HOW TO JUMP START PHD THESIS IN ENTREPRENEURSHIP
RESEARCH: A PRACTICAL HEURISTIC FOR PHD
INSTRUCTORS AND STUDENTS.
Sean Patrick Sassmannshausen: Schumpeter School Of Business And Economics,
Stefan Gladbach: Schumpeter School Of Business And Economics, Wuppertal,
Contact: Sean Patrick Sassmannshausen, Schumpeter School of Business and Economics,
University of Wuppertal, Gaussstrasse 20, 42119 Wuppertal, Germany, (T) 00492024393904,
(F) 00492024392464, Email: [email protected]
This paper reflects status of work in progress! Proof reading will be completed before the conference.
“PhD programs that allow students to combine research training
with working on their own research agendas
from the beginning of their doctoral studies
(as is generally the case in Australia, Canada, and Europe)
might have an advantage over programs that require students to
complete years of course work prior to embarking on their own research.“
(Nancy J. Adler & Anne-Wil Harzing 2009)
In this paper we define a “Ten Step Heuristic” that can help to systematically define research projects
in Entrepreneurship. We particularly address PhD students and their instructors, but our road map
might also be found useful by other scholars in the distinct field of entrepreneurship research. The
paper is a “good practice report” based on our personal experience from ten years in PhD programs.
Many partners have found the approach—especially the order of the various steps—contra intuitive at
first sight, but our heuristic proofed to be advantageous whenever it was implemented. PhD students
who follow our approach will not only create competitive research designs, but will also gain a deeper
understanding of Entrepreneurship as a scholarly field of research.
At many universities in the beginning of doctoral studies, PhD students face the challenge of
identifying a promising research topic. They do not only need to be able to work on that topic but also
want to emotionally commit to it. To our experience in ten years of Entrepreneurship Education,
freshmen in PhD-Programs find it difficult to define a research question that – at the same time – has a
promising potential in terms of scientific outcomes, is manageable in terms of research process, and is
appealing to the candidate. Over the years, we have developed a set of ten questions which PhD
students should answer in the early stage of their program. Step by step, students address these
questions in weekly workshops. Between each workshop, there is time to reflect and to consult existing
The benefit of this approach lays in systematically exploring the full range of Entrepreneurship in a
first phase, then narrowing down the field, identifying research gaps, and being guided by the “state of
the art” in Entrepreneurship Research. Instead of following a solely practical decision making process
(which often starts from students’ questions like “is there data that I could easily access?”), students
can follow a heuristic. The heuristic is designed to foster good scholarship: Find interesting topics first
and care for practical problems (like data gathering) thereafter. In addition, the guideline saves time
compared to random search for a research topic and provides solid insides in Entrepreneurship
Research and research methods within only a few weeks.
After some remarks on method and existing literature (chapter 2) we will introduce each of the ten
steps (chapter 3). We will address how this relates to the “rigor and relevance-paradigm” in chapter 4,
where we will point out how young PhD students can learn to gain relevance in their research. In the
final chapter 5 some closing remarks and conclusions are derived from the “Ten Step Heuristic”. These
remarks link our “Ten Step Heuristic” with the development of Entrepreneurship as an independent
field of research and with some considerations in the philosophy of science.
2. Motivation, Method, and Literature Review
The paper is a report on good practice. Therefore, it might not be regarded as “rocket science”, but
rather a useful application in the field of Entrepreneurship Education, especially for those who run (or
contribute to) or participate in PhD Programs in Entrepreneurship. The “Ten Step Heuristic” has
proven to be useful at our school and might be considered helpful in other places, too. For this reason,
we would like to share this practice.
The paper contributes to the rare literature on (or for) PhD programs in Entrepreneurship (e.g. Brush et
al. 2003). Since structured reviews addressing the special needs of PhD students are so limited in
number, we advise PhD students to read through a group of influential articles (reaching from “A” like
in Aldrich & Baker 1997, Aldrich & Fiol 1994, or in Aldrich & Martinez 2001 to “Z” like in Zahra &
Dess 2001) and to get their noses in some books, including for instance Schumpeter 1934, Casson
1988, Davidsson 2005, Davidsson (ed.) 2008, Landström 2005, and the Blackwell Handbook of
Entrepreneurship (by Sexton & Landström (ed.) 2000).
The “Ten Step Heuristic” is not just an extension of the “six research specifications” introduced by
Low & MacMillan (1988). There might be some similarities and interrelations, but after more than 20
years of Entrepreneurship Research have passed since Low’s & MacMillan’s constitutive contribution,
it seems to be important to go beyond their six dimensions framework (see Davidson et al. 2001). Our
road map is designed to guide researchers who have yet not defined their research interest and have
little or no experience in Entrepreneurship Research. So this paper is complementary to the “six
research specifications” (Low & MacMillan 1988) as well as to the twelve “topics to be covered by all
good research” introduced by Hofer & Bygrave (1992). In fact, the checklist provided by Hofer &
Bygrave (1992) is a reliable instrument to measure one’s personal success after working through the
“Ten Step Heuristic”. Readers will find our contribution rather useful if they are facing the invaluable
challenge of academic freedom. In contrast, PhD students will not benefit from this paper if they are in
programs which ‘dictate’ decisions about research topics, questions and methods for PhD theses.
