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International Journal of Management Reviews Volume 8 Issue 2 pp. 91–112 91

International Journal of Management Reviews (2006)

DOI: 10.1111/j.1468-2370.2006.00122.x

Blackwell Publishing LtdOxford, UKIJMRInternational Journal of Management Reviews1460-8545© Blackwell Publishing Ltd 2006

82ORIGINAL ARTICLEAdaptation in new technology-based ventures: Insights at the company level: Insights at the company level

Adaptation in new

technology-based

ventures: Insights at

the company level

Petra Andries and Koenraad Debackere

Recent research shows that, owing to the presence of uncertainty and ambiguity, new

ventures have great difficulties in defining a viable business model from the outset and that

minor or major adaptations to this initial business model are needed as the venture evolves.

Technology-based companies are confronted with particularly high degrees of uncertainty

and ambiguity. This paper therefore focuses on new technology-based ventures as a special

case worth investigating. Most of the entrepreneurship literature studies adaptation at the

individual level. However, many new technology-based firms are founded by a team of

entrepreneurs. This paper therefore looks at how existing literature at the company level can

inform us about adaptation in new technology-based companies. It starts by relating the

concept of adaptation in new technology-based ventures to the existing literature on

organizational adaptation at the firm level. Based on an overview of existing literature at the

firm level, a propositional model is then put forward, describing (1) the process of

adaptation and (2) the factors enabling adaptation in new technology-based ventures.

Introduction

New businesses often start from a market

vision or from a technological capability.

In both cases, the initial idea needs to be

exploited through the development of a busi-

ness model (Chesbrough and Rosenbloom

2002; Hamel 2000). Especially for new

technology-based ﬁrms (as we explain below),

deﬁning an appropriate business model from

the beginning is difﬁcult, and adaptation of

the initial business model is therefore crucial

for success.

This paper looks at what we can learn

about adaptation in new technology-based com-

panies from existing literature at the company

level (including literature on new as well as

on established ﬁrms). More speciﬁcally, we

start by relating the concept of adaptation in

new technology-based ventures (NTBVs) to

the existing literature on organizational adapt-

ation at the ﬁrm level. Based on an overview

of this existing literature, we put forward a

propositional model describing (1) the

process of adaptation in NTBVs and (2) the

factors enabling adaptation.

92 © Blackwell Publishing Ltd 2006

Adaptation in new technology-based ventures: Insights at the company level

A business model is a construct that mediates

the value creation process, by selecting and

ﬁltering technologies and ideas, and packag-

ing them into particular conﬁgurations to be

offered to a chosen target market. However,

because new businesses are confronted with

uncertainty and ambiguity, the set of all feasi-

ble business models is often not foreseeable

from the outset (see Druilhe and Garnsey

2002, 2004, on university spin-outs). This is

especially true for technology-based busi-

nesses that are coping with high degrees of

both technical and market newness (see also

Aldrich and Fiol 1994; Loch et al. 2005;

Morris et al. 1999; Shane and Stuart 2002;

Utterback 1987, on technical and target uncer-

tainty). The latter can be present even after

technological feasibility has been established

(Burgelman et al. 2001) and appears to have

an even larger effect on the development of

opportunities than the former (Autio and

Lumme 1989; Eisenhardt and Schoonhoven

1990; Saemundsson and Lindholm Dahlstrand

2005). Although uncertainty and ambiguity

remain present throughout a technology-based

company’s life, they are most problematic

during the early life stages, when the company

has only restricted knowledge, experience and

resources for dealing with this uncertainty and

ambiguity (Bhidé 2000). Therefore, this paper

will focus on NTBVs as a special case worth

investigating.

If the set of all feasible business models is

not foreseeable from the outset (Druilhe and

Garnsey 2004) and it is not possible for a

NTBV to identify upfront what the most

viable business model will be, then it does not

come as a surprise that most initial selections

of business models by NTBVs have to be

abandoned later on (Drucker 1985; Stoica and

Schindehutte 1999) and that minor or major

adaptations to the initial business model are

needed as initially unavailable information

becomes known (Brokaw 1991; Champion

and Carr 2000).

Most existing research on new venture

development has deﬁned adaptation as a cap-

ability of the individual entrepreneur (Morris

et al. 1999; Pitt and Kannemeyer 2000). How-

ever, previous research on NTBVs – the focus

of this paper for reasons explained above –

has shown that these ventures are often estab-

lished by a team of founders (Cooper 1986;

Utterback and Reitberger 1982) and that

venture strategy has a larger effect on new

venture performance than do data describing

the entrepreneur (Sandberg and Hofer 1987).

Although we do not intend to minimize the

role of the individual entrepreneur, it is obvi-

ous that, if we seek to study business model

adaptation in NTBVs, we need to do this at

the company level. At this ﬁrm level, we can

then deﬁne a NTBV’s adaptation as a NTBV’s

adjustments to its business model as the venture

evolves from an initial idea or business plan

through the early stages of the organizational

life cycle towards a more stable business.

Because of the relevance of the ﬁrm level in

NTBVs, the existing ﬁrm level research on

adaptation (in new as well as in established

companies) is relevant for developing insights

into NTBVs’ adaptation and, more precisely,

into the process of and the enablers for adapt-

ation in NTBVs. In the following section, we

look at the existing literature on the concept

of adaptation at the ﬁrm level, which has

focused mainly on established companies. We

discuss some important dimensions of organ-

izational change behaviors and circumstances

under which these behaviors are appropriate.

We then analyze how adaptation in NTBVs

relates to change in established ﬁrms.

Views on Organizational Change in

Established Firms

Organizations can be viewed as dynamic

systems of adaptation and change – two terms

that are often used interchangeably – that con-

tain multiple parts that interact with one another

and the environment (Morel and Ramanujan

1999). Existing views on adaptation and their

deﬁnition of ‘change’ differ with respect to

(1) whether the pressures for change reside

within the organization or within its environment,

(2) timing and (3) the radical nature of change.

June 2006

Pressures for Change

Change or adaptation is often regarded as an

organization’s response to changes in external

factors, threats and opportunities (e.g. Kraatz

1998). Chakravarthy (1982) also discusses

‘states of adaptation’ in terms of immunity

from environmental changes. However, other

research streams have focused more on

internal pressures for organizational change.

