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A multi-level perspective on innovation ecosystems for path-breaking innovation



Path-breaking innovations are increasingly developed and commercialized by networks of co-creating actors, called innovation ecosystems. Previous work in this area demonstrates that the ‘internal’ alignment of actors is critical to value creation in the innovation ecosystem. However, the literature has largely overlooked that the success of an innovation ecosystem also depends on its ‘external’ viability, determined by the broader socio-technical environment. That is, path-breaking innovations inherently challenge the prevailing socio-technical regime in a domain (e.g., established rules, artifacts and habits) that tends to be resistant to change. Overcoming this resistance is a major challenge for ventures pioneering path-breaking innovations. The paper contributes to the literature on innovation ecosystems by explicitly considering the socio-technical viability of the innovation ecosystem around a path-breaking innovation. In particular, we theorize about the objects of manipulation in an innovation ecosystem and discuss the strategies that a focal venture, orchestrating the innovation ecosystem, can employ in manipulating these objects so as to increase the socio-technical viability of the ecosystem. We arrive at a multi-level perspective on innovation ecosystem development that integrates internal alignment and external viability and informs a research agenda for future studies in this field.
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Bob Walrave
Madis Talmar
Ksenia S. Podoynitsyna
A. Georges L. Romme
Geert P. J. Verbong
All authors are affiliated with:
Eindhoven University of Technology
Department of Industrial Engineering & Innovation Sciences
P.O. Box 513, 5600 MB Eindhoven
The Netherlands
E-mail addresses:
Accepted for publication in Technological Forecasting and Social Change
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Path-breaking innovations are increasingly developed and commercialized by networks of
co-creating actors, called innovation ecosystems. Previous work in this area demonstrates
that the ‘internal’ alignment of actors is critical to value creation in the innovation
ecosystem. However, the literature has largely overlooked that the success of an innovation
ecosystem also depends on its ‘external’ viability, determined by the broader socio-technical
environment. That is, path-breaking innovations inherently challenge the prevailing socio-
technical regime in a domain (e.g., established rules, artifacts and habits) that tends to be
resistant to change. Overcoming this resistance is a major challenge for ventures pioneering
path-breaking innovations. The paper contributes to the literature on innovation ecosystems
by explicitly considering the socio-technical viability of the innovation ecosystem around a
path-breaking innovation. In particular, we theorize about the objects of manipulation in an
innovation ecosystem and discuss the strategies that a focal venture, orchestrating the
innovation ecosystem, can employ in manipulating these objects so as to increase the socio-
technical viability of the ecosystem. We arrive at a multi-level perspective on innovation
ecosystem development that integrates internal alignment and external viability and informs
a research agenda for future studies in this field.
Keywords: innovation ecosystem, path-breaking innovation, ecosystem strategy, strategic
niche management, multi-level perspective, objects of manipulation.
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Across industries, there is an ongoing transformation from separate products and services
toward complex value propositions which are accomplished by integrating complementary
products and services of different actors (Adner, 2006, 2012; Podoynitsyna et al., 2013).
Referring to such a network where actors collectively create, deliver and appropriate value as
an innovation ecosystem (henceforth: ecosystem) (Adner, 2012; Nambisan and Sawhney,
2011), innovation research has emphasized the importance for firms to consider an explicit
ecosystem strategy (Adner, 2012, 2016). Correspondingly, in addition to managing their own
technological and commercial challenges, an innovating venture needs also to consider how
to align the different and often diverse actors supplying the complementary offerings towards
accomplishing an integrated value proposition (Adner, 2016; Adner et al., 2013; Koenig,
2012; Williamson and De Meyer, 2012). Previous ecosystem research has identified several
strategies that a focal venture can pursue in creating such an alignment, including defining
the respective modularity in the ecosystem (Nambisan and Sawhney, 2011), coordinating
value creation activities across actors (Williamson and De Meyer, 2012), establishing
technological standards (Koenig, 2012), and creating mechanisms for fair value appropriation
(Iansiti and Levien, 2004). We refer to these activities of the focal venture towards aligning
the different actors as the internal development of the ecosystem.
However, consider Better Place, the technology venture that developed a network of
smart charging stations and battery swapping facilities, enabling a unique switchable battery
electric car service (Shankar, 2009). The venture took the lead in developing an ecosystem
that integrated, among others, a battery manufacturer, a car producer, a network of switching
stations and the software and hardware elements needed to enable that network. In the
process, they successfully engaged a relevant set of highly diverse parties into an ecosystem
wide value proposition of revolutionary electric mobility (Ofek and Wagonfeld, 2012). As
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such, the strategies and operations applied by Better Place have been used as state-of-the-art
examples of effective ecosystem (internal) development (Adner, 2012; Johnson and
Suskewicz, 2009). Yet, in 2013, the venture filed for bankruptcy, due to disappointing sales
of just under 2,000 of the initially planned 100,000 cars (Kershner, 2013).
Indeed, many ecosystems seeking to introduce path-breaking value propositions fail in
the market place, even when technological challenges are overcome and alignment of key
actors is achieved (cf. Adner, 2012). A key reason why these systems nevertheless fail is that
path-breaking value propositions often meet strong societal resistance, as they conflict with
the prevailing socio-technical regime—the rules, artifacts and habits that structure economic
viability and social life in a particular domain (e.g., city transportation, home heating) (Geels,
2004; Geels and Schot, 2007; Nelson and Winter, 1982). Typically, large incumbent actors
combined with strong social networks sustain the socio-technical regime, by carrying the
dominant elements that keep a domain on a certain developmental path (Geels, 2004; Kemp,
Loorbach, and Rotmans, 2007). A path-breaking value proposition tends to challenge (at least
some of) the elements underlying a socio-technical regime and can thus only become
successful if relevant societal subsystems adapt or transform to accommodate it (Nelson and
Winter, 1982; Raven, 2007).
The complexity and nature of the broader socio-technical setting therefore gives rise to
specific challenges for those ventures pioneering a path-breaking value proposition. These
pioneers need to adopt particular strategies that increase the likelihood of societal
stakeholders accepting and adopting the ecosystem’s value proposition. Yet, to date, the
literature on innovation ecosystems has not explicitly considered the socio-technical viability
of the ecosystem around a path-breaking innovation; and whether and how the venture
orchestrating the ecosystem can influence such viability.
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In this paper, we draw on a quasi-evolutionary perspective, and in particular on the
literature on transition and strategic niche management (e.g., Kemp, Schot, and Hoogma,
1998; Schot and Geels, 2007), to develop a framework of ecosystem development for path-
breaking innovations. We contribute to the innovation ecosystem literature by introducing the
concept of external development of the ecosystem, alongside its internal development, which
refers to deliberate efforts directed to enhance the viability of the ecosystem in its broader
socio-technical environment.
To this end, we first identify the ecosystem-level objects, that is the ‘ecosystem’s value
proposition’ and ‘ecosystem model’, which a focal venture can ‘manipulate’ in developing
their innovation ecosystem. Previous research argues that a focal venture can manipulate
these objects to improve the internal alignment of the ecosystem—which then determines the
extent to which the ecosystem is able to create and deliver its value proposition (Adner, 2016;
Adner and Kapoor, 2010; Iansiti and Levien, 2004). We draw from research on socio-
technical transitions to detail how manipulating the ecosystem’s value proposition and/or the
ecosystem model based on feedback from the socio-technical environment can also be used
to improve the ecosystem’s external viability. As such, by explicating the objects and the
basis of manipulation, we link together the internal and external development of the
ecosystem as performed by a focal actor. The resulting framework informs a research agenda
for future work in the area of innovation ecosystems and ecosystem strategy.
Conceptualizing innovation ecosystems
In view of resource constraints and the need for specialization, it is difficult for any single
firm to develop and commercialize a (technology-based) offering from start to finish (Kapoor
and Furr, 2015; Clarysse et al., 2014). This is especially the case if the intended innovation
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disrupts the existing development path in a socio-technical domain. Thus, increasingly
complex constellations of organizations have been emerging, in the form of innovation
ecosystems, in which actors interact with each other to create, deliver and appropriate value.
In this study, we apply the ‘ecosystem as structure’ conceptualization of innovation
ecosystems as suggested by Adner (2016), Adner (2012) and Gulati, Puranam, and Tushman
(2012), rather than the broader ‘ecosystem as affiliation’ conceptualizations proposed
elsewhere (e.g., Autio and Thomas, 2014; Iansiti and Levien, 2004; Moore, 1993; Rong and
Shi, 2015). Accordingly, the defining element of an innovation ecosystem is a system goal in
the form of an overarching common offering, which we refer to as the ecosystem’s value
proposition (EVP). Similar to the value proposition at the individual firm level, the EVP can
be viewed as a statement about the deed (to be) performed, or the performance that is
achieved for the end users when the contributions of the actors in the ecosystem network are
successfully combined (Ulaga and Reinartz, 2011). The EVP as defining element of an
ecosystem has the following implications.
The notion of a system goal suggests that meaningful boundaries for the ecosystem arise
from those elements of the system that in interaction (are likely to) accomplish the EVP
(Adner, 2016). These elements can only be identified from the viewpoint of an end user
(Clarysse et al., 2014). For example, a carmaker can integrate the entire vertical value chain
in producing an electric vehicle. However, the perspective of the end user serves to reveal
that, no matter how advanced the car is, a sustainable mobility experience (as EVP) is only
achieved when the users can also conveniently charge it, for instance, via the infrastructure
provided by local grid companies. In creating and delivering the EVP, the grid company is
therefore a critical actor, even though it may have no direct transactional links with the value
chain that produces the car. Such interdependencies can only be identified through
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considering the viewpoint of the end user, for whom the electric car and the ability to charge
it are necessary complementarities (Nambisan and Sawhney, 2011).
The boundaries of the ecosystem are thus determined by the EVP to include such
elements that are required to achieve the intended EVP. Consequently, any change in the
EVP is likely to give rise to changes in the elements and/or the interactions of the elements of
the ecosystem, and vice versa. In this respect, ecosystems can be understood as networks in
which actors are co-evolving (Li, 2009; Moore, 1993). As such, the typically specialized
actors in an ecosystem are interdependent in their efforts to accomplish the EVP (Adner,
2016; Adner et al., 2013; Gulati et al., 2012). However, interdependence also means that
failure of any key actor to successfully contribute to the EVP negatively impacts the success
chance of the whole ecosystem and thus every actor partaking in it (Brusoni and Prencipe,
2013). Furthermore, the embeddedness of actors in an ecosystem network implies that the
ability of any particular actor to appropriate value for itself is influenced by the other actors
(Nambisan and Sawhney, 2011). A defining element of ecosystems is thus also the
distribution of appropriated value among its actors (Autio and Thomas, 2014).
We therefore define an innovation ecosystem as a network of interdependent actors who
combine specialized yet complementary resources and/or capabilities in seeking to (a) co-
create and deliver an overarching value proposition to end users, and (b) appropriate the gains
received in the process.
