Technology Entrepreneurship : A Treatise on Entrepreneurs and Entrepreneurship for and in Technology Ventures

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Microeconomic theory McGraw -Hill, lnc. P . R. G . Layard & A. A. Walters السنة: 2015 اللغة: english File: PDF, 53.79 MB

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Learn Python in One Day and Learn It Well: Python for Beginners with Hands-on Project. The only book you need to start coding in Python immediately CreateSpace Independent Publishing Platform Jamie Chan السنة: 2015 اللغة: english File: EPUB, 397 KB

Wolfgang Runge
Technology Entrepreneurship
A Treatise on Entrepreneurs and Entrepreneurship for and in Technology Ventures

VOLUME 2

Technology Entrepreneurship
A Treatise on Entrepreneurs and Entrepreneurship
for and in Technology Ventures
VOLUME 2

by
Wolfgang Runge

Many of the designations used by manufacturers and sellers to distinguish their
products are claimed as trademarks. The quotation of those designations in
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Copyright Acknowledgements
Acknowledgements are due to the Zentrum für Europäische Wirtschaftsforschung
GmbH, Mannheim (ZEW) for permissions to reproduce a large number of figures
and tables from its publications.
Permission to use figures from the Global Entrepreneurship Monitor (GEM) 2008
Global Report, which appear here, has been granted by the copyright holders. The
GEM is an international consortium and this report was produced from data collected in, and received from, 43 countries in 2008. Our thanks go to the authors,
national teams, researchers, funding bodies and other contributors who have made
this possible.

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Print on Demand 2014
ISBN 978-3-7315-0107-7 (Set)
DOI: 10.5445/KSP/1000036457
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DOI: 10.5445/KSP/1000036459
ISBN 978-3-7315-0109-1 (Band 2)
DOI: 10.5445/KSP/1000036460

Table of Contents

iii

CONTENTS

PREFACE .....................................................................................................................vii
How to Read and Use this Book ..................................................................................xvi
APPROACH ................................................................................................................ xvii
1. CONTEXTUAL SETTINGS........................................................................................ 3
1.1 Setting the Stage ................................................................................................. 3
1.1.1 Technology Entrepreneurship and New Technology-Based Firms ............. 3
1.1.1.1 Entrepreneurship and Technology Entrepreneurship ............................... 8
1.1.1.2 New Technology-Based Firms and Research-Based Startups............... 15
1.1.2 The Conceptual Skeleton of Entrepreneurship .......................................... 20
1.2 Systems, Change, Innovation and the Future ................................................... 32
1.2.1 General Systems Theory and Systems Thinking....................................... 32
1.2.2 Outlining Relevant Systems for Technology Entrepreneurship ................. 78
1.2.3 Systems, Intelligence, and Learning .......................................................... 94
1.2.4 The Technology Entrepreneur in Capitalistic Systems ............................ 100
1.2.5 Innovation, Technology, Competition and Growth ................................... 109
1.2.5.1 Innovation, Its Adoption and Technology Classes ................................ 109
1.2.5.2 Aspects and Perspectives of Value....................................................... 130
1.2.5.3 Industry, Markets, Growth and Competition.......................................... 137
1.2.6 The Science & Technology System, the Innovation System and New
Technology-Based Firms .................................................................................. 156
1.2.6.1 Differentiating Groups of Technology Entrepreneurs............................ 188
1.2.6.2 Technology Incubation, Science or Technology Parks and Clusters.... 197
1.2.6.3 Technology Transfer to Small and Medium-Sized Enterprises............. 207
1.2.7 The Financial Subsystems in the US and Germany ................................ 210
1.2.7.1 Financial Sources for Technology Entrepreneurship ............................ 210
1.2.7.2 The Components of the Financing Subsystem for Technology
Entrepreneurship ............................................................................................... 223
1.2.7.3 Options for Financing New Technology Ventures................................. 244
2. THE ENTREPRENEUR AND THE ENTREPRENEURIAL TEAM......................... 255
2.1 The Entrepreneurial Personality ...................................................................... 256
2.1.1 Personality and Systems Theory ............................................................. 256
2.1.2 Personality and Behavior ......................................................................... 257
2.1.2.1 Psychometric Approaches to Entrepreneurial Personality and ProblemSolving............................................................................................................... 272
2.1.2.2 Creativity, Imagination and Inspiration for Entrepreneurship ................ 280
2.1.2.3 The Culture Factor ................................................................................ 283

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2.1.2.4 Education, Age and Work Experience of Technology Entrepreneurs ...297
2.1.2.5 Foundation Motivations – Technology Entrepreneurs and Entrepreneurial
Teams as Systems ............................................................................................311
2.1.2.6 The Gender Factor for NTBFs...............................................................347
2.1.2.7 Visions, Missions and Values ................................................................352
2.1.2.8 Ethics in Technology Entrepreneurship.................................................356
2.1.2.9 Conceptual Particulars of Applied General Systems Theory for
Observation, Measurement and Practice ..........................................................374
2.2 The Corporate Entrepreneur – the Intrapreneur..............................................382
2.2.1 Corporate Culture, Shaping Elements and Processes for Intrapreneurship
...........................................................................................................................388
2.2.2 Large Firms’ Problems with Disruptive Innovation ...................................398
2.2.3 Bootlegging in Large Firms ......................................................................403
3. IDEAS, IDEATION AND OPPORTUNITIES ..........................................................407
3.1 Business Ideas and Problem-Solving ..............................................................408
3.2 The Idea and the Opportunity ..........................................................................427
3.2.1 Hierarchies for Segmenting Macro-Trends for Revealing Opportunity ....454
3.2.2 Opportunity Evaluation and Feasibility .....................................................478
3.3 Ideation ............................................................................................................488
3.3.1 More on Principles of Ideation: Technological Paths, Combinations and
Transfer .............................................................................................................495
3.3.2 The Fuzzy Front-End of Ideas ..................................................................513
3.4 Specifics for Software Firms and Technology-Based Services .......................515
3.4.1 Entrepreneurship in Video and Computer Games ...................................531
3.4.1.1 Gameforge AG and Zynga, Inc. ............................................................542
3.4.2 Special Entrepreneurship in Professional Social Networks .....................551
3.4.2.1 Xing AG and LinkedIn Corp...................................................................551
4. ENTREPRENEURIAL SUCCESS AND VENTURE GROWTH .............................557
4.1 Perspectives of Success of Entrepreneurship.................................................559
4.1.1 Hidden Champions – a German Business Success Configuration..........575
4.2 Entrepreneurial Risk-Taking and Decision-Making ........................................583
4.2.1 Risk Taking...............................................................................................590
4.2.1.1 Risk-Taking by Customers and Suppliers .............................................602
4.2.2 Decision-Making .......................................................................................603
4.2.3 The System of Failures and the Pitfalls for the Start-Up and Early Growth
Phase.................................................................................................................617
4.3 Approaches to New Technology Venture Growth ..........................................635
4.3.1 Life-Cycle Models and Stage-Based Views .............................................641
4.3.2 The Initial Architecture and Initial Configuration.......................................659
4.3.3 Resource-Based Views ............................................................................684
4.3.3.1 Bootstrapping a Technology Startup .....................................................690
4.3.4 Cybernetic Principles and Concepts for Technology Entrepreneurship...695
4.3.5 A Bracket Model of New Technology Venture Development ...................708
4.3.5.1 The Bracket Model ................................................................................718
4.3.5.2 The Bracket Model for Framing Empirical Observations and Explaining
NTBF Development ...........................................................................................735
4.3.5.3 Selected Quantitative Applications of the Bracket Model.....................770
4.3.6 Expectations of Growth of Technology Ventures .....................................783

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v

5. PATHS OF TECHNOLOGY ENTREPRENEURSHIP ........................................... 819
5.1 Firm’s Foundation as Systems Design ............................................................ 822
5.2 The Startups’ Evolvements for Growth............................................................ 831
5.3 Some Concluding Remarks............................................................................. 845
REFERENCES........................................................................................................... 847
NOTES....................................................................................................................... 924
APPENDIX A.............................................................................................................. 935
A.1 Entrepreneur, Company and Market Cases ................................................... 935
A.1.1 The Biofuels Bubble and the Related Outburst of Entrepreneurship and
Intrapreneurship ................................................................................................ 935
A.1.1.1 The Origins and the Drivers .................................................................. 936
A.1.1.2 The Technologies and Products’ Situation ........................................... 943
A.1.1.3 Intrapreneurship and Entrepreneurship in Biofuels: The Biomass-toBiofuels Boom ................................................................................................... 951
A.1.1.4 The Special Algae-to-Biofuels Boom .................................................. 1002
A.1.1.5 Structuring Entrepreneurship in Biofuels ............................................ 1051
A.1.1.6 The Shift from Biofuels and Co-Products to Biobased Chemicals as the
Primary Target of Entrepreneurship ................................................................ 1112
A.1.2 William Henry Perkin and Industry Genesis in the Last Third of the
Nineteenth Century ......................................................................................... 1133
A.1.3 Structures and Issues of Current University-Industry Relationships ..... 1138
A.1.4 Foundation and Development of SAP AG in Germany ......................... 1146
A.1.5 Entrepreneurship Cases Referring to Ionic Liquids ............................... 1150
A.1.6 Formalization of Structures of Founder Teams and Architectures of New
Firms................................................................................................................ 1171
A.1.7 Special Networking Effects for Entrepreneurship: The “PayPal Mafia” . 1182
APPENDIX B............................................................................................................ 1191
B.1 Background Information on the NTBF Selections........................................ 1191
B.2 List of NTBFs and Other Companies Surveyed by the Author ..................... 1193
B.3 Publicly Available Case Documents of Companies ...................................... 1199
Glossary ................................................................................................................... 1200
Acronyms ................................................................................................................. 1218
INDEX ...................................................................................................................... 1225
Company Index.................................................................................................... 1225
Subject Index ....................................................................................................... 1236

