..", and "Please explain..."
are not formulated objectively. This gave us enough insights in the mind of the entrepreneur, but
makes hard conclusions more difficult.
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7 Conclusion
To determine the most important factors among the stages of the internet startup life cycle, four
interviews were held and an online was conducted that has been filled out by 48 entrepreneurs. This
study was not conducted before, and new within the domain of internet startups, therefore it was
not an easy task to perform. That’s why we’ve addressed this study with a mixed method to gather
qualitative and quantitative data and it showed us new and exciting results.
Through statistical analysis we found the answer to our main research question. In discovery and
efficiency we found six significant factors that were most important. In the first stage pivot / adapt-
ability showed to be important, and in the third stage customers showed to be important and in both
stages commitment and learning showed to be important. The factor customers is related to the ex-
ternal environment and the other three factors are related to the founding team. Hence, we conclude
that the founding team is most important throughout the internet startup life cycle where customers
play an important role as well. Additional, commitment was mentioned in the interviews a couple
of times to be important, but also as a reason for failure. Being committed is half work. Therefore,
we conclude that the factor commitment is the most important factor overall.
Three research subquestions were derived from the main research question. We knew that the first
subquestion to find differences for factors over time could be easily be answered through statistical
analysis and we found that staffing becomes significantly more important and pivot / adaptabil-
ity significantly less important over time. Hence, we conclude that staffing is important over time
and therefore attention should be paid from the beginning. Next to this, we conclude that star-
tups shouldn’t be afraid to pivot when its necessary. The best way is to start measuring from the
beginning with certain predefined metrics (see implications).
For the second and third subquestion we tried to find differently valued factors among different
characteristics of the entrepreneur and startup characteristics. While conducting statistical analysis,
we had to reduce the predefined groups to two groups to conduct more reliables analysis. We
found in total 24 factors that were significantly different among the characteristics. But, we found
119
that the sample size was to thin and therefore we neglected those at a significant level of .05 and
discussed those at a significant level of .01. Five were discussed in the previous section. But,
although interesting and exciting enough we still found these findings to unreliable in order to really
connect a solid conclusion to it. Hence, future research is needed to investigate these findings more
thoroughly.
And last, we conclude that we achieved our goals in order to contribute to the scientific world
and the world of practitioners. Where not much have been researched about internet startups, we
found some significant evidence for important factors for success. From these findings some clear
implications can be derived that are presented later.
7.1 Future Research
From literature lots of factors were derived that already proven significantly important for the suc-
cess of new firms. Most of these factors were mapped into a conceptual internet startup framework
into factor groups, namely the founding team, the startup capability and the external environment.
Next to the found factors, new factors were introduced and directly tested with our online survey.
A more thoroughly factors analysis will contribute to the extension of this study, including not only
the twelve factors, but also others.
The stages were adapted from a technical report which has been conducted with 17,000 startups,
although highly reliable, its not scientifically accountable. Therefore, research is needed in order to
validate the stages of the startup life cycle and found applicable for all types of internet startups.
Where the conceptual internet startup framework has been tested with 4 interviews and 48 en-
trepreneurs. Another suggestion for future research can be made in order to test whether the factor
groups can actually be grouped together.
Finally, the relation between the factors and the startup performance can be further researched.
Startup performance was not explicitly documented in this study. If this happens, better statistically
proven success or failure factors can be extracted.
120
7.2 Implications for Entrepreneurs
Throughout this study, we had one clear goal: write implications for today’s internet entrepreneurs
in order to help to build a sustainable business. Interviews were held with both successful and unsuc-
cessful entrepreneurs of internet startups. After that, factors were valued by internet entrepreneurs
with different backgrounds. From our findings we come to the following implications.
The beginning
In the beginning of the startup its all about the finding the customer (discovery) and validating the
business model (validation). Factors related to the entrepreneur were valued as most important for
success in the first stage. The same factors almost seemed to be most important as well in the second
stage. Those factors were commitment (I), pivot / adaptability (II), and learning (III) which lead to
the following tips:
• (I) Engage. Marry your startup. You’re not going to survive if you’re not 100% committed.
• (II) Change. Pivot when you can’t find your customers or your business model.
• (III) Practice. Execute, measure and learn. Convert learnings into actions.
The sequel
Later on, internet entrepreneurs found their business model and are ready to optimize their product
or service and business processes (efficiency) and when this is done they’re ready to scale and even
to expand (scale). Now, entrepreneurs valued three factors as most important during these stages
and those were customers (IV), commitment (I), and learning (III) that lead to the following tips:
• (IV) Interact. Your customer is most important. Go and talk to them. Don’t forget to listen.
• (I) Engage. Re-marry your startup. Stay focused. Be passionated about your vision.
• (III) Practice. Keep executing, measuring and learning. Convert learning into actions.
121
As you’ve seen there are twee general findings that keeps being important, namely commitment
(engage) and learning (practice). We argue that pivot / adaptability (change) and customers (interact)
are also important over time in a broader sense. Change being presented as not only changing
your business model, also your product, your strategy, your market, etc. And interact resembles
every entity with whom you are communicating where the customers are most important, but also
investors, advisors, etc. are important to talk you regarding your product / startup. Summed up,
if we combine above tips we get the epic startup where the e stands for engage, the p stands for
practice, the i stand for interact, and the c stands for change. Graphically, it look like this:
Figure 4: The Epic Startup
The Epic Startup
Practice
InteractChange
Engage
internet startup life cycle
su
cce
ss
122
• Engage. Marry your startup. You’re not going to survive if you’re not 100% committed. Stay
focused. Make clear agreements with one another.
• Practice. Execute, measure, and learn. Execute your plan. Measure through metrics. Learn
from your experience. Define actions from these findings.
• Interact. Where your customer is most important, also consider your environment. Go and
talk to them. Don’t forget to listen.
• Change. Pivot when you can’t find your customers or your business model. And change your
product / service and processes to follow vision.
If you follow these steps and iterate over time your road to success is more easy to find. Besides
this, staffing was named as an important factor over time. We believe that only a startup performs
better when the best people come on board therefore we adopt the tip of Pablo: "Hire slow, fire
fast".
123
Acknowledgements
As a child, I always expected to finish my master by my 24th birthday. After a long time, and a four
year break during my master program, I’m happy that this moment finally arrived. Although I’m
not 24 anymore, this is a great milestone in my life. During the period of conducting this research a
lot of people supported me, I want to take this opportunity to thank them.
First, I would like to thank Prof. Dr. Brinkkemper for his time, valuable feedback, creativity, and
patience. He managed to send me into the right direction where I needed it the most. Together, we
introduced a great new framework, exciting results, and more research to come.
Second, I’m thankful that Dr. Franch was willing to receive me at the Universitat Politècnica de
Catalunya in Barcelona. Both Dr. Franch and Barcelona gave me great new insights.
Third, I thank Jordi, Christof, Jose Luis, and Pablo for their valuable time and willingness to share
their experiences with me. It was fun doing the interviews with you guys.
Fourth, I thank all entrepreneurs who took the time to fill out our survey. Although time is most
valuable to them, I believe they helped other internet entrepreneurs by making the factors under-
standable.
Fifth, Kevin, Martijn, and Willem showed me the best experience in my life. It was the best roller
coaster ride I’ve ever been in. Where the roller coaster went through all crazy loops possible, we
managed to stick together, and we’ll always be the Yunoo founders for life.
Sixth, my brother Albert deserves a special thank you. He coached me and gave me very helpful
insights in this project. Thanks for the advice.
And last, I would like to thank my family for their great support. My parents for giving me the
opportunity to study, I really appreciate your hard work for your children. My brother Jan-Willem
for his great personal and business related feedback. And Anneriek, Femke, Jens, and Isa for their
love. Without their support I wouldn’t be able to graduate.
124
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A Variable Names and Abbreviations
Table 61: Independent variables of the factors
Discovery Validation Efficiency ScaleWorking experience A_WOREXP B_WOREXP C_WOREXP D_WOREXPCommitment A_COMMIT B_COMMIT C_COMMIT D_COMMITLearning A_LEARNN B_LEARNN C_LEARNN D_LEARNNPivot / adaptability A_PIVOTA B_PIVOTA C_PIVOTA D_PIVOTABusiness model / plan A_BMOPLN B_BMOPLN C_BMOPLN D_BMOPLNNetwork A_NETWRK B_NETWRK C_NETWRK D_NETWRKBusiness partners A_BUSPAR B_BUSPAR C_BUSPAR D_BUSPARStaffing A_STAFFN B_STAFFN C_STAFFN D_STAFFNFinancial capital A_FINCAP B_FINCAP C_FINCAP D_FINCAPMarket / competitors A_MARKET B_MARKET C_MARKET D_MARKETCustomers A_CUSTOM B_CUSTOM C_CUSTOM D_CUSTOMIncubator / advisors A_INCUBA B_INCUBA C_INCUBA D_INCUBA
Table 62: Dependent variables of the startup profile
Startup Characteristics Dependent variableSuccess or failure S_SUCFALCurrent stage S_CSTAGEFounding team size S_FTSIZEFounding team business or technical centric S_FTBUTENumber of employees S_NREMPLProduct / service consumer or enterprise market S_B2BB2CProduct / service consumer or target S_TRLRNIStartup location S_LOCATIStartup founding year S_YEARFO
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Table 63: Dependent variables of the profile of the entrepreneur
Startup characteristics Independent variableGender E_GENDERAge of the entrepreneur E_AGEEducation level E_EDULVL
129
B Factors Found in Literature
Table 64: All factors identified by nine studies
Author(s) Factor groups Significant factorsDuchesneau andGartner (1990)
The lead entrepreneurs
Startup behaviors
Firm behaviors and strategy
Entrepreneurial parentsBreadth of management experienceRisk-reduction behaviorsLocus of controlBusiness ideaBreadth of visionStart-up behaviorsTime in planningPlanning breadthMarket researchUsed professional advicePurchased firmEmployee specializationLE-’s personal commandOrganizational formatStrategic decision makingOperational decisionsLE communicationCapital investment levelLowest cost and service to broad mar-kets
Bruno et al. (1992) Product/market
Financial
Managerial/key employee
TimingDesignDistribution/sellingBusiness definitionToo great a reliance on one customerInitial undercapitalizationAssuming debt too earlyVenture capital relationshipIneffective teamPersonal problems
130
Schutjens and Wever(2000)
Entrepreneur-associated factors
Firm-associated factors
External factors
Invested hoursSideline activitiesPush or pull motivesTurnover increasePreparation (p<.05)Thoroughness of preparationEmployment history (p<.05)Industry experienceManagement experienceEmployed experienceAgeEducation levelBusiness partners (p<.05)Ownership structureType of firmStart up capitalTurnover levelNumber of employeesBusiness activitiesLocation
Lee and Lee (2006) Traits of entrepreneur
Strategy and resource capabili-ties
Environmental conditions
AgeEducation level (p<.05)Start-up experienceRisk taking propensity (p<.05)Need for achievement (p < .10)Technology driven (p < .10, p < .01)Market driven (p < .10)Low cost drivenNumber of patent rightsRatio of R&D peopleTechnological cooperationNo. of experienced managerComplexityDynamismCompetitivenessSupports from Gov. (p<.05)Supports from Non Gov. (p<.05)
van Gelderen et al.(2006)
IndividualProcessEnvironment
Intended organization
Demographics - GenderDemographics - AgeHuman capital - Work experienceHuman capital - Management experi-enceHuman capital - Experience in firmfoundingHuman capital - EducationMotivation - Push motivation
131
Motivation - Ambition become richBusiness planInformation and guidanceFinancial - Third party moneyFinancial - Start-up capitalNetwork - Industry experience(p<.05)Ecological - Risk of the market(p<.05)Ambition to grow largeStart out part- or fulltime (p<.05)Techno nascentTeamIndustry type (p<.05)
Lasch et al. (2007) Human capital and working experi-ence
Pre- start-up activities
Post- start-up activities
General human capital - AgeGeneral human capital - EducationGeneral human capital - Startup fromunemploymentGeneral human capital - AcademicspinoffsFirm size of last employmentIndustry specific knowledgeManagement experiencePreparation activitiesExisting clients at startup (p<.05)Startup capital (p < .10)Firmsize at startup (p<.05)Founding team (p<.05)SubcontractorNew capital (p < .10)Type of clients (p<.05)Evolution of numbers of clients (p <
.01)Local marketNational marketInternational market (p < .10)Evolution of products and services -DiversificationCooperation
Song et al. (2008) Market and opportunity Competition intensityEnvironmental dynamismEnvironmental heterogeneityInternationalizationLow-cost strategyMarket growth rateMarket scope (p < .001)Marketing intensityProduct innovation (p < .001)
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Entrepreneurial team
Resources
Industry experience (p<.05)Marketing experience (p<.05)Prior startup experienceR&D experienceFinancial resources (p < .01)Firm age (p < .001)Firm size (p < .01)Firm type (p < .001)Nongovernmental fin. supportPatent protection (p<.05)R&D Alliances (p < .001)R&D InvestmentSize of founding teamSupply chain integration (p < .001)University partnerships
Lussier and Halabi(2010)
Success and failure variables Capital (desc.)Record keeping and financial control(desc.)Industry experienceManagement experience (desc.)Planning (desc.)Professional advisors (desc.)Education (desc.)StaffingProduct/service timingEconomic timingAgePartnersParentsMinorityMarketing (desc.)
Cardon et al. (2011) Misfortunes
Mistakes
Market forcesFunding (external)Financial (internal)TimingUnrealistic external expectationsBusiness model/planMismanagementUnrealistic internal expectationsHubrisFinancial (internal)Innovation
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C Interviews
C.1 Questions V1
Personal1. What’s your name?2. What’s your age?3. What’s your background?4. Did you always planned to be an Entrepreneur?5. What company or companies did you found or founded?
Company profile6. What the name of the company?7. What year was it founded?8. By how many founders?9. [8] What’s the background of the founders?10. What’s your role?11. What is your product?12. Is it B2C or B2B?13. How many customers do you have?14. Focus locally or internationally?15. Is it available on multiple platforms (e.g. Website, iOS, Android)?
[SHOW FRAMEWORK]
Startup Life Cycle16. Are you familiar with the four steps (Steve Blank’s - The four steps to the Epiphany)?17. At what stage are you know?18. Do you recognize the steps?
Factors related to the Investor(s)19. If you had to prioritize a top 3, what would be the most important factor? Do miss a factor?
Factors related to the Founder(s)20. If you had to prioritize a top 3, what would be the most important factor? Do miss a factor?
Factors related to the Startup21. If you had to prioritize a top 3, what would be the most important factor? Do miss a factor?
Factors related to Facilitator(s)22. If you had to prioritize a top 3, what would be the most important factors? Do miss a factor?
Factors related to External environment23. If you had to prioritize a top 3, what would be the most important factors? Do miss a factor?
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Factors related to the customer?24. If you had to prioritize a top 3, what would be the most important factors? Do miss a factor?
Startup Life Cycle factors per stage?25. In Discovery, what would be the 5 most important factors?26. In Validation, what would be the 5 most important factors?27. In Optimization, what would be the 5 most important factors?28. In Scale, what would be the 5 most important factors?
Startup Life Cycle factors per stage?25. In Discovery, what would be the 5 most important factors?26. In Validation, what would be the 5 most important factors?27. In Optimization, what would be the 5 most important factors?28. In Scale, what would be the 5 most important factors?
Hypotheses29. Hypothesis 1 (H1) Agree or not, why?30. Hypothesis 2 (H2) Agree or not, why?31. Hypothesis 3 (H3) Agree or not, why?32. Hypothesis 4 (H4) Agree or not, why?33. Hypothesis 5 (H5) Agree or not, why?34. Hypothesis 6 (H6) Agree or not, why?35. Hypothesis 7 (H7) Agree or not, why?36. Hypothesis 8 (H8) Agree or not, why?37. Hypothesis 9 (H9) Agree or not, why?38. Hypothesis 10 (H10) Agree or not, why?39. Hypothesis 11 (H11) Agree or not, why?40. Hypothesis 12 (H12) Agree or not, why?41. Hypothesis 13 (H13) Agree or not, why?42. Hypothesis 14 (H14) Agree or not, why?
General43. What’s your definition of success?44. What’s your definition of failure?45. If you had to pass 3 lessons learned to starting entrepreneurs, what would you pass?46. What the best advice you had ever get?47. What would you do different the next time?
Open48. Any open discussion or suggestions?
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C.2 Questions V2
Only the questions 29 - 42 of Questions V1 were replaced by:
Hypotheses29. Divide 100 by H1 and H2. Why?30. Divide 100 by H3, H4, H5, and H6. Why?31. Divide 100 by H7 and H8. Why?32. Divide 100 by H9, H10 and H11. Why?33. Divide 100 by H12, H13 and H14. Why?34. H15. When the combination of the factors of the resource availability is high, the startup ismore likely to succeed. Agree or not? Why?35. H16. When the combination of the factors of the resource availability is high, the startup ismore likely to succeed. Agree or not? Why?36. H17. When the combination of the factors of the founders performance is high, the startup ismore likely to succeed. Agree or not? Why?37. H18. When the combination of the factors of the startup performance is high, the startup ismore likely to succeed. Agree or not? Why?38. Divide 100 by H15, H16, H17 and H18. Why?39. H19. The combination of the 4 performance groups guarantees success. Agree or not. Why?
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C.3 Interview Transcript - Habitissimo.es
Interviewer: Dirk Jan MenkveldInterviewee: Jordi Ber, Co-founder and CEO of Habitissimo.es
Date and time: May 21, 2012Duration: 51:28Medium: Skype
– Start interview transcript –
Interviewer: First I’m talking about myself. My name is Dirk, I’m 28 years old and I’m studying at theUtrecht University. Now I’m on exchange here in Barcelona at the UPC.Interviewee: Ok.Interviewer: I had two choices what to do: one project from here and one project of my own and that is thisproject about internet startup. Because I was involved in an internet startup, in the Netherlands, it was AFASPersonal, it was a social personal finance platform. And, actually, in fours years time, I think we did almosteverything. From the seed investment, to a huge investment, to growing a big user base, and eventually anacquiry by a software company. So I know how it works, and that’s my experience. And with my experienceI can write something, yeah, for my thesis. And I think it’s really interesting to keep in this domain of internetstartups, and see what we can find out. And, see.. So, eventually I rolled up to this thesis I had. Well, I’mresearching: critical success factors for internet startups.Interviewee: Ok.Interviewer: And, so, that’s why I developed.. I did some research and I developed a framework and I justwant to talk about the framework with you.Interviewee: Ok.Interviewer: So, that’s it, with my experience, back in the Netherlands, it was really awesome. We didalmost everything. We also won awards, and we were in a incubator. I thought you were in Seedrocket?Interviewee: Yeah.Interviewee: So, I think it’s good to share some knowledge in this one and we can help other entrepreneursin the future.Interviewee: Yeah, absolutely. Ok.Interviewer: So, that’s basically it, it’s a short introduction. But, I think we don’t have a lot of time as yousaid so.Interviewee: I will talk about my background from my startup. But, 6:10 that would be my limit.Interviewer: Ok, good to know. Yes.Interviewee: Ok, I reveal my startup. Actually, I’m a civil engineer, I started civil engineering at UPC.Interviewer: Ah ok, it’s the same location.Interviewee: Ok, so I started there, and I had the opportunity to make a double degree, with I should spoiledsize. At the end of my study as an engineer I went to France for two years to get a diploma on management.That was in the year 2000-200, that was the dot.com bubble in the management school. So, it was a greatexperience to go abroad and to learn about the internet. And I should say I spent three years there. Andmy second year I specialized in entrepreneur. So, I did a workshop. And then I came back to Barcelona. Ifinished my final project. I try to start something at that time, but it didn’t work out. So, I decided to get a joband I got a job in a big construction Spanish company. And then, as an engineer I realize I didn’t match and Iwanted to look for information, I went to google, and, actually there was a gap, there was no information onconstruction. And, I sense an opportunity there, and after three years, I started to do something by my own, apersonal project, I had a blog, and a wiki, things like that. And then, I had this opportunity to go to the States,
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I went to MIT for a year, a full bright scholarship. And, there I learned about IT management and also en-trepreneurship. And finally, when I came back to Spain, that was 2005, I decided I want to startup something.At that time I had several ideas and I went for an idea that was more developed and that was a constructionwiki that I called Construpedia that later became Construmatica.com which is a project I co-founded with thehelp of grupointercom,Interviewer: Ok.Interviewee: A IT group here in Spain. [...] Actually, you should go and meet these guys.Interviewer: Yeah, that’s an idea.Interviewee: Because, they really are a hub and a kind of incubator and the model is interesting.[...]Interviewee: The CEO is Antonio González-Barros and you probably find videos.Interviewer: Alright, that’s fine, I will take a look at those.[...]Interviewee: So, actually, habitissimo is my second startup next to construmatica.com, it was a wiki for theconstruction industry in Spain with technical information for engineers and basically the experience was myschool as an entrepreneur.Interviewer: Yeah, I understand.Interviewee: And, in the end of 2008 I decided to startup again and I started habitissimo with my [...]Interviewer: O, you started with two? With two persons?Interviewee: Yeah, actually the first thing I, there are many mistakes made with construmatica. One of themwas that I co-founded with a partner that was not fully committed since the beginning of the project and that’sa typical mistakeInterviewer: Yeah, that’s one part of my framework which I’ll show you later.Interviewee: Ok.Interviewer: So, yeah, ok. Go on.Interviewee: And, the first thing I actually did when I decided I wanted to start another company after con-strumatica, because [...] with many other things and I look for a partner actually. I look for any, I needed anIT guy and I found Martin and we did a small project, a small side project just to know each other and to seewe could really work together.Interviewer: Yeah.Interviewee: And we decided to start.Interviewer: O, that’s a good idea.Interviewee: And, yeah, because if you marry someone you live together and ...Interviewer: Yeah, I understand. But, you’re than the more business and he’s more the technical man andthat’s how you started.Interviewee: Exactly. And, ok. We decided to take part of the SeedRocket incubator, because they’ve accel-erator things. And I knew a lot of people in Barcelona and know how to get to investors, but we believe if wegot into SeedRocket and we won the award we, it could be easier for us. I mean, the SeedRocket investorswould take part of the company, but that was a prize we were willing to pay.Interviewer: Ok, so may I ask you. If you go to SeedRocket, you get a seed investment?Interviewee: Exactly.Interviewer: And they provide kind of [?].Interviewee: Yeah, and they get a piece of the cake, yeah.Interviewer: Ok, ok.Interviewee: [...] if you take part and you win, they get some reward.Interviewer: Yeah, that’s logical.[...]Interviewer: About habitissimo, can you explain it to me in one sentence?
