It is evident that Governments today regard technology diffusion as an important route to increased competitiveness, especially diffusion into small businesses (La Rovere, 1998; Tran and Kocaoglu, 2009) with advantages of flexibility, dynamism and responsiveness. However, small firms have disadvantages related to the lack of technological and financial resources which can lead not only to problems in their ability to source technology but also in their capability to absorb it into their organisation and diffuse it into their industrial sector (Jones-Evans, 1998).
The objectives of this chapter are threefold: first, to investigate technology diffusion (Brooksbank et al, 2001) in the form of new or improved technology through formal and informal networks enabling learning by interacting; second, to develop a model of technology diffusion including external sources, channels of technology transfer, and mechanisms involved in the transfer of technology into the innovative small business; and third, to relate the model to “best practice” and to note situations where “low activity” can be improved. Finally, the implications for policy relevant to technology and entrepreneurship arising from the model of technology diffusion are investigated and conclusions drawn.
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Innovation and Small Business: Volume I
Technology Diffusion
Since there is a time dimension involved in the study of the diffusion of technology into small businesses, similar to other investigations of innovation, theories based on these studies will tend to lag behind the
“best” current practices. All models of technology diffusion, including refined models such as the Bass Norton model, are a simplification of reality (Islam and Meade, 1997) and, therefore, have a measured influence upon policy. One theoretical model that has informed policies is the Centre Periphery Model (Schon, 1971) which rests on three basic assumptions -
i) the technology to be diffused exists prior to its diffusion,
ii) technology diffusion takes place from the source outwards to small businesses, and
iii) the support of technology diffusion involves incentives, provision of resources and training.
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Technology Diffusion
This model is shown in Figure 4.1.
Small business
Small business
Small business
EXTERNAL
SOURCE
Small business
Small business
Figure 4.1 Centre-Periphery Model
By applying the Centre-Periphery Model to Technology Transfer Network Theory it is possible to
construct what can be described as the “Hub and spoke” or “Star” network. This is a simple construct that can be used as a building block for more intricate networks. Diffusion will take place from the source of the technology through channels by a “diffuser”, using a transfer mechanism, to the small firm. The effectiveness of the system will depend upon the resources available to the external source to enable the transfer, the efficiency of the diffuser and the mechanism involved, and the ability of the small company to acquire technology. The scope of the system will vary directly with the level of technology and the flow of information.
Technology Diffusion
When a new technique has been adopted the speed at which other small businesses adopt may differ
widely. This leads to what can be called the rate of diffusion (imitation). The rate of diffusion will be faster, the greater the improvement over existing technology and, the lower the cost of the technology in general (Roy and Cross, 1975). Using the definition of Bradley, et al (1995) technology diffusion can be defined as the spread of a new technique from one small firm to another (ìnter-firm diffusion’) (Stoneman and Karshenas, 1993). The two principal types of technology diffusion are “disembodied” diffusion (the transmission of knowledge and technical expertise) and “embodied” diffusion (the introduction into
production processes of machinery, equipment and components incorporating new technology)
(Papaconstantinou, Sakurai and Wyckoff, 1995). Research spillovers are the means by which new
knowledge or technology developed by one firm become potentially available to others and the absorptive capacity of the receiving firms will determine the extent to which the technology is incorporated.
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Innovation and Small Business: Volume I
Technology Diffusion
The time pattern of adoption and the speed at which it takes place are distinct happenings. The exploration time period when implementing an innovation can provide imitators with a “window of opportunity” to proliferate (Jayanthi, 1998). Empirical studies suggest that the adoption of a new technology follows a bell-shaped, or normal, distribution curve (Norris and Vaizey, 1973). By plotting cumulatively this shows the number of small businesses who have adopted a new technology in any given year, and the
distribution will give an `S’- shaped curve. (It was Gabriel Tarde who in the Laws of Imitations, 1903, proposed that adoptions plotted against time assume a normal distribution, or if plotted cumulatively assume thèS’-shaped curve.) (Baker, 1976; Pijpers et al, 2002; UoT, 2004) An `S’-shaped distribution, not necessarily derived from a normal distribution, shows the spread of most new technology. There are two general reasons for the occurrence of this distribution.
(i) The diffusion process for small businesses is a learning process.
Small businesses who are potential users have to become aware of the technology and then to attempt to evaluate it. Consequently they may use the technology on a trial basis. The learning process takes place at this stage. Information about the technology has to be disseminated, and as it is adopted by other small firms, or by the small company on an experimental basis the information becomes more reliable. The
importance of accumulated knowledge and expertise is an important factor determining whether firms are likely to adopt new technology or to act as sources of innovation (Gurisatti, Soli and Tattara, 1997).
