Phenomenon-based research in management and organization science:
Towards a research strategy
Georg von Krogh, ETH Zurich
Cristina Rossi Lamastra, Politecnico di Milano and ETH Zurich
Stefan Haefliger, ETH Zurich
April 2009
No phenomenon is a phenomenon until it is an observed phenomenon, Niels Bohr
Abstract: Recently, the editors of Long Range Planning called for more phenomenon-based research. Such
research focuses on capturing and reporting on new or recent phenomena of interest and relevance to
management and organization science. In this article we seek to explore the nature of, and opportunities
associated with phenomenon-based research. We seek to develop a research strategy for this type of work and
provide guidelines for researchers interested in conducting this mode of scientific inquiry. Phenomenon-based
research is a pre-theoretical research strategy because it explores and informs research designs that enable
scientific inquiry to proceed. We illustrate this strategy with a prominent and recent example, namely the study
of the open source software phenomenon by an interdisciplinary community of scholars.
Keywords: Research methods, phenomenon-based research, organization theory, invisible college, academic
community
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Introduction
Recently several scholars have criticized the strong devotion to theory they believe characterizes management
and organization science (Hambrick, 2007; Helfat, 2007; Miller, 2007). Hambrick (2007: 1346) noted that:
“Even if many nice things can be said about theory, too much focus on it is likely to prevent the reporting of rich
details about interesting phenomena for which no theory exists (Hambrick, 2007, p. 1346). Contributing to this
debate, the editors of Long Range Planning called for more phenomenon-based research.
Phenomena can be defined as regularities that are unexpected and unexplainable against the background of
existing knowledge, including extant theory and that are relevant for the scientific discourse. Thus, the target of
phenomenon-based research is to capture, describe, document, and conceptualize a phenomenon so that more
detailed theoretical work and development of research designs can proceed.
Phenomenon-based research is characterized by two main interdependent elements. First, no currently available
theory has enough scope to account for the phenomenon or for relevant cause and effect relationships associated
with it. Second, no research design or methodology is superior to others in exploring the different aspects of the
phenomenon. First studies generate insights based on exploratory (pre-theoretical) work with data and research
strategies that inform subsequent research designs. Hence, the lack of appropriate theory gives rise to first
attempts at making sense of preliminary results and data and research on the phenomenon proceeds along pretheoretical research strategies.
Although often forgotten in the current debate on the epistemology in our discipline, phenomenon-based
research and pre-theoretical work has a long tradition in management and organization science. In 1938, Chester
Barnard published a book entitled “The Functions of the Executive”. This book develops some components of a
possible theory of cooperative behavior in organizations and the roles and tasks of executives to foster this
behavior. According to the foreword by Kenneth Andrews (Barnard and Andrews, 1968) to the anniversary
edition, Barnard's urge to write the book came from a deep dissatisfaction with theories of scientific management
formulated by F.W. Taylor and the rationalistic theory of organizations originating in the work of H. Fayol.
Andrews writes: “The Functions is a direct outcome of Barnard's failure to find an explanation of his own
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executive experience in classic organization or economic theory. His own extensive multidisciplinary reading
offered him few clues until his encounter with Vilfredo Pareto and with L.J. Henderson, a biochemist of
interdisciplinary bent who studied and wrote about Pareto. Barnard was stimulated by what sociology could
explain that classical economic and organization theory could not. His acquaintance with Henderson, Donham,
Mayo and the other members of the coalition of social scientists and clinicians who were rediscovering human
motivation in the Hawthorne Works was indispensable to the development of his own central thesis (Barnard and
Andrews, 1968: x).”
Barnard discovered the phenomenon of roles played by executives based on his own experience. He searched for
theories but those he found failed to explain the outcome for cooperative behavior in organizations. Thus, he
joined forces with others who were interested in discovering factors that impact on human motivation and
cooperation in organizations. Originating in pre-theoretical reflection on the phenomenon of cooperation in
organization, Barnard's work became instrumental for future research and theory building on leadership and
organization behavior, known as the “human relations” perspective. Many similar examples can be found in
areas including strategy (Andrew's own work), organizational behavior, organization theory, and technology and
innovation management, all having in common the observations of an interesting phenomenon and an awareness
that established theory from the home discipline eventually would not advance the understanding of the
phenomenon under study.
As far as recent research on relevant phenomena, Bartlett and Ghoshal's work (1989) on transnational
corporation is phenomenon-driven, in the sense that they explicitly claim to have started their inquiring process
by observing interesting phenomena, followed by identifying and describing their salient aspects. The authors
(2002) have explicitly acknowledged that they don't believe the transnational corporation really came out of
any...literature (p. 13) and have described their research as hypotheses creation rather then hypothesis testing. In
acknowledging the great importance of their work for the international management field, Cheng (2007) noted
that their phenomenon-motivated research has lead to break-through knowledge, and, subsequently to new
theory (p. 29). Similarly, Lavie (2006) has recognized a phenomenon-driven approach in the rapid evolving
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literature on alliance formation, stemming from the accumulation, proliferation and significance of inter-firm
alliances in recent years (638). He observes that the traditional theories of the firm, such as the resource-based
view, have limited explanatory power in accounting for strategic behaviors and performances of connected firms
and puts forward the need of integrating and extending them, explicitly adopting an interdisciplinary approach.
As these examples show, the call of Long Range Planning editors is of great interest and importance for several
reasons. First, in social science (as in science) there is a continual appearance of new phenomena that require
explanation. These problems stimulate investigations which are considered interesting in their own right, as
opposed to merely representing arenas for theory testing (Simonson et al., 2001). In this respect, the call supports
a general tendency amongst top tier journal in our field (e.g. Academy of Management Journal, MIS Quarterly or
Organization Science), to publish research that is relevant (Vermeulen, 2007; Fendt et al., 2008), interesting
(Bartunek et al., 2007), and has a significant impact on managerial decisions (Pfeffer, 2007).
Second, phenomenon-based research represents a different approach to the scientific inquiry. In order to account
for complex phenomena, researchers should avoid starting their analysis with the a priori formulation of specific
hypotheses. A longer period of observation of the real world is needed before reaching the level of theorizing.
Specifically, such observation of the phenomena give rise to new research problems and constructs that later
serve as foundations for the development of new theories (Colquitt and Zapata-Phelan, 2007; Siggelkow, 2007).
Giving up to the approach of conducting research as a tool to test and extend the existing theories from the
established scientific discourse, this way to conduct the scientific inquiry may generate break-through
knowledge that re-shapes the scientific discourse in management and organization science.
Third, phenomenon-based research calls for a different approach to empirical data collection and analysis,
informed by a rejection of reductionism in favor of more pragmatic (Fendt et al., 2008) viewpoints on research
design. Specifically, the employment of quantitative and qualitative methods is required for researching on the
unfolding reality (Peirce, 1992). As the editors of LRP expected, observational methods in all their guises,
including laboratory experiments, field observations, or statistical analyses, may be useful to capture the
heterogeneity and richness of management and organization phenomena (Weick, 2007). As recently underlined
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by Gulati (2007) the preference for either qualitative or quantitative methods may be an obstacle to scientific
progress.