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4.3 Approaches to New Technology
Venture Growth
Venture growth is currently an issue of strategic management or entrepreneurship –
and of particular interest to policy. For the field of strategy the emphasis was and is on
existing firms and business growth, but this makes insights to be transferred to firm’s
foundation and early growth of new (technology) ventures problematic.
Understanding the origins of new venture growth and why and how startups grow and
become successful or even very successful firms (“promising startups”) is still one of
the least understood aspects of entrepreneurship research.
It is our conviction, in line with Bhidé [2000:11],
“We cannot expect to derive a fool-proof formula or a ‘complete’ description
for starting a profitable business.”
Furthermore, entrepreneurs or the leadership team of young technology-based ventures are being presented with a much larger “menu” or array of choices for decisionmaking (opportunities, financing, etc.), at many points in time, than established firms.
From a choice-taking perspective the critical questions become the following: a) Are
there identifiable patterns of growth, technology, and financial choices for a particular
industry or even industry segment? b) What factors shape or determine which choices
are taken? c) Are these patterns related to venture productivity and performance
(Equation I.2)?
Furthermore, are the above questions to be differentiated for the various types of
NTBF – RBSUs, academic NTBFs, EBSUs (ch. 1.2.6.1)? Do they differ with regard to
initial (startup) financing, such as financing by bootstrapping, mixed private/loan
financing, financing by private investors or venture capital investors? What is the role
of the different types of markets for NTBFs (ch. 1.2.5.3; “economic markets” “policydriven markets”, etc. – Table I.15)?
Under which circumstances do we have a transition of a growing young firm from
“strategy logics” to formal “strategy-making”? How is the evolvement of strategy bound
to the change of entrepreneurial leadership to management, if at all?
Following Drucker’s third pitfall (4.2.3) one can say: Growth creates problems!
There is evidence that the young firms’ growth dynamics, as a teleological process
targeted at a given vision, mission and goal, may not be governed by a random
process and this has stimulated scholars to investigate factors and put forward a large
number of growth models.
Each of these theories focus on explaining different aspects. There is no commonly
agreed framework or theory for growth of startups. The frameworks are not mutually
compatible or consistent. They do not agree on which (endogenous and/or exoge-

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nous) variables are the essential drivers of startup growth. Bhidé [2000:210] suggested, for instance, that “the transition to a large enterprise requires greater heterogeneity of assets and functions and investment in administrative infrastructure.”
Most of the literature on the theory of the firm assumes a firm to be already in operation, but “mainstream economics has little to tell us about how and why some firms
survive and grow and others do not.” [Bhidé 2000:242]
What is needed is a conceptually grounded explanatory model allowing making sense
of the extremely broad spectrum of findings in the technology entrepreneurship area.
Such an approach to tackle the developmental processes found among new technology firms as they generate and increase revenues and build their employees’ base
can only be fully illuminated by micro-data from case histories.
In this line it is important to find out how the overall GST framework for technology entrepreneurship as the conceptual basis of this book can make use of gross aspects of
common venture growth models and add insights on the structural and processual
levels – and raise further research questions.
Teleological, future-oriented GST models would imply that it is the purpose or final
goal of the founder(s) and their views of “success” that guides the development process of a new firm. Hence, the developing entity is purposeful and adaptive to internal
and external forces and events, and the process can be seen as a repetitive sequence
of goal formulation, implementation, execution, evaluation and modification of intermediate goals or milestones or even distinct changes of goals (purposeful enactment).
For our context, the explicit consideration of economic recession for firms’ growth will
illustrate important broader conceptual implications for reasoning and exemplify the
general paths followed to generate statements like hypotheses, proposals, propositions or explanations.
Figure I.2 and surrounding text has outlined that for statements with conditionals there
is a need for care in making clear whether “reason why” or “reason for thinking that”
relations illustrated in terms of antecedents and consequents are being stated. For instance, “prediction” in chemistry refers often to properties and reactivities of molecular
classes and exceptions (“single events,” “single data points”) explained a posteriori by
a particular condition.
In a related way, our growth models targeting expectations are often statements of
that kind, for instance: the particular startup configuration let expect strong growth (>
25 percent) over the next 4-5 years unless an economic recession prevents that. Or,
the startup can be expected to show good growth (around 10 percent) provided the oil
price will not fall significantly below $80 per barrel.
Discussing NTBF growth we shall focus essentially on the time periods surrounding
firm birth (Figure I.122) and its first eight to ten years of existence. The entrepreneurs’

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reasons and motivations to found a firm (ch. 2.1.2.5) and the ideas and opportunities
they pursue (ch. 3) have been discussed in previous sub-chapters.
However, growth of a new firm is not only a matter of the drive for achieving the goal,
but also of the pace of development (Figure I.122) and attitudes toward resources.
“But founders, not outside investors, should determine the proper pace of growth for a
company. And a founder who is about to lose his or her life savings is far more likely
to drive a company towards profitability.” “Landing equity money early on quickly leads
to bad habits” and “bringing in outside money usually creates expectations of very rapid growth.” In the end, creating a culture that emphasizes long-term profitability over
rapid growth is critical for success.” [Wadhwa 2009]
The author encountered the description of the above situation several times with
founders as guest lecturers for his Technology Entrepreneurship curriculum (Box
I.20). All the cited firms were LLCs and for the first ten years of existence under full
control of the founder-owners who had invested much of their private money.
Box I.20: How founders of NTBF with preferences for financial sources determine the pace of their firms’ developments.
As Wadhwa [2009] says “Hungry companies figure out ways to keep eating because
they don’t know whether there will ever be another meal.”
We hear the same from WITec GmbH (B.2). WITec was funded with private money,
which is not necessarily a bad thing, one of the founders (Klaus Weishaupt) said,
because it creates pressure to make profits as soon as possible. “If the fridge is
empty, the pressure is greater to make money than when you have millions from an
investor to spend,” he said, adding that he does not want the company to get listed on
the stock exchange anytime soon. “We don’t want to sell. It’s better when the profits
go into your own pocket.”
Corresponding statements are heard from one of the founders of Nano-X GmbH (B.2),
Reimund Krechan. “Permanently, I have been addressed by venture capital firms, but
so far I have rejected their offers,” Krechan said. “Money makes only lazy” (in German
“Das Geld macht nur bequem”).
“In hindsight, this scarce funding had also a positive impact as we had to focus on the
essentials,” said Niels Fertig (founder of German Nanion Technologies GmbH), “we
have learned how important it is to orient ourselves toward the market and not toward
the investors.”
(“Im Nachhinein hatte diese äußerst knappe Finanzierung auch positive Folgen, weil
wir uns auf das Wesentliche fokussieren mussten,” erläutert Fertig. „Dabei haben wir
gelernt, wie wichtig es ist, sich am Markt zu orientieren und nicht an den Investoren.”)
And ChemCon GmbH (B.2) follows a strict strategy that growth (in terms of employees
and office/laboratory space) follows cash/profit development; positive growth allowed
expansion. (in German: Das sehr positive Wachstum erlaubte eine Erweiterung des

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Teams um 10 Mitarbeiter bis zum Ende des Jahres). ChemCon’s principle from the
beginning: continue to invest only if a new order was caught (“…weil immer erst dann
investiert wurde, wenn auch ein neuer Auftrag vorlag.)
A graphical reflection of this attitude is also seen for German Nano-X GmbH (B.2)
after having bought a building in 2001. After having caught a big order for its products,
Nano-X additionally bought the adjacent area for a new production hall and office. At
first Nano-X increased the number of employees to then later execute the request
(Figure I.137).
Looking at growth of young firms is associated with perspective (Table I.64). For
instance, the policy perspective (and expectation) is related to job creation (and
growth). We shall take primarily a perspective of the firm and its founder(s) (and
probably stakeholders).

Indicators of Growth
Development of a new firm can be tackled along several dimensions which characterize “input,” internal structures, events and processes in a (new) firm or relate to performance and output, for instance, growth in terms of revenues or number of employees over time or interrelate both of these aspects (productivity, Figure I.130).
Garnsey et al. [2006] have critically discussed the various indicators that can be used
for observing and measuring growth according to relation to input, value and output.
The most common ones are absolute figures of revenues and numbers of employees
(ch. 4.1). Each is subjected to limitations. Employment figures are the most commonly
used measure because they seem to offer standardized, comparable data on the rate
and direction in which a firm has been expanding. But, developments of revenues
(disregarding inflation effects over time) and numbers of employees are not necessarily correlated.
Absolute figures of revenues and numbers of employees, particularly with regard to
NTBFs, may have special issues. To a certain degree it has become common practice
of NTBFs to incorporate money (funds or grants) from public sources for R&D into reported revenues. But, reliance on public grants or funds must be viewed as timedelimited projects. If this money is used for temporarily hiring personnel and without
knowing about this may easily lead to misinterpretations of an effect of the decrease in
the number of employees.
Depending on the situation the following discussions of NTBF developments will usually focus on “absolute years” for a time period or a sequence of individual years (for
instance, 1997-2006 or 2003, 2004, 2006, 2008) rather than years of existence. Furthermore, we shall usually consider

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Absolute figures of revenues and numbers of employees and
Productivity (revenues per employee),
For production-oriented firms also output-oriented indicators, such as pieces
of items (devices, instruments) sold or produced, volume of material (pounds
or kg, barrels or liters) or overall performance of items sold, such as producible power (cf. Figure I.150, Figure I.154).
Getting data on revenues and numbers of employees is rather difficult, particularly for
privately held firms. Except for public firms which are required to publish such data by
law and according to standard accounting rules one has to rely on data collected by
special for-profit firms, data reported to and published by the media or published by
firm founders (in interviews).
Hence, one is plagued with issues of missing data for timelines and reliability and
quality of the data. And even official data, for instance, in annual reports sometimes
vary – and it is well known that such data for a year to year may be distorted in the
framework of accounting rules to fit corporate policy.
Concerning growth rates we shall sometimes refer to the “Compound Annual Growth
Rate.” Compound Annual Growth Rate (CAGR) is a widely used mathematical formula that provides a “smoothed” growth rate. CAGR is often used to describe the
growth over a period of time of some element of the business, for example revenues.
The compound annual growth rate is calculated by taking the nth root of the total percentage growth rate, where n is the number of years in the period being considered
(Equation I.10).
Equation I.10:

V(t0) : start value, V(tn) : finish value, tn − t0 : number of years
In any case, specifically for a GST approach, understanding a new firm’s development
requires taking firm-internal and external factors into account. Following the axiom that
at any point in time, metrics of firm size change will show the firm undergoing growth,
stability or decline and transition points between these expressions of development
will indicate change of the firm from one state to another one, one may encounter
problems of interpretation over a time period if economic recession is not taken into
account. Its effect may show up in one or the other indicator or, worst, it may show up

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as growth in one (in revenues), but decline in the other (employees) as is observed,
for instance, for Novaled (Figure I.148).
Growth discussions are especially critical if a sample of firms is considered using
growth indicators based on “year of existence” (year = 1, 2, 3, …) of NTBFs. Any
observation and related comparisons referring to “year of existence” may cut off any
external effect with a relevant impact for growth a startup may be subjected to and
compares or group together “apples and pears” and other fruit.
Referring again to recession this could mean to group together startups with lacking
necessary (external) financing during foundation, startups in their third year and
almost no chance to catch customers due to the recessions and struggle for survival
and “stable” NTBFs in their sixth year which just encounter a manageable reduction of
revenue due to reduced orders of customer with conviction to overcome the recession
and will be back to growth.
Generally, recessions may lead to difficulties in interpreting just growth curves (revenues or employees) which show setbacks (back to growth, plateauing; Figure I.107) in
terms of firm internal problems or recessions or both. Additionally, revealing firms with
delayed growth require careful examination of whether this is a reflection of slow firm
growth in the early development phase or whether the situation reflects structurally
effects of the firm, a characteristic of good or high growth hindered by recession and a
rather long time for catching up to structurally appropriate characteristics – or just a
favorable event that leads from a state with a medium or low growth to an “explosion
of growth.”
In addition to recession, there is a further environmental factor for (technology) entrepreneurship one must be aware of, the situation of industry genesis which may show
up in waves of segments, such as the chemical industry and particularly the synthetic
dye industry or automotive industry [Runge 2006:266-269, 274-275]. Currently such
waves occur in the I&CT industry and here particularly the hard- and software industry
and the “Internet industry” – and also in CleanTech with the biofuels segment (A.1.1)
Entrepreneurship in a segment of industry genesis usually has a special constellation
concerning attracting entrepreneurs and financial backers as well as the government.
This may induce a “push” for founding and funding affecting the early state of new
firms compared to startups in other industry segments.
Finally, to understand growth of new technology venture it is important to be aware of
factors and their interrelations (Figure I.114, Figure I.115) which led to decline and ultimately closure of the firm.
To proceed selected aspects of common growth models and their key fundamentals
shall be discussed to reveal how to integrate them or, at least, put them into the context of an embracing GST framework.

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4.3.1 Life-Cycle Models and Stage-Based Views
Life-cycle models [Bhidé 2000:244-259; Dorf and Byers 2007:459-465] similar to
those of technologies and industries (Figure I.32) reflect stage-based views and suggest that organizations evolve in a consistent and “predictable” manner.
One widely-cited conceptual life-cycle work was published by Larry Greiner in 1972
and 1998. His emphasis is on five continuous phases of growth (“stages of evolution”)
interrupted by “stages of revolution.” A growth phase (evolution) is characterized by a
particular style of management (Figure I.118). Each “revolution” is specified by a management crisis and the solutions that lead to the next phase of growth. The same organizational practices are not maintained throughout a long life span (Table I.68).
The model’s phases cover explicitly the development of firms till maturity. However, in
the context of entrepreneurship the main emphasis will be only on foundation, early
and later growth phases which are the “S-part” of a development curve (Figure I.32).
Greiner tackles key issues that are relevant for entrepreneurship as effects and
organizational processes.
Table I.68: Larry Greiner’s Five Phases of Business Growth [Greiner 1998].
Size: From Small to Large ↓

Life-Cycle (Age): From Start Up to Maturity

Revolution: stages of crisis

Growth through

Crisis of

Practices become outdated.

Creativity

Leadership

Companies that do not change
will fold or cease to grow.

Direction

Autonomy

Delegation

Control

Coordination

Red Tape

Often solutions for one crisis
become a major problem in the
next crisis.

Collaboration

Generally, a stage-based view may be viewed as a “stimulus-response” mechanism.
Stage-based models presume that development is achieved by firm-internal change
initiated by controllable or even uncontrollable events or processes or intentionally
initiated change by entrepreneurs/managers or responding to external effects (cf. US
Osmonics [Runge 2006:91]; German Zweibrüder Optoelectronics (B.2); Google
(Figure I.160, Figure I.163; Box I.24).
An internal “event” could be the detection that the productivity of employees has decreased or grasping an opportunity and pushing a firm into a new direction. Fundamentally, in staged-based models new firm growth will be described in terms of some
prototypical triggers affecting a stage and responses to initiate a new stage.
Mostly related to entrepreneurs starting in niche businesses who initially do not face
obvious growth opportunities an emphasis can be that by intention – and dissatisfac-

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tion with the status quo – entrepreneurs decide consciously to go for larger opportunities or change development direction and invest in broadening the offering line or become active in another area of the value system [Bhidé 2000:252].
Drucker’s pitfall number three – outgrow your production (deliverables) capabilities,
management capabilities (Figure I.118) – seems to provide a good rule of thumb for
entrepreneurship for growing private firms and associated effects on the organization
of the startup. Furthermore, its empirically founded occurrence after four to five years
shows up when the early period of risk of failure of the startup has passed the
maximum and decreases (ch. 4.2).
But the new firm enters a first growth crisis. We look at the period of the new firm’s ca.
four years of existence simultaneously as the “startup thrust phase” for “lift-off” (ch.
4.3.2, Figure I.125) into potential growth of the startup. This shifts the focus to special
organizational life-cycle (OLC) models for NTBFs.
The “startup thrust phase” coincides temporarily largely with a definition of “earlystage entrepreneurship activities” (Figure I.15) that covers a time span which begins
with the initial communication of startup intentions, continues with the transition into
active business as defined by the actual start of business activities (first sales
revenues), and includes the ensuing survival or failure of the new venture. Thus the
period covers the subject of nascent entrepreneurship as well as that of new venture
survival/failure matching recent work [Keßler et al. 2010].
The paper of Keßler et al. [2010] based on a model (not specifically for NTBFs) consisting of the person, resource/environment and founding process forwards the basic
assumption that characteristics of nascent entrepreneurship have significant explanatory power for founding success and new venture survival.
Growth of a firm is associated with development of organization. Organization refers
to structure (order of components/parts) and function (order of processes/activities)
and coordination for the pursuit of a goal.
Organization in firms is seen essentially as being determined by lines of communication and influence, authority or power as well as data and information flows through
these lines of communication. Lines of influence/authority/power to structural components of the entity will be superimposed by coordination among the structural and
functional components.
Corporate culture is usually seen as the basement of communication and coordination. Treating organizational development is often reduced to a special “one-dimensional” aspect in terms of the organizational structure and management complexity.
Malone [1988] defines coordination operationally “as the additional information processing performed when multiple, connected actors pursue goals that a single actor
pursuing the same goals would not perform.” (Emphases added) Coordination means
extra organizing activities related to achieving a goal.

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Boiled down to entrepreneurship and micro- or small firms this definition of coordination implies the following components: 1) a set of (two or more) actors, 2) who perform
tasks, 3) in order to achieve goals.
The common problems that have to do with coordination are [Malone 1988]:
How can overall goals be subdivided into tasks?
How can tasks be assigned to groups or to individual actors?
How can resources be allocated among different actors?
How can information be shared among different actors to help achieve the
overall goals?
How can the different knowledge, education and professionalism and professional (special) languages be overcome and conflicting preferences of different actors be combined to arrive at overall goals?
How can we track and measure the level of overall goal achievement referring
to a system of activities and sub-processes? (added by the author)
These problems have been tackled partly in the discussion of the single entrepreneur
(A.1.2) versus team constellations (ch. 2.1.2.5) and specifically entrepreneurial teams
(Table I.41; Figure I.72, Figure I.73), but shall get more attention for entrepreneurship.
A paper by Hanks et al. [1993] presents an effort toward an empirical taxonomy of lifecycle organization-related stages in young high-technology organizations. In GST
language, however, one would speak about navigation through a series of (system)
“states” rather than “stages” each of which can be induced by a significant change or
development challenge.
Two aspects of particular importance for organizational change (the internal dynamics
of growth) are “specialization” and “centralization.” Organizational specialization
means how many functional areas exist in the firm so that at least one full-time employee fills the function. It should be noted, however, that specialization may be
present already by functional roles at the start and in the very early phase of a young
firm (Table I.41, Figure I.72). It may appear as a path from personal operational competencies to corporate functions (and establishing the value chain).
Formalization has been introduced as a further division of functional areas according
to particular activities and professionalization, such as finances as financing versus
controlling versus accounting.
Organizational centralization was measured by Hanks et al. [1993] referring to a list of
five decision issues and finding out the level of management that must approve the
decision (authority/power) before legitimate actions may be taken.
Cluster analysis has been used by Hanks et al. [1993] to derive empirically a taxonomy of growth stage/state architectures (originally called configurations) in a 1988
sample of high-technology organizations (R&D intensity on average 3.1 percent)

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reflecting a situation in 1987/1986. The derived architectures were interpreted as a
sequence of four growth stages.
The notion architecture in the context of a firm may represent various expressions of
79
organizational structures (Table I.69) . It was proposed in this study that life-cycle
stages could be defined and operationalized as unique architectures of organization
context and strategy.
However, one has to note that in the sample firms which are seven years in existence
could be affected by two recessions and those of sixteen years even three recessions
in the US (Nov 1973–Mar 1975; Jan–July 1980; July 1981–Nov 1982), if sales and
growth rates are considered. Suffering from a severe recession may require up to two
years to catch up to the growth level before the recession.
Our interpretation of State I in Table I.69 is that it represents early growth until the
“management crunch” after four to five years of existence (Figure I.118) reaching 6-7
employees with organizational settings probably close to the startup architecture. The
NTBF is still a “micro enterprise” (Table I.4). State II has emerged after having
crossed the “management crunch” and having adopted a functional basis of the organization and further differentiation toward less centralization but more formalization
(a small enterprise; Table I.4).
State III having an average age of seven years similar to State II seems to represent a
quite rapidly growing firm in terms of number of employees and sales with an operationally functioning manufacturing orientation and related necessary functional specialization, such as customer/product service, production planning and scheduling and
quality control.
State II and State III show comparable original productivity which is on average
$59,200 sales per employee for State II and $59,000/employee for State III. And the
proportion of number of employees per special functions is 7.0 (State II) versus 6.2
(State III). However, the clusters differ markedly by level of centralization.
Hanks et al. [1993] view their State III as a fast expansion stage of development and
this may tentatively assumed to be associated with a transition from the stage of
Direction in State II to Delegation in III in the sense of Greiner (Table I.68).
The increase of number of employees above “25” would reflect a change of the firm’s
organization in terms of communication including reporting lines and coordination
following the “10 - 25 - 150” rule of thumb (Table I.72).