In our opinion, the challenge of identifying and properly defining a research question is a challenge
that should not be taken away from PhD students. Academic freedom seems to be something we have
to fight for. Contemporary evaluating criteria for academics and therewith pressure to publish journal
papers of limited length create a tendency towards solely quantitative, positivistic and fragmented
research (see Wicks 2004, Nkomo 2009, p. 108). Unfortunately, to some extend this is also true for
Entrepreneurship Research (Gartner 1995, p. 68; see Gartner 2001, Harrison & Leitch 1996). Under
these conditions, it seems more important than ever for scholars to develop a holistic view on
epistemology and the subject they study (Rebernik & Mulej 2000 address the need of a holistic view
on entrepreneurship, see Hindle 2004, p. 583, who argues that entrepreneurship may be “insolubly
holistic in nature”). PhD Programs offer this opportunity for candidates to first see the full picture of
Entrepreneurship before narrowing it down to a well-defined thesis in a second step. Knowing about
epistemology and the full picture of Entrepreneurship is a precondition for a productive and creative
use of academic freedom as well as for the ‘mass production’ of successful journal papers during a
later stage of academic career. Therefore, we think it is important that scholars learn how to define
one’s own research program in Entrepreneurship from scratch (but of course building on existing
literature). We accept as true that ‘dictating’ research topics and methods can save time and direct
resources to core areas of an institutions interest (e.g. entrepreneurial finance). But at the same time
‘dictating’ research topics and methods is putting at risk the quality of PhD education and the ability to
make best use of academic freedom.
The “Ten Step Heuristic” might not only be useful for PhD candidates, but also more generally help
various researchers who are in the process of identifying new research challenges or are facing a
temporary lack of creativity. In the next chapter with each of the ten steps, some exemplary details will
be provided together with some references to the existing literature. To some of these contributions we
refer to as ‘mile stones in Entrepreneurship Research’. Epistemological considerations are not
addressed in this paper as part of the “Ten Step Heuristic” because most universities run special PhD
seminars on that topic.
3 Results and Implications: The “Ten Step Heuristic”
“Like the elders of any tribe,
academic elders pass on the wisdom and “tricks” of the culture
to the next generation.” (Adler & Harzing 2009, p. 87)
It is important to note that the ten questions should be asked and answered in the given order. It is
important not to change the list to its reverse order. This would put the advantages of the heuristic at
risk. To each question, we conduct a workshop where we brainstorm input on potential answers. Since
we discuss approximately two questions per workshop, the whole process takes about four to five days
within just a couple of weeks. Step 1 to 5 are opening up the field of Entrepreneurship Research. From
Step 6 on, the process is changing to decision of personal addiction or technical requirements. After
making each set of questions as broad as possible in the group, each student is asked to narrow down
his or her answer individually according to his or her personal preferences, prior knowledge and future
interests. Some literature is provided before sessions start to support preparation and to develop skills
in reading critically; some literature is provided after the according sessions to support a phase of
reflection on every decision question. In face-to-face meetings with the PhD instructors, PhD students
discuss the outcome from personal reflection. The ten questions a PhD student (or other researchers in
the need to identify and define research projects) should systematically address are summarized in the
following figure and will be addressed in more detail in the subsequent chapters 3.1 to 3.10.
Figure 1: The “Ten Step Heuristic” to jump-start PhD-theses and other research in the field of Entrepreneurship
3.1) Step 1, Entrepreneurship Phenomenon: What phenomenon in the field of Entrepreneurship
do you want to address?
The phenomenon of Entrepreneurship still has no clear borders. The academic debate on the nature of
Entrepreneurship still continues. Therefore, students should narrow down what kind of phenomenon
they are going to refer to: e.g. the entrepreneur, new venture creation, rapid growth of newly founded
businesses, corporate entrepreneurship, family business, franchising to name a few. (Readings: Rocha
& Birkinshaw 2007, Davidsson 2003 Davidsson 2005, chapter 1 and 2, Davidson & Wiklund 2000,
Gartner 1985, Carland et al. 1984, Gartner 1988, Carland et al. 1988, Low & MacMillan 1988,
Venkataraman 1997, Low 2001, Shane & Venkataraman 2000 and 2001, Gartner 2008).
At this stage, instructors need to ensure that PhD students understand the difference between a
phenomenon and a theoretically grounded definition. A definition of entrepreneurship—for instance
when defined as the discovery (or creation), evaluation and exploitation of commercial opportunities
(Venkataraman 1997, Shane & Venkataraman 2000, 2001)—could apply to various kinds of “real
world” phenomenons in Entrepreneurship, such like starting a company, corporate entrepreneurship, or
1) Chosing an
2) Identifying relevant
Level of Analysis in
3) Reflecting on the
4) Reflecting on
Subsequent Fields in
8) In-Depth Literatur
7) Reflecting on
6) Selecting an
5) Reflecting on
9) Chosing from
even becoming a franchisee. Even a person running a “Mom and Pop” corner store might be regarded
as someone who still exploits a sustainable opportunity that he once discovered many years ago (see
Bygrave 1995, who objects that those businesses should not be part of what Entrepreneurship Research
examines). However, in contrast you might also find start-ups which are not based on an opportunity,
but rather on necessity. Therefore, two elements of the same entrepreneurial phenomenon (starting a
business) may not be applicable to a single definition of entrepreneurship (utilizing an opportunity),
but a single definition can be applicable to a broad variety of phenomenons. In general, a phenomenon
is built on a group of elements who are somehow similar in their empirical attributes. A theoretical
definition can sometimes be applicable for a much broader set of elements than a just a single
phenomenon, but at the same time not for each and every single element within a phenomenon.