Objects of manipulation
A common understanding, or alignment, among ecosystem actors about how to accomplish
an intended EVP is a key condition for success of the ecosystem (Adner, 2012; Williamson
and De Meyer, 2012). Yet, and especially for path-breaking value propositions, reaching
alignment provides a serious challenge due to, for instance, differences in industrial contexts
(Autio and Thomas, 2014; Moore, 1993), conflicting cultural backgrounds of the parties
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involved (Lavie, Haunschild, and Khanna, 2012), and initial misalignment in terms of the
goals and intentions of key actors (Casadesus-Masanell and Yoffie, 2007; Kapoor and Lee,
2013; Sharapov, Thomas, and Autio, 2013). As such, despite the possibility that an ecosystem
can be self-organized (Autio and Thomas, 2014; Williamson and De Meyer, 2012), most
path-breaking innovation ecosystems need an entity that orchestrates the process of
integrating the ecosystem and realizing its EVP (Iansiti and Levien, 2004; Nambisan and
Sawhney, 2011). Such an orchestrating position is often assumed by a central innovator in the
ecosystem—the so-called focal actor (Adner, 2012; Clarysse et al., 2014). Accordingly, we
focus in this paper on innovation ecosystems operating around a given focal venture that
orchestrates (a) the EVP and (b) the alignment of the various actors in the ecosystem that
surrounds such an EVP (Adner, 2006; Iansiti and Levien, 2004; Moore, 1993; Teece, 2007).
This focal venture ‘lens’ resonates with recent (empirical) research on innovation ecosystems
(e.g., Adner and Kapoor, 2010; Clarysse et al., 2014; Kapoor and Lee, 2013; Williamson and
De Meyer, 2012).
As the orchestrator of the ecosystem, and likely main proponent of the EVP, the focal
venture can influence how the ecosystem as a whole operates (Nambisan and Sawhney,
2011). In this respect, the ecosystem model (EM) refers to the structure of how the ecosystem
as a network creates and delivers value, and how value is appropriated by the actors in it
(Adner, 2012; Thomas, Autio, and Gann, 2014; Williamson and De Meyer,
2012)corresponding to the two main aspects emphasized in our definition of an innovation
ecosystem. In particular, the EM encompasses the activities necessary for accomplishing the
EVP, the actors performing these activities, the positioning of these actors in the ecosystem
and the links specifying the transfers between these actors (Adner, 2016). As such, the EM is
a network-oriented extension of the business model concept that specifies the value logic for
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an individual firm (Adner, 2016; Osterwalder and Pigneur, 2010; Zott, Amit, and Massa,
Given a specific EVP, a focal venture can influence the associated EM, both in terms of
innovation as well as network design aspects (Nambisan and Sawhney, 2011; Thomas et al.,
2014). For example, it can develop an awareness of what a functional ecosystem might look
like for accomplishing a specific EVP (Autio and Thomas, 2014; Overholm, 2015;
Williamson and De Meyer, 2012). The focal venture can also affect the EM by defining the
respective modularity in the ecosystem (Nambisan and Sawhney, 2011), choosing
technological standards (Gawer and Cusumano, 2002), gaining insights into who/what could
be the appropriate complementary actors/technologies to include in the ecosystem (Adner,
2012; Fjeldstad et al., 2012; Koenig, 2012), and orchestrating these technological
complementarities (Thomas, et al., 2014). Moreover, the focal venture can coordinate
alignment with regard to the activities contributed by the actors involved (Adner et al., 2013;
Koenig, 2012; Williamson and De Meyer, 2012), comprehend the flows of resources in the
ecosystem (Adner, 2012; Nambisan and Sawhney, 2011), establish the resources and rules to
be shared among the actors (Fjeldstad et al., 2012; Koenig, 2012), design an incentive system
for the ecosystem to attract new actors (Ritala et al., 2013; Williamson and De Meyer, 2012),
assure fair mechanisms for value appropriation (Dhanaraj and Parkhe, 2006; Iansiti and
Levien, 2004; Thomas et al., 2014), and establish mechanisms that lead to continuous self-
renewal of the ecosystem (Iansiti and Levien, 2004; Moore, 1993, 1998). Previous research
therefore suggests that ecosystems can be deliberately developed toward achieving an EVP
and in doing so, the main object of manipulation is the EM, which can be manipulated by (a
selection of) the strategies illustrated above.
However, developing an ecosystem is challenging for the focal venture, especially in
view of the considerable effort required to adequately assess the vast number of options for
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building a complex system (Massa and Tucci, 2014). In this respect, many focal ventures
initially struggle in choosing a strategy for the dimensions of the EM, given the uncertainty
about which critical components and activities a functional EM might require (Autio and
Thomas, 2014; Overholm, 2015; Williamson and De Meyer, 2012). In the early stages of the
ecosystem, it may also be highly uncertain how effective the cooperation with other
(potential) ecosystem actors will be and what kind of dynamics and interdependencies will
emerge (Brown and Eisenhardt, 1997; Gulati et al., 2012).
For example, Overholm (2015) describes how ventures offering solar panels as a service
considered different kinds of partners, and engaged in a series of ‘experiments’ to determine
how the relationships between actors in the ecosystem could be arranged to allow for the
intended EVP to be realized. Notably, the question of who (and how) to include as an initial
financing party in the service offering led these focal ventures to test multiple partner options.
These ventures thus assumed the EVP to be fixed, but manipulated the (emerging) EM in an
iterative manner, in order to converge to an increasingly better alignment between the EVP
and the EM.
Conversely, Adner (2006, 2012) and Williamson and De Meyer (2012) argue the focal
venture might first aim to achieve alignment between the EM and a less complex EVP, and
then subsequently develop both elements toward greater complexity by attempting to
incorporate new technological complementarities, activity structures and actor-network
configurations in creating and delivering value. In addition to the EM, the EVP as an
intended system goal can thus also be the object of manipulation.
More specifically, considering the uncertainties associated with path-breaking value
propositions, developing the ecosystem constitutes a dialectic process (Van de Ven and
Poole, 1995) in which the focal venture attempts to manipulate the EVP and EM, challenged
by the complexity of the situation and the other actors involved (Adner, 2012). The synthesis
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of these antagonistic forces informs subsequent attempts to align the ecosystem, giving rise to
new experiments around a different EVP and/or EM (Gavetti, Levinthal, and Rivkin, 2008).
Here, a key strategy for the orchestrating venture is to adopt feedback-driven learning, in
which one perceives the current EVP and EM as experimental propositions to be tried out
(Adner, 2012; Gavetti et al., 2008; Schön, 1984). Ideally, the EM fully enables the creation
and delivery of the EVP. We characterize this ideal state by a high level of internal alignment
of the ecosystem (Adner, 2016; Adner et al., 2013; Nambisan and Sawhney, 2011).
Correspondingly, the internal development of the ecosystem refers to the focal venture’s
efforts to increase internal alignment by manipulating the EVP, the EM, or both.
External viability of the ecosystem
Achieving internal alignment is, however, just one side of the coin. Especially for those
ventures that are developing an ecosystem around a path-breaking innovation (Smith and
Raven, 2012) another major challenge is to achieve viability of the ecosystem in its broader
socio-technical environment (Nambisan and Sawhney, 2011). More specifically, an
evolutionary perspective implies technology development in society involves a process of
variation, selection and retention (Basalla, 1988; Nelson and Winter, 1982). Path-breaking
innovations represent a dramatic departure from the current development trajectory in a
particular domain (Birkinshaw, Bessant, and Delbridge, 2007; Smith and Raven, 2012). Such
innovations are, therefore, subject to the selection environment that is dominated by a socio-
technical regime: the currently prevailing collection of artifacts, habits and the action-guiding
rules about the domain which are upheld by a wide actor network surrounding a vested
solution (Geels, 2004, 2005; Raven, 2007). The established actors backing these solutions
have usually invested substantially in the existing regimefor example in terms of
infrastructure (Nelson and Winter, 1982; Raven, 2007)and thus prefer incremental
improvements that build on existing artifacts, rules and habits in use. As a result, the
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dominant socio-technical regime creates a high level of retention, as most resources and
attention get channeled to improving the existing and proven solutions (Adner and Snow,
2010; MacKenzie, 1992). Consequently, path-breaking innovations are at a structural
disadvantage in the selection environment because they are simply too demanding in terms of
their socio-technical implications to the regime (Smith and Raven, 2012).
The lock-in in the selection environment goes beyond the user and market dimensions, to
include public policies and institutions, infrastructure, cultural discourse, and maintenance
networks (Lie and Sørensen, 1996). Moreover, there may be no established markets and user
preferences to start with, so an initial interface with potential adopters may be absent. Finally,
the adoption process itself is not straightforward either, as users have to integrate the
innovative solution into their infrastructure, practices, organizations and routines—all of
which involves adjustments and time (Geels, 2002) and may be subject to retention of the
dominant regime. In this respect, so-called transitions of the socio-technical regime are quite
rare, take a long time, and follow a rather unpredictable path (Geels, 2004).
For example, in the context of mobility, the current socio-technical regime entails
vehicles based on internal combustion engines; and the behavioral patterns and infrastructure
enabled and supported by this regime accommodate and prioritize this particular approach to
mobility. This, in turn, inhibits any development that is not in line with the regime. For
ventures developing a path-breaking EVP (e.g., Better Place), the socio-technical regime’s
inertial forces thus present a formidable challenge (Geels, 2004). In developing the ecosystem
for a path-breaking innovation, internal alignment is therefore not sufficient; a successful
ecosystem also arises from its socio-technical fitness or external viability. Consequently, the
external development of the ecosystem pertains to the interaction of the focal venture and
other key actors with their socio-technical selection environment in order to increase the
external viability of the ecosystem.
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In the remainder of the paper, we seek to develop a systemic framework that considers the
internal as well as the external development of the ecosystem. We do so by drawing from the
strategic niche management (SNM) discourse. The literature on SNM involves (public)
policy-oriented studies that, based on evolutionary theory (Basalla, 1988; Levinthal, 1998;
Nelson and Winter, 1982) and a dynamic multi-level perspective (Geels, 2002), investigate
the mechanisms that facilitate the development and commercialization of path-breaking
innovations (Huijben and Verbong, 2013; Markard, Raven, and Truffer, 2012; Smith and
Raven, 2012). As such, SNM proposes a set of policy strategies for overcoming the
potentially hostile influence of the socio-technical regime on a path-breaking innovation.
These strategies have been successfully applied in domains such as biogas (Raven et al.,
2008), social entrepreneurship (Witkamp, Raven, and Royakkers, 2011), long-term care
(Loorbach and Rotmans, 2010), and eco-housing and organic food (Smith, 2007). The set of
SNM strategies provides a foundation for the framework of innovation ecosystem
development proposed in this sectionhowever, contrary to the public policy-orientation
prevailing in the SNM literature, we operationalize the strategies of the focal venture as
propositions at the venture/firm level, directed toward the external development of a given
The core argument of SNM is that actors operating in a particular upcoming technology
domain (need to) collectively maintain a so-called (socio-)technical niche—the unit of
analysis in SNM. This particular type of niche constitutes a community of actors who are
interested in influencing the development (trajectory) of the particular domain (Geels, 2002).
It is thus a cross-functional group, consisting not only of different innovation ecosystems
(applying related technologies), but also of, for example, universities, scientists, NGOs,
associations and policy makers (Geels, 2004). In the dynamic multi-level perspective (Geels,
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2002), the niche constitutes a system level that is located between the single
actors/ecosystems and the broader environment dominated by a prevailing socio-technical
regime. Positioned as such, activities on the niche level can significantly counteract the
retention and inertia of the socio-technical regime (Schot and Geels, 2008; Smith and Raven,
2012) and thus mediate the influence of mainstream selection forces on the path-breaking
innovation. The positioning of the different levels is presented in Figure 1.