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Interviewee: Yeah, actually we help people find home contractors they can trust with user reviews. Withhome contractor I mean a builder, a plumber, an architect, an interior designer, etc.Interviewer: Yeah, I thought so, I know the, we also have Dutch version of this oneInterviewee: They have werkspot.Interviewer: Yes, yes, yes.Interviewee: How it work, I mean it’s the market leader there, right?Interviewer: Yeah, yeah, I think so. I really like the site, it look the same as yours.Interviewee: Yes, it a little bit different. I haven’t really taken a look to the website, because I don’t speakDutch. And there are also similar models like the German one, hammer.Interviewer: Hammer, yes.Interviewee: [?] in the UK. For me, it’s much easier to understand the business model.Interviewer: Yeah, but what’s your business model than now?Interviewee: Our business model is a lead generation businesss model. So, let’s say a house owner wantsto renovate the kitchen, they post a job description on our website, I want to renovate my kitchen, I live inBarcelona. The builders want to contact this guy to pass him a quote and they gonna pay us some euros foreach contact data.Interviewer: A, ok.Interviewee: So, our builder buys qualitatively data for that. So, it’s a guy who want to renovate a kitchenand they provide this service and buy contact data.Interviewer: Clear.Interviewee: So, for you evaluation, we’ve a banner, a CPC and that’s the next step. CPL.Interviewer: Yeah, kind of different models there. Alright, and, let me ask you, so, you started in 2008, whendid you go into SeedRocket and when did you launch your product?Interviewee: So, we took time to started out in 2009 with a prototype, within a business directory, and inApril 2009, we launched the product.Interviewer: On April the first?Interviewee: April the first.Interviewer: Of 2009?Interviewee: 2009, yes.Interviewer: Ok. ok. And did you got a lot of attention in blogs or ?Interviewee: Yes, and that was thanks to SeedRocket, so actually SeedRocket was on January, and we wonthe first prize.Interviewer: O, wauw.Interviewee: So, that gave at that moment some mentioning in the blogosphere and in the press.Interviewer: Yeah.Interviewee: Although we didn’t have a prototype, a working website yet, and when we launched on April,SeedRocket had a public event and we raised our first round a few months later and we got in to the pressthanks to SeedRocket.Interviewer: O, that’s perfect. Alright, clear. And, what next? How did you stay at SeedRocket?Interviewee: And then, we got our first customer on September of that year and was just to validate, I mean,afterwards we actually started to, how do you call it, a bootstrapping.Interviewer: Yes, bootstrapping, yeah.Interviewee: It is more like the Lean Startup Methodology which we like. Just trying to solving the equationonce at a time, you know?Interviewer: Yeah.Interviewee: So, with our product we had some traction and we had some people who were trying the web-site, and we had some leads, and it was completely free and our next step was to get some customers, and Istarted to do in inter sense myself on September 2009, and then we set up a team and we also wanted to be
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international from the very beginning, so we launched a Italian website and thus for us to do it was makingsure we were able to have a website in another language and we got some traffic traction there and our nextstep was to try and get some customers in another country besides Spain.Interviewer: Really good.Interviewee: So, this were the steps and the most difficult for us was to really escalate the business.Interviewer: Accelerate?Interviewee: Accelerate, yes?Interviewer: Ok, ok, but, yeah, I mean, you that’s what you say, in startups there are different stages.Interviewee: Yeah, in startup you’ve, what do you call it, pivot..Interviewer: Pivotting.Interviewee: I believe we’ve tried different business models that we propose to our customers, but we werenot able to escalate. We didn’t have time for giant growth. And, we finally found it last year, and we’re reallygrowing really fast.Interviewer: A, that’s good. Yeah, and that is how it works, I mean, this is the Lean Startup, you’ve totry different business models and if it doesn’t work, you try something else. I mean, if the platform is stillgrowing, that’s the most important part, there are still people seeking for constructors, and then you can getsomewhere, because, I think, with our, my startup experience, Yunoo, AFAS Personal, like mint.com, do youknow mint.com?Interviewee: Yeah.Interviewer: So, that’s the Dutch version of mint.com, and we had a big problem with our business model,but we were not able to pivot at the right moment. So, that was are main problem, so, at some point, we werejust spending a lot of money on product development, and getting users, everything, but there was no revenuecoming in, and then you have to make a decision, ok, how do we do this? Because, we can not go back tobootstrapping, we already had that, and we had a lot of employees. So, eventually, there was no way out, andwe had to sell it, it was a little bit crazy, a crazy time.Interviewee: We went through that too. I mean, we didn’t have the problem we didn’t sell, actually, onSeptember we were already selling, and actually we didn’t sell form the very beginning in Italy, or in Brazil,we also have a website, and has been a mistake, being so long without selling things. Because, you think thatcustomers are gonna fall from the sky and it’s not, I mean, the value proposition is perhaps still foreign whenyou’re trying to sell and another validator to that is find to sell something.Interviewer: Yes.Interviewee: To value what you, means that value what you offering to them, that’s why I miss favorites it.The biggest mistake with me, coming to [?], is that we really look at the grow metrics, we were looking atmetrics like users visits per month, like, you know, how traffic was growing, and that was not very high atthe beginning, and we did SEO and traffic was growing and when that stopped, everything fell down, and, soactually I mean, and we also have been in typical situations with money.Interviewer: Yeah, I can imagine. But, than you had only one investment of SeedRocket, no?Interviewee: No, actually at the time we raised money of [investor x], it’s a serial, actually it is a very wellknown business angel in Spain and they have invested in lots of SeedRocket startups.Interviewer: Ok.Interviewee: And, we got money from them, and this is like a super angel, and now it’s small business.Interviewer: So, this second investment was enough to..Interviewee: We got that on summer 2009, and next year, we also do a second round, on 2010.Interviewer: A third round?Interviewee: We started with our own savings, and then we went into SeedRocket, it was only e20,000, andthen we raised e100,000 from [?], that was 2010. So, 100,000 plus 20,000 plus our own savings, was 20,000more.Interviewer: So, after the 100K, more investments?
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[...]Interviewee: In 2009, the next year in 2010, we raised 100 more from [?]. And then we also raised, actuallywe got a loan from the Spanish the government, [...], and that was a loan, it was a 100,000 loan, by, we haveto give by 2014. Ok.Interviewer: Yeah, to be honest, we did partly the same, so we did our own savings, I don’t know how much,so, than we had the business angel investment, from 100,000 euros, and then we had the big investment of1,5 million euros, but it was, 1 million was like advertising, so it was from a big media company here, in theNetherlands, and after that there was no more rounds, we could have got an investment, but it’s a long story,and we don’t have time for that.Interviewee: I can imagine what happened.Interviewer: Yeah.Interviewee: I mean we were not growing, it was to passive, and we mean guys we have business for you,but we do not wanna invest anymore, because it isn’t growing.Interviewer: Understandable, than you’ve to do something else.Interviewee: We had to make some adjustment, we changed a few things, [...], only when you’ve a crises,you’ve to make the right decisions, and then we have to make choices and we focus and thanks to that webeen doing well enough.Interviewer: That’s really good to hear, I mean, at some point, you’ve to just get through.Interviewee: And actually, we just closed a new round.Interviewer: A, wauw.Interviewee: [...] But, soon we gonna make it public.Interviewer: Congratulations.[...]Interviewer: I will explain the framework. On the left side you see the life cycle, and you see differentfactors groups, and the performance of the startup, and that’s the most important part. So, on the left sideyou’ve, what you said, the Lean Startup, but also, do you know Steve Blank?Interviewee: Yeah, I know the name, I haven’t read it.Interviewer: Ok, on the left side I adapted in this framework his steps, the four steps to the epiphany.Interviewee: Epiphany, yeah, that say something to me.Interviewer: So, those four steps on left side, they influence per stage, I say, per stage there are different fac-tors that are more important for the startup to succeed. Yes. So, there are four stages, so, in discovery, you’regoing to test whether you’re solving a problem. So, you’re just talking to users, ok, is this something for you.And there are different factors important in that stage. For example, when you’re going to scale. Because,than you’re product market fit is better, you only need users, so you’re going to market. So, I assume that,so, right now, it’s not really important, because you’re my first interview, I just want to reflect this model.So, the second column, you’ve three factor groups, investors, founders and startups together, and a facilitator.Investors is clear I think, founders and startups also, [..], and the facilitators in your story is SeedRocket,so, it can be SeedRocket, it can be advisors, it can be an accelerator. And the third column, is the startupperformance, and startup performance is identified by KPI’s, what you said, I state its user acquisition andactivation. So, that’s important. But, they come back and have to tell others, thanks to the referral, revenue isimportant, and eventually, you want to make a profit with it.Interviewee: Yeah.Interviewer: In a normal case. So, than you’ve the founders performance. Well, that’s the skills of thefounders. And then you’ve the product / service performance, how its doing, awareness, product market fit,innovation, and many we can come up with some more. And then we have the resource availability. So,eventually, you need some hardware, software, open source, and also developers, designers are really impor-tant, I mean, marketeers and sales, and son on. And on the right side we’ve the factors related to the externalenvironment and to the customer. And also two groups, I think those are important.
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Interviewee: Ok.Interviewer: So, I adapted some papers and things and put them together in this model.Interviewee: Ok.Interviewer: So, first of all, I would like to ask you, going to the second column, factors related to the in-vestor. Can you / Do you recognize these factors, like what is really important to make the startup succeed?Interviewee: Ok, in my case, I think there a difference between smart money and not smart money. So, inour case, [investor x], is not smart money. So, for us, investors have money and that’s all we’ve got fromthem.Interviewer: Ok, but in your case. If you’ve to prioritize these three factors. What’s the most important?Interviewee: I would say capital.Interviewer: After that?Interviewee: KnowledgeInterviewer: And then?Interviewee: Resources.Interviewer: Ok, do you miss something here? Or is this all you think?Interviewee: I miss Network, but what do you mean with resources?Interviewer: Yeah, that’s included.Interviewee: No, that’s ok to me.[...] Interviewer: Ok, the same question for the second, so, the founders? [...] If you see this list, what doyou think is the most important factor related to the founder?Interviewee: Commitment.Interviewer: I think there’s no explanation needed. And second one.Interviewee: I mean if you’re really committed, and motivated, you can learn. If you make a mistake, youkeep trying.Interviewer: And the second one?Interviewee: The second one here would be, I would say competence. I mean its all about execution right?So, if you choose well, you succeed.Interviewer: I agree. And, another one?Interviewee: My third would be pivot / adaptability.[...]Interviewer: And, if we go to the factors related to the startup. Or do you miss something here?Interviewee: I would say, if you, you need a team, right, I think you need a team to complement each other.Ok, if you’ve two engineers, its not gonna work, I mean you need a sales guy, an IT guy, so it’s good if you’veone..Interviewer: A divers team or something?Interviewee: Yeah, I would say a divers team, to complement each other, you know.Interviewer: Yeah, I understand, in our scenario we were with four guys, it was one sales guy, one backender,one frontender, and it was me.Interviewee: Actually, our sales guy came one year later. And I wish we had him from the very beginning.Interviewer: Ok, yeah, that’s something you learn. Ok, factors related to the startup?Interviewee: The most important would be, I don’t know. Strategy, business model..Interviewer: Strategy go first?Interviewee: Yeah, strategy go first, even before business model. I mean because, you’re starting fromscratch, right, so I mean, how are gonna penetrate? So, I would put that first. And than the business model.Interviewer: Ok, and third?Interviewee: The third would be .. I don’t know. I think mission and vision, that’s something we value herequite a lot, it is something to help motivate the team. Yeah, I would say that.Interviewer: Ok, we go to the next. Facilitator?
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Interviewee: I would say network.Interviewer: Yes, and then?Interviewee: And then, experience and facilities, in that order.Interviewer: Do you miss something here? What can they offer more or what is critical? You can also thinkabout..Interviewee: Sometimes they even give you more, invested like in SeedRocket, sometimes they, perhapsother resources, like things with partners, they can provide you with web hosting, things like that.Interviewer: So, I should change experience to resources or something. I can think about that. Alright, so,than we go to the right, factors related to the external environment.[...]Interviewee: Ok, I, [pause], I think economical environment is important, and competitors is very impor-tant to. But, the thing is here, I mean economical environment is in our case, being in a crises, I think it issomething positive for us. Because, if we were two years ago, the construction move in Spain, we couldn’tenter that, we couldn’t get customer on the internet, they didn’t need more customers. And now, thanks tothe crises, they have reason to. At the same time, obviously, people don’t have a lot of money, it is positivefor us. And competitors are also important, because they also operate in the same market, and they are also asource of [?] of which you can learn. So, its really that, they are a competitor, but you can learn a lot fromthem.Interviewer: And the third one?Interviewee: The third one, I would say, perhaps technological environment. Otherwise we were not possibleto do, than ten years ago. There are types of technology available now.Interviewer: Yeah, and a lot of open source as well. Ok, and the customer?Interviewee: Customer, .., I would say first need, because all companies solve a problem for the need of thecustomer, so I would put need first. User satisfaction second. And network maybe third place. But, what doyou mean by network?Interviewer: Network I mean that they can provide new customers.Interviewee: Word of mouth, yeah, that would be the third. Yeah, you cover’s its need, they are happy withthe service and they would recommend you.Interviewer: Alright. So now you know the factors, and we’ve the startup performance that will come later.If you have to define, if you look at the startup life cycle, discovery you know. Validation, do you know whatI mean with that?Interviewee: Yeah.Interviewer: Ok, optimization is than, you’ve everything and now you’re optimizing until everything is re-ally working until its good in order, before you scale. So, if you have to define three factors in the discoveryphase, and you can choose anything from the framework, what would be the most important per stage? Intotal its twelve. So, first discovery.Interviewee: Discovery. I would say market fit. I can choose of all four blocks.Interviewer: Let me see, so actually the second column, and the fourth column.Interviewee: So, I can choose from he second and the fourth column from the factor groups.Interviewer: Yes.Interviewee: Ok, from discovery. You mean specific point, or you mean factor related to the founder orstartup. Sorry, I don’t what you want to do.Interviewer: Ok, in discovery, you’re trying to solve the problem. And there are some factors that are reallyimportant to do this, right? Now, you’ve a list of 30 - 40 factors, and what do you think are the most impor-tant, it doesn’t matter if it’s related to the founder, startup, external.Interviewee: Ok, the need.Interviewer: Ok, the customer need, he?Interviewee: Customer need yeah.
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Interviewer: And second? In your example of habitissimo, what was really important in that stage?Interviewee: Strategy.Interviewer: And then?Interviewee: And then, I would say the team, the commitment of the team.Interviewer: Ok. ANd validation stage?Interviewee: In validation I would say, competence of the team, business model, and, I don’t know, pivot /
adaptability, that would be third.Interviewer: And optimization. Sorry, before we go on, with your company I think you are in the optimiza-tion stage, no?Interviewee: Yeah, we are in between optimization and scale.Interviewer: In between?Interviewee: In between.Interviewer: Ok. Than, we, for three you can say that’s true, but four you can assume it will be true, yeah.Ok, so for three?Interviewee: I’ve to choose three again?Interviewer: Yeah, please.Interviewee: For optimization I would say user satisfaction, I would say, monetization, costs.Interviewer: And the last one?Interviewee: For scale. I would say network from the customer, I would say mission and vision, that’s some-thing I would assume. And costs again. That’s also something I assume.Interviewer: Yeah.[...] Interviewee: I’ve five minutes.Interviewer: Ok, than we’ll wrap it up, because I’ve more questions.. Maybe you can write it down later forme. Let me see, we are at question 27, and I’ve 46 questions. But, maybe you can. Because now its easy,you’re familiar with the framework. In between factors groups and performance from both sides, you seearrows. Those arrows are actually hypotheses.Interviewee: Ok.Interviewer: So, for example, for the factors related to the investor [...], you see hypotheses one, I say, butI’m not sure its true. The combination of all factors related to the investors positively influences the foundersperformance and therefore the startup is more likely to succeed. And I want to ask you whether you agree ordisagree with the hypotheses?Interviewee: Ok, yes.Interviewer: There are fourteen.Interviewee: I don’t agree.Interviewer: Ok, we don’t have time to discuss everything.[...] Interviewer: Maybe you’ve some feedback on the framework.Interviewee: Ok, when the first time I saw it, it looked complicated to me, a lot stuff, but that was my firstimpression.Interviewer: But, when we were working with it, it became more clear?Interviewee: Yeah, in all groups, in groups, yeah, it makes sense.Interviewer: So, eventually want I’m trying to do with this, is trying to talk to a lot of entrepreneurs with alot of experience and trying to identify the most important factors per stage.Interviewee: But, what I don’t understand is, why do you put the factor groups customer and the externalenvironment on the right, and not on the left?Interviewer: Actually, it is possible to put it on left. But, the investor, the founders, and the facilitator arealso really close to each other. Yeah, you can see the combination.Interviewee: Yeah, I understand.Interviewer: But, I think I need to add an arrow in between customer and the startup, I think that’s an impor-
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tant one.Interviewee: I would like all factors groups together, I don’t understand. Perhaps you can, you have to [...]Interviewer: I understand, but in a startup there are different kind of connection, so the investor, the facili-tator, the external environment, those are really important. And I adapted another framework and that’s thereason I think and I mapped it into that one, but maybe I can switch a little bit. That’s an idea. But, I’ve tofigure out how that work.Interviewee: I mean, partly I understand, everything will be in a graph like this one, in this conceptual frame-work. I think you really have to work on the design of this, just to make it sexy.Interviewer: Yeah, of course, but than you’re talking about presentation for everybody. But, this is morescientific.[...]Interviewer: But, it will lead to a top important factors per stage, in total 12, for entrepreneurs, ok, take careof this and this, make sure that works, and then you continue going.[...]
Unfortunately, we didn’t have time to finish, so last questions were answered by email:
General28. What’s your definition of success?To have a purpose and succeed in that purpose, AND to be happy.To give back to society.
29. What’s your definition of failure?Not learning anything.To be selfish
30. If you had to pass 3 lessons learned to starting entrepreneurs, what would you pass?Do something you’re passionate aboutHave a purposeBe humble and try to learn every day to be a better entrepreneur, manager, person...
31. What the best advice you had ever get?Do what you think it’s right for you, not what others think is right for you. Live your own life, be yourself.
32. What would you do different the next time?Follow the lean startup method, and talk to customers before and more often
Hypotheses 33. Hypothesis 1 (H1) Agree or not, why?Yes
34. Hypothesis 2 (H2) Agree or not, why?No, too much capital might be harmful.
35. Hypothesis 3 (H3) Agree or not, why?Yes in the case of the Founders factorsNot in the case of the startup factors. Having a good business plan does not mean the startup is going tosuceed. The mission / vision / strategy / business plan can also be wrong...
36. Hypothesis 4 (H4) Agree or not, why?Yes
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37. Hypothesis 5 (H5) Agree or not, why?Not, for the same reasons desribed in question 35
38. Hypothesis 6 (H6) Agree or not, why?No, I think it’s mostly unrelated
39. Hypothesis 7 (H7) Agree or not, why?Yes
40. Hypothesis 8 (H8) Agree or not, why?Yes
41. Hypothesis 9 (H9) Agree or not, why?No, external factors can harm the startup performance but I do not believe they all can improve it. Forinstance, too much media attention might prove a distraction, overconfidence, etc.
42. Hypothesis 10 (H10) Agree or not, why?No, I do not think the external factors have so much influence. These external factors can harm but I do notbelieve they positively influence.
43. Hypothesis 11 (H11) Agree or not, why?Same answer: No, I do not think the external factors have so much influence. These external factors can harmbut I do not believe they positively influence.
44. Hypothesis 12 (H12) Agree or not, why?Yes
45. Hypothesis 13 (H13) Agree or not, why?No
46. Hypothesis 14 (H14) Agree or not, why?No
Open45. Any open discussion or suggestions?None
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C.4 Interview Transcript - GuideGuide.com
Interviewer: Dirk Jan MenkveldInterviewee: Christof Damian, Co-founder and CTO of GuideGuide.com
Date and time: May 31, 2012Duration: 1:09:46Location: Restaurant bar
–Start interview transcript –
Interviewer: I would like to ask you. So, I introduced myself. Who are you? Little bit of your backgroundand what did you do?Interviewee: Ok, I’m Christof Damian, and I’m from Germany. I went to school in Germany, I went toUniversity. But, during University, around ’94, ’95, I was, I noticed that the internet was taking off, kind of,and I wanted to be a part of it, and I started already websites, and stuff like that.Interviewer: Really? So, you started learning HTML and that kind of stuff?Interviewee: Yes, really early stuff, just as a hobby, not from the university side, they didn’t use it.Interviewer: What was your education?Interviewee: Computer science.Interviewer: So, there were no courses like..Interviewee: Not at that time.Interviewee: No, there was no internet at that time. First web browsers, Gova, and ILC, and [...] Mosaicmight be before Netscape and Mozilla. So, I was not happy with the University. It was very theoretical,for me there was no connection to the real life, because there was no information about the internet. Allthe programming was in my free time, and the University was about mathematics, physics, and not so muchabout computers.Interviewer: But, not in BASIC or something, like that, or standalone applications?Interviewee: Just in my free time, or working at the university, but not in the substance, in the beginning itwas just theory, and it takes quiet long to study. So, I decided to stop my studies. And then, just one or twoyears later, friend of my brother called me from London, and had a problem with this website, he had alsoa very early website, and I was able to fix it remotely, and then a day later he said, why don’t you come toLondon and work for me? So, ok, [...], I went to London and he also saw that the internet was taking of andhe had a small kind of web agency and made websites for other companies like for the French embassy, forthe German embassy in London.Interviewer: Can I see those websites as static pages?Interviewee: Yeah, in the beginning they were completely static. And, than when I saw, I helped him outwith that, but there were some dynamics, like guestbook, and contact forms and that kind of stuff.Interviewer: Yeah.Interviewee: But, over time it developed, because we wanted to develop quicker and got more dynamics, andhad features like CMS, that the client could change the information themselves and continued like that, but,em, my friend who is the business side, and really the entrepreneur of the company, he was not happy withthe company, because it was just a project based company, so you’ve a project, and work on it for a couple ofmonths. And after that you forget it, and also the companies maybe just go to a different company. For themit means not much investment and don’t have a connection with you, because they can just switch the websitewith someone else.Interviewer: Yeah.Interviewee: It’s just a marketing website for some companies. [...]. You can’t really, you build on it, you
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don’t gain in speed, if you build 10 websites, the 11th one might be not easier, because it’s completely newdesign, new features, and so on, so you can’t grow really. You can just grow by employing more and morepeople doing the same work, in parallel.Interviewer: Yeah, at that time of moment, it was actually presenting your company on the web, there wasno more, right?Interviewee: It was really easy to get business, you just had to go to companies and ask do you want awebsite? Yeah.Interviewer: I believe, everybody was seeing the potential, and that’s why eventually everybody wanted toinvest.Interviewee: Exactly. [...] So, in the end we decided we needed a product that we want to sell and from thatcompany we started a new company with we employed another developer, a designer, and the product was,the idea was that everybody wanted to be on the internet, but it was very expensive to have a website like forreally small clients.Interviewer: Because you had to buy servers, computers, or?Interviewee: If we sold website, it was a couple of thousand pounds, and for a shop around the corner, itwas too expensive. Especially if you don’t know whether the internet is really taking of, because it was likebefore 2000, people had not really, they were using modems, and it was really.. [...] So, we, the idea was tohave just, we started with restaurants to sell the restaurant website to a restaurant, which was standardized,but they were able to change, standardized was on a template, and they were able to put there own images in,and colors, and change the content.Interviewer: Nice.Interviewee: And, to make it even easier, because lot of them didn’t even had internet, we sold them a littlebox, like a plastic box, nicely designed in London, which contained a camera, through away camera, a coupleof forms where they put in all the information specific to the restaurant, and an envelop to put all this in andsend to us, and we would automatically scan this.Interviewer: Ah ok, because nobody had a scanner and there was no digital cameras of course.Interviewee: Yeah, it was just cameras, so we had to deal with a photo developer and they developed it andwe scanned automatically the things. And, from that stage we produced the website. So, that was the idea.[...]Interviewer: This was guideguide.com. Let me ask you, you founded the company with somebody else,with the two of you.Interviewee: Yes, he was the business guy, and I was the technical guy.Interviewer: So, you were responsible for all HTML, and setting up the server, ..Interviewee: At the beginning everything.Interviewer: And, did you stay up to date of all new things happening, like the new update of HTML, orother languages in development?Interviewee: I always learn online this. All information I get online, and I still learn now, every day I haveto get, lots of blogs, and twitter, mailing lists, being involved in open source projects.Interviewer: With the two of you, what age were you back then?Interviewee: In 1999, i was 30, his colleague was 24. And the same time he was going to the EuropeanBusiness School in London.Interviewer: A ok, he was along his education, he decided he wanted to start this company.Interviewee: Exactly.Interviewer: And formal stuff, you went to the chamber of commerce there to register?Interviewee: Yeah, he registered, first it was called Media Consult Limited in the UK, and later GuideguideLimited was only registered in the UK. In Germany we also had Guideguide ED, because we were targetingthe German market for the restaurant thing, so Marketing and Sales were in Germany, headquarters were inEngland.
