05_Diffusion of technology / innovations

Diffusion is the process by which an innovation is communicated through certain channels over time among the members of a social system.

Technological diffusion is the process by which innovations (be they new products, new processes or new management methods) spread within and across economies

Conventional diffusion analysis:

• focuses more on generic technologies, rather than individual generations of technologies

• considers the technologies as improving over time

Measurement problem: what can be considered as a new technology, and what is just an improved technology (e.g. mobile phones, computers)

1. Diffusion of new technology takes time, often a long time, esp. capital intensive technologies

2. Timing and rate of adoption differs among (heterogeneous) decision-makers / entities (notion of representative agent not very useful)

3. Diffusion paths (of successful innovations) often follow a sigmoid path

• Common fallacy: In public policy-making and even academic circles associates technological change with R&D

• Benefits of new technologies (e.g. higher productivity, competitive advantage, economic welfare gains) can be only reaped if they actually diffuse in the market

• Study of technological diffusion = study of spread of use and / or ownership of new technology

• Innovation diffusion phenomena have been studied in many different research disciplines (e.g. anthropology, geography, marketing)

• J. Schumpeter considered the father of diffusion studies in economics; starting point for modern work are epidemic theories of diffusion (origin: analysis of spread of diseases)

• Delayed response time to information:

  • not all potential adopters are informed immediately about the availability / market introduction of an innovation

• Learning from others:

  • previous product experience plays an important role

• Desire to adapt to social norms:

  • trend-following as classical example

• Actors are heterogeneous

• Heterogeneity in society is an important factor for explaining the long process of diffusion phenomena

• Heterogeneity of actors often only taken into account to a limited extent in diffusion modeling

2 complementary driving forces (1934)

• Selection

• Imitation

• Competition between ‘innovative’ and ‘traditional’ firms (using old technology)

• Diffusion as the relative market share of the two kinds of firms

• Possibility of traditional firms giving up old technology in favor of new one

• Diffusion as the rate at which adoption occurs

1. Relative advantage (subjective perception, e.g. of economic profitability, increased comfort, social prestige, time and effort saved, and immediacy of rewards)

2. Compatibility (consistency with existing values and social norms, past experiences and needs)

3. Complexity (degree to which an innovation is subjectively perceived to be difficult to understand and use)

4. Trialability (possibility for experimentation on a limited basis)

5. Observability (degree to which the results of an innovation are visible to others

The difference relies on the different character of the related studies:

• Adoption studies: concerned with reasons for adoption at one point in time, or the reasons for time of adoption of individual users

• Diffusion studies: focus on the market behavior of the diffusion process over time – i.e. it is the study of a dynamic, aggregative process over continuous time

1. The presence of an innovation

2. A channel through which communication flows (mass media and/or interpersonal communications

3. Time

4. The social system (a set of interrelated units engaged in joint problem solving to accomplish a common goal)

Depending on the timing of adoption of the technology, these can be divided into early adopters, early majority, late majority, and laggards.

The distribution of adopters on the base of innovativeness follows a normal distribution.

Takeoff time

• Is defined as “the time in the life-cycle of an innovation when it transitions from the introduction stage to the growth stage” (Laciana et al. 2013).

• Mathematically, this point corresponds to the time when the change in the derivative of the proportion of adopters reaches a maximum. It is, therefore, a useful macro-level indicator of the penetration of an innovation.