Fourth, a phenomenon-based approach to the scientific inquiry may be a way to reconcile long lasting
epistemological divisions within management and organization science. Judging by the number of papers
published in JCR journals, the field has experienced a strong expansion over the past half century compared to
that of adjacent disciplines, such as economics, sociology, and psychology (Rynes, 2007). This growth has been
coupled, particularly throughout the 1970s and 1980, with a raging debate among the scholars about the
epistemological and ontological foundations of the disciplines (see, among the others, Burrell and Morgan, 1979;
Hinings et al., 1988; Reed, 1988; Jackson and Willmott, 1987), which has lead to questioning assumptions,
theories, and methodological approaches (Hatchuel, 2001; Hambrick, 2004)1.
Starting from early 1990s, various scholars have commented that such divides should come to an end, as it were
threatening the fabric of knowledge development in the field (Gordon, 2001). Burrell (1996) argued management
and organization science had become a “tower of babel” of fragmented explanations, and Pfeffer (1993)
lamented that the discipline had no consensus on amongst scholars about what are the most significant research
issues. In this debate, it is important to come back to the study of relevant real world phenomena. For example,
McKelvey (1997) proposes a scientific realistic approach to the inquiry according to which scientific progress
stems from theory testing and falsification, as well as the inductive development of new theories (Churchman,
1971; Seth and Zinkhan, 1991) for phenomena not previously explained, and from the “abductive” (Peirce,
1992) expansion of the existing knowledge to include such phenomena (Hunt, 1991).
1 Starting from the commonly accepted view that social reality is different from the natural world, scholars mainly
positioned their theory-building and research efforts in positivist or post-positivist epistemology. Positivist claims were
rooted in the Western tradition of the old good science (Kuhn, 1970; Behling, 1980; Whitley, 1984), and held that
research methods in natural sciences would benefit management and organization science (Nodousani, 2000). The goal
of the scientific inquiry in management and organization science is to develop theory, articulate this in falsifiable
hypotheses (preferably defined using the language of mathematics and logic), and test them through observations (see
also Popper, 1959). At the center of positivism we find sophisticated experimental designs, careful sampling rules, and
precise measurements (Hempel, 1966). On the contrary, post-positivists reject this methodological realism (i.e. the idea
of a reality independent on the observer) and claim that the search for laws (or quasi-laws) for explaining social science
regularities needs to be replaced with methods of interpreting meaning by social scientists. As human societies are
characterized by different meanings, symbols, rules, norms, and values (Weber, 1968), management and organization
scholars need to “take a closer, richer, thicker, and more subjective view of organizational phenomena” (McKelvey,
1997, p.354; see also Lincoln, 1985; van Maanen, 1989).
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Fifth, phenomenon-based research also promises to overcome the relevance-rigor divide that has been much
debated in management and organization science (see Kharuna, 2007; Davies, 2006). Straub and Ang (2008)
suggest two causes for this divide. First, researchers have been unable or unwilling to transform academic
knowledge into actionable, pragmatic knowledge of use to practitioners. Second, a strong adherence to
established theories has made researchers inapt at uncovering problems of interest to practitioners, and take part
in development of solutions to those problems (Hambrick, 2007: 1346). Given publication policies that favor
theory development and -testing, there has not been sufficient level of incentives for academic researchers to
study “important or emerging phenomena that cannot be linked to the current theoretical frameworks” (Reynes,
2007: 1380; see also Raelin, 2007; Vermuelen, 2007). Notwithstanding that rewards for relevance are still
largely absent within the academic system, real-life phenomena and real-world organizations are those that rank
highest in the interest of practitioners. Already in 1993, Daft and Lewin observed that “the cataclysmic changes
occurring in the environment of organizations call for research that does not presume to test normal science
hypotheses” (Daft and Lewin, 1993: ii). In order to help managers to succeed in a continuing evolving and
complex world, the authors propose scholars should start searching for and investigating important phenomena.
Finally, phenomenon-based research allows to bridge disciplines through social integration. Phenomena attract
interest and bring together scholars with diverse training, inclination, agendas, and resource endowments
(Hambrick and Chen, 2008). With time, research groups may reach critical mass that allows them to acquire
shared identity, goals, and values (Merton and Storer, 1973) and to develop specific norms (Shapin, 1995;
Whitley, 1984) governing their membership and boundaries.
While the expectations may be high with respect to the outcome of phenomenon-based research, there is limited
systematic treatment of possible strategies for conducting this type of research at the same level we find it for
other unorthodox research strategies2. What characterize such strategies? Prior work has suggested researchers
need to formulate broad, open-ended research questions which have to be framed in “terms of the importance of
the phenomenon and of the lack of plausible existing theory” (Eisenhardt and Graebner, 2007, p. 26). Because
2 For example action research discussed in Carr and Kemmis (1986), McNiff and Whitehead (2006), or grounded theory,
Glaser and Strauss (1967), Corbin and Strauss (1990).
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the researcher has no knowledge of puzzling issues that may emerge from observations, a priori hypothesizing
of specific relationships among the variables should be avoided. Moreover, Edmondson and McManus (2007)
suggested qualitative approaches match topics for which little or no previous theory exists as they represent new
phenomena in the world (p. 1161). However, beyond this general advice there is room for systematic work on
research strategies for phenomenon-based research. In this paper, we aim to contribute to this work. We construe
phenomenon-based research as a pre-theoretical research strategy and develop a five-step framework for
conducting this type of research. We illustrate this with research on a prominent technological and social
phenomenon; open source software.
The paper is organized as follows. In the next section, we characterize phenomena and phenomenon-based
research in management and organization science and describe the main phases in the evolution of the scientific
community focusing on it. In the third section, we propose a pre-theoretical strategy for researching phenomena.
In the fourth section, we illustrate our research strategy on the phenomenon of open source software. Fifth, we
discuss implications and conclude the paper.
Characterizing phenomena and phenomenon-based research in management and organization
science
The Oxford English Dictionary of Current English presents a broad definition for common use: a. a particular
(kind of) fact, occurrence, or change as perceived through the senses or known intellectually; b. especially, a fact
or occurrence, the cause or explanation of which is in question.3 The last part of the definition suggests a
perceived fact, occurrence, or change which creates a tension within existing knowledge. This latter broad
understanding has evolved through centuries of work in philosophy, psychology, history, sociology, science
studies that have been concerned with the relationship between scientific knowledge and phenomena.
On the one hand, the emergence of new phenomena is a crucial occurrence in any science. As observed by
Herbert Simon, the real world is a generator of basic research problems (Simon, 1965, p. 5), while Auguste
Comte considered phenomena as starting points in the process of building scientific knowledge. In his view, the
3 The NASA Science Glossary defines a phenomenon as “a fact or event of scientific interest susceptible to scientific
description and explanation”, while the popular usage of the word often refers to an extraordinary event.
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word “phenomenon” refers to anything which may be a subject to observation; they are the facts (faits) which
occur and that a given science should explain (Comte, 1855). On the other hand, phenomena challenge common
believes within the scientific discourse, thus creating a tension with knowledge, which leads to multiple and
conflicting interpretations.
