Database Management Systems Ramakrishnan (Raghu Ramakrishnan)

department in an established company – in order to
be successfully brought into use in markets and
organisations.

II.4 THE THREE CHAPTERS OF
PART II

Chapter 4 introduces the core issues and central
ways of understanding innovations and innovation
processes. The variety and complexity of
innovation will become clear, as well as some of
the main challenges related to managing
innovation. Insights into the concepts and
classifications of innovation and innovation
platforms are presented. Next, methods to organise
and manage innovation processes, from the idea
development stage to prototyping of the innovation
life cycle, are presented. Some key challenges for
organising and managing innovation processes are
identified, along with some suggestions for
overcoming them. Finally, Chapter 4 addresses the
technology diffusion process of moving
innovations through commercialisation into
widespread use. The end-of-chapter case study,
Salma, tells the story of a biotechnology
innovation research project in the food industry
from the product development stage through
marketing of the product. It illustrates the typical
non-linear path of innovation processes, and how
dead ends may spur new ideas that eventually lead
to market success.

Chapter 5 presents fundamental and critical
issues behind IP faced by technology
entrepreneurs, and outlines a set of common routes
to commercialisation. While many entrepreneurs
are familiar with some of the basic concepts
behind IP, such as patents, copyrights or
trademarks, for the first-time entrepreneur

managing IP can take on the aura of a full-blown
crusade. Assessing IP, its value and whether or not
it is important to a start-up can seem like a
minefield. This chapter unravels some of the
conundrums and mysteries associated with the
unique cross-disciplinary skills at the interface of
business, law and technology required to manage
IP. Furthermore, the chapter outlines and discusses
IP strategy and routes to commercialisation, such
as licensing and new venture formation.

The chapter covers the following key themes.
First, it explains what IP and IP rights are, before
discussing how to choose and implement
appropriate protection. Then, the development of
IP strategy is outlined, before explaining how to
search for IP information and how to enforce IP
rights. Last, routes to commercialisation are
presented and their pros and cons discussed. The
chapter concludes with a case outlining the
challenges presented in the realm of
nanotechnology.

Chapter 6 emphasises the development of
business concepts and business models for testing
and learning how to create a profitable match
between customer values, production factors and
income factors. The use of lean start-up methods,
business model innovation and a series of related
approaches (design thinking, agile, growth
hacking, discovery-driven growth, to name but a
few) has become an important way to get ahead of
competitors in today’s globalising and increasingly
connected world. Related themes of scaling and of
metrics for measuring business growth are
included. Chapter 6 invites the reader to work on

the commercialisation of the invention and the
organising of the venture: How can the invention
create value for users and revenues for the
venture? How should it be produced and brought
to market, with what activities and resources?
Business modelling is put at the centre in this
chapter, signalling the preference for business
modelling and other iterative and learning-
orientated tools that are suited to assisting
entrepreneurs in the early stages of a start-up. We
would also like to highlight that a well-developed
and tested business model is critical for building a
high-growth venture.

First, we seek to explain that opportunities need
to be developed into business concepts consisting
of products/services and what value they will
create in the market (value proposition). Second,
we argue that the iterative development of a viable
business model helps configure the available
resources in order to create unique customer value
(value proposition) and how the company will
capture economic and other value from this. In
other words, how the business can be organised in
order to meet customers’ needs and make money.
Finally, we discuss how to develop metrics for
measuring growth and business model
performance, and some core challenges of
identifying scalable business models.

The end-of-chapter case study in this chapter is
Spotify Inc. The Swedish music-streaming service
has taken a strong position in many countries with
a disruptive service, demonstrating that people are
willing to pay for user-friendly and socially
orientated online services.

II.5 REFERENCES

Blank, S.G. (2005) The Four Steps to the Epiphany: Successful
Strategies for Products That Win, 2nd edn, Cafepress.com.

Honig, B. (2004) “Entrepreneurship Education: Toward a Model of
Contingency-based Business Planning”, Academy of
Management Learning and Education, 9(1): 258–273.

McGrath, R.G. (2010) “Business Models: A Discovery Driven
Approach”, Long Range Planning, 43(2–3): 247–261.

Ries, E. (2011) The Lean Startup: How Today’s Entrepreneurs Use
Continuous Innovation to Create Radically Successful
Businesses. New York: Crown Publishing.

Sarasvathy, S.D. and Dew, N. (2005) “New Market Creation
through Transformation”, Journal of Evolutionary Economics,
15: 533–565.

Schumpeter, J. (1942) Capitalism, Socialism, and Democracy. New
York: Harper and Row.

Stevenson, H.H. (1983) “A Perspective on Entrepreneurship”,
working paper, Harvard Business School, Cambridge, MA.

INNOVATION Chapter
4
AND

DIFFUSION

OF

TECHNOLOGY

IN PRODUCTS

AND

SERVICES

4.1 LEARNING OBJECTIVES

In this chapter, core issues and central ways of understanding
innovations and innovation processes are introduced. The
variety and complexity of innovation will become clear, as well
as some of the main challenges related to managing
innovation. First, an overview of the concepts and
classifications of innovation and innovation platforms is
provided. Next, methods to organise and manage innovation
processes, from the idea development stage to prototyping of
the innovation life cycle, are presented. We also share
common challenges and suggestions for overcoming them.
Last, the diffusion process of moving innovations through
commercialisation into widespread use is reviewed.

After reading this chapter, you will be able to:

1. Define innovation and classify different kinds of
innovations;

2. Identify different sources of innovations;

3. Understand some of the complexities of managing
processes with high levels of uncertainty; and

4. Outline the various stages of the innovation life cycle and
their particular challenges.

4.2 CHAPTER STRUCTURE

The core elements of this chapter are as follows:

• Introduction
• Defining Innovation
• Classifying Innovations

◦ Product versus Process Innovations
◦ Infrastructure and Platform Innovations
◦ Incremental versus Radical Innovations
◦ Disruptive Innovations
◦ Open Innovation
◦ Overview of Classifying Innovations
• Sources of Innovation
• Technology Innovation Life Cycle
• Diffusion of Innovations
◦ Diffusion of Innovation and Adopter Categories
◦ Rogers’s Diffusion of Innovation Paradigm
◦ Moore’s Technology Adoption Life Cycle
◦ Diffusion in Practice
• Managing Innovation
◦ Management of Uncertainty
◦ Managing (in) Networks
◦ Managing Iteration

◦ The Contrary Forces of Innovation
◦ Innovation Investments
• Chapter Summary
• Case Study – Salma
• Revision Questions
• Further Reading and Resources
• References
• Glossary of Terms

4.3 INTRODUCTION

This chapter will define innovation, review
different types and classifications of innovation,
and identify some of the key characteristics of
each type. Further discussion includes from where
innovative ideas come and the technology
innovation life cycle to put the innovation into
practice. Sometimes ideas emerge from local
settings such as interdisciplinary teams, creative
individuals or boundary-spanning activities. At
other times ideas are sourced via increasingly
global networks, and concepts such as “open
innovation” help us grasp how ideas and patents
may be sourced via internet communities,
knowledge databases, business networks, and even
via businesses creating global markets for
intellectual property (IP).