3.2) Step 2, Level of Analysis: What level of analysis are you interested in?
At least two dimensions are under consideration here, later we can even add more dimensions. First,
the phenomenon of Entrepreneurship can affect elements of certain levels on a hierarchical scale, e.g.
the personal level, organizational (often i.e. firm) level, regional level, industry level, environmental
level, national economical level, and international economical level. In a second dimension, levels are
not reflecting hierarchies of elements but of dynamic processes, reflecting initial conditions, processes,
context, and outcomes (Aldrich & Martinez 2001). Students should reflect what level they want to
address and instructors should advise them to consider multi level analysis, combining at least two or
three levels in both dimensions. A study that would not cover a wide span of levels but only a single
level (for instance only initial conditions) and not relating its findings with other levels (for instance
processes and outcomes) will remain descriptive or explorative in nature at its best. The same holds
true for studies examining only outcomes without relating them to any of the previous levels.
(Readings: Low & MacMillan 1988, p.151f., Davidsson & Wiklund 2001, Busenitz et al 2003, p.
278f., West 2003, Aldrich & Martinez 2003 and – as just one example of a multi-level/multi-
dimensional study – Groen 2005).
Exemplary Hierarchical Levels of an
international economic level
national economic level
regional economic level
local economic level
Entrepreneurial team level
Entrepreneur at individual level Exemplary
Figure 2: Exemplary two dimensional matrix to organize and combine levels of analysis when starting out
dynamic entrepreneurship research.
More dimensions can be added to this model. For instance, it might be suitable to add a disciplinary
dimension (see e.g. Herron et al. 1991 and 1992 or Wortman 1987). Research on Entrepreneurship can
be undertaken from a solely economical, psychological, sociological, anthropological, or political
perspective. It could also reflect merely managerial research. Within each dimension, there are again
more levels, for instance the economic approach consist of Neoclassical, Austrian, Institutional,
Up to 32 (8x4) research quadrants
which could be combined (all of
them or – more likely – in part) in
Evolutionary reasoning and so forth. A multi-level approach would combine different perspectives:
For instance a study on a managerial level combined with an economic approach on an institutional
level (“Ordnungsökonomik”, to be precise), and some elements from the level of political analysis
could help to understand “rent seeking” processes in start-up support programs. Such a multi-level
approach would be sufficient to examine all three parties involved: Entrepreneurs, politicians, and
agents of start-up support agencies.
3.3) Step 3, Life Cycle: What phases in the entrepreneurial life cycle do you want to examine?
In Entrepreneurship Research, different phases of the entrepreneurial process can be under
examination, from idea generation, business planning, launching, establishing and growing a new
venture to exist or sustaining a business or the succession of a family business. Before selecting a
phase of interest, researchers should answer the question to what life cycle concept they refer to? Some
life cycle models distinguish early stage phenomenons like idea creation and business planning,
prototype development, the stages of legally starting the venture, market entry, and the later stages of
growth and exiting (or retaining) the business. Others refer to the model of opportunity recognition (or
creation), development, evaluation and exploitation, others are based on technological life cycles or
market cycles. Students should know the different models and take a decision on the stages they are
interested in. Models can also be recombined.
Life cycle models can help to identify certain tasks which are characteristic of (or critical to) certain
stages of entrepreneurial processes. Distinctive measurements for entrepreneurial processes and
outcomes apply for various stages, as pointed out by Wilkinson & Hindle at the AGSE International
Entrepreneurship Research Exchange 2006 (see figure 3). (Readings: E.g. Churchill & Lewis 1983,
Scott & Bruce 1987, Scott 1990, Carter et al. 1996, Kaiser & Gläser 1999, Ferrary 2003, Wilkinson &
Hindle 2006, and—as just one example of a study referring to a life cycle model—Hite & Hesterly
1999 and 2001).
Instructors should point out that researching the transition from one stage to another can be extremely
rewarding (e.g. like executed by Delmar & Shane 2004 and Delmar & Shane 2004a). For instance it
could be examined why so many participants in business plan completion never enter the start-up
stage, thus never walking the walk after talking the talk, while other entrepreneurs still do. By the way:
A longitudinal research design that tries to follow businesses from early stage to exit might be of great
academic value, but—for reasons of duration—might not be applicable for PhD students.
Figure 3: Life cycle model identifying typical activities, measurements and decisions that are characteristic of
certain stages in the entrepreneurial process (figure taken from Wilkinson & Hindle 2006).
3.4) Step 4, Research Topic: Which topic / subsequent field in entrepreneurship research are you
Entrepreneurship research often combines common research fields with the phenomenon of
entrepreneurship. Titles of articles published in the field of entrepreneurship often reflect this
recombination of Entrepreneurship Research with existing fields of research by combining the word
‘entrepreneurship’ with a second research topic in a way that indicates a certain research context like
in: entrepreneurship and finance, entrepreneurship and venture capital, entrepreneurship and networks,
entrepreneurship and social capital, entrepreneurship and strategic alliances, strategic entrepreneurship,
international entrepreneurship, entrepreneurship education, social entrepreneurship, entrepreneurial
psychology, entrepreneurship and economics, and so forth. Step 4 is interrelated with the disciplinary
dimension in the previous step. PhD students should build on their existing knowledge and consider
their future (academic) career options when narrowing down potential areas. Writing a thesis that is at
the interface of entrepreneurship and a second field of your choice might increase your ‘academic
employability’. A PhD student who for instance is publishing a thesis on entrepreneurship and
marketing might later on apply for academic positions in entrepreneurship as well as for positions in
However, if Entrepreneurship is to be regarded “as a distinctive field of research” (Low 2001, p. 17,
see Venkataraman 1997, Shane & Venkataraman 2001) we will need at least some scholars who take
courage to focus on the core of Entrepreneurship (whatever this might be in your eyes) – without
adding a justifying little phrase “…and something” behind the term ‘Entrepreneurship’. Dealing with
the framework of opportunity recognition or creation, evaluation and exploitation (see Sarasvathy et al.