As shown by Siggelkow and Levinthal (2005),

authors such as Chandler (1962) and Law-

rence and Lorsch (1967) alluded to internal

reasons for change and most life-cycle models

adhere to this perspective. A more inclusive

view on change suggests that both external

and internal pressures for change are relevant

(Morel and Ramanujan 1999). Organizational

attributes are then adapted in response to

changes internal and/or external to the organ-

ization (Siggelkow and Levinthal 2005). The

innovation literature, in particular, pays atten-

tion to internal as well as external drivers for

change. Examples are the distinction between

market pull and technology push, the concept

of architectural innovation (Henderson and

Clark 1990) as an internal driver for innova-

tion, as well as the shift in focus from product

solutions to customer solutions as an indication

of external pressures for change (Burgelman

et al. 2001; Christensen 1997; Christensen

and Raynor 2003; von Hippel 1988, on lead

user research).

We saw that a NTBV cannot deﬁne the set

of all relevant business models from the out-

set, owing to the presence of uncertainty and

ambiguity. Changes to its original business

model are thus needed as initially unavailable

and unknown information becomes known.

Adaptation in NTBVs is therefore required,

regardless of environmental change. Ventures

have to search for their place in the environment.

They even have to ﬁnd the most appropriate

environment. While there are conceptual

differences between reacting to changes in

the environment and adapting an idea to ﬁt the

current environment, one could argue that

the latter is part of the former. Indeed, adapting

to changes in the environment includes com-

ing up with ideas on how to work in this

‘new’ environment. These ideas may need to

be reﬁned and adapted to ﬁt the new situation.

Insights on adaptation in NTBVs can there-

fore also be of importance for established

companies that adapt to changes in their

environment.

Timing of Change

Different perspectives exist on how change is

distributed over time (Burgelman et al. 2001;

Tyre and Orlikowski 1994). In the life-cycle

literature, change is suggested to occur through

periodic, on-time corrections (Gersick 1994;

Romanelli and Tushman 1994; Tushman and

Romanelli 1985). Similarly, Winter (2003)

suggests one way of dealing with change is by

‘ﬁreﬁghting’ or ad hoc problem solving. This

type of high-paced, contingent, opportunistic,

perhaps creative search for satisfactory alter-

native behaviors typically appears as a response

to novel challenges from the environment or

other relatively unpredictable events. An

advantage of ad hoc problem solving is that

its costs largely disappear when there are no

problems to solve or changes to make. The

exercise of ad hoc problem solving behavior

is largely non-repetitive and intendedly

rational. It is neither highly patterned nor

repetitious, although it may be patterned

at a higher level, guided by adherence to rel-

atively simple rules and structural principles

(Winter 2003).

However, when change is frequent, ‘ﬁre-

ﬁghting’ becomes expensive and takes on a

more continuous nature. As a consequence,

novel ways of dealing with it should be taken

into consideration (Winter 2003). Studies on

innovation (Brown and Eisenhardt 1997;

Muzyka et al. 1995; Nonaka 1991) and on

industry evolution and evolutionary econo-

mics further suggest the need for continuous

change over extended periods of time.

In continuously changing markets, dynamic

capabilities1 – as opposed to ad hoc ﬁreﬁght-

ing – are often regarded as a main source of

94 © Blackwell Publishing Ltd 2006

Adaptation in new technology-based ventures: Insights at the company level

sustained competitive advantage. They relate

to the capacity to renew competences continu-

ously so as to achieve congruence with the

changing business environment (Collis 1994;

Winter 2003). Dynamic capabilities are about

continuously integrating, building and recon-

ﬁguring internal and external competences

(i.e. organizational routines and processes that

are typically viable across multiple product

lines, individual business units within an

organization and even outside the organ-

ization) to address changing environments

(Burgelman et al. 2001; Helfat and Peteraf

2003; Helfat and Raubitschek 2000; Teece

et al. 1997). They govern the rate of change of

ordinary capabilities (Collis 1994; Winter

2003). Examples are capabilities that change

the product, the production process, the scale

or the customers. Product development, strate-

gic decision-making and alliancing have been

put forward as concrete examples of dynamic

capabilities (Eisenhardt and Martin 2000;

Teece et al. 1997).

The Radical Nature of Change

Some of the characteristics of dynamic capa-

bilities discussed above have limited the gen-

eral use of the ‘dynamic capabilities’ concept

to situations of moderate change. As indicated

earlier, routines form the building blocks of

capabilities. Routines – and thereby also

dynamic capabilities – can only be learnt

through frequent repetition over long periods

of time. Because of the notion of ‘routines’,

Nelson and Winter (1982) delimit the validity

of their work on capabilities mainly to organ-

izations that provide goods or services that are

visibly the same over extended periods of

time. So, according to the existing literature,

capabilities and thus also dynamic capabilities

can only be developed when circumstances

are relatively stable over a signiﬁcant period

of time.

However, some empirical research ﬁndings

suggest that dynamic capabilities can also be

developed and of value under circumstances

of fast-paced, radical change. Eisenhardt and

Martin (2000) explicitly distinguish between

dynamic capabilities for moderately dynamic

markets and for high-velocity markets.

Eisenhardt and Martin do not believe in the

possibility of leveraging existing resource

conﬁgurations in the pursuit of long-term

competitive advantage in high-velocity mar-

kets (D’Aveni 1994). However, they propose

that the strategic imperative under high-

velocity markets is change and not leverage.

Instead of enhancing/leveraging the existing

resource conﬁgurations in the pursuit of long-

term competitive advantage, an organization

in high-velocity markets should build new

resource conﬁgurations in the pursuit of

temporary advantages or opportunities, thus

creating a series of temporary advantages.

Winter (2003) however, does not support

the proposition of Eisenhardt and Martin to

broaden the traditional deﬁnition of routines

and dynamic capabilities towards high-

velocity markets. He argues that ad hoc pro-

blem solving may be patterned at a higher

level, guided by adherence to relatively simple

rules and structural principles; and considers

the activities put forward by Eisenhardt and

Martin as examples thereof. The existing liter-

ature thus lacks consensus about the existence

of dynamic capabilities for high-uncertainty/

high-velocity environments.