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textbfInterviewer: So, guide guide is offering a website, web portal to restaurants, that was the idea.Interviewee: The first part was a personalized website for the restaurant, and obviously, when you have acouple of hundred restaurants, it also makes sense to have a portal for the restaurants, and it makes sense toget some kind of sponsor, main sponsor for the portal. In the beginning we had some sparkling water, or beercompany, sponsoring the portal. The portal was called gomee guide by [?]. The paid us a big sum, to havethe full like, we didn’t have like banners, there were no google adwords at that time. So, there was no, wehad like one sponsor who gave us a lot of money and they all had advantages, they had direct contact intothe restaurants. Because, suddenly they had a new way for a business relationship with a couple of hundredrestaurant that might not been targeted before.Interviewer: I understand.Interviewee: And, that was kinda working. So, we had some investment money from some friends, and alsomy partner had good connection in Germany to get money, so we had some investment, I don’t exactly thenumber, but it was enough to finance the office in the UK, and a small office in Germany.Interviewer: Ok, so, when you started this, the pie was 50/50 I think, and then a investor came in, a Germaninvestor?Interviewee: No, before it lower, because I didn’t put any money in. I just put in my knowledge.Interviewer: Ok, that enough for you to get 50% of the company, or how did it work?Interviewee: No, it was not enough for me, there was quite a bit of investment already.Interviewer: So, you got a small piece?Interviewee: Exactly.Interviewer: Ok, that’s good. Than, you were saying he was the real entrepreneur, but than he made thedecisions?Interviewee: He made the business decisions, he listened to my input, but I was responsible for the technicalpart.Interviewer: Ok. First, about the business model, [...], restaurants paid a one time fixed fee, or?Interviewee: No, a monthly fee, a setup fee, and monthly fee. It was something like maybe 40 GermanMarks setup and 20 Mark a month fee.Interviewer: Alright.Interviewee: But, the big money came from the sponsor, he paid maybe XXX,XXX Marks, he had his nameon the portal.Interviewer: But, that was a sponsor like, do you mean a money company, like a venture capitalist?Interviewee: No, it like advertise, like [?], a company related to restaurant, which they had their name on theportal.Interviewer: Ok, that was the idea. But, they also got, but they didn’t had shares of the company, than?Interviewee: No.Interviewer: But, the private money came from a company in Germany?Interviewee: Yeah, private.Interviewer: That was only one investment?Interviewee: No, that was from the family from my colleague, also contacts they had.Interviewer: Ok, it was one time in the history of the company? Or multiple times?Interviewee: It was multiple times. First setup.Interviewer: Ok, you began with the setup. That was in 99. And then, the second time was?Interviewee: Every year we got some money.Interviewer: Ok, and when did the business model started to work? When was the money coming in? Atwhat point?Interviewee: Well, we started, the first customer, and also when the sponsor.Interviewer: Ok, when was time of the first customer and the sponsor?Interviewee: I think it was a year after we started developing the product. Something like that.
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Interviewer: That was the first customer?Interviewee: No, the sponsor.Interviewer: And the first customer?Interviewee: The first customer was quiet quick, shortly after we got the system running, a few months after,first, we had test customers, people who directly contacted us, and afterwards, it slowly..Interviewer: Yeah, so restaurant were saying to other restaurant why do they have a website?Interviewee: Exactly.Interviewer: Also for your colleague to go the restaurants and sell the product?Interviewee: Yeah, and we also started employing sales people in Germany.Interviewer: Yeah, but first you started in the UK, if I’m correct, and after how many times did you expand?Interviewee: We wanted to target the German market.Interviewer: The UK market and the German market?Interviewee: No, just the German market. The UK was just development, and design, and that kind of stuff.So, we never targeted the UK market.Interviewer: Ok, your office was in the UK.Interviewee: Yeah, and then we opened a office in Germany, where all the sales and marketing, and latercustomer support.Interviewer: Ok, customer support as well. You were in the UK, because the previous company where youworked for, was there. And you met this guy there, and he was still on the Business school and that’s whyyou start development there.Interviewee: Yeah, and he also found that it was to easier to get, he was really interested in design, in productdesign, and he founded easier to get in London, higher quality maybe, and also later we found it easier toemploy developers in London than in Germany, because in German it’s spread all over in Germany, and itdidn’t convince people to move somewhere else, and at that time it was really difficult to get developers, therewere no so many around.Interviewer: There were no good developers, or?Interviewee: In London it’s completely different, with ten million people, which is, everybody lives aroundthe corner, all the companies develop..Interviewer: How were you seeking for developers than? Universities, or how did you..Interviewee: For us it was through contacts, and then later we used companies to recruit to do the pre screen-ing, and they brought us developers and we did the interviews, and we employed them.Interviewer: And the every age of the developer back than, was?Interviewee: Young, 20-24.Interviewer: And was the knowledge of the developers?Interviewee: We had pretty good people, and on average it was good. I think than even it developed evenquicker. Everything was new, so there were changes in technology all the time.Interviewer: It still is, it goes really fast. Wow, really interesting story. Ok, So, the customers coming inafter two years, and what happened after, so we’re now in 2001, so what happened than? First employeescoming.Interviewee: Yeah, we had employees and then we started, one of the main income was the sponsorship. So,the idea was to spread into more different portals. I don’t know exactly which one we start. Barbershops, orhair cut shops, I think. And the idea was to sell it to one of the shampoo brands. And then we had a contact to[?], they do tools. A really large German company. They really liked the idea, and what they wanted to wasnot have one handyman portal, they wanted one for woodworkers, one for roofers, I don’t know, the different.Interviewer: Of course.Interviewee: They wanted to have different portals, they wanted 8 or so.Interviewer: So, you guys managed, after the restaurants, the barbers, ..Interviewee: And, we had setup, yeah, we had to develop eight, at the same time, and that meant employing
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more people. And, also a lot money from [?], because they paid a large sum for all of these, and also expand-ing the German office, because we employed more sales people, to directly sell to the shops. And also weneeded a larger customer service department. Clients had problems with their computers.Interviewer: And, in number of FTEs, how big was your sales department getting?Interviewee: I don’t know the exact number. But, ..Interviewer: 10, 20, 30? 2?Interviewee: I think at the high time we had 18 developers in London, and some support people, and inGermany all together 60 or 70 people which was plot into sales, support, and marketing.Interviewer: So, there was a lot of personnel to pay?Interviewee: Yeah.Interviewer: I mean, for shops coming to contract, to provide a website, and pay a monthly fee, it was tocover the costs?Interviewee: No, it was not covering the costs, it was a lot of money, for the developers, and for the market-ing people it’s quite expensive.Interviewer: Ok, but than you were still making costs over 2 years.Interviewee: Yeah, it still costs money, so, we had more investment coming in, some private investors, andthey, also we had support from the German, sometimes you get deals from the, innovation things. If you getinvestment, they give you the same money, also investment something like that.Interviewer: Ok.Interviewee: So, we got a lot of money for that, but obviously at that time, it was already past internet crash.Interviewer: But, than investors were holding back, and people..Interviewee: Investors were holding back, the shops themselves, they were holding back, obviously, andalso, marketing departments form big companies that would sponsors, and they also, they thought all internetthings, but that didn’t worked out, so we stopped all of that.Interviewer: Ok, but in what time was this, in 2000..Interviewee: Em, that was 2002, 2003.Interviewer: And then you also had to fire people?Interviewee: We had to fire a lot of people. At one day I had to fire 5 developers. That was really bad, Imean they were direct colleagues, I worked with them, and yeah, I had to fire them. Yes, than over the time,I had to more and more people. Nearly nobody was left. And, in Germany they also fired a lot of people. Wereduced the size of the company very much.Interviewer: So, but at the high time it was 50 people or more?Interviewee: Altogether it was we were with 80 people, the whole company.Interviewer: And after the crash?Interviewee: After the crash it was in London maybe 5, and in Germany 20.Interviewer: I mean the product was ready, it was more like maintenance..Interviewee: Yeah, everybody liked it, it was not enough, you’ve to sell a lot of that stuff to be successful tocover costs. I think one of the main problems was that at this point we grow to fast, you want 8 things, wedon’t have enough people, we do 2 now, the next three months, and then.. But, keep the company size thesame, than it would be more possible, we wouldn’t have the time to invest. And also in the UK it’s quiet easyto fire people, and in Germany it’s quiet difficult, you’ve some really long running contract, especially salespeople, and, you want to get rid of them, but you can’t, you’ve to pay 1,5 year extra. We had lot of costs thatwe couldn’t get rid of, and that was a big problem.Interviewer: Ok.Interviewee: We also, my colleague, also employed a new CEO, because he thought, he had more experi-ence, but that’s obviously too late..Interviewer: But, at what time you changed the CEO? After the crash?Interviewee: Around that time.
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Interviewer: And the new guy came, and he made some changes?Interviewee: No, he didn’t really make changes, it didn’t help, and he left after a year or so.Interviewer: Really? And then? I mean we are in 2004 or something.Interviewee: Yeah, at some point my colleague also left the company. And then, his father continued themanagement. He’s very experienced manager in Germany.Interviewer: But, he had no technical background, or?Interviewee: He’s from technical companies, not internet companies, and 2004, the UK office was nothingleft, I decided I could work from home, and if I can work from home I can work as well from Spain. So, Iwent to Spain.Interviewer: So, by than, you had some customers left.Interviewee: Yeah, the website was in maintenance mode, we didn’t do new development, we just did likebug fixing, and then I decided with two more developers..Interviewer: But, than you were with three left?Interviewee: Yeah.Interviewer: In 2004. It was enough to pay yourself by then?Interviewee: It was alright, and then, we basically we closed the UK office. And, at some point, I moved toBarcelona, and work from here.Interviewer: Ok, and when did you decide to close it?Interviewee: Not close, at some point, it went bankrupt, in bankrupt proceeding. It was 2006 I think. Justbefore it went bankrupt I also left the company, and something else bought the company, so it’s still running.Interviewer: It’ still running?Interviewee: But, obviously it went bankrupt, he bought it without debt of the company, and for, I don’tknow how many clients we had, maybe 4,000 clients, which pay 10 or 20 euros a months. Which is a niceincome, it easy for covering the costs. I think they did little changes. I don’t regularly look on it. But, it isstill running anyway.Interviewer: But, it’s than.. The URL is? guideduide.de?Interviewee: Guideguide.com. [...] It works, I’m not involved anymore, one of the ex-programmers stilldoes freelance work for them, otherwise I’ve no connection to it.Interviewer: Wow, interesting story, I’ve a lot of questions, but I’ve to show you my work. Otherwise wedon’t have time. But, what do you do now than?Interviewee: After guide guide it was quiet stressful thing. [...] You work a lot of hours. So, in Barcelona Idecided the best thing is just employed work.[...]Interviewer: That’s what I wanted to ask. I mean, with the company you started your own. How did youmanage to lead the teams? Go from the only technical guy to managing everybody, maybe different develop-ment teams, and what software development method did you use?Interviewee: Well, you learn with a lot of mistakes. And, in the beginning it was standard, like waterfall, andwe planned a lot. And at the end, it was not enough. Later, we switched to extreme programming, more likean agile development process. And, than we integrated more and more..Interviewer: Extreme was in pairs, no?Interviewee: Yeah, pair programming, it is also like scrum. Extreme programming have some overlaps, shortcycles, and testing.Interviewer: And how short was the cycle when you were in the waterfall development?Interviewee: It was months, maybe 3 months. The whole design of the portal, and then we delivered it withthe client and took care of it.Interviewer: Interesting.Interviewee: And, with management, you learn. I think the most difficult part in the beginning was likeemploying people, and doing the interviews, and like firing again. But, also programmers are quiet difficult
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to manage, because they don’t really like to talk.Interviewer: Yeah, I know.Interviewee: It is difficult also to delegate. Like, with 20 people to manage, you can’t manage them all, youneed 2 or 3 people to manage, you need volunteers, and nobody volunteers.Interviewer: But, than you’ve to hire some programmers with some managerial experience.Interviewee: We tried it, but it was really difficult at that time.Interviewer: Really interesting. I had the same. I didn’t know scrum, and before I knew I had two develop-ment teams under me, and I always had to keep them busy, but I also was the CFO at that point. So, I neededto do that. Product management, writing requirement, and then coach the guys, that’s really difficult, I mean,but still if you want to communicate with developer.Interviewee: Did you also have the tech guy on your team?Interviewer: Yes, that was perfect. We were with four of us, one frontender, one backender, there was me,more the product manager, and one sales person. It was a really good team. I think we go to the next phase,[...]. So, I developed a framework to identify the critical success factors. I’ll show the framework right now.It looks scary, but it isn’t. I’ll explain it. On left side you’ve the startup life cycle. Do you know Steve Blank?Interviewee: No.Interviewer: He’s a guru from the United States. He had several, involved in several startups, 8 or something.He now teaches at Standford, Berkley, and something else. And he defined four steps, for a internet startup.The first step is discovery, what problem are you solving and for who? And you’ve to provide a solution. Thesecond phase is validation, validation is when you develop the solution and go out and see whether they’rewilling to use it, and whether you can make money of it, so, you start also discovering a business model. Andthe third stage, is than, now we’ve it working, and we know this is going to work and you can optimize yourprocesses over all business. And if you’re done with that, you can go and scale your company. So, everythingis ok, now you need sales and marketing to really get it to the people, you know. Is it clear to you?Interviewee: Yeah.Interviewer: So, I think, per stage.Interviewee: It’s quiet overlapping.Interviewer: It can be, but we’ll see in your story. Maybe discovery and validation. Optimizing and scale.He defined it as really, so in optimizing for example you make more the company, scaling is making it re-ally big, and make departments, you know. So, I believe over time, in these stages, they’re different factorsimportant, so I’ll ask you later. But, than with a startup, in the beginning you’ve the founders, and you’vethe startup. And this is a really important factor group, with founders, they should do commitment in orderto succeed. But, for a startup it can be your strategy that is really important to succeed. When we look atthese two, the investor can be important, but also the facilitator, a facilitator can be an advisor, it can be anincubator, it can be an accelerator, so those are connected. And on the right side we’ve the external environ-ment, a technical environment, [...], social environment, political, competitors, etcetera. And then we’ve thefactors related to the customer. Eventually, you need the customer to buy your product or service. So, thesefactors influence the startup performance, the company performance, the founders performance, the product/ service performance, and the resource availability. So, with resources I mean hardware, software, people,designers, developers, sales, marketeers, etcetera. So, this is basically it. I want to found out the relations, andeventually I want to look at the, per stage, and what will be the critical factors for the startup performance.So, is this clear to you? How it works?Interviewee: Yeah, I think I understand the areas.Interviewer: Ok. [...] First, I would like to ask to you, if we take a look at the investor, in your companyyou had some investment rounds, you see three factors here, capital, resource, and knowledge. What do youthink, if you had put on the front, is the most important for an investor to provide to a startup to you?Interviewee: Capital. Possible, no knowledge. Knowledge of the investors gets in the way.Interviewer: Ok, capital is the most important, and the second most important would than be?
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Interviewee: Resources.Interviewer: Resources, and the third, than? There’s no other choice.Interviewee: Knowledge.Interviewer: Knowledge in your case.Interviewee: If they think they have the knowledge, but the investor wants also to force this into the startup,that’s really difficult. A problem with the founders you say, because they’ve the idea, especially early on, theywant to change, than it’s really, it gets in the way.Interviewer: Yeah, I understand. And, do you miss something that seems to be important to investors, fromyour perspective?Interviewee: I think there’s an overlap between investors and facilitators, because the investors also providenetwork, I think.Interviewer: Yeah, that should be the same as the resources. That’s the thing. And maybe something else?Or do you think this is..Interviewee: NoInterviewer: Alright, the same question for the second part, the founders, if you had to pick the most impor-tant part, for you and colleague, what was most important for success.. In general, what was most important?Interviewee: I think most important was the vision.Interviewer: The vision, yes. And the second most important?Interviewee: The motivation.Interviewer: And third?Interviewee: Commitment.Interviewer: Alright, and do you miss something here. When you think of your founding team? If not, wego on.Interviewee: Overall, the background a little bit.Interviewer: Background, so you mean the division in the startup team? So, you were the CTO, and he wasthe business man?Interviewee: No, the experience we gained through the previous company, but also the experience we had,like where we coming from, like shaped.Interviewer: But, that is more like working experience, or experience in general.Interviewee: Experience in general.Interviewer: We can leave the work from experience and make it experience, what is important for founders.Alright, next one for the founders, we had the life cycle, business plan, etcetera. If you take a look at the list..Interviewee: Mission and vision again, is the most important thing.Interviewer: Mission and vision yes, and then?Interviewee: And, the business model.Interviewer: Business model second, and the third?Interviewee: Em, the network.Interviewer: Ok, and when we take a look at the facilitator?Interviewee: Network, facilities, and experience.Interviewer: Ok, do we miss something here for those two?Interviewee: No.Interviewer: Alright, than we go to the right, the external environment. Political. economical, social, tech-nological, competitors, partners, media attention?Interviewee: Em, economical environment is the most important?Interviewer: And then?Interviewee: Competitors.Interviewer: Yeah, and then?Interviewee: Technnology environment.
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Interviewer: And the customer?Interviewee: User satisfaction.Interviewer: Yes,Interviewee: What do you mean with contracting?Interviewer: The same as, ok, if he wants to be a customer, than, you can provide them the details to become,it’s like you contract the customer.Interviewee: Ok, second, is the need. And third, contracting.Interviewer: Ok, thank you. Alright, so, now I want to take a look at the top 3. You’re familiar with allfactors, you saw everything there. Now, I want to look the first stage. It was just you and your partner andyou had an idea. What was the important factor, top 3, in that stage?Interviewee: In the beginning the vision was the most important thing.Interviewer: Yes, vision.Interviewee: And, motivation.Interviewer: Yes.Interviewee: And network.Interviewer: And in the second stage, where you, try the business model, you build the company, you buildthe product, you’ve the first product.Interviewee: Commitment.Interviewer: YesInterviewee: Environment in London. It was technical, but also social, like which helped developing theproduct.Interviewer: So, social and technical enviroment.Interviewee: And, still the networking.Interviewer: Ok, and for the next stage. You had your product, your business model was working, you’reoptimizing, more employees, in that stage?Interviewee: Capital.Interviewer: Capital, yes.Interviewee: And still, motivation.Interviewer: Of course.Interviewee: And, also the user satisfaction of the product.Interviewer: Alright, and in the last one, the scaling one. So, more marketing, more customers.Interviewee: Capital.Interviewer: Yes.Interviewee: And, the business model. And technical background.Interviewer: Technical background of the founders?Interviewee: Yes, because, before you’ve no customers, it’s easy, it you have to scale, more users, the tech-nical part becomes important.Interviewer: I understand. Thank you. And now. You see the arrows, dependencies in between, you see14 hypotheses. So, actually I wrote the down. I’ll explain the first one. So, hypotheses one, says that: thecombination of investors factors, altogether, positively influences the founders performance. Do you agree ordisagree?Interviewee: I don’t really think it influence the founders performance,Interviewer: Why?Interviewee: Because, the founders are more interested in the vision of the thing, they the money, but theystill want to do their thing. They don’t want to really.Interviewer: They still want to execute the...Interviewee: If they get more capital, it make it easier, but they don’t get any capital, they would still, be-cause of the vision.
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Interviewer: Clear, and altogether, these factors influence the resources availability. Hardware, developers.Interviewee: Yes.Interviewer: You agree upon that?Interviewee: Yes.Interviewer: So, they make it easy..Interviewee: Easy to facilities, find developers.Interviewer: So, they also had a network for you guys.Interviewee: Yeah, and the money helps?Interviewer: Alright. Hypotheses three. So, all theses factors combined, for the founders, and startup, havea positive influence at the startup performance. Do you agree or disagree?Interviewee: No, I agree.Interviewer: Ok. And for the second one, the founders performance, do you agree that these factors, thecombination of these factors, influence the founders performance?Interviewee: Yeah.Interviewer: And, also the product / service performance?Interviewee: Yeah, more or less?Interviewer: More or less. Yes or no?Interviewee: Yes.Interviewer: Why?Interviewee: Yeah, I think it’s, the vision and commitment is important for this. Vision for innovation andmarket fit for commitment, and software development.Interviewer: Alright, and the last one. The resource availability. Do they influence the resource availability?Interviewee: Yes, because you’ve, vision, it’s also easier to get developers, and also if you can convincesomeone of your vision, you can get that stuff.Interviewer: Yes. It’s kind of a job creation. And then the facilitator, positively influence the founders per-formance and the resource availability?Interviewee: No.Interviewer: Disagree, why?Interviewee: I don’t think the network nor experience, for us, it doesn’t really help.Interviewer: Ok, and resources availability?Interviewee: Yeah. The networking.Interviewer: Alright, than we move to right. So, the external environment, positively influences the perfor-mance of the founders, product / service, and resource availability? Nine, ten, eleven.Interviewee: Nine, no. It wouldn’t say it has an influence. And, yeah, because. They change with the exter-nal environment. And, the same for resource availability also. For example, when the dot.com crash came, itwas really easy to get developers.Interviewer: Ok, so they were all out of job.Interviewee: Yeah.Interviewer: But, before, the dot.com?Interviewee: It was really difficult, it was really expensive.Interviewer: Difficult and expensive. Ok. Than, the customer positively influences the startup performance,the founders performance, and the product / service performance?Interviewee: I would say yes. Yes to all of them.Interviewer: Alright, clear. Ok. I think we’re almost done here. I only have some general and open questionsleft.Interviewee: Ok.Interviewer: So, if you had to pass on, three lessons learned, to other entrepreneurs, what would you say?What advice would you give them?
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Interviewee: In any way possible, don’t get investment money, try to grow with your company.Interviewer: So, that means you’ve to, you need to have a business model working from the beginning?Interviewee: Exactly.Interviewer: Or other money?Interviewee: Yeah.Interviewer: Bank loan.Interviewee: Yeah, all money. I mean, two guys, cannot make money, just keep it that way until you makemoney. And then employ something else. Once you start making money, employ more people, not beforethat.Interviewer: Ok, but that’s different rule.Interviewee: No, like, grow with your company. Because, another way to grow is with investment.Interviewer: Ok, that’s one, and second?Interviewee: Don’t plan too far in the future.Interviewer: Ok, and the third?Interviewee: Don’t care about the competition.Interviewer: Good one. And was the competition?Interviewee: In the beginning there was no so much. But later, there were different, like build you ownwebsite, software packages, and upload. And also host your own website for 1,99, something like that. And,others, it’s not, the market is so big, it is not important, the competition. You just have to sell to the peoplethat buy your stuff. There’ll always be like high-end product, low-end product.Interviewer: Alright, and, what is the best advice you ever got from somebody else?Interviewee: I think, also, grow with your company.Interviewer: Ok, and last one, if you had to define success, and failure. What would be a success for youand a failure?Interviewee: I think, continuous growth.Interviewer: Continuous growth is success?Interviewee: Yeah.Interviewer: With that you mean, the company is growing, the customers are growing, or revenue is grow-ing, or profit is growing?Interviewee: No, the company is growing. Doesn’t have to be profit.Interviewer: And failure?Interviewee: The opposite.Interviewer: Failure, you mean..Interviewee: The company shrinks. But, also if you loose your, you can’t implement your business model. Imean, you can still be growing, but it is not the thing you want. Than, it is also failure.Interviewer: That maybe was the thing you [?], or wasn’t it?Interviewee: I think, for me..Interviewer: Or, was it more the shrinking of the company?Interviewee: Yeah, I didn’t see, it was the shrinking, and, my partner already left, and I already stayed. Thewhole was mine, from the beginning I moved to London.Interviewer: It was a long time?Interviewee: Yes.Interviewer: I think that was it.[...]Interviewee: I think the most important thing is the motivation and the vision of the partners. Everythingelse doesn’t really matter. If they really want something, they can do it. You learn what you need, you get thepeople you need, you can convince people if you’ve the right vision.Interviewer: I agree upon it. [...]