Phenomena have undoubtedly different features, depending on a specific scientific field. When passing from the
natural to the social sciences, phenomena would increase complexity and decrease generality (Hilbron, 1990). At
one side of the spectrum, Comte envisioned the simplest physical phenomena, such as the motion of a ball which
rolls down a hill before stopping at a certain point, whose explanation could be provided in mathematical
formula with general validity. At the other side of the spectrum, social phenomena are complex and less general
because human beings learn, modify behaviors, and create norms and rules for self-governance (Little, 1991).
A clear-cut distinction between social and natural elements of a phenomenon runs the risk of being misleading.
Specifically, phenomena in management and organization science have been defined as quasi-natural
(McKelvey, 1997: 353), having both a social and a natural dimension. They result from human intentionality and
natural causes independent of individual behaviors. Hence, in studying them scholars have to take into account
not only natural forces but also people's intentions, intuitions, and interactions observed at the levels of
individual, groups, organizations, industries, or society related to the shape, functioning, and processes of
organizations.
The social dimension of phenomena cause them to have two main specificities. First, phenomena in management
and organization science share an idiosyncratic (Lincoln, 1985), multi-causal (Reed and Hughes, 1992), and
chaotic nature (Forgues and Thiétart, 1995). As all the social phenomena, they reveal themselves with unique
characteristics. Scholars have been acknowledging for a long their (often extraordinary) complexity and
fundamental unpredictability. These elements make it impossible to apply a reductionistic approach as each
single element influences the whole system and must be understood in that way (Daft and Lewin, 1990, p. 3).
Second, phenomena in management and organization science are constructed, becoming apparent through
scholars reflections (Lewis, 2000) on complex, variable-rich, and changing aspects of the real world, which can
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be studied from multiple perspectives.
Phenomena in organization and management science pose challenges that impact the way in which scientific
inquiry about them can and should be conducted. Our central argument about why phenomena-based research is
pre-theoretical in our discipline is that research on a phenomenon is characterized by exploration into
complexity, ambiguity, and contradiction. At the outset, no research design appears as dominant. Scholars
should aim at reducing equivocality (Daft et al., 1987) emerging from the existence of multiple and conflicting
interpretations about an organizational questions to be asked and corrections to be made. Scholars cannot rely
on extant theories and the application of a theory-driven design, even if phenomenon-related, may result in
advancing the understanding of the established theory from the home discipline rather than phenomenon under
study (Cheng, 2007: 28). In the presence of novel phenomena, the traditional hypothesis-testing strategy fails to
generate new knowledge about the phenomenon. Hence, such a strategy may be given up in favor of the
formulation of open-ended research questions (Daft, 1987) to be answered through the definition of new
concepts and new variables representing them. This often implies turning to a mix of research methods, which
Daft and Lewin (1990 p. 6) suggest depart from conventional approaches4.
The product of inquiry into phenomena is far from being formal theory (Blau, 1990) rather it is its prerequisite.
Whereas scholars in management and organization science are getting increasingly aware of the prominent role
held by novel phenomena in advancing scientific progress in the field, there is limited discussion of the merits of
phenomenon-based research and on the proper ways of conducting it. A first step in this direction is to go in
depth in the characterization of a phenomenon, whereby, as suggested by Stephen Cole (1992) progress in
scientific knowledge should always be examined against the interest, work, and organizations of scientists who
create this knowledge.
The co-evolution of a phenomenon and its scientific community
A phenomenon can be more or less significant in the eyes of the beholder. Yet, it is difficult to identify objective
4 For instance the authors suggest to examine outliers rather than central tendencies, claiming that the average
organization does not exist.
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or reliable criteria for how to judge significance. In the field of management and organization science, industry
representatives, experts, commentators, and observers often gauge phenomena to the extent that they impact on
the status quo of firms, markets, industries, economies, and society at large. Thus, significance can refer to the
impact of a phenomenon on the latter objects or units of analysis, and can be assumed by questions such as: does
the phenomenon change ways in which goods and services are produced and exchanged within the markets and
industries? Does it enable the use of new technologies or alter existing technology? Does the phenomenon lead
to new institutions or change existing institutions in society, affecting firms, universities, or government
agencies and challenging explicit and implicit social and legal norms (Hodgson, 2006)? Does the phenomenon
impact on the society as a whole by making individuals' everyday life better or worse, for example allowing
them to access a range of goods and services at different prices or to interact among each others in different
manners? Typically, the extent to which a phenomenon is deemed significant by an observer will depend on the
extent to which it has evolved to affect many people, groups, and institutions.
The perceived significance strictly depends on the stage of the evolution of the phenomenon. We identify four
stages in the evolution of a phenomenon. As we acknowledged earlier, a community of scholars constructs the
scientific phenomenon and generates knowledge about it. By definition, the phenomenon and the community of
scholars as observers co-evolve. In the following, we discuss the stages of the evolution with respect to the
observation (a novel phenomenon) and the observers (the scholarly community).
First, in an embryonic state, a novel phenomenon can hardly be singled out against a background of other known
phenomena and states of the world. Yet, individuals and groups display behaviors that, if continued or reinforced
could become significant for our understanding of organizations. Possibly, the phenomenon may be path
dependent whereby early events, actions, or decisions may shape its subsequent evolution (Arthur, 1989).
At this embryonic stage, if the impact of the phenomenon is deemed relevant, a small group of scholars may
develop an interest in understanding it5 and report on it, even if the initial curiosity may be restrained by strategic
considerations. Choosing research problems can be likened to an investment process (Bourdieu, 1988): scientists
5 However, this is not always so. Hamel and Prahalad (1994) suggested the scholarly community is too preoccupied by
theory and research methods, and forget to identify and research emerging and significant phenomena.
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can invest their knowledge, experience, time and effort in different research directions and focusing on not yet
explored topics is a risky strategy.
On the one hand, the likelihood of success for scientists focusing on new phenomena may be low. First, it may
be difficult to obtain funding, as, in general, funding agencies tend to reward proposals built on normal science
rather than on new phenomena (Campanario and Maritin, 2004, p. 422). Second, scientists may perceive the
difficulties of publishing in mainstream journals. Notwithstanding that top tier journals in management and
organization have reaffirmed the need to open our field to new ideas (Daft and Lewin, 2008, p. 177); journal
reviewing may sometimes be biased against controversial or novel findings, while articles that agree received
wisdom are more likely to be accepted that those that challenge dominant belief (Pfeffer, 2007: 1337). Third,
those who focus on new phenomena run the risk of remaining isolated within their referring community.
Isolation is highly disadvantageous as science is becoming more and more a social enterprise (Penrose and Katz,
2004), where scientific collaborations play a crucial role (Hackett, 2005)
On the other hand, if the idea pans out the returns can be huge. Scientists experience a trade-off in the choice of
the topics to be investigated. A conservative research strategy would be to pursue small, incremental innovations
on established bodies of knowledge, with a high likelihood of success but a modest return on investment in term
of visibility. However, the puzzling character of a new phenomenon, which can not be adequately addressed by
extant knowledge may boost the motivations of scientists – first of all their pursuit of peer recognition (David,
2008) - thus favoring their early engagement. An early engagement may be a prerequisite of successful research
paths. For researchers it may be important to detect significant phenomena in their embryonic or early growth
phases. The benefits of early detection are improved observations of antecedents of the phenomenon, and the
opportunity to capture unfolding characteristics.