Adaptation in NTBVs was found to imply

continuous opportunity detection and identi-

ﬁcation, acquisition, mobilization, combina-

tion, organization and reconﬁguration of

resources (Druilhe and Garnsey 2004; Vohora

et al. 2004). This characterization of adapta-

tion as a continuous effort shows remarkable

similarities to the description of dynamic

capabilities as being about continuously

integrating, building and reconﬁguring internal

and external competences to address changing

environments (Teece et al. 1997). In spite of

these similarities, the ﬁnding that adaptation

in new ventures can imply gradual as well as

radical business model changes (Brokaw

1991; Drucker 1985) goes against the

traditional view on dynamic capabilities. It

apparently supports the view of Eisenhardt

June 2006

and Martin (2000) on the existence of dynamic

capabilities for high-velocity environments.

Therefore, research on adaptation in NTBVs

can add insight to the general discussion of

whether or not dynamic capabilities can sup-

port and imply radical change. We particularly

need to study the adaptation process in

NTBVs to verify whether it consists of

underlying routines, whether it is governed

solely by ‘ad hoc problem solving’, or whether

perhaps ‘ad hoc problem solving’ itself is

a routine or capability in high-velocity

environments. In addition, research on ena-

bling factors of the adaptation process will

reveal whether adaptation is really an organ-

izational capability or a personal skill of the

entrepreneur, or whether it is a mixture of

both. The following section looks at what

insights the existing literature offers on the

adaptation process in NTBVs.

The Adaptation Process

When trying to understand how NTBVs adapt

their initial business model, we can draw on

insights derived from two important streams

of literature on the organizational or team

level: the entrepreneurship literature (and,

more precisely, life-cycle models) and the

innovation literature. The life-cycle literature

studies how ventures change over different

stages in their life (in response to external as

well as internal changes) and how each of

these stages is characterized by speciﬁc

opportunities and challenges. The need to

adapt an initial concept into a viable business

model is one such challenge faced in the early

life of a new venture. From the life-cycle

literature, we can thus learn about the busi-

ness model adaptation process in NTBVs and,

more precisely, about how business model

adaptation evolves over the early life-stages of

a NTBV. In addition, we can gain useful

insights from research on the management

and development of innovations. Although

most of these studies have taken place in

business units of large, established organizations,

research suggests that some core processes

of innovation are similar in established

companies and NTBVs (Loch et al. 2005; Van

de Ven et al. 1999).

Life-cycle Models

Numerous studies (for an overview, see Bam-

ford et al. 1999; Hanks et al. 1993; Kazanjian

and Drazin 1989, 1990; Reynolds and Miller

1992; Vesper 1990) suggest that ventures

change over their life and that it is exactly

this change that is crucial to their success and

survival. Most of this literature argues that

companies progress through different stages

of growth in which speciﬁc growth and market

opportunities (e.g. Chandler 1962; Scott

1970) as well as challenges (Greiner 1972;

Kazanjian and Drazin 1989) and demands

(Siggelkow and Levinthal 2005) must be

addressed through the use of adequate skills

and appropriate organizational structure. The

literature lacks consistency on the number of

life stages of a company. Three-stage, four-

stage (e.g. Hanks et al. 1993; Kazanjian and

Drazin 1989, 1990), ﬁve-stage (e.g. Galbraith

1982; Greiner 1972; Miller and Friesen 1984),

and even seven- and ten-stage models have

been proposed. Those differences are largely

due to the fact that most existing models were

developed in a conceptual manner, without

much empirical testing, as well as to the

lack of speciﬁc measures for the relevant

con-textual and structural dimensions (Hanks

et al. 1993) of the different stages.

When reviewing the life-cycle literature

(Hanks et al. 1993; Kazanjian and Drazin

1989, 1990), one is forced to conclude that the

majority of life-cycle models do not provide

an adequate framework for studying NTBVs,

because (1) most of them do not pay sufﬁcient

attention to the initial stages in a company’s

life (Churchill and Lewis 1983) and (2)

business model adaptation is particularly pro-

blematic in these early stages (Bhidé 2000). We

therefore turn to models that do pay special

attention to these early years. They can be

classiﬁed into unidirectional stage-based

models, on the one hand, and multidirectional,

96 © Blackwell Publishing Ltd 2006

Adaptation in new technology-based ventures: Insights at the company level

non-sequential models, on the other hand.

Although life-cycle models are concerned

with organizational adaptability in general,

our discussion will focus on what these

models tell about the process of business

model development.

Unidirectional stage-based models. In general,

the majority of life-cycle models distinguish

between two major early life-phases in which

the development and adaptation of an initial

idea into a viable business model takes place

(Figure 1). In a ﬁrst phase, the product or

service are developed, and the ﬁrst sales are

realized. This phase is termed ‘start-up phase’

(Hanks et al. 1993), ‘conception and develop-

ment’ (Kazanjian and Drazin 1989, 1990) or

‘existence’ (Churchill and Lewis 1983), etc.

During this stage, the product or service is

developed, often through prototyping and

experimentation (Kazanjian and Drazin 1998,

1990). Products and services are customized

(Abernathy and Utterback 1975, 1978) to suit

the needs of innovators and early adopters

(Moore 1995, 1999; see also Burgelman et al.

2001). Other authors discern between differ-

ent phases within this ﬁrst phase. Clarysse and

Moray (2004) as well as Vohora et al. (2004),

in their study of academic spin-offs, ﬁnd

evidence for the existence of (1) a research or

idea phase, (2) a phase in which the oppor-

tunity is framed and validated, (3) a phase in

which resources and organizational arrange-

ments are put in place, and (4) a phase in

which strategic focus is gained, where the

venture tries to generate revenues and possi-

bly adapts its business model. Vohora et al.

(2004) ﬁnd that a venture must pass through a

previous phase in order to progress to the next

one, but that each phase involves an iterative,

non-linear process of development in which a

need to revisit some of the earlier decisions

and activities may arise.

In a second phase, the product or service is

commercialized on a larger scale. The venture

is investing heavily in growth (Churchill and

Lewis 1983) by targeting early majority cus-

tomers (Moore 1995, 1999) and by standard-

izing the initial prototypes and customized

products or services (Abernathy and Utterback

Figure 1. Overview of sequential views on the start-up phase.

June 2006

1975, 1978). So also in this phase, further

changes occur to ﬁne-tune the product or

service to target customer segments, products

and services. All aspects of the initial business

model are to be challenged (see also Burgel-

man et al. 2001).

These models all suggest that ventures

develop their business model in sequential

phases. Quite a number of empirical studies

obtained results that support this unidirec-

tional, stage-based view (e.g. Hanks et al.

1993; Hansen and Bird 1997; Kazanjian and

Drazin 1989; Miller and Friesen 1984; Roure

and Keeley 1990). Although Vohora et al.

