Dynamics of Technological Innovation Systems – The case of biomass energy

Introduction

The starting point of this thesis is the problem that the current energy system is largely fossil fuel based leading to severe negative environmental problems. Besides the negative environmental impacts the energy system is perfectly optimised to satisfy society’s needs. This makes that society is ‘locked in’ the current way of producing and consuming energy. The consequence is that the breakthrough process of renewable energies is slow and tedious.

The aim of this thesis is to contribute to insights necessary to accelerate the diffusion of renewable energy by identifying the underlying factors that induce or block the development, diffusion, and implementation of renewable energies. Biomass energy technologies in the Netherlands and Germany will be used as empirical case studies.

To identify the relevant factors, this thesis starts from the perspective that technological success is not only determined by economic and technical characteristics but also by the social system in which a technology – and the knowledge involved – is developed and diffused or rejected. Until now most of the studies are devoted to the techno-economic analysis of renewable energy technologies, however in this thesis the focus will be on the analysis of the social system. To do so, the recently developed ‘Innovation Systems’ perspective will be applied to analyse the evolution of biomass technologies. More specifically the Technological Innovation System (TIS) approach is applied as unit of analysis.

The TIS approach focuses on all actors, networks, organisations and institutions that influence the development, diffusion, rejection or implementation of a particular technology. Recently the TIS approach has developed into a very dynamic approach by not only focusing on the structure of the system (actors, networks and institutions) but also on the key processes that take place within the system and contribute to the build up of a TIS and thereby to the successful development and diffusion of the emerging technology. These key processes are labelled as Functions of Innovation Systems (or System Functions) since these are processes that the TIS needs to fulfil in order to perform well. Just like the function of a car is to deliver mobility, the function of a TIS is to generate a number of key processes (System Functions) in order to propel the development of new technology.
Recently a number of studies have applied the System Functions approach, which has led to a number of System Functions lists in the literature. This creates unanimity about which System Functions are relevant. This thesis uses the recently developed list of System Functions at Utrecht University as stated in Table 1. This leads to the first research question of this thesis: How suitable is the set of System Functions to describe and analyse the dynamics of the TIS?

Functions of Innovation Systems

F1: Entrepreneurial Activities F2: Knowledge Development (learning) F3: Knowledge Diffusion through Networks F4: Guidance of the Search F5: Market Formation F6: Resources Mobilisation F7: Counteract resistance to change

For a technology to develop successfully, the individual System Functions need to be fulfilled. A powerful way of accelerating the individual System Functions is a process of interaction and reinforcement that causes a built-up of virtuous cycles. Literature states that these virtuous cycles are necessary to propel the technology from a fragile state of early development to a robust state of diffusion. Insights in what type of interaction (functional) patterns take place and how exactly these patterns fluctuate over time promise to provide a deeper insight in the dynamics and barriers that hamper technological change. Therefore this thesis aims to answer the second research question: What do functional patterns tell us about the dynamics of Biomass Innovation Systems?

The methodology applied is based on the approach by Van de Ven and colleagues in the Minnesota project to study the dynamics of innovation projects. The approach is called process study and is based on event analysis. This consists of retrieving events from literature, observations, and interviews that contribute to the change and development of processes, in this case the development, diffusion and implementation of biomass energy technologies. In our case we aim to adapt the methodology that was used to study one innovation project to analysing a complete Innovation System. This leads to the third research question of this thesis: How can the process study approach be applied in order to analyse System Functions and the dynamics of Technological Innovation Systems?

To recapitulate, by applying the TIS approach the development, diffusion and implementation of a technology is analysed where the System Functions approach is applied to identify the underlying dynamics that hamper or incite the process of technological change. Furthermore the methodology applied is an event based longitudinal process study that allows graphical representation of the individual System Functions and a narrative that provides insights in the development and change process within the TIS studied.

The final aim of this thesis is to make a first step in translating the findings to handholds for policy design that aims to accelerate the diffusion of biomass energy technologies. The fourth and final research question is therefore: What can we learn from the approach applied and findings obtained, in terms of options to accelerate the diffusion of biomass in particular and renewable energy in general?

Results

The case of biomass digestion in the Netherlands, 1980-2004
For biomass digestion in the Netherlands an irregular functional pattern is observed, as positive and negative System Functions seem to take alternative turns every so many years. In the period 1974-1987 only System Functions such as Knowledge Development (F2) and Entrepreneurial Activities (F1) occur, however no other System Functions are triggered. In the following years, negative guidance against biomass digestion (-F4) hinders any market formation (-F5), investments (-F6) or lobbies to occur (-F7). Only in 1989 a cautious built-up of System Functions occurs when guidance (F4) stimulates knowledge creation and diffusion (F2 and F3) of biomass digestion, resulting in the set up of several plants (F1). However some System Functions remain unfulfilled, such as Market Formation (-F5) and Resource Mobilisation (-F6). These negatively fulfilled System Functions serve as nourishing ground for a vicious cycle to take off in 1995. The trigger is negative guidance (-F4) with respect to biomass digestion, leading to a lack of resources (-F6), forcing several plants to shut down (-F1). This results that only 4 biomass digestion plants are left over in the Netherlands. The only activities that continue are lobby activities (F7), which seem to be heard by the government (F4), when co-digestion is partially permitted several years later. In addition, the government wants to increase the share of green electricity (F4) and introduces a feed-in tariff system (F5). Finally also biomass digestion can profit from this market formation (F5) and an increase of biomass digestion plants (about 18 plants in 2005) occurs in the following years (F1). This TIS for biomass digestion is evaluated as a poorly functioning system. During long periods no continuous built up of System Functions occurs. Some System Functions are fulfilled but they do not interact with each other as to reinforce each other and trigger other System Functions. This provides a scattered functional pattern that easily collapses if negative System Functions reinforce each other instead.