Fig. 1. A multilevel perspective on innovation ecosystems.
The socio-technical niche somewhat resembles the ‘fuzzy front end’ of an emerging
industry (Suarez, Grodal, and Gotsopoulos, 2015), characterized by great uncertainty about
the technology and market, which results in a wide diversity of technological and market
approaches adopted by the actors within the niche (Geels, 2004). However, a niche emerges,
by definition, in the face of an existing socio-technical regime, the latter hindering
progression of path-breaking innovations promoted in the niche. Therefore, the relational
dynamics within the niche are likely to differ substantially from the competition-oriented
behavior observed in some early-stage industries (e.g., Santos and Eisenhardt, 2009). In this
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respect, a socio-technical niche invokes more cooperation between actors, as a means to
survive and challenge the dominant regime (Raven, van den Bosch, and Weterings, 2010).
An example is the international network of stakeholders collectively pioneering the use of
building-integrated photovoltaics: these various kinds of enterprises, non-profit organizations
and other actors actively seek a common agenda and action framework, to increase the
societal prominence and commercial application of the proposed technology.
The SNM literature suggests four strategic principles to develop and commercialize
path-breaking innovations in the face of an unfavorable selection environment. That is, niche
actors should: (1) engage in socio-technical experimentation; (2) maintain a collective
knowledge base; (3) converge their efforts in getting the technology widely adopted; and (4)
achieve and take advantage of protection measures that help sustain the niche and its
participants (Raven et al., 2010). The principles together serve to inform the external
development of the ecosystem. In this respect, while previous research suggests that the EVP
and EM can be manipulated to achieve internal alignment, we argue that the principles, as
developed by SNM scholars, inform the basis for manipulating the EVP and EM to achieve
external viability of the innovation ecosystem. In particular, we posit that driving the
innovation ecosystem towards overall success is dependent both on ‘internal’ (as elaborated
earlier) as well as ‘external’ feedback-driven action.
External viability and socio-technical experimentation
In a situation where markets and user preferences are underdeveloped, niche actors can seek
to enhance the reciprocity (i.e., co-evolution) between their niche and the socio-technical
environment (Geels, 2005). The central driver of this reciprocity is socio-technical
experimentation, involving attempts to engage the (potential) stakeholders in the environment
to interact with the niche actors and their offerings (Raven et al., 2010). To be effective in
enhancing reciprocity, this experimentation strategy calls for repeated interaction and
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continual learning from feedback arising from the interactions. In the context of path-
breaking innovation ecosystems, this implies that any EVP and EM are treated as no more
than current ‘best estimates’ that are iteratively exposed to the socio-technical environment to
trigger responses that inform subsequent experiments (Gavetti et al., 2008; Lynn, Morone,
and Paulson, 1996; Voss, 1984). In doing so, external viability is enhanced via two
First, the focal venture can gain feedback concerning the viability of the current EVP-
EM combination by means of pilot cases, living labs, user tests, and other forms of socio-
technical experimentation (Hoogma, 2002). These experimentation modes also serve to create
a better understanding of the characteristics of the selection environment and the level of
discrepancy between the two (Geels and Raven, 2006). More specifically, by introducing
versions of the EVP-EM to prospective users, policy makers and support organizations, the
focal venture can measure their responses in terms of potential enablers as well as barriers to
adopting/supporting it. Such data provides valuable cues about the actual strength of the
regime lock-in as well as the changes needed to overcome it. For instance, in case of a strong
lock-in arising from the dominant regime, the focal venture and its partners may steer toward
versions of the EVP and EM that challenge the regime less (Raven, 2007). Experimentation
can thus serve to grow the level of acceptance regarding the EVP in the selection
environment, by leading the ecosystem to adapt its EVP and/or EM to the existing rules,
habits and artifacts in the environment.
An example of such a deliberate learning strategy is the innovation ecosystem
orchestrated by the Dutch venture Qurrent. Qurrent’s ecosystem aimed to offer a range of
devices and services enabling the creation of small local energy networks. This ecosystem
experimented with several EVPs and EMs, engaging a combination of municipalities,
housing corporations, an office real estate developer, private residence owners, a utility
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company and a manufacturer of heat pumps (Ceschin, 2013). In each case, Qurrent measured
the opportunities for technical integration as well as the societal response. The overall
purpose of Qurrent’s experimentation strategy was to understand which EVP might gain the
highest adoption rate, which user segments it would need to target, which EM it would
correspond to, and who would be viable actors to include in the ecosystem (Ceschin, 2013).
Second, socio-technical experimentation is also instrumental in asserting influence to the
selection environment, especially by gradually building support for the new EVP as a
potential alternative to the technologies/solutions established and enabled by the dominant
regime (Raven et al., 2008). First, via socio-technical experimentation, the ecosystem can
grow awareness of the potential need in terms of its EVP. Second, the novel offering is
exposed to various stakeholders, increasing the chances that at least some of them may
choose to experiment with and subsequently adopt the novel rules, artifacts and habits
involved. Third, experimentation invites institutional stakeholders, such as governmental
agencies, public media or NGOs, to pay attention to what the ecosystem is offering (Schot
and Geels, 2007), which can be critical in sculpting (a positive) public opinion about the
EVP. Socio-technical experimentation can thus serve to increase the acceptance and
legitimacy of the EVP, by gradually leading the environment to alter itself.
For example Tesla Motors, the electric vehicle manufacturer, at the time steered its
ecosystem to develop and launch their first full-electric car models in the high-price segment.
Introducing the EVP of a sustainable but also fast and luxury vehicle that is little bound by
range limitations has been instrumental in growing the societal awareness of ecological
mobility. In this respect, Tesla’s offering has challenged conventional beliefs regarding the
shortcomings of electric mobility, and in doing so, also raised a significant amount of public
attention, as well as motivated an increasingly growing number of customers to buy Tesla’s
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vehicles (Hurst, 2014). In sum, we formulate the proposition, defined from a focal venture
P1. Developing the EVP and EM iteratively, informed by feedback from socio-
technical experimentation, serves to increase the external viability of the ecosystem1.
Empirical work informed by this proposition can draw on longitudinal studies of
ecosystems to identify whether and how ecosystem actors have installed deliberate learning
mechanisms (Almeida, Dokko, and Rosenkopf, 2003), what the critical (events in)
interactions with actors outside the ecosystem are, and whether and how these learnings and
interactions inform the development of the EVP and EM.
To measure the external viability of the ecosystem, one could draw on (a) formal
analysis of the total value appropriated by the actors in the ecosystem (e.g., Garcia-Castro
and Aguilera, 2015); (b) financial analysis of the individual performance of these actors; (c)
content analysis of data collected from public and social media, to assess the public sentiment
regarding the EVP (e.g., Riffe, Lacy, and Fico, 2013); and (d) analysis of survey data (e.g.,
Berger and Schwartz, 2011). Finally, incumbent regime actors might be probed for
information on the particular technological niches and innovation ecosystem (actors)
challenging the regime, for instance by means of interviews.
External viability and inter-local learning
While engaging in socio-technical experimentation can improve the external viability of the
ecosystem, it may take (too) many iterations that are likely to drain the constrained resources
available within the ecosystem, hampering the ability to experiment further. In addition to
1 We emphasize that previous research highlights the importance of experimentation for the internal
development of the innovation ecosystem (e.g., Adner, 2016). Here, we specifically stress the importance of
socio-technical experimentation as a source for feedback in external development of the ecosystem.
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resource constraints, the focal venture and other ecosystem actors also have a tendency
towards satisficing (Geels, 2010; Simon, 1956) and due to the limited number of options
considered in their own local search, sub-optimal versions of the EVP and EM are likely to
be chosen.
In light of these issues, SNM theory implies that, to be more effective at increasing the
external viability of the niche offering, actors in the niche should converge to a common
knowledge base (Raven et al., 2010). Here, the core driver is so-called inter-local learning,
that is, learning from the lessons of others in other local contexts (Raven et al., 2008). For the
focal venture, complementing its own experimentation by means of sharing knowledge across
different ecosystems and different institutional settings accelerates the learning curve and
reduces the risk of sub-optimality. External viability is thus created by learning from others to
more effectively develop those EVP-EM combinations (and subsequent experiments) that are
receiving a level of success (i.e., have not been ‘eliminated’) in interacting with the selection
This kind of learning can be reciprocal in nature, when actors across ecosystems jointly
discover and blend knowledge and skills in repeated interactions (Lubatkin, Florin, and Lane,
2001). The local learning of each actor is then extended toward more distant learning that
benefits all parties (Rosenkopf and Almeida, 2003). Reciprocal learning is more likely to
happen with help of a third-party facilitator, such as an industry association or a
governmental agency (Rotmans and Loorbach, 2006).
Alternatively, a focal venture can employ associative reasoning and carry over
information (Schön, 1984) by imitating the behavior of organizations and ecosystems that
they perceive as analogous. Strategy scholars have long advocated this approach to learn
from the practices of the best performing organizations in the field, or to avoid mistakes made
by others (Casadesus-Masanell and Zhu, 2013; Csaszar and Siggelkow, 2010; Gavetti,
- 20 -
Levinthal, and Rivkin, 2005). In contrast to reciprocal learning, imitation does not require the
consent of the model/benchmark organization. For example, Overholm (2015) observed that
new entrants to the emerging solar service industry in the US followed the logic (cf. EM) of
previous entrants in building their ecosystems, even using the same bank as the incumbents
had chosen to work with. While imitation without consent may reduce the quality of
(knowledge about) the benchmark (Amit and Zott, 2012), even irrelevant analogies tend to
provide better results than making decisions solely based on one’s local optimum (Gavetti et
al., 2008).
Ryanair, the Irish company that built the first low-fare airline operation in Europe,
provides an example of inter-local learning. In the late 1980s, Ryanair already adopted a price
advantage strategy. However, after the general collapse of the airline industry during the Gulf
War, the firm set out to introduce in Europe the value proposition that Southwest Airlines had
developed successfully in North America (Regani and Dutta, 2003). In 1991, the deputy CEO
visited Southwest in Dallas to obtain detailed information about the operating logic of the
American benchmark (Maier, 2006). Rather than merely introducing single elements, Ryanair
was able to carry over much of the EM that Southwest had pioneered. This included 1)
standardizing the fleet; like Southwest, Ryanair chose to exclusively partner with Boeing; 2)
flying to secondary airports where the costs per passenger were much lower than at major
ones; 3) fast turnaround times and point-to-point flights; and 4) mediating extra services from
a network of partners such as hotels, transfer services, car rental offices and insurance
providers (O’Higgins, 1999; Regani and Dutta, 2003). In conclusion, this suggests the
following proposition, again defined from a focal venture perspective:
P2. Developing the EVP and EM by learning from the experiences of other
organizations that have pioneered (somewhat or highly) similar path-breaking
innovations, serves to increase the external viability of the ecosystem.
