Technology ventures and their ecosystem within the socio-technical settings : a systemic frameworkCitation for published version (APA):Walrave, B., Podoynitsyna, K. S., Talmar, M., Verbong, G. P. J., & Romme, A. G. L. (2013). Technologyventures and their ecosystem within the socio-technical settings : a systemic framework. Poster sessionpresented at First International Entrepreneurship Research Exemplars Conference, May 23-25, 2013, Catania,Italy, Catania, Italy.

Document status and date:Published: 01/01/2013

Document Version:Accepted manuscript including changes made at the peer-review stage

Please check the document version of this publication:

• A submitted manuscript is the version of the article upon submission and before peer-review. There can beimportant differences between the submitted version and the official published version of record. Peopleinterested in the research are advised to contact the author for the final version of the publication, or visit theDOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and pagenumbers.Link to publication

General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.

• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.

If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, pleasefollow below link for the End User Agreement:www.tue.nl/taverne

Take down policyIf you believe that this document breaches copyright please contact us at:openaccess@tue.nlproviding details and we will investigate your claim.

Download date: 31. Mar. 2020

1

TECHNOLOGY VENTURES AND THEIR ECOSYSTEM WITHIN THE SOCIO-

TECHNICAL SETTINGS: A SYSTEMIC FRAMEWORK

Bob Walrave

Ksenia S. Podoynitsyna

Madis Talmar

Geert P. J. Verbong

A. Georges L. Romme

Key words: technology ventures, ecosystem management, transition management, systemic

framework

Start-up success is generally believed to be primarily determined by a thorough understanding of the

customer combined with optimal exploitation of resources (e.g., Henderson and Clark, 1990; Perry et

al., 2012). Nevertheless, few technology entrepreneurs are successful, even those who clearly fulfill

these criteria. The primary reason for such failures has been the ongoing transformation from separate

products and services toward the need for highly ‘integrated’ solutions and services, such as cars with

integrated navigation and media systems (Adner, 2012; Adner, 2006). In the modern ‘connected’

world, more and more industries exhibit indirect network externalities: settings in which the value of a

particular product or service depends on other products or services (Podoynitsyna et al., 2013;

Srinivasan et al., 2004; Stremersch et al., 2010; Wuyts et al., 2010). Thus, the high-tech industry is

increasingly characterized by interdependence among firms, organizations, and other entities (Adner,

2012; Adner and Kapoor, 2010; Raven, 2007). Failure rate of technology ventures remain high (Song

et al., 2008). Although consumer insight and optimal exploitation of resources still contribute to the

success of high-tech startups, these capabilities are no longer sufficient (Adner, 2012; Srinivasan et

al., 2004).

The notion of ‘ecosystem management’ has been introduced in order to address these

challenges (Iansiti and Levien, 2004). In this respect, the development and maintenance of ecosystems

is becoming increasingly important for the success of technology entrepreneurs. In order to create and

appropriate value by way of new technologies, technology entrepreneurs need to collaborate with

many partners in their ecosystem surrounding the new technology (Adner, 2012; Sarasvathy, 2001).

Designing and managing the interdependencies between all partners and their environments requires

not only a deep understanding of the venture’s own (new) business model and innovation, but also a

comprehensive understanding of the roles and positions of the other actors within the ecosystem. For

example, in many cases, other companies have to adopt the startup’s innovation (i.e., adoption chain

risk caused by intermediaries), or other firms have to co-innovate alongside the technology

2

entrepreneur (i.e., co-innovation risk), for the innovative offering to become successful (Adner, 2012;

Adner, 2006).

Another systemic perspective builds on socio-technical thinking, to address broader concerns

like the political constellation, the dominant artifacts and prevailing infrastructure that are

increasingly influential on entrepreneurial success chances (i.e., socio-technical environment and

socio-technical regime) (Grin et al., 2010; Raven, 2007; Verbong and Loorbach, 2012). New high-

tech innovation often has to challenge the dominant practices and regimes. Consider the changes to

the recharging and refueling infrastructure necessary to realize the large-scale introduction of electric

vehicles. In this respect, such transition would challenge – and find resistance from – the powerful

regime (i.e., the shared routines among the engineering community and across firms that results from

a certain dominant technological design) underlying the existing infrastructure for gas-powered cars

(Nelson and Winter, 1982). As such, the introduction of this type of innovation can only be successful

if it considers and transforms societal subsystems in a rather radical manner (Raven, 2007). Therefore,

another crucial factor for the success of technology ventures, besides active management of their

ecosystem, is the embedding of the ecosystem in its larger social-technical regime and landscape

(Grin et al., 2010). This implies that entrepreneurs need to actively influence, manage and/or

challenge the dominant – and upcoming – ‘socio-technical regime’, also referred to as ‘transition

management’ (Grin et al., 2010; Rotmans et al., 2001).