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Table I.69: Growth states and related organizational features for young technologybased firms [Hanks et al. 1993].
State I – Average growth in sales
Relatively young, small, highly centralized and informal firm, focusing on the development
and early commercialization of their technology-based product(s)
Age
(Years)

Average
Sales ($)

Number of
Employees

Employee
Growth

Special
Functions

4+x

271,000
1)
(404,000)

6.46

29%

1.5
(mainly R&D)

Organization
Structure

Organization
Level

Centralization

Formalization

Simple

Little (2.2)

High

Quite informal

State II – Average to low growth in sales
Appears to represent an expansion state of development; in addition to research and development, specialized functions present in at least 50 percent of firms; include sales and accounting, indicating that these firms are actively involved in the commercialization
Age
(Years)

Average
Sales ($)

Number of
Employees

7.36

1.4 million
1)
(2.0 million)

23.64

Organization
Structure

Organization
Level

Adopted
generally a
functional
basis of
organization

Compared to
State I firms
an additional
organization
level (3.18)

Employee
Growth
94%

2)

Centralization
Still very centralized, but less so
than in State I

Special
Function
3.4
Formalization
Little more
formal than in
State I

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Table I.69, continued.
State III – Good-growth in sales
Firms are still growing quite rapidly. In addition to research and development specialized
functions are present in at least 50 percent of the firms and include sales and accounting;
include functionally also shipping and receiving, finance, purchasing, customer and product
service, production planning and scheduling, quality control and payroll. This appears to indicate expansion and increased professionalization, particularly in the manufacturing arm.
Age
(Years)

Average
Sales ($)

Number of
Employees

Employee
Growth

Specialized
Function

6.6

3.7 million
1)
(5.5 million)

62.76

28%

10.17

Organization
Structure

Organization
Level

Centralization

Formalization

Average four
levels of management

Have the lowest
centralization
mean of all the
clusters

Employ a
functional
organization
structure

The second
highest level of
formalization

State IV
Specialized functions present in this architecture, over and above those present in the other
states; include personnel, building maintenance, advertising, market research and inventory
control.
Presence of these specialists may suggest greater formalization of human resource programs
and policies, cost control, and market expansion; a divisional structure has emerged in several firms.
They have overcome obstacles, such as a recession, and via healthy growth have achieved
the status of a medium-sized firm. They have achieved the characteristics of Drucker’s forth
pitfall (ca. $60 million with 300-500 employees after 8–14 years of existence (ch. 4.2.3; Table
I.67; Figure I.143, Figure I.144).
Age
(Years)

Average
Sales ($)

Number of
Employees

16.2

46 millions
1)
(69 million)

495

Organization
Structure

Organization
Level

Employee
Growth
57%

2)

Specialized
Function
15.3

Centralization

Formalization

Centralization is
low

Formalization is
the highest of all
the clusters

1) To make monetary values from 1986/1987 comparable with those observed for 2006/2007
we assumed an average inflation rate of 2 percent, which is multiplying the original figures by
1.49. 2) Not clear; due to the way of measuring growth, our emphasis will be more on absolute
employee numbers.

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State IV is characterized by a productivity (sales per employee) of $93,000. Hanks et
al. [1993] put forward several limitations which hinders clear interpretation of State IV.
But it may be tentatively associated with a further development of the high growth
State III. The nearest comparable example to the situation of State IV could be the
German SAP AG which after fifteen year of growth in 1987 had 468 employees and
sales of €77.7 million (Table I.67).
Other clusters revealed by Hanks et al. [1993] are notable characterizing essentially
non-growth firms:
While similar in size to Clusters A (State I) and B (State II), respectively, they
are significantly older than their counterparts. Companies average 18.7 years
of age, yet employ a mean of only seven employees. Employee growth is
non-existent, actually declining slightly. These firms have virtually no specialization, less than two organization levels (1.71) and employ a simple organization structure. Centralization is the highest of all the cluster groups and formalization is lowest. These are old small firms. They are presently not growing,
and appear to have their product(s) fairly well developed.
This is in line with the discussion of “non-growth” NTBFs (ch. 4, Table I.63). For these
firms entrepreneurs or owners, respectively, have consciously chosen to keep their
firms small with a size of five to nine employees. The phenotype growth pattern corresponds to that of the “Growth Setback – Plateauing” phenotype or “Continuous
Growth – Asymptotic” (Figure I.107).
Specialization in terms of developing functions of startups may appear by more or less
fast hiring of appropriately targeted personnel of an otherwise unsystematic hiring
process during the startup’s development so far.
For instance, Cisco System’s founders relied on improvised staffing for its first four
years, but obviously ran into a “management crunch” (Figure I.118). John Morgridge
“built the management structure” after he was recruited as President and CEO of
Cisco in 1988 (Figure I.145, Figure I.158). He concentrated on hiring of “professional
and experienced people in all the main functional areas – a Chief Financial Officer, a
Vice President of Engineering, a Vice President of Manufacturing, and a marketing
person” and recruited a professional sales staff. [Bhidé 2000:285].
Organizational development of NTBFs concerning specialization may follow a path
from personal competencies and roles and activities of founders’ functions outlined in
Figure I.72 and Table I.41.
An illustrative development of internal and external organizational structures through
specialization, leadership structure and networking during ca. nine years is given for
the German NTBF IoLiTec GmbH (A.1.5; B.2). Furthermore, by the end of 2011
IoLiTec achieved a status concerning the level of progression from R&D via piloting to

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commercialization of offerings. One can also see how IoLiTec’s technology strategy is
implemented in the firm’s state reflecting executing the strategy.
Disregarding the environment, for instance, that business growth is determined by
technology and market environment of its industry, as a summary of internal effects
for the firms’ early growth one finds:
Problems tend to change with increased number of employees and sales
revenue.
New functions emerge (specialization).
Structural hierarchy increases.
Formalized processes are established – for control (formalization).
Jobs become more interrelated.
Coordination and communication become more difficult.
Organizations that do not grow can maintain the same structure for longer
periods of time.
Prior to change being possible the owner-managers need to develop skills
and competencies in leadership, coaching and management before effective
delegation and team building could take place.
A growing firm needs “feeding” (ch. 5.2); it must draw in new resources to support
growth, but it may face coordination and delivery problems and planning delays as it is
very difficult to synchronize resources to requirements in a dynamic system.The need
for internal coordination and resource allocation sets a brake on the rate at which
business opportunities can be pursued.
Start-up and early growth of NTBFs encounter several organizational challenges for
growth. Parallel to increasing the number of hierarchies (organizational levels) relevant changes include
The way of communication and the flow of information,
Individual working processes and their coordination,
The scope of tasks for employees,
Employee development (Figure I.121),
The felt extent of responsibility of the individual employee for the firm (commitment).
However, revisiting development of specialization in new firms requires lifting the assumption that the new firm builds functions or functional activities only internally to get
results of particular activities. In contrast to the notion “outsourcing” meaning transfer
of existing activities or whole functions of a firm to external service providers we look
into “outcontracting.” This will be understood here as an NTBF buying in “contract
services” for functional activities or a “whole function” that are needed for the business, but do not exist so far in the NTBF and will not be established in due course.
Concerning the necessary activities of the startup a decision must be made between

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“do-it-yourself” or “let others do it.” “Outcontracting functional activities” means additional and other kinds of coordination efforts.
Gottschalk et al. [2007] found that ca. 87 percent of young firm of research-intense
industry sectors “outcontract” functional activities in Germany. They found the following levels of totally or partially utilizing contract services:
Accounting (74 percent)
Payroll (57 percent)
IT Infrastructure (26 percent)
Production (24 percent)
PR/Marketing (18 percent)
R&D (15 percent )
Distribution/Sales (12 percent).
The vast majority of these contract services are done by domestic firms. The highest
costs for outcontracting have been observed for outside manufacturing.
Young German firms have various reasons for outcontracting functional activities
[Gottschalk et al. 2007]. Only 47 percent of the firms put forward cost as an argument.
The major line of arguments followed a longer term strategic decision to outcontract
functional activities to concentrate on core competencies and activities.
The insufficient endowment with personnel, technology and laboratory or pilot plant facilities, but also lack of experience in the context of application-oriented R&D projects
imply that necessary scientific resources and research services, such as chemical or
technical testing or engineering activities, must be purchased from external firms or
research institutes to push the own R&D projects or to produce own products.
For young high-tech firms it is important to gain or complement, respectively, the lacking or insufficient technical and administrative infrastructure by external providers.
Reasons for outcontracting are as follows [Gottschalk et al. 2007].
Data security (16 percent)
Reduce risk (28 percent)
Lack of special personnel (33 percent)
Lack of personnel (44 percent)
Reduce cost (47 percent)
Get better quality (55 percent)
Gain flexibility (61 percent)
Access to technology and know-how (65 percent)
Focus on core competencies (97 percent).
A particular interesting case of outcontracting is the German firm Xing AG (ch. 3.4.2;
B.2). For starting his Internet company the founder who perceived the opportunity implemented his business idea essentially by outcontracting a very large proportion of
needed functionality from the beginning, in particular, software development.