- 21 -
Future empirical work informed by this proposition can operationalize the learning
variable in terms of knowledge transfer across ecosystem boundaries (Maurer, Bartsch, and
Ebers, 2011), drawing on survey data (Li, 2005) and social network analysis (Sammarra and
Biggiero, 2008). Additionally, learning from others in the niche can in some contexts be
considered a ‘knowledge spillover’, which can be measured, for instance, by means of patent
analysis (Jaffe, Trajfenberg, and Henderson, 1993).
External viability and niche trajectory
In SNM theory, the niche is seen as a source of disturbance for the progress of the dominant
socio-technical regime. That is, a niche provides an alternative (potential) trajectory to
societal and industrial development in a domain (e.g., transportation, health care) (Geels,
2002). However, this alternative trajectory cannot be explored and sustained by learning from
peers only (i.e., P2). Another driving force arises from sequences of experiments in different
local contexts, which gradually add up to a niche trajectory (Geels and Raven, 2006). As a
result, the initially divergent and dispersed processes and routines become more articulated,
specific and stable over time (Raven et al., 2010). Together with these changes, any approach
to commercializing the new technology that follows these (increasingly articulated and
stable) processes and routines is more likely to survive and thrive (Schot and Geels, 2008).
In this respect, convergence toward a particular (set of) EVP(s) and EM(s) will
substantially affect which propositions and models are externally viable in the long run, and
which are not (Suarez et al., 2015). For example, in the case of a substantial and unexpected
surge in market demand arising from a new EVP, other actors/ecosystems in the same niche
are likely to imitate it (Argyres, Bigelow, and Nickerson, 2015), which in turn brings in
resources and institutional support that further enhance the emerging path (Raven, 2007).
This ‘bandwagon’ effect amplifies the external viability of the particular EVPs and EMs in at
- 22 -
least two ways. First, the increasing number of actors supporting the development trajectory
for the niche empowers the lobby for specific protection measures that would support it
(Kemp et al., 2007). For instance, as a result of lobbying efforts for sustainable energy,
(local) governments have adopted policies that enable specific solutions in this area.
Examples of this would be the German 1,000 Roof and 100,000 Roof programs that provided
financial support to owners of residential photovoltaic solar panels, building the foundation
for the German residential solar market to grow exponentially for more than two decades
(Bergek and Jacobsson, 2003).
Second, niche actors are also likely to collectively influence the market, user practices,
routines, policies, cultural discourse, infrastructure, and maintenance networks more than any
single actor (Lie and Sørensen, 1996). Here, the convergence in their interactions with the
socio-technical environment and increasing public exposure enhances the cognitive as well as
socio-political legitimacy of the niche trajectory (cf. Aldrich and Fiol, 1994). For instance,
Smith (2007) studied such a process for organic food in the UK. The initially small niche of
organic producers converged explicitly on matters such as supply chain composition, organic
labeling and joint marketing. As a result, since the 1990s, the organic food movement has
been gaining substantial societal support, and was adopted as part of the processed and
packaged food regime in the UK.
If the focal venture timely spots an emerging trajectory in terms of a distinctive EVP and
EM becoming more prevalent in the niche, aligning to that trajectory is likely to make the
venture’s ecosystem more externally viable. Timely spotting any convergence in the niche is
largely a question of the (cognitive) abilities of people in the focal venture and other actors in
its ecosystem. Cues may arise in the form of, for example, innovation shocks (Argyres et al.,
2015), emergence of dominant categories (Suarez et al., 2015), or protection measures that
selectively support certain offerings (Kemp et al., 2007). Furthermore, once a potential
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trajectory is identified, the ease with which the ecosystem can be repositioned toward an
emerging path is determined by the available resources of the focal venture and its ecosystem
partners (Argyres et al., 2015). In other words, repositioning is less risky and takes less effort
when the focal venture and its key partners possess information and capabilities relevant to
the approach adopted—providing further support for P1 and P2. In sum, we propose:
P3. Aligning the EVP and EM with the development trajectory that is emerging in
the socio-technical niche serves to increase the external viability of the ecosystem.
Empirical work informed by P3 can draw on the notion of innovation shocks, dominant
categories, and specific protection schemes as proxies for the emergence and convergence of
a niche development trajectory. These trajectories can be inferred from qualitative data, in
terms of dominant EVPs and EMs, using content analysis of keywords that refer to specific
propositions and models (e.g., Pontikes, 2012). The work on ‘dominant designs’ (Abernathy
and Utterback, 1978), and how to measure such designs (e.g., through market share analyses
and/or expert interviews), might also be utilized as inspiration on how to measure emerging
development trajectories (Anderson and Tushman, 1990; Srinivasan, Lilien, and
Rangaswamy, 2006).
Sustaining ecosystem development
SNM theory postulates that any niche emerging in the context of a dominant socio-technical
regime needs protection in its early stages, as the niche actors are not likely to survive the full
selection pressure if exposed to it too early (Smith and Raven, 2012). Protection can come in
financial and non-financial forms. The former can take shape as subsidies, tax breaks, grants,
or market stimulation mechanisms. An example would be the support scheme that the Dutch
government has developed for supporting large scale renewable energy generation. Namely,
considering the financial disadvantage of renewable energy generation compared to fossil
- 24 -
alternatives, producers of renewable energy are compensated for that difference with a feed-
in tariff the size of which is determined by the price dynamics of fossil-based energy
(Chatelin, 2016). Non-financial forms of protection include for example policy support, legal
requirements, education and public appraisal (of the niche’s EVPs at the expense of
alternative EVPs). Examples of non-financial forms of support would be the entrepreneurial
education programs run by European Institute of Innovation & Technology Knowledge
Innovation Communities. Such programs provide entrepreneurial education to individuals
with an engineering background on strategically important areas, such as climate change,
sustainable energy and raw materials (EIT, 2016). The various forms of protection are
provided by either governmental agencies or other stakeholders interested in developing the
niche (Huijben and Verbong, 2013; Smith and Raven, 2012), possibly as a result of lobbying
efforts by niche actors.
For any ecosystem, the usage of niche protection measures provides the space and time
to develop the internal alignment and external viability of its (emerging) EVP-EM, and thus
make the ecosystem increasingly fit to face the socio-technical selection environment. In
other words, while protection creates neither internal alignment, nor external viability per se,
it ‘buys time’ for the focal venture and its ecosystem to develop, learn and grow in terms of
the mechanisms outlined in P1 to P3. We therefore propose that:
P4a. The use of niche protection schemes enables the focal venture and other
ecosystem actors to exploit the mechanisms defined in P1, P2 and P3, and thus
serves to indirectly increase the external viability of their ecosystem.
The level of available resources, other than those originating from protection schemes, is
also likely to enable the ecosystem to develop, learn and grow. That is, ecosystems without
any slack in resources, such as financial assets and human resources, have to be much more
- 25 -
selective in engaging in the activities outlined in P1 to P3, compared to ecosystems with
substantial resource slack (cf. George, 2005). In this respect, a high level of resource slack
provides a buffer that allows for more time and discretion in responding to the challenges
arising from, for example, the interaction with potential customers, other focal ventures and
their ecosystems, and the emerging niche trajectory (Bradley, Shepherd, and Wiklund, 2011;
Dolmans et al., 2014). This suggests the following proposition:
P4b. Resource slack enables the focal venture and other ecosystem actors to exploit
the mechanisms defined in P1, P2 and P3, and thus serves to indirectly increase the
external viability of their ecosystem.
Future empirical work informed by proposition 4a-b might draw on data such as the
number and size of (governmental or other) grants, subsidies or tax breaks the niche and
specific ecosystems within the niche have received or indirectly benefited from, in addition to
firm-specific measures such as a federal loan (e.g., Tesla’s loans from the US federal
government) investment capital obtained from external investors, and so forth. Resource
slack, for proposition 4b, is typically operationalized on the basis of current assets and
liabilities (e.g., current ratio). Future work, however, needs to consider that resource slack
entails a perception at the decision-making level, which would likely demand a more fine-
grained (qualitative) measure (see Dolmans et al., 2014).
- 26 -
Fig. 2. Ecosystem development for path-breaking innovations.
Figure 2 outlines a multi-level perspective on how a focal venture should enhance both the
internal alignment and the external viability of its innovation ecosystem. Previous research
suggests that the focal venture may manipulate the EVP and/or EM to improve the internal
alignment in the ecosystem (Adner, 2016). In this research, we have argued that internal
alignment is not sufficient for the success an ecosystem that is trying to develop a path-
breaking innovation. Here, a focal venture and associated ecosystem also need to carefully
consider and learn from the selection environment surrounding them, in order to develop
external viability; that is, by manipulating the EVM and/or EM using feedback obtained from
the socio-technical environment.
More specifically, in the first feedback interface, the ecosystem actors interact directly
with the socio-technical environment via experimentation activities (see P1). Socio-technical
- 27 -
experimentation further informs changes in the EVP and EM, as well as asserts influence to
the environment. Furthermore, the focal venture can draw in its ecosystem development
activities from peers by means of inter-local learning (P2, the second feedback interface) as
well as from the collective agency on the socio-technical niche level, which may lead to
convergence of certain EVPs and/or EMs (P3, the third feedback interface). Acquiring
feedback for ecosystem development from these three levels is enabled by resource slack and
protection mechanisms, typically assigned first to the niche as a whole, and then exploited by
the focal venture and other ecosystem actors for sustaining the development of their
ecosystem (P4).
A case featuring such niche protection as well as the use of all three feedback interfaces
in ecosystem development can be found from the US residential solar industry. First, the
market for residential solar was largely enabled by a protection measure in the form of the US
Energy Policy Act (2005) that allowed residential solar installers to receive a 30% investment
tax credit (P4) (Hannah and Eisenhardt, 2016). Second, focal ventures such as Solarcity, and
Sunedison developed their ecosystems consistently through socio-technical experimentation
with each next installation, often with different partners in different geographical regions,
providing feedback to their EM (P1) (Overholm, 2015). Third, taking analogy from peers was
a commonly used strategy in ecosystem development, especially considering EM design
questions such as which elements of the EVP to outsource versus which to internalize, which
parties to collaborate with, and how to support the partner networks (P2) (Hannah and
Eisenhardt, 2016; Overholm, 2015). Fourth, as the EVPs in the industry were developing
over time, the niche featured several points of convergence where a certain EM composition
allowed focal ventures to achieve continued growth. In particular, Hannah and Eisenhardt
(2016) illustrate how the success of these ventures highly depended on their ability to steer
- 28 -
their ecosystem strategy according to the convergence in the development trajectory of the
niche with regard to the means of targeting cost savings (P3).
With the framework, our paper contributes to the literature on innovation ecosystems by
explicitly considering the socio-technical viability of the ecosystem around a path-breaking
innovation. To guide future (empirical) work on this framework, we provided potential
measures for the concepts featured in the different propositions above. In the remainder of
this section, we present an additional research agenda informed by the framework.
