Content uploaded by Georges Romme
Author content
All content in this area was uploaded by Georges Romme on Aug 26, 2019
Content may be subject to copyright.
Contents lists available at ScienceDirect
Research Policy
journal homepage: www.elsevier.com/locate/respol
Studying transitions: Past, present, and future
Mohammadreza Zolfagharian
a
, Bob Walrave
a
, Rob Raven
b,c,⁎
, A. Georges L. Romme
a
a
Eindhoven University of Technology, School of Industrial Engineering, the Netherlands
b
Monash University, Monash Sustainable Development Institute, Australia
c
Utrecht University, Copernicus Institute of Sustainable Development, the Netherlands
ARTICLE INFO
Keywords:
Innovation studies
Transitions
Transition studies
Research methods
Systematic review
ABSTRACT
The domain of transition studies has been drawing more and more scholarly attention and, as a result, its body of
knowledge is rapidly growing. This raises new challenges as well as opportunities, not the least regarding the
methodological and philosophical underpinnings of research in this domain. In this respect, transition research,
as a relatively young field of inquiry, has been little concerned with methodological investigation and reflection.
We propose a framework that enables this reflection: the so-called ‘transition research onion’. Subsequently, we
utilize this framework to systematically assess 217 peer-reviewed papers in the field of transition studies, to
distill key methodological patterns and trends of the field. The findings suggest that the methodology of tran-
sition studies, in terms of depth and diversity, is underdeveloped. These insights serve to guide future research
on transition processes.
1. Introduction
Systemic innovations directed toward more sustainable socio-tech-
nical systems are increasingly understood in terms of ‘transitions’
(Smith et al., 2010). A transition involves far-reaching structural
changes in socio-technical systems that enable particular desirable so-
cietal functions (e.g., mobility, energy, healthcare). In this respect,
transitions are multi-dimensional processes that often include techno-
logical, material, organizational, institutional, political, economic, and
socio-cultural changes. As such, transitions typically involve a broad
range of actors (e.g., individuals, firms and organizations, and collec-
tive actors), institutions (e.g., societal and technical norms, regulations,
standards of good practice), and technological elements (e.g., material
artifacts and knowledge).
The domain of transition studies has experienced a rapid growth
over recent years. Much work in this area has focused on studying the
characteristics of historical transitions and applying the obtained in-
sights to the development of governance frameworks to guide ongoing
(e.g., energy, food and health) transition processes. Only recently has
the field started to broaden, as new scholars from different disciplinary
backgrounds became (more) engaged. Examples of disciplines engaging
with transition studies are sociology (Geels, 2005;van Lente and Rip,
1998), psychology (Axsen and Kurani, 2014;Sorrell, 2015), economics
(Rogge and Hoffmann, 2010;Trutnevyte et al., 2015), political science
(Kern, 2012;Meadowcroft, 2011;Scrase and Smith, 2009), manage-
ment (Walrave and Raven, 2016;Walrave et al., 2018), engineering
(Davis et al., 2013), geography (Coenen et al., 2012) and philosophy
(Paredis, 2011). This broadening of the field also implies the in-
troduction of diverging methodological and philosophical under-
pinnings.
1
As an increasing number of researchers with different backgrounds
have become interested in transition challenges, we believe the time is
right to reflect on how to study transition problems. Indeed, “reflections
on methodologies for transitions research” is one of the key themes for
future research identified in a recent, collaboratively developed re-
search agenda for the field (Köhler et al., 2019: 4). Despite a few pio-
neering exceptions (e.g., Garud and Gehman, 2012;Geels, 2009,2010;
Genus and Coles, 2008;Loorbach et al., 2011;Pel, 2014;Turnheim
et al., 2015), transition scholars have been little concerned with
methodological reflection (Markard et al., 2012)—while being influ-
enced by many different research traditions. In this study, we take stock
of the kinds of research methods that have been used so far, in order to
provide directions on how to move forward.
Such an effort requires an evidence-based approach, in order to map
and understand the various methodological designs already used in
transition research (cf. Tranfield et al., 2003). Here, we draw on the so-
called ‘transition research onion’ to review 217 transition studies. The
results shed light on various aspects of transition problems and the
https://doi.org/10.1016/j.respol.2019.04.012
Received 30 January 2018; Received in revised form 2 April 2019; Accepted 26 April 2019
⁎
Corresponding author.
E-mail address: rob.raven@monash.edu (R. Raven).
1
For instance, formal modelling approaches to transitions are being explored (Holtz et al., 2015;Walrave and Raven, 2016).
Research Policy 48 (2019) 103788
Available online 21 May 2019
0048-7333/ © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
T
corresponding research designs that have been used so far—but also
signal that the methodology of transition studies is underdeveloped.
Subsequently, these insights allow us to identify various research op-
portunities for transition studies.
The next section contains a brief overview of the prevailing meth-
odological debates in transition research. Section 3explains our re-
search approach, involving a systematic literature review informed by
the transition research onion. Subsequently, section 4presents the re-
sults of the review. Section 5provides a discussion of these results,
including opportunities for future work on transitions.
2. Transition research and methodological challenges
Transition research is an interdisciplinary field, firmly rooted in the
tradition of system thinking (Grin et al., 2010;Rodrigo et al., 2015).
There is no agreed list of fields that constitute transition studies, similar
to what Fagerberg et al. (2012) observed for the field of innovation
studies. At the heart of transition studies is the socio-technical system
2
as the unit of analysis, and the features of fundamental structural
change as the main object of research.
3
But, transition researchers have
been drawing on insights from many different areas
4
: Complex adap-
tive systems theory (e.g., Holland, 1995;Kauffman, 1995;Prigogine
and Stengers, 1984), post-normal science (e.g., Ravetz, 1999), govern-
ance (e.g., Sabatier and Jenkins-Smith, 1999), evolutionary economics
(e.g., Dosi, 1982;Nelson and Winter, 1982), innovation studies (e.g.,
Smits and Kuhlmann, 2004), science and technology studies (e.g.,
Bijker and Law, 1992), history (e.g., Hughes, 1983), and institutional
theory (e.g., Scott, 1995).
As a result, transition researchers have contributed to theoretical
progress at the cross-roads of many different fields, in particular with
regard to questions related to sustainable development (e.g., Markard
et al., 2012;Martens and Rotmans, 2005;Smith et al., 2005). However,
there has been little reflection on the methodological challenges that
arise when one builds upon different fields and perspectives with dis-
tinct methodological traditions. The study by Genus and Coles (2008) is
one of few notable exceptions, as it reviews the challenges of the multi-
level perspective (MLP) in understanding transition processes. Genus
and Coles (2008) call for research that includes the role of agency and
political dimensions, moving beyond the MLP as a high-level heuristic
tool. Furthermore, they are also concerned about the quality of data and
data analysis in transition studies (e.g., the observer-expectancy bias
and boundaries of analysis). Similar criticisms and suggestions have
been voiced by others (e.g., Hurlbert, 2011;Markard and Truffer, 2008;
Smith et al., 2010;Vasileiadou and Safarzyńska, 2010).
In response to such criticisms, Geels (2011) reviews specific chal-
lenges arising from the MLP and provides important epistemological
and methodological arguments about transition studies. In this respect,
regarding the heuristic nature of the MLP framework, he argues that the
MLP framework serves as a middle range theory, rather than a ‘truth
machine’ in which researchers insert data to get an automatic answer to
a question. Geels also argues that research on complex phenomena,
such as transitions, cannot be reduced to models with detailed metho-
dological procedures, such as the statistically verifiable models com-
monly used in management and marketing studies. He also claims that
research on the MLP will always (need to) involve the creative inter-
pretation of researchers (cf. observer-expectancy bias), and therefore
largely draw on qualitative research methods (Geels, 2011).
In addition, MLP’s hierarchical levels often give rise to ambiguity in
definitions, boundaries and (conceptions of) relationships among niche,
regime and landscape. In this respect, Shove and Walker (2010) re-
commend that social practice theory is used to conceptualize transition
problems. In this view, the unit of analysis changes to practices, rather
than societal functions delivered through socio-technical systems
5
.
Accordingly, stability and change are conceptualized in terms of how
actors actively combine the elements of practice within and between
‘regimes’. The main questions of transition research thus become re-
formulated as “how variously sustainable practices come into existence,
how they disappear and how interventions of various forms [of prac-
tice] may be implicated in these dynamics” (Shove and Walker, 2010:
471). In contrast to the hierarchical perspective assumed by MLP,
which requires some sort of definition of the boundaries and mechan-
isms of level relationships, a practice-based view implies a horizontal
view of transitions.
In this vein, Jørgensen (2012) tried to moderate the limitations of
MLP by addressing the role of agency. Inspired by actor-network and
sense-making theories, Jørgensen (2012) introduced a flat and process
oriented approach, called arenas of developments (AoD), to explore
situated actors’ possibilities of engaging in transitional processes. An
AoD consists of actor constellations and the actors’ collective sense-
making activities in interpreting context and performing interventions.
Accordingly, change dynamics arise from tensions between actor-
worlds resulting in changing alignments and boundaries, rather than
MLP’s focus on discrepancies between regimes, niches, and landscapes.
Furthermore, some scholars are seeking new ways to study socio-
technical change and explore deeper methodological issues in transition
studies. In this respect, Geels (2010) discusses seven social science
ontologies, their assumptions regarding agency and causal mechanisms,
and their views on socio-technical transitions and environmental sus-
tainability. This serves to identify an ontological foundation for MLP
(Geels, 2010). Similarly, Loorbach et al. (2011) provide general re-
flections and guidelines on the methodological requirements of the
transition field. They demonstrate that research designs in this field
should have an integrative nature, be normative in their ambitions,
have a desire to contribute to societal change, and be planned through
the active involvement of scientists, policy makers, and various stake-
holders—both in the development of new knowledge and in its appli-
cation.
Wittmayer and Schäpke (2014) focus on action research and pro-
cess-oriented approaches, and more specifically transition manage-
ment, to study sustainability transition problems. In this respect, they
identified ideal-type roles and activities that help researchers create and
maintain space for societal learning. These roles are as follows: change
agent, knowledge broker, reflective scientist, self-reflexive scientist and
process facilitator. Finally, they acknowledged the importance of dif-
ferent research designs and related competences and skills of transition
researcher to carry out each role.
In another effort to extend the methodological choices for transition
researchers, Holtz et al. (2015) provide an overview of specific op-
portunities, benefits and challenges of various modeling approaches.
Specifically, they call for more precise versions of the various transition
frameworks to be conducive to modeling exercises (see also de Haan
and Rotmans, 2011;Haxeltine et al., 2008;Walrave and Raven, 2016).
McDowall and Geels (2017) also assess the challenges of modeling, and
proposed pluralist ‘bridging strategies’ and a dialogue between analytic
approaches to exploit the full analytic and practical potential of
2
Loorbach et al. (2017) distinguished three different perspectives on transi-
tion research: the socio-technical, socio-institutional, and socio-ecological per-
spective. In this paper, we focus on the socio-technical approach that con-
stitutes the roots of transition studies.
3
These are co-evolutionary, multi-dimensionality, multi-actor, multi-level,
path-dependency, long term thinking and non-linearity (Geels, 2002;Holtz,
2011).
4
Also see: van der Brugge and van Raak (2007);Geels et al. (2008), and
Frieler et al. (2015).
5
Shove et al. (2012: 14) define the elements of practice as: “(1) materials –
including things, technologies, tangible physical entities, and the stuff of which
objects are made; (2) competences – which encompasses skill, know-how and
technique; and (3) meanings – in which we include symbolic meanings, ideas
and aspirations’.
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
2
modeling. They demonstrate that mutual learning and cooperation of
both modelers and non-modelers within the transition field can facil-
itate such synergy. In a similar vein, recent studies integrated the dif-
ferent approaches of transition studies (e.g., Geels et al., 2016;Pel,
2014;Trutnevyte et al., 2014;Turnheim et al., 2015) to reveal the
underlying assumptions, strengths and weaknesses of existing analy-
tical tools, which in turn could help to develop crossovers and bridges
between the different approaches and thereby generate a deeper un-
derstanding of transition processes and outcomes.
Despite these initial efforts, the methodological debate has re-
mained rather ad-hoc, unstructured, and largely conceptual and ab-
stract in nature. Therefore, there is a need for a structured procedure
that systematically assesses the state of the field. In the remainder of this
paper, we conduct a systematic review of transition research methods
to shed light on the past, present and future of research methodology in
this field.
3. Method: systematic review
To systematically appraise the contribution of a given body of litera-
ture, an analytical approach is needed (Ginsberg and Venkatraman, 1985).
To this end, we adopt a systematic review approach to identify, analyze
and consolidate relevant sources of data regarding the methodological
choices in transition studies. A systematic review involves a comprehen-
sive, explicit, replicable and synthesized review of all relevant literature
regarding a particular question of interest (Tranfield et al., 2003). Gen-
erally, systematic reviews involve three main stages: (1) the planning stage
that often starts with a research question, which in turn informs the
searching and screening steps in the selection of articles; (2) the con-
ducting stage, typically involving data extraction and coding that are
usually accompanied by data synthesis, analysis and interpretation; and
(3) the stage of reporting what was (not) found with respect to the re-
search question (Tranfield et al., 2003;Briner and Denyer, 2012).