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Effects similar to directions of outcontracting in the US have been observed by
Ardichvili et al. [1998] who looked into timing and sequence of startup teams’ delegation of business functions in growing entrepreneurial ventures.
In 1986/87 their related study surveyed startups founded in the period 1979-84; and
they repeated the survey in 1992/93. They found that there was no difference in the
patterns of delegation of functions between manufacturing and service firms. Irrespective of the sales level and timing top level delegated functions included Accounting,
Warehousing and Shipping, Production, Computer Systems, Purchasing and Personnel.
Currently, for NTBFs with larger production facilities also “Quality Management” has
become a very important formalization (cf. IoLiTec (A.1.5, B.2), Nano-X GmbH (Figure
I.137; B.2), Novaled AG (Figure I.148; B.2), Heppe Medical Chitosan GmbH (B.2)).
For NTBFs, also other kinds of specialization show up rather early – according to applications (IoLiTec (A.1.5, B.2), products or product groups and business lines (for
instance (all described in B.2), WITec GmbH, Novaled AG; Zynga, Inc. (online games
as products; ch. 3.4.1.1).
Finally some facts with regard to resources and organizational development of startups and NTBFs are to be noted.
Startups, particularly RBSUs, often need internal and also a distinct external
organization in terms of networking and cooperation with universities and
public research institutes (as exemplified by the IoLiTec GmbH case (B.2)).
VC-based startups and NTBFs usually get organizational structures of medium to large firms imposed by the investors which may occur rather early
(Novaled AG (Figure I.148), biofuels NTBFs – A.1.1);
NTBFs with management and organizational structures closely related to
those of large firms are characterized by Bhidé [2000:4, 21] as “transitional
firms” to indicate their way to become large firms.
Founders with industry experience in (very) large firms tend to set up early an
organizational structure for the NTBFs that mirrors business and organizational processes they encountered with their previous employer (ATMgroup
AG, Polymaterials AG; B.2).
To inquire further into the details of NTBF growth complementing the sales and number of employees figures from Table I.69 one can refer to the study of Gottschalk et al.
[2007] which provides averages of related indicators for German NTBFs (Table I.70).
The data differentiate the high-tech area according to Table I.1, but do not differentiate
initial funding and ownership (Table I.74). The data cover the 2001 dot-com recession.
According to the study, only ca. 7 percent of the high-tech firms in Germany did not
achieve any revenues in the first year after foundation. In the first year of business all
firms of the sample had average revenue of €190,000 which increased to €840,000

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after ca. six years in 2006. The extents of growth of revenues and employees depend
on the industry segment of the NTBF. On average the firms started with three to four
persons.
Concerning employee growth after ca. seven years the firms had on average nine employees with five employees having a university degree; after ca. five years the firms
had seven employees (see next page) roughly comparable with State I in Table I.69.
Young technology firms’ growth during the first few years is rather strong with the
growth rate decreasing significantly after four years. However, one must be aware of
the fact that for startups high growth rates are often due to the low level they have
started from. More realistic impressions would consider growth rate calculations to
start with year four of the firm’s existence. This would be after the “startup thrust”
phase (Figure I.125).
The data of Cowling et al. [2007] reported for an NTBF sample from Germany and the
UK collected 1997-2003 fit these findings: in the median firm in its 12th year there
were 12 persons in Germany and 10 in the UK.
Furthermore, for the NTBFs growth in sales is consistently larger than growth by employee numbers. That indicates the productivity (sales per employee) has continuously increased over the time period under consideration, probably due to learning effects.
The data in Table I.70 show that after foundation on average revenues for NTBFs
from the industrial high-tech areas TVT and HVT are considerably larger than those
from the software and TBS areas. The yearly averages across the Dot-Com Recession shed some light on an recession’s impact and the issue of sampling for statistical
79
descriptions of NTBFs, such as that of Hanks et al. [1993] (Table I.69).
Table I.70: Sales, number of employees and average growth rates of German NTBFs
[Gottschalk et al. 2007].
Averages

Sales
Year 1
1) ;
1,000 €

Sales
2006;

People
Year 1
2)

People
2006
3)

Growth,
Employees

Growth,
Sales
4)

1,000 €

All 5)

190

840

3

7 (3)

24%

34%

TVT

260

1,130

4

8 (3)

25%

34%

HVT

350

1,530

4

10 (2)

29%

39%

Software

140

480

3

6 (3)

25%

37%

Other
TBS

160

670

3

7 (4)

22%

32%

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Table I.70, continued.
Year
Started
19982000

210

1,270

4

9 (5)

13%

28%

2001

170

740

3

7 (4)

17%

34%

2002

190

690.

3

6 (4)

18%

40%

2003

220

760

3

6 (3)

23%

50%

2004

170

650

3

6 (3)

39%

–

20052006

150

260

3

5 (2)

60%

–

Growth rates are actually calculated in terms of a CAGR formula (Equation I.10).
1) Sales in first year of business; 2) Number of full-time employees;
3) Total employee number and employees with university degree in parentheses;
4) Foundation years 1998 - 2003; 5). For acronyms cf. Table I.1.

In addition to the above outline on NTBFs’ growths the following observations were
made for German NTBFs. With regard to the foundation dynamics NTBFs differ already during their early years by their development paths [Creditreform - KfW - ZEW
2009]:
Most young technology ventures exhibit only little economic activities. Except
for the founding persons there are rarely additional employees. Except for the
year of foundation there are no further investments and neither a product nor
process innovation is launched.
They probably represent largely RBSUs characterized (for the UK) as a “spinout becoming one of the ‘living deads’ with little prospect of success.” They
have limited growth and hence, become the ‘living deads’ rather than disappear completely [Fyfe and Townsend 2005] – They are “non-growth NTBFs.”
For a second group of NTBFs’ foundation indicators for development reflect a
build-up process which, after some time, comes to an end (cf. Clusters A
(State I) and B (State II) text below Table I.69): Growth in terms of number of
employees and volume of investments slows down and the NTBF does not
launch additional new products or processes.
Technical developments concentrate on updates or improvements (phenotype: growth setback – plateauing, back to (low) growth or asymptotic growth
(Figure I.107) – they are “marginal NTBFs.”

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The third group of NTBFs comprises firms which in their core domain exhibit
high activities. Over several subsequent years they show high growth rates in
terms of number of employees, they launch new products or processes or issue high investments (innovation and investment persistence; ch. 4.2.3,
Figure I.117) in expansions or renewal of their capacities. The related phenotype could be assigned to “continuous growth or growth setback – back to
growth” or even non-linear exponential growth (Figure I.107) – they are
“promising NTBFs.”
This grouping is in line with data in Table I.63 and associated text, which is: most
NTBFs start small and stay small, having roughly between twelve and fifty employees
(Table I.69). A general analytical description of the developments is displayed in
Figure I.155.
The above grouping is also reflected by a study of German NTBFs founded in incubators with entrepreneurial teams, the survey’s population being from 2007 [Zolin et al.
2008]. Accordingly, all firms with an entrepreneurial team are rather small. On average
they have twelve employees, 80 percent of them achieved less than €2 million in revenues and 82 percent report a balance sheet total of less than €2 million. Since no firm
in the sample exceeds €50 million in sales or a balance sheet total of €43 million,
according to Table I.4 the sample can be classified as reflecing a sample of small and
medium-sized enterprises mainly consisting of micro firms.
Though not strictly related to technology ventures, a rough “80:20” rule seems to be
also applicable for mid-sized firms. An investigation of 1,300 German mid-sized,
usually family-controlled firms [Fröndhoff 2008] and comparisons with the 180 firms
(14 percent) showing the strongest growth revealed that the top firms have growth
rates of 10 – 39 percent, far exceeding the others (ch. 4.3.6).
Concerning the proportion of NTBFs with growth or fast growth characteristics, in line
with general results from GEM (ch. 4.1), a recent US study [Stangler 2011] found for
new (technical and non-technical) firms, for instance, that about two-thirds of job creation came from young firms, many of which were small and never got much bigger.
Only a small number of firms creates a disproportionate share of such additional jobs;
these are the top-performing firms. According to the study
Measured by employment growth, in any given year, the top-performing 1 percent of firms generates roughly 40 percent of new jobs.
The top 5 percent of companies (measured by employment growth) creates
two-thirds of new jobs in any given year.
The fastest-growing young firms (between the ages of three and five years)
account for less than 1 percent of all companies in the economy, yet generate
10 percent of new jobs each year.
The “average” firm in the top 1 percent contributes eighty-eight jobs per year. The
large majority of these companies end up with somewhere between twenty and 249

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employees. On average, fast-growing young companies create about twenty-seven
jobs per year, with most growing to a size of about twenty to ninety-nine employees.
The average firm in the economy as a whole adds two or three net new jobs per year
[Stangler 2011]. This has also been described for NTBFs in Germany (ch. 4.3.1).
Importantly to note, however, many of the jobs created by these fast-growing firms will
disappear. Most of the companies in the top 5 percent and top 1 percent are young
and so susceptible to failure even if they have been creating jobs. That means promoting fast developing, high-growth companies will not guarantee the creation of sustainable firms. Three or four years later the business may fail and the jobs disappear.
Specifically, controlling for industry sector and ranking on the Inc. 500 lists, it was
found [Markman and Gartner 2002] that extraordinary high growth – in terms of sales
and number of employees – was not related to firm profitability (cf. also LinkedIn
Corp., ch. 3.4.2.1, B.2).
Venture capital and large private investment are viewed in the US to be important for
the development and growth of certain firms. However, it does not appear to be universally important for creating high-growth companies.
Of several hundred fast-growing companies on the Inc. list over the last decade, only
sixteen percent ever received a venture capital investment (cf. also the German
situation, Table I.24, Table I.25, Figure I.54, Figure I.55). Venture capital, moreover, is
highly concentrated in just a few sectors, but high growth companies can be found in
nearly every sector of the economy [Stangler 2011].
We assume that foundations of technology-based firms are roughly a quarter of all
foundations (Table I.2). But young, high tech firms create a greater percentage increase of net new jobs than do the other categories of young firms [Kirchhoff and
Spencer 2008]. Hence, we propose that job creation by NTBFs can be approximately
related to a kind of “80:20” pyramid displayed in Figure I.119.
From a point of view targeting practice providing rules of thumb, similar to Drucker’s
pitfall No. 3 (ch. 4.2.3), and in a context of a stage-based view of firms’ growth one is
led to search for approximate time lines with development-related “markers” for
NTBFs, keeping Bhidé’s [2000:247] basic approach into account that “does not try to
force empirical regularities into a recurring temporal sequence.”