The role of experimentation. A key implication of our framework is that both the EVP
and the EM can be the target of innovation efforts, similar to how the firm-centric value
proposition and its corresponding business model have become the objects of innovation
(e.g., McGrath, 2010; Zott et al., 2011). The focal venture can orchestrate the development of
an ecosystem iteratively via experimenting with different EVPs and EMs, changing the way
the ecosystem as a whole creates, delivers and appropriates value. For the focal venture,
deliberately experimenting with these elements therefore constitutes an important element of
its ecosystem strategy, which thus far has received little attention (cf. Adner, 2006; Adner
and Kapoor, 2010; Kapoor and Furr, 2015; Kapoor and Lee, 2013). Our framework also
raises several research questions for future work in the area. For example, research might
explore the extent to which testing and experimentation activities provide diminishing
returns, and when the focal venture should settle on a specific ecosystem configuration
(Sommer and Loch, 2004); how the focal venture balances its resource constraints with the
perceived need to continue experimenting; and how the focal venture’s experimentation
activity affects the behavior of other actors in the ecosystem. The latter question is
particularly relevant, considering that external feedback is (a) likely to disturb the
ecosystem’s internal alignment and (b) a precondition for long-term value appropriation
opportunities for ecosystem actors, which seems to imply that the external development of
- 29 -
the ecosystem should take prominence over its internal development. How to alleviate the
resulting tensions between actors is left for future research.
Prioritizing feedback. Related to the previous, to what extent should a focal venture and
its ecosystem partners use their (limited) resources on each of the strategies of external
development of the ecosystem? While this is predominantly a question for future research,
there appears to be a trade off in the resource use (P4) and the contextual accuracy of the
sources of feedback (P1 to P3). Own experimentation implies placing the EVP into its
intended context. The mechanisms presented in the argumentation for Proposition 1 are thus
fully operational, either towards building support for the EVP or towards providing feedback
for further developing the ecosystem in that context. At the same time, such experimentation
likely entails a high resource commitment. Meanwhile, inter-local learning (P2) or aligning to
the emerging development trajectory of the niche (P3) is lighter in terms of resource
necessity, but can render feedback that is perhaps not directly applicable in the ecosystem’s
context, due to its more holistic nature. How to balance the ecosystem external development
activities over the three feedback interfaces is an important strategic consideration for the
focal venture; one that is likely dependent on factors such as the existence of appropriate
peers, the maturity of the niche, level of context-specific elements in the domain (such as
legislative control), as well as uniqueness and replicability of key EM elements (Overholm,
2015). As such, future research could, besides extending this list of factors, study what
specific form of feedback interface is most effective for ecosystem external development, at
what moment in time.
Strategies for manipulation. In this study, we focused on creating an understanding
about how a focal firm can use feedback-driven learning from the socio-technical
environment to develop its ecosystem’s external validity. We have, however, implicitly
assumed that the focal venture can manipulate the EVP and/or EM if achieving such external
- 30 -
viability (or internal alignment for that matter) would require so. In reality, however,
attempting to manipulate the ecosystem is likely subject to misaligned agendas (Casadesus-
Masanell and Yoffie, 2007), power struggles, and interplay between independent,
interdependent and dependent elements of the ecosystem structure (Adner, 2016). Sculpting
an ecosystem strategy would thus be much more than a question of knowing which direction
to steer it. Although research provides some cues (as also outlined in this paper), future
studies on innovation ecosystems should investigate (a) how agents incentivize others to align
to their (path-breaking) EVP; (b) how to sculpt a value distribution logic for a future
ecosystem constellation (Dhanaraj and Parkhe, 2006) before it is fully clear how much value
will there be available for appropriation; (c) how to assert influence on the actors with whom
the ecosystem has an asymmetric dependence: for instance, actors that perform activities that
are necessary for the EVP to be realized, but who themselves are largely indifferent to being
part of the ecosystem constellation (Adner, 2016); and (d) how to increase the resilience of
the ecosystem in dealing with the failures of some actors to (re)align to the EVP.
Ecosystem management as dynamic capability. Our framework also implies that
ecosystem management by the focal venture can be studied from a dynamic capability
perspective (Eisenhardt and Martin, 2000; Teece, Pisano, and Shuen, 1997), that is, ‘the
capacity of an organization to purposefully create, extend, or modify its resource base’
(Helfat et al., 2007: 4). As argued earlier, ecosystem actors provide critical resources such as
knowledge, complementary products and market distribution channels for the EVP and EM
orchestrated by the focal venture (Mahmood, Zhu, and Zajac, 2011). In this respect, the
primary resource base for accomplishing the EVP is located at the ecosystem level, as
opposed to the venture or firm level. As changes at the ecosystem, niche and/or regime levels
unfold, the focal venture thus needs to possess a dynamic capability to keep the EVP viable
by sensing and seizing these changes and managing the experimentation-driven
- 31 -
transformation of the EVP and EM implied by them. In this respect, a promising avenue for
future research might arise from developing the micro-foundations of ecosystem management
as dynamic capability (cf. Helfat et al., 2007), for instance in understanding how particular
individuals as agents of ecosystem actors make sense of the shifts at the ecosystem, niche
and/or regime level and sculpt strategies for (re-)steering the EVP and/or EM.
The faster the better? The speed and phasing of socio-technical transitions constitute
critical challenges for technology ventures. While punctuated equilibrium theory suggests
that, at times, the socio-technical environment accommodates path-breaking innovations
quite rapidly (Anderson and Tushman, 1990; Mokyr, 1990), it is more realistic for path-
breaking innovators to adopt a longer time horizon in trying to accomplish their EVP (Geels,
2005), in line with Adner’s (2012) notion of ‘staged expansion’. In this respect, technological
development trajectories are often characterized by several episodes of S-shaped growth
(Christensen, 1992a, 1992b) and socio-technical transition processes evolve through a series
of thresholds (Gold, 1983), where the speed of change is difficult to predict. Indeed, part of
the failure of Better Place’s ecosystem (see Introduction) can be attributed to underestimating
the resistance arising from the prevailing mobility regime. In particular, Better Place’s CEO
assumed and expected a high rate of change of the dominant socio-technical regime would be
achieved (Ofek and Wagonfeld, 2012), an assumption that turned out to be false. The non-
linear and unpredictable nature of transitions from one regime to the next also raises the
question how a focal venture can assess the status of an unfolding transition of the prevailing
regime and the strength of the regime-level actors to fight back. We have provided some
ideas in our argument supporting proposition 3, but this key question warrants more attention.
Survival in niches. While we have developed a framework for ecosystem external
development that builds on the literature on SNM, it is necessary to emphasize a critical
difference that adopting the focal venture viewpoint to ecosystem development adds to the
- 32 -
argumentation in SNM (e.g., Raven, 2007), as well as in parallel transition-oriented research
streams such as studies on technology innovation system (TIS) (e.g., Wieczorek and Hekkert,
2012). Namely, in concentrating on the support of a path-breaking technology, it is implied in
these literatures that individual initiatives (i.e., manifestations of these technologies in
specific value proposition by specific actors) can increase the common knowledge base for
benefit of other proponents of the same technology even if they are not successful. In fact, it
has been argued that failed projects often provide more fruitful contributions to the shared
knowledge base of the niche, allowing for subsequent initiatives to be stronger as a result
(Raven and Verbong, 2004). Contrastingly, by taking the viewpoint of a focal venture and its
ecosystem actors, the focus logically shifts to achieving success of these actors and the EVP
they represent. As such, our research contributes to transition studies (e.g., SNM and TIS) by
providing an actor- and ecosystem-based viewpoint to navigating transitions; and serves as an
example of the potential insights that can be gained from bridging transition studies and
innovation/strategy research. Future research might explore other insights that such cross-
overs can deliver.
The value of the niche concept. Finally, a key notion in our framework is the (socio-
technical) niche (Geels, 2002; Schot and Geels, 2007), an additional layer of networks and
activities that single actors and ecosystems in emerging fields can leverage in order to
enhance their external viability. While the niche concept has been widely used in innovation
policy research, our argument suggests it is also highly relevant to strategy research,
especially in the area of disruptive innovation. Future research in this area might, for
example, explore how focal ventures and other actors in their ecosystems identify the broader
niche community (if any) they are part of, and how and when they connect and collaborate
with other actors in this niche.
- 33 -
Boundaries and limitations
Any model or framework is inevitably limited in its assumptions. For one, we assumed a
path-breaking innovation originates from outside the dominant socio-technical regime.
However, incumbents of the socio-technical regime can sometimes also develop path-
breaking innovations (Van der Vleuten and Högselius, 2012). These instances are likely to
face significantly different selection pressures than those pioneering an innovation outside the
dominant regime though. The case of Kodak that invented digital photography but then
decided not to commercialize it (Tripsas and Gavetti, 2000) suggests incumbents of the
prevailing regime may face more severe corporate ‘selection environments’ (Walrave, Van
Oorschot, and Romme, 2011), even when their external environment is less selective. This
raises interesting questions with regard to path-breaking innovation by focal firms that are
incumbents to the prevailing regime versus those that are not.
In this paper, we focus on the formative stages of an innovation ecosystem and its socio-
technical niche. In the early stages, the cooperation-competition dynamics in the niche tend to
be different than when the innovation has already gained substantial foothold (Brandenburger
and Nalebuff, 1996). More specifically, our framework suggests that focal ventures
emphasizing niche level collaboration in these formative stages, which facilitates knowledge
sharing and subsequent niche building and protection, are more likely to generate viable
ecosystems. Yet, the stronger the niche and its actors become, the more the actors are likely
to compete with each other. Our framework does not explicitly consider this shift in
competitive dynamics.
In order to keep the framework parsimonious, we assumed an innovation ecosystem is
linked to merely one socio-technical niche. In practice, however, the ecosystem can be
embedded in multiple (emerging) niches existing and evolving simultaneously (Levinthal,
1998; Raven, 2007). This raises questions about how and when the focal venture chooses the
- 34 -
most promising niche trajectory, under which conditions the focal venture is better off by
connecting to multiple niches simultaneously, and whether and how this venture and its
ecosystem can potentially switch from one niche to another. Real options theory may inform
future work in this area (Damaraju, Barney, and Makhija, 2015).
This paper presents a theoretical framework of how a focal venture develops an innovation
ecosystem for path-breaking innovation. We argued that ecosystem success arises from
achieving internal alignment as well as external viability of the ecosystem, which are both
dependent on the configurations of the EVP and the EM. Considering the EVP and EM as
objects that the focal venture in the ecosystem can manipulate, we developed a multi-level
perspective on innovation ecosystem development. This framework considers the internal
alignment as well as the external viability of the ecosystem, through iterative development of
the EVP and/or EM, according to cues from inside the ecosystem, from the socio-technical
niche level, as well as from the external environment. Based on the framework, we developed
a substantial research agenda to guide future studies on innovation ecosystems.
Abernathy, W.J., Utterback, J.M., 1978. Patterns of industrial innovation. Technology Rev.
8(June-July), 40–47.
Adner, R., 2006. Match your innovation strategy to your innovation ecosystem. Harvard Bus.
Rev. 84(4), 98–107.
Adner, R., 2012. The Wide Lens: A New Strategy for Innovation. Portfolio/Penguin, New
Adner, R., 2016. Ecosystem as structure: an actionable construct for strategy. J. Manage.
Adner, R., Kapoor, R., 2010. Value creation in innovation ecosystems: how the structure of
technological interdependence affects firm performance in new technology
generations. Strateg. Manage. J. 31(3), 306–333.
Adner, R., Oxley, J.E., Silverman B.S., 2013. Collaboration and Competition in Business
Ecosystems. Emerald, Bingley.