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C.5 Interview Transcript - ChangeYourFlight.com
Interviewer: Dirk Jan MenkveldDuration: 42:55Interviewee: JoseLuis, Co-founder COO of ChangeYourFlight.com
Date and time: May 31, 2012Location: Barcelona Activa
– Start interview transcript –
Interviewer: [.. introduced himself ...]. So, than we, I want to ask, your name and age I know, but what isyour background and your co-founders background?Interviewee: Ok, my name is JoseLuis, I’m 31, my co-founder name is Inaki, he’s 35. We’ve both back-ground in engineering, he’s civil engineering, but also, he began at forest, we usually joke about gardening,like that, but forest engineering, and he did civil engineering, and he switched to finance and did master the-sis, or whatever it’s called, in France. We me, it’s a similar path, I’m an industrial engineering, or mechanicalengineering in Europe, and I switch into designs. I did a post-graduate, and master on design.Interviewer: Ok, you guys also have code skills?Interviewee: No, neither, none of us has code skills.Interviewer: Ok, you’re more the product manager, and he’s more the business man?Interviewee: Let’s say that he’s more the analytical one, and I’m more the creative designer, I knew a littlecode, but not now. I could never consider myself as a frontender or backender. However, we both, especiallyme, I did coding at the university, so I’m more familiar what’s about.Interviewer: With HTML, CSS, also PHP, or?Interviewee: No, Java, but also I knew from..Interviewer: But, you get the idea of coding?Interviewee: Yeah, of course, I mean HTML and CSS is quiet easy, and now even, we do, in our spare time,code academy, and learning how to, even Javascript. We are not coders, and that was our main problem,because they saw the system here I think, and everywhere is design is how coders, geeks, or freaks, can starta business. So, if you come here, to Barcelona Activa, or you go to another seed camp, or event for startups,you’ll find a lot of mentors, or courses on how to find money, we knew how to do that, how to sell your stuff,we knew how to do that, so all the skills that complement coding, but not you’ll never find a code course, or amentor that can help you to explain the structure, or to identify the different code skills that you need in yourteam, or different personalities, and so. We match all the technical, but, which is not a huge problem. But, atthe beginning, when we didn’t knew, we didn’t know anything, it was a quiet challenge for us.Interviewer: I can imagine, but tell me about your company. So, it’s changeyourflight.com. How did youcame up with the idea and when did you found the company?Interviewee: Yes, to end with the background.Interviewer: Sorry.Interviewee: So, this is our educational background, so our professional background. Inaki comes from thefinancial background, a investment company, also in banking, in Paris, London, also here in Barcelona.Interviewer: So, a good network for investments?Interviewee: Not really, because he was more into the B2B, or ... So, at the last stage of his professional. Heworked in a little investment company here in Barcelona, he got in touch with the familiar offices, and little.. of Spain, but even that contacts were not useful for us at the beginning. So, this is his professional back-ground. My professional background is in to engineering in the early stage, and at the second stage, moreinto marketing, innovation, and management consulting strategy. I used to work in Paris as a engineering
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for Renault. I moved here to Barcelona and for my last stage I was working in .. opening a new office of aconsulting company.Interviewer: O, so you had a lot of experience on the business side than?Interviewee: Yeah. So, as I mentioned before, he was more the analytical guy, financial guy. I was more thecreative, business, management, strategy guy. With a little touch of design. So, we complement each otherquiet well.Interviewer: Yes.Interviewee: Where the story begins. Three years ago we met each other, always the same, quiet romantic,we met each other in Paris, while I was working as an engineering at Renault, and he was studying finance at.. We met there, and we start to thinking about business ideas, we should do this, we should do that. Even, westart a couple of things. Than, the love came to an end. And, I decided, I came back here, and I worked for acouple of years, for this management consultant. And, before leaving to Dubai, we’re talking about a meetup,with the international friends, while planning this, we suffered a change your flight problem. The problemof having everything arranged, thinking that we were organizing this meet up with friends. And, than finally,with last minute work stuff, we only met with Inaki and I.Interviewer: Really?Interviewee: Yeah, we supposed to be with five, and end with two. On sunday having a coffee, in Paris,discussing this idea, how could it happen? We had three friends, with three plane tickets, and they were notused. We knew, in week of advance, that this was not possible to get this flight. Maybe, it’s possible to findsomething to change this. So, we were inspired by a couple of businesses that were running at that time.Peer-to-peer second markets, of changing train tickets, concert tickets, and so. And, we begin about the ideaof getting rid of this ticket, and try get the money back. And, it took more or less one year of development,idea development during the nights. And, of course, as I said before, I was going to Dubai, and I end by goingto Dubai. He moved from Paris to Barcelona, to be near and develop the idea. And, we invest a lot of timein this side project. And at he beginning, and one year after, we decided, I decided to quit my job. I cameback, and we corporate the company. In the beginning it was only me, I was working for the company, forfree. And then, Inaki quit. On the middle of the story, we had a third founder, but he didn’t decide to start in.He was helping us in the early stage of the side project and in the moment, he had to step in, he didn’t stepin, because his..Interviewer: But, was the skill of this guy, a technical guy?Interviewee: Yeah, he’s a MBA, .., best in his class, whatever he does. He’s on the private equity.Interviewer: Ok.Interviewee: So, it’s about running business in a different stage, meeting from investment in another stage.He ones a little sum. Little, like, the biggest of southern Europe. But, he’s in the management of a big fundhere in Barcelona. And, he handles a couple of companies. He helps the management by M&A, and privateequity stuff.Interviewer: But, it was probably also good for your network?Interviewee: Yeah, of course.Interviewer: Because he could introduce you to..Interviewee: More or less, it’s a different stage. The mechanics are similar, so, it always helps to, I meanfrom the personal perspective, it’s great. He’s a really clever guy, and we are with two founders. So, everytime we’re in blocking point, he’s the third person to balance a bit. It’s interesting.Interviewer: He has a kind of an advisory role.Interviewee: At the end he has a kind of a minor stake. It doesn’t disturb a lot.Interviewer: Ok, but with this stake he can not influence the big decisions.Interviewee: No. I mean that is what everybody wants to buy per se. I don’t want to invest in a company thatis run by two people and owned by three.Interviewer: More or less, I mean, we have this idea clear from the beginning, and we said, if you step in,
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the same stake as we have. Little differences, statics, if a different part, you would have the same stake. Ifyou don’t step in, you have a minor stake. If you have more to invest, we don’t care.Interviewee: But, how often do you see this guy?Interviewer: We do, .., little committees, if we are lucky every two months.Interviewee: I think that’s enough, just to reflect how it’s going.Interviewer: Exactly. But, tell me a bit more. It was, in the beginning a side project. So, what did you do?Writing a business plan, or making a prototype?Interviewee: Building network, that was the huge line. That was and is the biggest challenge we have. Wedon’t come from the airline industry, and this is an airline business. So, to build confidence, credibility, allthe important issues. What you need to have, to deal with an airline, the key elements, success elements youneed to have when you do deal with an airline, we build that during that year. Meeting the relevant people.Learning about the sector. We bought books about running airlines. Understanding what was revenue man-agement. How we could build this confidence with managers. So, personally, we are leaving in Barcelona,and Barcelona has one local airline, which is called vueling. So, we try to find the vueling top management,and try to get in touch with the business. And, know more or less, you are the relevant person, like whowere the .. people, and how we could approach them. We build this advisory committee, which was more orless top management of vueling from the relevant areas. We had the founders, kind of business strategy, therevenue manager, the phone .. guy, I mean, we met the top management. And, we kept only 4-5 people thatreally helped us to shift the business model, and think all the things through.Interviewer: That’s really good. So, than, from this stage on, you made decisions to stop your job.Interviewee: Yeah.Interviewer: And, really go to the product phase.Interviewee: Doing this year, we have like three, the main objective was to be clear that this business goingto run. So, to make the picture that this business will work, we had to be sure that the airlines would beinterested. We had to be sure that the travel agencies would allow us to compete. And, to be sure we wereable to find the money.Interviewer: Of course, but also, how did you pitch to the customers. There are a lot of people who can notmake the flight and want to switch..Interviewee: Yeah, ok, during this year we switched the business idea, we really find what was the businessbehind. When you miss a flight, when you know when you get a flight, you’ve a problem. Because, you investmoney you’ll not get back. But, as an airline you also have a problem. Because, you’ll fly a seat that could beresolved again with the maximum price. But, also, you’ve an unhappy customer. And, an unhappy customerthat could deliver more money to you. So, at the end, we realize, that our customers, the people who wasgoing to pay change your flight, were the airlines, and the people who were going to use the platform werethe users, the passengers. So, when we think about customers, and we think about income for the company,we always have the airlines in mind. So, we wanted to get the airlines on the loop, and we avoid the idea ofbridging them and creating the second market peer-to-peer stuff. And, I think that is and was our key success.And, finding that you can make money out of this collaboration in between, being in the middle of passengersand airlines. It’s a different business, because it now has a different .., it’s quiet difficult to engage airlines,which are huge companies, complex organizations and so. But, I think it is the only to..Interviewer: I think so too, because, it’s the only way to, for most passengers, if you’ve a flight, and youwant to switch, you’ve to pay a lot if you call the air company.Interviewee: Exactly.Interviewer: I think you can also manage to do something about the switching costs.Interviewee: Exactly.Interviewer: One way or another.Interviewee: We were about a lower fee, but at the end, who owns the business? The business is owned bythe airlines. And, are you sure that the airlines will allow you to a bit of money out of this business if you
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don’t allow them to make more money out of it. What kind of, can you, they will give you a part of thebusiness to you for free, or do you have to give them? For example, ..., online travel agency, also get a shareout of this business. And, they are shifting this business model into selling tickets, airplane tickets, but alsogetting money out of the auto’s. At the end, the commission, they get is nothing. But, they’re building a newbusiness around, an internet page, that allows people to get flight, get an auto, and I don’t know. They’reshifting the business model.Interviewer: I understand, but than your business model, you only earn from the airlines? Not the customer?Interviewee: Yeah, no.Interviewer: So, there’s a little commission for you guys.Interviewee: Exactly. Again, it’s not about switching. If you go to the solution. Ok, we allow passengers toget a part of the refund, in a form of a voucher. It’s a voucher code, a discount voucher for the next flight. So,we build, we allow passengers to come back to the airlines and spend more. And this, where we build newrevenue for the airlines. Because, we allow passengers to go back, make a new purchase, and for the momentit’s a great success. They’re going back, buying more. For example, you’ve this problem with business flight,you get a 20 euros voucher, 40 euros vouchers, and you can decide to use it on a personal with your family,or with a friend, so you’ll spend more, and this is the reason to create a big lea sure trip with your friends.Because, you’ve this discount voucher which allows you to fly cheaper. And, this is a great success.Interviewer: I think so to, this is a good solution.Interviewee: It is a kind of loyalty program. It’s not only about optimizing the lock factor of the plane, butit is also about having new marketing tool. With your customer relationship management, voucher holders,with a just an empty flight here or there.Interviewer: Actually, the airplane websites, they should promote your website one way or another.Interviewee: They do.Interviewer: They are do from vueling?Interviewee: No. Because, we need to do sign agreements with all the airlines. So, we go one by one. Forthe moment we’ve an agreement with Air One, which is a low-cost of Alitalia, which operates in Milan, andflights to many places. Milan, Pisa, and Venezia.Interviewer: Alright. So, in this year you build a network and you started to build the product.Interviewee: No, the product was always paper. The biggest investment with this, was the printer machine.The dream printer, we convinced, most of our clients, with a mockup.Interviewer: Really?Interviewee: Yeah, with paper.Interviewer: That’s awesome.Interviewee: Than, we decide to build a .., which was also the fronted. Without any database layer, withoutany intelligence, to sell more. And it helped, it helped to get more money.Interviewer: And, the money came form?Interviewee: The money came from a first round of friends and family. Ok, yes, and we got 250K. And, thathelped us to get one client, develop the platform, and..Interviewer: And then, you also get to hire a CTO you can manage to build the platform. [...] Ok, whatdid you do more with the money, only building a product, setting up the servers, and also expanding morenetwork?Interviewee: Traveling. We spend one year incorporate, than we developed the commercial pitch, themockup, this is working, three months later, we decided to build a mockup with only content. This is al-ways about thinking, thinking about the other guy think this is robust and this is working.Interviewer: Yeah, validating also for you guys.Interviewee: The biggest you can have is if they say, it is an idea, a project. This is about project, this aboutservices and reality. Our biggest concern was to make this real. So, had to make a little prototype, that wasnot working. Because, people when he visit the website, only an little mockup, but it was a website. By
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saying that this will not work, because, you show them, you can share with that this is working, and this willwork like this. Even if it’s paper or a little mockup.Interviewer: Yeah, I understand.Interviewee: We work all the time on that. And, when we got the money, we decide to invest, and we designeverything. Like fronted, and backend, all the intelligence, the algorithm, all we said that works.Interviewer: Yeah, but than, on the backend you were connecting to the airplanes?Interviewee: Our system is a quiet easy system, our frontend, all the beauty, all the interface to satisfy thepassenger, you’ve to get simple information, and who is, and what is your booking code. And, in the backend,you’ve two: we receive information of the airline system, show them in a fancy way, estimate what is value,what is probability of reselling the seat, giving the options. And then, when the passenger decides, you’ve togo back to the backend, and do some aggregations, and selling this ticket, and getting this voucher..Interviewer: I understand.Interviewee: It’s not rocket science.Interviewer: Yeah, I think it is a little much detail. Most important thing is you hired a CTO, did you hire ateam around the CTO, or did you outsource?Interviewee: The first development we outsourced, the first mockup. We thought, the outsourcing couldwork. But, at the end..Interviewer: But, it was a company here?Interviewee: Yeah. But, it didn’t work, it was only HTML and CSS.Interviewer: Really?Interviewee: It was painful, our first experience were a disaster.Interviewer: What did you get to this company than?Interviewee: I mean. Than, we tried that, we learned from our mistakes, and we decide to hire a guy. A littlemistake, is that we hire the right guy, or not the right guy. And, we see it today. As, you was doing part-time.Interviewer: Still here?Interviewee: No. And, we were into that. Because, it was less expensive. But, he was not involved, emo-tionally, and the quality of the work was not good at all.Interviewer: Ok.Interviewee: And, than we decided to invest, we find a CTO. We decide to engage him, and now he’s in thecompany.Interviewer: He’s on a salary basis, no shares?Interviewee: Yes. No, we find a kind of management package, kind of stock options or something in thefuture of course. So, we if we take a look at the resources time. We were with two for a year, without salary,and then we get funding and a loan, we put the salary.Interviewer: For you guys?Interviewee: Yes, the founders. Than, we got a friend, who was not working, and we thought, if you wannawork, you can help for some time. And, we hired this kind of support, for everything, communication, mar-keting, development. And that time the IT development was outsourced.Interviewer: Ok, it was led by one CTO?Interviewee: No, led by us.Interviewer: By new guys? So, there was no new CTO coming?Interviewee: I’ve to write it down to put it all together. [...] It’s like march 2009, the idea. [...] In Maywe corporate the company. In July, first airline meeting. Than, next milestone, is 2010, than we get loan inFebruary 2010, we get a loan, and we get friends and family 250K. In April. Here the founders had salary.Here the founders job views. And then, we had the first airline engaged. Before having the first airline en-gaged, we started development. Development with design, like the front. In this period of time, we had thefirst dummy, prototype, horrible design. The product was ready in October, launched in December. [...]. Thisis 2011. It’s called side project. Until now, May 2011, we got more than 50K investment. And here we had
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this IT crises, and here we engaged a CTO on October. Our current CTO.Interviewer: He’s good?Interviewee: Yes, the best.Interviewer: [...] Only hire the best.Interviewee: I used to make this estimation. Ok, if he is not the best. How much time will you invest? And,at the end, you see that, finding the best or not, could cost you around 10, I mean, around 5,000 to 10,000, ofthe time you’ve to invest. So, while discussing 5,000 or 10,000 euros on the salary, it’s not worth discussing.Interviewer: Ok, with this investment, you can go big, all airlines, in all Europe..Interviewee: Maybe, we’ll with Egypt, because summertime it’s a pain in the ass for European wise. So, letme read. Did you always plan to be an entrepreneur? I think that was not planned. But, it was on our blog [...].Because, we try to be, to do something before. WIth company. [..] We didn’t found any companies. But, wehelped our friends in their own initiative. Of course, we do not consider to sell t-shirts doing summertime asentrepreneurship. I mean, most of the people do this. I mean, cleaning the garden, and being paid. That’s notbeing an entrepreneur. US guys consider that. What is the name of your company? It was changeyourflight.What year it was found? The idea March 2009, incorporated in May 2010. By how many founders? We werewith three, but early two founders. Than, what’s your role?Interviewer: We covered that?Interviewee: This is the biggest, this one of the parts you’ve to do, choose the roles. We’ve on the emotional,we are, I’m the creative, he’s the analytical, with a labels he’s the CEO, and I’m the commercial one. Is yourproduct B2B or B2C?Interviewer: I know.Interviewee: It’s really B2B2C. We’re paid in B2B. How many customer do you have? We have only oneairline, since December. We’re working really hard to get a new airline.Interviewer: Now you’ve a working product.Interviewee: Focus local, or internationally? We’re focused internationally. Internationally, on a Europeanway, but also a global way. Last year, we were pitching Air Asia. Pacific Airlines. Is this available on mul-tiple platforms? This is funny. It’s a website, obviously, because target should be on a website. It could bemobile. The main reason could be, because the airline CEO’s and general managers, want to have to targetof mobile. But, it is not, because it’s a key element for the service to succeed. No, it’s a key element for theproduct to be sold. It’s a need that we have on the selling process to the airline. It’s not because your businesswill use it, the application, or platform. Nowadays, it is a function to have an app, for an iPhone or android.And, if an airline is convinced, because we have it, we will have. But, it’s not a business requirement.Interviewer: Not yet. Maybe in the future. [...] I know everything about your company profile, really nicestory. Now, I want to show you the thing I developed. And, I will ask you some questions about it. I think.[...] So, first, the most important is that I explain my framework, and later on we can do some questions. So,on the left side, this is my conceptual internet startup framework. On the left side we’ve the startup life cycle,are you familiar with Steve Blank?Interviewee: More or less. [...] Steve Blank is not the Lean Startup, Eric Reis.Interviewer: No, not Eric Reis, but Steve Blank is the Four Steps to the Epiphany. They are complementaryin this. So, four steps. So, per stage what is the most important factor, eh, for entrepreneurs in order to go tothe next stage, in order to succeed. I think you guys are more or less in 2 or 3. More or less in optimization,means that you’re now approach a new round of funding, and now you can just create the company. I thinkyou’re in stage 3. Because, you already know it’s working. So, than we go to the factor groups. The mostimportant groups is the startup and founders. Because, I believe the founders are the startup, and the startupare the founders. Because, it there’s a founder, there’s a startup. So, you can say about the founders, in orderto succeed, commitment is most important. Or, you have to solve constrains, or the technical background canbe important, decision making, pivoting. All factors related to the founders that maybe important to succeed.And also for the startup we’ve, the business plan, the working business model, or strategy. So, I defined
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some factors, and later I’ll ask you to prioritize the factors, the top 3 everywhere. So, when we are finished,you also have another factor groups, like the investor, that plays a role. With the investor you’re probably toperform better, and are more likely to succeed. So, and then we also have to facilitator, and the facilitatorfactor maybe network, and this incubator here, has a large network, also of other companies, and you canshare your experiences. And you can create a network. And in your case, B2B, it’s more or less difficult. But,maybe an incubator can provide, connections to the investors.Interviewee: Yeah, with network of investors, having half of the problems solved.Interviewer: So, next to these two, these are also interconnected, the external environment, the economicalenvironment, or the social environment, or the competitors, and also maybe media, the media companiestalking about you. And, than you have eventually the customer.Interviewee: Ok.Interviewer: And the customer in your case is the airline, and the consumers than is the user. And they alsoplay an important role. And what is there the most important factor in order to go to success.Interviewee: Why did you not include the external [?]?Interviewer: What do you mean with that?Interviewee: For example, I can see the facilitator, media attention, and not as an external environment.Interviewer: That’s a good question. I put it here, because..Interviewee: I think about it, because it’s, let me share with you a framework that I..[...]Interviewer: So, eventually, these factors influence the performance, and when you’re performing well, it ismore easy to succeed, you know.Interviewee: Yeah.Interviewer: And, later on, these arrow are the hypotheses, so, this will say. These combined factors willpositively influence the performance of the founders, and with my test, I’m struggling a little bit with thehypotheses that really get to succeed. But, you can map mind into this. At what stage, what is important, andeventually the goal is to help other entrepreneurs in this, and ...Interviewee: I think it’s correct. I really like your framework. Like when you start, you have the idea, youhave the business, and you have the market, than you have the founder, than you have the money or invest-ment, and when I heard about this, I think it was quiet good. So, can you make a business out of this idea, ..,can you make a product of this idea, is this market ready for this product, are you the right person to run thisbusiness, are you right person to be with this investor, is the investor right for you business. More or less. Itwas quiet simple. And, he was talking about this adjustments between the five elements.[...]Interviewer: Is this a scientific paper?Interviewee: No, a new movement, an agile, it’s a mix of agile development.Interviewer: Actually, mine is the same, I look at this.. Yeah, it’s really nice.Interviewee: Like, you have to work in this adjustments, it’s quiet interesting from your side, you includethis facilitators, and external.Interviewer: Yes, it’s Belassi’s framework, Belassi is a guy who identified IT projects, in IT companies,when they succeed. And, I than I mapped into the startup ecosystem.[...]Interviewer: I think it’s good to send it later, and then you can prioritize, this, this, and this. Because, weneed to go. Thank you for your time. [...]
Unfortunately, we didn’t have time to finish, so last questions were answered by email:
Startup Life Cycle16. Are you familiar with the four steps (Steve Blank’s Ð The four steps to the Epiphany)? YES, from blogsand articles
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17. At what stage are you know? Customer creation? or may be we still in customer validation because Ithink that 1 customer is not enough18. Do you recognize the steps? YES, somehow, not so linear because sometimes we must run two streamsin parallel
Factors related to the Investor(s)19. If you had to prioritize a top 3, what would be the most important factor? Do miss a factor?1. Traction -> Media and other investors attention. Similar concept as ANCHOR investor2. Capital (terms & conditions)3. KnowledgeOther factors: Network (founders, media, investors) and Awareness
Factors related to the Founder(s)20. If you had to prioritize a top 3, what would be the most important factor? Do miss a factor?1. Commitment2. Adaptability3. Competence
Factors related to the Startup21. If you had to prioritize a top 3, what would be the most important factor? Do miss a factor?1. Business model2. Market knowledge3. Cooperation
Factors related to Facilitator(s)22. If you had to prioritize a top 3, what would be the most important factors? Do miss a factor?I should better understand what you mean with Facilitator, because can be a journalist, can be an incubator1. Motivation (in exchange of... money?)2. REACH3. Resources
Factors related to External environment23. If you had to prioritize a top 3, what would be the most important factors? Do miss a factor?1. Awareness (media attention)2. Competitors (e.g., other startups fundraising should be considered as competitors in the $ arena)3. social environment (useful to look for talent).