(2004) argue that each phase of their model

involves an iterative, non-linear process of

development in which some earlier decisions

and activities need revising, they do propose

that a venture must pass through the previous

phase in order to progress to the next one.

Although feedback loops appear necessary,

their model also assumes that no phases can

be skipped and that an ‘optimal’, sequential

order exists in the development of a company.

Loch et al. (2005) suggest that most venture

capital companies adhere to this type of

sequential, unidirectional model, expecting

ventures to progress through various phases in

which certain milestones need to be reached

and organizing their investments accordingly

in a number of rounds.

Multidirectional and non-sequential models.

Other authors, however, have argued that the

linear idea of a unidirectional sequence of life

stages is too simplistic (e.g. Tornatzky et al.

1983; Utterback 1987). They suggest that

multiple paths through these stages exist (e.g.

Adizes 1979). Reynolds and Miller (1992)

and Gersick (1994) have conﬁrmed the sto-

chastic nature of a ﬁrm’s adaptive processes.

Autio (1997) proposes a more systemic view,

moving away from a linear and evolutionary

view and looking at how ﬁrms become

embedded in the innovative environment in

which they operate. The embeddedness of a ﬁrm

in its environment relates to the ‘gestalt view’,

which criticizes the hypothesized existence of

related life-cycle phases and replaces the

life-cycle model by different and distinct

organizational categories. Each category then

represents an adequate organizational approach

for dealing with driving forces such as tech-

nology, environment, internal structure and

leadership (Kazanjian and Drazin 1989).

Among these ‘gestalts’, no determined pro-

gression patterns exist. They are therefore

episodes rather than phases or stages. The

terminology of ‘episodes’ thus underlines the

idea of non-linearity and multidirectionality.

Recent work has indeed proposed cyclical

models of business model development.

Druilhe and Garnsey (2004), describe venture

development as an iterative, non-linear and

bidirectional interaction between shifting

opportunities and emerging combinations of

resources. New businesses then go through

alternating cycles of opportunity detection

and resource mobilization, combination and

organization. The authors ﬁnd that the interac-

tion between opportunities and resources is

iterative, non-linear and bidirectional. On the

one hand, the type of business opportunity

selected in the initial business model inﬂu-

ences the resource requirements and, on the

other hand, improved knowledge of resources

and opportunities will allow entrepreneurs to

adapt and modify their business model.

Innovation Literature

In the previous section, we looked at what

insights life-cycle literature can offer on the

business model adaptation process in NTBVs.

In this section, we now want to gain under-

standing from research on the management

and development of innovations. The literature

on innovation processes is vast and diverse.

Therefore, it is not our goal to provide an

all-inclusive overview of its research ﬁnd-

ings here. Only aspects deemed useful for

gaining further insight into the adaptation

process will be discussed. First, we discuss the

work of Van de Ven et al. (1999), who have

modeled the innovation process based on in-

depth studies in business units of established

98 © Blackwell Publishing Ltd 2006

Adaptation in new technology-based ventures: Insights at the company level

organizations as well as in new ventures.

From this model, we can develop further

insights into the process of NTVs’ business

model adaptation. We ﬁnd striking similarities

to the bidirectional life-cycle models discussed

above.

We then give an overview of relevant ﬁnd-

ings from the new product development

(NPD) literature. Whereas technology-based

ventures try to develop an initial technological

opportunity into a viable business model,

NPD teams likewise struggle with the trans-

formation of an initial idea into a viable product

for their company. Because of this similarity,

the insights from the NPD literature – where

decision-making under uncertainty and ambi-

guity has since long been a central theme –

can improve our understanding of the NTBV’s

adaptation process (Loch et al. 2005). We also

look at how insights on process innovation

can add to this understanding.

The innovation process in general. Van de Ven

et al. (1999) model the innovation process (in

new as well as in established companies) as a

cyclical process (similar to the life-cycle model

by Druilhe and Garnsey 2004). Innovators

alternate between episodes of divergence and

convergence, where divergence involves the

exploration of new directions, and conver-

gence implies testing and exploiting a given

direction. Divergence is triggered by the

infusion of resources, while convergence is

triggered by external constraints (e.g. institu-

tional rules) and internal constraints (e.g.

resource limitations and the discovery of a

possibility that focuses attention) limiting the

complexity of the problem.

Van de Ven et al. (1999) pay special atten-

tion to the different ways of learning that a

company can and must adopt in order to

develop an innovation. They suggest that, in

the divergent phase, companies must learn

through discovery, by exploring a variety of

new directions. However, they also state that

‘all this information was localized to the

immediate area and used to energize or

modify the local discovery effort rather than to

generate major changes in direction or with-

drawal’ (Van de Ven et al. 1999, 203). Diver-

gence thus involves the discovery of various

but closely related options. In the convergent

phase, trial and error learning should take

place by testing a given, even more focused

direction. The authors consider complexity as

the reason for choosing one way of searching/

learning over the other and suggest that this

complexity results from different factors,

namely: (1) the ambiguity or uncertainty in-

herent in the development of an innovation;

(2) the fact that most innovations consist

of families of related new products and

procedures (see also the notion of platform

innovation projects by Wheelwright and Clark

1992); (3) the division of labor among func-

tions and organizational units; (4) the use of

diversiﬁcation for risk reduction; and (5) the

fact that complicated development paths may

result from pursuing alternative processes in

different parts of the innovation.

The model by Van de Ven et al. (1999)

appears more valid than the life-cycle models

discussed above, for three reasons. First, con-

trary to many models from the life-cycle liter-

ature which are developed without much

empirical testing (Hanks et al. 1993), this

model is based on detailed, longitudinal

empirical observations. Second, the cyclical-

ity of their model relates to and conﬁrms the

bidirectionality and non-linearity described in

recent life-cycle models. And third, the model

reserves a speciﬁc role for complexity and

ambiguity, the latter being the main driver for

adaptation (as discussed in the introduction to

this paper). We ﬁnd additional insights into

the role of uncertainty/ambiguity in literature

on NPD.

Product innovation. Although a broad con-

sensus exists that uncertainty and ambiguity

trigger the need for adaptation, much less is

known about the precise role of uncertainty

and ambiguity in the adaptation process. New

product development literature can provide

additional insights in this respect, since it has

a long tradition of examining and classifying

June 2006

various types of uncertainty. Sometimes,

uncertainty is classiﬁed by its source (techni-

calities, market issues, quality issues, etc.) or

by its potential impact (e.g. Chapman 1990).