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Figure I.119: The inverted pyramid of growing NTBFs related to employment contributions according to a rough 80:20 rule.
For instance, all the previously described observations suggest the following tentative
time-related markers (Table I.71) concerning revenues for NTBFs with founders
having full or majority ownership and full control of the venture (Table I.74) – unless
significant firm-internal or external events interfere strongly with the development. The
attribution also takes productivity (revenues per employee) into account.
Table I.71: Approximate time-markers for NTBFs with above average growth (nonVC-controlled startups).
Years of
Existence

Revenue

Number of
Employees

Average Growth
Rates *)

4-5

$400,000; €300,000

7-8

Year 2: 60%

5-6

$1.6 mio.; €1.2 mio.

9

Year 3: 50%

7

$5.5 mio.; €4.1 mio.

30-60

Year 4: 40 %

15 - 17

$50 – 70 mio.
€37 -52 mio.

500

Year 6: 30%

*) Estimations using data from Table I.70.

Other time markers for such kinds of NTBFs can refer to three rules of thumb reflecting organizational issues of young firms (Table I.72).

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Table I.72: Approximate time-markers for development phases of NTBFs without VC
participation and control via an implemented management.
Drucker’s third pitfall, the management crunch after 4-5 years (Figure I.118) for
startups without a professional management team – and the NTBF having 9-11
employees;
Fourth pitfall, the “Let go” issue (Figure I.118) after 10-15 years and ca. $60 million
revenues (Table I.67, Table I.71);
The “10 - 25 - 150” rule of thumb relating the number of employees to organizational
issues, particularly related to leadership/management, specialization, communication,
coordination and delegation.

The “10 - 25 - 150” rule of thumb, covering essentially the ranges 8-12 or 20-30, relates to the approximate number of employees of a growing firm or an overall range of
8 to 30 employees without discrimination. It has emerged from various discussions
with entrepreneurs and confirmed by several of those who contributed to the author’s
Technology Entrepreneurship curriculum. For instance, in the time table of Attocube
AG (B.2) one reads: “2005 >10 employees, introducing new organizational structures.”
The situation inducing new firm structures was characterized by P. Klausmann [2011]
by relating to communication and coordination issues: “You can gather up to ten
people at one table to have a productive meeting.” And N. Fertig, founder of Nanion
Technologies, explained: “Sticking points for organizational problems occur with ten to
fifteen employees. Then, internal communications becomes the decisive factor for the
future development.” (in German “Knackpunkte für Organizationsprobleme treten bei
zehn bis fünfzehn Mitarbeitern auf. Dann wird die interne Kommunikation zum entscheidenden Faktor für die weitere Entwicklung.” [Fertig 2012:Slide 42].
The rule relates to typical thresholds associated with necessary adaptation of the organization and its infrastructure to changed conditions of growth. The “10-threshold” is
in line with Drucker’s “management crunch” in year four to five of a new firm having on
average seven to nine employees and Greiner’s “revolutions” (Table I.68).
Overcoming these thresholds requires time, energy and money (including conflicts
with employees and partners or stakeholders). According to Weber [2002] the ability
of large groups or organizations to coordinate 12 people successfully (ch. 4.3.2)
represents a certain threshold of efficient coordination per se.
The “10 - 25 - 150” rule of thumb is corroborated also considering growth of a startup
in terms of the number of employees and associated expansion of building facilities.
This means relating “communication intensity” (probability of communicating at least
once per week) of the firm’s employees in relation to separation distance in meters between the employees. Accordingly, communication intensity is ca. 30 percent, decreasing to 15 percent for a distance of 5 meters and converging to 12 – 10 percent if

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10 meters are exceeded. The last measured distance was 80 meters [Ulrich and
Eppinger 2000:Exhibit 14-12].
Concerning the “25 threshold” we hear from Niels Fertig (Nanion Technologies GmbH,
B.2) when the firm founded in 2002 after seven years had 30 employees: “We now
have reached a size which requires new structures (in German “Wir haben jetzt eine
Größe erreicht, bei der man neue Strukturen braucht.”; cf. also Table I.90).
Lars Hinrichs, the founder of German Xing AG (ch. 3.4.2.1; B.2), pointed to another
relevance of the number 30 for firm development. During the early phase of Xing he
held regularly meetings with his employees every Friday. Every employee was motivated to speak out, what went well and what went wrong – and to make suggestions
for betterments. This worked until the group reached the number of thirty as a
threshold because with more people no longer everyone could or would speak up. For
more people in the firm corresponding meetings were organized by department in a
face-to-face manner or for distributed departments via video conferences.
According to the above view one can assume that the “30 marker” more or
less ends a startup’s state of organizational success as an outcome of a dynamic organization-wide and all employees embracing process.
It is notable that, for instance, Autio [2005] interconnects the “25 threshold” to “highexpectation activity” which is attributed to “all startups and newly formed businesses
which expect to employ at least 20 employees within five years’ time.” His rationale:
achieving the size of 20 employees is not simple (cf. also Solazyme – Table I.90).
Firms of this size, typically, will have a developed internal specialization, identifiable
management roles and some separation of ownership and employees, in the sense
that not all employees are also owners of the company.
Several entrepreneurs the author spoke to mentioned that the “twenty-five employees
threshold” has shown up as a dip in the firm’s productivity chart (revenue per employee). Crossing successfully the “twenty-five employees threshold” has been identified as inducing a period with a rather long lasting organizational stability – unless
other factors like recessions interfere.
An economic recession may show up every 5-10 years (with predictable occurrence, but ignorance when it will occur and with what intensity). Furthermore, a recession requires usually other qualities of leadership/management
than a “normal” growth phase. In particular, it may turn an NTBF’s state into
“survival mode.”
Hence, a recession does not only affect the financial state of the organization,
but also the organization in terms of management, control and execution.
The “150 rule” has been put forward, for instance, by Sonnete [2011] through a social
hypothesis, which covers also the “10 - 25” part: The brain size constrains the size of
social networking (by group size) which requires memory on relationships and social
skills. And the human brain can only remember 150 meaningful relationships.

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Indeed, evolutionary anthropology suggests a hierarchy of social networking according to the number of sub-group members [Sonnete 2011]: Support Clique (ca. 3-5
members), Sympathy Group (ca. 10-15), Camp (ca. 25-30), Village (ca. 130-180) and
Tribes (ca. 500-1,000). This fits also with the organizational hierarchy of the army with
Sections (squads) (10-12 soldiers), Platoons (of 3 sections, ≈ 35 soldiers), Companies
(3-4 platoons, ≈ 120-150 soldiers) and Battalions (3-4 companies plus support units, ≈
550-800).
The “150 threshold” is also seen in Microsoft’s (Table I.67) and Xing’s (B.2; Figure 8)
productivity data.
Gladwell [2000] also remarks upon the unusual properties tied to the size of social
groups. Accordingly, groups of less than 150 members usually display a level of intimacy, interdependency and efficiency that begins to dissipate markedly as soon as
the group’s size increases over 150. This concept has been exploited by a number of
corporations that use it as the foundation of their organizational structures and marketing campaigns.
Staged models mostly emphasize the fit between the design of the organization and
growth stage. Growth is considered to distort the balance between the design of the
organization and the stage of growth, and the task of leadership/management is to restore a balance. In this sense, the models are also metamorphosis models, as the
organizational architecture of the firm needs to be changed for each stage.
The above patterns do not generally apply to VC-based NTBFs and NTBFs striving for
large scale productions. Here, the following rules of thumb may be useful (Table I.73).
Table I.73: Approximate time-markers for developments of VC-based and productionoriented NTBFs.
Venture capitalists assume that “lemons” ripen in two or three years, but the “pearls”
take seven or eight.
A new business rarely establishes itself in less than three or four years.
Developing a company of sufficient size out of a new business development (NBD)
initiative of a large firm will take five to eight years [Runge 2006:464].
A seven-eight years requirements is also often observed in non-technical areas, e.g. it
took FedEx eight years from idea to become operational [Bhidé 2000:168-185].
For (existing) companies observed for a period of almost a century it took 6-11 years to
transform laboratory results into mass production [Runge 2006:654-655].
This seems also to be the case for NTBFs (cf. Nanophase Technology (Figure I.140)
and biofuels startups – A.1.1). The related phenotype of growth corresponds often to
that of “delayed growth” (Figure I.107).
However, delayed growth may also be associated with an “unexpected event,” such as
a political interference as in the case of US firm First Solar (Figure I.154) and the
German firm Enercon GmbH (Figure I.150; B.2) or due to firm-specific development
issues, as observed for US Closure Medical [Runge 2006:98-103].

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As a summary, staged approaches do have the merit of making observations of firms’
dynamics with regard to revenues and number of employees as growth indicators –
and combining both into productivity. However, without observations at the firm level,
the mechanisms and processes of growth remain obscure.
Disregarding VC-based startups with their stage (“series”) approach (Table I.27), “lifecycle and staged models” fail to adequately account for the great variety in the manner in which new technology-based firms grow. Moreover, comparing developments of
“Ford versus General Motors” there appeared “great differences in how the two
competitors developed their assets and routines, and in the role of their founders.”
[Bhidé 2000:245-247]
VC-based NTBFs follow often the VC-staged process (Table I.27) for (anticipated)
growth which is structurally related to the Stage-Gate® (PhaseGate) process for innovation in large firms (ch. 1.2.7.2 Figure I.76, Figure I.180). In large firms intrapreneurship is often following strict phased processes with decision points and a restricted
number of progression paths for innovation, NPD or NBD processes. Here, the prototype is the Stage-Gate® process (Figure I.79, Figure I.180).
Moreover, the early phases of a new product development project (which is concept
generation and product planning) are commonly acknowledged to play a central role
in the success of product innovation of large firms. Early decisions are unlikely to be
changed during downstream phases, unless high costs and time are experienced.
They have therefore the highest influence on project performance.
However, early analysis and problem-solving is also a difficult task, because the necessary information and insights are not available until one gets into detailed design.
Most companies are locked in this dilemma between anticipation (anticipating decisions in the early phases of product development, where influence on performance is
substantial) and reaction (delaying decisions to downstream phases, where information and opportunities are manifest).
A structurally similar situation is also found for startups. Though for a large part of new
technology ventures developments seem to evolve in a phased manner following
“stimulus-response” mechanisms and representing particular states of the firm the absence of prototypical initial startup constellations and conditions in stage-based models and the absence of predetermined development paths precludes so far some common features in the growth of NTBFs.