In the embryonic state, efforts are uncoordinated and often duplicated (Gilbert, 1977, p.276), while a crucial
element of this phase is the development of a new language and a terminology through which scholars can
express and exchange their ideas. Language contributes to the social construction of the aspects of the reality to
be investigated (Astley, 1985; Grace, 1987). Common language provides the basis for the emergence of a
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distinctive identity shared by the members of a scientific community (Nag et al. 2007, p. 938).
Second, in a growing state, the phenomenon becomes visible to a larger academic community and more distinct.
It “solidifies”, which means that uncertainty as to the state of regularities decrease in facts or occurrences at the
levels of individual, groups, organizations, industries, or society related to the shape, functioning, and processes
of organizations. In addition, facts and occurrences become increasingly intertwined, increasing the complexity
of the phenomenon. The cause or explanation of the facts and occurrences are being called into question. The
discrepancy of the phenomenon and scientific knowledge prompts the interest of a growing number of scholars
who multiply their attempts to capture aspects of the phenomenon using a variety of research designs and
methods and gauging the emerging phenomenon against existing and novel theoretical frameworks and concepts.
The small circle of interested scholars evolves into an informal scientific community, that is in a group of
scholars who identify themselves as such and who interact and are familiar with each others' works (Cole, 1983,
p. 130). Kuhn (1970 p.) acknowledges that informal community may form around a theory, a phenomenon, a
class of problems. However, while in Kuhn's view, members of a scientific community have undergone similar
educations and professional initiation (Kuhn, 1970, p. 177), in case of phenomenon-based research the multiple
facets of the investigation and their interdisciplinary nature tend to attract scientists with different training. A
crucial element which characterizes the scholarly community at this stage is the increasing intensity of the
communication among its members. Namely, the informal community takes the form of an “invisible college” 6,
a set of informal communication relations among scholars or researchers who share a specific common interest
or goals (Lievrouw,1990, p. 66).
Third, in a mature state, the phenomenon has reached a level of solidity where regularities encountered in the
6 The term was originally coined by Price (1963). The idea of invisible college stems from development of the
natural sciences in 17th century Europe, where scholars were mainly exchanging problems, methodological
remarks, and findings through letters. The invisible college was a precursor to the scientific journals which
allowed for more efficient interaction among scientists. In Price's (1963) understanding, the invisible college
refers to transfer of thought, expertise, and technical capabilities without designated facilities and institutional
authority. It can be applied to uncertain research projects which have yet to materialize in concrete results.
Typically on- and offline mailing lists, working paper repositories, social networks, or apprenticeship allows
for increasing membership in the college. Its members interact, exchange information, and monitor progress
in their field cooperating across national and institutional borders for the purpose of intellectual advancement
(Crane, 1972; Verspagen and Werker, 2003).
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previous phase become predictable. Thus, classes of regularities emerge, as being distinct from each other. Such
classes make the phenomenon appear more multifaceted and richer. The market for ideas (Sent, 1999) enters the
boundaries of the phenomenon. Scholars become aware that some aspects are more challenging and deserve
more attentions and prompt an increasing variety of research designs, methods, and explanations. At the same
time, the invisible college starts to become visible (Zuccala, 2006). Scientists investigating the phenomenon
acquire tenured positions in departments of major universities (Stinchcombe, 1994), thus being grouped together
within defined spatial boundaries. They succeed in regularly procuring financial support (White et al., 2004)
through successful grant bidding and in setting up new organizational forms in term of associations, conferences,
journals (Sarafoglou and Paelinck, 2008), and Ph.D. programs.
Fourth, in a declining state, the phenomenon looses its coherency, facts and occurrences become less regular and
thus less predictable. To the observer, the phenomenon gradually merges with the background of other known,
scientific phenomena, disciplinary bodies of knowledge, and methodological schools. The decline may result
from the interplay of two tendencies. On the one hand, as the complexity of the phenomenon increases its
multifaceted characteristics may lead to the emergence of competing regularities. On the other hand, phenomena
in management and organization science also “vanish” in the sense that their significance to organizations
wanes, or that their occurrences and practices become an integral and normal part of the functioning of
organizations.
In the former case, competing notions, interests, and research agendas do come into the limelight. Strong
regularities emerge that can be seen as new phenomena in embryonic states. Some scientists may find that their
research is revealing unexplored problems and start to investigate them making contested observations and using
different research designs and methods. This brings us back to the first phase for another new phenomenon
(Gilbert, 1977, p. 276). The core underpinnings are progressively lost, scholars are driven on divergent paths of
inquiry, and the research on the phenomenon looses its unit and distinctiveness. The visible college tends to
break up, even if research areas, once established, take a long time to die and a small rear guard (may) remain
which carries on the research tradition long after the main focus of interest has moved elsewhere (Gilbert, p.
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276).
In the latter case, there is a strong overlap between facts, occurrences, and scientific knowledge. The
phenomenon integrates with the body of new and extant scientific knowledge and looses its challenging nature to
become one of the many others (Gilbert, 1977, p. 275), so that scientists tend to move to more promising areas.
Furthermore, the social practices and occurrences that gave rise to scientific inquiry in the embryonic stage cease
to surprise scientists and management practitioners and become a normal part of a functioning organization.
So far we have outlined the evolutionary stages of a phenomenon-based on its underlying social dynamics, and
we proposed the evolution of the phenomenon can be intertwined with the development of a community of
scholars which focuses on it and co-evolve with from an invisible to a visible college. Next we turn to a research
strategy for phenomenon-based research and illustrate it through the case of research in open source software.
A strategy for phenomena-based research
In the following we propose a framework that aims at guiding scholars to conduct phenomenon-based research.
The framework deviates from the mainstream way knowledge is built in our discipline, starting with theory
formulation, proceeding with model development and model implementation, - testing, -analysis, and
identification of implications and open issues. Before such normal science can commence, a challenge of
phenomenon-based research is to distinguish phenomena or “give them an identity” that make them stand our
from other facts and occurrences. The framework should be understood as a set of activities that proceed in a
circular manner.
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Figure 1: Phenomenon-based research strategy
1. Distinguishing
As pointed out by Ludwig Wittgenstein (Philosophical investigations) there is a difference between a concept
(e.g. the process of thinking) and a phenomenon (e.g. thought), whereby the former may be instrumental for
understanding the latter. Thus, the first activity of phenomenon-based research consists in giving the
phenomenon an identity, by distinguishing it from its background. Researchers engage in a differentiation
process by revealing the peculiarities and distinctive characteristics of the phenomenon (Merton, 1973). They
place bracket around the phenomenon and these conceptual boundaries allow them to distinguish what belongs
to the phenomenon and what does not. Actors typically define phenomena by explaining what it is not (Lewis,
2000, p. 762).