4.4 DEFINING INNOVATION

Innovation can be defined in many ways. The
bottom line is that innovation is more than just the
invention of something new. And, rather than a
label of an outcome (“an innovation”), it is about
the whole process from the inception of an idea
through developing and testing to successfully
putting the innovation in use – whether
commercially in a market or as part of improving a
business or organisation (Garud et al., 2013).
Scholars studying the management of innovation
tend to use open definitions such as anything “new
to the involved actors” (Van de Ven et al., 1999) or
something that changes the practice of which it is a
part (Mork et al., 2010). On other occasions one
may talk about innovation being something new to
the industry, to the region or – ultimately – to the
world (Garcia and Calantone, 2002). While the
first two definitions tend to be more useful for
understanding innovation work in practice, the
latter is often applied when evaluating innovations
in retrospect.

However, innovation is different to invention:
“Invention is the first occurrence of an idea for a
new product or process, while innovation is the
first attempt to carry it out into practice”
(Fagerberg, 2005, p. 4). Frequently, and
particularly within science and technology, there is
a delay of years, if not decades, before an
invention has the potential to become an
innovation (Rogers, 1995). The time gap from
invention to innovation to common usage and
acceptance is bridged by the entrepreneur.

Although innovative ideas may be easy to
comprehend, the role of the entrepreneur is to

achieve “successful economic implementation”
(Fagerberg, 2002, p. 11). The entrepreneur is a
passionate visionary who has the responsibilities
of combining the factors necessary to successfully
lead innovations to market. The entrepreneur
pursues business opportunities that can change the
market and is considered “an innovative economic
agent” (Wadhwani, 2010). This concept directly
connects the success of an innovation with
entrepreneurship, as it is the entrepreneur’s
responsibility to guide the innovation process.

However, the function of entrepreneurship
differs from regular business management within
the firm. Business managers provide results by
imitating existing methods, while entrepreneurs
experiment with new combinations and overcome
obstacles – including the resistance to change – to
bring their vision to fruition (Schumpeter, 1928, p.
380). Innovations are difficult to develop and
implement, so the collaborative effort of a well-
rounded team will be essential to long-term
success. This will be discussed in further detail in
Chapter 10.

Schumpeter (1942) found that entrepreneurs
had the role of introducing new products, services
and even production methods to the economy.
While established companies are concerned with
incremental improvements of their ongoing
activities, new entrants (innovators) coming with
new technologies and new ideas can have the
effect of “creative destruction” in the economy.
Creative destruction is when innovative solutions
are introduced by entrepreneurs, undermining the
current practice in the economy, and thereby

moving existing products, production methods and
even companies out of business. Paradoxically,
this is both what brings growth to the economy, for
instance by opening up new markets, and at the
same time what destroys the position and profits of
established dominant companies.

Entrepreneurs may be part of undermining the
traditional ways of doing things and hence trigger
large-scale industry and market changes. In this
way, Schumpeter believed that entrepreneurial
practices of supporting innovation served as the
catalyst for building the economy. The frequency
or infrequency of ideas and successful innovations
explained the ups and downs of economic waves
and the cyclical nature of economic development.

The remainder of this chapter will discuss the
elements of innovation management that are
essential for entrepreneurial success. For
technology innovation and the purposes of this
book, we will focus on the innovation process in
the context of new technology-based products or
services that are introduced to and implemented in
user settings, such as commercialisation.

4.5 CLASSIFYING INNOVATIONS

4.5.1 Product versus Process Innovations

A product innovation is the introduction of a good
or service that is new or significantly improved
with respect to its characteristics or intended uses.
This includes significant improvements in
technical specifications, components and
materials, incorporated software, user friendliness
or other functional characteristics. Product
innovations can utilise new knowledge or

technologies or can be based on new uses or
combinations of existing knowledge or
technologies (OECD, 2005). An example of a
product innovation is the development of electric
vehicles (EV), like Tesla, and hybrid electric
vehicles (HEV), like the Toyota Prius, where
elements of traditional cars (e.g. wheels, steering
wheel, brake systems, etc.) are combined with new
power sources (electric motors) and control
systems (e.g. electronic control of efficient use and
recharging of battery power). In the digital age,
product innovation increasingly includes service
aspects, often called “servitisation”. Examples are
when new technologies are presented as services
rather than products, such as software as a service
(SaaS), or when products (such as EVs) are sold as
a subscription service (such as car-sharing
solutions). In Chapter 8 we will elaborate on this
in terms of “service dominant logic”.

A process innovation is the implementation of a
new or significantly improved production or
delivery method. This includes significant changes
in techniques, equipment and/or software. Process
innovations are typically intended to decrease unit
costs of production or delivery, to increase quality
or to produce or deliver new or significantly
improved products or services (OECD, 2005). End
users may not always be aware of process
innovation, as the tangible product itself is not
necessarily altered significantly; however, process
innovation might still have led to improved
methods of production for that product. The
scaling up of the production of EVs and HEVs has
required intensive process innovation, particularly

related to the production of batteries and the
software-based control systems of the power
trains. The continuous innovation of production
methods for semiconductor chips paved the way
for making smaller and smaller computers.
Similarly, in heavy industrial activities, such as
energy production, farming, construction and
pharmaceuticals, process innovations may be
critical to the profitability of the industry. In other
words, innovative value propositions of reducing
cost/improving quality in production to established
firms may be highly attractive business
opportunities to entrepreneurial ventures.

Yet another example is the continuous technical
innovation efforts that enabled IKEA to keep the
price low and constant on its Lack tables for
decades. From manufacturing these tables in solid
wood in the 1970s, the production has gradually
been completely transformed through a number of
process innovations. While the Lack tables have
looked externally similar over the years, the
production technologies and the material
composition of the table have been altered
constantly to maintain a steady price point.
Currently, they are produced with cost-effective
pulp and advanced printing technology to simulate
the wood finish (Baraldi and Waluszewski, 2005).