4.3.2 The Initial Architecture and Initial Configuration
The startup constellation represents a key for entrepreneurship as the basis for further
development of the firm and its assessment by others (“observers,” particularly financial backers). It will generate expectations concerning the development or even generate expected values for the firm (,for instance, financial projections of VCs).

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In line with the GEM model (Figure I.15) we assume this constellation to be preceded
often by a “pre-startup” phase comprising linking idea generation and revealing opportunity and conceptualizing the firm (Figure I.125). In the GEM-approach (Figure
I.15) the pre-startup phase covers activities of the “potential entrepreneur” and the
“nascent entrepreneur.”
The diaries of the German firm Suncoal Industries GmbH (B.2) provides a lucid insight
into the pre-start phase of an NTBF.
Basically, one must differentiate the founding success and the survival of the new firm.
We shall denote the one to four years period after firm’s foundation as the “startup
thrust phase” (Figure I.125). Our discussion will follow an approach focusing on the
founder person(s), resources and environment as well as the founding process. Here
the vision and mission of the founder(s) (ch. 2.1.2.7) are important for building the firm
and expectations.
Previous research suggests that the initial choices of the entrepreneur or the team
have a lasting impact on the way the company evolves. In particular, they may facilitate self-reinforcing mechanisms (ch. 2.1.2.5), positive feedback mechanisms, by
which a system’s conversion processes and output (Figure I.5) or states are enhanced
or brought into a more favorable situation.
For instance, group formation is often associated with processes of system’s development by self-reinforcement and self-enforcement (ch. 2.1.2.5). Early decisions referring to intangible and tangible resources (Table I.8) will be important (ch. 4.2.2).
The discussions so far emphasized the fact that startup and NTBF development will
be affected not only just by financing, but also by associated issues of ownership and
control of the new firm. Correspondingly, initial architectures of NTBFs must be differentiated – by one of several classes of taxonomy given later in Table I.74 and Figure
I.128 – to discuss the various NTBF developments adequately (cf. also A.1.1.6).
Initial resource endowments – the stocks of resources including the founders’ experiences (ch. 2.1.2.4) that entrepreneurs contribute to their new firms at the time of
founding – may explain the different life chances of new firms during start-up (cf.
[Bhidé 2000; Klepper 2001]). In that way certain firms, such as spin-outs of industrial
firms or serial entrepreneurs already control a relatively large productive base and
some financial reserves at start.
Initial financing and very early development will often rely on own resources and resources of family and friends (3F) and significant cash flow (Table I.23, Table I.24,
Table I.25).
And there is a number of NTBFs which were started because the founders had already customers (notable cases cited in this book are ChemCon GmbH (B.2) and
PURPLAN GmbH (Box I.21) whose founders started as consultants or engineering
planners, IoLiTec GmbH and Solvent Innovations GmbH (A.1.5), WITec GmbH (Table

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I.41, Figure I.123; B.2) and US Cambridge Nanotech ([Yang and Kiron 2010], Table
I.80; B.2) , SAP AG (A.1.4) and Concept Sciences, Inc. (CSI; Box I.11).
Furthermore, family and family members may not only provide financial resources (3F,
ch. 1.2.7) or buildings/land to the entrepreneur, but also other business-related support and advice or other commitments as observed for William Henry Perkin in Britain,
the “father” of the synthetic organic dye industry (A.1.2.), ChemCon GmbH (B.2) and
Nanopool GmbH [Runge 2010].
Additionally, the Family & Friends System (ch. 1.2.2, Figure I.16, Figure I.17) may provide emotional support and role modeling. For instance, spouses with similar or complementary talents, skills or education (for instance, commercial rather than technical
orientation) may enter the startup of the entrepreneur full- or part-time, as described
for the role of spouses of the US firms Osmonics, Inc. and Avery Dennison [Runge
2006:91-94, 474-477]. Spouses also founded Cisco Systems in the US (both with IT
competence; Figure I.145) or in Germany ATM Group AG (B.2), CeGaT GmbH
([CeGat 2011], B.2) and OHB AG (end of ch. 2.1.2.4).
Hence, many entrepreneurs owe much of their success to parental education or inherited or won family contacts. WITec GmbH could take advantage from two factors. One
of the founders, J. Koenen, got a loan from his father-in-law who also served as a role
for being self-employed (Table I.41).
Special family-related cases occur if entrepreneurial activities sprout out of existing
firms of the family. One case concerns business succession. Another case is “branching” or “specialization” of a family-owned firm. For instance, the German startup
“Heppe Medical Chitosan GmbH” providing nano-chitosan as well as high-quality and
high-purity chitosan and chitosan derivatives for medical and cosmetics applications is
run by Katja Heppe (now Katja Richter), whose parents run the company Heppe
GmbH. The parents’ firm produces among other things chitosan for industrial paper
and textile applications.
Chitosan is a natural product, a linear polysaccharide, which is produced for commercial use from the shells of shrimps and other sea crustaceans. It is one of the most
important renewable raw materials of the world, cellulosics being the most important
one.
At the startup phase the founders’ aspirations, ambitions, experiences, competencies
and skills are crucial to the company’s growth, as are financial and business resources. But, potentially interconnected to financing aspects, the initial startup setting
is influenced by the fact whether the startup will strive for large-scale production or
whether the characteristics of the opportunity requires fast development for entering
the market.

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Large-scale production requires tremendous amounts of capital. To be successful a
rule-of thumb says: For markets with short product cycles the time till market entry is
important, for longer product cycles cost of production is critical.
For the startup the environment of the NTBF is relevant, for instance, statuses and
developments of technology, existing or emerging functionally equivalent technologies
and industry (segments, markets and competition, and other relevant systemic influences). Therefore, the entity of inquiry will be the initial configuration which covers
the startup’s initial architecture (ch. 1.1.2; Table I.5).
Technology entrepreneurship may be compared with an across country auto
racing with a starting point and various initial conditions, but with a given
finish. At the start there are cars with various technical and design features
having a driver or driver team with various capabilities and experiences. But to
reach the finish (goal) there are several courses with various hindrances, barriers, ups and downs as well as bumpy or smooth roads and an environment
affecting the course, for instance, wind and rain making the course slippery.
And there will be gas stations to get needed power and cross-roads requiring
a decision to follow the planned route or changing direction. The “starting constellation” of the entity determines the momentum for “lift-off” and then decisions will have to be made which route to follow initially (the “expected path to
success”) and in which manner (“action and execution and speed”).
A complementary metaphor can focus on the start of an aircraft: A runway is used for
preparation and then there is a needed thrust for the departure of the aircraft (lift-off).
All that is in the aircraft’s “potential”; and sometimes there may be an additional momentum, for instance, wind from behind (for instance, reflecting a startup having already customers on foundation, as described above).
The metaphor concerns the “startup thrust phase” (Figure I.125) which may cover a
one to four years period with the startup and the founder(s) having their new firm
steam up (Figure I.122).
For those NTBFs which started with having customers the thrust phase will be very
short, probably one or two years. The startup thrust phase of NTBFs will be associated mostly with characteristic “average” growth rate patterns (Table I.70, Table
I.71) reflecting “acceleration” to lift-off. The startup thrust phase must be differentiated
from the “scale-up period” of new firms with large-scale production which usually takes
six to eleven years until product launch into the relevant market (Table I.73).
If vision is where the entrepreneur wants to arrive at (ch. 2.1.2.7), culture is
the foundation he/she can get there (cf. also Table I.43).
In this context of direction, execution and control Reid Hoffman, co-founder of
LinkedIn (ch. 3.4.2; B.2), made some recommendations for entrepreneurship [Kaiser
2004]:

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“Smart people tend to think that they can execute on a complex plan. Executing on a
complex plan is generally a recipe for failure. If you can’t make a startup work on a
simple plan then your chances of success are very low.
Another lesson is that as an entrepreneur you want to choose a project that is far
enough away from what others are doing. You want as much distance from other
players so that you have the opportunity to create something.
The last thing I would add is that you want to measure your endeavor as soon as
possible. You want to be able to gauge the viability at the earliest possible moment, so
that you can change and adapt your model as needed.
Entrepreneurs tend to want to launch only when their product or service is perfect.
The problem is that waiting undermines the ability to evaluate whether the idea works
as quickly as possible, so that you can correct course. Correcting course frequently is
key to success.” (cf. overshooting, Figure I.88)

Creating Firm Culture and Developing Employees
In Silicon Valley, it is often said that the founder is the startup.

One of the components of initial resource endowments of NTBFs, being also a differentiator, is corporate culture which plays an important – though generally hidden –
role. It emerges in the first few years of the startup. Particularly as an intangible asset
a unique culture offers an advantage over competitors. It will affect product design,
prototyping and realization, hiring practices and the values empowering employees to
live the mission [Lowry 2011].
Usually it is assumed that the entrepreneurs play the key role in shaping corporate
culture which is “intrinsic” to the initial architecture. Focusing on the founders we put
forward a model of corporate culture to be formed essentially by a self-replicating process. Figure I.120 illustrates this for “behavioral patterns” as the important and observable expression of culture.
Self-replication is any process by which an entity will make a copy of itself – usually by
distinct steps increasing the number of entities by one or more. The important ingredients to such a step comprise entrepreneurial leadership by example, influence and
employee development (Figure I.141). Establishing behavior and “how things are
done here” through “leading by example” (“walk as you talk”) is a characteristic of
many CEOs of Hidden Champions (ch. 4.1.1).
Metaphorically, assuming the founder(s) to determine the DNA for behavioral patterns
can be compared with gene expression, which is the process by which information
from a gene is used in the synthesis of a functional gene product.
An NTBF usually starts with up to five persons. That means shaping culture starts almost from scratch with the entrepreneurs/owners driving its direction. There is mostly
one “leader” who has the greatest influence – usually the founder or the “primus inter

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pares” of a team. Disregarding situations were only two persons form the new firm, the
model of a self-replicating system can start with a three-person constellation.