Adner, R., Snow D., 2010. Old technology responses to new technology threats: Demand
heterogeneity and technology retreats. Ind. Corp. Change 19(5), 1655–1675.
- 35 -
Aldrich, H.E., Fiol, C.M., 1994. Fools rush in? The institutional context of industry creation.
Acad. Manage. Rev. 19(4), 645–670.
Almeida, P., Dokko, G., Rosenkopf, L., 2003. Startup size and the mechanisms of external
learning: increasing opportunity and decreasing ability? Res. Policy 32(2), 301–315.
Amit, R., Zott, C., 2012. Creating value through business model innovation. MIT Sloan
Manage. Rev. 50(3), 1–11.
Anderson, P., Tushman, M.L., 1990. Technological discontinuities and dominant designs: a
cyclical model of technological change. Admin. Sci. Quart. 35(4), 604–633.
Argyres, N., Bigelow, L., Nickerson, J.A., 2015. Dominant designs, innovation shocks, and
the follower’s dilemma. Strateg. Manage. J. 36(2), 216–234.
Autio, E., Thomas, L.D.W., 2014. Innovation ecosystems: implications for innovation
management. In Oxford Handbook of Innovation Management, Dogson, M., Gann,
D., Philips, N. (eds). Oxford University Press, Oxford, 204–228.
Basalla, G., 1988. The Evolution of Technology. Cambridge University Press, Cambridge.
Bergek, A., Jacobsson, S., 2003. The emergence of a growth industry, a comparative analysis
of the German, Dutch and Swedish wind turbine industries. In Change,
Transformation and Development, Metcalfe, P.J.S., Cantner, P.D.U., (eds). Physica-
Verlag HD, 197–227.
Berger, J., Schwartz, E.M., 2011. What drives immediate and ongoing word of mouth? J.
Marketing. Res. 48(5), 869–880.
Birkinshaw, J., Bessant, J., Delbridge, R., 2007. Finding, forming, and performing, creating
networks for discontinuous innovation. Calif. Manage. Rev. 49(3), 67–84.
Bradley, S.W., Shepherd, D.A., Wiklund, J., 2011. The importance of slack for new
organizations facing “tough” environments. J. Manage. Stud. 48(5), 1071–1097.
Brandenburger, A., Nalebuff, B., 1996. Co-opetition, Doubleday, New York.
Brown, S.L., Eisenhardt, K.M., 1997. The art of continuous change: linking complexity
theory and time-paced evolution in relentlessly shifting organizations. Admin. Sci.
Quart. 42(1), 1–34.
Brusoni, S., Prencipe, A., 2013. The organization of innovation in ecosystems: problem
framing, problem solving, and patterns of coupling. Adv. Strateg. Manage. 30, 167–
Casadesus-Masanell, R., Yoffie, D.B., 2007. Wintel: cooperation and conflict. Manage. Sci.
53(4), 584–598.
Casadesus-Masanell, R., Zhu, F., 2013. Business model innovation and competitive
imitation: the case of sponsor-based business models. Strateg. Manage. J. 34(4), 464–
Ceschin, F., 2013. Critical factors for implementing and diffusing sustainable product-service
systems: insights from innovation studies and companies’ experiences. J. Clean.
Prod. 45, 74–88.
Chatelin, M., 2016, April 8. The rise of Solar Power in the Netherlands. Lawyer Issue.
Retrieved December 3, 2016, from
Christensen, C.M., 1992a. Exploring the limits of the technology S-curve. Part II:
architectural technologies. Prod. Oper. Manag. 1(4), 358–366.
Christensen, C.M., 1992b. Exploring the limits of the technology S-curve. Part I: component
technologies. Prod. Oper. Manag. 1(4), 334–357.
Clarysse, B., Wright, M., Bruneel, J., Mahajan, A., 2014. Creating value in ecosystems:
crossing the chasm between knowledge and business ecosystems. Res. Policy 43(7),
- 36 -
Csaszar, F.A., Siggelkow, N., 2010. How much to copy? Determinants of effective imitation
breadth. Organ. Sci. 21(3), 661–676.
Damaraju, N.L., Barney, J.B., Makhija, A.K., 2015. Real options in divestment alternatives.
Strateg. Manage. J. 36(5), 728–744.
Dhanaraj, C., Parkhe, A., 2006. Orchestrating innovation networks. Acad. Manage. Rev.
31(3), 659–669.
Dolmans, S.A.M., Van Burg, E., Reymen, I.M.M.J., Romme, A.G.L., 2014. Dynamics of
resource slack and constraints: resource positions in action. Organ. Stud., 35(4), 511-
Eisenhardt, K.M., Martin, J.A., 2000. Dynamic capabilities: what are they? Strateg. Manage.
J. 21(10/11), 1105–1121.
EIT., 2016. Education | European Institute of Innovation & Technology (EIT). Retrieved
December 3, 2016, from
Fjeldstad, Ø.D., Snow, C.C., Miles, R.E., Lettl, C., 2012. The architecture of collaboration.
Strateg. Manage. J. 33(6), 734–750.
Garcia-Castro, R., Aguilera, R.V., 2015. Incremental value creation and appropriation in a
world with multiple stakeholders. Strateg. Manage. J. 36(1), 137–147.
Gavetti, G., Levinthal, D.A., Rivkin, J.W., 2005. Strategy making in novel and complex
worlds: the power of analogy. Strateg. Manage. J. 26(8), 691–712.
Gavetti, G., Levinthal, D.A., Rivkin, J.W., 2008. Response to Farjoun’s ‘Strategy making,
novelty, and analogical reasoning — commentary on Gavetti, Levinthal, and Rivkin
(2005)’. Strateg. Manage. J. 29(9), 1017–1021.
Gawer, A., Cusumano, M.A., 2002. Platform Leadership: How Intel, Microsoft, and Cisco
Drive Industry Innovation. Harvard Business School Press, Boston.
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., 2004. From sectoral systems of innovation to socio-technical systems: insights
about dynamics and change from sociology and institutional theory. Res. Policy 33(6–
7), 897–920.
Geels, F.W., 2005. Technological Transitions and System Innovations: A Co-evolutionary
and Socio-Technical Analysis. Edward Elgar Publishing, Cheltenham.
Geels, F.W., 2010. Ontologies, socio-technical transitions (to sustainability), and the multi-
level perspective. Res. Policy 39(4), 495–510.
Geels, F.W., Raven, R.P.J.M., 2006. Non-linearity and expectations in niche-development
trajectories: ups and downs in Dutch biogas development (1973–2003). Technol.
Anal. Strateg. 18(3-4), 375–392.
Geels, F.W., Schot, J., 2007. Typology of sociotechnical transition pathways. Res. Policy
36(3), 399–417.
George, G., 2005. Slack resources and the performance of privately held firms. Acad.
Manage. J. 48(4), 661–676.
Gold, B., 1983. On the adoption of technological innovations in industry. In The Trouble with
Technology, Macdonald, S., Lamberton, M.D.D., (eds). Francis Pinter, London, 104–
Gulati, R., Puranam, P., Tushman M.L., 2012. Meta-organization design: rethinking design in
interorganizational and community contexts. Strateg. Manage. J. 33(6), 571–586.
Hannah, D., Eisenhardt, K.M., 2016. How firms navigate cooperation and competition in
nascent ecosystems. Working paper.
Helfat, C.E., Finkelstein, S., Mitchell, W., Peteraf, M., Singh, H., Teece, D., Winter, S.G.,
2007. Dynamic Capabilities: Understanding Strategic Change in Organizations.
Blackwell Publishing, Oxford.
- 37 -
Hoogma, R., 2002. Experimenting for Sustainable Transport: The Approach of Strategic
Niche Management. Spon, London.
Huijben, J.C.C.M., Verbong, G.P.J., 2013. Breakthrough without subsidies? PV business
model experiments in the Netherlands. Energ. Policy 56, 362–370.
Hurst, A., 2014. The Purpose Economy: How Your Desire for Impact, Personal Growth and
Community Is Changing the World. Elevate: Boise, Idaho.
Iansiti, M., Levien, R., 2004. The Keystone Advantage: What The New Dynamics of Business
Ecosystems Mean for Strategy, Innovation, and Sustainability. Harvard Business
School Press, Boston.
Jaffe, A.B., Trajtenberg, M., Henderson, R., 1993. Geographic localization of knowledge
spillovers as evidenced by patent citations. Q. J. Econ. 108(3), 577–598.
Johnson, M.W., Suskewicz, J., 2009. How to jump-start the clean-tech economy. Harvard
Bus. Rev. 87(11), 52–63.
Kapoor, R., Furr, N.R., 2015. Complementarities and competition: unpacking the drivers of
entrants’ technology choices in the solar photovoltaic industry. Strateg. Manage. J.
36(3), 416–436.
Kapoor, R., Lee, J.M., 2013. Coordinating and competing in ecosystems: how organizational
forms shape new technology investments. Strateg. Manage. J. 34(3), 274–296.
Kemp, R.P.M., Loorbach, D., Rotmans, J., 2007. Transition management as a model for
managing processes of co-evolution towards sustainable development. Int. J. Sust.
Dev. World 14(1), 78–91.
Kemp, R.P.M., Schot, J., Hoogma, R., 1998. Regime shifts to sustainability through
processes of niche formation: the approach of strategic niche management. Technol.
Anal. Strateg. 10(2), 175–198.
Kershner, I., 2013, May 26. Israeli Electric Car Company Files for Liquidation. The New
York Times.
Koenig, G., 2012. Business ecosystems revisited. M@n@gement 15(2), 208–224.
Lavie, D, Haunschild, P.R., Khanna P., 2012. Organizational differences, relational
mechanisms, and alliance performance. Strateg. Manage. J. 33(13), 1453–1479.
Levinthal, D.A., 1998. The slow pace of rapid technological change: gradualism and
punctuation in technological change. Ind. Corp. Change 7(2), 217–247.
Li, L., 2005. The effects of trust and shared vision on inward knowledge transfer in
subsidiaries’ intra- and inter-organizational relationships. Int. Bus. Rev. 14(1), 77–95.
Li, Y.R., 2009. The technological roadmap of Cisco's business ecosystem. Technovation
29(5), 379–386.
Lie, M., Sørensen, K.H., 1996. Making Technology Our Own: Domesticating Technology
into Everyday Life. Scandinavian University Press, Oslo.
Loorbach, D., Rotmans, J., 2010. The practice of transition management: examples and
lessons from four distinct cases. Futures 42, 237–246.
Lubatkin, M., Florin, J., Lane, P., 2001. Learning together and apart: a model of reciprocal
interfirm learning. Hum. Relat. 54(10), 1353–1382.
Lynn, G., Morone, J.G., Paulson, A.S., 1996. Marketing and discontinuous innovation: the
probe and learn process. Calif. Manage. Rev. 38(3), 8–37.
MacKenzie, D., 1992. Economic and sociological explanations of technological change. In
Technological Change and Company Strategies: Economic and Sociological
Perspectives, Coombs, R., Saviotti, P., Walsh, V. (eds). Academic Press, London, 25–
Mahmood, I.P., Zhu, H., Zajac, E.J., 2011. Where can capabilities come from? Network ties
and capability acquisition in business groups. Strateg. Manage. J. 32(8), 820–848.