In many cases, technology-based service
innovations can provide more efficient processes
through the use of technology in cases where the
service was previously delivered without
technology. Examples are SaaS for media
monitoring or project management, automated
DNA sequencing, and the use of micro sensors for

monitoring technical facilities in hazardous
environments.

Most product innovations occur at the
beginning of the product life cycle (PLC), as
designers analyse possible issues and make
changes – consequently innovating – before they
agree on design standards. As opposed to this,
process innovations usually intensify once the
design standard has been established and the
development team searches for improvements in
quality, efficiency or effectiveness throughout the
production process. In reality, product and process
innovations are closely linked to one another.
Many product innovations are based on process
innovations and vice versa (Table 4.1).

4.5.2 Infrastructure and Platform Innovations

Increasingly, the concept of innovation or
entrepreneurial “ecosystems” is used to denote
how innovation and entrepreneurship processes are
conditioned by their more or less favourable
environments (Granstrand and Holgersson, 2020).
Indeed, we can think of ecosystems as consisting
of the actors, resources and activities needed to
enable innovation within specific fields, including
everything from co-working spaces and
accelerators to investment capital and digital
platforms. In this section we focus on two related
types of innovations, which are often crucial to
enable other kinds of innovation for technology
entrepreneurs: infrastructures and platforms.

Table 4.1 Product versus process innovation classification
matrix

Type of Definition Examples Product life
cycle (PLC)
innovation attributes

Product The Electrical Typically
innovation introduction of vehicles (EVs), occurs at the
a good or such as Tesla; beginning of
Process service that is tablet the PLC
innovation new or computers, before
significantly such as the design
improved with Apple iPad; standards
respect to its online are set
characteristics services, such
or intended as Dropbox or
uses Zoom; Internet
of Things (IoT)
solutions for
monitoring,
learning or
communicating

The Use of 3D Typically
implementation modelling for occurs after
of a new or product design
significantly development; standards
improved innovative are set to
production or production improve
delivery methods for quality,
method semiconductor effectiveness
chips for or efficiency
computers;
Uber’s
software for
real-time
analytics and
managing
millions of
drivers;
improving
production
processes and
software
control
systems for EV
batteries;
IKEA’s Lack
table material
composition

improvements
to maintain a
low and steady
price point for
decades

First, infrastructure innovations are wider
technical systems that enable or improve
communication, such as transport systems, energy
grids, 5G networks and financial systems. The
realisation of infrastructure innovations most often
depends on joint efforts by a number of actors,
often involving science and business as well as
politics. Van de Ven et al. (1999) refer to
successful infrastructure innovators as a number of
different actors that “run in packs”. The common
investments will in the longer run provide joint
resources for improved action, often even
enlarging the market opportunities for all.
Typically, this includes negotiating standards and
regulations, to frame how multiple actors and
entities may operate or utilise parts of the
infrastructure. The internet is obviously a large-
scale example of an infrastructure innovation, and
the roll-out of 5G networks globally enables an
enormous expansion on Internet of Things (IoT)
solutions (Table 4.2).

Second, there are platform innovations. These
are novel technological solutions that serve as
platforms for the distribution of services. The aim
is usually for the innovators to create an “ecology”
of complementary and competing services that
may attract and deliver value for large numbers of
users (Rietveld et al., 2019). Hence, an innovative
actor can get “help” to speed up and expand

product and/or service innovation and thereby
further develop the market, or the use, for the new
technology. This may also be seen as part of the
“open innovation” trend (Chesbrough, 2006).
Apple’s App Store, Google Play and the gaming
platform Steam are examples of platform
innovations where innovative companies created
platforms for thousands of new and established
businesses to distribute services, such as games
and other applications. The Open Source Drug
Discovery platform (www.osdd.net) became a
successful R&D platform for the collaborative
development of drugs for neglected diseases in
developing countries. Amazon.com provides its
Webstore as a distribution platform for other
businesses to establish trust while reaching a larger
customer base. In addition, Amazon.com offers
cloud storage solutions via its large data centres
and payment systems to external businesses, which
is a powerful example of how service and process
innovations for Amazon’s own business developed
further into platform innovations. It is also
interesting to see how the music-streaming service
Spotify for a period of time provided editorial and
service content by opening its application to
“apps”. This enabled Spotify to offer its users
concert tickets, music reviews, lyrics, playlists and
recommendations from both entrepreneurs and
major players in the press and the music industry,
until it joined the ecology of Facebook when
scaling globally (see the Spotify case study in
Chapter 6).

Table 4.2 Infrastructure versus platform innovation
classification matrix

Type of Definition Example Common
attributes
innovation

Infrastructure Wider technical Transport Typically
innovation systems that systems and requires
enable or energy grids; joint efforts
improve the internet; and
usability 5G networks, investments
blockchain from a
technologies; variety of
financial actors, and
systems standards
and
regulations

Platform Novel Apple App Opening up
innovation technological Store and new
solutions that Google Play; technologies
serve as a Amazon and services
platform for the Web to larger
distribution of Services; user groups,
services with Steam network
the aim of gaming logic of
attracting large platform; connecting
numbers of AirBnB and providers
users through Uber sharing and users
complementary platforms;
and competing GitHub
services software
platform

4.5.3 Incremental versus Radical Innovations

Another classification of innovation relates more
to the degree of novelty – whether the innovation
concerns smaller improvements or a relatively
high number of novel elements, thus creating a
bigger divide between the innovation and
established products (Table 4.3).

Incremental innovations are evolutionary in
nature: they consist of smaller improvements, or
extensions, in existing products, processes or

organisational activities introduced over time. As
these innovations typically come about in response
to specific and articulated customer needs, they are
likely to occur in demand-side markets (Shanklin
and Ryans, 1984) and tend to be based on what we
call “market pull” (as opposed to “technology
push”). Most firms engage daily in incremental
innovation, although some firms are more
conscious and strategic about the benefits of
empowering their employees to engage in
incremental innovation and improvement work. In
many instances, as illustrated in the previous
process innovation examples, we can see how a
series of incremental innovations over time may
add up to significant change in companies.