While ecosystem management is mainly about managing an entrepreneur’s local

technological niche in relation to its key suppliers, customers, service providers and other actors,

transition management is about challenging the dominant rule sets that are supported by larger

incumbent social networks and embedded in dominant artifacts and prevailing infrastructure (Kemp et

al., 2007; Rotmans et al., 2001). As such, in order to develop high-tech innovations, and then

successfully scale up these innovations (e.g., cross the infamous ‘chasm’) (Moore, 1991), there is a

need for high-tech entrepreneurs (and scholars studying them) to adopt a systemic lens which

combines ecosystem and transition management.

The aim of this research, therefore, is to develop a theoretical framework that provides a

systemic perspective on technology ventures’ innovation processes. As such, in this paper we develop

such a systemic lens by combining and integrating the ecosystem development and transition

management literatures (Adner, 2012; Adner and Kapoor, 2010; Geels, 2002; Raven, 2007).

Developing this framework is important, because it can provide a solid basis for (re)developing tools

that help technology start-ups become more successful in commercializing their offerings. This paper

contributes to the literature by connecting and synthesizing the ecosystem and socio-technical system

literatures in a multi-level framework of technology-driven innovation processes.

This paper is structured as follows. First, we review the literature on ecosystem management

and transition management. In this review, the boundary conditions of the two different frameworks

are distilled, thereby uncovering their potential overlap. Hereafter, we integrate the two frameworks

3

and, from there, develop a systemic perspective on entrepreneurial innovation process. We conclude

this theoretical review by discussion, conclusions, and opportunities for future research.

LITERATURE REVIEW

Ecosystem management

It has long been recognized that technology ventures face tremendous challenges related to the

development and production of their innovations. As such, research with respect to innovation

processes has worked on and provided a rich set of dimensions, which characterize – and aim to deal

with – the internal challenges that entrepreneurs face (Henderson and Clark, 1990; Tushman and

Anderson, 1986). Think here of ideas and tools like effectuation, stage-gates and portfolio

management techniques (Chao and Kavadias, 2008; Cooper, 2008; Sarasvathy, 2001); tactics that all

emphasize the internal structure and capability of the entrepreneur. Nevertheless, the challenges faced

by contemporary high-tech startups are often not limited to the focal startup any more. Recent

technological and societal advancements cause people and technology to be increasingly connected,

transforming traditional markets into increasingly networked ones (Adner, 2006; Podoynitsyna et al.,

2013). In this respect, the success chances of an innovation are highly depending on the technology

venture’s environment – its innovation ecosystem – for its own success (Adner and Kapoor, 2010).

An innovation ecosystem refers to (Adner, 2006, p.2): “the collaborative arrangements

through which firms combine their individual offerings into a coherent, customer-facing solution”. In

this respect, an innovation ecosystem dictates that the success of a technology venture depends on its

ability to create alignment between partners in the value chain (e.g., upstream suppliers and

downstream customers), who must work together to bring an invention to the market (Adner, 2012).

Enabled by information technologies that have drastically reduced the costs of coordination,

innovation ecosystems have become a core element in the growth strategies of firms in a wide range

of industries. While leading exemplars tend to come from high-tech corporate settings (think Intel,

Nokia, SAP, and Cisco), ecosystem strategies are being deployed for the development of innovation

in industries as varied as commercial printing, financial services, basic materials, and logistics

provision (Adner, 2006).

The ecosystem construct, as defined above, is relatively new but has gained increasing

scholarly attention (Adner, 2006; Adner and Kapoor, 2010; Iansiti and Levien, 2004). Research till

date has mainly focused on creating an understanding of the coordination among firms in exchange

networks that face simultaneous cooperation and competition (e.g., Afuah, 2000). In this respect,

these studies are primarily interested in learning how firms capture/loose value by means of

interaction, in the context of the ecosystem (as such extending the studies on bilateral partnerships).

For instance, Afuah (2000) argues that, after a post-technological change, a firm’s performance is

reduced to the extent to which such technological change decreased the value of its co-opetitors’

capabilities (i.e., supplies, customers, and complementors). Furthermore, Adner and Kapoor (2010)

find that innovation challenges can either enhance or erode a firm’s competitive advantage, depending

4

on the location of the firm within its ecosystem. As such, the embeddedness of a technology venture

within its ecosystem brings along – besides opportunities – risks that need to be considered.

In this respect, three ecosystem risks are identified that need to be managed while developing

an innovation (Adner, 2012): (1) execution risk, (2) co-innovation risk, and (3) adoption-chain risk.