In the planning stage, the goal of our review was to answer: ‘What
are the methodological practices (dimensions) that are explicitly men-
tioned in transition studies?’ Building on the work by Markard et al.
(2012), who also conducted a systematic literature review in this field
of studies, we applied the same search string
6
in Scopus, to gather re-
levant literature. In addition, we also identified all papers, published
before 2016, that refer to one or more of the 20 core papers (in field of
sustainability transitions) listed by Markard et al. (2012). Notably, in
order to extract only the most relevant articles and keep the size of the
review workable, we focused on the five most influential journals in the
field—based on relative number of publications and citations on tran-
sitions studies. These journals are Energy Policy, Research Policy,
Technological Forecasting and Social Change (TFSC), Technology
Analysis and Strategic Management (TASM) and Environmental In-
novation and Societal Transitions (EIST). Markard et al. (2012) de-
monstrated that the first four journals are the main transitions-focused
journals. We added EIST because this journal has been established
specifically for the sustainability transitions research community.
By applying this search strategy, we distilled 350 potentially re-
levant papers. Since our goal is to review methodological practices in
transition studies, we only included papers that address one (or more)
empirical transition problem(s). As such, we excluded 133 conceptual
papers (e.g., opinion-driven or purely theoretical papers
7
). Table 1 lists
the final number of reviewed papers for each journal. The final database
of papers, subject to further analysis, included 217 papers.
To review how transition problems are investigated, we need to
systematically examine the methods applied. In this regard, we also
need to determine the various issues that influence method selection in
the field, such as paradigms, theoretical frameworks, and so forth. In
management research, the ‘research onion’ framework has been suc-
cessfully used to depict the different methodological dimensions, in
terms of the choice of data collection and data analysis techniques
(Saunders et al., 2015). Accordingly, we adapt and customize this fra-
mework to explain and evaluate the methodologies employed in tran-
sition studies. The framework outlined in Fig. 1 involves different layers
(with sub-layers or options). From the core to the outer layer, these are:
(1) research question, (2) paradigms, (3) theoretical frameworks, (4)
research methods, (5) data collection methods and data sources, and (6)
time horizons. In the following paragraphs, each layer is further de-
tailed. Whenever necessary, operational definitions are provided to
assure the consistency and replicability of the review (Babbie, 2010).
(1) Research question. A research question typically guides a
study (Bryman, 1992;Patton, 1990). Methodological fit is often as-
sessed in terms of the research question, which in turn is likely to be
influenced by the goal of the research, the background, skills and ex-
pertise of the researcher, interests of the stakeholders, and available
time, data and other resources (Brannen, 2005;Flood, 1995;Marsland
et al., 2000). To transform various research questions to a standardized
form, for the purpose of this review, a qualitative coding procedure is
used, following Saldaña (2015). Here, the first author of this study read
each paper to identify and extract information about the research
question(s) mentioned. In line with the inductive nature of the review
approach, we avoided the use of any predetermined categories
(Saldaña, 2015) to code the research questions. The categories were
thus allowed to emerge, through comparing and finding common fea-
tures among research questions. This coding process was iterative in
nature, to assure reasonable relations between categories and data to
emerge. For example, when a new potential category was identified, the
researcher would return to the papers already read to explore if there
was any related evidence. This coding process of category determina-
tion through continual and iterative comparison proceeded until no
new categories emerged and, as such, saturation in coding was
achieved.
(2) Paradigm. A paradigm refers to the set of key beliefs and as-
sumptions that affect (or guide) method selection. Within transition stu-
dies, four paradigms are identified, which serve as ‘options’: the positivist,
critical realist, interpretivist, and pragmatist paradigm. The main compo-
nents of each paradigm are the researchers’ assumptions about the nature
and relation of the relevant realities on transitions (i.e., ontological as-
sumptions), the nature and limitations of knowledge about transitions (i.e.,
epistemological assumptions), and the role of values and ethics within the
transition research processes (i.e., axiological assumptions) (Burrell and
Morgan, 1979;Crotty, 1998;Geels, 2010;Lincoln and Guba, 1985;
Tashakkori and Teddlie, 2010). Notably, each paradigm implies distinctive
assumptions for studying transition problems that may, in turn, require
different methods. The four paradigms are generally acknowledged ‘ideal
types’ in the social sciences (Weber, 1978). In coding the paradigm(s) used
in each paper, we placed it in one or more paradigms, thus also allowing
for positioning it between paradigms.
Empirical researchers often do not explicitly define and discuss their
paradigmatic orientations (Alise and Teddlie, 2010). In case of such a
paper, the paradigmatic designation resulted from our interpretation of
the ontology, epistemology, and axiology actually used in the study, as
well as information provided on the theoretical frameworks and re-
search methods used.
(3) Theoretical framework. Theoretical frameworks shed new
light on specific transition problems, and thus act as a lens that can
make researchers consider only specific concepts and/or theories
(Sovacool and Hess, 2017). However, there is no agreement on the
definition of ‘theory’ and the boundaries between theory and non-
theory (e.g., Mintzberg, 2005). Following Sovacool and Hess (2017), we
6
To find the relevant papers for the systematic review we used the following
search string: (TITLE-ABS-KEY ((sustainab * OR environmental * OR bio * OR
renewable OR socio-technical) AND (transition OR transform * OR "system
innovation" OR "radical innovation" OR shift OR change)))
7
For example, we excluded the conceptual papers by Azar and Sandén
(2011);Halbe et al. (2015) and Meadowcroft (2011) from the review.
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
3
consider theoretical frameworks to be any theoretical construct, con-
ceptual framework, analytical tool, heuristic device, analytical frame-
work, concept, or model that guides transition research. Accordingly,
theoretical frameworks in transition studies are grounded in the the-
ories and concepts of the relevant disciplinary contexts and areas
8
. For
Table 1
Number of articles included in the systematic review (per journal).
Publication Number of papers after applying the primary inclusion
criteria
Subset of papers that address at least one empirical transition
problem
Energy Policy 118 82
Technological Forecasting and Social Change 81 50
Environmental Innovation and Societal Transition 72 40
Technology Analysis and Strategic Management 40 28
Research Policy 39 17
350 217
Fig. 1. Transition research onion.
Note: the options identified for each layer were first pre-specified based on some initial literature, and then complemented and extended by additional literature
(reported in this section). This approach helped to ensure that each option is accurately labeled and unambiguous in its meaning.
8
Most recently, Sovacool and Hess (2017) presented the results of 35 semi-
structured interviews with experts to identify theories and conceptual frame-
works of socio-technical change. The authors identified 96 conceptual frame-
works, spanning 22 identified disciplines, which can be used for transition
studies. Here, we only mention some of the theories that have been used more
substantially in the transitions literature: Evolutionary economics (Nelson and
Winter, 1982;van den Bergh and Gowdy, 2000) (self-organization and com-
plexity theory [e.g., Rotmans and Loorbach, 2009], path dependence and lock-
in [Arthur et al., 1987;Cowan, 1990;David, 1985], and longwave theories
(footnote continued)
[Freeman and Louçã, 2001;Perez, 2002]); industrial economics (industry life
cycle approach (McGahan et al., 2004), the innovation systems tradition, dis-
ruptive innovations (Christensen, 1997) and technological discontinuities
(Anderson and Tushman, 1990)); economic geography (regional innovation
systems (Asheim and Isaksen, 2002;Cooke, 2002;Cooke et al., 2004)); man-
agement (resource-based view of the firm (Barney, 1991;Wernerfelt, 1984) and
corporate political action (Sarasini, 2013)); science and technology studies (ac-
tor–network theory (Callon, 1984;Law and Hassard, 1999), social construction
of technology (Bijker et al., 1987), large technical systems theory (Coutard,
1999;Hughes, 1983,1987;La Porte, 1991;Mayntz and Hughes, 1988;
Summerton, 1994)); political science (the advocacy coalition framework
(Sabatier and Jenkins-Smith, 1999)); institutional theory (institutional work
(Lawrence and Suddaby, 2006;Voronov and Vince, 2012)); and sociology
(practice theory (Reckwitz, 2002;Schatzki, 1996;Shove, 2003;Shove et al.,
2012)).
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
4
this layer, we provide statistics on four theoretical frameworks identi-
fied in the set of papers reviewed: the multi-level perspective (MLP)
9
,
strategic niche management (SNM)
10
, transition management (TM)
11
,
and technological innovation systems (TIS).
12
Furthermore, in our re-
view we also identified two additional sets of theoretical frameworks:
(1) ‘borrowed frameworks’ that were originally developed in other
disciplines and then used to study transition problems and (2) ‘new
frameworks’ that are designed by the authors by combining concepts
and theories from disciplinary perspectives such as sociology, (in-
dustrial and evolutionary) economics, political science, and cultural
studies.
(4) Research method. Research methods are organized and sys-
tematic ways of inquiry to address specific research questions. When
conducting empirical research, transition researchers have three gen-
eral options regarding the research method (Guba and Lincoln, 1989;
Niglas, 2010;Tashakkori and Teddlie, 1998;Teddlie and Tashakkori,
2009;van de Ven, 2007). First, they can draw on qualitative research
methods that involve narrative data sources and data analysis techni-
ques such as ethnography, action research, grounded theory develop-
ment, and narrative inquiry. These methods typically adopt idealist
(relativist), subjectivist, deductive, value-bound inquiry and provide an
ideographic understandings of the concerned problems. Second, one
can use quantitative research methods that involve numeric data
sources and analytical approaches such as mathematical and statistical
methods. These methods derive realist, objectivist, inductive, value-free
and nomothetic approaches to study the phenomena of interest. Third,
transition researchers can draw on mixed research methods in which
different research strategies and methodological aspects are combined
(e.g., using both qualitative and quantitative viewpoints and/or in-
ference techniques) for the purpose of breadth and depth of under-
standing and corroboration (Johnson et al., 2007). We labeled a re-
search method as mixed if both qualitative and quantitative methods
were used for data analysis.
13
(5) Data collection method and source. Any data collection
method involves the act of gathering data from a particular source. Our
review implies that transition researchers collect data from the fol-
lowing sources (see Fig. 1): document, interview, survey, observation,
and workshop. In codifying the data sources and collection methods in
the papers reviewed, we coded very specific sources and methods in one
of the aforementioned categories. For example, we considered a ‘nar-
rative walk’ and ‘informal discussion’ to be a kind of interview.
(6) Time horizon. It is critical to understand how time and timing
affects transition processes (e.g., Ancona et al., 2001;George and Jones,
2000;Poole et al., 2000). As such, a time horizon is a key attribute of
research that significantly limits the choices made at other levels of the
research onion. Generally, there are two fundamental types of research,
which consider the role of time in an opposing manner (van de Ven,
2007): (1) cross-sectional studies that are designed to look at a variable
at a particular point in time and (2) longitudinal studies that are di-
rected to study a particular phenomenon (or phenomena) over an
(extended) period of time.
In the second phase of the review process, one of the authors of this
study conducted the work on inclusion/exclusion and the data
extraction from the papers reviewed, to ensure coding consistency
(based on the options and their definitions depicted previously), while
another author double coded 10% of all papers reviewed (22 articles).
This subset of papers included those papers which were found proble-
matic by the first coder. The inter-rater reliability was 96%, indicating a
high level of reliability. In those cases where there was disagreement
between the coders (5 out of 132 cases), the article was reassessed until
consensus was reached. All information was collected in a tabular
format (in Microsoft Excel).
Whilst this paper provides some interesting lessons, there are a
number of limitations arising from such research setup. While com-
prehensive in nature, our review is still bounded by inclusion/exclusion
criteria, which may indeed have affected the results of our study.
14
The
main limitation is, however, linked to the limited number of articles we
reviewed; the reviewed evidence thus excludes articles published in
other journals as well as monographs and edited books. Nevertheless,
the selected papers appear to sufficiently represent the current body of
knowledge on transition studies. Because we achieved the saturation
point in coding all papers, the inclusion of more studies in the review is
not likely to significantly change our main findings. Nonetheless, the
layers and the options of the onion are open to change, as scholars and
practitioners are continually exploring new directions and perspectives
to study transition problems.
4. Main findings
4.1. Research questions
Transition problems can be categorized in terms of societal func-
tions (e.g., energy, transportation and food) or with regards to various
themes in the transition process (e.g., governance, power and politics,
civil society, culture and social movements).
15
However, for the pur-
pose of our review, a classification of research questions based on their
methodological requirements is more relevant. Accordingly, four main
categories of transition research questions were identified:
Questions that relate to explaining a whole, or part of, a transition.