`Bugs’ will be overcome, which will in turn reduce the risk of adopting the technology. The concept of the individual small business learning curve can be extended to a network group of small firms where
experience with a new technology increases as each successive small company adopts the new technology.
As a result, the distribution of small businesses adopting a technology might be expected to yield a normal curve.
(ii) An interaction effect occurs for small businesses.
When only a small number of small businesses have adopted a technology, there are a small number of diffusers who can generate information on the technology and from whom the technological idea can
spread. Diffusion rates at this point are low. When the number using the technology increases the
“information base” broadens and because there is still a considerable number of small firms who have not adopted the new technology the rate of diffusion increases. When there is a large proportion of small companies using the technology the number of potential small businesses still remaining becomes small.
The remaining small firms will be resistant to change and there will be a slow down in the cumulative number of small companies using the new technology. This will yield an `S’-shaped curve. The first
formal study of diffusion was the spread of hybrid corn (Grilliches, 1960). The adoption rate in different states in the USA was studied and it was found that there were significant differences between states in the rate of hybrid corn adoption. Logistic growth curves were fitted by Grilliches to his data and the
parameters found from the curves for the different states showed wide variations.
Another formal study of the rate of diffusion was carried out by Mansfield who studied the rate of
diffusion of twelve innovations in four industries - coal, iron and steel, brewing and rail (Mansfield, 1961, 1968). Although small firms were not included in the analysis, for medium-sized and large firms in most cases, the spread of innovations over time approximated thèS’-shaped curve. According to Mansfield the spread of innovations is best described by a logistic curve.
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Innovation and Small Business: Volume I
Technology Diffusion
Despite the shape of the curve for technology diffusion appearing `S’-shaped, there will be differences in the speed at which technology is diffused and the length of the diffusion process. Both within and between industries there will be considerable variations in the rate of the diffusion of technology between small businesses.
Important factors which appear to affect the rate of diffusion (speed at which a new technology is accepted) are the characteristics of the small business and the characteristics of the technology itself. Early work on the categories of adopters found that further to adoption following a normal distribution curve the distribution could be used to show the categories of adopters (Rogers, 1962). Table 4.1 shows the
categories of adopters with the majority of adopters lying between the mean and the mean minus/plus the standard deviation on the normal distribution curve.
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Table 4.1
The Categories of Adopters
Categories
Innovators
Early Early
Late
Laggards
Adopters Majority Majority
Number of
2.5%
13.5%
34%
34%
16%
Adopters
x - 2
x -
x
x +
Years
The categories of adopters can be described as follows:
Innovative small businesses are those who want to explore new technologies. They will have relationships with other firms in their network, and with suppliers and customers.
Early adopters will be those who will adopt new technology if it is to their advantage. Since they will act as òpinion leaders’ their influence will be greater than innovative small businesses.
The early majority will be intentional while the late majority will be sceptical and will adopt when the technology has diffused.
Last, the laggards will be so late adopting a new technology that it will have been superseded.
The categories of adopters show that small businesses which adopt an innovation independently are
innovators (Tassopoulos and Papachroni, 1998). Early research studies aimed at defining the
characteristics of adopters found that early adopters relied to a greater extent on impersonal sources of information from wider and more sources (Rogers, 1962). They used sources in close contact with the origin of new ideas including technical journals. Small firms that are early adopters will tend to be
“technically progressive” and will be close to the best that can be achieved in the practice of applying technology (Carter and Williams, 1957). On this assumption a progressive small company will take a wide range of authoritative technical journals, will have a variety of contacts with sources of technology including similar small businesses, and will assess ideas from these sources. It is expected that
communication within the small firm will be well organised and co-ordinated and there will be a
willingness to share knowledge with other small companies in its network. A progressive small business will set its standards by reference to best practice in other small firms.
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Innovation and Small Business: Volume I
Technology Diffusion
The speed of diffusion will also be faster the greater the awareness of small businesses to the advantages of adopting a new technology. The process of communication will be important here as well as the ability of small firms to assess the merits of the technological advance. A small company is more likely to adopt a new technology as it diffuses due to being under increasing competitive pressure to do so, through the technology becoming more attractive, and as a result of information about the technology being broadcast from an increasing base (Green and Morphet, 1975).
Technology Transfer Networks
Technology transfer networks are of particular importance to small businesses with little in-house
resources and experience to explore the potential of new technologies. Small firms usually lack awareness to the value of technology transfer, are diffident to enabling services, and therefore rely on co-operation with others. Two basic mechanisms available to small companies are technology exchange (technology
passed from one small business to another) and technology exploitation (technology transferred to a small firm from an external source).