Developing various concepts and choosing amongst them creates distinction and constitutes a key part of
phenomenon-based research. As researchers start to gather data about the phenomenon, they may also change
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the concepts that allow them to make those distinctions. The amended concepts in turn guide the search for new
data. Conceptualizing is done in order to allow for exploration of the phenomenon. Concepts should be
understood as a filter through which data are selected (Bettis and Prahalad, 1995). However, a filter may not fit
to the data emerging on the phenomenon, and existing concepts need to be rejected, stretched, or new concepts
developed. As a vehicle for distinguishing phenomena, concepts thus change in two directions. First, they may
become more granular and diverse as research progresses through data gathering. Second, they may expand or
contract depending on what data the researcher exposes them to. Concepts need to pay “respect” to the
phenomenon, rather than be concomitant to theory. Their purpose is to help research filter data for a description
of the phenomenon.
2. Exploring
Distinguishing and exploring are intertwined processes. Once distinguished and described through concepts, the
phenomenon can be further explored by the researcher. This starts with intensifying the gathering of data that
may fall within or outside the concepts chosen to describe it. The latter set of data is important because it also
shows the limits of the concept as well as the phenomenon. Exploration best proceeds through relatively
unrestricted gathering of primary data on the phenomenon, for example through interviews, as well as secondary
data, for example through news reports or online sources. In grounded theory, scholars have proposed data
gathering should continue until theoretical saturation has been achieved (Glaser and Strauss, 1967). This is when
marginal benefits of gathering additional data rapidly decline because the analysis tends to confirm working
constructs or emerging theoretical links. However, exploration in our research strategy is different. The purpose
is to create a concept that serves as an efficient filter for data. A critical question for choosing whether or not to
continue with data gathering refer to the fact that the concept allows researchers to capture insights about the
phenomenon by distinguishing relevant from non relevant data. Moreover, is data filtered out telling about the
limits of the phenomenon? Finally, should the concept be stretched so as to include new data
3. Designing
Activities 1 and 2 lead to new concepts, new data, information, and interpretations. Thus, as understanding is
16
gradually gained about the phenomenon, the researcher may recognize a need for new research designs. In a
framework of a classical, deductive research strategy designs would follow theory formulation. However, given
the emergent nature of the phenomenon and the data, a research design evolves from attempting to answer a
broad question, “what is the nature of this phenomenon?” to “how can this phenomenon best be researched?” At
this stage, the researcher may not pursue an ambition to build theory but rather report on the phenomenon. The
type of data gathered as well as the concepts indicate what alternative research designs can be useful to study the
phenomenon. For example, phenomena may produce a host of qualitative or quantitative data. The concepts may
indicate that qualitative data may be more important for understanding the phenomenon in the early phases of
research. Or, quantitative data may be useful to generate internal validity for a new observation and triangulate
findings based on qualitative data. Accordingly, concepts may need to be “stretched” or replaced in order to
cover both qualitative and quantitative data. Furthermore, there might be a need to gather cross-sectional data or
longitudinal data providing concepts with some filtering capability that changes over time.
In phenomenon-based research, because research designs initially are not guided by pre-given or inductive
theory, and since the phenomenon under study is evolving, research designs may be opportunistic. This is so
because aspects of the phenomenon may only be studied at one particular point in time. Opportunist research
designs provide unprecedented insights into the phenomenon and the dynamics of the social practice. However,
such designs may also limit the depth and scope of the data gathered, as well as the extent to which the concepts
that describe the phenomenon can actively work as a filter. Opportunistic designs are important in the
advancement of scientific knowledge on the phenomenon because they reveal insights about how the
phenomenon can best be researched. Therefore, accompanying work that reviews and evaluates research designs
on the phenomenon (alongside substantial contributions on the evolving theory) is imperative for the rapid
advancement of the field, even more so than in traditional hypothesis testing.
4. Theorizing
In this paper we proposed that phenomenon-based research is a pre-theoretical research strategy. Thus, the new
research designs that evolve to capture the phenomenon provide increasingly rich understanding of its nature.
17
Thus, with time, scholars can also come to judge the extent to which the phenomenon overlaps or deviates from
existing theory. Since the phenomenon and scientific knowledge co-evolves as discussed above, scholars will be
able to theorize along three paths: 1) use existing theory to predict the phenomenon, 2) adapt, modify existing
theory or create new theory through combination of existing theories to predict the phenomenon, 3) where 1) and
2) fail, inductively generate new theory. While this work may include inductive theorizing as described by
Glaser and Strauss (??), there are two areas of marked difference. First, a phenomenon-based research considers
both inductive and deductive theorizing as viable approaches to predict occurrences based on the facts that
constitute the phenomenon. Second, phenomena-driven research advocates an overlap and interaction between
designing research and theorizing. Because phenomena evolve, research designs need to be adapted alongside
theory development. Thus, a research design does not produce a grounded theory per se. Rather, the unfolding
theory in itself may require a new research design to capture the phenomenon. This iteration between design and
theorizing is one reason why phenomena-driven research should be considered pre-theoretical.
It should be noted that the iterations between designing and theorizing may be numerous, until a match has been
achieved between the phenomenon and the scientific knowledge about it. Thus, the type of research advocated
by the LRP editors requires considerable patience before quality can be judged on the basis of standard scientific
criteria (e.g. goodness of fit, reliability, validity). This is a challenge in so far as urgency often leads to
opportunistic research designs intended to do “real-time” capturing. In fact, the phenomenon may quickly “out
pace” theory and research designs, making phenomenon-based research a risky strategy. The research strategy
also calls for considerable reflection on where the evolving theory and research on the phenomenon is heading.
We refer to this as “synthesizing” which we discuss next.
5. Synthesizing
With time, as the phenomenon evolves, gains significance, and attracts interest, there is considerable scope for
work that takes stock of and reflects on the increasing amount of academic research output. This involves
analyzing various contributions including their strengths and weaknesses, but also using the emerging work for
synthesis. Such a synthesis is a prerequisite in order to guide future research on the phenomenon. Synthesis
18
decreases the risk of numerous scattered contributions inattentive to each other, leading to slow theoretical
progress, fragmented insights, or the repetition of flawed research designs across studies. As part of the research
strategy, synthesis is also important for assessing whether or not continued research on the phenomenon is
warranted, for example, judging whether or not the phenomenon is gradually maturing or rapidly declining. Such
work will also need to assess whether or not new theorizing and designing make substantial or rather marginal
contributions to the understanding of the phenomenon.
A difficult part of synthesizing is for researchers to remain theory- and design-neutral. Neutrality is important
because synthesizing aims to garner insights about the phenomenon as a whole, rather than separate,
compartmentalized units, including facts or concepts. Synthesizing aims at forging new links between theorizing
and research designs and may lead to counter-intuitive propositions. In this sense, synthesizing may even break
with principles of good “theory development” such as consistency and sensitivity to theoretical or
methodological assumptions.
In our view, pre-theoretical research is very much aimed at producing scientific knowledge and a research
practice that enables researchers to think, talk, and write about a phenomenon. Being able to approach a
phenomenon in such a systematic way enables researchers to propose and select theories, and conduct research
using various types of methods. Thus, synthesis is absolutely essential in achieving the level of understanding of
a phenomenon around which an “invisible college” can be formed and a social practice of research can evolve.
Thus, phenomenon-based research is creating a kind of “discursive commitment”, namely a system of social
practices in which something can be treated or taken as an assertion (Brandom, 1994, p. 157) .