Table 4.3 Incremental versus radical innovation classification
matrix

Type of Definition Example Common
attributes
innovation

Incremental Evolutionary Kodak’s Lower risk;
innovation in nature; continuous often good fit
consists of improvement with
smaller of traditional established
improvements film for the practices;
in products, camera tend to come
processes or industry; from market
organisational continuous pull (Shanklin
activities development and Ryans,
introduced of traditional 1984)
over time; surgery
often based methods; Higher risk;
on extensions smartphones
of existing with new
products, features
processes or
organisational
activities

Radical Revolutionary Development

innovation in nature; of digital requiring
break the imaging; changes in
accepted development multiple
norm, of minimally interfaces;
bringing invasive tend to be
about new surgery driven by
and superior (laparoscopy), technology
advantages using push(Shanklin
compared to advanced and Ryans,
the old imaging, 1984)
technology sensor and
robot
technologies;
introducing
smartphones
in the first
place;
development
of artificial
intelligence-
supported
decision-
making in
medicine or
law

Market pull is a term commonly used when users or
market forces drive changes within an innovation. The
opposite is called technology push, which is when the
firm, often including its R&D community, pushes new
technologies without a request from the market or users
(Shanklin and Ryans, 1984).

Incremental innovation is more appealing for
many firms than radical innovation because it
involves less uncertainty, lower risks and a lower
degree of change in the processes that the
organisation is already successfully conducting.
However, there are also fewer increases in returns
associated with incremental innovation; moreover,
if firms become too inward-looking and only
pursue incremental change, they run the risk of not

discovering new and disruptive trends in their
environment before it is too late.

As opposed to incremental innovation, radical
or breakthrough innovations involve bigger
changes, may be more disruptive and require more
network relationships to change. In other words,
radical innovations tend to trigger more friction
with established counterparts, as well as
confrontations between the new and the old
(Hoholm and Olsen, 2012). However, while a
radical innovation in this way implies higher levels
of risks, it also carries the potential of higher
returns if successful. Radical innovations are
revolutionary in nature: they break the accepted
norm, bringing about new and superior advantages
compared with the old technology. In the context
of radical innovations, customer needs are often
unknown, therefore breakthrough innovations
frequently occur in supply-side markets (Shanklin
and Ryans, 1984), meaning that the “technology
push” governs the process.

Generally, the more radical the innovation, the
higher the risk, while potentially also bringing
higher rewards. Recent evidence suggests that the
chances of radical innovation increase when
innovation teams include more diverse experience,
and/or include scientists or engage with scientific
communities (Kneeland et al., 2020). Often radical
technologies emerge from research laboratories.
These can operate within publicly funded research
institutions (i.e. universities) or as part of larger
companies, which have their own research
laboratories. Companies and public research
bodies patent their discoveries and later can pursue

the commercialisation themselves, or license the
technology to others who apply it in the creation of
new products, services or processes (see Chapter 5
on IP and routes to commercialisation).

Radical and incremental are relative terms: how
radical an innovation is depends on perspective
and position in the industry. The classification of
an innovation as incremental or radical is relative
to degrees on a continuum. The bottom line is that
a radical innovation contains a relatively high
number of novel elements and combinations,
hence requiring significant changes in multiple
interfaces. Most technology innovations are not
entirely new. They are in fact modifications of the
existing body of technologies, evolving from
current technologies or combining several existing
technologies. In other words, technological
change, to a significant extent, is based on the
cumulative effects of many small incremental
innovations.

4.5.4 Disruptive Innovations

An innovation that brings about significant
upheaval within an industry with major
implications for all the major stakeholders is
known as disruptive (e.g. digital technologies have
dramatically changed many industries). However,
to be disruptive, an innovation does not necessarily
have to be radical in the sense of containing
radically new breakthrough technologies. The
distinction is rather found in how the technology
“fits in” or challenges the established system
(Ansari et al., 2016).

Clayton M. Christensen (1997) pioneered our
understanding of disruptive innovation. He
identified how new technologies, like the internet,
enabled a range of inventions that implied
disruptive breaks with the logic of the established
market. Key characteristics of disruptive
innovations are that in the beginning they are
simpler and are lower quality on some parameters,
but – importantly – they are also more accessible
or user-friendly and cheaper than the established
alternatives or incumbent technologies. Typically,
therefore, disruptive innovations create new
markets, emerging from “below” – from
entrepreneurs finding their niche in the “shadow”
of the high-quality and high-priced alternatives of
established firms – before growing into the
mainstream and threatening existing markets.

Key characteristics of disruptive innovations (Christensen,
1997):

• Solution is simpler and lower quality;
• Solution is more user-friendly;

• Solution is cheaper.

For established firms, Christensen (1997) states
that the three main challenges from disruptive
innovation are, first, that such technologies seem
so immature and of such low quality that they are
not perceived as a threat to the company or its
market position. This is normally a very
favourable situation for entrepreneurs with
emerging technologies. Second, when disruptive
technologies mature and gain a significant volume
of users, it may sometimes be too late for

established firms to catch up with the latest
entrepreneurial ventures already populating the
new field. Third, a change from an established to a
disruptive technology will for many established
firms mean extremely high costs as they have
invested heavily in the present techno-economic
system, which may be rendered of less use to the
company. Such expensive changes, as well as the
fear of contributing to the cannibalisation of the
established firm’s own products in the
marketplace, typically lead to conservative
attitudes towards potentially disruptive emerging
technologies among many firms.

Main challenges disruptive innovations create for
established firms (Christensen, 1997):

• Newer technologies are not viewed as a threat due

to the market position of the firm and the immaturity
and low quality of the product;

• Late reaction to the innovative technology may be

irrecoverable;

• Path dependency to established technologies makes

transitioning to newer technologies costly.

A classic example is the mp3 file format, which
enabled users to share their music without the help
of record companies, distributors and retail stores.
This technology spread without any help from
traditional distributors of music, either through
pirate consumers or through more or less legal
websites. It was an information and
communication technology company that gained
the market. Apple, by setting up iTunes as a web
store for mp3 files, was the first to demonstrate
how to earn money from this disruptive

technology. Note that the quality of an mp3 is far
lower than the compact disc format. Combined
with the ease of copying, this made the music
industry overlook the mp3 threat, which the
industry later tried to fight by all means available.
Today, the big and once-powerful record
companies still shiver over this industrial
earthquake. Another example is how cloud-based
services, such as Google Apps and Google Drive,
are gradually pushing aside the established
software solutions packaged with computers. This
has put significant pressure on the dominant
players, such as Microsoft, in the established
market. Furthermore, we could mention companies
like Uber and AirBnB as disruptive to transport
and accommodation industries, and the emergence
of 3D printing as potentially disruptive to a series
of manufacturing settings. Entrepreneurs
commercialising disruptive innovations need to
think carefully about how to balance the work to
attract end customers, while reducing the threat to
incumbents (producing resistance and counter-
attacks; Ansari et al., 2016). It is common to
distinguish between disruptive technologies and
disruptive business models. Experience tells us that
the former often require the latter to succeed (more
on business model innovation in Chapter 6).