Factors related to the customer?24. If you had to prioritize a top 3, what would be the most important factors? Do miss a factor?1. User satisfaction (B2B, manager’s satisfaction)2. Need3. Added Value
Startup Life Cycle factors per stage?25. In Discovery, what would be the 5 most important factors?1. Customer needs2. Network3. Adaptability4. Market knowledge5. Commitment
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26. In Validation, what would be the 5 most important factors?1. Adaptability2. Customer satisfaction3. Media exposure - reach4. Capital5. Network
27. In Optimization, what would be the 5 most important factors?1. Capital2. Network3. Knowledge4. Partners5. Awareness
28. In Scale, what would be the 5 most important factors?1. Capital2. Vision3. Awareness4. Network5. Competitors
Hypotheses29. Hypothesis 1 (H1) Agree or not, why? Agree30. Hypothesis 2 (H2) Agree or not, why? Not really, COULD but is not straight forward31. Hypothesis 3 (H3) Agree or not, why? Agree32. Hypothesis 4 (H4) Agree or not, why? Agree33. Hypothesis 5 (H5) Agree or not, why? Agree34. Hypothesis 6 (H6) Agree or not, why? Not really35. Hypothesis 7 (H7) Agree or not, why? Agree36. Hypothesis 8 (H8) Agree or not, why? Agree37. Hypothesis 9 (H9) Agree or not, why? Not38. Hypothesis 10 (H10) Agree or not, why? Not39. Hypothesis 11 (H11) Agree or not, why? Agree40. Hypothesis 12 (H12) Agree or not, why? Agree41. Hypothesis 13 (H13) Agree or not, why? Not42. Hypothesis 14 (H14) Agree or not, why? Agree
General43. What’s your definition of success? Reach your objectives44. What’s your definition of failure? Attempt, not focus or when you quit45. If you had to pass 3 lessons learned to starting entrepreneurs, what would you pass?1. impossible is nothing, there are a lot of things you don’t know but only a few you cannot learn2. fail, but fail fast and learn from the past mistakes3. there is no plan B (side projects or secure jobs) just do it!46. What the best advice you had ever get?think as a rich man, spend as a poor man47. What would you do different the next time?speed and focus (easy to say after)
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C.6 Interview Transcript - Teambox.com
Interviewer: Dirk Jan MenkveldDuration: 1:06:23Interviewee: Pablo, Founder and CPO of Teambox.com
Date and time: May 31, 2012Location: Restaurant bar
– Start interview transcript –
Interviewer: Alright. So, first of all I would like to ask you, who you are and what did you do?Interviewee: I’m Pablo. I studied aerospace engineering in Madrid, I lived in the US for four years as a kid.And then I studied in Madrid and Paris. But, Barcelona .., so, I ended up here.Interviewer: Ok.Interviewee: I didn’t. So, I always have been a coder. I was making small websites and so on. Three of fouryears ago I started this small business with some friends for collaboration tools. So, I’m a developer, I do myown. So, that’s when I started with teambox. I didn’t really think become a company. It’s nog big anyway.But, eventually we raised some money. I raised some money, and found some people around. And, actuallyit’s taken off. It has been almost three years, but full time a year.Interviewer: So, you started coding, when you were a child, or?Interviewee: 14, 15..Interviewer: For me the same, and how old are you?Interviewee: I’m 26. My father told me some day. If you like games, you should make your own. I was like,ok.Interviewer: Yeah, sure, why not. Really cool.Interviewee: And later with PHP, with the boom of websites, I was able to buy myself a new computer everynow and then.Interviewer: Yeah.Interviewee: That’s how I got started.Interviewer: Ok, but than, you could make product, but you didn’t really know how to run a business?Interviewee: O, no. I still don’t.Interviewer: Ok, but you can always hire people to help you. Maybe you’ve a lot of advisors?Interviewee: Yeah. The truth is at the end, you’ll have to deliver everything yourself. So, people can tell youthings, but at the end,..Interviewer: Yeah, I agree. I couldn’t agree more with this.Interviewee: You’ve your own story about that.Interviewer: Yeah. The small things, everything needs to be done. So, you founded teambox, is that the onlycompany you founded?Interviewee: No, this is the third one. The first one was a really small thing. It was a website for exams. So,basically, I put it up some questions with the answers, so people would pay to take exams for, like for theirtests. I sold that for about 30K. But, at the very beginning of the crises, it was super hard to get me paid.Interviewer: But, you sold to the university?Interviewee: No, another company.Interviewer: Ok, the technology to another company, or was it like a competitor or something?Interviewee: They went into the test, and give like training. And we were with 2 or 3 friends, and even mysister was helping me out. So, we sold that, I was happy, because it was some money, I put the money intoApple stock, so, I went very lucky, multiplied by ten. And, with that money, I start doing a couple of things,
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until than, they were just prototypes, and they failed. One I try do this, was ..., I would make a cable, fromone tower to the next one, those power lines. I would try to do that. Senior people. But, at the end it wasreally hard to get funding.Interviewer: But, was the reason? Because of the product, the team?Interviewee: We didn’t have a real team. We didn’t have an office. It was just me.Interviewer: But, did you make a plan for it?Interviewee: It was, it a high investment initially, it was a half million to a million euros.Interviewer: Yeah, that’s high.Interviewee: But, it was a real name, like in the space, there were no power lines anymore, they’ve .., andwe presented it to the Spanish government, they had some initiative, but, it didn’t work at all. So, I startedsomething cheaper, how to make a program with a ... I did it for a while. It took me 9 months to ship it,the first version of teambox. It was very good, but people started using it. So, I thought, well, maybe I’ll gofurther and see how far we can get. And, that’s what we are doing.Interviewer: Ok. So, you found three companies, and now you are still working with teambox?Interviewee: Yeah.Interviewer: And, when did you found this company?Interviewee: 2009, or late 2008. But, at the beginning it was not a real company. It was just me, saying, theproduct. But, full-time I started in 2009.Interviewer: But, than the idea this is what it is going to be, you know.Interviewee: It was really helpful to me, to have a .., one the co-founders of .., he put in some money, andgave me very good advice about the startup. Him and me have this crazy idea that we all have. And, than say,hey, let’s see how this can become a product. So, that helped. And, many of the ideas we had than, are stillbeing implemented right now.Interviewer: There already was a road map for like five years?Interviewee: Not serious. More idea, some day we’ll have this thing to share files. Maybe simply your harddrive. We’re still working on some ideas.Interviewer: This guy was an advisor?Interviewee: He was an investor.Interviewer: A real investor?Interviewee: Real, like 30,000 euros.Interviewer: So, he got shares?Interviewee: For him a really good deal, yeah, 10% at that time. The current valuation, multiplied by 30.Interviewer: Wauw.Interviewee: Still, it’s not, we have the money in the bank yet.Interviewer: It doesn’t say anything.Interviewee: For example, we .. Some people, Facebook investors came in on the valuation.Interviewer: Really?Interviewee: Yeah, and the biggest part was from .. Madrid. Pretty cool, to see seriously investments.Interviewer: Ok, but than you had multiple rounds of investments.Interviewee: Yeah. We had 3 or 4 rounds, depend on how you count them.Interviewer: Everything with money, give out shares for money, that’s a round. So, you had three than?Interviewee: We had like, 3 different valuations, or 4. One of them was one guy, coming with a little bitmore, and a little bit higher valuation. So, exactly it was the same one.Interviewer: That’s really nice. You founded it in 2009, and then as a solo founder. When was your firstproduct launched?Interviewee: The first product was in 2009, after nine months I started working. If was really .. in the begin-ning, I only got like a 1,000 users or something.Interviewer: 1,000 users after the launch? So, you got some media attention?
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Interviewee: Actually, we went up to 10,000, before it was paid.Interviewer: 10,000 is really good. But, what do you define as users? Like people really using it, I mean,for teambox can be used by a company. And if they have like 10,000 employees.Interviewee: Than it would be 10,000 e-mails of people. So, companies, it depends, at the beginning, com-panies were very small. Actually, teambox wanted to have the concept per company. Especially the newones. But, lately, we see large companies come, with 20, 50, up to 300, or 500 users. Obviously, we’re doingbetter. But, they take a lot more work. So, basically, for..Interviewer: Why? I mean, the product is finished, is it only support?Interviewee: When you’re so big, they call you, they want special things.Interviewer: They want to customize the product?Interviewee: Yeah.Interviewer: Special feature request or something?Interviewee: Each time is easier. Because we work a lot in standardizing the product. So, it’s become morea process. But, in the very early times we did this, like one year ago, it was hell, it break loose the company.Interviewer: Ok. What kind of software development method do you use?Interviewee: We use teambox a lot at everything we need to do. We create a path. We’ve two teams today.The support and backend team and work on stability. And the new feature team, they work on design, launch-ing a new feature. So, about 50% of our workforce is in the stable part, and 40% is on the new stuff.Interviewer: Ok. May I ask you, how is your recycle now then?Interviewee: Every day.Interviewer: Every day is a new release? Really?Interviewee: We don’t call it a release, but everyday we push a new version to the server. So, this morning,we pushed already one. And we’ll push another one after lunch.Interviewer: Really? But, is it not a risk, you’ve to test it as well.Interviewee: We’ve automated test.Interviewer: That’s awesome.Interviewee: So, the way it works. We make scenarios. And the app clicks itself. And whenever we developa feature, we push a test.Interviewer: Ok. [...]. But, than you support multiple platforms as well?Interviewee: Yeah, but’s hard. The way we did it. We structure the product, so there’s an API would neverchange. We are in the second version of the API. People are still using it. And, all of our products, use thesame API. So, even the web version is not an application. It is really a JavaScript application that is the askingthe data.Interviewer: A ok. I thought it was only the website.Interviewee: No, we have iPhone, [...] chrome extension, we’ve integration for Dropbox.Interviewer: But, if big companies use it, they’ve the source?Interviewee: Most companies don’t see the code. But, shortly we will launch, what we call teambox enter-prise. The basic idea, that I give you, it is locked, and if you pay can unlock it, and you can have 50, or 100users, but, you own the data. And, you don’t even need a internet connection. So, we’re excited about this,because that means, we have a new product. Today [..]. But, if you’re somebody like, say Microsoft, or thegovernment, they’re really strict about this.Interviewer: Yeah, the solution will help so. [...] You started charging for the product, and that’s B2B.Interviewee: We also see, like small freelancers, we have people pay for one user.Interviewer: But, there’e no free version anymore now?Interviewee: Yeah, after 5 users, it’s free, but if you want feature like Dropbox, or having multiple projects,you have to pay. It’s interesting, because some people pay for one feature. I thought it would never happen.Interviewer: [..] We come to the competitors, I think Asana, and Basecamp or something. Those are thecompetitors?
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Interviewee: Yeah, the biggest.[...]Interviewer: Basecamp, has 8, or 10 times more signups than us. The product is less smaller. Basically,typically they’ll see freelancers, and people like this using it, but when you get the larger organizations, youneed to manage support, or cycles, or gantt charts, than they come to us.[...takling about competitors...]Interviewer: But, you’re now the CEO?Interviewee: I’m not. I brought in another guy from the United States.Interviewer: At what point did you decide to do that?Interviewee: In September last year.Interviewer: September last year, was there also an investment?Interviewee: No, not at the time. But, I found that I lost time in doing in things I don’t do very well, likeaccounting, or legal things. Making sure that the Spanish company can pay an American company, and ...I just want to build a product. I brought in this guy, and it works well. It costs money of course, but I findmyself for free time, and ..Interviewer: Of course, and now you’ve your focus, you focus on the product, and you want to build the bestproduct ever for you users. I completely understand. [...] Now, you started with some customers after thelaunch, and now you’ve a lot of customers. Do you see the sales going up?Interviewee: We tripled the amount of money that we were doing from September to today.Interviewer: Really?Interviewee: Yeah. We did a lot of changes. So, we changed our pricing model, before it were projects, likebasecamp. And we attracted different users, of different companies. We changed the position a little. We’retalking more serious customers.Interviewer: And, these decisions were made by the CEO?Interviewee: No, most of them. Well, pricing was made by me. Positioning, we work on it together. Themain difference, that our users went up, was just our user interface. It was somewhere you had to put up thenumber of users. Before it was.. You come in, maybe 7,8 maybe 5, but that guy didn’t really needed. So,it made you really think. But now, I put in range, it’s up to 15, up to 30, up to 50. And, we’re making 50%more.Interviewer: Ok. Than, it’s a psychological thing, this model, and they make the decision.Interviewee: It’s very stupid. If you multiply all numbers by point whatever.Interviewer: I believe in clear communication. Show everything what you got, and keep it as simple aspossible.[...]Interviewer: Your team is now 15 people or something. When was your first employee? Developer or? Is iteasy to get a developer?Interviewee: I think it’s easy to get that kind of your profile, you build your DNA around that. For someonelike me it’s easy to find technical people. Because, you know what inspires them, and you can sell them thedream. It took me very long to get a proper sales person.Interviewer: Really? How long?Interviewee: Two years or something.Interviewer: Now, the guy is flying around the world to big companies?Interviewee: No, we’re like, hey, do you want to meet on Skype?Interviewer: Skype calls.[...]Interviewer: Now, we continue. I want to show the framework I developed and I ask you question. I thinkit will take about 25 minutes and then we’re out of time. [...] This is the framework. I will explain you theframework first. Can you read it?
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Interviewee: Yeah, I can.Interviewer: Alright. So, it looks difficult, but it’s not. So, on the left side we’ve the startup life cycle, anddo you know Steve Blank?Interviewee: Yeah. Actually, I was with one of his students, this morning.Interviewer: Really? Cool.Interviewee: Also one of the American advisors is a friend of. He used to attend his classes.[...]Interviewer: I adapted those steps, and I’ll explain them. I think, I believe, per stage there are differentfactors, that are more important. That’s what I;m trying to find out. This influence the all model. And then,we’ve factor groups, this factor groups, and these. And they are all interconnected. So, the important factoris around the startup. And the startup and the founders, I put them in one. I always say like there’s no startupwithout a founder. So, that’s why the founder is the startup. So, you see factors, I’ll explain later. Next, wehave the investors, couple of factors. And then, you’ve facilitator, that can be the advisor, it can be an incu-bator, an accelerator, that kind of stuff, you know. And then, we’ve the customer, the customer is important,and is connected to the startup, that factors. And then, external environment. Like, now we’re in a crises,maybe it helps, maybe not. So, that’s it, eventually, those are, the arrows point to the middle, and that’s thestartup performance. And the startup performance is the startup itself, measured by KPI’s. The foundersperformance, ... probably the product / service is really bad, or. And then the product / service performance,and the resource availability. It’s about the availability of the persons, the people, the developer,..Interviewee: Who’s the owner? For you, a founder, a executive in the company there like interchangeable?Interviewer: Yeah. So, a CEO can be founder. I believe the founders are the most important here. They’vethe vision, and you carry out the vision. And that’s [...] So, this is it, do you’ve any questions?Interviewee: Make sense.[...]Interviewee: I miss something more related to the customers. It’s like everything here is under your control,except for these two, these are not factors. What about user acquisition?Interviewer: It’s there. Ok, let me ask you the first question. If you take a look at the investors, there arethree factors. What do you think is the most, if you miss something you miss please say so, but, if you had toprioritize these three, what would be number one?Interviewee: For me, it’s more the alignment, that they don’t .. in the company. Because some investors,they start doing a lot of internal work, so they become a hassle. They take away your work from what’s inimportant in just into internal qualities. I heard from other companies. For me, early investors were compa-nies, give us via friends, so, than it was really easy and they value that. It gave us time to build a companyand we didn’t worry about politics. It helped us to buy time.Interviewer: I understand. So, they provide capital and that’s it? They shouldn’t intervene with the dailyprocess?Interviewee: Yeah, it depends. If we’re talking about early stage, for me it’s knowledge, because, you’vecapital, but you don’t have enough experience. But, if we move on, there’s no knowledge somebody can giveyou, because you’re already an expert in your field. So, I would say knowledge, capital and resources. If Ijust had the money at the beginning it would be much easier.Interviewer: Alright, and then for the second one, like the best three? Only founders, what’s most importantfor the founders.Interviewee: Complementary team is important, because if not, you feel just one in the crowd, and nobodyfears about it, or.Interviewer: So, what do you think than?Interviewee: Complementary team. Vision. Work experience.Interviewer: Alright. But, work experience, you think it’s important to, for a startup, to be successful?Interviewee: What I mean, is that, like somebody who is not .. you can bring more into the company, be-
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cause, it easy, you know, what you shouldn’t be doing. You should get someone inspire the company, andnot. People come and go. O, this is for founders. Than decision making should be there.Interviewer: But, than instead of work experience?Interviewee: Yeah.Interviewer: Ok, and then the next one. The startup?Interviewee: I don’t believe at all in business plans, I believe more on Steve Blank in this one. Businessmodel is the first thing you should have. I didn’t have it at the beginning.Interviewer: I agree upon this one.Interviewee: Everytime when I hear someone. They’re like we’ve a startup. How are you gonna makemoney? People don’t know and don’t worry about it. That’s number one.Interviewer: It’s like twitter.Interviewee: Yeah, why do you care?Interviewer: I think, it is more like the American way also.Interviewee: It can be like soccer. If you’ve Messi, and you think you can be like Messi. But, there are alsostartups that didn’t make it.Interviewer: Alright, business model, and than?Interviewee: Market knowledge is very important. But, you can get that? Or time by working, or just..[...]Interviewee: Market knowledge, because you need to know how people are going to find you. I mean, if youdon’t have that.Interviewer: Market knowledge. You need to know your customers. And also your competitors. It’s allabout the market.[...]Interviewer: We go to facilitator.Interviewee: Choose one?Interviewer: Top 3.Interviewee: I think that’s the right order. You know, the thing is, experience is something. Resources andfacilitities you can just.. Somebody can count on, can help you. Hey, I can help introduce to people. I usedto be at Barcelona Activa for a while, but I moved somewhere else.Interviewer: You’ve been there with teambox?Interviewee: Yeah, I was for six months at the beginning.Interviewer: O, but they invested as well?Interviewee: No, it was because, I was a friend with somebody of SeedRocket, he told me, you’re coming toBarcelona. Stay with us, we’ve a table. He was good for me. Often I saw people coming by, and..Interviewer: And, that is what the facilitator is about, you know.Interviewee: Yeah.Interviewer: The incubator is, Barcelona Activa, they have the experience, they have the network, and theconnection to other entrepreneurs that helping to solve the problem.Interviewee: If I think of Barcelona Activa, it’s helping the starter, one is the experience, .. hey, this is thething, it doesn’t really work. Than, I got some network, because, I met people, I wouldn’t have had it at myapartment, it’s nice to have. It was cool.Interviewer: Alright. Than, the customer, the best 3?Interviewee: What is contracting?Interviewer: For example, if you’re selling teambox to another company.Interviewee: Ok.Interviewer: It’s making a contract, make sure everything is fine.Interviewee: So, first the need. Because, it’s super hard to sell something people don’t need.Interviewer: I couldn’t agree more. Sales people can do it.
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[...]Interviewee: User satisfaction is a really good indicator, because, when you’re starting, and you’ve like 100users, it can also happen about marketing and scale. And what do you mean by network?Interviewer: If they talk to friends about it.Interviewee: Oh yeah, that’s really important. Actually for us, it’s one of the main drivers.Interviewer: If they’re happy with the product, so they’re starting. It’s like the referral.Interviewee: Yes, we’ve the referral. So for us, it’s not linear, but quite high. With collaboration software,you need to collaborate with somebody.Interviewer: Alright, and the last one in this case?[...]Interviewee: Media attention is really important. For us, it really market spaces that’s driving growth. So,I would media attention and blogs. Technological environment, some companies are way ahead before theirtime, and fallen back into, they were, they have this.. Technology wasn’t there. And the competitor. But,they’re not the most important things.[...]Interviewer: It’s also an indication for the need, that there is a market. ... Than I’m going to ask you, youknow all factors, right. Now, per stage, the top 3 per stage. So, in discovery stage ... What’s the most impor-tant in the discovery stage?Interviewee: Find the need of the customer.Interviewer: Yes.Interviewee: Find the business model.Interviewer: Business model.Interviewee: Not capital. Really. That’s comes later, no? More for scaling. But, some experience.Interviewer: Experience. Alright, for the second stage?Interviewee: For validation. Capital. For me validating is entering the point that we have 500 customers. So,capital definitely, because, especially for a startup you are the money much later. So, capital. Complementaryteam, and user satisfaction.Interviewer: Alright.Interviewee: For optimization.Interviewer: Yes.Interviewee: For optimization in factors related to the startup, monetization, you’ve to make money. I wouldhave resources, like network. Dependeping on your stage. Make partnerships. We’re now going to Dropbox,hey, let’s market together.Interviewer: Cool. Last one.Interviewee: And competitors. You should make sure you go ahead for the product market. For scale I don’treally know. Because, we are not in that stage.Interviewer: I thought so, yeah.[...discussing...]Interviewee: But, scale, what do you think would be the most important?Interviewer: Marketing, sales, and retention of the startup. So, we need a lot of people the you can find us.[...discussing...]Interviewer: But, I mean, if you had to pick here.Interviewee: Capital, for the sales cycle.Interviewer: So, first should be capital, and second?Interviewee: Experience maybe, you need strong VPs of whatever they’re doing.Interviewer: And then, third?Interviewee: Retention. But, it’s at another level. You need somebody that will keep on top of everything.Interviewer: Alright. Than we go to question 29. Now, we look at the arrows, it are the hypotheses. And,
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you see, I want to test whether these are true or not. So, I want to ask you. Here you see the factors related tothe investor, influences the founders performance and the resources availability. I want to ask you, if you had100%, what would be, if you had to divided that, would it be to 10-90, 20-80, 50-50. According to you.Interviewee: I think it’s mostly for resource availability. Most of the time we needed capital, was becausewe needed developers, like people doing something, that we couldn’t do as founders. Still, they do influencethe founders in a way how they can coach you. Ok, 30-70, probably. Business monitoring is also good. It’snot that we do that directly, but it having by somebody that can coach you, it helps you...[...discussing...]Interviewer: The same question is actually for. So, we’ve the startup and founders. Together they influencethe founder’s performance, startup performance, everything in this. So, if you had to divide 100, what wouldbe the thing that mostly influences the performance?Interviewee: I would say mostly. So, for resource availability. I think a founder, helping the way of shapingit, but it’s not a major factor. So, 10 percent there. Most important are the KPI’s, even if they’re not measur-ing. So, I would put 40 percent there. 30 percent in startup performance.Interviewer: Than we have 20 left for the founders performance.Interviewee: Yes. That makes sense.Interviewer: Alright, and then the next one. Facilitators, we’ve a connection to the founders performance,and a connection to product / service performance.Interviewee: I think it’s, almost everything goes to the founders performance.Interviewer: 100-0.Interviewee: I don’t think nobody can help you, and really understand your product, and only coach you todo better.Interviewer: Yeah, I understand. And then, on the other side. If you had to divide 100, from the customerthat influences the startup, founders, and the product / service.Interviewee: 70-10-20. .. They help you and tell you more, how they use and you learn from them. But,mostly, how you see your customers they’re aggregated in KPI’s.Interviewer: Yeah.Interviewee: For example, our support processes, is now a core part in the development, methodology, comesfrom the customer, from the way they work with the things. It’s for them.[...discussing...]Interviewer: So, it’s more like the product / service performance.Interviewee: Ok, 60-10-30.Interviewer: Now, the last one here. So, again, 100 percent, what external environment influences the most?[...discussing...]Interviewee: So, external. I think it’s almost equally. Because, it effect the founder in a way that. It canbe a lot more inspiring for you to start a startup during a recession, because the conditions are more differ-ent. Product / service it also, like there a lot competitors, you’ve the opportunity to ahead, it’s also reallyimportant. When I started teambox, the competitors were really bad. I thought, I can do better, if I had thatenvironment, I wouldn’t have better. With resource availability I also think it influences a lot. During thebubble, for example, you can go out like crazy, here’s seed money, and you hire quickly, you start quickly,and you fail quickly. So, here it would be equal.Interviewer: 33, 33, 33. Cool. Than, we’re almost done. Now, we’ve the middle left. What do you think, ifthe combination is all there, than the startup will succeed according to you? So, if the acquisition, activationis good, retention, referral, than you can say the startup is a success? Do you agree?Interviewee: Yeah, you can say. No. Because, for example, you can still have everything going on, [...]Apple had succeeded in many parts of this, they managed to build the next product that kills the previousproduct. iPod right, take the iPhone, it’s the new iPod.Interviewer: Yeah.