The phenomenon of open source software
Over the last years, OSS has become a significant economic and social phenomenon. The demand for OSS
solutions is increasing very fast, with more and more users running open programs on their systems. There is
compelling evidence that open source has a significant share of many markets: the open source Web server
19
Apache7 has been dominating the public Internet since April 1996, the Linux operating system is rapidly
catching up in the server segment and quickly growing on the client segment, the open source program Sendmail
is the leading provider of reliable and secure email and messaging infrastructures, while Microsoft Internet
Explorer has been losing market share to the open source Web browser Mozilla Firefox since mid 2004.
Open source projects are growing in both number of contributors and in project size (Wheeler, 2007). As in
October 2008, the kernel of Linux operating systems has surpassed the 10 million Lines of Codes8. A large-scale
survey conducted on more than 900 Small and Medium Enterprises in the software sector in 5 European
countries (Finland, Germany, Italy, Portugal, and Spain)9 has shown that about one third of the respondents
chose a business model partially or entirely based on the provision of open solutions. At the same time, many
governments, especially in developing countries, are adopting policies to promote the adoption and the diffusion
of open source software (Lee, 2005; von Reijswoud and Topi, 2003).
After briefly introducing the history of the open source movement as a scientific phenomenon, we illustrate the
application of phenomenon-based research strategies on the phenomenon of open source software.
A history of the scientific phenomenon of open source software
The evolution of the Open Source Software (OSS) movement (see Benussi, 2006, for a comprehensive
treatment) created facts and occurrences that warranted scientific exploration and the creation of a phenomenon
by a scholarly community, however, long after the movement took shape more than 30 years ago. The first who
wrote on the phenomenon (e. g. Richard Stallman, Eric Raymond, Bruce Perens, and others: see DiBona and
Ockman, 1999) were computer scientists who were the founding fathers of the movement, and hence, had been
actively participating in it since its very inception. The first authors identified the phenomenon as worthy of
scientific inquiry and defined terms to be adopted from the field. They included terms such as “hacker culture”,
open standards, open development, or Open Source business. Differentiating the software categories was part of
7 As in October 2008, according to Netcraft's statistics on Web servers, Apache had 50.43% of the market, while
Microsoft had 34.44%. http://news.netcraft.com/archives/web_server_survey.html, accessed
8 http://linux.slashdot.org/article.pl?sid=08/10/22/1713241&from=rss, accessed on December 12th 2008.
9 The survey was carried out within the CIPR project of the PRIME Network of Excellence (http://www.prime-noe.org/).
See Colombo et al. (2009) for further details.
20
the early identification process: free software, open source software, libre software, and other types of software
protected by various forms of licenses gave rise to complementary or even competing interpretations. For these
categories a proper terminology was developed.
Economists puzzled by the voluntary contributions to a public good started with cost-benefit analysis and
predictions from existing theories (Lerner and Tirole, 2002) which only partly accounted for the multifaceted
aspects of the phenomenon. Researchers became aware that the extant body of knowledge was inadequate for
properly addressing the issue of voluntary contributions, especially if a narrow disciplinary lens would have
been adopted (Reynes, 2007). Intrinsic motivations of altruism and sense of community belonging had been
widely documented in the sociological literature on collective action processes (Hardin, 1982), but had not been
applied to the analysis of the collaborative production of complex goods. Furthermore, the phenomenon deviated
sharply from established theories and findings on innovation in many fields, including management and
organization theory. Von Hippel and von Krogh (2003) observed that innovation in OSS could neither be
explained by a traditional private-investment model of innovation incentives nor by the collective innovation
approach. The authors elaborated the private-collective model of innovation that contained elements of both the
private investment and the collective action model (p. 209).
The forming of an “invisible college” marked the growth state of the scientific phenomenon. A (less and less)
invisible college pursued a research agenda on OSS over the last ten years and created a deep understanding of
the phenomenon. Theorizing had been favoured by the development of several institutional arrangements that
support the discussions among the scholars and have helped the invisible college to become more and more
visible. First, in 2000, an Internet platform was set up by Eric von Hippel and Karim Lakhani at the MIT Sloan
School of Management10 where interested scholars could register themselves, publish their papers (also in the
form of work in progress), discuss about their projects, and make announcements of importance. As in
December 12th 2008, the platform featured two very active mailing lists and counted 320 contributions from
more than 350 authors.
10 http://opensource.mit.edu.
21
Second, a number of special conferences and workshops were organized and repeated11, while tracks devoted to
the open source phenomenon were organized are repeated within important management and organization
conferences, such as Academy of Management, Strategic Management Society, HICCS, INFORMS, DRUID, or
EURAM. Third, as in 2001, special issues on open source related topics started to be published by high impact
factor journals in the management, such as Information System Journal (2001 and 2002), Research Policy
(2003), Management Science (2006), Journal of Management and Governance, Information Economics and
Policy (2008). They served as vehicles for scholars to communicate about their research to other scholars in their
respective fields. These channels stimulated theory development and testing theories using a wide variety of
research designs and methods.
Current research explores several new and challenging avenues which progressively branch out as new and
interrelated regularities emerge and pose challenges for all of the five research strategies outlined above. Firms
entering the OSS arena find themselves confronted with an unconventional intellectual property rights regime,
designed for fostering instead of preventing the access to relevant information. A plethora of taxonomies of open
source business models have been proposed (see, among the others, Hemphill, 2006; Krishnamurthy, 2002;
Nosko et al., 2004; West, 2007), whilst the question of their long term sustainability is still under-explored
(Chang and Newhouse, 2007). Research about open source entrepreneurship is still in its infancy but it is
attracting increasing attention (Dahlander and Magnuss, 2005; Gruber and Henkel, 2006; Alexy, 2008) as
scholars are getting aware that the economics and innovation performance of open source firms deserve more
attention (Dahlander, 2007).
Phenomenon-based research strategies applied to research on open source software
In the following, we illustrate the set of activities of phenomenon-based research in the case of open source
software, relating it to the development of the scientific community doing research on the phenomenon at the
various stages of its evolution. Table 1 classifies salient phenomenon-based research on OSS. The table shows
phenomenon-based research strategies in a complex field of multiple disciplines and methods. Table 1 maps the
11 The first edition of the International Conference on Open Source Systems was held in Genoa (Italy) in 2005 and
repeated in Como (Italy) in 2006, in Limerick (Ireland) in 2007, and in Milan (Italy) in 2008.
22
work of scholars who employed a phenomenon-based research strategy and perceived the phenomenon in a
specific stage of its evolution.
Table 1: Phenomenon-based research strategies on open source software
The evolution of the scientific knowledge on a phenomenon can be traced along four stages: embryonic, growth,
mature, and decline. We defined the phenomenon as an observed fact or occurrence and specified five research
strategies conducive to identifying and understanding the phenomenon in order for theory building and testing to
proceed. The OSS movement offers a recent and prominent example for a phenomenon in management and
organization science. The purpose of linking the evolutionary stages with the research strategies is twofold. First,
23
we substantiate the research strategies with specific examples of successful research projects and, second, the
resulting matrix may be used as a template for building a research agenda for other phenomena.
Whereas the evolutionary stages are by definition sequential, the research strategies are not, at least not strictly.