In complex industrial systems, sometimes even
relatively incremental innovations may bring about
disruption. One small example is the attempt to
replace traditional surgery with the implementation
of a microwave technology for the treatment of
enlarged prostates in Swedish hospitals (Wagrell
and Waluszewski, 2009). This turned out to

challenge the established system on several
dimensions. The professional hierarchy was
challenged by the innovation, as medical doctors
in this field are trained in surgery, and hence many
resisted the new method. Every problematic aspect
with the new procedure would be used to
undermine the legitimacy of the innovation. The
reimbursement system and the purchasing function
in Swedish hospitals were based on having only
one main treatment procedure for each disease,
and as the microwave treatment could only be used
for some of the patients, it was difficult to fit it into
the economic and organisational structure. In sum,
this meant that many hospitals would resist
adopting the innovation – even several of those
that participated in the development process.

4.5.5 Open Innovation

Open innovation (Chesbrough, 2006; Enkel et al.,
2020) has become a very popular issue in the last
decade. It is putting the tension between openness
and protection of knowledge and IP to the fore.
The term is based on the acknowledgement that
the best competence and the best ideas often are
found outside the company needing it. Hence,
companies that are able to utilise and mobilise
knowledge, ideas and resources from other
companies and actors will be more innovative. In
today’s digital knowledge and information society,
knowledge has become much more available
globally, including via crowdsourcing,
collaborative communities and machine learning
(Enkel et al., 2020). One of the problems related to
open innovation is the “not invented here”

syndrome. In many established companies, people
will try to resist innovative ideas coming from the
outside because they are unfamiliar, or use
something emerging from a different setting.

The leadership skills needed to handle open
innovation include a strategic understanding of
intellectual property rights (IPR). Companies that
are really good at this do not just open up their
processes to anyone. They are also very conscious
about what processes and knowledge they are
willing to open up and what they need to keep
secret or protected within the company. There is
sometimes a delicate balance between openness
and protection. Entrepreneurial leaders thus need
negotiation skills and the ability to create win-win
situations, because no one will be interested in
long-term collaboration if it is not co-creating
solutions that may benefit both parties. It is also
good for a leader to have a multi-disciplinary
perspective, to understand people with different
professional and industrial backgrounds and to
move and translate between different perspectives.
Engineers, sales and marketing people, designers
and end users all communicate and understand the
world differently.

4.5.6 Overview of Classifying Innovations

In general, an organisation will usually be involved
in a mixture of the different types of innovation. It
is very likely, for instance, that while engaging in
product innovation, an organisation will also go
through process innovation in an attempt to
improve a possible prototype. As the
entrepreneurial company matures, we recommend

the successful practice of having a well-balanced
portfolio of lower-risk, short-term projects
focusing on incremental innovations, as well as
longer-term, high-risk projects focusing on
breakthrough technology. Incremental innovation
could bring in the quick returns needed for daily
activities and the survival of the business, while
radical innovations take a more long-term view,
with the possibility of more significant positive
results in the future. Successful innovators often
manage various projects at different stages in their
life cycle, so that the company is always involved
in new projects before other projects are
completed; this ensures continuity, while instilling
an organisational culture where innovation is on
the daily agenda.

In Chapter 6, we explore additional innovation
categories: organisational innovation and business
model innovation. These innovative ways of
organising and developing a business are
frequently paired with innovative technologies.
Further study of these innovation categories will
enhance the entrepreneurial toolbox.

4.6 SOURCES OF INNOVATION

There are many sources of innovation, from both
within and outside the organisation. Ideas can be
generated on the basis of some technical insight of
an individual or a group of individuals; innovation
can also occur following the identification of
previous problems or possible future issues.
Creative thinking is considered a core competency
in new ventures and having creative, inventive

employees and teams is a great source of
innovation.

Entrepreneurs, as well as creative people within
established organisations, are usually able to see
novel linkages in the wealth of information
gathered from all these various sources (Casson et
al., 2006; Foss et al., 2019; Rietveld et al., 2019).
Once an opportunity is recognised, the idea is
evaluated and tested. If successful and in line with
the organisation’s goals and available resources, it
then enters a development process, based on an
envisioned new product, service or process.
Gathering a wealth of information from varied
sources and developing further information creates
a good environment for innovation.

However, most of the time the roots of
innovation can be traced back to real problems or
issues in the market. An essential source of
innovation within organisations is the “voice of the
market”: listening to and understanding customers’
needs and expectations; networking with other
players in the market or in a company’s own
supply chain; collaborating openly with research
bodies and so on. Ideas can also be stimulated by
specific organisational goals or by external
environmental factors (i.e. opportunities).

While a simplistic classification would be to
divide innovations into technology-driven (push)
or market-driven (pull), in reality most innovations
occur due to a combination of these major factors.
Trott (2008) suggested an interactive model of
innovation, where innovation occurs as a result of
the interaction between the marketplace, scientific
research and the organisation’s capabilities (see

Case Box 4.1 for an example). Innovation happens
at the boundaries and companies must provide
those at the boundaries with enough freedom (in
both time and resources) to be able to generate and
pursue innovative ideas. A successful innovation
occurs when a need and a means to resolving that
need are simultaneously recognised and
developed. However, not all new ideas become
successful innovations. Research shows that
roughly only 1 in 3,000 raw innovative ideas
results in a commercially successful product or
service (Stevens and Burley, 2003).

CASE BOX 4.1 MICRO-PARTICLES: THE

CASE OF CONPART

Case written by Tom Ove Grønlund, CEO, Conpart.

Conpart is a technology company specialising in materials
for the international electronics industry. The business is
based on a unique and patented process for manufacturing
of extremely precise and mono-sized micrometre-sized
polymer particles. There are numerous different application
areas in electronics where Conpart’s particle technology can
be used. By applying nano-layers of different metals on the
particle surface, the particles can be rendered electrically
conductive, making them suitable as micro-connectors for
assembly of micro-components in electronics. One important
market is conductive adhesives, where such particles can be
filled into epoxy resins to make different types of conductive
adhesives, which are commonly used in modern electronics
manufacturing. There are several other fields of use for
conductive and non-conductive polymer-based particles in
the electronics industry.