Other classiﬁcations relate uncertainty to the

different management techniques required in

dealing with them. The latter type of classiﬁ-

cation often distinguishes between ‘uncer-

tainty’ and ‘ambiguity’ (e.g. Schrader et al.

1993). On the one hand, ‘uncertainty’ is

thereby deﬁned as a situation in which the

relevant decision variables are known, but the

organization does not know the exact values

these variables should take. A difference thus

exists between the amount of information

available and the amount of information

required to execute a task at hand (Galbraith

1977). In situations of ambiguity, on the

other hand, there is an inability to recognize

and articulate variables and their functional

relationships (Schrader et al. 1993).2 Sommer

and Loch (2004) use the terms ‘unknown

unknowns’ and ‘unforeseeable uncertainty’ to

this end. Differing interpretations of the situa-

tion exist. It is unclear to the actors involved

which information is needed to solve these

differences (Van Looy et al. 2001).

According to NPD literature, the adequacy

of various organizational approaches will

differ, depending on the presence and the

balance of the degrees of uncertainty versus

ambiguity. In situations dominated by uncer-

tainty, ‘traditional’ project management –

making extensive use of clear goals and

planning based on milestones and phases in

order to reduce lead-times – is appropriate

(Debackere and Van Looy 2003; Eisenhardt

and Tabrizi 1995). In situations marked by

high levels of ambiguity, characterized by

different interpretations on the nature and the

scope of the application envisaged, the ‘tradi-

tional’ approach of planning and intensive

preparation of the product deﬁnition is no

longer sustainable. Flexibility and adaptability

(Iansiti 1995; Verganti et al. 1998), delaying

the ﬁnal concept choice, and experimenting

then become the dominant organizational

themes (Eisenhardt and Tabrizi 1995; Thomke

2003; Thomke et al. 1996; Verganti et al.

1998). Similarly, Pich et al. (2002) discern

between instructionist, learning and selection-

ist approaches to project management and

organization, with the relevance of each

approach depending on the (in)adequacy of the

information available and the risk involved.

The authors suggest that these three project

management approaches may represent

different phases in a stage gate process, in

which uncertainty is gradually reduced over

the course of a NPD project (see also Loch

et al. 2005). Note, though, that this suggests a

linear, unidirectional path through different

stages, which we have shown to be a point of

discussion in life-cycle literature.

Process innovation. In addition to the extant

literature on new product innovation, we also

want to point to the body of literature that has

looked into process and organizational

innovation. One of the most prominent and

powerful concepts can be found in the model

developed by Abernathy and Utterback (1978),

linking product, process and organizational

innovation into one conceptual frame-

work. The main argument developed along-

side this model states that, as a dominant

product design emerges, the rate of process

innovation will temporarily supersede the rate

of product innovation. After some time,

though, process innovations level off and both

the rates of product and process innovation

become similar and interlinked, pointing to

the more routine character that both product

and process innovation assume during the

post-dominant design phase. Between the pre-

and the post-dominant design phase, innova-

tion has thus shifted from being highly radical

and conceptual to become more incremental

and gradual. Along this process, the organiza-

tion has evolved from a ‘ﬂuid’ state towards a

‘speciﬁc’ state. In other words, the organiza-

tion has become specialized, focused and

committed to a particular innovation path

(Utterback 1994). This co-evolution of product

and process innovation and organizational

adaptation leads to powerful path dependencies

100 © Blackwell Publishing Ltd 2006

Adaptation in new technology-based ventures: Insights at the company level

that may impede an organization in shifting to

more radical modes of innovation (Garud and

Karnoe 2001). These insights on product and

process innovation have been at the origin of

an emerging body of literature on organiza-

tional innovation. How can organizations adapt

and reinvent themselves to move from a

routine or mature state of innovation towards

more radical, predominant design innovation

states again? So, whereas the initial model

by Abernathy and Utterback (1978) is of a

unidirectional nature, more recent work has

stressed the need for companies in a mature

innovation state to go back to a more radical

innovation state, implying a cyclical innova-

tion process.

Recent insights by Christensen (Chris-

tensen 1997; Christensen and Overdorf 2000;

Christensen and Raynor 2003) have pointed in

the direction of a need for a portfolio of

organizational innovations that enable sustain-

ing versus disruptive innovation. They advocate,

among others, the use of incubator or spinout

forms of organization in order to support

disruptive innovation processes, pointing to the

fact that existing organizational processes

and value systems may be at odds with the

requirements of those more radical types of

innovation. Volberda (1998) leads us in the

same direction, i.e. the need for organizational

adaptation, ﬂexibility and innovation, when

he develops the concept of the ‘ﬂexiform’

organization.

Conclusion

Traditional life-cycle models have distinguished

between two main early life-phases in which

a venture’s initial idea is developed and

adapted into a viable business model. In the

‘start-up’ phase, products and services are

customized to the needs of innovators and

early adopters, often through prototyping. In

the ‘expansion’ or ‘commercialization’ phase,

the initial prototypes and customized products

or services are standardized. In these tradi-

tional stage-based models, later life-stages are

not characterized by adaptation. This is in

contrast to more recent work proposing

cyclical models of venture development, where

new businesses continuously move between

alternating cycles of opportunity detection

and resource mobilization, adapting their

business model in each cycle. Similarly, most

of the innovation literature develops argu-

ments concurring with this view that in-

novation processes move between different

episodes in a multidirectional and non-

sequential way. From the literature on process

organizational innovation, we learn that

organizations have to move between various

‘organizational states’ in order to support

pre- versus post-dominant design innovation

processes and that this movement between

organizational states need not be linear

and sequential. An exception to this cyclical,

non-linear view is the work by Pich et al.

(2002) modeling venture development as a

unidirectional stage-based process.

As the main driver for alternations between

various episodes, Van de Ven et al. (1999) put

forward complexity, resulting from ﬁve fac-

tors, of which ambiguity and uncertainty are

one. However, in the context of new ventures,

we should ask ourselves whether uncertainty

and ambiguity ought not be given a more

prominent role in driving this alternation,

especially since uncertainty and ambiguity

are the core reason why new businesses are

unable to deﬁne a viable business model

upfront. Complexity can be handled relatively

well when ambiguity is minimal or absent.