2005 for a review) can be one way to write a thesis at the very core of our field. Three more examples
will be provided by the next step (see Landström & Sexton 2000 for some more suggestions on further
research in entrepreneurship).
3.5) Step 5, Entrepreneurship Theory: What entrepreneurship theory or construct do you want to
A single Entrepreneurship Theory in terms of a normal science paradigm (Kuhn 1962) does not exist
(see Harrison & Leitch 1996 for discussion), yet not even a unifying definition has occurred. (Even
though Shane’s & Venkataraman’s (2001) definition gains much attention, there still is criticism and
conceptual extension, e.g by Kumar (2006)). This situation continues since many decades, even so
some leading scholars in the field have called for such a unifying framework. Bygrave & Hofer (1991,
p. 16) have put forward the search for a deterministic Entrepreneurship Theory, following the role
model of theories in physics: „With that kind of predictive power, we would have the key to economic
growth! Need we say more!! Entrepreneurship would be the giant of the business sciences, perhaps of
all the social science!!” (Bygrave 1995, pp. 258f., see Bygrave 1989, Bygrave 1993, Bygrave & Hofer
1991, Fallgatter 2004, and Aldrich & Baker 1997 for a reflection).
It can be doubt that such a single Entrepreneurship Paradigm will ever emerge, due to several reasons.
Entrepreneurship is an interdisciplinary field; from which discipline should our framework origin
(Fallgatter 2004)? However this decision would be taken, wouldn’t such a decision exclude other
disciplines with their fruitful contributions? Would the establishment of a dominant paradigm therefore
support or hinder the future development of the field? Entrepreneurship deals with unforeseeable
creativity, unpredictable novelty and unanticipated innovation. Could a deterministic theory ever apply
to such an ambiguous context? Can deterministic theories altogether apply to social science? As
Landström (2005, p. 21, see Landstöm 2000) pointed out: „Entrepreneurship is an inherently
complicated and ambiguous phenomenon, and the content of the concept changes over time. Because
the phenomenon in itself is complicated, ambiguous and tends to vary, it is reasonable to expect that
our definitions of the concept will also be ambiguous and changeable.” Gartner (2001, p. 34) argues
that “[t]here is no theory of entrepreneurship that can account for the diversity of topics that are
currently pursued by entrepreneurship scholars.” And last but not least, would a paradigmatic theory of
entrepreneurship foster or hinder entrepreneurship education and entrepreneurship itself (the
phenomenon called “entrepreneurship”, which exists out there in the field)? We know from other
context, that sometimes our well-intended, sophisticated theories can destroy good managerial practice
(Ghoshal 2005). PhD students should reflect arguments for and against a normal science paradigm in
Entrepreneurship Theory. For example, they can outline the contrary positions of Bygrave and Gartner
in a group work and then debate in the class room on the pros and cons of the two contrary positions,
one group representing Bygrave’s position, the other one taking a stand for Gartner.
Entrepreneurship is still a young field of science (Low 2001). Most leading researchers have entered
from other fields (e.g. Aldrich from social science, Audretsch, Davidsson, and Turik from economics,
Bygrave from physics, Freese from psychology, Gartner from business administration, Hisrich from
marketing, Reynolds from engineering, just to name a few). (See Landström (2005) for a refelction on
the phenomenon of academic mobility in the case of Entrepreneurship Research.) Based on
biblionmetric analyses in a special issue of Entrepreneurship Theory and Practice, Gartner et al.
(2006) have noted: “[…] we have observed: entrepreneurship researchers borrow heavily from their
home disciplines and retain their academic loyalties to these disciplines.“ Therefor again, a single
dominant normal science paradigm is yet not expected to get established because of the heterogeneous
body of entrepreneurship faculty. Even Bygrave (1995) acknowledged: „We do not want to erect a
wall around our field with notice that trespasser should keep out. Rather, we need a fuzzy boundary
around the field that posted with welcome signs for scholars who share our beliefs and want to join us
and labor in the field of entrepreneurship.”
We agree and we believe that at this stage scientific pluralism (Feyerabend 1975) is much more
productive than a normal science status with a strong paradigm (Kuhn (1963) never called for such a
paradigm, his work was not meant to be normative but rather solely descriptive). Scientific pluralism
can hinder the establishment of normal science status and still boost advances in Entrepreneurship
Research. As Gartner (2001, p. 34) mentioned: “The conundrum, as I see it, is that the totality of
current academic research does not espouse (nor can it espouse) an entrepreneurship theory, per se;
rather entrepreneurship research espouses a diverse range of theories applied to various kinds of
phenomena. There is no theory of entrepreneurship that can account for the diversity of topics that are
currently pursued by entrepreneurship scholars. […] I do not see a way for scholars to generate a
theory of entrepreneurship based on so many different research topics that seem to constitute the field
of entrepreneurship. All of the disparate findings that compose our field are unlikely to be connected
into a coherent whole.”