The first risk, execution risk, refers to the initiative risks of managing the focal project. This risk

refers to the evaluation of the feasibility of the project itself, by the technology entrepreneur (e.g.,

technical feasibility of the innovation, what is the benefit to the customers, what is the quality of the

project team). The second risk, co-innovation risk, refers to those actors within the ecosystem who

also need to develop innovation, if the technology entrepreneur’s offering is to become successful. As

such, this risk is about chance that complementary innovators fail and, as such, the innovation of the

entrepreneur (Adner, 2006). The last risk, adoption chain risk, is about the chance of not getting the

innovation adopted across the complete value chain. More specifically, this specific risk concerns

intermediaries positioned between the venture’s innovation and the final customer, who need to adopt

the technology venture’s innovation, in order to bring true value to the end customer. In this respect,

the further the venture is located up the value chain, the more intermediaries there are, and the higher

the adoption chain risks (Adner, 2006).

Creating a deep understanding of the three described risks allows for the technology

entrepreneur to craft informed expectations among the relevant players within its ecosystem. Even if

the risks turn out high, at least they can be managed as they are known beforehand (Adner, 2012). In

this respect, ecosystem management can be considered as an important tool for the management of

innovation expectations among stakeholders within the ecosystem. Furthermore, knowing the risks

allows for the development of a so-called minimum viable footprint: the simplest ecosystem possible

that still creates new value (Adner, 2012, p.179). The minimum viable footprint aims at creating value

early which allows for a staged expansion of the project and ecosystem (i.e., potential partners will be

more interested in the innovation since there is already an established customer pool).

The description of the three types of risk then also clearly delineates the boundaries of the

ecosystem framework. Studies concerned with innovation ecosystems are clearly sensitive to the

presence of different roles and actors within the ecosystem. More specifically, clear distinctions are

made between suppliers, complementors, and buyers. Nevertheless, the main limitation is that

ecosystem management fails to consider the interaction between different levels (i.e., macro-level and

meso-level aspects, such as the socio-technical regime and landscape). That is, ecosystem

management specifically targets actors that are located within the value chain of the innovation (co-

innovators and intermediaries that need to adopt the innovation – all micro level aspects). The current

‘technological regime’ (Nelson and Winter, 1982) – the shared routines among the engineering

community and across firms that results from a certain dominant technological design – also influence

the success chances of an technology venture to great extent. Think, for instance, about the

5

introduction of an electrically powered car within a technological regime that favors combustion

engines.

In this respect, certain variations (close to the standing dominant artifact) are often preferred

above more deviating innovation. Such, usually incremental improvements, fit the prevailing routines

and beliefs, captured by the current technological regime, better and result therefore in less adoption

resistance (Nelson and Winter, 1982; Raven, 2007). Policymakers, industry consortia and other

standards-setting agencies, influenced by stakeholders of the current dominant design, often channel

resources to an existing and proven technology (Adner and Snow, 2010). This is likely to increase the

performance of the ‘old’ technology, thereby creating resistance to any new offering (which would

potentially render to the old technology obsolete). Such influences, originating from the current

technological regime or landscape and capture by the notion of ‘transition management’, need to be

factored explicitly – alongside the actors described within the ecosystem literature – if the technology

venture’s invention is to succeed on the marketplace (Geels, 2002; Smith and Raven, 2012).

Transition Management

Transition Management aims to explain the process of transformation of socio-political landscapes,

socio-technical practices and the structural character of society from one technology state to another

(Verbong and Loorbach, 2012). Think, for instance, of the change from physical telegraphy toward

electric telephony and the related shift within society as a whole. Such transition involved many

different actors and levels. Transition management entails a multi-level perspective detailing that

transitions come about through interactions between processes at different levels (Schot and Geels,

2008). Most authors, with respect to transition management, discriminate between processes on three

levels that conceptualize transformations (e.g., Verbong and Loorbach, 2012) (from macro, to meso,

to micro-level): (1) socio-technical landscape, (2) socio-technical regime, and (3) technological

niches.

Socio-technical landscape

The socio-technical landscape highlights the role of events and development in the, to the technology

venture’s, exogenous environment (Raven, 2007). It captures all macro-level aspects that cannot be

controlled by the socio-technical regime or niche (Geels and Schot, 2007). As such, the landscape

encompasses the overall socio-technical setting: Both intangible aspects (e.g., social values, political

constellations, economic cycles, the broad societal trends, etc.) and tangible aspects (e.g., institutions,

the marketplace, geographical position, climate, available resources of the land, etc.) (Geels, 2002;

Verbong and Loorbach, 2012).

Generally, changes at this level occur rather slowly. Think for instance of the current gradual

increase in environmental awareness. This cultural process is leading to pressure on numerous

technological regimes within the aviation and agriculture industry, whilst simultaneously providing

openings for new technologies to emerge (e.g., energy efficient jet planes, and biofuels). But the

concept is also used to capture the influence of rapid historical pulses (Raven, 2007). Think, for

6

instance, of the impact that the Chernobyl explosion had on the technological regimes related to

power.