- 38 -
Maier, M., 2006, March 31. A radical fix for airlines: make flying free. Business 2.0
Magazine (CNN Money). Atlanta.
Markard, J., Raven, R.P.J.M., Truffer, B., 2012. Sustainability transitions: an emerging field
of research and its prospects. Res. Policy 41(6), 955–967.
Massa, L., Tucci, C.L., 2014. Business model innovation. In The Oxford Handbook of
Innovation Management, Dodgson, M., Gann, D.M., Phillips, N. (eds). Oxford
University Press, Oxford, 421–441.
Maurer, I., Bartsch, V., Ebers, M., 2011. The value of intra-organizational social capital: how
it fosters knowledge transfer, innovation performance, and growth. Organ. Stud.
32(2), 157–185.
McGrath, R.G., 2010. Business models: a discovery driven approach. Long Range Plann.
43(2–3), 247–261.
Mokyr, J., 1990. Punctuated equilibria and technological progress. Am. Econ. Rev. 80(2),
Moore, J.F., 1993. Predators and prey: a new ecology of competition. Harvard Bus. Rev.
71(3), 75–86.
Moore, J.F., 1998. The rise of a new corporate form. Wash. Quart. 21(1), 167–181.
Nambisan, S., Sawhney, M., 2011. Orchestration processes in network-centric innovation:
evidence from the field. Acad. Manage. Perspect. 25(3), 40–57.
Nelson, R.R., Winter, S.G., 1982. An Evolutionary Theory of Economic Change. Harvard
University Press, Cambridge.
Ofek, E., Wagonfeld, A.B., 2012. Speeding ahead to a Better Place. Harvard Business School
Business Case 9-512-056, 1–22.
O’Higgins, E., 1999. Ryanair: the low fares airline. University College Dublin Business Case
399-122-1, 1–30.
Osterwalder, A., Pigneur, Y., 2010. Business Model Generation: A Handbook for
Visionaries, Game Changers, and Challengers. John Wiley & Sons, Hoboken.
Overholm, H., 2015. Collectively created opportunities in emerging ecosystems: the case of
solar service ventures. Technovation 39-40(1), 14–25.
Podoynitsyna, K., Song, M., van der Bij, H., Weggeman, M.C.D.P., 2013. Improving new
technology venture performance under direct and indirect network externality
conditions. J. Bus. Venturing 28(2), 195–210.
Pontikes, E.G., 2012. Two sides of the same coin: how ambiguous classification affects
multiple audiences’ evaluations. Admin. Sci. Quart. 57(1), 81–118.
Raven, R.P.J.M., 2007. Niche accumulation and hybridisation strategies in transition
processes towards a sustainable energy system: an assessment of differences and
pitfalls. Energ. Policy 35(4), 2390–2400.
Raven, R.P.J.M., van den Bosch, S., Weterings, R., 2010. Transitions and strategic niche
management: towards a competence kit for practitioners. Int. J. Technol. Manage.
51(1), 57–74.
Raven, R.P.J.M., Heiskanen, E., Lovio, R., Hodson, M., Brohmann, B., 2008. The
contribution of local experiments and negotiation processes to field-level learning in
emerging (niche) technologies: meta-Analysis of 27 new energy projects in Europe.
B. Sci. Technol. Soc. 28(6), 464–477.
Raven, R.P.J.M., Verbong, G.P.J., 2004. Ruling Out Innovations - Technological Regimes,
Rules and Failures: The Cases of Heat Pump Power Generation and Bio-gas
Production in the Netherlands. Innov.-Manag. Policy P., 6(23), 178–198.
Regani, S., Dutta, S., 2003. Ryanair: the Southwest of European airlines. ICMR Case
collection Business case BSTR-059, 1–14.
- 39 -
Riffe, D., Lacy, S., Fico, F.G., 2013. Analyzing Media Messages: Using Quantitative Content
Analysis in Research. Routledge: New York.
Ritala, P., Agouridas, V., Assimakopoulos, D., Gies, O., 2013. Value creation and capture
mechanisms in innovation ecosystems: a comparative case study. Int. J. Technol.
Manage. 63(3), 244–267.
Rong, K., Shi, Y., 2015. Business Ecosystems: Constructs, Configurations, and the Nurturing
Process. Palgrave Macmillan, London.
Rosenkopf, L., Almeida, P., 2003. Overcoming local search through alliances and mobility.
Manage. Sci. 49(6), 751–766.
Rotmans, J., Loorbach, D., 2006. Transition management: reflexive steering of societal
complexity through searching, learning and experimenting. In The Transition to
Renewable Energy: Theory and Practice, Van Den Bergh, J.C.J.M., Bruinsma, F.R.,
(eds). Edward Elgar Publishing, Cheltenham.
Sammarra, A., Biggiero, L., 2008. Heterogeneity and specificity of inter-firm knowledge
flows in innovation networks. J. Manage. Stud. 45(4), 800–829.
Santos, F.M., Eisenhardt, K.M., 2009. Constructing markets and shaping boundaries:
entrepreneurial power in nascent fields. Acad. Manage. J. 52(4), 643–671.
Schön, D.A., 1984. The Reflective Practitioner: How Professionals Think in Action. Basic
Books, New York.
Schot, J., Geels, F.W., 2007. Niches in evolutionary theories of technical change. J. Evol.
Econ. 17(5), 605–622.
Schot, J., Geels, F.W., 2008. Strategic niche management and sustainable innovation
journeys: theory, findings, research agenda, and policy. Technol. Anal. Strateg. 20(5),
Shankar, B., 2009. Business model innovation by Better Place: a green ecosystem for the
mass adoption of electric cars. ICMR Center for Management Research Business
Case 310-147-1, 1–23.
Sharapov, D., Thomas, L.D.W., Autio, E., 2013. Building ecosystem momentum: the case of
AppCampus. Paper presented at the DRUID Society Conference, Barcelona, Spain.
Simon, H.A., 1956. Rational choice and the structure of the environment. Psychological
Review 63(2), 129–138.
Smith, A., 2007. Translating sustainabilities between green niches and socio-technical
regimes. Technol. Anal. Strateg. 19(4), 427–450.
Smith, A., Raven, R.P.J.M., 2012. What is protective space? Reconsidering niches in
transitions to sustainability. Res. Policy 41(6), 1025–1036.
Sommer, S.C., Loch, C.H., 2004. Selectionism and learning in projects with complexity and
unforeseeable uncertainty. Manage. Sci. 50(10), 1334–1347.
Srinivasan, R., Lilien, G.L., Rangaswamy, A., 2006. The emergence of dominant designs. J.
Marketing 70(2), 1–17.
Suarez, F.F., Grodal, S., Gotsopoulos, A., 2015. Perfect timing? Dominant category,
dominant design, and the window of opportunity for firm entry. Strateg. Manage. J.
36(3), 437–448.
Teece, D.J., 2007. Explicating dynamic capabilities: the nature and microfoundations of
(sustainable) enterprise performance. Strateg. Manage. J. 28(13), 1319–1350.
Teece, D.J., Pisano, G., Shuen, A., 1997. Dynamic capabilities and strategic management.
Strateg. Manage. J. 18(7), 509–533.
Thomas, L.D.W., Autio, E., Gann, D.M., 2014. Value creation and appropriation in platform
ecosystems. Working paper, Imperial College Business School, London.
Tripsas, M., Gavetti, G., 2000. Capabilities, cognition, and inertia: evidence from digital
imaging. Strateg. Manage. J. 21(10/11), 1147–1161.
- 40 -
Ulaga, W., Reinartz, W.J., 2011. Hybrid offerings: how manufacturing firms combine goods
and services successfully. J. Marketing 75(6), 5-23.
Van de Ven, A.H., Poole, M.S., 1995. Explaining development and change in organizations.
Acad. Manage. Rev. 20(3), 510–541.
Van der Vleuten, E.B.A., Högselius, P., 2012. Resisting change? The transnational dynamics
of European energy regimes. In Governing the Energy Transition: Reality, Illusion or
Necessity?, Verbong, G.J.P., Loorbach, D., (eds). Routledge, London, 75–100.
Voss, C.A., 1984. Technology push and need pull: a new perspective. R&D Manage. 14(3),
Walrave, B., Van Oorschot, K.E., Romme, A.G.L., 2011. Getting trapped in the suppression
of exploration: a simulation model. J. Manage. Stud. 48(8), 1727–1751.
Wieczorek, A.J., Hekkert, M.P., 2012. Systemic instruments for systemic innovation
problems: A framework for policy makers and innovation scholars. Science and
Public Policy, 39(1), 74–87.
Williamson, P.J., De Meyer, A., 2012. Ecosystem advantage: how to successfully harness the
power of partners. Calif. Manage. Rev. 55(1), 24–46.
Witkamp, M.J., Raven, R.P.J.M., Royakkers, L.M.M., 2011. Strategic niche management of
social innovation: the case of social entrepreneurship. Technol. Anal. Strateg. 23(6),
Zott, C., Amit, R., Massa, L., 2011. The business model: recent developments and future
research. J. Manage. 37(4), 1019–1042.
... The platform sponsor increases the legitimacy of the ecosystembased standard through alignment with the socio-technical environment (Walrave et al., 2018). However, the legitimacy and identity associated with prior versions in turn causes standard inertia that hinders the emergence of new ecosystem-based standards, thus slowing down the progress through the technology life cycle . ...
... Committee based Market based Government based Adomavicius et al., 2012Aijaz, 2020Aaldering et al., 2019Carvalho, 2018Engert et al., 2022Alberti et al., 2003Arribas-Ibar et al., 2021Gibbons et al., 2008Hein et al., 2019Ansari and Garud, 2009Arribas-Ibar et al., 2022Helveston et al., 2019Schmeiss et al., 2019Bechtold, 2003Brem and Nylund, 2021Karachalios and McCabe, 2018Spaeth and Niederhöfer, 2022Bouhnik and Giat, 2015Brem and Nylund, 2022Lenard, 2019Tee, 2019Cvar et al., 2020Cenamor, 2021Mergel, 2018Wareham et al., 2014Costabile et al., 2022Cennamo et al., 2020St-Pierre et al., 2015den Uijl et al., 2013Cervantes-Zacarés et al., 2022Tsatsou et al., 2010Dey et al., 2019Chang and Chen, 2020Walrave et al., 2018Fréry et al., 2015Chen et al., 2017Hernández-Muñoz et al., 2011Chester and Dentskevich, 1995 Government and Committee Hodapp and Hanelt, 2022Dedehayir and Mäkinen, 2011Groesser, 2014Hogle, 2009Dupont et al., 2017Househ et al., 2015Eckhardt et al., 2018 Government and Market Jones et al., 2021bFerràs-Hernández et al., 2017Banda et al., 2018 Lin-Gibson and Srinivasan, 2020 Frenkel et al., 2015Bessagnet et al., 2021Losavio et al., 2004Fürstenau et al., 2021Polydoropoulou et al., 2020Marshall et al., 2016Gagliardi et al., 2017Pushpananthan and Elmquist, 2022McDonnell et al., 2005Garnsey et al., 2008Thomas et al., 2022Miller and Toh, 2022Gawer and Cusumano, 2008Wang and Ren, 2012Moon and Lee, 2020Gawer and Cusumano, 2014Zhang and Williamson, 2021Nishioka et al., 2016Holgersson et al., 2022Parker et al., 2017Husmann et al., 2008 Committee and Market Ranganathan et al., 2018Jiang, 2022Calcei and M'Chirgui, 2012Robert et al., 2017Jones et al., 2021aJiang et al., 2020Rysman and Simcoe, 2008Kang and Downing, 2015Planko et al., 2019Shim et al., 2019Kapoor and Furr, 2015 Committee based Market based Market based (ctd.) Simcoe, 2012Kar et al., 2018Tchoffa et al., 2021Simcoe et al., 2009Kim and Shin, 2017Teece, 2018Tan et al., 2020bKirsten and Hummel, 2016Verduin, 1992Tchoffa et al., 2016Konsynski and McFarlan, 1990Viecens, 2011Toh and Miller, 2017Kumar et al., 2020Waßenhoven et al., 2021Vakili, 2016Kwak et al., 2019Weber and Hine, 2015Varjovi and Babaie, 2020Lampert et al., 2020Wulfert et al., 2022Leuenberger and Leuenberger, 2016Yildirim et al., 2022Zhou et al., 2020Lingens et al., 2021Luo, 2018Mäkinen and Dedehayir, 2014Marion et al., 2015Markus and Bui, 2012McIntyre and Srinivasan, 2017Mesquita and Sugano, 2013Miric et al., 2023Pankov et al., 2021Parker and Van Alstyne, 2018Presenza et al., 2019Rajala et al., 2016Rathje and Katila, 2021Sandner et al., 2020Slowak, 2012Tamayo-Orbegozo et al., 2017Tan et al., 2020a ...