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Interviewee: This works for a snapshot of the company, but not it’s missing a .. for innovation. [...] I thinkinnovation is missing here.[...discussing...]Interviewer: So, the next, these factors combined, do you think the startup is more likely to succeed?Interviewee: If you have all of this. It’s more likely to succeed. Yes, I think it is. Because, if you’re stayingon the top of your team and the business, if something fails, you can correct it. And you can turn around thecompany. So, I think, ..Interviewer: And the product / service performance, combined this, innovation, market fit, milestones, andthe method.Interviewee: Yeah, I think it does.Interviewer: Why?Interviewee: The difference with the KPI’s is that in this one it includes innovation. So, you can have aworking today, but you’re also working on the next thing.Interviewer: Yeah. This is really what investors what to see, and is where try to work your market, youknow. Try something new.Interviewee: And the last one. By itself, it’s not a component of success, you need to have that, it you’rebones and muscles in the company.Interviewer: Ok. I have three or four more questions. So, if you’ve you had 100, and these combined tosuccess, what would be the most important? So, 100 points for these four.Interviewee: Do you considering revenue also a function of .. For example, if you’re work in a business,only the revenue is margin. So, you’re Apple vs. Dell, the different is the operating market. So, it is a KPI?Interviewer: This is. You started with nothing, and you start making money, that’s the revenue. The prof-itability is than when your revenue is getting higher than, you do break-even, and then profit.Interviewee: 40-30-20-10. No. 40-25-25-10.Interviewer: So, the startup performance is the best that lead to success.Interviewee: I think so, yeah.Interviewer: But altogether, they will lead to success.Interviewee: When you told me you had 40 percent of user engagement, o, that’s a really good company.Nobody gets to that number. When told .. our engagement number, o, how did you get here?Interviewer: Yeah, that’s true.[...discussing...]Interviewer: So, you think, everything is performing good, will lead to success?Interviewee: I think it will.Interviewer: Do we miss something in this framework what you can think of, or?Interviewee: [...] I think you have everything here. In Spain, it’s hard to get investment, but it’s really easyto get public grants.Interviewer: Like Barcelona Activa.Interviewee: Yeah, they give you a loan for maybe 100K, and when an investor comes in, they master yourmoney.[...discussing...]Interviewer: So, we are done with the framework here. Thank you.[...joking...]Interviewer: If you had define success, what would be your definition?Interviewee: For a company or for yourself.Interviewer: For a startup.Interviewee: Creating a meaningful product that is self sustainable, a meaningful product that is profitable,and innovative in some sector.Interviewer: Ok, self sustainable. And failure? [...] When it’s not working out, it’s actually the opposite,
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when it’s not self sustainable, and it’s not.Interviewee: For me, failure will also be, failing to grow about some threshold. But, that’s personal I think,because, a lot [...]/Interviewer: Of course, that’s also possible. And, ok, if you had to had pass three lessons learned to anotherguy, if you start a company, this, this, and this.Interviewee: First of all, it’s .., everything seems to have some market flow and start. They way people wantto hear. And everything just comes together. So, first, start today. Somebody told me with, and I didn’tlistened to this, but I should have. Be very slow at hiring. Hire slow, and fire fast.Interviewer: Hire slow, and fire fast.Interviewee: Yes.Interviewer: I agree, I can not agree more with this one.Interviewee: And you never listen when somebody tells you.Interviewer: That’s also true. And that’s number three, try to listen.Interviewee: Yeah, but maybe they didn’t listen. I think the third one should be no one knows better thanyou. Because a lot of people when you’re starting, they come as experts in whatever. And that’s the gain youdiscover there’s no magic to it. Like, there’s not a magic keeper that somebody have, like when you work atDropbox. Many times you get somebody a the right moment. No magic.Interviewer: I understand. So, you’re best advice ever was hire slow, fire fast.Interviewee: Yes.Interviewer: Alright, if you had to redo your teambox experience, what would you have done different?Interviewee: Probably I would start worrying about metrics a lot earlier. But, again, that is something youwill understand when you’re here. My next company I would make it very very light, I would automateeverything, to be .. company. Surf like google, just have something that people would buy, that really works,the [...] Have everything working.Interviewer: Ok. Cool. I think me too. Keep it as simple as possible. Everything.Interviewee: Yeah.Interviewer: And a clear communication to your customer. I think, in the end, it’s all communication, if youdo that properly, the right words at the right time. You can do anything you know.Interviewee: You had a lot of customers asking you for new features and changes all the time.Interviewer: I was the product manager.Interviewee: Wasn’t that hard for you?Interviewer: Most hard for me was, not gathering requirements, it was managing the business side, andthe development side, and all factors what influence the product, and prioritize in this way, that was reallydifficult. Because on the business side, we wanted to focus more on monetizing, we had to build features thatmake money. But, on the other side, if you don’t have a good product, and people start going away. I meanwhat do you do? It was crazy, that was really hard to do. Especially, I had a double job as well, I was theCFO at that time as well, I mean, that’s also what I mean, focus. What you did, is the best thing. Hiring aCEO. Let him do that stuff. I would focus on the product and make the best product ever and that’s what I do.Interviewee: Probably, somebody hire wants to able to do things they he wants, or business give away orsomething.Interviewer: That’s doesn’t matter, everybody will profit, and that’s the most important. Ok. I think this isit. Do you have any questions or suggestions?
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D Startup Profiles - Extended
Habitissimo.es
Most Important Factors in each Factor GroupThe interviewer asked the interviewee to prioritize a top 3 for each of the factor groups, namely fac-tors related to the investor, the founders and the startup, the facilitator, and the external environmentof the first conceptual internet startup framework (figure 2).According to Jordi, capital is the most important factor that the investors should provide. There’sa difference between smart money and not smart money. First, Habitissimo needed some smartmoney from SeedRocket, later on they only needed money in order to really accelerate.Commitment is the most important factor related to the founders, because you need to be committedand stay motivated. When you keep trying, you learn, and then you’re more likely to succeed. Ina startup it’s all about execution, so founders need to be competent enough in order to do so. Andthen, they’re also able to pivot when its necessary. Jordi also mentioned a complementary team,your team is stronger when you complement each other.A startup’s strategy is the most important factor related to the startup. Because, from the start, youreally need to know how you’re going to penetrate the market. The business model is also importantin order to make sure you’re able to make money with it. Next to it, a startup’s mission and visionis used to help you and the team to stay motivated.The most important factors related to the facilitator are the network, the experience, and the facili-ties. In some cases the facilitator brings money as well that can really help you to take off, like therole of SeedRocket.The economical environment is important for a startup and is therefore the most important factorrelated to the external environment. For Habitissimo it was helpful, because a couple years before,construction companies were fully booked, but because of the crises they were accepting ordersfrom the internet. Competitors are also an important factor, because its an indicator for the market,its a source of best practices, and you can learn from them. And last, the technological environmentfactor is important, because it makes things possible whereas it was impossible a few yeas ago, nowit’s more accessible and much cheaper.Companies rely on the customers’ need for solving the solution of a problem, so the need is animportant factor related to the customer. Solving the need, but keeping the customer satisfied is alsoreally important, and when they’re happy, they start spreading the word via their network.
The Startup PerformanceThe interviewer asked the interviewee to validate the hypotheses by answering the question whetherthey agreed with the hypotheses or not (page ??).According to Jordi the factors related to the investors influence the founders performance (H1) anddon’t influence the resource availability (H2), because at some point capital might be harmful.The factors related to the founders and the startups influence the startup performance (H3), onlyin the case of the factors related to the founders and not the factors related to the startup. Havinga good business plan does not mean the startup is going to succeed, and the mission and vision,strategy, and the business plan can also be wrong.
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The factors related to the founders and the startups influence founders performance (H4) and don’tinfluence the product / service performance (H5) and the resource availability (H6). It’s also becauseof the same reasons mentioned in the previous paragraph.The factors related to the facilitator influences the founders performance (H7) and the product /
service performance (H8).The factors related to the external environment don’t influence founders performance (H9), product/ service performance (H10), and the resource availability (H11). External factors can harm thestartup performance, but it doesn’t have to be that they all can improve it. For instance, too muchmedia attention might prove a distraction, overconfidence, etc.The factors related to the customer influence startup performance (H12) and do not influence thefounders performance (H13) and the product / service performance (H14).
Guideguide.com
Most Important Factors in each Factor GroupThe interviewer asked the interviewee to prioritize a top 3 for each of the factor groups, namelyfactors related to the investor, the founders and the startup, the facilitator, the external environment,and the customer of the first conceptual internet startup framework (figure 2).Investors should provide capital, and if possible no knowledge. Because, knowledge of the investorsgets in the way. The resources provided by the investor are more important than the knowledge.Investors should not intervene in the daily tasks of the startup. So in this correct order, it are thefactors capital, resources, and knowledge that are the most important factors related to the investor.The vision is the most important factor related to the founders, motivation and commitment comesecond and third. Vision is the ultimate goal of the founders and should be clear from the beginning.In case of the factors related to the startup mission and vision is again the most important. Businessmodel and network come second and third. Network, facilities, and experience in this order are mostimportant in factors related to the facilitator. Economical environment is the most important factorrelated to the external environment. Competitors and the technology environment come second andthird. User satisfaction is most important factor related to the customer. Need and contracting comesecond and third.
The Startup PerformanceThe interviewer asked the interviewee to validate the hypotheses by answering the question whetherthey agreed with the hypotheses or not (page ??).The factors related to the investors don’t influence the founders performance (H1). Because, thefounders are more interested in their vision rather than the money. They just want to do their thing.If they get more capital, it makes it easier, but if they don’t get any capital, they would still trying,because of their vision. The factors related to the investors and influence resource availability (H2),because they’ve access to facilities, developers, network and the money helps.The factors related to the founders and the startup all influence the startup performance (H3), thefounders performance (H4), the product / service performance (H5), and the resource availability(H6). Vision and commitment is really important. With vision you stimulate innovation and withcommitment you’re trying to find your product market fit.The factors related to the facilitator do not influence founders performance (H7), because network
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nor experience helps you to perform better. On the other side, it does influence the resource avail-ability (H8), because facilitators help via their network.The factors related to the external environment do not influence the founders performance (H9) andthe product / service performance (H10), because they change with the external environment. But,the external environment influences the resource availability (H11). For example, when the dot.comcrash came, it was really easy to get developers.The factors related to the customer influence the startup performance (H12), the founders perfor-mance (H13), and the product / service performance (H14).
ChangeYourFlight.com
Most Important Factors in each Factor GroupThe interviewer asked the interviewee to prioritize a top 3 for each of the factor groups, namelyfactors related to the investor, the founders and the startup, the facilitator, the external environment,and the customer of the first conceptual internet startup framework (figure 2).Followed by the factors knowledge and resources, capital is the most important factor related to theinvestor. Jose Luis also mentioned creating traction is really important for the awareness of yourstartup.The most important factors related to the founders are commitment, adaptability, and competence.And the most important factors related to the startup are business model, market knowledge, andcooperation.By the most important factors related to facilitator(s), Jose Luis mentioned motivation and reach.These factors are not included in the framework, but are important factors related to the facilitator.Resources is also important.Media attention (awareness), competitors (e.g., other startups fundraising should be considered ascompetitors in the $ arena), and the social environment (useful to look for talent) are the mostimportant factors related to the external environment.The most important factors related to the customer are user satisfaction, in B2B cases Jose Luismentioned the manager’s satisfaction, then the need, and the added value for the customer.
The startup perfomanceThe interviewer asked the interviewee to validate the hypotheses by answering the question whetherthey agreed with the hypotheses or not (page ??).The factors related to the investors do influence the founder’s performance (H1), but do not influenceresource availability (H2). The factors related to the founders and the startup do influence the startupperformance (H3), the founders performance (H4), and the product / service performance (H5), butnot the resource availability (H6), because it’s mostly unrelated. The factors related to the facilitatordo influence founders performance (H7) and the resource availability (H8). The factors relatedto the external environment do not influence founders performance (H9) and the product / serviceperformance (H10), but do influence the resource availability (H11). The factors related to thecustomer do influence startups performance (H12) and the product / service performance (H14), butdo not influence the founders performance (H13).
Teambox.com
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Most Important Factors in each Factor GroupThe most important related to the investor is capital, and they shouldn’t intervene with the internalprocesses of the startup, because otherwise is more of a hassle. So, it should be properly aligned.Then, in early stage startups, knowledge is more important, and in later stage startups resources aremore important. So, in this order, knowledge, capital and resources are most important.A complementary team is the most important factor related to the founders. Because if you don’thave this, you’re just one in the crowd, you’ll not be noticed.Then vision and decision making comesecond and third.The business model is the most important factor related to the startup and you should have it fromthe beginning. Market knowledge is important, becuae you need to know how people are going tofind you.The current order is the right order, so experience, resources, and facilities are the most importantfactors related to the facilitator. Experience is handful in order to assist you in the beginning.The customer need is the most important factor related to the customer, because it’s hard to sellsomething people don’t need. User satisfaction comes second and is contracting third.The most important factor related to the external environment is media attention. You need it todrive growth. The technological environment comes second and the competitor third.
The Startup PerformanceThe interviewer asked the interviewee to validate the hypotheses by answering the question perfactor group to divide 100 by the connected arrows that indicator the hypothese (page ??).The interviewee divided 100 by 30 for H1 and 70 for H2. In a way investors coach the founders(H1). The investor mostly influences the resource availability (H2), because most of the time youneed capital and developers.By the factors related to the founders and startup that influence the performance, the intervieweedivided 100 by 40 for H3, 20 for H4, 30 for H5, and 10 for H6. Resource availability (H6) is nota major factor, more important are the KPI’s (H3), and then the product / service (H5), and thefounders are not really influenced bu the founders and startup (H4).For the factors related to facilitators only influence the founders performance (H7) and not theresource availability (H8). So, it’s divided by 100-0. Everybody can help you by understand theproduct and coach you to do better.The factors related to the external environment equally influences the founders performance (H9),the product / service performance (H10), and the resource availability (H11). So, it’s 33 for H9, 33for H10, and 33 for H11.The interviewee divided the factors related to the customer by 60 for H12, 10 for H13, and 30 forH14. The customers influence the startup performance (H12) by providing you insights about theirbehavior. They customer less strongly influences the founders performance (H13) and the product /
service performance (H14).Last, the interviewee divided 100 among the hypotheses H15-H18, namely the startup performance,the founders performance, the product / service performance, and the resource availability. Thedivision is 40-25-25-10.
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E Online Survey
The survey has been constructed with QuestionPro.com, because they provide a Spotlight Report.The Spotlight Report allows us to share the results of the survey in a very unique way with all theusers who took the survey. The Spotlight Report also allows the respondents to visually see howtheir responses compared to the overall survey responses.
Page 1
[like button] [tweet button] – on every page –
internet Startup Success Factors – on every page –
[progress bar]
Hi,
Do you or did you own an internet startup that has been successful or unsuccessful? Great. We, of the UtrechtUniversity, are trying to identify success and failure factors at the different stages of the internet startup lifecycle.
You can help us by filling out this survey and share it with other entrepreneurs you know. The survey existsof 6 parts and will take approximately 10-15 minutes.
Your survey responses will be strictly confidential and data from this research will be reported only in theaggregate. Your information will be coded and will remain confidential. If you have questions, contact DirkJan.
After submitting the survey you’ve the possibility to benchmark your internet startup with all answers. Afteranalyzing the results we’ll write a research report and sent it to you as well.
Thank you very much for your time and support. Please start with the survey now by clicking on the ’Con-tinue’ button below.
Dirk Jan Menkveld Utrecht University http://about.me/djmenkveld [email protected]
and
Prof. Sjaak Brinkkemper Utrecht University personal webpage
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Page 2
Questions marked with an * are required[progress bar]
1. Discovery - finding the customer
In this stage you’re trying to find out who your customer is. This means answering the question whether yoursolution is solving a real life problem. Besides this, you:
• create a founding team
• conduct customer interviews
• find value proposition
• build a minimal viable product
• join incubator, first advisors on board
• finance it yourself
How important is each factor in the discovery stage?
Unimportant Of little im-portance
Moderatelyimportant
Important Very impor-tant
Working experience * o o o o oCommitment * o o o o oLearning * o o o o oPivot / adaptability * o o o o oBusiness model / plan * o o o o oNetwork * o o o o oBusiness partners * o o o o oStaffing * o o o o oFinancial capital * o o o o oMarket / competitors * o o o o ocustomers * o o o o oIncubator / advisors * o o o o o
Working experience: general knowledge of the industry and previously working experience.Commitment: the state of being dedicated to the startupLearning: the acquisition of knowledge or skills through experience and apply itPivot / adaptability: the ability to shift to a new directionBusiness model / plan: the way how the startup creates, delivers, and captures valueNetwork: a group or system of interconnected people or things that surrounding the startup
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Business partners: a commercial entity with which you can form an allianceStaffing: the process of hiring people (who and why)Financial capital: the amount of money and assets needed to build a sustainable businessMarket: a combined place of different entities whereby parties engage in exchangeCustomers: the people or firms that use the product or serviceIncubator / advisors: support from an instance or people in order to accelerate
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Page 3
Questions marked with an * are required[progress bar]
2. Validation - validating the business model
In this stage you’re validating whether your users are willing to pay for your product or service. This meansdeveloping your business model. Besides this, you:
• are refining core features
• initiate user growth
• implement metrics and analytics
• get seed funding
• hire first employee
• find your product market fit
How important is each factor in the discovery stage?
Unimportant Of little im-portance
Moderatelyimportant
Important Very impor-tant
Working experience * o o o o oCommitment * o o o o oLearning * o o o o oPivot / adaptability * o o o o oBusiness model / plan * o o o o oNetwork * o o o o oBusiness partners * o o o o oStaffing * o o o o oFinancial capital * o o o o oMarket / competitors * o o o o ocustomers * o o o o oIncubator / advisors * o o o o o
Working experience: general knowledge of the industry and previously working experience.Commitment: the state of being dedicated to the startupLearning: the acquisition of knowledge or skills through experience and apply itPivot / adaptability: the ability to shift to a new directionBusiness model / plan: the way how the startup creates, delivers, and captures valueNetwork: a group or system of interconnected people or things that surrounding the startup
184
Business partners: a commercial entity with which you can form an allianceStaffing: the process of hiring people (who and why)Financial capital: the amount of money and assets needed to build a sustainable businessMarket: a combined place of different entities whereby parties engage in exchangeCustomers: the people or firms that use the product or serviceIncubator / advisors: support from an instance or people in order to accelerate
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Page 4
Questions marked with an * are required[progress bar]
3. Efficiency - optimizing product and processes
In this stage you’re optimizing the business processes and the product / service (customer experience). Thisincludes improving the user acquisition process. Besides this, you:
• refine the value proposition
• improve the user experience
• optimize conversion funnels
• achieve viral growth
• find repeatable sales process and scalable user acquisition channels
How important is each factor in the efficiency stage?
Unimportant Of little im-portance
Moderatelyimportant
Important Very impor-tant
Working experience * o o o o oCommitment * o o o o oLearning * o o o o oPivot / adaptability * o o o o oBusiness model / plan * o o o o oNetwork * o o o o oBusiness partners * o o o o oStaffing * o o o o oFinancial capital * o o o o oMarket / competitors * o o o o ocustomers * o o o o oIncubator / advisors * o o o o o
Working experience: general knowledge of the industry and previously working experience.Commitment: the state of being dedicated to the startupLearning: the acquisition of knowledge or skills through experience and apply itPivot / adaptability: the ability to shift to a new directionBusiness model / plan: the way how the startup creates, delivers, and captures valueNetwork: a group or system of interconnected people or things that surrounding the startupBusiness partners: a commercial entity with which you can form an alliance
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Staffing: the process of hiring people (who and why)Financial capital: the amount of money and assets needed to build a sustainable businessMarket: a combined place of different entities whereby parties engage in exchangeCustomers: the people or firms that use the product or serviceIncubator / advisors: support from an instance or people in order to accelerate
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Page 5
Questions marked with an * are required[progress bar]
4. Scale - conquering the market
In this stage you’re accelerating very rapidly in order to create growth aggressively. Besides this, you:
• get a large round
• start massive customer acquisition
• improve back-end scalability
• hire first executive
• implement processes
• establish departments
How important is each factor in the scale stage?
Unimportant Of little im-portance
Moderatelyimportant
Important Very impor-tant
Working experience * o o o o oCommitment * o o o o oLearning * o o o o oPivot / adaptability * o o o o oBusiness model / plan * o o o o oNetwork * o o o o oBusiness partners * o o o o oStaffing * o o o o oFinancial capital * o o o o oMarket / competitors * o o o o oCustomers * o o o o oIncubator / advisors * o o o o o
Working experience: general knowledge of the industry and previously working experience.Commitment: the state of being dedicated to the startupLearning: the acquisition of knowledge or skills through experience and apply itPivot / adaptability: the ability to shift to a new directionBusiness model / plan: the way how the startup creates, delivers, and captures valueNetwork: a group or system of interconnected people or things that surrounding the startupBusiness partners: a commercial entity with which you can form an alliance
188
Staffing: the process of hiring people (who and why)Financial capital: the amount of money and assets needed to build a sustainable businessMarket: a combined place of different entities whereby parties engage in exchangeCustomers: the people or firms that use the product or serviceIncubator / advisors: support from an instance or people in order to accelerate
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Page 6
Questions marked with an * are required[progress bar]
5. Startup profile
Do you consider your startup as a success, failure, or still undecided? *o Successo Failureo Still undecided
Please explain your answer shortly. *[textbox]
In what stage of the startup life cycle is the startup now? *(in case of failure: in what stage of the startup life cycle did the startup fail?) *o Discovery - finding the customero Validation - validating the business modelo Optimization - optimizing the product and processeso Scale - conquering the market
How many people found the startup? *[– Select – ]1234567 or more
Is the founding team more business- or technical centric? *o Business centrico Technical centrico Balanced
How many employees do you have? *o 0o 1-5o 6-10o 11-20o 21-50o 51-100o 101 or more
Is your product or service targeting a consumer market or an enterprise market? *o Consumer producto Enterprise producto Both
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Is your product or service targeting the local, regional, national, or international market? *o Local marketo Regional marketo National marketo International market
Where is the startup located? (please provide city and country, e.g.: "Amsterdam, The Netherlands") *[textbox]
When was the startup founded? *o 2010o 2009o 2008o 2007o 2006o Other [textbox]
What is the name of your startup? (optional; will not be published and will be used more in-depth knowledge)[textbox]
What is the URL of your startup? (optional; will not be published and will be used more in-depth knowledge)[textbox]
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Page 7
Questions marked with an * are required[progress bar]
6. Profile of the entrepreneur
Are you male of female? *o Maleo Female
What is your age? *[textbox]
What is the highest level of education you have completed? *[– Select –]Didn’t graduate high schoolHigh School / GEDSome collegeAssociates degreeBachelors degreeMasters degreeDoctorate degreeProfessional degree
What is your email address? (will not be published; the report will be sent to this email address and oncompletion of this research project your email address wil be deleted) *[textbox]
Page 8
This page shows the respondents the Spotlight Report where it allows the respondents to visually see howtheir responses compared to the overall survey responses. A blue star is presented to mark "Your choice" anda open square is presented with the "Overall", so the respondent can compare the results. All question arepresented, except the "email address" question.