Technology transfer networks enable small business to reach a common understanding regarding new
technologies quickly. Important aspects of technology transfer networks are the type and size of the network. Whereas, small networks appear more efficient, since communications are easy and network
dynamics controllable, large networks benefit from a greater pool of resources. There are four principal types of networks. The “star” network has already been reported. A “nodal linkage” network involves small firms on an equal footing and is not suitable for those businesses with different levels of experience.
“Ad hoc” or “informal” networks are those without a formal structure where small companies intimately know each other concentrating communication where required. These tend to be mature networks, but are not well suited for heterogeneous groupings, or those with little commonality between small businesses.
“Regional” networks are the most complex type consisting of multi-tiered structures linking local
networks. These are suitable for heterogeneous small firms. The descriptions of these four types of network are exemplars in their purist form. Networks adapt to changing internal and external factors and evolve from one (centre-periphery) to another (multi-tiered). Although co-operation with other technology transfer networks provides the possibility of accessing a wider contact base it carries with it some competitive risk.
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Technology Diffusion
A Model of Technology Diffusion
A model of the diffusion of technology into small businesses can be described as innovation (supply) from the source of technology (origins) and diffusion (demand) to the small firm (destination). The model can be expressed concisely in algebraic form:
Origins
i = 1, 2, … m
Destinations
j = 1, 2, … n
Supply at each origin
a i
Demand at each destination
b j
Constraint; supply = demand ∑ a i = ∑ b j
In order to find a solution we must specify the variable x i j as the unit(s) of technology transferred from origin i to destination j over time t.
All supply
∑ x i j = a i
j = 1, 2 … n
j
All demand
∑ x i j = b j
i = 1, 2 … m
i
The diffusion of technology D can be expressed:
m n
D = [ ] x i j
i=1 j=1
where i = 1, 2, … m and j = 1, 2, … n
The rate of diffusion of a new technology can be likened to waves of adoption involving distinct time packages. This is illustrated in Table 4.2.
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Innovation and Small Business: Volume I
Technology Diffusion
Table 4.2
The Rate of Diffusion
Innovators
Imitators
Waves of
1st Wave
2nd Wave
3rd Wave
4th Wave
5th Wave
adoption
Categories
Innovators
Early
Early
Late
Laggards
Adopters
Majority Majority
Number of
2.5%
13.5%
34%
34%
16%
Adopters
Time
Period 1
Period 2
Period 3
Period 4
Period 5
Periods
m
n
n
n
n
Diffusion =
x i j
x i j
x i j
x i j
x i j
for each
i=1
j=1
j=1
j=1
j=1
period
1
2
3
4
5
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Innovation and Small Business: Volume I
Technology Diffusion
The rate of diffusion (R) can be calculated according to time (t) (number of years) as follows:
m n
[ ] x i j
i=1 j=1
R =
t
where i = 1, 2, … m and j = 1, 2, … n
This equation is a temporal model (Thomas et al, 2001) of technology diffusion which measures the
speeds of diffusion (or rates of technology transfer) (Bradley, McErlean, Kirke, 1995).
Technology transfer is an active process whereby technology is carried across the border of two or more social entities (the external source and the small business), and technology transfer channels are the link between the entities (in which various technology transfer mechanisms are activated) (Autio and
Laamanen, 1995). A technology transfer mechanism is defined as any specific form of interaction between entities during which technology is transferred (Autio and Laamanen, 1995). The ability to establish external linkages is of critical importance to small firms and a critical mass of small company users will spread the usage and acceptance of the technology (Jain, 1997). The success or uptake of technology depends on how successful the performed community of (implied or ideal) users match the characteristics of actual users (Woolgar, Vaux, Gomes, Ezingeard and Grieve, 1998). Success can be achieved by
“configuring the user”. Further to this Malecki has stated that “as new technology and products are learned, acquired, evaluated, and improved upon, a firm or region comes to know about best-practice
technology …” (Malecki, 1991, p.122). Laranja calls these “cumulative processes of learning” (Laranja, 1994, p.173).
“Best practice”
Technology transfer networks are one of the best forums for small businesses to learn from each other, to exchange experiences, and to diffuse technology. The typical areas where the benefits of “best practice”
can be found are technology transfer skills (determining a small firm’s needs by auditing and drawing-up agreements and contracts), technological expertise and know-how (including standards and regulatory issues), service provision (assembling the provision of services), and management and organisation
(public relations) (Commission of the European Communities, 1998).
Networks are usually segmented by geographical region, industry sector or by technology and they can work with a mixed sector-technology focus. The danger with specialisation is that it carries the
disadvantage that eventually the potential market will be exhausted. It is possible to overcome this by anticipating and looking for opportunities in complementary technology areas.
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Innovation and Small Business: Volume I
Technology Diffusion
“Best practice” procedures for the diffusion of technology within networks usually include minimum