Open access link: Digital platforms are changing economies and societies, challenging the fundamental institutions of democracy and requiring an understanding of the driving factors behind the development of such platforms. Therefore, we have investigated the impact of dominant platforms on standardization in innovation ecosystems on the level of technologies, firms, and societies. We have conducted a systematic review of the literature on standardization and ecosystems. We define ecosystem-based standardization as the development of a standard embodied in a dominant platform. Important innovation-related findings include that processes are embedded in the platform, allowing for complementary innovation using modular capabilities and, thus, requiring the traditional view of the relationship between product and process innovation to be revisited. Ecosystem-based standardization foments both technological and organizational modularity, which increases innovation speed as well as synergies within the ecosystem. However, the power asymmetry generated by ecosystem-based standardization favors value appropriation by platform sponsors, which has vast implications for the development of regulations and institutions.
... Prime examples of disciplines dabbling in transition research include management (Bögel et al., 2019;Gatti et al., 2019), economics (Hafner et al., 2020), geography (Fazey et al., 2018Wanner et al., 2018), and sociology (Papachristos et al., 2018). Walrave et al. (2018), for example, focused on action research and process-oriented approaches to study transition problems. In this respect, one main driver behind the emergence of research-to-practice transitions has been the search for new insights into achieving a desirable evidence-based practice. ...
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In this book, circularity is introduced and discussed as a driver of the UN Sustainable Development Goals (SDGs) and its progress in emerging and developing countries. As we move forward, we want to capture the realities of the circular economy concept as much as possible by moving quickly to the fascinating theoretical and practical progress across various sectors in these economies. The circular economy approach is inherently accompanied by a wide range of other issues, which one must address while exploring its progress path: early in the book, a state-of-the-art review provides a theoretical framework for mapping the subtle characteristics, scope, and progress of emerging and developing economies, while the diverse case studies provide insight into the real stories—the progress and challenges. This book was written to help students at universities, and other institutions of higher education find empirical case studies on circular economy from emerging and developing countries. It is also intended for people pursuing a professional career in sustainability and readers with a general interest in circular economy and the SDGs. At an advanced level, this text can also be used as a handbook, providing an overview of current theoretical and empirical debates and controversies regarding circular strategies and SDGs. As well as providing a non-technical entry point towards circular economy strategies in emerging and developing economies, the book provides a broader perspective on circular economy as an emerging field. This indispensable reference is written by a team of international scholars from a variety of disciplines, including development, education, business, ecology, geography, and planning, and presents the current state of circular economy research within emerging and developing economies.
... Prime examples of disciplines dabbling in transition research include management (Bögel et al., 2019;Gatti et al., 2019), economics (Hafner et al., 2020), geography (Fazey et al., 2018;Wanner et al., 2018), and sociology (Papachristos et al., 2018). Walrave et al. (2018), for example, focused on action research and process-oriented approaches to study transition problems. In this respect, one main driver behind the emergence of research-to-practice transitions has been the search for new insights into achieving a desirable evidence-based practice. ...
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The continuing emergence of circular economy (CE) research and practice as a critically important concept for the foreseeable future has renewed interest in understanding its theory and practice. In this chapter, we first analyse the evolution of CE research and practice by examining research published over the last decade. We then summarise the key themes emerging from review articles over the past decades. These themes form the basis of a proposed integrative CE research and practice synergy model. We further offer suggestions for future research by proposing critical topics and emerging themes for future research, such as organisational circular economy attitudes, knowledge synthesis and exchange, circular economy practice taxonomy, and circular economy pandemic response. We conclude by offering conceptual perspectives and highlighting key recent developments that will likely impact future practice and should be addressed by scholars.
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A falta de consistência teórica em relação à terminologia do ecossistema de inovação produz uma teoria muito fragmentada e diversificada, que não garante consolidação do conhecimento. Dessa forma, através de uma revisão sistemática da literatura indexada na base de dados Web of Science de 2017 a 2022, este trabalho se propôs a verificar o atual panorama publicações a respeito dos conceitos atribuídos ao ecossistema de inovação. Primeiro, mostramos um panorama de publicações a respeito da conceituação dos ecossistemas, abordando os anos, as revistas e os autores mais representativos. Em seguida trouxemos um quadro conceitual a respeito dos ecossistemas que foram abordados nesses últimos cinco anos, juntamente com uma discussão cronológica da evolução do ecossistema de negócios e inovação, trazendo os principais termos usados e as similaridades e disparidades entre eles.
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This paper is about the design, functions, and implementation of regulatory innovations platforms for public utility. Such platforms are intended to enable the rapid testing of new technologies and business models, incorporating at least some regulatory flexibility as necessary to facilitate testing, while managing and limiting exposure to associated risks. The platforms are also designed to ensure rapid learning for all participating parties, including innovators, utility companies, and utility regulators. Almost every regulatory jurisdiction is home to at least some kinds of organizations and functions that support innovations, and participants often include one or more government agencies. But not every innovation platform focuses on or includes regulatory innovations. At least some innovations in the realm of public utility services could possibly be associated with, or even necessitate changes in, long-standing regulatory practices. Therefore, industry participants might have a special interest in mechanisms that can allow regulatory flexibility, at least to enable innovations trials. This paper seeks to identify, describe, and review regulatory innovations platforms that include four major features: 1. Public announcement of the innovations support activities, including a broad invitation for participation by all parties that are genuinely interested in potentially viable innovations 2. Some focus on regulatory innovation, which might include innovations in financial incentives and business models for regulated utility companies, competitive utility services providers, and new market participants 3. Regulatory flexibility, where regulators might relax or waive rules or agree to allow, during innovations trials, specific activities that could otherwise face challenges under existing rules and regulations 4. A prominent oversight role for the utility regulatory authority, participating in the design and implementation of trial projects intended to validate innovations This report explores reasons why regulatory innovation is needed now and examines how regulatory innovations platforms are defined, designed, and implemented. The current heightened interest in, and urgency associated with regulatory innovation stems from perceived needs resulting from multiple interconnected factors. This report reviews those underlying pressures for change, and briefly describes ongoing energy regulatory innovations activities in a dozen US states and the District of Columbia. It reviews literature about regulatory innovations platforms, describing both the major potential benefits associated with such platforms, and their attendant potential risks, tensions, challenges, and obstacles. Then the report presents preliminary ideas about how state policy makers, including public utility regulatory commissions, might consider implementing such approaches. An Appendix briefly summarizes energy utility regulatory innovations platforms already operating or planned for 15 other countries. The report is also available from the NARUC web site, at:
This paper focuses on dynamic capabilities and, more generally, the resource‐based view of the firm. We argue that dynamic capabilities are a set of specific and identifiable processes such as product development, strategic decision making, and alliancing. They are neither vague nor tautological. Although dynamic capabilities are idiosyncratic in their details and path dependent in their emergence, they have significant commonalities across firms (popularly termed ‘best practice’). This suggests that they are more homogeneous, fungible, equifinal, and substitutable than is usually assumed. In moderately dynamic markets, dynamic capabilities resemble the traditional conception of routines. They are detailed, analytic, stable processes with predictable outcomes. In contrast, in high‐velocity markets, they are simple, highly experiential and fragile processes with unpredictable outcomes. Finally, well‐known learning mechanisms guide the evolution of dynamic capabilities. In moderately dynamic markets, the evolutionary emphasis is on variation. In high‐velocity markets, it is on selection. At the level of RBV, we conclude that traditional RBV misidentifies the locus of long‐term competitive advantage in dynamic markets, overemphasizes the strategic logic of leverage, and reaches a boundary condition in high‐velocity markets. Copyright © 2000 John Wiley & Sons, Ltd.
This paper focuses on dynamic capabilities and, more generally, the resource-based view of the firm. We argue that dynamic capabilities are a set of specific and identifiable processes such as product development, strategic decision making, and alliancing. They are neither vague nor tautological. Although dynamic capabilities are idiosyncratic in their details and path dependent in their emergence, they have significant commonalities across firms (popularly termed ‘best practice’). This suggests that they are more homogeneous, fungible, equifinal, and substitutable than is usually assumed. In moderately dynamic markets, dynamic capabilities resemble the traditional conception of routines. They are detailed, analytic, stable processes with predictable outcomes. In contrast, in high-velocity markets, they are simple, highly experiential and fragile processes with unpredictable outcomes. Finally, well-known learning mechanisms guide the evolution of dynamic capabilities. In moderately dynamic markets, the evolutionary emphasis is on variation. In high-velocity markets, it is on selection. At the level of RBV, we conclude that traditional RBV misidentifies the locus of long-term competitive advantage in dynamic markets, overemphasizes the strategic logic of leverage, and reaches a boundary condition in high-velocity markets. Copyright © 2000 John Wiley & Sons, Ltd.
The success of an innovating firm often depends on the efforts of other innovators in its environment. How do the challenges faced by external innovators affect the focal firm's outcomes? To address this question we first characterize the external environment according to the structure of interdependence. We follow the flow of inputs and outputs in the ecosystem to distinguish between upstream components that are bundled by the focal firm, and downstream complements that are bundled by the firm's customers. We argue that the effect of external innovation challenges depends not only on their magnitude, but also on their location in the ecosystem relative to the focal firm - whereas greater innovation challenges in components enhances the benefits that accrue to technology leaders, greater innovation challenges in complements erodes these benefits. We further argue that the effectiveness of vertical integration as a strategy to manage ecosystem interdependence increases over the course of the technology life cycle. We explore these arguments in the context of the global semiconductor lithography industry from its emergence in 1962 to 2005 across nine distinct technology generations. We find strong support for our arguments.