Examples are questions about how transitions come about, the emer-
gence and progress of an innovation in a market, and factors that sti-
mulate or hinder the development and diffusion of a particular tech-
nology. For instance, “how do the various subsystems of regional
innovation systems [science, politics, public administration, industry,
finance, intermediaries and civil society] trigger, push or hinder re-
gional change, and how do these subsystems interact with each other in
local energy transition processes?” (Mattes et al., 2015: 256), how the
slow diffusion of biomass digestion technology in the Netherlands can
be explained (Negro et al., 2007), and “exploring the historical evolu-
tion of the electricity regime in the province of Ontario from 1885 to
2013” (Rosenbloom and Meadowcroft, 2014: 670).
Questions about particular transition policies and transition pathways,
including exploring future transition trajectories (as well as transition
patterns and mechanisms), scenario development and assessment of
historical policies or analysis of future policy options. Examples are
studies assessing the cost effectiveness of potential future pathways and
9
The multi-level perspective has been developed specifically for analysing
transition problems and builds particularly on evolutionary economics, science
and technology studies, and institutional theory (with many extensions made
after its original inception in the 1990s) (e.g., Geels, 2002;Rip and Kemp, 1998;
Schot, 1998).
10
See, e.g., Kemp et al., 1998;Schot et al., 1994.
11
See, e.g., Rotmans et al., 2001.
12
See, e.g., Bergek et al., 2008;Carlsson and Stankiewicz, 1991;Carlsson
et al., 2002;Hekkert et al., 2007;Jacobsson and Bergek, 2006.
13
This is a more specific definition than the broader definitions of ‘mixed
methods’ proposed by others (e.g., Creswell and Plano Clark, 2007;Denzin and
Lincoln, 2011).
14
For instance, we identified relatively few studies that took a transdisci-
plinary approach, which has been adopted by some transition scholars to
complement their fundamental/theoretical work with societal knowledge and
expertise (Grin et al., 2010;Scholz, 2017), but may have been published in
different journals than the five core to our analysis. In addition, we discovered
limited action research and knowledge co-production studies. These approaches
may not only benefit policy officers and planners with new knowledge, but can
also serve scientists to discover overlooked aspects of transitions (Audet and
Guyonnaud, 2013;Frantzeskaki and Kabisch, 2016;Wittmayer and Schäpke,
2014;Wittmayer et al., 2014).
15
These dimensions, among others, have been identified in the 2017 STRN
research agenda (Köhler et al., 2017).
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
5
the influence of government policy on growth and diffusion of sus-
tainability-oriented innovations. Some of the research questions in the
reviewed articles are: appraising the investment and total system costs
of the UK transition to a low-carbon electricity system under different
governance pathways from 2010 to 2050 (Trutnevyte et al., 2015), or
exploring how “the nature and scope of transition pathways vary with
differing economic development realities and priorities” in Brazil, Ma-
lawi and Sweden (Johnson and Silveira, 2014: 2), and “how do different
lock-in mechanisms of socio-technical regimes influence new transition
pathways” (Klitkou et al., 2015: 23).
Questions that address the influence of specific variables or factors un-
derlying transition processes. Examples of questions in this category are
“how political conditions and industrial events influenced the rise and
fall of offshore wind on the political agenda in Norway between 2005
and (Normann, 2015: 180), “how does an exogenous shock [i.e., the
Fukushima nuclear accident] affects the onset, magnitude, and per-
manence of changes in key energy-related metrics, such as electricity
consumption” in Japan (Wakiyama et al., 2014: 655), and how im-
portant non-economic factors are influencing technological change
across technology and country contexts (Hultman et al., 2012).
Questions that involve the role and influence of (networks of) actors
(e.g., users, customers, citizens, firms, and collective actors) on transi-
tion processes. These research questions thus address the role of beliefs,
expectations, cognitions, and characteristics of heterogeneous agents in
transition process. Accordingly, issues that emerge from network
communication through discourses, narratives, power relations and
usages of language and meaning are placed in this category. Examples
include the analysis of “how and the extent to which an individual
academic, Professor Hofbauer, has influenced the formation of a TIS
centered on gasified biomass in Austria” (Hellsmark and Jacobsson,
2009: 5597), “what are the rationales of actors to support a socio-
technical transition and to take part in niche-activities” (Bakker, 2014:
61), “what is the dominant discourse amongst incumbents in the Dutch
energy regime regarding the future of the energy system and which
developments put pressure on their discourse” (Bosman et al., 2014:
47), and “what is the relation between changing actor expectations and
changing actor strategies” (Budde et al., 2012: 1037).
Table 2 shows how the papers reviewed are distributed across the
categories. Note that some papers formulate more than one research
question. In these cases, each question was separately coded. In other
words, any given paper may include one or more question types (see
Table 3). The results indicate that the first question type, which relates to
general questions about a (part of a) transition currently prevails in
transition studies. Table 2 also provides examples of the methods used for
each kind of research question. Deductively, the four question types can be
linked to holistic analysis, pathway analysis, actor analysis and variance-
oriented analysis, respectively. However, our review suggests that such a
clear relationship does not exist. That is, methods with the same functions
have been applied to address different types of questions.
4.2. Paradigms
All paradigms previously identified are found in the papers
reviewed. Table 4 provides illustrations. Only a few papers, however,
make their paradigmatic stance explicit and, as such, we do not report
numbers in Table 4.Table 4 describes the philosophical assumptions
underlying the main paradigms in transition research and provides
examples of papers drawing on each philosophy. While many authors
do not explicitly define their paradigmatic stance, traces of this stance
(e.g., in theoretical frameworks and research methods used) allowed us
to effectively distill the paradigms used in most articles. For instance,
the study by Choi and Anadón (2014: 80) “provides a quantitative
analysis of the interactions between different types of solar photovoltaic
(PV) networks at the niche level, the complementary semiconductor
sector at the complementary regime level, and the solar PV policies”.
Although these authors do not explicitly mention their paradigmatic
stance, they assessed the relationship (by means of three equations)
between different independent variables on a dependent variable (i.e.,
technology diffusion, production, and knowledge generation in the
solar PV sector). As such, we categorized this paper as an example of
positivist transition research (see Table 4, Positivist transition re-
search).
Another example is Bosman et al. (2014), who used argumentative
discourse analysis to scrutinize discursive regime dynamics in the Dutch
energy transition. Accordingly, they hypothesized about “the discursive
changes and how this affects positioning, coalitions and regime struc-
tures through time” (Bosman et al., 2014: 56). They also accepted a
certain degree of subjectivity in the results, because of the qualitative
and explorative nature of their research. We designated this study as a
critical realist transition research, as it aims to shed light on the un-
derlying dynamics, within a particular regime, that might be a pre-
condition for a transition to occur (see Table 4, Critical realist transition
research).
Bakker (2014) used interpretative analysis to explore the interests
and expectations of the niche actors (involved in electric vehicle re-
charging) for explaining their rationales in supporting the e-mobility
transition. Here, the author explicitly mentions he is conducting in-
terpretative research (compared to, for example, a more structured
approach such as codifying the interview data). Therefore, we con-
sidered this paper as an interpretivist transition research paper (See
Table 4, Interpretivist transition research).
Finally, Martin and Rice (2015) analyze the velocity of Australia's
renewable energy project approvals through shifts in policy. They ex-
plicitly use a pragmatic approach, following Sperling et al. (2010) who
“commend the merits of using combinative governance, planning and
community engagement as the cornerstone of renewable energy pro-
jects approval” (Martin and Rice, 2015: 130). This pragmatism is also
Table 2
Total number of distilled generic research questions and their typical research methods observed in the sample.
Research question or transition problem Number Percentage Examples of methods used
Questions that relate to explaining a whole, or part of, a transition.
(‘Whole’ questions.)
111 51% Case study, multi-facet analysis, PEST analysis, historical event analysis,
qualitative analysis, thematic analysis, grounded theory
Questions about particular transition policies and transition pathways.
(‘Pathway’ questions.)
67 31% Sustainability foresight method, Quantitative modeling and assessment, and
dynamic decision trees
Questions that involve the role and influence of (networks of) actors.
(‘Actor’ questions.)
44 20% Survey based studies, Q methodology, meta inquiry and discourse analysis.
Questions that address the influence of specific variables or factors
underlying transition processes (‘Variable’ questions.)
41 19% Econometric models, multivariate analysis, autoregressive moving average
model, qualitative comparative analysis and process tracing (coding).
Table 3
Number of studies that address one or more research question types.
Question types Whole Pathway Actor Variable
Whole 83 (38%)
Pathway 11 (5%) 44 (20%)
Actor 10 (5%) 8 (4%) 20 (9%)
Variable 7 (3%) 4 (2%) 6 (3%) 24 (11%)
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
6
Table 4
Philosophies underlying the main paradigms in transition research (adapted from Saunders et al., 2015).
Ontology Epistemology Axiology Typical methods Examples
Positivist transition
research
There is a real and external transition
process independent of the researcher. Also,
only one true transition reality exists
(universalism). Transitions are made up of
solid, granular ‘things’ in an ordered form.
The scientific method can provide the
knowledge about transition. Transitions are
composed of observable and measurable
facts, and law-like generalizations on
transition can thus be discovered. As such,
numbers play a pivotal role in developing
knowledge. Causal explanation is critical to
making predictions.
Transition studies are value-free. The
researcher is detached, neutral and
independent of what is being researched,
and thus maintains an objective stance.
Typically, deductive, highly structured,
large samples, measurement, typically
quantitative methods of analysis, but a
range of data can be analyzed.
Schmidt et al., 2012;Boon
and Dieperink, 2014;Choi
and Anadón, 2014
Critical realist
transition
research
A transition is stratified and composed of
three layers: the empirical layer (i.e. events
that are actually observed or experienced),
the actual layer (i.e. events and non-events
generated by the real layer; which can or
cannot be observed) and the real layer (i.e.
causal structures and mechanisms with
enduring properties). Also, the reality of
transition is external and independent of the
researcher. There are objective and
intransient (relatively unchanging)
structures and causal mechanisms in any
transition process.
Concentration on in-depth historical analysis
of structures to provide a bigger picture of
which we see only a small part of transition.
As such the critical realist adopts an
epistemological relativism (Reed, 2005), a
(mildly) subjectivist approach to knowledge.
Causality in transition cannot be reduced to
statistical correlations and quantitative
methods, and a range of methods is
acceptable (Reed, 2005). Historical causal
explanation is the main contribution of
transition research.
Transition studies is value-laden research.
Transition researcher acknowledges bias by
worldviews, cultural experience and
upbringing. Transition researcher tries to
minimize these biases and errors. Transition
researcher is as objective as possible
Retroductive (Sayer, 1992), that is, in-
depth historically situated analysis of pre-
existing structures and emerging agency.
Range of methods and data types to fit
subject matter.
Bosman et al., 2014;
Jhagroe and Loorbach,
2015;Fuenfschilling and
Truffer, 2014
Inter-pretivist
transition
research
The nature of transition is complex and rich.
However, transition is socially constructed
through culture and language. With its focus
on complexity, richness, multiple
interpretations and meaning-making,
interpretivist transition research is explicitly
subjectivist. Transition involves a flux of
processes, experiences and practices.
Theories and concepts of transition are too
simplistic to capture the full richness of the
world. Transition knowledge can be obtained
by focusing on narratives, stories,
perceptions and interpretations of actors
involved. New understandings and
worldviews are the contribution of transition
research.
Transition research is value-bound.
Researchers are part of what is researched
and subjective interpretations of transition
researcher is key to contribution of the
research. Transition researcher is reflexive
about own thinking and writing.
Typically inductive. Small samples, in-
depth investigations, qualitative methods
of analysis, but a range of data can be
interpreted.
Bakker, 2014;Diaz et al.,
2013;Sarasini, 2013;
Domènech et al., 2015
Pragmatist
transition
research
The nature of transition research is complex,
rich and external to transition researcher. A
transition is the practical consequence of
ideas, and knowledge is valued for enabling
actions to be carried out successfully.
Transition involves a flux of processes,
experiences and practices.
Practical meaning of knowledge in specific
contexts is emphasized. ‘True’ transition
theories and knowledge are those that enable
successful action. Focus on problems,
practices and relevance of transition. The
contribution of transition research is
problem solving and informed future
practice.
Transition research is value-driven, and is
initiated and sustained by the researcher’s
doubts and beliefs. Researcher is reflexive
about own thinking and writing.
Following research problem and research
question. Range of methods: mixed,
multiple, qualitative, quantitative, action
research. Emphasis on practical solutions
and outcomes
Martin and Rice, 2015;Bos
and Brown, 2014;Kiss and
Neij, 2011;Yuan et al., 2012
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
7
reflected in the research design of the paper, involving business process
analysis coupled with qualitative analysis (see Table 4, Pragmatist
transition research).
4.3. Theoretical frameworks
Our review demonstrates that most researchers in transition studies
(around 90 percent of the papers reviewed) use a theoretical frame-
work. Table 5 provides an overview. This also implies that 21 papers in
our sample do not report any particular framework for data collection/
analysis. As can be seen in Table 5, around 29 percent of the reviewed
papers adopted one specific transition framework (i.e., MLP, SNM, TIS,
or TM) individually or in combination with other theories and con-
cepts.
16
Among the specific transition frameworks, MLP has been
adopted most frequently.