As such, this level concerns the macro-aspects involved with developing an innovation as

entrepreneur. Dynamics within the socio-technical landscape shape to a large extent the conditions to

which technology ventures can operate on the short term (i.e., anticipating the current dominant socio-

technical landscape) or the long term (i.e., foreseeing changes in the socio-technical landscape). In

this respect, the dynamics at this level often create a window of opportunities for new developments

(Raven, 2007) for technology ventures.

Socio-technical regime

The socio-technical regime captures meso-aspects and refers to (Rip and Kemp, 1998, p.340): “the

rule-set or grammar embedded in a complex of engineering practices, production process

technologies, product characteristics, skills and procedures, ways of handling relevant artifacts and

persons, ways of defining problems; all of them embedded in institutions and infrastructures”. Socio-

technical regimes are similar and shared among many different locations making it difficult to change

one rule without altering others (Geels, 2004; Geels, 2002; Raven, 2005). Such rules are assumed to

enable and constrain activities within certain communities and tend to offer more structuration to local

practices (Raven, 2005).

It is important to note that socio-technical regimes do not encompass the entirety of other

regimes, but only refer to those rules, which are aligned to each other and are from a particular

domain (e.g. energy, water, transport) (Geels, 2004). To extend that point, Geels (2005) describes that

a socio-technical regime refers to the alignment of the rules upheld by the different social groups and

is centered around a technological system or technological artifact. Thus, the electricity regime, for

example, refers to the alignment between the rules upheld by users (e.g., their preferences regarding

electricity supply), policymakers (e.g., regulations regarding emissions), engineers (e.g., design

heuristics regarding power production), et cetera.

Change at the regime level is primarily incremental of nature, geared toward optimization of

the current dominant design. In this respect, radical change is potentially threatening to the vested

interests of the established regime. Such behavior creates inertia within key industries which can be

seen as a root cause for the difficulties in achieving transitions to, for example, sustainability

(Verbong and Loorbach, 2012). This level thus accounts for the stability of existing large-scale

technological systems (in transport, energy, etc.) (Schot and Geels, 2008).

The conceptualization of regimes incorporates a wide set of selection processes to better

explain the emergence and decline of socio-technical regimes: Industry structure, technologies and

infrastructures, knowledge base, users, relations and markets, public policies and political power, and

the cultural significance and associations of the regime (Smith and Raven, 2012). Furthermore,

building on neo-institutional theory, three dimensions of socio-technical regimes can be distinguished:

regulative (laws, regulations, standards, procedures, incentive structures, governance systems –

7

legally sanctioned), normative (values, norms, role expectations, duty, codes of conduct, behavioral

practice, identity – morally governed), and cognitive (belief systems, models of reality, bodies of

knowledge, guiding principles, search heuristics – culturally supported, conceptually correct) (Scott,

1995).

Technology niche and experiments

A technology niche can be defined as (Schot and Geels, 2008, p.538): “Protected spaces that allow

nurturing and experimentation with the co-evolution of technology, user practices, and regulatory

structures”. The description of landscape and regime, as described earlier, imply that the mainstream

selection environments hinder the development of radical innovation (Smith and Raven, 2012).

Because these niches are protected or insulated from ‘normal’ market selection in a regime, they act

as ‘incubation rooms’ for radical novelties (Schot and Geels, 2008). As such, the development of such

innovation should take place in initial niche markets, where it can build up enough internal

momentum through a process of niche accumulation (Raven, 2007; Smith and Raven, 2012). Initial

niches can be passive spaces where the selection pressures are felt less keenly for contingent rather

than strategic reasons, and in a sense precede mobilisation by advocates. The innovation can then

move from one niche market to another, thereby improving the fit between the technology and

markets, increasing the internal momentum, making for a new regime to emerge (Raven, 2007).

Several historical examples illustrate the working of this mechanism. Think about the

application of solar cells in space travel and mobile phones for business people (Raven, 2007). Today

these products are commonplace, yet these technologies started out in niche markets. Furthermore, the

military can be seen as a primary niche for major technologies, being involved in the development

several technologies (e.g., radio, aircraft, computers and the internet). In this respect, niches have also

been referred to as experiments, which take place within networks of organizations (i.e., ecosystems)

(Geels, 2004; Geels, 2002; Schot and Geels, 2008). Furthermore, a regime can host a range of

experiments and niches which generate innovation and, as such, challenge the status quo of the

current regime.

As a research stream, strategic niche management conceptualizes experimental projects, pilot

projects and demonstration projects with new technologies as important phase between R&D and

market diffusion. Real-world experimental projects can be considered important for developing new

technology niches, as such early markets can be exploited to explore the alignments between

technology and user demands (Schot and Geels, 2008). In this respect, the concepts of experiment and

niche can be considered as separate, where experiments are the actual means to create niches – that is,

a more local and less institutionalized early version of a niche (Raven, 2005). Such experimental

projects provide space for interactions between actors and the building of social networks (Geels and

Raven, 2006). Experiments can play a role in creating social networks for niche development. In a

sense, therefore, transition management can be considered to include four layers (i.e., experiment,

8

niche, regime, landscape) instead of the generally referred three, although no author has thus far

explicitly stated so.