However, under the aegis of scientific pluralism scientist need to take responsible decisions on
research design. “Anything goes” (Feyerabend 1993, p. 93), but anything does not go at the same time
in the same paper or thesis. For Feyerabend, the notion of “anything goes” only addresses pluralism in
choice of method and framework. It is a misinterpretation that this notion would be directed against
methodological rigorness once someone has chosen or developed a method or has selected or created a
framework (Feyerabend 1993 pp. 93f). Hence, decisions need to be taken regarding the framework and
the methods. PhD students could either develop their own framework in terms of a new
Entrepreneurship Theory, or they could contribute by researching within a given framework,
contributing to its validity, reliability, and extension. We suggest the latter: Leave the development of
new theories and concepts to the more senior researchers and thereby stick to your last, gain a deep
understanding of the existing literature and the structure of the field, demonstrate your ability to
contribute to an existing stream of research, achieve solid research results, and save time and reduce
risk of failure. The same opinion applies to methods: PhD students may either choose from the broad
variety of existing methods (qualitative or quantitative or—preferred—a mix of both – e.g. developing
a questionnaire for empirical research based on previous in depth qualitative research) or develop new
methods. We suggest leaving the development of methods to the most senior researchers. In a PhD
thesis, it is by all means sufficient enough to demonstrate the ability to make best use of existing
methods. (We will not address the matter of methods here, see below Step 7. PhD candidates are
advised to consult the existing literature on methodological issues and to participate in course work.)
A number of conceptual frameworks in Entrepreneurship have emerged during the last decades. A
dominant Entrepreneurship theory does still not exist. But as a result of academic pluralism, we own a
considerable amount of non-exclusive Entrepreneurship Theories. This demonstrates how “hard cores”
in science (Lakatos 1970) can emerge from years of pluralistic approaches to science. Theoretical
frameworks in Entrepreneurship include for instance the constructs of Entrepreneurial Orientation
(Covin & Selvin 1986, 1988, 1991, 1993), Entrepreneurial Management (Stevenson 1983/2006,
Stevenson & Gumpert 1985, Stevenson & Jarillo 1990, Brown et al. 2001) and Entrepreneurial
Effectuation (Sarasvathy 2001, Sarasvathy 2004, Sarasvathy & Dew 2008), just to name three
examples. This is a different story than those theoretical frameworks provided under Step 4, where we
have considered frameworks and research topics which do not originate from the field of
Entrepreneurship Research, but rather have been imported from other fields for combination with
Entrepreneurship (e.g. social science in the case of Entrepreneurship and social capital, or strategic
management in the case of Entrepreneurship and strategic alliances). Frameworks considered under
Step 4 have usually—before they had been adopted to Entrepreneurship Research—been out there for
many years, and have been tested and improved over and over again, like for example in the case of
network theory (Kilduff et al. 2006).
By contrast, theoretical constructs which have just emerged from Entrepreneurship need different
scientific treatment. For instance they need to be tested for validity and reliability of scales. Some
measurement instruments still need to be improved or tested under different cultural or circumstantial
influences. Some constructs (like entrepreneurial management) need to be linked with more levels of
analyses, e.g. linking the measurement scale of entrepreneurial management with firm performance or
outcomes on an industry level or a regional economic level (for example see Kuhn et al. 2010). Our
field needs what we call “creative replication” of previous research (see Davidsson 2005, chapter 9).
In addition, it might be a fruitful approach to combine external frameworks with Entrepreneurship
Theories. Combining considerations from Step 4 with those from Step 5—i.e. combining theoretical
frameworks from other fields with constructs that emerged within the field of entrepreneurship—could
lead to promising PhD-theses which for instance would examine “the role of networks in
entrepreneurial management”, “the influence of strategic alliances on entrepreneurial orientation”, or
“the challenge of entrepreneurial finance within an effectuational approach to entrepreneurship”.
Taking into account the current status of reviews and textbooks on Entrepreneurship Theory (not on
Entrepreneurship in general) it might be quite difficult to systematically identify all the current
constructs in Entrepreneurship theory, especially for new PhD students. Here, we have limited our
exemplary sample to three constructs (entrepreneurial orientation, management, and effectuation).
Only very few publications address the need of a broad systematic review (e.g. Low & MacMillan
1988, Brush et al. 2003, Acs & Audretsch (ed.) 2005, Landström 2005, and a series of journal papers
with a clear focus on reviewing the field called “Foundations and Trends in Entrepreneurship”, edited
by Acs & Audretsch (2005-2010). Therefore it currently remains an individual challenge for PhD
instructors to clearly and systematically communicate the distinctive constructs which already exist in
3.6) Step 6, Empirical Objects: What “real world objects/matter” do you want to examine?
After all those theoretical considerations, it is time to take a break, take a deep breath and then take on
the next big challenge. Contemporary research needs to combine theoretical reasoning with empirical
analyses. Within the five previous steps, PhD students have defined their research interest. It may
surprise some readers that the process didn’t start with an empirical observation. Often, the starting
point for defining a research interest is such an observation: Students read about venture capital, or
some social enterprise, or the biography of an entrepreneur. Thereby they get interested in this
particular topic (e.g. VC, social entrepreneurship, entrepreneurial personality etc.). Students try to craft
a research design around that particular interest. We believe that students who follow this simple
evolutionary approach are victims to mere chance. They might end up lucky, but they might also get
hit by contretemps, unable to complete research. And they may miss opportunities for promising
research just because they weren’t aware of the full range of chances for developing meaningful
research which existed in the first place.