Table 5 also shows that 62 percent of the papers in our sample use a
framework other than those designed specifically for transition studies
(i.e., MLP, TIS, SNM and TM). Notably 55 papers (25%) use a ‘borrowed
framework’ while 80 papers (37%) designed a completely new frame-
work. With respect to the latter, Wesseling et al. (2015), for instance,
designed a conceptual framework that combines corporate innovation
and political influence strategies. Also, Elzen et al. (2011) drew on
innovation studies and the multi-level perspective with insights from
social movement theory and political science. Furthermore, Naus et al.
(2014) developed a framework derived from ‘practice theory’ in so-
ciology, and ‘informational governance’ in particular, for analyzing the
role of information flows in smart grids. Examples of the former include
the societal needs framework in social psychology used by de Haan
et al. (2014), the application of the political sociology of science and
technology based on Moore et al. (2011) by Hess and Mai (2014) and
the use of actor network theory and the notions of ‘framing and over-
flowing’ developed by the French sociologist Callon (1998) in Jolivet
and Heiskanen (2010).Table 5 illustrates that researchers resort to new
and borrowed frameworks rather often—independent of the journal
that published their work; and Fig. 2 shows they increasingly do so.
Furthermore, Fig. 2 illustrates that in recent years studies started to
appear that do not define their theoretical framework (i.e., from 2012
onward).
4.4. Research methods
We also assessed all 217 papers in terms of the research method
layer in the onion framework. For most papers, this was a straightfor-
ward exercise but 21 papers did not explicitly describe the method(s)
adopted. These studies were initially labelled as ‘no method men-
tioned’. Subsequently, 10 out of these 21 papers were coded by
screening the entire text for words such as review, analysis, description,
discussion and explanation; the paragraphs in which these words were
used then often served as good indications of the methods adopted. The
remaining 11 papers appeared to apply or test an existing theoretical
framework in an exemplary transition problem and, as such, no method
was explicitly mentioned. Based on what the authors in each of these
studies actually did, it was possible to classify them under one of the
three main research methods. As a result, 20 papers in this set were
categorized as using a qualitative research method and one paper as
using a mixed research.
Table 6 shows the results for the entire set of papers. As such,
qualitative methods are used most frequently in transition research
(82%). Fig. 3 denotes that this has always been the case. That is, we see
a relative decrease in the number of quantitative and mixed method
studies. As such, while the relative amount of such types of studies has
always been rather low, they are becoming even more exceptional.
Only 19 papers (9%) adopts a quantitative research method such as
econometric methods and statistical analysis. We also identified 19
papers that adopted a mixed method approach (9%).
17
According to
Table 6, all three types of research methods can be found in a sub-
stantial amount of work published by TFSC and Energy Policy. With a
few exceptions, Research Policy, EIST and TASM primarily published
qualitative papers.
Our review also demonstrates that transition researchers most fre-
quently adopt a case study method (in 116 articles, 53% of the papers
reviewed). This includes single cases as well as multiple and com-
parative case studies, and theory-guided as well as explorative case
studies. Moreover, various quantitative and qualitative techniques have
been adopted by transition scholars drawing on case studies: for ex-
ample, (double) coding, content analysis, discourse analysis, thematic
analysis, ethnography and patent analysis.
4.5. Data collection and data sources
Table 7 demonstrates that published and unpublished documents
are used in 82% of the papers reviewed. The primary and secondary
data sources of these documents include, among others, legal docu-
ments, annual reports, press releases (e.g., in newspapers and maga-
zines), position papers, policy documents, parliamentary hearings, re-
search reports, minutes and slides from meetings, informative internet
websites, blogs, company websites, governmental websites; and aca-
demic sources such as books, journals and conference proceedings.
More than half of all the studies used interviews as a data collection
method. Different interview techniques are utilized, such as formal and
informal interviews, and structured and semi-structured interview
protocols. Surveys, observations and workshops are utilized in less than
15% of the papers reviewed. Furthermore, 121 studies (about 56%)
used more than one data source and data collection method.
4.6. Time horizon
Table 8 demonstrates the distribution of research designs in terms of
the time horizon. This table shows that 88% of the papers reviewed has
a longitudinal research design, while only 12% of the papers use a
cross-sectional research design with a relatively short time horizon.
Fig. 4 suggests that transition scholars have long been preferring
Table 5
Total number of theoretical frameworks observed in the sample.
Theoretical frameworks New framework Borrowed framework MLP SNM TIS TM Not defined
TFSC 22 10 5 1 8 1 4
EIST 13 11 10 1 1 3 1
TASM 11 7 4 3 2 2 1
Research Policy 12 3 1 1 0 0 0
Energy Policy 22 24 12 2 5 2 17
80 (37%) 55 (25%) 32 (15%) 8 (4%) 16 (7%) 8 (4%) 23 (11%)
16
For example, while Raven (2007) follows the MLP framework, Diaz et al.
(2013) used MLP in combination with actor network theory.
17
Note that a combination of two qualitative methods, or two quantitative
methods, is not considered a mixed method.
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
8
longitudinal research designs. That is, longitudinal studies, relatively,
are becoming increasingly dominant over time. Notably, 18 papers
(8%) did not explicitly mention their time horizon. The time horizon of
these papers was coded based on indirect evidence, such as the time
dimension (implicit in) the research question. Also, around 80% of the
papers included data for a period beyond ten years in the past or the
future, naturally aligning with the long-term nature of transition pro-
cesses. While only 28 articles (13%) considered a period less than 10
years, 88 articles (41%) specified a time horizon between 10–30 years,
and 83 studies (38%) focus on a period of more than 30 years to answer
their research question.
5. Discussion
Many research domains have become methodologically more di-
verse, and as a result, scholars in these domains have engaged in
methodological reflection to progress these domains (e.g., Hanson and
Table 6
Distribution of research methods observed in the sample.
Qualitative
methods
Quantitative
methods
Mixed methods
(Quan-Qual)
TFSC 39 4 7
EIST 39 1 0
TASM 27 1 0
Research Policy 15 1 1
Energy Policy 59 12 11
179 (82%) 19 (9%) 19 (9%)
Fig. 3. Number of used research methods observed in the sample, per year.
Table 8
Time horizon: Longitudinal vs. cross-sectional observed in the sample.
Numbers in the papers
reviewed
Percentages in the papers
reviewed
Cross sectional 27 12%
Longitudinal 190 88%
Fig. 2. Number of theoretical frameworks observed in the sample, per year.
Table 7
Distribution of data collection methods and sources observed in the sample.
Data collection/sources Number of studies Percentage
Documents (published and unpublished) 177 82%
Interviews 125 58%
Surveys 28 13%
Observations 23 11%
Workshops 12 6%
Several data collection methods used 121 56%
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
9
Grimmer, 2007;Hurmerinta-Peltomäki and Nummela, 2006;
Hutchinson and Lovell, 2004;Molina-Azorín, 2009;Scandura and
Williams, 2000;Wells et al., 2015). The field of transition research has
also been experiencing a substantial growth in methodological di-
versity. This is a positive trend, as researchers from different fields
bring along different methodological traditions, but it also reinforces
the need for reflection on method selection. The onion framework
proposed in this paper serves to integrate the contributions that can be
achieved by means of different methods (e.g., what types of studies can
solve what types of transition-related research questions), and may also
create higher levels of synergy between different types of studies in the
transition field.
Although this framework does not provide any detailed guidelines,
it can be used as a heuristic to assess and advance the methodological
depth and diversity of the field. Methodological depth here involves the
coherence between the different elements of the transition research
onion, that is, research questions, philosophical assumptions, theore-
tical frameworks, etcetera. In this respect, transition researchers can
also turn to Table 4—and in particular the ‘Typical methods’ co-
lumn—for guidance on achieving coherence in their research design.
Specifically, this table offers information on the relationship between
paradigmatic stance and method used. The notion of methodological
diversity reflects the variety within each level of the research onion, as
an important source of creativity and future growth of the field. As
such, the focus here is on the question of how transition problems
should be studied. This implies that we seek to contribute to transition
research by (a) observing and discussing the limitations of the metho-
dological boundaries currently prevailing in transitions research; and
(b) developing a research agenda that spurs knowledge development in
this field. In the remainder of this section, we explore these two con-
tributions.
5.1. Transition research: limitations, reflections, and challenges
First, questions (should) drive research and, as such, greatly de-
termine all other layers of the research onion. We found that 51% of the
transition problems observed include a ‘whole question’, and as such
adopt a bird's-eye view on matters (see Tables 2 and 3). This is in line
with the STRN research agenda: “Some scholars are ‘zooming-out’ to
develop an even more encompassing understanding of transitions. This
includes interactions between multiple systems such as electricity-
transport, agriculture-transport, and heat-electricity” (Köhler et al.,
2017: 12). On the other hand, scholars are also zooming-in to study and
understand the roles of particular actors (e.g. users, firms, civil society
actors) and dimensions in transitions and the MLP (Köhler et al., 2017).
Although important, it is important to position this type of work in a
larger context, in order to include aspects like co-evolution and multi-
actor dynamics (Köhler et al., 2017).
Second, most theoretical frameworks in the papers reviewed fit the
category of ‘new and borrowed’ frameworks (62%) rather than specific
transition frameworks (i.e. MLP, TIS, TM and SNM) (30%). This is a
notable advancement of the field, given Shove and Walker’s (2007:
768) plea for “loosening the intellectual grip of innovation studies, for
backing off from the nested, hierarchical multilevel model as the only
model in town, and for exploring other social scientific, but also sys-
temic theories of change” (see also Köhler et al., 2017). Our analysis
also appears to signal a recent broadening of the field in terms of new
dimensions (e.g., geography, politics, strategic and organizational is-
sues) that are increasingly acknowledged as critical, previously over-
looked, dimensions shaping transition processes. However, we note that
while new and/or borrowed frameworks are increasingly used to study
transitions (see Fig. 2), such studies often build upon frameworks and
traditions from related disciplines, which may trigger further metho-
dological complexity, and implies a need for continued methodological
advancement and reflection.
Third, we observed no clear relationships between the types of
questions being addressed and the methods applied. As mentioned
earlier, a significant number of the papers reviewed does not explicitly
describe the method used. Moreover, many of the other papers we re-
viewed did not fully articulate their methods and theoretical/analytical
frameworks, justify their research design, or mention any limitations of
their research. Some studies even fail to explicitly elaborate on the
applied method—in relation to other options identified in the research
onion—regardless of whether the chosen approach was (not) valid for
the research question under investigation. This is highly remarkable
because of the close relationship between the type of method and the
knowledge that can be obtained by it, and therefore missing metho-
dological information severely constrains the legitimacy of the knowl-
edge claims made in these studies.
Fourth, methodological investigation gives a sense of the kind of
knowledge that is warranted or closed off in a particular field, by
studying the relative usages or lack of certain methodological options
(Bryman, 2011). For one, our analysis demonstrates that more than
80% of the studies draw on qualitative approaches, and more than 50%
of all articles are based on case studies. In 38% of all articles reviewed,
various types of methods were identified (see section 4.4). Furthermore,
as illustrated in section 4.5, around 56% of the papers used more than
one data source and data collection method, while surveys (13%), ob-
servations (11%) and workshops (6%) are less frequently utilized than
interviews and documents. Although these statistics indicate a sub-
stantial level of diversity, they do point at a potential asymmetry in
theoretical insights arising from several data sources possibly being
underused. In other words, it might be the case that most knowledge is
developed by drawing on subjective data (following from interviews
Fig. 4. Time horizons observed in the sample over time.
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
10
etc.), at the cost of knowledge building by means of collecting and
analyzing large scale data and/or observations techniques. Future re-
search needs to assess whether this asymmetry actually occurs and what
its implications are.
Fifth, the ratio between quantitative and qualitative studies (see
section 4.4) suggests that few studies draw on realist, objectivist, in-
ductive, value-free and nomothetic approaches, and idealist (relativist),
subjectivist, deductive, value-bound inquiry and ideographic under-
standings prevail in transition studies (section 4.2; see also Niglas,
2010;Tashakkori and Teddlie, 1998;Teddlie and Tashakkori, 2009;
Guba and Lincoln, 1989). Some have argued that the latter under-
standings are more compatible with the nature of transitions, because
of epistemological and ontological reasons (McDowall and Geels,
2017). Qualitative research and especially narrative theories have been
advocated as being more suited to handle the heterogeneous, con-
tingent and multi-level nature of socio-technical transitions (see, e.g.,
McDowall and Geels, 2017;Andersson et al., 2014). In this respect,
within the various research paradigms there are particular preferences
for research methods. We argue that, while quantitative approaches
may not be compatible with all transition-related research questions,
they might be rather valuable for particular transition-related research
questions. For example, specific variables or conditions of decision
making processes that determine the purchase of sustainable goods and
services may be derived more effectively from controlled experiments
than from any other research method; another example involves the
long-term consequences of a range of policy interventions—which can
be derived from simulation modeling in addition to field work.