Transition management dynamics

The outlined model of transitions entails dynamics that are multi-level and multi-actor by their nature.

In this respect, transitions (e.g., from one dominant design toward the new dominant design) are not

characterized by linear replacement processes. Instead, such transitions are the result of complex

interactions between incumbent firms, technology ventures, users, governments, scientists and

NGO’s, which often have conflicting strategies, interests and motivations. Furthermore, power within

the transition process is distributed rather than being top-down in nature and not necessarily evenly

distributed. As such every actor plays a part in shaping the transition and the system gives rise to

different forms of interaction and transition. Although this distributed power enables the process of

mutual adaptation toward collective goals and the emergence of self-organized socio-technical

‘trajectories’, it also slows down transitions and inhibits radical innovation (Raven, 2007). In this

respect, the model illustrates how the success of a new technology depends on developments and

alignment across all levels; from landscapes to regimes, and from regimes to niches (Kemp et al.,

1998).

Raven (2007) describes two strategies to facilitate transitions and thus prevent the lockout of

frame-breaking innovation. The first strategy is to create a specific niche market by means of

experimentation. Through this method internal momentum should be built through the process of

niche accumulation, which eventually results in a regime shift. The innovation survives due to the

specific characteristics of the niche market (e.g., investment grants, tax exemptions, but also

geographical location) (Raven, 2007). The second strategy is to start more closely to the dominant

regime, and achieve transition though a process called ‘hybridisation’ (Raven, 2007). Hybridisation

refers (Raven, 2007, p.2395): “to the process were the ‘old’ and ‘new’ technology hook up to form

some kind of a hybrid technical design”. Examples of hybridization are the introduction of gas

turbines in the electricity regime and the transition from sailing ships to steam ships. For both cases

goes that the old dominant design was gradually ‘taken over’ by the new technology (Raven, 2007).

Both strategies, however, are built on the notion that the ongoing processes (and gradually

occurring shifts) at the regime and landscape level present windows of opportunity for

experimentation and the development of niches. These breakthrough innovation then eventually cause

for regime shifts through niche-accumulation or hybridisation. Nevertheless, as argued, regime actors

often actively hinder the emergence of a new dominant designs, originating from the technology niche

level (Raven, 2007). This hindering might be intentionally, due to invested capital in factories or

existing infrastructures; but can also be unintentionally – through cognitive and institutional forces

causing a lock-in in the current technology (Tripsas and Gavetti, 2000; Walrave et al., 2011). As such,

agents at the regime level can be (made) blind to certain advantages of the new technology and

increasingly encourage incremental improvements to the dominant design. Transition management

9

offers no insight with respect how to manage these dynamics at the micro-level, despite the

challenging characteristics found within emerging technology niches (highly uncertain, involving an

increasing number of actors with, at first, undefined roles) (Raven, 2005).

TOWARD A MULTILEVEL FRAMEWORK FOR TECHNOLOGY VENTURES

The key characteristics identified with respect to technology niche development resonate strongly to

problems and solutions that ecosystem management describes and provides (Adner, 2012; Raven,

2005): (1) An emerging niche is accompanied by a social network, including producers, users,

regulators, societal groups, etc. – referred to as the value chain by ecosystem management (2) In the

early years of experimentation, the size of the network can be limited: only one or a few firms are

investing in the development of the technology, the number of users is limited and the technology

may be invisible to regulating actors. – This has been defined by ecosystem management as the

minimum viable footprint. (3) The role of actors in the network may be unclear: supplier-producer-

user relationships have not yet stabilized, it is unclear who the user is, and firms lack long-term

security of supply. In the course of time, when actors have gained more experience, the role of actors

and their relations becomes clearer – these risks are captured by co-innovation risk and adoption-

chain risk.

Furthermore, transition management literature states that actors, embedded in networks (i.e.,

ecosystems), are willing to invest resources in projects only if they have a shared, positive expectation

of a new technology. This shared expectation, together with shared cognitive rules, provides direction

to the experiments (Geels and Raven, 2006). Interestingly, as discussed, developing such shared

expectations is what ecosystem management is primarily concerned with (by assessing the different

risk types and developing a minimum viable footprint) (Adner, 2012). In this respect, Iansiti and

Levien (2004) state that among the principle tasks of an ecosystem is the ability to create niches and

opportunities for (technology) startups. This is then where the two frameworks – ecosystem

management and transition management – overlap. More specifically, ecosystem management

concerns the management of those actors (i.e., suppliers, complementors, and buyers) that are active

within a certain technology niche and are, therefore, involved in the development of an experiment.