Micro-particles have been used in electronics for decades,
but almost all technology development and volume
manufacturing have taken place in Asia, with Japan, Korea
and Taiwan in the lead. Hence, the Norwegian technology
company Conpart needed to address an international market
from the start. With very limited finances and resources, but
with a strong technology basis and world-leading

competence in its field, Conpart targeted big companies with
a leading position in their respective field. It focused on
applications where the technology could give long-lasting
technical advantages for the customers, either by improved
reliability or quality for their products or by reducing their
manufacturing cost with improved manufacturing processes.
Just two years after its foundation, Conpart signed a contract
with a major Japanese company, and after a three-year joint
development project, it got the first supply agreement.

This strategy has been a model for Conpart in order to
establish new projects and business. The development time
is relatively long and costly for such products, and the
development projects require high competence, strong
technology and hence good funding. Conpart has
successfully established many collaborative projects with
industrial actors, with support from either Norwegian
governmental funding, like the research council, or EU
funding. Through these development projects, Conpart
generates new applications and markets for its polymer
particles, and the plan is to become a world-leading supplier
of these highly specialised materials to the electronics
industry.

The outcome of innovation initiatives should be
closely monitored and assessed, with the company
gaining valuable insights from each experience
whether it was a failure or a success. According to
O’Sullivan and Dooley (2009), innovation
management should be based on a set of stages
that must be implemented; organisations should
either adopt or develop their own methodology
around managing innovation, which usually
encompasses the following steps:

1. Understand requirements and define goals –
understand the requirements of the
organisation’s stakeholders, define state of the
art and best practice in other organisations and
define goals based on these considerations.

This step is usually executed at the beginning
of each planning period.

2. Engage users and model processes – engage
various users and providers in problem
identification and idea generation; then create
models in order to help users understand how
the innovative value proposition works and
how it differs from the current offer. This step
is executed several times throughout the period
of the plan.

3. Create actions and empower teams – ideas are
converted into initiatives and projects with their
associated teams. This step occurs often as new
actions are defined.

4. Develop a migration plan – this is a dynamic
plan, which changes according to the progress
achieved in reaching (and changing) goals and
as various actions are implemented. It is
usually part of a knowledge management
system within the firm. This step is very
frequent; it should be reviewed once a week, as
goals, actions and teams change.

5. Implement actions and monitor results – this
consists of the implementation and monitoring
of goals, actions and teams over time and the
results. Monitoring what is happening should
provide feedback to the first steps, as results
are used to redefine goals. Step 5 occurs daily
as the performance outputs of each
organisational effort are monitored.

The trends regarding the increasing speed and
globalisation of innovation have led to a number of

new perspectives on how to keep up with or,
preferably, be at the forefront of innovation. An
important movement in the field of innovation
management is towards observing and/or involving
the users in the process. In the field of user-driven
(or sometimes “customer-driven”) innovation (Von
Hippel, 2006), methods and tools are being
developed to get beyond the scarce information
about users’ needs that can be obtained from
market/consumer surveys and focus groups. For
example, experienced and highly motivated “lead
users” are included in the innovation team, or
consulted throughout the innovation process, to get
hold of their unique experience and expertise as
users of similar technologies. A problem may be
that in the face of more or less radical inventions,
the user is often not able to articulate their own
need, or to predict their own consumer behaviour
in the future. Instead, sometimes companies seek
to observe the user in their own “natural
environment” to unveil their frustrations, daily
routines and relations to other technologies. At
other times, companies develop “toolkits” along
with their inventions to enable lead users (highly
skilled and highly interested users) to develop and
adapt the product to their own user patterns and
context. Design innovation methods have recently
been introduced to technical and service
innovation settings (Jevnaker, 2005; Verganti,
2009), since designers have a long and strong
tradition of developing and using methods to
identify users’ needs.

At the end of this phase, at least one idea
should be formulated. The following section will

provide further information on the technology
innovation life cycle, which will guide the
innovation to implementation.

4.7 TECHNOLOGY INNOVATION
LIFE CYCLE

There are several systematic steps within the
innovation process: problem analysis and idea
generation, testing and evaluating the idea, project
planning, prototyping and product development,
testing and launching the product into the
marketplace. These steps are not usually linear, but
rather overlap each other. The entrepreneur
generally needs to iterate several cycles of the
innovation life cycle before succeeding in
developing both a product and a market. There are
mainly three stages, or types of work to be done, in
the technology innovation life cycle:

1. Diagnose. The aim of this stage is to identify
and evaluate new ideas for products and
processes, usually through a comprehensive
analysis of environmental and internal factors
that will impact the potential success of
innovative ideas. Next, ideas are screened and
evaluated, as innovators try to assess the
feasibility and possible rate of success of each
project. A Strengths, Weaknesses,
Opportunities and Threats (SWOT) analysis
could be conducted in order to identify and
assess possible opportunities and threats in the
marketplace, including working with customers
in the process of identifying what is important
to them. Examples of best practices and

competing alternative solutions should also be
identified. This external scanning should be
paired with an internal assessment, which
would help decide on which strengths to
exploit and weaknesses to address (the SWOT
analysis tool is covered in Chapter 7).

2. Develop. After identifying the more promising
avenues, move on to the development stage,
whereby the idea is transformed through
planning and developing into a viable product
or process. Ideas are developed further in
response to the result of the initial analysis, and
propositions should be analysed and ranked
according to their importance and potential.
Resources should be devoted to the most
promising initiatives, and prototypes should be
developed and tested with users. Objectives
should be developed as the understanding of
the product and its use evolve (see Chapter 7).

3. Deploy. This phase consists of planning the
migration and roll-out. Roll-out is the process
of introducing the new product to the market or
employing the new or improved process in
particular areas of the business. The new
technology should be continuously monitored
and assessed in terms of meeting the initial
objectives; support systems should be in place
and ongoing training should be provided to all
those affected by the change brought about in
the organisation through the innovation.
Continuous learning from current experiences
would help in future decisions, and objectives
should therefore be revised often (the

marketing of technology is covered in Chapters
7 and 8).

The stages in the innovation process are all
interrelated and each individual decision at every
stage will influence all the other stages. These
stages also show the different contexts within
which the innovation needs to “fit” or find
alliances: the development setting, the production
setting and the user setting. While the initial stages
(also termed the “fuzzy front end”) in the
innovation process allow for a higher level of
uncertainty and encourage creativity, the
remaining stages of the process, where more
structure and solid and committed business
decisions are required, do not tolerate the same
level of uncertainty.