More importantly, the dominance of particular methodologies and
paradigms over others may limit the societal impact of transition re-
search. Public policy makers and company executives also exhibit
particular preferences for paradigms and research designs. In fact, their
decision-making processes may more often than not align better with
research results expressed in quantitative ways (e.g., in tables and
statistical correlations) than with contextualized knowledge requiring
substantial interpretation, such as insights and narratives developed in
qualitative case studies. The challenge here is to find the right balance
between doing justice to the real-world complexities of transitions (that
some have argued are best addressed by narrative approaches) versus
the ability to communicate and align with the realities of decision-
making in policy and business (in which results expressed in straight-
forward quantitative ways are often perceived as more legitimate). By
reflecting more explicitly on who the primary client/audience of a
particular transition research project is, and adapting the methodology
accordingly, this balance is more likely to be found and sustained.
Sixth, given the relative usage of longitudinal versus cross-sectional
studies (section 4.6), process research appears to be far more prevalent
in transition studies compared to variance research.
18
This may be due
to the temporal nature of transition processes—which resonates better
with longitudinal than cross-sectional data. While this might be true for
complete transition processes, transition scholars also need to study
sub-elements/systems of these processes by means of variance studies,
in order to better understand the complex matter associated with a
transition. In other words, detailed studies of the relationships between
specific variables might serve to build a better understanding of the
overall transition process. As such, in addition to analyzing the systemic
nature of transition processes, one needs to study the interactions and
associations of sub-systems and social groups which shape overall
emergent patterns and behaviors at the systems level. Van de Ven
(2007) argues there is a strong complementary relationship between
process and variance approaches, that is, any answer to variance
questions requires answers to the corresponding process questions, and
vice versa.
While the number of cross-sectional studies has recently been
growing (see Fig. 4), transition scholars traditionally prefer longitudinal
research designs. We believe that this potentially undermines knowl-
edge development on more specific sub-elements and/or systems
driving transitions. In this respect, our findings resonate with the re-
cently updated STRN research agenda that also emphasizes the need for
more studies combining qualitative and quantitative approaches
(Köhler et al., 2017): accordingly, transitions research would need to
develop (1) approaches “for ‘structured navigation’ between broad
transition frameworks, including the multiplicity of transitions and
more precise theories and concepts for studying more confined phe-
nomena” (Köhler et al., 2017: 43); and (2) methodologies “for com-
bining quantitative and qualitative methods in the context of sustain-
ability transitions research” (Köhler et al., 2017: 47).
5.2. Methods in transitions research: a research agenda
Based on the analysis earlier in this paper, we believe the following
avenues are important for enhancing the methodological rigour and
richness of transition studies.
First, while current transition research is relatively strong in ex-
plaining past transitions and case studies, it seems less strong in de-
signing (practical) interventions. Indeed, the focus has primarily been
on process questions of “how things develop and change over time” at
the expense of studies focusing on variance or causal questions of “what
causes what” (van de Ven, 2007: 146). Extending the methodological
toolbox beyond primarily qualitative process theories might lead to a
better understanding on possible intervention strategies—and as such,
greater policy impact. In this respect, transition studies might be best
positioned at the interface of the social sciences and the design (inter-
vention-oriented) research, or what Simon (1969) called a design sci-
ence. One can thus consider the transition field to be part of a broader
set of design science disciplines including architecture, medicine, in-
formation systems, and similar fields (Boehnert et al., 2018;Irwin et al.,
2015). Subsequently, we can learn from how some of these other in-
terdisciplinary disciplines have built—and continue to build—a col-
lective body of knowledge that is adaptive to particular local condi-
tions, cultural constraints, social values, and so forth. One key insight is
that different methods, with distinctive underlying assumptions and
epistemologies, result in different types of insights that can be synthe-
sized in a body of knowledge about the contextual conditions, gen-
erative mechanisms, intervention strategies and outcomes of societal
transitions (e.g., March and Smith, 1995;van Aken and Romme, 2012;
van Burg and Romme, 2014).
Second, in order to achieve such an ambitious goal, transition scholars
need to make and communicate methodological and epistemological
choices in an informed and transparent manner. Practically, this implies
that transition scholars should consider designing their studies based on
the options available in each layer of the research onion, developed in this
paper. The key purpose of selecting options from each layer in the onion is
to achieve coherence in research design, with a sufficient level of meth-
odological depth and diversity. As such, researchers need to explicitly
report all important choices, with respect to the options chosen as well as
the coherence between these choices across layers of the onion. This will
also allow for a more structured methodological dialogue across different
approaches in transition studies, by enabling a better articulation of un-
derlying methodological assumptions and choices across different studies.
As detailed, our in-depth review illustrates that this articulation often does
not take place, which impedes such a dialogue. Of course, any attempt to
explicitly design a transition study involving all layers and options may be
a mission impossible and result in overly complicated research designs. As
such, the research onion’s main function is to make transition scholars
aware of and reflect on the methodological dimensions of their research
efforts.
18
In general terms, variance theory aims to explain relationships in terms of
correlations among a set of variables, while process theory aims to explain
change as result of a particular sequence of events unfolding over time (van de
Ven, 2007).
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
11
Third, our analysis suggests that the four transition question types
we identified (section 4.1) can be deductively linked to holistic ana-
lysis, pathway analysis, actor analysis and variance-oriented analysis.
Powerful tools and techniques are available for each of these types of
analysis, but some of them are rarely used in the papers we reviewed.
These tools and techniques can be related to all the identified para-
digms and their ontological and epistemological requirements. There-
fore, this suggestion cannot be considered in support for, or against, a
specific paradigm. For instance, various types of systems modeling are
drawing their pre-assumptions from positivism, interpretivist, prag-
matism and critical realism (see, e.g., Jackson, 2003;Mingers, 2006).
Likewise actor-oriented approaches can adopt different paradigmatic
assumptions (e.g., Pruyt, 2010). For instance, (systems) modeling and
simulation methods
19
can support a pathway and/or actor analysis,
because they especially serve to handle and dissect key features of
transition problems involving non-linear, complex, multi-dimensional,
multi-level and multi-actor processes (e.g., Squazzoni, 2008;Holtz,
2011;Holtz et al., 2015;Halbe et al., 2015;McDowall and Geels, 2017;
Köhler et al., 2018;Walrave and Raven, 2016).
Likewise, policy analysis and scenario planning tools
20
could be uti-
lized more for pathway analysis. As an applied discipline, policy analysis
draws on multiple methods of inquiry and arguments to produce client-
oriented knowledge and advice towards resolving transition policy pro-
blems (e.g., Dunn, 1981;Weimer and Vining, 2017). Also, a scenario ap-
proach serves to develop future situations and describe the (transition)
paths from any given present to these future situations (Pillkahn, 2008;
Raven and Walrave, 2018). As such, scenarios can be instrumental in re-
cognizing, considering and reflecting on the uncertainties inherent in
possible future system discontinuities, to identify the nature and timings of
transition processes, to project the consequences of any particular choice
or policy decision, and to highlight the interactions among several trends
and events in transition processes (e.g., Strauss and Radnor, 2004).
Moreover, methods and frameworks for actor analysis
21
serve to
address questions that involve the role and influence of (networks of)
actors (e.g., users, customers, citizens, firms, and collective actors) on
transition processes. Methods for actor analysis focus on identifying key
characteristics of the various actors involved. These methods can be
classified, theoretically, in terms of perceptions, values, resources and
networks (Hermans and Thissen, 2009). Accordingly, such methods
help transition scholars to capture important (effects arising from)
features of the various actors in a specific transition process.
Finally, we reflect on the potential contribution of mixed methods.
The prevalence rate
22
of mixed research in the social and behavioral
sciences has been estimated to be 15 percent (Alise and Teddlie,
2010).
23
However, our review implies that only 9% of papers in tran-
sition studies apply a mixed research strategy (section 4.4). Although a
mixed strategy is not necessarily always the best choice, given the
preliminary research question, the application of mixed methods in
transition research may offer several benefits (see, e.g., Andersson
et al., 2014;Geels et al., 2016;Markard et al., 2012;Tashakkori and
Teddlie, 2010;Turnheim et al., 2015). These benefits include the ability
to address problems more comprehensively as well as enhanced op-
portunities to generate more valid inferences by triangulating different
sources of data and methods (Howick and Ackermann, 2011;Ivankova
and Kawamura, 2010).
Notably, mixed research can be also conducted at the level of
paradigms and theories. In this respect, future work can and should
engage much more in permutations and cross-overs between existing
paradigms and related theoretical frameworks (Geels, 2010). The ‘new’
and ‘borrowed’ frameworks identified in Table 5 do not necessarily
constitute examples of mixed theorizing, as many of these studies build
on a single theory. Because mixed research is not a novel idea,
24
transition scholars can draw on the experiences of other fields (e.g.,
behavioral sciences and operations research). Accordingly, customizing
and adopting frameworks from other disciplines can be a highly in-
teresting and promising route for future research (e.g., Creswell and
Plano Clark, 2007;Jackson and Keys, 1984;Jackson, 1997a,1997b;
Midgley, 2000;Mingers and White, 2010;Pollack, 2009;Tashakkori
and Teddlie, 2010;Zolfagharian et al., 2018).
Overall, the field of transition studies would greatly benefit from
developing clear protocols for reporting and explaining the methods
used, to increase the quality of transition research efforts and outcomes,
but also to facilitate the replication of findings obtained in empirical
papers. In this respect, the transition research onion provides a platform
for exploring many available methodological options—also to the
benefit of journal reviewers and editors.
6. Concluding remarks
In this paper, we reviewed the methodological foundations of
transition research. Drawing on the so-called transition research onion,
we identified and explained various methodological challenges. The
research onion framework can guide researchers to achieve more co-
herence throughout their research as well as to inform and guide fun-
damental shifts in socio-technical systems. Our review suggests there
are major opportunities to grow the methodological transparency and
diversity of the field of transition studies. Notably, we observed that
many studies fail to articulate the methods used, and also pointed at an
imbalance between qualitative versus quantitative research. It is clear
that the path-dependent nature of any academic field does, over time,
increasingly facilitate the usage of specific methodological options and
demotivate the use of others. This also implies a stabilized preference
for particular types of knowledge, once the field becomes more estab-
lished. Arguably, an unbalanced usage of methodological options can
also signal that particular kinds of scholarly expertise and skills are
lacking. In any case, the plurality of the field of transition studies im-
plies any effort—in terms of data and/or method—to build a broader
and more pluralistic body of knowledge is a worthwhile one.
Conflicts of interests
There are no conflicts of interests.
19
For example, see Pidd (2004) for an overview of systems modeling in
theory and practice, and Holtz et al. (2015) for an appraisal of experiences and
suggestions for modeling transitions.
20
See Amer et al. (2013) and Varum and Melo (2010) for literature reviews of
scenario planning.
21
For example, see Hermans and Thissen (2009) for an overview of methods
and frameworks in this area.
22
Prevalence rate here refers to the proportion of articles using a particular
methodological approach (Alise and Teddlie, 2010).
23
Various numbers (5% to 29%) are reported for the prevalence rates of
mixed method research in the literature. The rates differ based on several
factors including topical content of the journals selected, the operational defi-
nition of ‘mixed methods,’ and the time period examined (Alise and Teddlie,
2010).
24
Creswell and Plano Clark (2007) specified four, often overlapping, time
periods in the emergence and evolution of mixed methods: the formative period
(1950s - 1980s) characterized by the initial interests to use more than one
method in a single study; the paradigm debate period (1970s - late 1990s) that
was dedicated to discussions on the role of paradigms in mixed research; the
procedural development period (late 1980s – 2000) involving a shift towards
the methods or procedures of designing a mixed methods study; and finally the
advocacy of mixed research as a separate design (2000 to date) alongside
quantitative and qualitative approaches. Nowadays, there is an established
community of mixed method researchers with several handbooks, journals and
conferences in different fields including the social, behavioural, educational,
and health sciences.
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
12
Acknowledgements
The authors are grateful for the constructive comments from the the
anonymous reviewers of the Journal of Research Policy. The earlier
draft of this paper benefited from suggestions and comments of the
participants, in particular professor Frank Geels, at SPRU 50th
Anniversary conference - ‘Transforming Innovation’, 7-9 Sept, 2016,
Brighton, UK. The first author would also like to acknowledge the
support by the Rushd Center of Imam Sadiq University (Tehran-Iran)
during conducting this research.
Appendix A. Supplementary data
Supplementary material related to this article can be found, in the
online version, at doi:https://doi.org/10.1016/j.respol.2019.04.012.
References
Alise, M.A., Teddlie, C., 2010. A continuation of the paradigm wars? Prevalence rates of
methodological approaches across the social/behavioral sciences. J. Mix. Methods
Res. 4 (2), 103–126.
Amer, M., Daim, T.U., Jetter, A., 2013. A review of scenario planning. Futures 46, 23–40.
Ancona, D.G., Goodman, P.S., Lawrence, B.S., Tushman, M.L., 2001. Time: a new research
lens. Acad. Manage. Rev. 26 (4), 645–663.