Although the body of ecosystem management literature acknowledges that the success of an

innovation depends on factors within its environment (Adner and Kapoor, 2010), the current state-of-

the-art with respect to ecosystem management fails to consider the multi-level nature and dynamics

that encompasses transition management (e.g., Adner, 2012; Adner and Kapoor, 2010). As such, the

main limitation of ecosystem management is that is focuses on the development of innovation within

a given technological niche, existing within a given regime and landscape, without considering trends

and shifts within the system. The fact is that technology entrepreneurs are bounded by their socio-

technological regime and landscape. Without consideration of these higher-level aspects (and the

dynamics between them), the risks and success chances concerning the introduction of radical

innovation remain opaque at best.

10

In this respect, following transition theory, the successful introduction of radical innovation

requires active management by the technology venture with respect to inert regime players. By

widening the participation of actors across levels, a vision can be developed that has shared common

factors across these levels. This is likely to result in support for and, therefore, less resistance with

respect to the innovation and transition (Rotmans et al., 2001). Moreover, it has been recognized that

the heterogeneity of society – and its input – allows for collective learning spurring the development

of innovations through exploration at the niche level (Foxon et al., 2010). As such, we propose to

combine the two frameworks to distill a theoretical framework that provides a systemic perspective on

technology ventures’ innovation processes. This framework is depicted in Figure 1.

Figure 1: Overview of a systemic framework on technology ventures’ innovation processes

A technology venture, launching an experiment, is subject to the forces dictated by transition

management. At first – following niche accumulation strategy – a niche needs to be created by means

of ecosystem management. Critical factor to manage at this point are execution risk, co-innovation

risk, adoption-chain risk. Starting from an initiator company and an experiment, it starts gathering

momentum and partners and eventually achieves a niche status (the process is quite messy and

11

recursive, sculpting the niche over time). Then, the ecosystem, embedded within a certain socio-

technological regime, needs to be shaped and developed in such a manner that it considers and

manages the current dominant regime and/or anticipate changes within this regime (which may follow

from changes in the socio-technological landscape).

DISCUSSION AND CONCLUSION

Technological advancements cause that people and technology are becoming increasingly connected,

transforming traditional markets into networked ones (Adner, 2006; Podoynitsyna et al., 2013). Such

a ‘connected’ world causes that the value of a particular product or service to depend on other

products or services (Podoynitsyna et al., 2013; Srinivasan et al., 2004; Stremersch et al., 2010; Wuyts

et al., 2010). As such, technology entrepreneurs face increasingly difficult challenges related to the

development and production of their innovation. In this respect, research has shown that the failure

rate of ventures remain high (Song et al., 2008). One cause for this entrepreneurial failure lies in the

fact hat the challenges that accompany an innovation today are often situated not only within a focal

venture but also in the venture’s ecosystem and broader social-technical system (Adner, 2012; Smith

and Raven, 2012).

This paper introduced a theoretical framework that provides a systemic perspective on

technology ventures’ innovation processes. More specifically, in this paper we develop such a

systemic lens by combining and integrating the ecosystem development and transition management

literatures (Adner, 2012; Adner and Kapoor, 2010; Geels, 2002; Raven, 2007). We make the

transactions and interconnections explicit, by linking the focal firms’ ecosystem and the influence of

higher system levels such as socio-technical regimes and landscapes. In this respect, the main

limitation of transition management is that it fails to generate normative insights from the point of

view of the technology entrepreneur – despite the fact that the described transition strategies revolve

about the success of experiments (Raven, 2007). This can be explained by the fact that, historically,

the focus within this body of literature has been top-down (e.g., policy development) (e.g., Foxon et

al., 2010; Geels and Raven, 2006; Verbong and Loorbach, 2012). On the other hand, although

ecosystem management has provided us with tools how-to manage an ecosystem (e.g., Adner, 2012;

Adner, 2006), if fails to consider the multi-level nature and dynamics that encompasses transition

management. As such, this paper contributes to the literature by connecting and synthesizing the

ecosystem and socio-technical system literatures in a multi-level framework of technology-driven

innovation processes. Furthermore, the developed framework can be considered practically relevant,

as it provides the basis for (re)developing tools that aid technology ventures in developing innovation.

The model outlined in this paper illustrates that the introduction of an innovation by a

technology venture starts by creating a technology niche. Technology niches are created by means of

experimentation – essentially an invention being introduced into a particular niche by the technology

entrepreneur. Such an experiment requires active supervision of the venture by means of ecosystem

management. That is, execution risk, co-innovation risk, and adoption chain risk need to be

12

considered and controlled; and the expectations among stakeholders managed. Development of the

ecosystem is important as it provides a means to ‘fight’ the largely inert socio-technical regime. This

is essential to further develop the innovation. In this respect, the currently dominant socio-

technological regime hinders the growth of innovation, as actors at this level tend to prefer the current

status quo (i.e., due to investments in the current technology and related processes). Successful

management of the ecosystem can move the experiment from one niche market to another, thereby

improving the fit between the technology and markets, further increasing the internal momentum,

making for a new socio-technological regime to emerge. In this respect, if the new technology is to be

successful, the technology entrepreneur needs to consider and shape the socio-technological regime

by means of ecosystem management. This, on the long run, can also imply changes within the socio-

technological landscape, generating further entrepreneurial opportunities.