Iterations between the research strategies help formulate new research questions and promote an understanding
of the phenomenon beyond the discipline or method currently applied. For this reason, one research team or one
agenda may carry out projects that aim at exploring after theorizing, or distinguish new concepts after having
synthesized prior work. Analogously, different scholars will perceive a phenomenon as embryonic whereas their
colleagues may speak of it as mature or declining. The stages of the phenomenon represent collective action by
the invisible college and are subject to framing (Hargrave and Van de Ven, 2006). Combining the stages and the
strategies into a matrix risks to gloss over the subtleties of varying research agendas and influential
developments in the field. However, the combination also yields an understanding regarding the direction of the
discourse within the community: depicted as an arrow in Table 1. Likely, exploratory work will dominate as
long as a majority of the scholars perceive the phenomenon to be in its embryonic stage. Synthetic work may
follow later and find more readers when scholars agree that a body of research on the phenomenon deserves to
be summarized and evaluated.
In the following, we briefly highlight exemplary work on the phenomenon in order of the research strategies
employed.
1. Distinguishing
First, distinguishing research set out to describe the phenomenon against a background of software development
practice known from firms (Raymond, 2000; Stallman, 2002; Himanen, 2001). Novel work on innovation theory
identified OSS as a model of innovation featuring a new combination of costs and benefits to contributors (von
Hippel and von Krogh, 2003). The authors perceived the phenomenon as growing and predicted far-reaching
implications for organization science. Distinguishing new concepts in a mature phenomenon required either the
concept to be particularly difficult to grasp or a sufficient understanding of the organizational structures and
routines within OSS communities. Shah (2006) analyzed the effect of governance structures in OSS
24
communities and O'Mahony and Ferraro (2007) identified emerging governance in Debian GNU Linux.
Equipped with years of research on the phenomenon by themselves and by the community of scholars, these
authors were able to build on a number of relevant concepts in their research design: communication routines in
OSS, code production and distribution, motivation of developers, just to name a few. Distinguishing work on a
declining phenomenon may appear to be a contradiction in terms. However, the transfer of well-understood
concepts to new empirical studies may link the phenomenon to emerging new phenomena, as discussed above.
Raasch et al., (2008) build on the concepts of free revealing (Harhoff et al., 2003) and develop the idea of open
source innovation by exploring the model applicability in domains outside software.
2. Exploring
As distinction proceeds and new scholars entered to investigate the phenomena, new metrics evolved whereby
the phenomenon could be more accurately or adequately observed. New measures, survey questions, frameworks
of reference, and observations deemed salient sharpened the definition of what is part of the phenomenon and
what is not.
For example, scholars studying motivations to engage in open source activities need indicators to capture the
efforts of participants in open source projects. Initially, effort was captured through the concept of number of
mails sent to a mailing list and as well the number of lines of code written (Koch and Schneider, 2000).
However, while these measures indicate level of effort, the more fine grained concepts filter the data
distinguishing, for example, between developers (code contributions) and other participants (lurkers, mailing list
participants, see for instance Nonneke and Preece, 2000; Spaeth et al., 2008). However, the fine-grained
concepts also filtered out contributions of real importance to the design of the technology. Lines of code have the
weakness that while some developers write highly efficient software with few lines of code that solve complex
tasks, other developers might need more lines of code to solve the same task. Moreover, some parts of a design
might be more important than others in getting the software to work. A number of authors (von Krogh et al.,
2003; Dalle and David, 2004; Baldwin and Clark, 2006) introduced measures of software architecture for OSS,
in which more or less important components in the designs were identified, and contributors' efforts could be
25
assigned to these components. West (2003) studied the software architecture of a number of large hardware and
software companies in order to understand the application of open source software as part of hybrid platform
strategies.
Treating OSS as a mature phenomenon, later works describe complex psychological measures, ranking order of
developers, and their degree of development efforts in a project (Robert et al. 2006). Exploration efforts
contributed to intensify communication among scholars. The FLOSSMetric project (Gonzalez-Barahona, 2009)
aimed at collecting and sharing data on software production within OSS projects and, thus, provided institutional
support for the gathering of data for examining problems specific to applications for industry. The project
published detailed practices for the adoption of OSS by small and medium sized firms 12. Their specific goal of
enabling industrial exploitation of research findings on OSS points to first signs of a stage of decline of the
scientific phenomenon because the initiators assumed general interest among practitioners and an integration of
OSS specific results in organizational and managerial routines.
3. Designing
In capturing the phenomenon of open source software, a huge variety of research designs have been developed,
which were often based on original and highly specific sources of data. OSS development usually relies on
computer-mediated communication and online repositories and produces in itself a large amount of data. With
code publicly available and software development transparent to external observers, researchers extracted
technical data from the code base of projects hosted on online repositories as well as from project mailing lists
used by developers to coordinate their efforts. This represents a distinguishing feature of the OSS phenomenon,
which has been heavily exploited in many studies (Koch, 2008 and Den Besten et al., 2008) and, as scientific
knowledge about the phenomenon grew, allowed for the use of advanced modeling techniques, as econometric
models on large samples (Giuri et al., 2008) or social network analysis (Oh and Jeon, 2007; Kuk, 2006).
Research on OSS developers and projects has adopted opportunistic designs when portraying the phenomenon in
its embryonic stage. Lakhani and von Hippel's (2003) work showed people's motives for contributing, sometimes
12 See URL: http://guide.flossmetrics.org/index.php/5._Best_practices_for_FLOSS_adoption
26
even anonymously, and helping beginners in the Apache project. This work was not rooted in research designs
for motivational psychology (e.g. inventory of items in questionnaire not used in prior work) but it revealed
insights about the phenomenon. Aware of the growing interest in the phenomenon by a global community of
scholars, researchers around George Madey at Notre Dame succeeded at providing access to the Sourceforge
database for academic purposes (van Antwerp and Madey, 2008). Access to developer and project
demographics, such as project maturity, prompted new research designs and supported theory development
(Comino et al.,2007).
The adoption of open source software by firms contributed to widening the space of appropriate research designs
and sample strategies applied by economics and management scholars, who often borrowed them from other
disciplines. Examining the application of OSS in business models of software firms on a large sample
(Bonaccorsi et al, 2006) marked the shift from a mature to a declining perception of the phenomenon because the
large population of firms represented and identified a normal practice in the Italian software industry.
4. Theorizing
Theorizing occurs in close iteration with new research designs which explains why phenomenon-driven research
is essentially pre-theoretical. Not surprisingly, we should observe multiple approaches to theorizing: abductive,
deductive, inductive, and theory integration and combination. Earlier stages of the phenomenon tend to see more
single cases studies, abductive and inductive work, whereas during later stages researchers start to theorize
deductively, using multiple cases and larger samples to test theoretical concepts that have been used to generate
data in earlier stages. The concepts remain pre-theoretical in that they usually cannot claim generality in
organization and management science. This may explain why we do not see theorizing work yet that perceives
the phenomenon as declining. A declining stage agenda understands that OSS is well integrated with regular
organizational structures and routines and we should anticipate research that draws general conclusions for
management and organization science. Theorizing and synthesizing strategies for a declining phenomenon seize
to be pre-theoretical and start to build theory of wider applicability to organization science.