Anderson, P., Tushman, M.L., 1990. Technological discontinuities and dominant designs:
a cyclical model of technological change. Adm. Sci. Q. 35 (4), 604–633.
Andersson, C., Törnberg, A., Törnberg, P., 2014. Societal systems – complex or worse?
Futures 63, 145–157.
Arthur, W.B., Ermoliev, Y.M., Kaniovski, Y.M., 1987. Path-dependent processes and the
emergence of macro-structure. Eur. J. Oper. Res. 30 (3), 294–303.
Asheim, B.T., Isaksen, A., 2002. Regional innovation systems: the integration of local’
sticky’ and global’ ubiquitous’ knowledge. J. Technol. Transf. 27 (1), 77–86.
Audet, R., Guyonnaud, M.F., 2013. Transition in practice and action in research. A French
case study in piloting eco-innovations. Innov.: Eur. J. Social Sci. Res. 26 (4), 398–415.
Axsen, J., Kurani, K.S., 2014. Social influence and proenvironmental behavior: the re-
flexive layers of influence framework. Environ. Plann. B. Plann. Des. 41 (5), 847–862.
Azar, C., Sandén, B.A., 2011. The elusive quest for technology-neutral policies. Environ.
Innov. Soc. Transit. 1 (1), 135–139.
Babbie, E.R., 2010. The Practice of Social Research, 13th ed. Wadsworth, Belmont Calif.
Bakker, S., 2014. Actor rationales in sustainability transitions – interests and expectations
regarding electric vehicle recharging. Environ. Innov. Soc. Transit. 13, 60–74.
Barney, J., 1991. Firm resources and sustained competitive advantage. J. Manage. 17 (1),
99–120.
Bergek, A., Jacobsson, S., Carlsson, B., Lindmark, S., Rickne, A., 2008. Analyzing the
functional dynamics of technological innovation systems: a scheme of analysis.
Research Policy 37 (3), 407–429.
Bijker, W.E., Law, J., 1992. Shaping Technology: Studies in Sociotechnical Change. MIT
Press, Cambridge, Massachusetts.
Bijker, W.E., Hughes, T.P., Pinch, T. (Eds.), 1987. The Social Construction of
Technological Systems: New Directions in the Sociology and History of Technology.
MIT Press, Cambridge, Massachusetts.
Boehnert, J., Lockton, D., Mulder, I., 2018. Editorial: designing for transitions. Storni, C.,
Leahy, K., McMahon, M., Lloyd, P., Bohemia, E. (Eds.), Proceedings of the Design
Research Society 2018 (DRS2018) Volume 3 (Section 9), 892–895.
Boon, F.P., Dieperink, C., 2014. Local civil society based renewable energy organisations
in the Netherlands: exploring the factors that stimulate their emergence and devel-
opment. Energy Policy 69, 297–307.
Bos, J.J., Brown, R.R., 2014. Assessing organisational capacity for transition policy pro-
grams. Technol. Forecast. Social Change 86, 188–206.
Bosman, R., Loorbach, D., Frantzeskaki, N., Pistorius, T., 2014. Discursive regime dy-
namics in the Dutch energy transition. Environ. Innov. Soc. Transit. 13, 45–59.
Brannen, J., 2005. Mixed Methods Research: A Discussion Paper. downloaded on 15 May
2018 from. NCRM Methods Review Papers. ESRC National Centre for Research
Methods. http://eprints.ncrm.ac.uk/89/1/MethodsReviewPaperNCRM-005.pdf).
Briner, R.B., Denyer, D., 2012. Systematic review and evidence synthesis as a practice and
scholarship tool. In: Rousseau, D.M. (Ed.), The Oxford Handbook of Evidence-Based
Management. Oxford University Press, New York, pp. 112–129.
Bryman, A., 1992. Quantitative and qualitative research: further reflections on their in-
tegration. In: Brannen, J. (Ed.), Mixing Methods. Qualitative and Quantitative
Research, Avebury, Aldershot, pp. 57–58.
Bryman, A., 2011. Mission accomplished? Research methods in the first five years of
leadership. Leadership 7 (1), 73–83.
Budde, B., Alkemade, F., Weber, K.M., 2012. Expectations as a key to understanding actor
strategies in the field of fuel cell and hydrogen vehicles. Technol. Forecast. Social
Change 79 (6), 1072–1083.
Burrell, G., Morgan, G., 1979. Sociological Paradigms and Organisational Analysis:
Elements of the Sociology of Corporate Life. Heinemann Educational, London.
Callon, M., 1984. Some elements of a sociology of translation: domestication of the
scallops and the fishermen of St brieuc Bay. Sociol. Rev. 32 (1_suppl), 196–233.
Callon, M., 1998. An essay on framing and overflowing: economic externalities revisited
by sociology. Sociol. Rev. 46 (1_suppl), 244–269.
Carlsson, B., Stankiewicz, R., 1991. On the nature, function and composition of techno-
logical systems. J. Evol. Econ. 1 (2), 93–118.
Carlsson, B., Jacobsson, S., Holmén, M., Rickne, A., 2002. Innovation systems: analytical
and methodological issues. Res. Policy 31 (2), 233–245.
Choi, H., Anadón, L., 2014. the role of the complementary sector and its relationship with
network formation and government policies in emerging sectors: the case of solar
photovoltaics between 2001 and 2009. Technol. Forecast. Social Change 82, 80–94.
Christensen, C.M., 1997. The Innovator’S Dilemma: When New Technologies Cause Great
Firms to Fail. Harvard Business School Press, Boston, Massachusetts.
Coenen, L., Benneworth, P., Truffer, B., 2012. Toward a spatial perspective on sustain-
ability transitions. Res. Policy 41 (6), 968–979.
Cooke, P., 2002. Knowledge Economies: Clusters, Learning and Co-Operative Advantage.
Routledge, London.
Cooke, P., Heidenreich, M., Braczyk, H.-J. (Eds.), 2004. Regional Innovation Systems: The
Role of Governances in a Globalized World, 2nd ed. Routledge, London.
Coutard, O., 1999. The Governance of Large Technical Systems. Routledge, London.
Cowan, R., 1990. Nuclear power reactors: a study in technological lock-in. J. Econ. Hist.
50 (3), 541–567.
Creswell, J.W., Plano Clark, V.L., 2007. Designing and Conducting Mixed Methods
Research. SAGE, Thousand Oaks, Calif.
Crotty, M., 1998. The Foundations of Social Research: Meaning and Perspective in the
Research Process. SAGE Publications, Thousand Oaks, Calif.
David, P.A., 1985. Clio and the economics of QWERTY. Am. Econ. Rev. 75 (2), 332–337.
Davis, K., Mazzuchi, T., Sarkani, S., 2013. Architecting technology transitions: a sus-
tainability‐oriented sociotechnical approach. Sys. Eng. 16 (2), 193–212.
de Haan, F.J., Rotmans, J., 2011. Patterns in transitions: understanding complex chains of
change. Technol. Forecast. Social Change 78 (1), 90–102.
de Haan, F.J., Ferguson, B.C., Adamowicz, R.C., Johnstone, P., Brown, R.R., Wong, T.H.F.,
2014. The needs of society: a new understanding of transitions, sustainability and
liveability. Technol. Forecast. Social Change 85, 121–132.
Denzin, N.K., Lincoln, Y.S. (Eds.), 2011. The Sage Handbook of Qualitative Research, 4th
ed. SAGE Publications, Thousand Oaks, Calif.
Diaz, M., Darnhofer, I., Darrot, C., Beuret, J.-E., 2013. Green tides in brittany: what can
we learn about niche-regime interactions? Environ. Innov. Soc. Transit. 8, 62–75.
Domènech, L., March, H., Vallès, M., Saurí, D., 2015. Learning processes during regime
shifts: empirical evidence from the diffusion of greywater recycling in Spain. Environ.
Innov. Soc. Transit. 15, 26–41.
Dosi, G., 1982. Technological paradigms and technological trajectories: a suggested in-
terpretation of the determinants and directions of technical change. Res. Policy 11
(3), 147–162.
Dunn, W.M., 1981. An Introduction to Public Policy Analysis. Prentice Hall, Upper Saddle
River, NJ.
Elzen, B., Geels, F.W., Leeuwis, C., van Mierlo, B., 2011. Normative contestation in
transitions ‘in the making’: animal welfare concerns and system innovation in pig
husbandry. Res. Policy 40 (2), 263–275.
Fagerberg, J., Fosaas, M., Sapprasert, K., 2012. Innovation: exploring the knowledge base.
Res. Policy 41 (7), 1132–1153.
Flood, R.L., 1995. Total systems intervention (TSI): a reconstitution. J. Oper. Res. Soc. 46
(2), 174–191.
Frantzeskaki, N., Kabisch, N., 2016. Designing a knowledge co-production operating
space for urban environmental governance—Lessons from Rotterdam, Netherlands
and Berlin, Germany. Environ. Sci. Policy 62, 90–98.
Freeman, C., Louçã, F., 2001. As Time Goes by: From the Industrial Revolutions to the
Information Revolution. Oxford University Press, Oxford.
Frieler, K., Levermann, A., Elliott, J., Heinke, J., Arneth, A., Bierkens, M.F.P., Ciais, P.,
Clark, D.B., Deryng, D., Döll, P., Falloon, P., Fekete, B., Folberth, C., Friend, A.D.,
Gellhorn, C., Gosling, S.N., Haddeland, I., Khabarov, N., Lomas, M., Masaki, Y.,
Nishina, K., Neumann, K., Oki, T., Pavlick, R., Ruane, A.C., Schmid, E., Schmitz, C.,
Stacke, T., Stehfest, E., Tang, Q., Wisser, D., Huber, V., Piontek, F., Warszawski, L.,
Schewe, J., Lotze-Campen, H., Schellnhuber, H.J., 2015. A framework for the cross-
sectoral integration of multi-model impact projections: Land use decisions under
climate impacts uncertainties. Earth Syst. Dyn. 6 (2), 447–460.
Fuenfschilling, L., Truffer, B., 2014. The structuration of socio-technical
regimes—Conceptual foundations from institutional theory. Res. Policy 43 (4),
772–791.
Garud, R., Gehman, J., 2012. Metatheoretical perspectives on sustainability journeys:
evolutionary, relational and durational. Res. Policy 41 (6), 980–995.
Geels, F.W., 2002. Technological transitions as evolutionary reconfiguration processes: a
multi-level perspective and a case-study. Res. Policy 31 (8-9), 1257–1274.
Geels, F.W., 2005. Co-evolution of technology and society: the transition in water supply
and personal hygiene in the Netherlands (1850–1930)—A case study in multi-level
perspective. Technol. Soc. 27 (3), 363–397.
Geels, F.W., 2009. Foundational ontologies and multi-paradigm analysis, applied to the
socio-technical transition from mixed farming to intensive pig husbandry (1930-
1980). Technol. Anal. Strateg. Manage. 21 (7), 805–832.
Geels, F.W., 2010. Ontologies, socio-technical transitions (to sustainability), and the
multi-level perspective. Res. Policy 39 (4), 495–510.
Geels, F.W., 2011. The multi-level perspective on sustainability transitions: responses to
seven criticisms. Environ. Innov. Soc. Transit. 1 (1), 24–40.
Geels, F.W., Hekkert, M.P., Jacobsson, S., 2008. The dynamics of sustainable innovation
journeys. Technol. Anal. Strateg. Manage. 20 (5), 521–536.
Geels, F.W., Berkhout, F., van Vuuren, D.P., 2016. Bridging analytical approaches for low-
carbon transitions. Nat. Clim. Change 6 (6), 576–583.
Genus, A., Coles, A.-M., 2008. Rethinking the multi-level perspective of technological
transitions. Res. Policy 37 (9), 1436–1445.
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
13
George, J., Jones, G.R., 2000. The role of time in theory and theory building. J. Manage.
26 (4), 657–684.
Ginsberg, A., Venkatraman, N., 1985. Contingency perspectives of organizational
strategy: a critical review of the empirical research. Acad. Manage. Rev. 10 (3),
421–434.
Grin, J., Rotmans, J., Schot, J.W. (Eds.), 2010. Transitions to Sustainable Development:
New Directions in the Study of Long Term Transformative Change. Routledge,
London.
Guba, E.G., Lincoln, Y.S., 1989. Fourth Generation Evaluation. SAGE Publications,
Newbury Park, Calif.
Halbe, J., Reusser, D.E., Holtz, G., Haasnoot, M., Stosius, A., Avenhaus, W., Kwakkel, J.H.,
2015. Lessons for model use in transition research: a survey and comparison with
other research areas. Environ. Innov. Soc. Transit. 15, 194–210.
Hanson, D., Grimmer, M., 2007. The mix of qualitative and quantitative research in major
marketing journals, 1993-2002. Eur. J. Mark. 41 (1/2), 58–70.
Haxeltine, A., Whitmarsh, L., Bergman, N., Rotmans, J., Schilperoord, M., Köhler, J.,
2008. A conceptual framework for transition modelling. Int. J. Innov. Sustainable
Dev. 3 (1/2), 93–114.