The latter framework also contributes to the business model literature that tends to define

components of a business model by focusing on within-firm issues and listing involved partners as a

means to come up with value propositions (Morris et al., 2005; Osterwalder and Pigneur, 2010; Zott et

al., 2011) or alternatively, focuses on different types and design themes of business models (Amit and

Zott, 2001; Zott et al., 2011; Zott and Amit, 2008). Although both approaches in the business model

literature are valuable, they only indirectly describe the essence of a business model, that is,

transactions between the focal firm and its exchange partners and environment (Zott et al., 2011).

To some extent, the need for a systemic lens has also been advocated in the business model

literature. The business model of a new venture depicts how it creates and appropriates (i.e.

monetizes) value (Morris et al., 2005; Osterwalder and Pigneur, 2010; Teece, 2010). More

specifically, it has been defined as the structure, content, and governance of transactions between the

focal firm and its exchange partners (Amit and Zott, 2001; Zott et al., 2011; Zott and Amit, 2008). In

this respect, the same basic technological idea can be the basis for many applicable business models,

and the choice for particular business models determines to a large extent the success of

commercialization efforts (Chesbrough and Rosenbloom, 2002). However, the business model

literature currently lacks a broader theoretical framework that explains why and how a particular

business model implies commercial success in one setting but failure in another.

FURTHER RESEARCH

A logical next step is to subject the proposed model to empirical testing and verification. An empirical

study could, for instance, be setup by planning in-depth case studies where technology entrepreneurs

are being observed for an extended period of time. From there, the model can be further developed,

for instance, by assessing the influence of the different risks and actors at the different levels. This

results in a more comprehensive understanding of the dynamics involved – and in opportunities for

developing formal models, allowing for further experimentation and development (Sterman, 2000).

This is inline with calls in the literature that argue for the importance of understanding the dynamics

of value creation as a precursor to the analysis of value capture (Raven, 2007).

13

REFERENCES

Adner, R. (2006). ‘Match your innovation strategy to your innovation ecosystem’. Harvard Business Review, 84, 98–107.

Adner, R. (2012). The Wide Lens: A New Strategy for Innovation. New York: Portfolio/Penguin.

Adner, R. and Kapoor, R. (2010). ‘Value creation in innovation ecosystems: How the structure of technological interdependence affects firm performance in new technology generations’. Strategic Management Journal, 31, 306–333.

Adner, R. and Snow, D. (2010). ‘Old technology responses to new technology threats: Demand heterogeneity and technology retreats’. Industrial and Corporate Change, 19, 1655–1675.

Afuah, A. (2000). ‘How much do your co-opetitors’ capabilities matter in the face of technological change?’. Strategic Management Journal, 21, 397–404.

Amit, R. and Zott, C. (2001). ‘Value creation in e-business’. Strategic Management Journal, 22, 493–520.

Chao, R.O. and Kavadias, S. (2008). ‘A theoretical framework for managing the new product development portfolio: When and how to use strategic buckets’. Management Science, 54, 907–922.

Chesbrough, H. and Rosenbloom, R.S. (2002). ‘The role of the business model in capturing value from innovation: Evidence from Xerox corporation’s technology spin‐off companies’. Industrial and Corporate Change, 11, 529–555.

Cooper, R. (2008). ‘Perspective: the Stage-Gate® idea-to-launch process - update, what’s new, and nexgen systems’. Journal of Product Innovation Management, 25, 213–232.

Foxon, T.J., Hammond, G.P. and Pearson, P.J.G. (2010). ‘Developing transition pathways for a low carbon electricity system in the UK’. Technological Forecasting and Social Change, 77, 1203–1213.

Geels, F. and Raven, R. (2006). ‘Non-linearity and expectations in niche-development trajectories: Ups and downs in dutch biogas development (1973–2003)’. Technology Analysis & Strategic Management, 18, 375–392.

Geels, F.W. (2004). ‘From sectoral systems of innovation to socio-technical systems: Insights about dynamics and change from sociology and institutional theory’. Research Policy, 33, 897–920.

Geels, F.W. (2005). Technological Transitions And System Innovations: A Co-evolutionary And Socio-technical Analysis. Edward Elgar Publishing.

Geels, F.W. (2002). ‘Technological transitions as evolutionary reconfiguration processes: A multi-level perspective and a case-study’. Research Policy, 31, 1257–1274.

Geels, F.W. and Schot, J. (2007). ‘Typology of sociotechnical transition pathways’. Research Policy, 36, 399–417.