In case the previous steps have directed towards a study on the phenomenon of new venture creation
(step 1) and the transition from the phase of planning the venture to entering the market (step 3), a real
world object that would combine individual and firm level (step 2) could for instance mean:
“Entrepreneurs who are in the process of launching their first venture”. However, this definition of an
object is much too broad. It is important to narrow down this phenomenon. For instance, research
could be limited to entrepreneurs who are scientists at non-private universities in a certain state of
Germany (or the US, or Australia, or any other country), and who are spinning off technology based
ventures in the year 2009, whereby the construct of “technology based venture” is indicated by the use
of patents. Now the sample under examination is much more well-defined. The thread of heterogeneity
in your data is significantly reduced (Davidsson 2008, Davidsson 2005, chapter 5) and the outer
conditions at the macroeconomic and the institutional levels are standardized. The likelihood that
empirical variance in entrepreneurial outcomes has been influenced by variables under examination—
and not by uncontrolled randomness—has increased (see Gartner 1995, p. 71). This also means that the
precise definition of the research object will allow formulating precise—and thus testable—hypotheses
in the further progress of a PhD study.
3.7) Step 7, Motivation: What is your personal philosophy about you doing research?
“Instead of socializing doctoral students into the current chase for A-listed journal publications,
why not attempt to fuel their natural desire to make a difference?” (Adler & Harzing 2009, p. 88).
Most researchers have their personal motivation for conducting research. For instance, some want to
provide results with strong practical implications; others care more about theory development. Most
are primarily interested in the object they study. To them, methods are nothing more than means to an
end; others again love to face the challenge of methodological development. Some get their motivation
from the object they study (a trend recently surveyed in social entrepreneurship) or from the theory of
their belief (a trend recently surveyed in effectuation). Both situations (being obsessed by the object of
study or the theory of belief) can lead to a lack of critical thinking. A reflection on the personal
motivation can help avoiding this human weakness. Some researchers are motivated by the end of the
mean: to obtain a doctoral degree. This can lead to brisk progress, but also a lack of thoroughness.
Whatever a student’s philosophy is, he or she should make it explicit. Personal goals and motivations
should influence the research design in a positive way while consciously avoiding possible negative
A research design that is not aligned with the personal motivation can be a pain; a pain that will
probably stick to the PhD student’s neck for many years. Not to mention that the experience of
“academic freedom” is hardly to be made if someone works on a research project he or she can’t
identify with. We know that some PhD instructors argue that life isn’t fair and that they can’t execute
their obligations from third party funding if they leave such decisions to their PhD students. Not the
personal motivation—they argue—but rather the imperatives of the research institution determine
research designs (see Wicks 2004, Rynes 2007 (Editor-in-Chief Academy of Management Journal) and
Nkomo 2009 for discussion). Such thinking may apply for professional research associates in post PhD
positions. They earn their money by executing research of all kind, it’s their job. PhD students in
contrast should be encouraged to follow a more idealistic road, since most of us take their PhD only
once and feel emotionally committed to this process.
3.8) Step 8, Literature Review: Do you really know the literature in your field of interest?
Students are asked to read through the existing literature according to their interests as indicated by
answers to question 1 to 7. “Reading” in science means to first generate economies of overview and
then to critically read and interpret the literature in order to identify weak spots and research gaps. A
first step is to realize how much contributions already exist and to find technics to deal with the
amount of existing literature. Besides searching online data bases like Ebsco Host, PhD students
should physically go to the library and spend some time on a discovery journey. The literature can be
brought to a certain order to gain maximum insights in minimum time. Therefore, students start to read
publications on the development of the field (including articles on theory development and
methodological challenges) and review articles, starting with the older contributions working their way
to the present. In a second step, meta-analyses are under consideration. In a third step, the vast majority
of remaining articles are screened. In many cases, the number of available publications is so big that it
is just impossible to read them all. For instance, approx. 1,500 articles have been published on
entrepreneurship and networks (Sassmannshausen 2010). Students can identify the most cited
publications using Google Scholar. All other articles can be screened by the abstract. If the article
seems to be an important contribution, the introduction and conclusion should be read. Then it can be
decided whether or not to read the full paper.
Reading needs guidance and support of experienced instructors who know the literature. To train
students’ abilities in the art of critical readings, instructors should discuss some of the readings with
their scholars in small group settings. Only thereafter students should spell out and write down their
research question. Just writing it down can already be an iterative process of several hours spend on
narrowing down, making it precise, fighting with heterogeneity, taking into account literature that has
not been evaluated earlier etc. And still, a research question will not be finalized in just a few hours.
Instead, the formulation will be revisited several times during weeks of the research process.
3.9) Step 9, Methodological Choices: What methods are applicable to address the issue you have
The aim of a study should determine the use of research methods—and not the other way around. We
will not go into detail here. We have already referred to methodological literature and course work. (A
very useful textbook is Blumberg et al. 2008: It comes with a CD that—amongst other content—
contains decision trees which help to select adequate quantitative methods.) The number of methods is
almost without limits. Some debate over qualitative or quantitative research. We argue that this is not
an “either/or-option”. Scholars could rather start out conducting qualitative research to gain an
understanding of the empirical object under examination (including the identification of a set of
influential variables) and to explore the boundaries of the phenomenon. Thereafter well-grounded
quantitative research can produce insights especially about how the various variables—which have
been identified by the qualitative approach—interact in total. PhD students should use the opportunity
to demonstrate their skills in both approaches. To show that a candidate really understands the methods
seems to be more important than questions of sample size and other common methodological issues.