Co-ordination between the various tasks of a

highly complex endeavor then becomes more

predictable. Under circumstances of minimal

ambiguity, the interpretability of the tasks to

be executed increases, as well as their analyz-

ability, while equivocality decreases (Daft and

Lengel 1986; Daft and MacIntosh 1981; Daft

and Weick 1984; Perrow 1967; Van de Ven

and Delbecq 1974). One might then even

argue that complexity without uncertainty

or ambiguity calls for a highly structured

organizational approach, banning adaptation

as much as possible. It therefore appears

that uncertainty and ambiguity, in particular

June 2006

(instead of complexity), are the driver of the

adaptation process. Recent life-cycle literature

proposing cyclical models of venture de-

velopment regards improved knowledge of

resources and opportunities (and thus reduced

uncertainty/ambiguity with respect to these

resources and opportunities) as the trigger for

going from a stage of resource mobilization to

a stage of business model (re)deﬁnition. This

is in line with ﬁndings in the NPD literature

that management processes should be made

contingent on the degree of uncertainty and

ambiguity.

The innovation literature, in general, agrees

that different episodes require different

approaches to business model development.

Van de Ven et al. (1999) discern between

episodes of convergence and trial and error

learning, on the one hand, and episodes of

divergence and learning through discovery, on

the other hand. This is similar to ﬁndings

from NPD literature that planning is appro-

priate under uncertainty, while ambiguity

requires an experimental approach. However,

the authors whose work we have discussed do

not agree on what this experimental approach

should look like. Van de Ven et al. (1999) rec-

ommend the discovery of various but closely

related options in episodes of divergence.

Similarly, Pich et al. (2002) describe experi-

mentation as a ‘local search process’, and

Roberts and Meyer (1991) ﬁnd that a new

product strategy focusing on an intermediary

level of technology and market relatedness

outperforms both more and less related

strategies in technology-based companies.

This contrasts with the recommendation of

De Meyer et al. (2002) that fundamentally

different approaches be tried under situations

of chaos.

Factors Enabling Adaptation

Since business model adaptation is crucial for

NTBVs, it is not only important to study

the adaptation process, but also the possible

enablers for adaptation. As stated earlier,

the literature on adaptation in entrepreneurial

companies focuses mainly on the characteris-

tics of the entrepreneur. Pitt and Kannemeyer

(2000), for example, investigate the effect of

the entrepreneur’s personality traits (intoler-

ance of ambiguity, locus of control and risk-

taking propensity) on the degree to which

marketing strategy has changed. However,

since existing research has demonstrated the

relevance of the ﬁrm level for NTBVs, this

paper wants to look at how factors at the ﬁrm

level can enable adaptation. Existing ﬁrm-

level research suggests that adaptation in

established organizations is highly related to

slack and inefﬁciency in resources used

(Holbrook et al. 2000; McGee et al. 1989;

Muzyka et al. 1995). To our knowledge however,

no one has studied the effect of resource

availability on adaptation in new (technology-

based) ventures. We ﬁnd it important to

investigate further the potential relationship

between resources and business model

adaptation, especially since research shows

that entrepreneurship is intimately connected

with the appearance and adjustment of unique

and idiosyncratic resources (Alvarez 2003)

and that new ventures often have difﬁculties

in acquiring resources. Although companies

need resources in all phases of their life,

young ventures, in particular, are confronted

with few key resources (Cooper 2002) and

may be hindered in their strategy selection

and implementation because of liabilities of

smallness and newness (Mc Cartan-Quinn

and Carson 2003; Wyer and Smallbone 1999;

for an excellent overview, see Mellahi and

Wilkinson 2004). New technology-based

ventures in particular have difﬁculties in

obtaining external ﬁnancing (Garnsey 1995;

Westhead and Storey 1997). We shall now

discuss how, according to existing research at

the ﬁrm level, resources can enable adaptation

in NTBVs.

Resources, Capabilities and Strategy

According to the resource-based view of the

ﬁrm, the success or failure of an organiza-

tion is directly inﬂuenced by its resources.

102 © Blackwell Publishing Ltd 2006

Adaptation in new technology-based ventures: Insights at the company level

Organizations can achieve competitive advan-

tage when they have resources that are valu-

able, rare, inimitable and non-substitutable

(Eisenhardt and Martin 2000). Unique,

difﬁcult-to-imitate resources acquired through

organizational learning are then seen as

sources of competitive advantage (Dierickx

and Cool 1989). Dosi et al. (2002) consider

organizational capabilities – deﬁned as ‘the

know-how that enables organizations to per-

form and extend its characteristic “output”

actions’ – a prominent example of such

gradually accumulated and shaped resources,

critical for a ﬁrm’s competitive advantage.

The resource-based view of the ﬁrm thus

suggests that the parameters of organizational

strategy are driven mainly by its resources and

capabilities, and less by its environment (Das

and Teng 2000; see also Burgelman et al. 2001

on the linkages between technological capa-

bilities, technology strategy and experience).

Various studies on innovation and entre-

preneurship have alluded to the role of

human, technological, ﬁnancial and networking

resources for strategy and success (for an

overview, see Table 1). Some authors discuss

the effect of resources/capabilities on possi-

bilities for change and innovation, whereas

others focus on the relationship between

resources/capabilities and success. Based on

their ﬁndings, we can derive a number of

hypotheses on the effect of human, techno-

logical, ﬁnancial and networking resources/

capabilities on business model adaptation in

NTBVs. These are given in the last column of

Table 1. Note that adaptation at the ﬁrm level

is apparently affected by human resource

characteristics deﬁned at the individual level

of the entrepreneur, as well as by human

resources deﬁned at the level of the ﬁrm.

Initial versus Accumulated Resources

In general, when studying the possible effects

of resource endowments, one needs to be

aware of differences between initial endow-

ments and resources that are accumulated

over time. As summarized by Shane and

Stuart (2002), some entrepreneurship studies

propose that initial resource endowments

have lasting effects on performance (Baron

et al. 1996; 2002; Stinchcombe 1965). The

resource-based view, in general, considers

resources/capabilities/endowments sticky in

the short-run, since they consist mainly of

routines (Cockburn et al. 2000; Collis 1994;

Teece et al. 1997; Winter 2003), which can

only be learned and remembered through the

execution of high-frequency, repetitive daily

business over long periods of time (Nelson

and Winter 1982; Winter 2003). Processes

(i.e. current routines) are then shaped by the

ﬁrm’s current asset positions and molded by

its development paths, because learning tends

to be local (Teece et al. 1997; see also Dosi

et al. 2002, on evolutionary economics).