Technology innovation is most successfully
implemented when conducted as a continuous
process, which is viewed as part of the daily
activities of the organisation. However, the scope
of the resources available must be considered
when going through the technology innovation life
cycle. New ideas that will add value to the
innovation cannot be continually added, but must
sometimes be held back for inclusion in later
phases after the innovation demonstrates initial
success.

4.8 DIFFUSION OF INNOVATIONS

This section explains innovation and market
dynamics. The theory of diffusion (Tarde, 1903;
Rogers, 1995) reveals the “S-shaped curve” of
how successful innovations reach different

segments of users and how this impacts their
development and the economic returns. Rogers’s
theory on the diffusion of innovation has been
adapted for the high-technology context by
Geoffrey Moore.

4.8.1 Diffusion of Innovation and Adopter
Categories

Diffusion is the process by which an innovation is
communicated through certain channels over time
among the members of a social system. Social
studies conducted in the area of innovation have
found that the rate of adoption for an innovation is
highly dependent on the social system it occurs in;
the social system constitutes a boundary within
which an innovation diffuses. It affects the process
of diffusion in two ways:

• through the norms establishing behavioural

patterns; and

• through opinion leadership (the degree to

which an individual is able to influence
informally other individuals’ attitudes or
overt behaviour).

Originating in the research conducted by Gabriel
Tarde in 1903, the S-shaped curve (shown in
Figure 4.1) is the most widely used diagram
describing how people adopt innovations.
According to the speed of diffusion, the slope of
the S-curve might be steeper (for rapidly diffused
innovations) or more gradual (for innovations that
take longer to become accepted in the market).

Forty years later, a study conducted by Ryan
and Gross (1943) analysing the spread of hybrid
seed corn among Iowa farmers led to the
identification of different adopter categories. By
researching the speed at which different groups in
the market adopted an innovation after its
introduction, this study acknowledged the
existence of five adopter categories: innovators,
early adopters, early majority, late majority and
laggards.

Five adopter categories (Ryan and Gross, 1943):
1.
Innovators;
2.
Early adopters;
3.
Early majority;
4.
Late majority;
5.
Laggards.

Figure 4.1 S-shaped curve
Source: Tarde (1903).

4.8.2 Rogers’s Diffusion of Innovation
Paradigm

The most widely acknowledged author in the study
of diffusion is Everett M. Rogers. His book
Diffusion of Innovations, first published in 1962
(5th edition 2003), is highly influential in the
established paradigm of the diffusion of
innovation. Rogers put forward four theories of
diffusion: the individual innovativeness theory; the
theory of perceived attributes; the rate of adoption
theory; and the innovation decision process theory.

The individual innovativeness theory states that
the rate of adoption depends on the degree of
innovativeness of an individual or other unit (e.g.
group or organisation). Innovativeness is the
degree to which an individual or other unit of
adoption is earlier in adopting new ideas than other
members of a social system. Individuals are
divided into five categories on the basis on their
innovativeness (see Figure 4.2).

Rogers (1995) further defines the five adoption
categories as part of this theory.

1. Innovators (on average 2.5 per cent of

adopters) are venturesome, interested in new
and risky ideas, able to understand and apply
complex technical knowledge and able to cope
with a high degree of uncertainty about an
innovation at the time of adoption. Innovators
are also usually engaged in more cosmopolitan
social relationships, in control of substantial
financial resources and eager to communicate
with other innovators. Even though innovators
might not always be accepted within their own
social network, they play an important role in

the diffusion process, by launching the new
idea in the system.
2. Early adopters (13.5 per cent) are a more
respected and integrated part of the local social
system than are innovators, with developed
interpersonal networks. This adopter category,
more than any other, has the greatest degree of
opinion leadership in most systems. Early
adopters provide advice and information about
the innovation and they serve as role models
for many other members of a social system.
They adopt innovations based on seemingly
well-judged decisions. Early adopters are
instrumental in getting an innovation to the
point of critical mass, which occurs when
enough individuals have adopted an innovation
that is being further adopted by other
individuals, and thereby becomes self-
sustaining.

Figure 4.2 Five categories of innovators

Source: Based on Rogers, E. (1995) Diffusion of Innovations.
London, New York: Free Press.

3. Early majority (34 per cent) adopt new ideas
just before the average member of a system.
They do not like to take the high risk associated
with “being the first”, but they want the benefit
of the advantages of new discoveries. The early
majority interact frequently with their peers and
often hold positions of opinion leadership in a
system. This group may deliberate for some
time before completely adopting a new idea,
but they seldom lead.

4. Late majority (34 per cent) adopt new ideas
just after the average member of a system. This
group is more sceptical about anything new
that would imply a change on their behalf.
They are more traditional and do not adopt
until most others in their system have done so.
Sometimes the pressure of peers is necessary to
motivate adoption.

5. Laggards (16 per cent) are the most traditional
group and hence most suspicious of
innovations. The point of reference for the
laggard is the past. Decisions are often made in
terms of what has been done previously. Their
resources are frequently limited and they need
certainty that a new idea will not fail before
they can adopt it. Because of all, this group
possesses no opinion leadership.

Second, the theory of perceived attributes states
that there are five attributes or characteristics of an
innovation that determine its rate of adoption and
success:

1. Relative advantage is the degree to which an
innovation is perceived by users as better than
the idea it supersedes. This is based on
perception and may be measured in economic
terms, but social prestige, convenience and
satisfaction are also important factors. In
simple terms, the greater the perceived relative
advantage of an innovation, the more rapid its
rate of adoption will be.

2. Compatibility is the degree to which an
innovation is perceived as being consistent with
the existing values, past experiences and needs
of potential adopters. This may speed up
adoption.

3. Complexity is the degree to which an
innovation is perceived as difficult to
understand and use. More complicated
innovations will be adopted more slowly, as
they require the adopter to develop new skills
and understandings.

4. Trialability is the degree to which an
innovation may be experimented with on a
limited basis. New ideas that can be tried and
have visible results will generally be adopted
more quickly than innovations that cannot. A
higher degree of trialability reduces uncertainty
for the individual who is considering it for
adoption.

5. Observability is the degree to which the results
and benefits of an innovation are visible to
others. The easier the attributes can be
observed, imagined or described to potential

customers, the more likely those customers are
to adopt it.