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F Tables
F.1 Factors in Discovery - Paired Samples Test
Table 65: Paired samples test for the factor pivot / adaptability vs. all factors in discovery (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. A_PIVOTA-A_WOREXP 1.292 1.031 .149 8.684 47 .000Pair 2. A_PIVOTA-A_COMMIT -.125 .789 .114 -1.098 47 .278Pair 3. A_PIVOTA-A_LEARNN .042 .944 .136 .306 47 .761Pair 4. A_PIVOTA-A_BMOPLN 1.333 1.078 .156 8.565 47 .000Pair 5. A_PIVOTA-A_NETWRK .583 1.048 .151 3.855 47 .000Pair 6. A_PIVOTA-A_BUSPAR 1.313 1.339 .193 6.789 47 .000Pair 7. A_PIVOTA-A_STAFFN 1.688 1.490 .215 7.848 47 .000Pair 8. A_PIVOTA-A_FINCAP 1.729 1.469 .212 8.153 47 .000Pair 9. A_PIVOTA-A_MARKET 1.542 1.271 .183 8.404 47 .000Pair 10. A_PIVOTA-A_CUSTOM .645 1.158 .167 3.865 47 .000Pair 11. A_PIVOTA-A_INCUBA 1.667 1.191 .172 9.695 47 .000
Table 66: Paired Samples Test for the factor learning vs. all factors in discovery (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. A_LEARNN-A_WOREXP 1.250 1.280 .185 6.766 47 .000Pair 2. A_LEARNN-A_COMMIT -.167 .859 .124 -1.345 47 .185Pair 3. A_LEARNN-A_PIVOTA -.042 .944 .136 -.306 47 .761Pair 4. A_LEARNN-A_BMOPLN 1.292 1.336 .193 6.697 47 .000Pair 5. A_LEARNN-A_NETWRK .542 1.202 .174 3.122 47 .003Pair 6. A_LEARNN-A_BUSPAR 1.271 1.425 .206 6.177 47 .000Pair 7. A_LEARNN-A_STAFFN 1.646 1.436 .207 7.938 47 .000Pair 8. A_LEARNN-A_FINCAP 1.687 1.518 .219 7.701 47 .000Pair 9. A_LEARNN-A_MARKET 1.500 1.321 .191 7.868 47 .000Pair 10. A_LEARNN-A_CUSTOM .604 1.250 .190 3.348 47 .002Pair 11. A_LEARNN-A_INCUBA 1.625 1.282 .185 8.782 47 .000
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F.2 Factors in Validation - Paired Samples Test
Table 67: Paired Samples Test for the factor learning vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_LEARNN-B_WOREXP .750 1.082 .156 4.803 47 .000Pair 2. B_LEARNN-B_COMMIT -.188 .816 .118 -1.592 47 .118Pair 3. B_LEARNN-B_PIVOTA -.188 .816 .118 1.592 47 .118Pair 4. B_LEARNN-B_BMOPLN .604 1.250 .180 3.348 47 .029Pair 5. B_LEARNN-B_NETWRK .396 1.216 .175 2.256 47 .002Pair 6. B_LEARNN-B_BUSPAR .708 1.458 .210 3.366 47 .000Pair 7. B_LEARNN-B_STAFFN .896 1.242 .179 4.998 47 .000Pair 8. B_LEARNN-B_FINCAP 1.125 1.282 .185 6.080 47 .000Pair 9. B_LEARNN-B_MARKET .771 1.207 .174 4.424 47 .000Pair 10. B_LEARNN-B_CUSTOM .083 1.285 .186 .449 47 .655Pair 11. B_LEARNN-B_INCUBA 1.083 1.200 .173 6.255 47 .000
Table 68: Paired Samples Test for the factor customers vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_CUSTOM-B_WOREXP .667 1.115 .167 4.000 47 .000Pair 2. B_CUSTOM-B_COMMIT -.271 1.280 .170 -1.590 47 .119Pair 3 B_CUSTOM-B_LEARNN -.083 1.285 .186 -.449 47 .655Pair 4. B_CUSTOM-B_PIVOTA .104 1.341 .194 .538 47 .593Pair 5. B_CUSTOM-B_BMOPLN .521 1.220 .176 2.957 47 .005Pair 6. B_CUSTOM-B_NETWRK .313 .949 .137 2.282 47 .027Pair 7. B_CUSTOM-B_BUSPAR .625 1.214 .175 3.567 47 .001Pair 8. B_CUSTOM-B_STAFFN .813 1.266 .183 4.447 47 .000Pair 9. B_CUSTOM-B_FINCAP 1.042 1.237 .179 5.834 47 .000Pair 10. B_CUSTOM-B_MARKET .668 .993 .143 4.798 47 .000Pair 11. B_CUSTOM-B_INCUBA 1.000 1.130 .163 3.345 47 .000
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Table 69: Paired Samples Test for the factor pivot / adaptability vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_PIVOTA-B_WOREXP .562 1.165 .168 3.345 47 .002Pair 2. B_PIVOTA-B_COMMIT -.375 .959 .138 -2.708 47 .009Pair 3. B_PIVOTA-B_LEARNN -.188 .816 .118 -1.592 47 .118Pair 4. B_PIVOTA-B_BMOPLN .417 1.427 .206 2.023 47 .049Pair 5. B_PIVOTA-B_NETWRK .208 1.320 .191 1.093 47 .280Pair 6. B_PIVOTA-B_BUSPAR .521 1.584 .229 2.278 47 .027Pair 7. B_PIVOTA-B_STAFFN .708 1.398 .202 3.509 47 .001Pair 8. B_PIVOTA-B_FINCAP .937 1.359 .196 4.779 47 .000Pair 9. B_PIVOTA-B_MARKET .583 1.235 .178 3.273 47 .002Pair 10. B_PIVOTA-B_CUSTOM -.104 1.341 .194 -.538 47 .593Pair 11. B_PIVOTA-B_INCUBA .896 1.309 .189 4.743 47 .000
Table 70: Paired Samples Test for the factor network vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_NETWRK-B_WOREXP .354 1.062 .153 2.311 47 .025Pair 2. B_NETWRK-B_COMMIT -.583 1.108 .160 -3.649 47 .001Pair 3. B_NETWRK-B_LEARNN -.396 1.216 .175 -2.256 47 .029Pair 4. B_NETWRK-B_PIVOTA -.208 1.320 .191 -1.093 47 .280Pair 5. B_NETWRK-B_BMOPLN .208 1.110 .160 1.300 47 .200Pair 6. B_NETWRK-B_BUSPAR .313 .971 .140 2.230 47 .031Pair 7. B_NETWRK-B_STAFFN .500 1.092 .158 3.174 47 .003Pair 8. B_NETWRK-B_FINCAP .729 1.026 .148 4.924 47 .000Pair 9. B_NETWRK-B_MARKET .375 .841 .121 3.089 47 .003Pair 10. B_NETWRK-B_CUSTOM -.313 .949 .137 -2.282 47 .027Pair 11. B_NETWRK-B_INCUBA .688 1.188 .171 4.010 47 .000
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Table 71: Paired Samples Test for the factor business model / plan vs. all factors in validation(n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_BMOPLN-B_WOREXP .354 1.062 .153 2.311 47 .025Pair 2. B_BMOPLN-B_COMMIT -.583 1.108 .160 -3.649 47 .001Pair 3. B_BMOPLN-B_LEARNN -.396 1.216 .175 -2.256 47 .029Pair 4. B_BMOPLN-B_PIVOTA -.208 1.320 .191 -1.093 47 .280Pair 5. B_BMOPLN-B_NETWRK .208 1.110 .160 1.300 47 .200Pair 6. B_BMOPLN-B_BUSPAR .313 .971 .140 2.230 47 .031Pair 7. B_BMOPLN-B_STAFFN .500 1.092 .158 3.174 47 .003Pair 8. B_BMOPLN-B_FINCAP .729 1.026 .148 4.924 47 .000Pair 9. B_BMOPLN-B_MARKET .375 .841 .121 3.089 47 .003Pair 10. B_BMOPLN-B_CUSTOM -.313 .949 .137 -2.282 47 .027Pair 11. B_BMOPLN-B_INCUBA .688 1.188 .171 4.010 47 .000
Table 72: Paired Samples Test for the factor network vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_BUSPAR-B_WOREXP .042 1.237 .179 .233 47 .816Pair 2. B_BUSPAR-B_COMMIT -.896 1.292 .187 -4.803 47 .000Pair 3. B_BUSPAR-B_LEARNN -.708 1.458 .210 -3.366 47 .002Pair 4. B_BUSPAR-B_PIVOTA -.521 1.584 .229 -2.278 47 .027Pair 5. B_BUSPAR-B_BMOPLN -.104 1.418 .205 -.509 47 .613Pair 6. B_BUSPAR-B_NETWRK -.313 .971 .140 -2.230 47 .031Pair 7. B_BUSPAR-B_STAFFN .188 1.161 .168 -1.119 47 .269Pair 8. B_BUSPAR-B_FINCAP .417 1.048 .151 2.753 47 .008Pair 9. B_BUSPAR-B_MARKET .063 1.156 .167 .375 47 .710Pair 10. B_BUSPAR-B_CUSTOM -.625 1.214 .175 -3.567 47 .001Pair 11. B_BUSPAR-B_INCUBA .375 1.299 .187 2.001 47 .051
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Table 73: Paired Samples Test for the factor working experience vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_WOREXP-B_COMMIT -.937 .976 .141 -6.652 47 .000Pair 2. B_WOREXP-B_LEARNN -.750 1.082 .156 -4.803 47 .000Pair 3. B_WOREXP-B_PIVOTA -.562 1.165 .168 -3.345 47 .002Pair 4. B_WOREXP-B_BMOPLN -.146 1.288 .186 -.784 47 .437Pair 6. B_WOREXP-B_NETWRK -.354 1.062 .153 -2.311 47 .025Pair 4. B_WOREXP-B_BUSPAR -.042 1.237 .179 -.233 47 .816Pair 7. B_WOREXP-B_STAFFN .146 1.148 .166 .880 47 .383Pair 8. B_WOREXP-B_FINCAP .375 1.084 .156 2.396 47 .021Pair 9. B_WOREXP-B_MARKET .021 1.082 .156 .133 47 .894Pair 10. B_WOREXP-B_CUSTOM -.667 1.155 .167 -4.000 47 .000Pair 11. B_WOREXP-B_INCUBA .333 1.059 .153 2.182 47 .034
Table 74: Paired Samples Test for the factor market / competitors vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_MARKET-B_WOREXP -.021 1.082 .156 -.133 47 .894Pair 2. B_MARKET-B_COMMIT -.958 1.220 .176 -5.444 47 .000Pair 3. B_MARKET-B_LEARNN -.771 1.207 .174 -4.424 47 .000Pair 4. B_MARKET-B_PIVOTA -.583 1.235 .178 -4.273 47 .002Pair 5. B_MARKET-B_BMOPLN -.167 1.243 .179 -.929 47 .358Pair 6. B_MARKET-B_NETWRK -.375 .841 .121 -3.089 47 .003Pair 7. B_MARKET-B_BUSPAR -.063 1.156 .167 -.375 47 .710Pair 8. B_MARKET-B_STAFFN .125 1.378 .199 .628 47 .533Pair 9. B_MARKET-B_FINCAP .354 1.345 .194 1.825 47 .074Pair 10. B_MARKET-B_CUSTOM -.688 .993 .143 -4.798 47 .000Pair 11. B_MARKET-B_INCUBA .313 1.133 .164 1.911 47 .062
197
Table 75: Paired Samples Test for the factor staffing vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_STAFFN-B_WOREXP -.146 1.148 .166 -.880 47 .383Pair 2. B_STAFFN-B_COMMIT -1.083 1.069 .154 -7.024 47 .000Pair 3. B_STAFFN-B_LEARNN -.896 1.242 .179 -4.998 47 .000Pair 4. B_STAFFN-B_PIVOTA -.708 1.398 .202 -3.509 47 .001Pair 5. B_STAFFN-B_BMOPLN -.292 1.501 .217 -1.346 47 .185Pair 6. B_STAFFN-B_NETWRK -.500 1.092 .158 -3.174 47 .003Pair 7. B_STAFFN-B_BUSPAR -.188 1.161 .168 -1.119 47 .269Pair 8. B_STAFFN-B_FINCAP .229 .831 .120 1.910 47 .062Pair 9. B_STAFFN-B_MARKET -.125 1.378 .199 -.628 47 .533Pair 10. B_STAFFN-B_CUSTOM -.813 1.266 .183 -4.447 47 .000Pair 11. B_STAFFN-B_INCUBA .188 1.331 .192 .976 47 .334
Table 76: Paired Samples Test for the factor incubator / advisors vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_INCUBA-B_WOREXP -.333 1.059 .153 -2.182 47 .034Pair 2. B_INCUBA-B_COMMIT -1.271 1.125 .162 -7.827 47 .000Pair 3. B_INCUBA-B_LEARNN -1.083 1.200 .173 -6.255 47 .000Pair 4. B_INCUBA-B_PIVOTA -.896 1.309 .189 -4.743 47 .000Pair 5. B_INCUBA-B_BMOPLN -.479 1.255 .181 -2.646 47 .011Pair 6. B_INCUBA-B_NETWRK -.688 1.188 .171 -4.010 47 .000Pair 7. B_INCUBA-B_BUSPAR -.375 1.299 .187 -2.001 47 .051Pair 8. B_INCUBA-B_STAFFN .-188 1.331 .192 -.976 47 .334Pair 9. B_INCUBA-B_FINCAP .042 1.166 .168 .248 47 .806Pair 10. B_INCUBA-B_MARKET -.313 1.133 .164 -1.911 47 .062Pair 11. B_INCUBA-B_CUSTOM 1.000 1.130 .163 -6.132 47 .000
198
Table 77: Paired Samples Test for the factor financial capital vs. all factors in validation (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. B_FINCAP-B_WOREXP -.375 1.084 .156 -2.396 47 .021Pair 2. B_FINCAP-B_COMMIT -1.312 1.095 .158 -8.307 47 .000Pair 3. B_FINCAP-B_LEARNN -1.125 1.282 .185 -6.080 47 .000Pair 4. B_FINCAP-B_PIVOTA -.937 1.359 .196 -4.779 47 .000Pair 5. B_FINCAP-B_BMOPLN -.521 1.321 .191 -2.732 47 .009Pair 6. B_FINCAP-B_NETWRK -.729 1.026 .148 -4.924 47 .000Pair 7. B_FINCAP-B_BUSPAR -.417 1.048 .151 -2.753 47 .008Pair 8. B_FINCAP-B_STAFFN -.229 .831 .120 -1.910 47 .062Pair 9. B_FINCAP-B_MARKET -.354 1.345 .194 -1.825 47 .074Pair 10. B_FINCAP-B_CUSTOM -1.042 1.237 .179 -5.834 47 .000Pair 11. B_FINCAP-B_INCUBA -.042 1.166 .168 -.248 47 .806
199
F.3 Factors in Efficiency - Paired Samples Test
Table 78: Paired Samples Test for the factor commitment vs. all factors in efficiency (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. C_COMMIT-C_WOREXP .667 .859 .124 5.378 47 .000Pair 2. C_COMMIT-C_LEARNN .167 .883 .127 1.307 47 .197Pair 3. C_COMMIT-C_PIVOTA .708 1.148 .166 4.2 76 47 .000Pair 4. C_COMMIT-C_BMOPLN .979 1.158 .167 5.860 47 .000Pair 5. C_COMMIT-C_NETWRK .813 1.003 .145 5.611 47 .000Pair 6. C_COMMIT-C_BUSPAR .688 1.035 .149 4.604 47 .000Pair 7. C_COMMIT-C_STAFFN .646 1.158 .167 3.865 47 .000Pair 8. C_COMMIT-C_FINCAP 1.000 .968 .140 7.160 47 .000Pair 9. C_COMMIT-C_MARKET .896 1.096 .158 5.662 47 .000Pair 10. C_COMMIT-C_CUSTOM -.083 .871 .126 -.663 47 .511Pair 11. C_COMMIT-C_INCUBA 1.375 1.044 .151 9.123 47 .000
Table 79: Paired Samples Test for the factor learning vs. all factors in efficiency (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. C_LEARNN-C_WOREXP .500 .989 .143 3.502 47 .001Pair 2. C_LEARNN-C_COMMIT -.167 .883 .127 -1.307 47 .197Pair 3. C_LEARNN-C_PIVOTA .542 .988 .143 3.797 47 .000Pair 4. C_LEARNN-C_BMOPLN .812 1.085 .157 5.189 47 .000Pair 5. C_LEARNN-C_NETWRK .646 1.176 .170 3.805 47 .000Pair 6. C_LEARNN-C_BUSPAR .521 1.148 .166 3.142 47 .003Pair 7. C_LEARNN-C_STAFFN .479 1.167 .168 2.845 47 .007Pair 8. C_LEARNN-C_FINCAP .833 1.191 .172 4.848 47 .000Pair 9. C_LEARNN-C_MARKET .729 1.198 .173 4.216 47 .000Pair 10. C_LEARNN-C_CUSTOM -.250 .957 .138 -1.811 47 .077Pair 11. C_LEARNN-C_INCUBA 1.208 1.129 .163 7.415 47 .000
200
F.4 Factors in Scale - Paired Samples Test
Table 80: Paired Samples Test for the factor commitment vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_COMMIT-D_WOREXP .313 .971 .140 2.230 47 .031Pair 2. D_COMMIT-D_LEARNN .563 .681 .098 5.721 47 .000Pair 3. D_COMMIT-D_PIVOTA 1.229 1.115 .161 7.634 47 .000Pair 4. D_COMMIT-D_BMOPLN .667 1.136 .164 4.065 47 .000Pair 5. D_COMMIT-D_NETWRK .354 1.000 .144 2.454 47 .018Pair 6. D_COMMIT-D_BUSPAR .167 .975 .141 1.184 47 .242Pair 7. D_COMMIT-D_STAFFN .063 .932 .135 .465 47 .644Pair 8. D_COMMIT-D_FINCAP -.083 .767 .111 -.753 47 .455Pair 9. D_COMMIT-D_MARKET .833 .907 .131 6.365 47 .000Pair 10. D_COMMIT-D_CUSTOM .313 .903 .130 2.398 47 .021Pair 11. D_COMMIT-D_INCUBA 1.646 1.101 .159 10.356 47 .000
Table 81: Paired Samples Test for the factor staffing vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_STAFFN-D_WOREXP .250 .957 .138 1.811 47 .077Pair 2. D_STAFFN-D_COMMIT -.063 .932 .135 -.465 47 .644Pair 3. D_STAFFN-D_LEARNN .500 1.072 .155 3.232 47 .002Pair 4. D_STAFFN-D_PIVOTA 1.167 1.260 .182 6.413 47 .000Pair 5. D_STAFFN-D_BMOPLN .604 1.180 .170 3.546 47 .001Pair 6. D_STAFFN-D_NETWRK .292 1.129 .163 1.790 47 .080Pair 7. D_STAFFN-D_BUSPAR .104 .857 .124 .843 47 .404Pair 8. D_STAFFN-D_FINCAP -.146 .799 .115 -1.265 47 .212Pair 9. D_STAFFN-D_MARKET .771 .905 .131 5.902 47 .000Pair 10. D_STAFFN-D_CUSTOM .250 .838 .121 2.067 47 .044Pair 11. D_STAFFN-D_INCUBA 1.583 1.412 .204 7.771 47 .000
201
Table 82: Paired Samples Test for the factor business partners vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_BUSPAR-D_WOREXP .146 1.321 .191 .765 47 .448Pair 2. D_BUSPAR-D_COMMIT -.167 .975 .141 -1.184 47 .242Pair 3. D_BUSPAR-D_LEARNN .396 1.086 .157 2.524 47 .015Pair 4. D_BUSPAR-D_PIVOTA 1.062 1.343 .194 5.480 47 .000Pair 5. D_BUSPAR-D_BMOPLN .500 1.321 .191 2.623 47 .012Pair 6. D_BUSPAR-D_NETWRK .188 1.085 .157 1.197 47 .237Pair 7. D_BUSPAR-D_STAFFN -.104 .857 .124 -.843 47 .404Pair 8. D_BUSPAR-D_FINCAP -.250 1.042 .150 -1.663 47 .103Pair 9. D_BUSPAR-D_MARKET .667 1.078 .156 4.283 47 .000Pair 10. D_BUSPAR-D_CUSTOM .146 .989 .143 1.022 47 .312Pair 11. D_BUSPAR-D_INCUBA 1.479 1.368 .197 7.490 47 .000
Table 83: Paired Samples Test for the factor customers vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_CUSTOM-D_WOREXP .000 1.130 .163 .000 47 1.000Pair 2. D_CUSTOM-D_COMMIT -.313 .903 .130 -2.398 47 .021Pair 3. D_CUSTOM-D_LEARNN .250 1.062 .153 1.631 47 .110Pair 4. D_CUSTOM-D_PIVOTA .917 1.412 .204 4.499 47 .000Pair 5. D_CUSTOM-D_BMOPLN .354 1.101 .159 2.229 47 .031Pair 6. D_CUSTOM-D_NETWRK .042 1.220 .176 .237 47 .814Pair 7. D_CUSTOM-D_BUSPAR -.146 .989 .143 -1.022 47 .312Pair 7. D_CUSTOM-D_STAFFN -.250 .838 .121 -2.067 47 .044Pair 9. D_CUSTOM-D_FINCAP -.396 .869 .125 -3.156 47 .003Pair 10. D_CUSTOM-D_MARKET .521 .899 .130 4.014 47 .000Pair 11. D_CUSTOM-D_INCUBA 1.333 1.243 .197 7.429 47 .000
202
Table 84: Paired Samples Test for the factor working experience vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_WOREXP-D_COMMIT -.313 .971 .140 -2.230 47 .031Pair 2. D_WOREXP-D_LEARNN .250 1.042 .150 1.663 47 .103Pair 3. D_WOREXP-D_PIVOTA .917 1.318 .190 4.818 47 .000Pair 4. D_WOREXP-D_BMOPLN .354 1.082 .156 2.269 47 .028Pair 5. D_WOREXP-D_NETWRK .042 1.071 .155 .270 47 .789Pair 6. D_WOREXP-D_BUSPAR -.146 1.321 .191 -.765 47 .448Pair 7. D_WOREXP-D_STAFFN -.250 .957 .138 -1.811 47 .077Pair 8. D_WOREXP-D_FINCAP -.396 .939 .136 -2.919 47 .005Pair 9. D_WOREXP-D_MARKET .521 1.010 .146 3.571 47 .001Pair 10. D_WOREXP-D_CUSTOM .000 1.130 .163 .000 47 1.000Pair 11. D_WOREXP-D_INCUBA 1.333 1.326 .191 6.965 47 .000
Table 85: Paired Samples Test for the factor network vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_NETWRK-D_WOREXP -042 1.071 .155 -.270 47 .789Pair 2. D_NETWRK-D_COMMIT -.354 1.000 .144 -2.454 47 .018Pair 3. D_NETWRK-D_LEARNN .208 1.166 .168 1.238 47 .222Pair 4. D_NETWRK-D_PIVOTA .875 1.378 .199 4.399 47 .000Pair 5. D_NETWRK-D_BMOPLN .312 1.323 .191 1.636 47 .109Pair 6. D_NETWRK-D_BUSPAR -.188 1.085 .157 -1.197 47 .237Pair 7. D_NETWRK-D_STAFFN -.292 1.129 .163 -1.790 47 .080Pair 8. D_NETWRK-D_FINCAP -.438 1.029 .149 -2.944 47 .005Pair 9. D_NETWRK-D_MARKET .521 1.148 .166 2.891 47 .006Pair 10. D_NETWRK-D_CUSTOM -.042 1.220 .176 -.237 47 .814Pair 11. D_NETWRK-D_INCUBA 1.292 1.288 .186 6.950 47 .000
203
Table 86: Paired Samples Test for the factor learning vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_LEARNN-D_WOREXP -.250 1.042 .150 -1.663 47 .103Pair 2. D_LEARNN-D_COMMIT -.563 .681 .098 -5.721 47 .000Pair 3. D_LEARNN-D_PIVOTA .667 .996 .144 4.635 47 .000Pair 4. D_LEARNN-D_BMOPLN .104 1.225 .177 .589 47 .558Pair 5. D_LEARNN-D_NETWRK -.208 1.166 .168 -1.238 47 .222Pair 6. D_LEARNN-D_BUSPAR -.396 1.086 .157 -2.524 47 .015Pair 7. D_LEARNN-D_STAFFN -.500 1.072 .155 -3.232 47 .002Pair 8. D_LEARNN-D_FINCAP -.646 .934 .135 -4.792 47 .000Pair 9. D_LEARNN-D_MARKET .271 .939 .136 1.997 47 .052Pair 10. D_LEARNN-D_CUSTOM -.250 1.062 .153 -1.631 47 .110Pair 11. D_LEARNN-D_INCUBA 1.083 1.088 .157 6.897 47 .000
Table 87: Paired Samples Test for the factor business model / plan vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_BMOPLN-D_WOREXP -.354 1.082 .156 -2.269 47 .028Pair 2. D_BMOPLN-D_COMMIT -.667 1.136 .164 -4.065 47 .000Pair 3. D_BMOPLN-D_LEARNN -.104 1.225 .177 -.589 47 .558Pair 4. D_BMOPLN-D_PIVOTA .563 1.319 .190 2.954 47 .005Pair 5. D_BMOPLN-D_NETWRK -.312 1.323 .191 -1.636 47 .109Pair 6. D_BMOPLN-D_BUSPAR -.500 1.321 .191 -2.623 47 .012Pair 7. D_BMOPLN-D_STAFFN -.604 1.180 .170 -3.546 47 .001Pair 8. D_BMOPLN-D_FINCAP -.750 1.062 .153 -4.893 47 .000Pair 9. D_BMOPLN-D_MARKET .167 1.260 .182 .916 47 .364Pair 10. D_BMOPLN-D_CUSTOM .354 1.101 .159 -2.229 47 .031Pair 11. D_BMOPLN-D_INCUBA .979 1.296 .187 5.233 47 .000
204
Table 88: Paired Samples Test for the factor market / competitors vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_MARKET-D_WOREXP -.521 1.010 .146 -3.751 47 .001Pair 2. D_MARKET-D_COMMIT -.833 .907 .131 -6.365 47 .000Pair 3. D_MARKET-D_LEARNN -.271 1.939 .136 -1.997 47 .052Pair 4. D_MARKET-D_PIVOTA .396 1.349 .195 2.304 47 .048Pair 5. D_MARKET-D_BMOPLN -.167 1.260 .182 -.916 47 .364Pair 6. D_MARKET-D_NETWRK -.479 1.148 .166 -2.891 47 .006Pair 7. D_MARKET-D_BUSPAR -.667 1.078 .156 -4.283 47 .000Pair 8. D_MARKET-D_STAFFN -.771 .905 .131 -5.902 47 .000Pair 9. D_MARKET-D_FINCAP -.917 .964 .139 -6.589 47 .000Pair 10. D_MARKET-D_CUSTOM -.521 .899 .130 -4.014 47 .000Pair 11. D_MARKET-D_INCUBA .813 1.197 .173 4.704 47 .000
Table 89: Paired Samples Test for the factor pivot / adaptability vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_PIVOTA-D_WOREXP -.917 1.318 .190 -4.818 47 .000Pair 2. D_PIVOTA-D_COMMIT -1.229 1.115 .161 -7.634 47 .000Pair 3. D_PIVOTA-D_LEARNN -.667 .996 .144 -4.635 47 .000Pair 4. D_PIVOTA-D_BMOPLN -.563 1.319 .190 -2.954 47 .005Pair 5. D_PIVOTA-D_NETWRK -.875 1.378 .199 -4.399 47 .000Pair 6. D_PIVOTA-D_BUSPAR -1.062 1.343 .194 -5.480 47 .000Pair 7. D_PIVOTA-D_STAFFN -1.167 1.260 .182 -6.413 47 .000Pair 8. D_PIVOTA-D_FINCAP -1.312 1.114 .161 -8.164 47 .000Pair 9. D_PIVOTA-D_MARKET -.396 1.349 .19 5 -2.034 47 .048Pair 10. D_PIVOTA-D_CUSTOM -.917 1.412 .20 4 -4.499 47 .000Pair 11. D_PIVOTA-D_INCUBA .417 1.350 .195 2.318 47 .038