Among the earlier contributions to the phenomenon in its embryonic stage, Lerner and Tirole (2002) postulated
27
an economic model to explain contributions to OSS. Their argument built on economic reasoning and less on
empirical observation. The authors transferred a set of assumptions about the rationale of OSS developers from
economic theory and, thus, theorized abductively. Hertel et al (2003), contributing to the phenomenon in its
growth stage, combined two theories, Klandermann's resource mobilization model and and the VIST model to
explain motivations to contribute to open source software. Rooted in the private-collective framework, Ulhoi
(2004) combines the model of private agency with that of collective agency to address innovations based on
open source or non proprietary knowledge.
Shah (2006) developed theory inductively showing that developers' motivations evolve differently in gated and
open source projects. An inductive approach is particularly apt for examining phenomena that are emergent and
poorly understood. This was explicitly claimed by O'Mahony and Ferraro (2007, p. 1083). However, these
authors built on insights about the phenomenon from earlier work and could hence refine their research questions
with concepts such as varying community types or communication behavior. A deductive approach was used by
Haefliger et al. (2008) to examine predictions from the software reuse literature in the context of OSS. All of
these authors understood the phenomenon as mature as they learned from earlier research designs and applied
established (pre-theoretical) concepts in their research.
5. Synthesizing
Synthesizing appears as a pre-mature research strategy for a phenomenon in its embryonic stage. In the growth
stage, a number of introductions to journal special issues took stock of what had been published on the
phenomenon both to help guide future research. Von Hippel and von Krogh (2003b) stress the novelty of the
phenomenon, acknowledging that it poses novel and fundamental questions for researchers in many fields (p.
1149). In 2006, the authors acknowledge the significance of the phenomenon for students and practitioners in
many fields (von Hippel and von Krogh, 2006: 975) and, contributing to the distinguishing process, categorize
the research on it into three areas: motivations of open source software contributors; governance, organization,
and the process of innovation in open source software projects; and competitive dynamics enforced by open
source software. Finally, the recent special issue of Information Economics and Policy contributes to the debate
28
of exploring and designing strategies addressing specifically the empirics of open source software.
There were also a number of edited and authored books that reviewed prior works and proposed a future research
agenda. For instance Feller et al. (2006) edited a more than 500-pages book on OSS with the aim of shedding
light on the multiple aspects of the phenomenon and offering something to everyone interested in it (p. 12).
Fogel (2006) focuses on the open source development process in order to provide useful insights to companies
wishing to successfully run their open source project.
Implications and conclusion
The target of phenomenon-based research is to capture a phenomenon so that theoretical work and development
of research designs can proceed. Yet, this is a much forgotten step in management and organization science.
While our discipline started out here, many authors claim we have become theory-driven and thus tend to forget
how to admire a phenomenon in its totality.
Flyvbjerg (2001) asks what it takes to make social science matter. In analyzing the progress between the natural
sciences and social sciences, he laments that natural sciences have progressed faster, achieved more results of
significance to humankind, and have a stronger legitimacy amongst many scholars. Clearly, Flyvbjerg's work is
important in that it asks of social scientists to reflect on our fields achievements. Phenomenon-based research
can never replace but rather should complement theory generation and testing as a pre-theoretical research
strategy. In relentlessly pursuing an improved understanding of an evolving phenomenon, insights matter more
than the choice between quantitative or qualitative methods. Moreover, scholars struggling with specific research
problems can find their possible solutions in the study of new phenomenon, rather than solely in studying
existing fields. Thus, in spite of working on a different problem, they may gain benefits from exchanging
knowledge on the phenomenon of common interest.
Future works need to address when a phenomenon is “ripe enough” for research. Committing to researching an
embryonic or growing phenomenon represents a high risk, in particular since researchers are unclear about the
sustainability of the phenomenon. However, engaging early in such work may also produce extensive returns on
any research project. Embarking on open source software research in 2000 was clearly risky. However, the
29
phenomenon had an unusual transparency of data and, as it evolved, it also showed theoretical tensions that
created new insights into many research problems in several fields.
Returning to the promises outlined in the introduction, we can summarize the following. First, a debate in
management and organization science has been whether or not the field should embrace pluralism in paradigms,
manifested by many complementary and/or competing theories and methods (van Maanen, Pfeffer). The call for
more phenomenon-based research implies pluralism in paradigms. This is so because scientific knowledge will
develop in close relation with the phenomenon. Thus when discovery of phenomena flourish, so will theory. By
experimenting with pre-theoretical concepts, phenomenon-based research strategies implement a pragmatic
approach to scientific inquiry. The creation of a scientific phenomenon, its representation in various stages of
development, and the iterations between research strategies unite scholars in the search for better data, more apt
filters of data (concepts), and innovative research designs that may cut across epistemological divides.
Further, when discovery of phenomena flourish, so will research designs. We have argued in this paper that
innovation in research designs might be needed in order to make phenomena researchable. The implications of
this argument are not trivial; researchers may need to draw upon methods from adjacent fields and disciplines in
their design. For example, in order to research the linkages between organizational form in development and the
evolution of open source software, MacCormack et al. (2006) needed to employ design structure methods
developed in computer science. This holds particular challenges, such as being able to cooperate with
researchers from different disciplines, formulate shared research problems, or scrutinize data gathering and
analysis by standards of various scientific disciplines. While this brings uncertainties to any research project, it
also greatly enriches our own discipline.
Social integration may be a regularity rather than an exception in phenomenon-based research. The emergence of
the “invisible college” marks commonalities between researchers across disciplines and institutions where none
were obvious before the common interest in the phenomenon. As observed in OSS research, a phenomenon can
unite scholars by reference to the same source texts, shared platforms and conferences. Eventually, the
community of scholars that drive the scientific inquiry on the phenomenon may ultimately redraw institutional
30
boundaries, thus perhaps establishing social integration across academic disciplines.
In the natural sciences and engineering, there are several outstanding outlets that openly encourage
interdisciplinary work, including Nature, Science, Physica, or Physical Review Letters. In our own field, many
outlets are open to interdisciplinary contributions as well. However, rather than explicitly encouraging
interdisciplinarity, LRP has positioned itself as embracing the phenomena-driven research that may involve
works across fields and disciplines. This seems to be a productive approach, in so far as it focuses on the object
of research rather than its process and outcome. An unconventional, inspiring, and interesting positioning. And
one, we are sure, that will greatly benefit our field.
Managers are working in practices deep within a phenomenon. Thus, phenomenon-based research, if well done,
has implications for practice. Through its interdisciplinary reach, the phenomenon may attract research from
several disciplines and inspire research questions and designs unavailable to a strictly disciplinary agenda. The
combination of the search for relevant data on the phenomenon with innovative research designs may in fact
generate highly relevant questions without sacrificing rigor. As discussed earlier, rigor in pre-theoretical work
cannot only mean adherence to disciplinary tools of evaluation only but evolves as scientific knowledge on the
phenomenon accumulates. Thus, we think LRP, being an outlet oriented towards managers as well as academics,
has chosen the positioning as an outlet for phenomenon-based research very wisely and may contribute to
delivering the third promise: publishing rigorous phenomenon-based research of high practical relevance.
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