Figure I.120: Development of firm culture expressed by behavior of a firm’s leader or
founder by a self-replicating system.
Whereas Figure I.120 refers to a pattern-related process of firm culture evolution an
interpretation of this process takes the following route. A small group, such as the
founding members of a firm, does not face substantial difficulties in coordinating efficiently. Once they have done so, they can establish a set of self-reinforcing rules or
norms either tacit or formalized governing what actions and behavior are appropriate.
These norms allow the group or organization to continue to successfully coordinate
activities.
As the group grows, new entrants’ exposure to these norms allows the entrants to be
aware of the appropriate behavior and creating an expectation for everyone in the
group of what everyone else (including the new entrants) will do. Therefore, relatively
slow growth and exposure of new entrants to the group’s previously established
norms can overcome large coordination failure.
The missing part of this interpretation is the “new employee” (“entrant”) of the firm,
which is associated with the firm’s hiring process. A complement to the interpretation
could tentatively refer to a “targeted selection” process which is ubiquitously applied
by large firms for hiring activities focusing on a primary facility (a technical, commercial or administrative/managing specification) and a secondary facility of importance
and additionally “needed to have” or “nice to have” competencies or personal traits
80
and overall fitting with the corporate culture.

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Creating NTBF culture is the leader’s responsibility to drive employee development by
a directing or supporting style according to the employee’s status of competence and
commitment (Figure I.121). Leadership focusing on people in startups will emphasize
influence rather than power as a means of assertiveness and execution (influence >
attitudes > behavior; ch. 1.1.2).
Delegation and transfer of responsibility to the individual employee increases the level
of identification with the firm. The leader’s goal must be:
Keep the corporate culture across growth processes.
The human resources philosophy of 3M made in 1948 can serve as prerequisite of the
interconnection of employee development and firm growth: “As our business grows, it
becomes increasingly necessary to delegate responsibility and to encourage men and
women to exercise their initiative. This requires considerable tolerance. Those men
and women to whom we delegate authority and responsibility, if they are good people,
are going to want to do their jobs in their own way.” [McLeod and Winsor 2003]
It is interesting to note that Greiner’s staged model of firm growth and associated style
of management (Table I.68) for growth of the firm also emphasizes directing and delegating as emphasized for leadership style for (individual) employee development in
Figure I.121.

Figure I.121: Leadership styles for employee development referring to employees’ development levels.

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Self-reinforcing mechanisms as described above occur specifically in the context of
coordination (ch. 1.2.1, 2.1.2.5; Table I.8, Figure I.73). There is ample evidence in experiments on coordination games that what a team did previously is likely to become a
self-reinforcing norm about what to expect in the future. Game theorists have also
recognized that organizational culture is one way in which a precedent helps select an
equilibrium by reinforcement.
Based on game-theoretical experimental settings with group sizes of 2 – 16
persons it was shown [Weber 2002] that the ability of large groups or organizations to coordinate successfully is critically affected by the group’s growth
process itself. Consistent with previous experimental research, coordination is
much easier in small groups. It was shown that, even though coordination
does not occur in groups that start off large, efficiently coordinated groups can
be “grown.” This corroborates also the interpretation of self-replication.
The experiments, indeed, indicated that efficient coordination in large groups is possible when groups start small and then grow slowly (coupled with the exposure of new
entrants to the group’s history). Moreover, the early failure of groups in the growth
sessions of Weber’s experiments appeared to produce an instance of the common
view in the business world that firms can “grow too fast.”
Following Kaplan [2003b] skills related to building the firm’s culture comprise
Leadership (ch. 1.1.2; Equation I.1): ability to build consensus in the face of
uncertainty
Communication: ability to keep a clear and consistent message
Being a good team player: knowing when to trust and when to delegate
Decision-making: knowing when to make a decision.
Trust, competencies and commitment will always be the foundation of success
through leading decision-making and related courses of actions and execution (Figure
I.111, Figure I.117). However, the starting point is always beginning with communication to ensure understanding of the vision and mission (ch. 2.1.2.7) and agreeing on
common priorities.
Hence, 1) the leader must share his/her goals and objectives with the staff. And, after
having a concept of activities and operations and specification of tasks in place he or
she must 2) clarify coordinating instructions and 3) explain control and how to
measure level of achieving objectives – having success (ch. 4.1).
Building consensus means achieving agreements among a set of possibly very diverse people. Building consensus is in the context of risk and uncertainty (ch. 4.2.1)
and making decisions (ch. 4.2.2) at the right time. The expected result is that everyone of the new firm is aware what his/her role and job is and what he/she contributes
to success. This implies to continuously check whether the firm’s operations (Figure

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I.5) have generated value and, moreover, whether value creation has been achieved
efficiently.
Communication based on explaining what is and why what to do is a key capacity to
influence someone else’s behavior as compared with one’s own behavior. In the context of entrepreneurship and building consensus among all the people of a startup it is
advantageous to refer to operational facets related to each individual’s decision problem in the context of objectives introduced by R. Ackoff.
Ackoff’s suggestion as cited by Runge [2006:341] is concerned with the valuation of
the objectives, the possible courses of action and the efficiency of each course of
action in achieving each objective and the individual’s probability of choice for each
course of action. Accordingly, there are three effects of communication with a related
basis, options and results referring to individual behavior and actions:
Motivation:
Information:
Instruction:

Values of the objectives
Possibilities of choice of the available courses of action
Efficiencies of the available courses of action.

Information usually affects a person’s mental state of cognition. Instruction refers to a
finite number of actions to achieve a result which, as the simplest case, may proceed
sequentially, but will become complicated through conditional branching options or
loops. An everyday example of an instruction is the “cooking recipe.” Motivation is the
major effect leaders should focus on.
Concerning operations, behavior and social interactions corporate culture in large
firms develops for new employees usually quite differently. Here one often observes
three paths:
Official and Codified:
“Manuals”; for instance, Operations Manual, Office Manual etc. (on paper or
the firm’s Intranet); spelled out by supervisors
Official and Not-Codified:
Expected behavior; “tacit,” rarely spelled out
Unofficial & Not Codified:
Do’s and Don’ts; individual leaders’ approaches to coaching and supporting.
This means, it takes rather long (and is costy) before a new employee has learned not
only about the firm’s offerings and strategies, but also the culture.

Initial Architecture and Initial Configuration with Corporate Culture
Given
The notions architecture and particularly configuration for (technology) entrepreneurship (ch. 1.1.2; Figure I.16, Figure I.72, Figure I.73) are fundamental if we are looking

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for that “footprint of a firm” which may be sufficient to understand, explain and make
statements about what can be expected from a firm’s development.
According to GST the architecture is always related teleologically to the founder’s
goals interconnected with his/her aspirations and expectations. But there are various
routes for the firm founder to reach the goals (Figure I.122). Accepting bounded rationality (ch. 4.2.2) the founder may not necessarily be aware of all the paths that are
possible. As a reflection of competitive situations for startups striving to reach the
“same goal” the systems view implies that there may be, for instance,
(Almost) identical architectures having different initial configurations (think of
startups in different countries, think of different input material as is observed
for the biofuels industry – A.1.1).
Initial architectures that may differ, for instance, just using generic technologies.
Different architectures which will usually follow different paths (such as various conversion processes);
however, at a particular “cross-roads” (Figure I.122), one architecture may
switch to a path of another one; think of the many processes in biofuels when
an initially thermochemical route switches over to a bioengineering process,
becoming a hybrid process (A.1.1.3; Figure I.175).
But, different architectures can generate the same value for firms and thus
would not provide competitive advantage.
The initial configuration (Figure I.122), structurally initial architecture plus environment,
depends essentially
on the industry’s or economy’s situations like a recession or a “bubble” or the
start of a new industry and
on the market level and type, whether foundation is oriented toward a megatrend, a niche, requires building a market (disruptive innovation strived for) or
start in a policy-driven market or mediatorial market (Table I.15).
Entrepreneurship in an area of industry genesis represents a special initial configuration for an NTBF (ch. 4.3.5; Figure I.143, Figure I.144, Figure I.145) and is often associated with the phenotype of “exponential” growth (Figure I.107).
Financing is a key component of a startup’s architecture. Initial financing of technology-based startups often begins before the formal incorporation of the new firm. It
begins during the pre-startup phase (Figure I.52, Figure I.125).
The “pre-startup phase” covers a time span which begins with the initial communication and discussions of startup intentions, driving forward related specific scientific or
technical inquiries and continues until the formal foundation as a legal entity that has
been authorized to operate by a state or other political authority (“incorporation”).

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After firm’s foundation there is the startup thrust phase which coincides essentially
with the phase of “early stage entrepreneurial activities” covering the first 3.5 years
after formal firm’s foundation according to the GEM model (Figure I.15).
Incubation of RBSUs (ch. 1.2.6.2; Figure I.) represents a particularly illustrative
example of financing toward formal firm’s foundation. Concerning availability or gathering of resources the pre-startup phase may overlap partially or totally with an
incubation phase, which, on the other hand, may also extend into the startup thrust
phase (Figure I.125; ch. 1.2.6.2; Figure I.).
Independently from sources of financing (Figure I.52, Figure I.59, Table I.30) one
should take the statement given by a “bioentrepreneur” as a general recommendation:
“The key thing I have learned over the past six-to-seven years is the importance of having enough cash in the bank. ... I have learned that it is a good
strategy to raise money, even when it is not needed, so that there is always a
sufficient cash cushion for when the market is uncertain.” [DeFrancesco 2004]
Initial financing as one basis of pursuing the business opportunity is a key component
of the startup’s (initial) architecture and configuration (ch. 1.2.7). As founders’ attitudes
(and goals) toward financing in relation to control/ownership of the new firm differ the
initial financing structure is an important factor and issue when addressing a firm’s
development and growth.
For proper discussio