Grin, J., Rotmans, J. and Schot, J.W. (2010). Transitions to sustainable development: New directions in the study of long-term transformative change. London: Routledge.

14

Henderson, R.M. and Clark, K.B. (1990). ‘Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms’. Administrative Science Quarterly, 35, 9–30.

Iansiti, M. and Levien, R. (2004). The keystone advantage: What the new dynamics of business ecosystems mean for strategy, innovation, and sustainability. Boston: Harvard Business School Press.

Kemp, R.P.M., Loorbach, D. and Rotmans, J. (2007). ‘Transition management as a model for managing processes of co-evolution towards sustainable development’. International Journal of Sustainable Development & World Ecology, 14, 78–91.

Kemp, R.P.M., Schot, J. and Hoogma, R. (1998). ‘Regime shifts to sustainability through processes of niche formation: The approach of strategic niche management’. Technology Analysis & Strategic Management, 10, 175–198.

Moore, G.A. (1991). Crossing the chasm: Marketing and selling technology products to mainstream customers. New York: HarperCollins Publ.

Morris, M., Schindehutte, M. and Allen, J. (2005). ‘The entrepreneur’s business model: Toward a unified perspective’. Journal of Business Research, 58, 726–735.

Nelson, R.R. and Winter, S.G. (1982). An Evolutionary Theory of Economic Change. Cambridge: Harvard University Press.

Osterwalder, A. and Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. Hoboken: John Wiley & Sons.

Perry, J.T., Chandler, G.N. and Markova, G. (2012). ‘Entrepreneurial effectuation: A review and suggestions for future research’. Entrepreneurship Theory and Practice, 36, 837–861.

Podoynitsyna, K., Song, M., van der Bij, H. and Weggeman, M.C.D.P. (2013). ‘Improving new technology venture performance under direct and indirect network externality conditions’. Journal of Business Venturing, 28, 195–210.

Raven, R. (2007). ‘Niche accumulation and hybridisation strategies in transition processes towards a sustainable energy system: An assessment of differences and pitfalls’. Energy Policy, 35, 2390–2400.

Raven, R. (2005). Strategic niche management for biomass: A comparative study on the experimental introduction of bioenergy technologies in the netherlands and denmark. Eindhoven: Eindhoven University of Technology.

Rip, A. and Kemp, R.P.M. (1998). ‘Technological change’, in Raynor, S. and Malone, E.L. (Eds), Human Choice and Climate Change. Vol. II, Resources and Technology. Ohio: Battelle Press.

Rotmans, J., Kemp, R.P.M. and Asselt, M. van (2001). ‘More evolution than revolution: Transition management in public policy’. Foresight, 3, 15–31.

Sarasvathy, S.D. (2001). ‘Causation and effectuation: Toward a theoretical shift from economic inevitability to entrepreneurial contingency’. The Academy of Management Review, 26, 243–263.

15

Schot, J. and Geels, F.W. (2008). ‘Strategic niche management and sustainable innovation journeys: Theory, findings, research agenda, and policy’. Technology Analysis & Strategic Management, 20, 537–554.

Scott, W.R. (1995). Institutions and organizations. Thousand Oaks: Sage Publications.

Smith, A. and Raven, R. (2012). ‘What is protective space? Reconsidering niches in transitions to sustainability’. Research Policy, 41, 1025–1036.

Song, M., Podoynitsyna, K., Van Der Bij, H. and Halman, J.I.M. (2008). ‘Success factors in new ventures: A meta-analysis*’. Journal of Product Innovation Management, 25, 7–27.

Srinivasan, R., Lilien, G.L. and Rangaswamy, A. (2004). ‘First in, first out? The effects of network externalities on pioneer survival’. Journal of Marketing, 68, 41–58.

Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. New York: McGraw Hill.

Teece, D.J. (2010). ‘Business models, business strategy and innovation’. Long Range Planning, 43, 172–194.

Tripsas, M. and Gavetti, G. (2000). ‘Capabilities, cognition, and inertia: Evidence from digital imaging’. Strategic Management Journal, 21, 1147–1161.

Tushman, M.L. and Anderson, P. (1986). ‘Technological discontinuities and organizational environments’. Administrative Science Quarterly, 31, 439–466.

Verbong, G. and Loorbach, D. (2012). Governing the energy transition: Reality, illusion or necessity? New York: Routledge.

Walrave, B., Van Oorschot, K.E. and Romme, A.G.L. (2011). ‘Getting trapped in the suppression of exploration: A simulation model’. Journal of Management Studies, 48, 1727–1751.

Zott, C. and Amit, R. (2008). ‘The fit between product market strategy and business model: Implications for firm performance’. Strategic Management Journal, 29, 1–26.

Zott, C., Amit, R. and Massa, L. (2011). ‘The business model: Recent developments and future research’. Journal of Management, 37, 1019–1042.