Good qualitative studies are in no means inferior to quantitative work. However, it is sometimes harder
to get them published, especially by so called ‘leading’ journals.
Besides the common general literature and text books on methods, there are some articles and books
that especially address methodological challenges in Entrepreneurship Research. Typical challenges
are such like: the definition of statistical groups (e.g. who is an entrepreneur?), problems with official
statistics on the number of start-ups (over- and under-coverage, i.e. the establishment of the legal body
of companies are registered, but not every company that is registered really is starting operations), the
challenge to find and measure appropriate variables of “entrepreneurial success”, the special need for
case study research in Entrepreneurship or the problems that occur when using methods that are based
on a statistical average (not saying that such research shouldn’t be done, but it should be execute with
care, and its limitations should be well reflected) and so forth. We recommend paying attention to
those publications. (Readings: e.g. Van de Ven & Ferry 1980, Carland et al. 1984, Bygrave 1989,
Gartner 1989, Hofer & Bygrave 1992, Chrisman 1994, Johannisson 1995, Davidsson & Wiklund 2000,
Chandler & Lyon 2001, Gartner & Birley 2001 and the subsequent articles in their JBV special issue
on qualitative research, Storey 2002, Hindle 2004, Davidsson 2005, Wilkinson & Hindle 2006, Gartner
2007, Davidsson (ed.) 2008).
3.10) Addressing Organizational Tasks: Asking practical questions!
Only now, after working through all the previous questions, students should address two groups of
practical question: (1) urgent technical and (2) important strategic questions. The first group consists of
questions such like: Where to get data from (make or buy-decision)? How much time and resources to
spend? How to fund and execute empirical research? Sometimes, entrepreneurial spirit (e.g. the ability
to work around bottle necks) is needed to find convenient answers to such questions. Practical issues
have been real obstacles only in sporadic cases. Thus the need to redefine a project will hardly ever
occur since in most cases small adjustments of the research question will already allow to continue
with the PhD research process. (Curran & Blackburn 2001 provide valuable recommendations on how
to address practical problems in research on Entrepreneurship and SME.)
The second group of questions addresses some more important strategic considerations: Who will
benefit from (or be interested in) the results? What publication strategy could work well with the
thesis? Which journals would care? In how many subsequent articles can the research be divided for
multiple journal publication? Students will notice that those strategic questions can be easily answered
after following the “Ten Step Heuristic”. If not, then it is likely that something went wrong on your
way. In this rare event, especially Step 1 to 6 need to be revisited. In general, students have worked
successfully through the “Ten Step Heuristic”, if they can provide answers to all twelve areas that are
included in a checklist for good research practice provided by Hofer & Bygrave (1992), p. 92.
4. STEP ZERO – ADDING A “SECOND LOOP TO MATTER MORE”
“…much academic research is rigorous but irrelevant”
(Adler & Harzing 2009, p. 80)
The “Ten Step Heuristic” is not a replacement for other guidelines. It’s complementary to existing
conventions. We especially agree with the notation that scholarly research should – in the best case –
be rigor and relevant (Vermeulen 2005, Tushmann & O’Reilly III 2007). The scholarly contributions
of doctoral students do not need to remain “insignificant” (Vermeulen 2007, p. 754). Our systematic
approach to defining research questions can help to add significant impact to the findings of a PhD-
thesis. Davidsson (2002) has described how Entrepreneurship Research can gain relevance and impact.
For the purposes of relevance and impact, in some cases a “Step Zero” needs to be implemented before
taking on with the following ten steps: PhD students who have no entrepreneurial family background,
have never been entrepreneurs, have never met and talked with “real” entrepreneurs, or worked inside
a start-up or VC company, should “add a second loop to matter more” (Vermeulen 2007, p. 754). This
loop consists by making hands-on contact talking with entrepreneurs and/or hands-on experience
working with (or for) entrepreneurs/start-ups.
We all have witnessed rare cases of young researchers presenting self-humiliating papers at
conferences, stating totally unrealistic assumptions about (and implications for) ‘the reality of
Entrepreneurship’. They build their ‘holistic’ picture solely upon statistical measurements from just
one single (but somehow significant) sample. (Not to mention a missing methodological consciousness
for a typical lack of normal distribution in our samples). But locked inside their ivory tower (locked by
well-intended instructors who want them to rapidly produce positivistic papers), they have never met,
spoken or worked with a ‘real’ entrepreneur in person. And the empirical results and their
interpretation of data seem somewhat wrong-headed to those who know Entrepreneurship from
firsthand. In such situations, we have always felt both sorry and angry. Sorry for the candidate and
angry because obviously no instructor took care of correcting specified misperceptions.
Entrepreneurship is about exceptional actions. Thus, Entrepreneurship should not be defined by a
statistical average; indeed, the ‘average’ start-up and the ‘average’ entrepreneur maybe are the least
interesting ones. Much more can be learned from the actions outliers took, than from the practice of the
average. We recall Gartner’s notation (1995, p. 75): “there is no average in entrepreneurship”! (See
e.g. Bruyat & Julien (2000) for a discussion of the advantages and disadvantages of both, positivism or
constructivism, in the field of entrepreneurship research.)
We therefore strongly recommend ensuring that young researchers get into contact with entrepreneurs,
learn about their spirits and fears, share their workload etc. In a word: send them to the field!