However, Shane and Stuart (2002) point out

that not much evidence exists on the lasting

effect of initial resource endowments because

of the difﬁculty of obtaining information on

the early phases of new ventures’ lives. Given

this lack of empirical evidence, it should not

be a surprise that other researchers believe

that initial resource stocks dissipate quickly

(Bruderl and Schussler 1990; Fichman and

Levinthal 1991).

Cockburn et al. (2000) refer to this duality

and point out that, under the current under-

standing, differences in performance are

related to initial conditions and inertial forces

(Cockburn et al. 2000; Helfat and Raub-

itschek 2000; Holbrook et al. 2000; Klepper

and Simons 2000; Langlois and Steinmuller

2000; Raff 2000) as well as ongoing efforts

and adaptation (Helfat and Raubitschek 2000;

Holbrook et al. 2000; Raff 2000; Rosenbloom

2000). The ability of a company to change is

further determined by the initial founding

conditions of the ﬁrm as well as by the

ongoing efforts it makes to adapt (Holbrook

et al. 2000; Langlois and Steinmuller 2000).

Conclusion

According to the resource-based view of the

ﬁrm, the success or failure of an organization

June 2006

Table 1. Possible effects of resources on adaptation

Resource type Previous findings

Possible effect

on adaptability

Technological resources

Internal availability

of in-depth know-how

about technology

and about possible

applications of

this technology

•Not the initial technological choice of a company, but the

adaptability of its technological capabilities, determine its

success (Tegarden et al. 1999)

•Successful exploitation of important external information

and technology is related to the capacity of adapting and

improving this technology through internal know-how

(Burgelman et al. 2001; Cohen and Levinthal 1990;

Freeman 1991; Lee et al. 2001, Macdonald 1987)

•Depth of technology strategy may offer the benefit of

increased flexibility and adaptability (Burgelman et al. 2001)

Broadness of technology

platform

•Scientific or technological knowledge can form the

foundation for multiple products and stages (Helfat and

Raubitschek 2000; Nerkar and Shane 2003, on

general-purpose technologies)

•The depth and width of technological opportunities in

the neighborhood of a firm’s prior research activities will

affect its future options (Saemundsson and Lindholm

Dahlstrand, 2005; Teece et al. 1997)

Specificity of technology

platform

•Cottrell and Nault (2004), in their study of the

microcomputer software industry, find that products

covering more computer platforms perform worse

•A specific (as opposed to a general) technology platform

may allow the development of more in-depth knowledge

of this technology and its potential applications, in turn

enabling adaptation

Human resources

In general • The long-term success of new ventures has been associated

with human capital endowments (Bruderl et al. 1992)

Prior experience • Prior experience enables and constrains innovation, market

entry decisions and thus change (Cockburn et al. 2000;

Helfat and Raubitschek 2000; Holbrook et al. 2000;

Klepper and Simons 2000; Langlois and Steinmuller

2000; Raff 2000; Tripsas and Gavetti 2000)

•The problems entrepreneurs have wrestled with in the

past develop the skills and intuition for how to meet

the challenge successfully the next time around

(Christensen and Raynor 2003; McCall 1998)

with the specific business

model

•Founder’s experience with the specific technical problem can

be crucial for new ventures’ success (Nerkar and Shane 2003)

with starting-up

and/or working in

new ventures

•Founder’s experience with starting-up new companies

and/or with working in new ventures can be crucial for

new ventures’ success (Nerkar and Shane 2003)

in different functional

backgrounds

•Experience in different functional backgrounds allows

the venture to acquire a sufficiently large capabilities and

knowledge base (Littunen and Tohmo 2003)

•There is a need for internal R&D (Cohen and Levinthal

1990; Lee et al. 2001)

•There is a need for management and market orientation

(Deeds et al. 1999; Helfat and Raubitschek 2000;

Roberts et al. 1968, 1969, 1970)

•The ability of entrepreneurial firms to continue

identifying and developing new opportunities depends

on the ability of its members to share and to articulate

knowledge (West 2001)

104 © Blackwell Publishing Ltd 2006

Adaptation in new technology-based ventures: Insights at the company level

Financial resources

Amount of financial

resources available in

general

•The inability to acquire physical assets may hinder a

firm’s ability to change (Holbrook et al. 2000)

Inverse

u-shaped

•Certain amount of financial slack has to be available

for opportunity capture (Evans and Jovanovic 2002;

Muzyka et al. 1995)

Amount of financial

resources initially

available

•It is not necessary to have huge amounts of financing at

the outset (Dorfman 1983; Stevenson and Gumpert 1985)

Inverse

u-shaped

Amount of financial

resources available later on

•Resources need to be gathered and deployed in stages

(Bhidé 1992; 2000; Churchill and Lewis 1983)

Inverse

u-shaped

Networking

Number of alliances • Networking provides companies with external know-how,

information and feedback from the environment, which

are important vehicles for change (Helfat and Raubitschek

2000; Holbrook et al. 2000; Kaufman et al. 2000; Low and

MacMillan 1988; Raff 2000; Saxenian 1994)

Inverse

u-shaped

•Networking reduces development costs and risk of

irreversibility (Stuart 2000), thus broadening the range

of choices available for the firm (Foray 1991)

•Networking relationships are firm-specific and usage-flexible

resources, allowing for commitment and flexibility at the

same time (Ghemawat and del Sol 1998; Larson 1992;

Nohria 1992; Stuart 2000)

•Developing a solid basis for collaboration takes time,

manpower and resources, and can therefore lead to a

loss of technical lead (Smith et al. 1991)

•The diffusion of new ideas must come through the weak

ties that connect people or businesses in separate cliques

(Debackere and Clarysse 1998; Granovetter 1973)

•If relations with key customers become too close, they

may insulate small firms from other sources of information

and foreclose opportunities (Bianchi and Bellini 1991;

Foray 1991; Glasmeier 1991; Pouder and St John 1996;

Yli-Renko et al. 2001)

Strategic fit between

partners

•A shared understanding of the business rationale for

the alliance positively affects alliance performance

(Harrigan 1988; Medcof 1997)

Inter-partner resource

similarity and resource

utilization

•Resource similarity and resource utilization (leading to

supplementary, surplus, complementary or wasteful

alignments) affect alliance performance (Chen 1996;