Hekkert, M.P., Suurs, R.A.A., Negro, S.O., Kuhlmann, S., Smits, R.E.H.M., 2007. Functions
of innovation systems: a new approach for analysing technological change. Technol.
Forecast. Soc. Change 74 (4), 413–432.
Hellsmark, H., Jacobsson, S., 2009. Opportunities for and limits to academics as system
builders—The case of realizing the potential of gasified biomass in Austria. Energy
Policy 37 (12), 5597–5611.
Hermans, L.M., Thissen, W.A.H., 2009. Actor analysis methods and their use for public
policy analysts. Eur. J. Oper. Res. 196 (2), 808–818.
Hess, D.J., Mai, Q.D., 2014. Renewable electricity policy in Asia: a qualitative com-
parative analysis of factors affecting sustainability transitions. Environ. Innov. Soc.
Transit. 12, 31–46.
Holland, J.H., 1995. Hidden Order: How Adaptation Builds Complexity. Addison-Wesley,
Reading, Mass.
Holtz, G., 2011. Modelling transitions: an appraisal of experiences and suggestions for
research. Environ. Innov. Soc. Transit. 1 (2), 167–186.
Holtz, G., Alkemade, F., Haan, F.Jd., Köhler, J., Trutnevyte, E., Luthe, T., Halbe, J.,
Papachristos, G., Chappin, E., Kwakkel, J., Ruutu, S., 2015. Prospects of modelling
societal transitions: position paper of an emerging community. Environ. Innov. Soc.
Transit. 17, 41–58.
Howick, S., Ackermann, F., 2011. Mixing OR methods in practice: past, present and future
directions. Eur. J. Oper. Res. 215 (3), 503–511.
Hughes, T.P., 1983. Networks of Power: Electrification in Western Society, 1880-1930.
John Hopkins University Press, Baltimore.
Hughes, T.P., 1987. The evolution of large technological systems. In: Bijker, W.E.,
Hughes, T.P., Pinch, T. (Eds.), The Social Construction of Technological Systems. New
Directions in the Sociology and History of Technology. MIT Press, Cambridge,
Massachusetts, pp. 51–82.
Hultman, N.E., Malone, E.L., Runci, P., Carlock, G., Anderson, K.L., 2012. Factors in low-
carbon energy transformations: comparing nuclear and bioenergy in Brazil, Sweden,
and the United States. Energy Policy 40, 131–146.
Hurlbert, M.A., 2011. Evaluating climate justice – attitudes and opinions of individual
stakeholders in the United Nations framework climate change convention Conference
of the parties. J. Integr. Environ. Sci. 8 (4), 267–286.
Hurmerinta-Peltomäki, L., Nummela, N., 2006. Mixed methods in international business
research: a value-added perspective. Manage. Int. Rev. 46 (4), 439–459.
Hutchinson, S.R., Lovell, C.D., 2004. A review of methodological characteristics of re-
search published in key journals in higher education: implications for graduate re-
search training. Res. Higher Edu. 45 (4), 383–403.
Irwin, T., Kossoff, G., Tonkinwise, C., Scupelli, P., 2015. Transition Design: A New Area of
Design Research, Practice and Study That Proposes Design-Led Societal Transition
Toward More Sustainable Futures. Carnegie Mellon School of Design, Pittsburgh, PA.
Ivankova, N., Kawamura, Y., 2010. Emerging trends in the utilization of integrated de-
signs in the social, behavioral, and health sciences. In: Tashakkori, A., Teddlie, C.
(Eds.), SAGE Handbook of Mixed Methods in Social & Behavioral Research, 2nd ed.
SAGE Publications, Thousand Oaks, CA, pp. 581–612.
Jackson, M.C., 1997a. Critical systems thinking and information systems research. In:
Mingers, J., Stowell, F.A. (Eds.), Information Systems. An Emerging Discipline?
McGraw-Hill, London, pp. 201–230.
Jackson, M.C., 1997b. Pluralism in systems thinking and practice. In: Mingers, J., Gill, A.
(Eds.), Multimethodology. The Theory and Practice of Integrating Management
Science Methodologies. John Wiley & Sons, Chichester, pp. 345–378.
Jackson, M.C., 2003. Systems Thinking: Creative Holism for Managers. Wiley, Chichester.
Jackson, M.C., Keys, P., 1984. Towards a system of systems methodologies. J. Oper. Res.
Soc. 35 (6), 473–486.
Jacobsson, S., Bergek, A., 2006. A framework for guiding policy-makers intervening in
emerging innovation systems in ‘catching-up’ countries. Eur. J. Dev. Res. 18 (4),
687–707.
Jhagroe, S., Loorbach, D., 2015. See no evil, hear no evil: the democratic potential of
transition management. Environ. Innov. Soc. Transit. 15, 65–83.
Jørgensen, U., 2012. Mapping and navigating transitions—The multi-level perspective
compared with arenas of development. Res. Policy 41 (6), 996–1010.
Johnson, F.X., Silveira, S., 2014. Pioneer countries in the transition to alternative trans-
port fuels: comparison of ethanol programmes and policies in Brazil, Malawi and
Sweden. Environ. Innov. Soc. Transit. 11, 1–24.
Johnson, R.B., Onwuegbuzie, A.J., Turner, L.A., 2007. Toward a definition of mixed
methods research. J. Mix. Methods Res. 1 (2), 112–133.
Jolivet, E., Heiskanen, E., 2010. Blowing against the wind—An exploratory application of
actor network theory to the analysis of local controversies and participation processes
in wind energy. Energy Policy 38 (11), 6746–6754.
Kauffman, S., 1995. At Home in the Universe: The Search for the Laws of Self-
Organization and Complexity. Oxford University Press, New York.
Kemp, R., Schot, J.W., Hoogma, R., 1998. Regime shifts to sustainability through pro-
cesses of niche formation: the approach of strategic niche management. Technol.
Analy. Strateg. Manage. 10 (2), 175–198.
Kern, F., 2012. the discursive politics of governing transitions towards sustainability: the
UK carbon trust. Int. J. Sustainable Dev. 15 (1/2), 90–106.
Kiss, B., Neij, L., 2011. The importance of learning when supporting emergent technol-
ogies for energy efficiency—A case study on policy intervention for learning for the
development of energy efficient windows in Sweden. Energy Policy 39 (10),
6514–6524.
Klitkou, A., Bolwig, S., Hansen, T., Wessberg, N., 2015. the role of lock-in mechanisms in
transition processes: the case of energy for road transport. Environ. Innov. Soc.
Transit. 16, 22–37.
Köhler, J., Haan, F.Jd., Holtz, G., Kubeczko, K., Moallemi, E., Papachristos, G., Chappin,
E., 2018. Modelling sustainability transitions: an assessment of approaches and
challenges. J. Artif. Societies Soc. Simulation 21 (1).
Köhler, J., Geels, F.W., Kern, F., Onsongo, E., Wieczorek, A., 2017. A Research Agenda for
the Sustainability Transitions Research Network (downloaded on 24 January 2018
from. https://transitionsnetwork.org/wp-content/uploads/2018/01/STRN_
Research_Agenda_2017.pdf).
Köhler, J., Geels, F.W., Kern, F., Markard, J., Onsongo, E., Wieczorek, A., Alkemade, F.,
Avelino, F., Bergek, A., Boons, F., Fünfschilling, L., Hess, D., Holtz, G., Hyysalo, S.,
Jenkins, K., Kivimaa, P., Martiskainen, M., McMeekin, A., Mühlemeier, M.S., Nykvist
Bjorn, Pel Bonno, Raven, R., Rohracher, H., Sandén, B., Schot, J., Sovacool, B.,
Turnheim Bruno, Welch Dan, Wells, P., 2019. An agenda for sustainability transitions
research. State of the art and future directions. Environ. Innov. Soc. Transit. 1–32
(Accepted/In press).
La Porte, T.R., 1991. Social Responses to Large Technical Systems: Control or
Anticipation. Springer Sciences+Business Media, B.V, Dordrecht.
Law, J., Hassard, J., 1999. Actor Network Theory and After. Blackwell, Oxford.
Lawrence, T.B., Suddaby, R., 2006. Institutions and institutional work. In: Clegg, S.R.,
Hardy, C., Lawrence, B.S., Nord, W.R. (Eds.), The Sage Handbook of Organization
Studies, 2nd ed. SAGE Publications, Thousand Oaks, CA, pp. 215–254.
Lincoln, Y.S., Guba, E.G., 1985. Naturalistic Inquiry. SAGE Publications, Beverly Hills,
Calif.
Loorbach, D., Frantzeskaki, N., Thissen, W.H., 2011. A transition research perspective on
governance for sustainability. In: In: Jaeger, C.C., Tàbara, J.D., Jaeger, J. (Eds.),
European Research on Sustainable Development Volume 1. Transformative science
approaches for sustainability. Springer, pp. 73–90.
Loorbach, D., Frantzeskaki, N., Avelino, F., 2017. Sustainability transitions research:
transforming science and practice for societal change. Annu. Rev. Environ. Resour. 42
(1), 599–626.
March, S.T., Smith, G.F., 1995. Design and natural science research on information
technology. Decis. Support Syst. 15, 251–266.
Markard, J., Truffer, B., 2008. Technological innovation systems and the multi-level
perspective: towards an integrated framework. Res. Policy 37 (4), 596–615.
Markard, J., Raven, R., Truffer, B., 2012. Sustainability transitions: an emerging field of
research and its prospects. Res. Policy 41 (6), 955–967.
Marsland, N., Wilson, I., Abeyasekera, S., Kleih, U., 2000. A methodological framework
for combining quantitative and qualitative survey methods. An Output from the
DFID-Funded Natural Resources Systems Programme (Socio-Economic
Methodologies Component) Project R7033 Titled Methodological Framework
Integrating Qualitative and Quantitative Approaches for Socio-Economic Survey
Work. Statistical Services Centre, University of Reading.
Martens, P., Rotmans, J., 2005. Transitions in a globalising world. Futures 37 (10),
1133–1144.
Martin, N., Rice, J., 2015. Improving Australia’s renewable energy project policy and
planning: a multiple stakeholder analysis. Energy Policy 84, 128–141.
Mattes, J., Huber, A., Koehrsen, J., 2015. Energy transitions in small-scale regions – what
we can learn from a regional innovation systems perspective. Energy Policy 78,
255–264.
Mayntz, R., Hughes, T.P. (Eds.), 1988. The Development of Large Technical Systems.
Westview Press, Boulder, Colorado.
McDowall, W., Geels, F.W., 2017. Ten challenges for computer models in transitions re-
search: commentary on holtz et al. Environ. Innov. Soc. Transit. 22, 41–49.
McGahan, A.M., Argyres, N., Baum, J.A.C., 2004. Context, technology and strategy: for-
ging new perspectives on the industry life cycle. In: Baum, J.A.C., McGahan, A.M.
(Eds.), Business Strategy Over the Industry Lifecycle. Emerald Group Publishing
Limited, pp. 1–21.
Meadowcroft, J., 2011. Engaging with the politics of sustainability transitions. Environ.
Innov. Soc. Transit. 1 (1), 70–75.
Midgley, G., 2000. Systemic Intervention: Philosophy, Methodology, and Practice.
Springer, Boston, MA.
Mingers, J., 2006. Realising Systems Thinking: Knowledge and Action in Management
Science. Springer Science & Business Media, New York.
Mingers, J., White, L., 2010. A review of the recent contribution of systems thinking to
operational research and management science. Eur. J. Oper. Res. 207 (3),
1147–1161.
Mintzberg, H., 2005. Developing theory about the development of theory. In: Smith, K.G.,
Hitt, M.A. (Eds.), Great Minds in Management. The Process of Theory Development.
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
14
Oxford University Press, Oxford, pp. 355–372.
Molina-Azorín, J.F., 2009. Understanding how mixed methods research is undertaken
within a specific research community: the case of business studies. Int. J. Mult. Res.
Approaches 3 (1), 47–57.
Moore, K., Kleinman, D.L., Hess, D.J., Frickel, S., 2011. Science and neoliberal globali-
zation: a political sociological approach. Theory Soc. 40 (5), 505–532.
Naus, J., Spaargaren, G., van Vliet, B.J.M., van der Horst, H.M., 2014. Smart grids, in-
formation flows and emerging domestic energy practices. Energy Policy 68, 436–446.
Negro, S.O., Hekkert, M.P., Smits, R.E., 2007. Explaining the failure of the Dutch in-
novation system for biomass digestion—A functional analysis. Energy Policy 35 (2),
925–938.
Nelson, R.R., Winter, S.G., 1982. An Evolutionary Theory of Economic Change. Belknap
Press of Havard University Press, Cambridge, Massachusetts.
Niglas, K., 2010. The multidimensional model of research methodology: an integrated set
of continua. In: Tashakkori, A., Teddlie, C. (Eds.), SAGE Handbook of Mixed Methods
in Social & Behavioral Research, 2nd ed. SAGE Publications, Thousand Oaks, CA, pp.
215–236.