Third, the rate of adoption theory states that an
innovation goes through a period of slow, gradual
growth before a period of speedy and significant
growth. The point is that as users gradually spread
their recommendations of the product, one may see
exponential growth until the market is saturated. In
this case, the rate of adoption is measured as the
number of members of a social system who adopt
the innovation in a given time period. The rate of
adoption is influenced by the five perceived
categories of adoption of an innovation, as
introduced above.

Finally, the innovation decision process theory
states that that diffusion is the mental process via
which an individual (or other decision-making
unit) passes through five distinct stages, from first
knowledge of an innovation to the confirmation
decision to adopt the innovation. The five stages
are:

1. Knowledge – a person becomes aware of the
innovation and has some idea of how it
functions;

2. Persuasion – a person forms a favourable or
unfavourable attitude toward the innovation;

3. Decision – a person engages in activities that
lead to the decision to adopt or reject the
innovation;

4. Implementation – a person puts the innovation
into use;

5. Confirmation – a person evaluates the results
of the innovation.

In terms of communication channels, research
shows that while mass media channels are more
effective in creating knowledge of innovations,
interpersonal channels carry more weight in the
later stages of the mental process of adopting an
innovation. Interpersonal channels are more
effective in forming and changing attitudes, as well
as influencing the decision to adopt or reject a new
idea. In other words, most individuals evaluate an
innovation not on the basis of expert advice, but
through the subjective evaluations of near-peers
who have adopted the innovation.

Rogers’s theory of diffusion has been very
important in explaining how innovations find users
and how mass markets are shaped. However, in
relation to technology innovation, Moore (2002)
found that some of the transitions between adopter
categories were more problematic than Rogers’s
theory suggested. This is what we turn to now.

4.8.3 Moore’s Technology Adoption Life
Cycle

Rogers’s theory on the diffusion of innovation was
adapted for the high-technology context by
Geoffrey Moore (2002). In the technology
adoption life cycle (TALC), the groups are still
characterised by different responses to the new
technology, yet there is a major difference in the
cycle of market penetration: it is not a continuum.
In this distinction, Moore pinpoints the important
problem of moving from one adopter group to

another, because their interests, needs and
resources may be very different. Hence, an
innovation’s ability to reach one group does not
necessarily mean that it is interesting to other
groups.

Therefore, for disruptive technologies, Moore
(2002) proposes a variation of the original life
cycle, in particular suggesting that there is a gap or
chasm between the early adopters group (the
visionaries) and the early majority group (the
pragmatists and starting point of the mainstream
market; see Figure 4.3).

Also, Moore updated the labels for the five
adopter categories (Table 4.4). The early market
consists of the first two groups: technology
enthusiasts and visionaries.

Figure 4.3 Discontinuous technology adoption

Source: Based on Moore (2002), The Revised Technology
Adoption Life Cycle.

Innovators are technology enthusiasts, having
technology as a central interest in their lives.
Techies are always looking for state-of-the-art
technology and are intrigued with the advancement
of technology in general. However, as opposed to
the innovators group in the classic theory of the
diffusion of innovations, technology enthusiasts do
not typically have the money to fund further
development.

Techies are not numerous in any market, but
they provide a good testing ground for a new
technology, and they are extremely important in
reaching the visionaries group. According to
Moore (2002), technology enthusiasts fulfil the
role of gatekeepers to the next group. In other
words, a technology-based product has to impress
technology enthusiasts in order to get the attention
of the visionaries (Moore, 2002).

Visionaries, or early adopters, are industry
revolutionaries looking for breakthrough
applications. They have the qualities necessary to
envision and understand discontinuous innovations
for the potential advantage it might provide, yet
they need the endorsement of technology
enthusiasts.

Visionaries can easily match the potential of a
new idea with strategic opportunities. They are
very important because they have the ability to
fund development, as well as positively
communicate and persuade within their own
organisation and also within an industry.

Visionaries are essential to opening the high-
technology segment for a specific technology
(Moore, 2002).The early majority are called
pragmatists by Moore (2002). They are a group
that value practicality more than the innovation
aspect. They will not venture into buying new
products unless they can have the reassurance of
established and credible references. They are risk
averse and price sensitive. They usually favour
products and brands that are established as market
leaders, which provide reassurance. Because they
represent a substantial segment in the market, they
are essential in achieving critical mass –
substantial profits and growth.

Table 4.4 Five innovation adoption categories (based on
Moore, 2002)

Market phase Adoption Key Challenges
group characteristics

EARLY Technology Technology is a Not
MARKET enthusiasts central interest numerous in
(Innovators) Always looking any market
for state-of-the- Gatekeepers
Visionaries art technology to the
and are visionaries
intrigued with group
the Technology-
advancement of based
technology in products
general Do not must
typically have impress
the money to them in
fund further order to get
development the attention
Provide a good of visionaries
testing ground
for a new
technology

Industry Require the

(Early revolutionaries endorsement
adopters) looking for of
breakthrough technology
applications enthusiasts
Possess the Essential to
qualities opening the
necessary to high-
envision and technology
understand segment for
discontinuous a specific
innovation for technology
the potential
advantage it
might provide
Can easily
match the
potential of a
new idea with
strategic
opportunities
Can fund
development
Communicate
and persuade
within their own
organisation
and within an
industry

THE CHASM Pragmatists Value Biggest
practicality challenge:
MAINSTREAM (Early more than the making the
innovation transition
MARKET majority) aspect Risk between
averse and visionaries
price sensitive and
Will not venture pragmatists,
into buying new what Moore
products unless refers to as
reassured by the chasm
established and Represent a
credible substantial
references, segment in
preferably by the market
market leaders and are
Want a essential in
completely achieving
functional critical mass

product and are Cross the
only willing to chasm only
accept by switching
incremental from a
improvements marketing
strategy
focusing on
functionality
to one that
can present
the
innovation
as the new
industry
standard,
which is
necessary
for
pragmatists

Conservatives Not comfortable One-third of
(Late majority) with handling the market,
novelty so the size
Usually wait of this
until the segment
technology makes it
becomes the highly
accepted attractive
standard before May be
purchasing it successfully
Averse to high targeted
prices Prefer once the
well-known product
companies and reaches the
expect maturity
significant stage
support during
and after the
purchase

Sceptics Not interested No
(Laggards) in new challenges,
technology in as sceptics
any form, be it are not
for economic or pursued by
personal technology-
reasons driven
Might even companies