205
Table 90: Paired Samples Test for the factor incubator / advisors vs. all factors in scale (n=48)
Mean Std. Deviation Std. Error Mean t df Sig. (2-tailed)Pair 1. D_INCUBA-D_WOREXP -1.333 1.326 .191 -6.965 47 .000Pair 2. D_INCUBA-D_COMMIT -1.646 1.101 .159 -10.356 47 .000Pair 3. D_INCUBA-D_LEARNN -1.083 1.088 .157 -6.897 47 .000Pair 4. D_INCUBA-D_PIVOTA -.417 1.350 .195 -2.138 47 .038Pair 5. D_INCUBA-D_BMOPLN -.979 1.296 .187 -5.233 47 .000Pair 6. D_INCUBA-D_NETWRK -1.292 1.288 .186 -6.950 47 .000Pair 7. D_INCUBA-D_BUSPAR -1.479 1.368 .197 -7.490 47 .000Pair 8. D_INCUBA-D_STAFFN -1.583 1.412 .204 -7.771 47 .000Pair 9. D_INCUBA-D_FINCAP -1.729 1.086 .157 -11.027 47 .000Pair 10. D_INCUBA-D_MARKET -.813 1.197 .173 -4.704 47 .000Pair 11. D_INCUBA-D_CUSTOM -1.333 1.243 .179 -7.429 47 .000
206
F.5 State vs. factors - Independent Samples Test
Table 91: State vs. factors in validation - Independent Samples Test
Decided (n=23) Undecided (n=25)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .008 .994 .008 .994Commitment -1.077 .287 -.1082 .285Learning -.478 .635 -.479 .634Pivot / adaptability .346 .731 .351 .728Business model / plan .177 .860 .177 .860Network 1.019 .313 1.038 .305Business partners .553 .583 .555 .582Staffing -.178 .859 -.177 .860Financial capital -.410 .683 -.406 .687Market / competitors .800 .428 .808 .423Customers -.692 .492 -.696 .490Incubator / advisors .846 .402 .842 .404
207
Table 92: State vs. factors in efficiency - Independent Samples Test
Decided (n=23) Undecided (n=25)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience 1.380 .174 1.382 .174Commitment -.873 .387 -.876 .385Learning .288 .774 .290 .773Pivot / adaptability -.528 .600 -.523 .604Business model / plan .749 .458 .755 .454Network 1.407 .166 1.439 .158Business partners 1.195 .238 1.206 .234Staffing .252 .802 .254 .801Financial capital 1.001 .322 1.012 .317Market / competitors 1.113 .271 1.127 .266Customers .010 .992 .010 .992Incubator / advisors 1.510 .138 1.504 .140
Table 93: State vs. factors in scale - Independent Samples Test
Decided (n=23) Undecided (n=25)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .660 .512 .660 .507Commitment -.629 .532 -.636 .528Learning -.199 .843 -.201 .841Pivot / adaptability .211 .834 .211 .834Business model / plan .857 .396 .859 .395Network -.113 .911 -.114 .910Business partners .760 .451 .766 .447Staffing .908 .369 .910 .367Financial capital -.194 .847 -.195 .846Market / competitors 1.023 .311 1.032 .308Customers -.109 .913 -.109 .913Incubator / advisors .362 .719 .365 .717
208
F.6 Current stage vs. factors - Independent Samples Test
Table 94: Current stage vs. factors in validation - Independent Samples Test
Less mature (n=24) More mature (n=24)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.557 .327 -.557 .327Commitment 1.277 .644 1.277 .644Learning 1.386 .715 1.386 .715Pivot / adaptability 1.299 .850 1.299 .850Business model / plan -.265 .550 -.265 .550Network -.704 .310 -.704 .312Business partners -.670 .417 -.670 .417Staffing -.285 .505 -.285 .505Financial capital -.151 .513 -.151 .513Market / competitors .318 .611 .318 .611Customers -.149 .522 -.149 .522Incubator / advisors .156 .579 .156 .579
209
Table 95: Current stage vs. factors in efficiency - Independent Samples Test
Less mature (n=24) More mature (n=24)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.207 .837 -.207 .837Commitment 1.061 .294 1.061 .294Learning .187 .853 .187 .853Pivot / adaptability .446 .657 .446 .658Business model / plan .000 1.000 .000 1.000Network .298 .767 .298 .767Business partners .000 1.000 .000 1.000Staffing -1.295 .202 -1.295 .202Financial capital .506 .615 .506 .615Market / competitors .602 .537 .622 .537Customers .676 .818 .231 .818Incubator / advisors .820 .872 .161 .873
Table 96: Current stage vs. factors in scale - Independent Samples Test
Less mature (n=24) More mature (n=24)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.983 .331 -.983 .331Commitment 1.274 .209 1.274 .210Learning .531 .598 .531 .598Pivot adaptability -.136 .892 -.136 .892Business model plan 1.865 .069 1.865 .069Network -.159 .874 -.159 .874Business partners .650 .519 .650 .519Staffing -.232 .818 -.232 .818Financial capital .941 .352 .941 .352Market competitors -1.154 .255 -1.154 .255Customers .526 .601 .526 .601Incubator advisors 1.218 .229 1.218 .229
210
F.7 Founding team size vs. factors - Independent Samples Test
Table 97: Fouding team size vs. factors in validation - Independent Samples Test
Small (n=20) Large (n=28)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .156 .876 .162 .872Commitment -.354 .725 -.333 .741Learning -.625 .535 -.643 .524Pivot adaptability .541 .591 .549 .586Business model plan -.449 .656 -.463 .646Network -2.040 .047 -2.128 .039Business partners .339 .736 .337 .738Staffing .726 .471 .703 .486Financial capital 1.545 .129 1.583 .120Market competitors -.976 .334 -1.003 .321Customers .530 .599 .530 .599Incubator advisors -.079 .937 -.077 .939
211
Table 98: Fouding team size vs. factors in efficiency - Independent Samples Test
Small (n=20) Large (n=28)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.244 .808 -.253 .802Commitment -.533 .597 -.533 .597Learning .158 .875 .161 .873Pivot adaptability .783 .438 .789 .434Business model plan -.564 .575 -.565 .575Network -.760 .451 -.785 .437Business partners -.318 .752 -.327 .745Staffing .593 .556 .569 .573Financial capital 1.304 .199 1.329 .191Market competitors -1.335 .189 -1.312 .197Customers .667 .508 .701 .487Incubator advisors .741 .463 .756 .454
Table 99: Fouding team size vs. factors in scale - Independent Samples Test
Small (n=20) Large (n=28)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience 1.517 .136 1.516 .137Commitment .424 .673 .425 .673Learning .268 .790 .259 .797Pivot adaptability .672 .505 .704 .485Business model plan 1.451 .154 1.451 .154Network -.675 .503 -.714 .479Business partners -1.108 .274 -1.176 .246Staffing -.118 .907 -.119 .906Financial capital .315 .754 .317 .753Market competitors -.257 .799 -.246 .807Customers .624 .536 .617 .541Incubator advisors .023 .982 .023 .982
212
F.8 Founding team focus vs. factors - Independent Samples Test
Table 100: Founding team focus vs. factors in validation - Independent Samples Test (n=48)
Balanced (n=21) Unbalanced (n=27)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .774 .443 .768 .447Commitment .582 .564 .570 .572Learning -.269 .789 -.272 .786Pivot adaptability -.241 .810 -.251 .803Business model plan -.535 .595 -.517 .608Network -2.386 .021 -2.280 .029Business partners -1.038 .305 -1.027 .310Staffing -1.430 .159 -1.377 .177Financial capital -1.583 .120 -1.621 .112Market competitors -1.136 .262 -1.087 .285Customers -.888 .379 -.855 .398Incubator advisors .020 .984 .019 .985
213
Table 101: Founding team focus vs. factors in efficiency - Independent Samples Test (n=48)
Balanced (n=21) Unbalanced (n=27)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -1.803 0.078 -1.803 0.078Commitment 1.207 0.234 1.272 0.210Learning 0.495 0.623 0.492 0.625Pivot adaptability 0.506 0.615 0.511 0.612Business model plan -1.441 0.156 -1.420 0.163Network -0.640 0.525 -0.638 0.527Business partners -0.876 0.385 -0.852 0.400Staffing -1.179 0.244 -1.188 0.241Financial capital 0.964 0.340 1.007 0.319Market competitors -1.067 0.291 -1.082 0.285Customers 0.496 0.622 0.486 0.629Incubator advisors -0.757 0.453 -0.761 0.450
Table 102: Founding team focus vs. factors in scale - Independent Samples Test (n=48)
Balanced (n=21) Unbalanced (n=27)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.765 .448 -.742 .462Commitment 1.509 .138 1.517 .136Learning .468 .642 .457 .650Pivot adaptability 1.205 .234 1.234 .224Business model plan -1.388 .172 -1.378 .176Network -.020 .984 -.021 .984Business partners -.655 .516 -.620 .539Staffing -.088 .931 -.088 .930Financial capital .828 .412 .839 .406Market competitors .000 1.000 .000 1.000Customers .732 .468 .727 .472Incubator advisors .556 .581 .557 .581
214
F.9 Employees vs. factors - Independent Samples Test
Table 103: Employees vs. factors in validation - Independent Samples Test (n=48)
Employees (n=34) No employees (n=14)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .942 .351 .962 .345Commitment -.733 .467 -.638 .531Learning -2.352 .023 -2.496 .019Pivot adaptability -1.372 .177 -1.630 .112Business model plan -1.388 .172 -1.628 .112Network -.289 .774 -.337 .738Business partners 1.154 .254 1.257 .218Staffing .709 .482 .802 .429Financial capital .014 .989 .015 .988Market competitors -2.204 .033 -2.259 .033Customers -.782 .438 -.800 .431Incubator advisors -.129 .898 -.119 .906
215
Table 104: Numbers of employees vs. factors in efficiency - Independent Samples Test (n=48)
Employees (n=34) No employees (n=14)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.551 .585 -.567 .576Commitment -.872 .388 -.900 .376Learning -.086 .932 -.082 .935Pivot adaptability 1.061 .294 1.203 .238Business model plan -2.314 .025 -2.177 .041Network -1.078 .287 -.988 .334Business partners -.869 .389 -.867 .394Staffing .029 .977 .029 .977Financial capital -.698 .489 -.625 .539Market competitors -1.544 .129 -1.430 .167Customers -.875 .386 -.864 .396Incubator advisors -.044 .965 -.044 .965
Table 105: Numbers of employees vs. factors in scale - Independent Samples Test (n=48)
Employees (n=34) No employees (n=14)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .268 .790 .243 .810Commitment -.927 .359 -.970 .341Learning .437 .664 .377 .710Pivot adaptability 1.799 .079 2.086 .044Business model plan -1.462 .151 -1.746 .089Network .718 .477 .691 .496Business partners -.475 .637 -.488 .630Staffing .064 .949 .062 .951Financial capital .085 .932 .083 .934Market competitors -.278 .782 -.248 .807Customers -.531 .598 -.569 .574Incubator advisors -.012 .990 -.012 .991
216
F.10 Target focus vs. factors - Independent Samples Test
Table 106: Target focus vs. factors in validation - Independent Samples Test (n=48)
Consumer market (n=13), Entreprise market (n=21), Both (n=14)Chi-Square Asymp. Sig.
Working experience .445 .801Commitment .151 .927Learning 1.246 .536Pivot adaptability 9.435 .009Business model plan 3.536 .171Network 3.888 .143Business partners .074 .964Staffing 3.769 .152Financial capital 1.261 .532Market competitors 1.158 .560Customers 6.584 .037Incubator advisors .350 .840
217
Table 107: Target focus vs. factors in efficiency - Independent Samples Test (n=48)
Consumer market (n=13), Entreprise market (n=21), Both (n=14)Chi-Square Asymp. Sig.
Working experience 1.808 .405Commitment 4.082 .130Learning 2.697 .260Pivot adaptability 2.390 .303Business model plan 3.008 .222Network .431 .806Business partners .599 .741Staffing .989 .610Financial capital 1.038 .595Market competitors .622 .733Customers 1.005 .605Incubator advisors .204 .903
Table 108: Target focus vs. factors in scale - Independent Samples Test (n=48)
Consumer market (n=13), Entreprise market (n=21), Both (n=14)Chi-Square Asymp. Sig.
Working experience 4.075 .130Commitment .183 .912Learning .850 .654Pivot adaptability .488 .784Business model plan 3.888 .143Network 6.594 .037Business partners 1.029 .598Staffing 1.293 .524Financial capital .313 .855Market competitors 2.020 .364Customers 1.663 .435Incubator advisors .448 .799
218
F.11 Target market vs. factors - Independent Samples Test
Table 109: Target market vs. factors in validation - Independent Samples Test (n=48)
National (n=25) International (n=23)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -1.527 .134 -1.507 .140Commitment -.613 .543 -.619 .539Learning -.691 .493 -.693 .492Pivot adaptability -.027 .979 -.026 .979Business model plan -.982 .331 -.979 .333Network .044 .965 .044 .965Business partners -.284 .778 -.289 .774Staffing -1.573 .123 -1.567 .124Financial capital -.499 .620 -.505 .616Market competitors -.478 .635 -.478 .635Customers -.504 .617 -.510 .613Incubator advisors 1.048 .300 1.051 .299
219
Table 110: Target market vs. factors in efficiency - Independent Samples Test (n=48)
National (n=25) International (n=23)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience 1.144 .259 1.132 .264Commitment .873 .387 .869 .389Learning -1.048 .300 -1.046 .301Pivot adaptability -.068 .946 -.067 .947Business model plan -1.059 .295 -1.060 .295Network 1.648 .106 1.648 .106Business partners 1.698 .096 1.697 .096Staffing -1.565 .124 -1.577 .122Financial capital -1.001 .322 -1.017 .315Market competitors 1.086 .283 1.089 .282Customers 1.406 .166 1.384 .174Incubator advisors .793 .432 .797 .429
Table 111: Target market vs. factors in scale - Independent Samples Test (n=48)
National (n=25) International (n=23)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -1.059 .295 -1.063 .293Commitment .629 .532 .617 .541Learning -.154 .878 -.154 .878Pivot adaptability -.485 .630 -.483 .632Business model plan .653 .517 .653 .517Network -.205 .838 -.205 .839Business partners .541 .591 .530 .599Staffing .495 .623 .492 .625Financial capital -.272 .787 -.271 .788Market competitors .127 .900 .126 .901Customers 1.549 .128 1.533 .133Incubator advisors 1.260 .214 1.256 .216
220
F.12 Startup age vs. factors - Independent Samples Test
Table 112: Startup age vs. factors in validation - Independent Samples Test (n=48)
Younger startups (n=27) Older startups (n=21)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.774 .443 -.741 .464Commitment .264 .793 .271 .787Learning 1.064 .293 1.066 .292Pivot adaptability 1.225 .227 1.226 .227Business model plan .267 .791 .266 .792Network -.221 .826 -.232 .817Business partners -1.142 .259 -1.148 .257Staffing .251 .803 .248 .805Financial capital .019 .985 .019 .985Market competitors -1.136 .262 -1.147 .257Customers .281 .780 .289 .774Incubator advisors .295 .769 .292 .771
221
Table 113: Startup age vs. factors in efficiency - Independent Samples Test (n=48)
Younger startups (n=27) Older startups (n=21)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -1.632 .109 -1.680 .100Commitment .503 .617 .506 .615Learning 1.418 .163 1.386 .174Pivot adaptability .094 .926 .091 .928Business model plan 1.441 .156 1.438 .158Network .338 .737 .341 .734Business partners -.079 .937 -.078 .939Staffing -.766 .448 -.779 .440Financial capital .064 .950 .067 .947Market competitors .430 .669 .436 .665Customers 1.396 .169 1.407 .166Incubator advisors .428 .671 .416 .680
Table 114: Startup age vs. factors in scale - Independent Samples Test (n=48)
Younger startups (n=27) Older startups (n=21)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -2.077 .043 -2.148 .037Commitment 1.972 .055 1.890 .067Learning .602 .550 .617 .540Pivot adaptability -.361 .719 -.347 .731Business model plan 1.070 .290 1.041 .304Network .020 .984 .020 .984Business partners .326 .746 .312 .757Staffing -.380 .705 -.383 .703Financial capital .589 .559 .575 .568Market competitors .000 1.000 .000 1.000Customers .687 .496 .674 .504Incubator advisors 1.641 .108 1.601 .118
222
F.13 Age vs. factors - Independent Samples Test
Table 115: Age of the entrepreneur vs. factors in validation - Independent Samples Test (n=48)
< 30 (n=24) 30 >= (n=24)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -1.718 .092 -1.718 .092Commitment .419 .677 .419 .678Learning .194 .847 .194 .847Pivot adaptability -.967 .339 -.967 .339Business model plan .265 .792 .265 .792Network -.351 .727 -.351 .727Business partners .401 .690 .401 .690Staffing -.285 .777 -.285 .777Financial capital .454 .652 .454 .652Market competitors -1.633 .109 -1.633 .110Customers -.149 .882 -.149 .882Incubator advisors -1.107 .274 -1.107 .274
223
Table 116: Age of the entrepreneur vs. factors in efficiency - Independent Samples Test (n=48)
< 30 (n=24) 30 >= (n=24)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -1.045 .302 -1.045 .302Commitment -.210 .835 -.210 .835Learning -.562 .577 -.562 .577Pivot adaptability -2.013 .050 -2.013 .050Business model plan -.915 .365 -.915 .365Network -1.210 .233 -1.210 .233Business partners .000 1.000 .000 1.000Staffing .000 1.000 .000 1.000Financial capital -1.925 .060 -1.925 .061Market competitors -.622 .537 -.622 .537Customers -3.347 .002 -3.347 .002Incubator advisors -1.487 .144 -1.487 .144
Table 117: Age of the entrepreneur vs. factors in scale - Independent Samples Test (n=48)
< 30 (n=24) 30 >= (n=24)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -.195 .847 -.195 .847Commitment -1.274 .209 -1.274 .210Learning -.531 .598 -.531 .598Pivot adaptability -2.147 .037 -2.147 .038Business model plan -2.563 .014 -2.563 .014Network .478 .635 .478 .635Business partners -.650 .519 -.650 .519Staffing .232 .818 .232 .818Financial capital -.941 .352 -.941 .352Market competitors -.763 .449 -.763 .449Customers -2.007 .051 -2.007 .051Incubator advisors -.133 .895 -.133 .895
224
F.14 Education vs. factors - Independent Samples Test
Table 118: Education vs. factors in validation - Independent Samples Test (n=48)
< Bachelor (n=19) Master > (n=29)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -1.510 .138 -1.519 .137Commitment .125 .901 .124 .902Learning .339 .736 .351 .728Pivot adaptability -1.187 .242 -1.139 .263Business model plan 1.772 .083 1.804 .079Network -.224 .824 -.223 .825Business partners -.738 .464 -.765 .448Staffing .548 .586 .568 .573Financial capital -.549 .586 -.584 .562Market competitors -.818 .418 -.840 .405Customers .746 .460 .751 .457Incubator advisors .140 .889 .140 .889
225
Table 119: Education vs. factors in efficiency - Independent Samples Test (n=48)
< Bachelor (n=19) Master > (n=29)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience .150 .882 .162 .872Commitment -1.921 .061 -1.796 .083Learning -2.981 .005 -2.937 .006Pivot adaptability -1.188 .241 -1.185 .243Business model plan 1.029 .309 1.048 .301Network -1.198 .237 -1.249 .218Business partners -2.097 .042 -2.252 .029Staffing .312 .757 .299 .767Financial capital -.453 .653 -.470 .640Market competitors -.410 .684 -.405 .688Customers -1.911 .062 -1.932 .060Incubator advisors -.392 .697 -.415 .680
Table 120: Education vs. factors in scale - Independent Samples Test (n=48)
< Bachelor (n=19) Master > (n=29)t Sig. (2-tailed) t Sig. (2-tailed)
Working experience -1.031 .308 -1.045 .302Commitment -2.003 .051 -1.929 .062Learning -1.026 .310 -1.036 .307Pivot adaptability -1.174 .246 -1.250 .218Business model plan -.876 .386 -.878 .385Network -1.592 .118 -1.598 .118Business partners -1.117 .270 -1.058 .298Staffing -.625 .535 -.633 .530Financial capital -.040 .969 -.042 .967Market competitors .518 .607 .544 .589Customers -.561 .578 -.581 .564Incubator advisors -.062 .950 -.062 .951
226