Normann, H.E., 2015. the role of politics in sustainable transitions: the rise and decline of
offshore wind in Norway. Environ. Innov. Soc. Transit. 15, 180–193.
Paredis, E., 2011. Sustainability transitions and the nature of technology. Foundations
Sci. 16 (2-3), 195–225.
Patton, M.Q., 1990. Qualitative Research & Evaluation Methods: Integrating Theory and
Practice, 2nd ed. SAGE Publications, Thousand Oaks, California.
Pel, B., 2014. Intersections in system innovation: a nested-case methodology to study co-
evolving innovation journeys. Technol. Anal. Strateg. Manage. 26 (3), 307–320.
Perez, C., 2002. Technological Revolutions and Financial Capital: The Dynamics of
Bubbles and Golden Ages. Edward Elgar Pub, Cheltenham.
Pidd, M., 2004. Systems Modelling: Theory and Practice. Wiley, Chichester.
Pillkahn, U., 2008. Using Trends and Scenarios as Tools for Strategy Development.
Publicis Corporate Publishing, Erlangen, Germany.
Pollack, J., 2009. Multimethodology in series and parallel: strategic planning using hard
and soft OR. J. Oper. Res. Soc. 60 (2), 156–167.
Poole, M.S., van de Ven, A.H., Dooley, K., Holmes, M.E., 2000. Organizational Change
and Innovation Processes: Theory and Methods for Research. Oxford University Press,
Oxford.
Prigogine, I., Stengers, I., 1984. Order Out of Chaos: Man’S New Dialogue Nature.
BANTAM Books, New York.
Pruyt, E., 2010. Multi‐actor systems and ethics. Int. Trans. Oper. Res. 17 (4), 507–520.
Raven, R., 2007. Co-evolution of waste and electricity regimes: multi-regime dynamics in
the Netherlands (1969-2003). Energy Policy 35 (4), 2197–2208.
Raven, R., Walrave, B., 2018. Overcoming transformational failures in the dynamics of
technological innovation systems. Technol. Forecast. Social Change (Accepted/In
press). https://www.sciencedirect.com/science/article/pii/S0040162516308460.
Ravetz, J.R., 1999. What is post-normal science? Futures 31 (7), 647–653.
Reckwitz, A., 2002. Toward a theory of social practices. Eur. J. Social Theory 5 (2),
243–263.
Reed, M., 2005. Reflections on the ‘realist turn’ in organization and management studies.
J. Manage. Stud. 42 (8), 1621–1644.
Rip, A., Kemp, R., 1998. Technological change. In: In: Rayner, S., Malone, E.L. (Eds.),
Human Choice and Climate Change Volume 2. Battelle Press, Columbus, Ohio, pp.
327–339.
Rodrigo, P., Muñoz, P., Wright, A., 2015. Transitions dynamics in context: key factors and
alternative paths in the sustainable development of nations. J. Cleaner Prod. 94,
221–234.
Rogge, K.S., Hoffmann, V.H., 2010. The impact of the EU ETS on the sectoral innovation
system for power generation technologies – findings for Germany. Energy Policy 38
(12), 7639–7652.
Rosenbloom, D., Meadowcroft, J., 2014. The journey towards decarbonization: exploring
socio-technical transitions in the electricity sector in the province of Ontario (1885-
2013) and potential low-carbon pathways. Energy Policy 65, 670–679.
Rotmans, J., Loorbach, D., 2009. Complexity and transition management. J. Ind. Ecol. 13
(2), 184–196.
Rotmans, J., Kemp, R., van Asselt, M., 2001. More evolution than revolution: transition
management in public policy. Foresight 3 (1), 15–31.
Sabatier, P.A., Jenkins-Smith, H., 1999. The advocacy coalition framework: an assess-
ment. In: Sabatier, P.A., Weible, C.M. (Eds.), Theories of the Policy Process, 3rd ed.
Westview Press, Boulder, Colorado, pp. 117–166.
Saldaña, J., 2015. The Coding Manual for Qualitative Researchers, 3rd ed. SAGE, Los
Angeles.
Sarasini, S., 2013. Institutional work and climate change: corporate political action in the
Swedish electricity industry. Energy Policy 56, 480–489.
Saunders, M., Lewis, P., Thornhill, A., 2015. Research Methods for Business Students, 6th
ed. Pearson, London.
Sayer, A., 1992. Method in Social Science: A Realist Approach, 2nd ed. Routledge,
London.
Scandura, T.A., Williams, E.A., 2000. Research methodology in management: current
practices, trends, and implications for future research. Acad. Manage. J. 43 (6),
1248–1264.
Schatzki, T.R., 1996. Social Practices: A Wittgensteinian Approach to Human Activity and
the Social. Cambridge University Press, Cambridge.
Schmidt, T.S., Schneider, M., Hoffmann, V.H., 2012. Decarbonising the power sector via
technological change – differing contributions from heterogeneous firms. Energy
Policy 43, 466–479.
Scholz, R.W., 2017. The normative dimension in transdisciplinarity, transition
management, and transformation sciences. New Roles Sci. Universities Sustainable
Transitioning Sustainability 9 (6).
Schot, J.W., 1998. The usefulness of evolutionary models for explaining innovation. The
case of the Netherlands in the nineteenth century. Hist. Technol. 14 (3), 173–200.
Schot, J.W., Hoogma, R., Elzen, B., 1994. Strategies for shifting technological systems.
Futures 26 (10), 1060–1076.
Scott, R.W., 1995. Institutions and Organizations. Ideas, Interests and Identities. SAGE
Publications, Thousand Oaks, CA.
Scrase, I., Smith, A., 2009. The (non-)politics of managing low carbon socio-technical
transitions. Environ. Polit. 18 (5), 707–726.
Shove, E., 2003. Comfort, Cleanliness and Convenience: The Social Organization of
Normality. Berg, Oxford.
Shove, E., Walker, G., 2007. Caution! Transitions ahead: politics, practice, and sustainable
transition management. Environ. Plann. A: Economy Space 39 (4), 763–770.
Shove, E., Walker, G., 2010. Governing transitions in the sustainability of everyday life.
Res. Policy 39 (4), 471–476.
Shove, E., Pantzar, M., Watson, M., 2012. The Dynamics of Social Practice: Everyday Life
and How It Changes. SAGE Publications Ltd.
Simon, H.A., 1969. The Sciences of the Artificial. MIT Press, Cambridge, Massachusetts.
Smith, A., Stirling, A., Berkhout, F., 2005. The governance of sustainable socio-technical
transitions. Res. Policy 34 (10), 1491–1510.
Smith, A., Voß, J.-P., Grin, J., 2010. Innovation studies and sustainability transitions: the
allure of the multi-level perspective and its challenges. Res. Policy 39 (4), 435–448.
Smits, R.E., Kuhlmann, S., 2004. The rise of systemic instruments in innovation policy.
Int. J. Foresight Innov. Policy 1 (1/2), 4–32.
Sorrell, S., 2015. Reducing energy demand: a review of issues, challenges and approaches.
Renewable Sustainable Energy Rev. 47, 74–82.
Sovacool, B.K., Hess, D.J., 2017. Ordering theories: typologies and conceptual frame-
works for sociotechnical change. Soc. Stud. Sci. 47 (5), 703–750.
Sperling, K., Hvelplund, F., Mathiesen, B.V., 2010. Evaluation of wind power planning in
Denmark – towards an integrated perspective. Energy 35 (12), 5443–5454.
Squazzoni, F., 2008. A (computational) social science perspective on societal transitions.
Comput. Math. Organ. Theory 14 (4), 266–282.
Strauss, J.D., Radnor, M., 2004. Roadmapping for dynamic and uncertain environments.
Res. Technol. Manage. 47 (2), 51–57.
Summerton, J. (Ed.), 1994. Changing Large Technical Systems. Westview Press, Boulder/
San Francisco, Oxford.
Tashakkori, A., Teddlie, C., 1998. Mixed Methodology: Combining Qualitative and
Quantitative Approaches. SAGE, Thousand Oaks, CA.
Tashakkori, A., Teddlie, C. (Eds.), 2010. SAGE Handbook of Mixed Methods in Social &
Behavioral Research, 2nd ed. SAGE Publications, Thousand Oaks, CA.
Teddlie, C., Tashakkori, A., 2009. Foundations of Mixed Methods Research: Integrating
Quantitative and Qualitative Approaches in the Social and Behavioral Sciences. SAGE
Publications, Thousand Oaks, CA.
Tranfield, D., Denyer, D., Smart, P., 2003. Towards a methodology for developing evi-
dence-informed management knowledge by means of systematic review. British J.
Manage. 14 (3), 207–222.
Trutnevyte, E., Barton, J., O’Grady, Á., Ogunkunle, D., Pudjianto, D., Robertson, E., 2014.
Linking a storyline with multiple models: a cross-scale study of the UK power system
transition. Technol. Forecast. Soc. Change 89, 26–42.
Trutnevyte, E., Strachan, N., Dodds, P.E., Pudjianto, D., Strbac, G., 2015. Synergies and
trade-offs between governance and costs in electricity system transition. Energy
Policy 85, 170–181.
Turnheim, B., Berkhout, F., Geels, F.W., Hof, A., McMeekin, A., Nykvist, B., van Vuuren,
D.P., 2015. Evaluating sustainability transitions pathways: bridging analytical ap-
proaches to address governance challenges. Global Environ. Change 35, 239–253.
van Aken, J.E., Romme, A.G.L., 2012. A design science approach to evidence-based
management. In: Rousseau, D.M. (Ed.), The Oxford Handbook of Evidence-Based
Management. Oxford University Press, New York, pp. 43–57.
van Burg, E., Romme, A.G.L., 2014. Creating the future together: toward a framework for
research synthesis in entrepreneurship. Entrep. Theory Pract. 38, 369–397.
van de Ven, A.H., 2007. Engaged Scholarship: A Guide for Organizational and Social
Research. Oxford University Press, Oxford.
van den Bergh, J.C.J.M., Gowdy, J.M., 2000. Evolutionary theories in environmental and
resource economics: approaches and applications. Environ. Resour. Econ. 17 (1),
37–57.
van der Brugge, R., van Raak, R., 2007. Facing the adaptive management challenge: in-
sights from transition management. Ecol. Soc. 12 (2).
van Lente, H., Rip, A., 1998. The rise of membrane technology: from rhetorics to social
reality. Soc. Stud. Sci. 28 (2), 221–254.
Varum, C.A., Melo, C., 2010. Directions in scenario planning literature – a review of the
past decades. Futures 42 (4), 355–369.
Vasileiadou, E., Safarzyńska, K., 2010. Transitions: taking complexity seriously. Futures
42 (10), 1176–1186.
Voronov, M., Vince, R., 2012. Integrating emotions into the analysis of institutional work.
Acad. Manage. Rev. 37 (1), 58–81.
Wakiyama, T., Zusman, E., Monogan, J.E., 2014. Can a low-carbon-energy transition be
sustained in post-Fukushima Japan? Assessing the varying impacts of exogenous
shocks. Energy Policy 73, 654–666.
Walrave, B., Raven, R., 2016. Modelling the dynamics of technological innovation sys-
tems. Res. Policy 45 (9), 1833–1844.
Walrave, B., Talmar, M., Podoynitsyna, K.S., Romme, A.G.L., Verbong, G.P.J., 2018. A
multi-level perspective on innovation ecosystems for path-breaking innovation.
Technol. Forecast. Soc. Change (Accepted/In press).
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
15
Weber, M., 1978. Economy and Society: An Outline of Interpretive Sociology. University
of California Press, Berkeley.
Weimer, D.L., Vining, A.R., 2017. Policy Analysis: Concepts and Practice. Routledge, New
York.
Wells, R.S., Kolek, E.A., Williams, E.A., Saunders, D.B., 2015. “How we know what we
know”: a systematic comparison of research methods employed in higher education
journals, 1996-2000 v. 2006-2010. J. Higher Educ. 86 (2), 171–198.
Wernerfelt, B., 1984. A resource-based view of the firm. Strateg. Manage. J. 5 (2),
171–180.
Wesseling, J.H., Farla, J., Hekkert, M.P., 2015. Exploring car manufacturers’ responses to
technology-forcing regulation: the case of California’s ZEV mandate. Environ. Innov.
Soc. Transit. 16, 87–105.
Wittmayer, J.M., Schäpke, N., 2014. Action, research and participation: roles of re-
searchers in sustainability transitions. Sustainability Sci. 9 (4), 483–496.
Wittmayer, J.M., Schäpke, N., van Steenbergen, F., Omann, I., 2014. Making sense of
sustainability transitions locally. How action research contributes to addressing so-
cietal challenges. Crit. Policy Stud. 8 (4), 465–485.
Yuan, J., Xu, Y., Hu, Z., 2012. Delivering power system transition in China. Energy Policy
50, 751–772.
Zolfagharian, M., Romme, A.G.L., Walrave, B., 2018. Why, when, and how to combine
system dynamics with other methods: towards an evidence-based framework. J.
Simulation 12 (2), 1–17.
M. Zolfagharian, et al. Research Policy 48 (2019) 103788
16