Participating in consulting / coaching entrepreneurs together with a senior consultant and/or writing a
case study (conducting the interviews, joining entrepreneurs in meetings inside and outside their start-
up, observing them while they execute tasks, structuring the case etc.) together with a senior researcher
are two valuable approaches to provide firsthand real world experience. It takes no more than one to
three month to gain deep personal insights, but it adds a lot of understanding, esp. in those research
students who never have been in contact with Entrepreneurship before joining the academic career path
(see Bjerke 2007 for an extensive discussion on “understanding entrepreneurship”). Vermeulen
(2007)—in his paper on rigor and relevance in the “Academy of Management Journal”—called this
approach of close exchange with practitioners “the second loop to matter more”.
To sum it up: In general, in our opinion, all PhD students should at least make some little experience in
qualitative research before moving on with quantitative research designs. They should also gain
firsthand insights into entrepreneurial activities. Assisting in consulting, coaching or in case study
projects, or conducting semi structured interviews (for the purpose of their own research) are just a few
promising approaches which only consume little time at the beginning of a PhD process.
5. CLOSING REMARKS AND CONCLUSION
We would like to address a number of issues in a closing remark: First, we have found this “Ten Step
Heuristic” a useful road map. It was successfully tested at our school. It helps not to miss important
decisions early on and not to act unaware of the structure of the field. This heuristic assists in
narrowing down research interests and provides structural guidance. Applied in various places and
programs, it would help to establish some common mental constructs that might be referred to as “hard
cores” of research in terms of Lakatos (1970) and therefore add to the academic viability of
Entrepreneurship Research (see Fallgatter 2004). However, it is not designed to take away the need (or
burden) of individual decision making from doctoral students. It’s rather designed to train young
scholars in making best use of the freedom of academic decisions and to encourage instructors not to
further reduce academic freedom, but to pass it on to the next generation of bright scholars.
Accordingly, reading through this article, some may have noticed with surprise that we didn’t discuss
theoretical sound definitions of Entrepreneurship, and how PhD students can select the ‘right’
definition. Shouldn’t students define what is meant by the term “Entrepreneurship” as used by their
theses? Yes, clearly they should. However, we do not intend to predetermine PhD students’ decisions
on what entrepreneurship definition is the best for their purpose. After working through each of the ten
steps, the question should be easily answered either by selecting an applicable definition from those
hundreds of entrepreneurship definitions that are already out there, or—in case none of these
definitions suites well—by creating a new definition. Consequently there is no single step that suggests
how to make a decision on choices of theoretical entrepreneurship definitions. (Step 5 was on testable
constructs and theories in entrepreneurship, not on definitions!) The preference for a certain definition
is usually resulting from the whole process of the Ten Step Heuristic. Or like Gartner et al. (2006, p.
327) have coined it: “Entrepreneurship scholarship is what entrepreneurship scholars pay attention to.”
Second, if one reads through the list of references, he or she will notice that most of the literature—
literature that might be regarded as “mile stones” defining the aim and scope of the field—was not
published in our leading journals of entrepreneurship research (such like Journal of Business
Venturing) but rather in other leading management journals like Academy of Management Review,
Academy of Management Journal and Journal of Management. On one hand side, it is notable that
Entrepreneurship as a distinctive field of research gains so much attention by leading management
journals (see Busenitz et al. 2003). On the other hand, it is a challenge to our dedicated
entrepreneurship journals: Shouldn’t they contribute more to the theoretical foundations and
development of our field? (This seems to be true especially for the Journal of Business Venturing,
were as Entrepreneurship Theory & Practice has made some more fundamental contributions to theory
Third, this paper has some limitations. It does not refer to all literature that might be regarded ‘mile
stones in Entrepreneurship Research’. PhD instructors may feel free to extent the list (Brush et al. 2003
suggest some lists of literature for course work in PhD programs; the lists are organized by
disciplines). PhD instructors may also feel free to change the order of some of the ten steps (but not to
the reverse order of the whole process!) or to add additional steps. As reported earlier, this contribution
reflects experience from a ‘good practice’, and a good practice might not be mistaken for ‘(the one and
only) best practice’. It is a heuristic that can (and often will) lead to good results, but it is not a logical
determinism that will always and under all circumstances produces best results.
Fourth, this road map is designed to help PhD students, not to rule them. Students may take detours or
decide for a different route. We allow for detours and different routes, because we believe that this will
help to achieve a “critical mess” (Gartner 2004, p. 199, see Gartner 2006a and 2006b) in
Entrepreneurship Research. In his work and much to our surprise, Gartner does not quote Paul
Feyerabend. However we do so, believing that scientific pluralism improves the critical power of
science (Feyerabend 1975, 1979, 1984, 1999). In our opinion, scientific pluralism does so especially in
a multi-faceted area of interest like entrepreneurship, which involves entrepreneurs’ “rule breaking
behavior” (Knyphausen-Aufseß et al. 2006) and which might only be tackled down successfully by
interdisciplinary efforts (Herron et al. 1991 and 1992, see Harrison & Leitch 1996). It might surprise
some readers that we agree with Lakatos and Feyerabend in the Conclusion of the same paper, but we
assume that there is some truth in both points of view. (Maybe this is the reason why Feyerabend and
Lakatos battled each other so hard (see Feyerabend 1999).)
So, where ever the journey of researching entrepreneurship will take you: Have fun and enjoy while
being productive in either way, following Lakatos or Feyerabend!
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