Das and Teng 2000)

+ for

complementary,

supplementary

and surplus;

– for wasteful

alignment

Efficiency of alliance

network

•Enhanced performance does not only depend on the

value of the individual alliances, but also on the way

these alliances are configured into an efficient network,

with a minimum of redundancy, internal conflict and

complexity, on the one hand, and a maximum of diverse

information and capabilities, on the other hand

(Baum et al. 2000)

Resource type Previous findings

Possible effect

on adaptability

Table 1 (Continued)

June 2006

is directly inﬂuenced by its resources. Various

studies on innovation and entrepreneurship

have alluded to the role of human, technolog-

ical, ﬁnancial and networking resources for

change, innovation and success. The current

understanding is that initial as well as later-

acquired resources affect a ﬁrm’s performance

and ability to change. However, to our know-

ledge, no one has studied the effect of initial

and later-acquired resources on business

model adaptation in NTBVs. This is particu-

larly surprising, given the difﬁculties these

ventures have in acquiring resources. We

therefore conclude that more research is

needed to investigate the effect of (initial as

well as later) resource availability on business

model adaptation in NTBVs. With respect to

human resources, experience and capabilities

on both the individual level of the entre-

preneur as well as the ﬁrm level need to be

taken into account.

Also, when we study the effect of resources

on adaptation, we can expect to ﬁnd interac-

tion effects between technological, ﬁnancial,

human and networking resources, both initially

present and accumulated over time. For exam-

ple, the absorptive capacity of an organization

– which is related to an organization’s pre-

existing knowledge structure (Cohen and Lev-

inthal 1990) – will inﬂuence its ability to use

new information (Burgelman et al. 2001;

Roberts 1991) such as information gathered

through networking. We can also expect an

interaction effect between the prior entrepre-

neurial experience present in the new venture,

on the one hand, and ﬁnancial resources, on

the other hand, especially if the company

attracts venture capital. Venture capitalists

differ in their value-added potential (Bygrave

and Timmons 1992; Hsu 2004a; Sahlman

1997), providing entrepreneurs not only with

ﬁnancial resources, but also with business

referral, mentoring, industry knowledge,

recruitment assistance, etc. (Hsu 2004a). In

addition, founders with prior entrepreneurial

experience affect the timing and valuation of

venture capital funding (Hsu 2004b) and may

be able to acquire ‘higher-quality’ capital,

such as investments from experienced, well-

networked venture capitalists. This means that

the effect of ﬁnancial resources on adaptation

may differ, depending on the experience of

the founders. This effect may be larger for

experienced founders because of the higher

intrinsic quality of the ﬁnancial resources they

are able to gather.

Summary and Directions for Further

Research

In this paper, we have argued that existing

ﬁrm-level research on adaptation (in new as

well as in established companies) is relevant

for developing insights into NTBVs’ business

model adaptation and, more precisely, into the

process of and the enablers for adaptation in

NTBVs. Furthermore, insights on adaptation

in NTBVs can be of importance for estab-

lished companies that adapt to changes in

their environment and can add to the general

discussion about the existence of dynamic

capabilities in high-velocity environments.

Based on an overview of various bodies of

literature at the ﬁrm level (including literature

on innovation management, life-cycle models,

and studies on performance enablers in new

ventures), we have tried to develop an insight

into the process of business model adaptation

in NTBVs and into factors enabling business

model adaptation in NTBVs. We put forward

initial as well as later-acquired human, tech-

nological, ﬁnancial and networking resources

as possible enablers for business model adap-

tation in NTBVs. In addition, we propose that

the process of business model adaptation in

NTBVs consists of different episodes, charac-

terized by uncertainty or ambiguity. A NTBV

then alternates between periods of uncertainty

and periods of ambiguity. The company’s

approach to business model development should

be made contingent on this presence of un-

certainty or ambiguity. Whereas uncertainty

requires testing and exploiting a given direc-

tion through planning, ambiguity requires

exploring new directions through experimen-

tation. However, it is not clear from existing

106 © Blackwell Publishing Ltd 2006

Adaptation in new technology-based ventures: Insights at the company level

literature whether this experimentation

should include related or unrelated business

models.

New research on NTBVs should verify

whether the model (as represented in Figure

2) is a truthful description of business model

adaptation in NTBVs. When studying the pos-

sible enablers for adaptation, one has to check

for interaction effects between technological,

ﬁnancial, human and networking resources,

both initially present and accumulated over

time. If ﬁrms’ resources turn out to enable

adaptation, this would suggest that adaptation

is indeed an organizational capability and not

just a personal skill of the entrepreneur.

With respect to the adaptation process,

research should pay special attention to

whether episodes characterized by ambiguity

require experimentation with more or less

related business models. In addition, research

should clarify whether the approach to busi-

ness model development in each episode con-

sists of routines or whether it is governed

solely by ‘ad hoc problem solving’. If routines

can be identiﬁed that underlie exploitation of

a given direction through planning (the

approach under uncertainty) and exploration

of new directions through experimentation

(the approach under ambiguity), this would

suggest that adaptation is indeed a dynamic

capability and that dynamic capabilities exist

in high-velocity environments.

Notes

1As pointed out by Eisenhardt and Martin (2000)

and Dosi et al. (2002), the term ‘dynamic

capabilities’ is very similar to ‘competences’ – as

in ‘architectural competences’ (Henderson and

Cockburn 1994) and ‘core competences’

(Prahalad and Hamel 1990) – and also ‘com-

binative capabilities’ (Kogut and Zander 1992).

2This deﬁnition of ambiguity does not correspond

to what economists understand under the term

‘ambiguity’ or ‘Knightian uncertainty’. In economics,

these terms refer to the absence of (knowledge

on) probability distributions. This situation can

be dealt with by representing ambiguity as

a probability distribution of probability distri-

butions (Camerer and Weber 1992). These economic

terms assume that the relevant decision variables

and their causal connections are known; only the

probability distributions of their possible outcomes

are unknown. Ambiguity as deﬁned by Schrader

et al. (1993) and used in this paper implies that

the relevant decision variables and outcomes

are not known. Economists refer to this as

‘unawareness’ or ‘unforeseen contingencies’ (Kreps

1992; Modica and Rustichini 1994); scholars in

public policy have used the term ‘wicked problems’

(Rittel and Webber 1973).

Figure 2. Propositional model.

June 2006

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