The case of biomass digestion in Germany 1990-2004
In the case of biomass digestion in Germany, positive interactions between the System Functions lead to the built-up of System Functions. Guidance by the government (F4) triggers entrepreneurs to create and diffuse knowledge (F2, F3), which results in the set up of the first digestion plants (F1). Then lobby activities (F7) start to improve institutional conditions. Shortly after the government increases the feed-in rates (F4). This leads to a market formation (F5), which results in an increase of plants constructed (F1). These activities trigger also other System Functions such as Resource Mobilisation (F6) and Knowledge Diffusion (F3) to be fulfilled, resulting that all System Functions are fulfilled, interact and reinforce each other. Here, a virtuous cycle occurs. This virtuous cycle overcomes a temporary vicious cycles, where negative guidance (-F4) results in a subsidy budget cut (-F6), which then leads to a decrease of projects (-F1). However, this vicious cycle is quickly broken by the provision of financial resources (F6) by another Ministry (F4) and the construction of plants is continued (F1). Then lobby activities (F7) ask for better institutional conditions (F4), and in 2004 better feed-in tariffs are introduced (F5). The feed-in tariffs lead to a market formation, which leads to the final breakthrough of biomass digestion in Germany (i.e. about 1700 plants in 2004) (F1).
This development and diffusion of the technology occurs in a time span of 10 years, where continuous interactions of System Functions reinforce each other as to build-up a virtuous cycle. The built-up is strong enough to overcome a vicious cycle, so that the virtuous cycle continues and a market is formed, which leads to the breakthrough of biomass digestion.
This case shows that technology development is successful when the System Functions are fulfilled, reinforcing each other.
However, some critics may say that the case of Germany is a big subsidy story, where the success is attributed to the large amounts of money provided by the government, rather then the System Functions fulfilment. Yet, our analysis clearly shows that the money and the institutional alignment were not in place beforehand, but that due to the build up of System Functions such as Entrepreneurial Activities and Advocacy Coalitions that provided a reliable technology and lobbied for better institutional conditions and financial resources respectively, the alignment occurred gradually over several years. Thus, this shows that the build up of a well functioning Innovation System around a technology plays a crucial role for its successful diffusion, as well as favourable technical and economic aspects.

The case of biomass gasification in the Netherlands, 1980-2004
In the case of biomass gasification first a build up of several System Functions occurs in the period of 1990-1998 due to very high expectations around biomass gasification, such as Guidance of the Search (F4) that trigger Knowledge Creation (F2), Knowledge Diffusion (F3), Resource Mobilisation (F6) and Entrepreneurial activities (F1) to occur. However in 1998 the liberalisation of the energy market triggers a vicious cycle, where negative guidance (-F4) results in the closure of several projects (-F1), less knowledge creation (-F2), less resources (-F6), less research (-F6), negative expectations (-F4) and finally the discontinuation of Entrepreneurial Activities (-F1). These negative events reinforce each other and result that no more activities are carried out anymore, so that the system collapses within a couple of years. Since then biomass gasification is still not diffused on large-scale.
The main blocking mechanism is the lack of guidance by the government to provide clear and consistent policies (-F4) and the lack of a market niche (-F5), where the actors could have experimented and built-up experience with the technology. At the beginning the expectations are high that biomass gasification will be the solution, however due to unsolved technical problems and inconsistent guidance by the government (-F4), the opinions change drastically as the energy market is liberalised. The liberalisation comes too early for gasification, as it still is an unreliable and expensive technology. Besides the unfortunate timing of the liberalisation, no additional time and space is allowed for trial and error, as to solve the technical problems and investors and government think the technology is unfit and unworthy for further support (-F7), which results in the collapse of the Biomass Gasification Innovation System.

The case of biomass combustion in the Netherlands, 1980-2004
For biomass combustion most of the System Functions are fulfilled and the TIS is built up so far as to be ready to go, however the last crucial trigger is missing to bring about breakthrough. Between 1990-1998 the build-up of a virtuous cycle occurs where guidance (F4) leads to research and knowledge creation (F2), and positive results lead to entrepreneurial activities (F1). However, between 1998-2001 no additional activities occur, nonetheless that biomass combustion is a proven and reliable renewable energy option. This results from the lack of market formation (-F5). As a matter of fact there is a flaw in the tax exemption system that favours the import of green electricity rather than producing it in the Netherlands. However, in 2003, the government introduces a feed-in tariff system (F4) that incites the formation of a market (F5), which directly results in a set up of projects and plants (F1). However in 2005 and 2006 the government decides that new biomass plants are not entitled to feed-in rates, which results that any new and future plans for projects are on hold (-F1). From this case we see, that nonetheless most of the System Functions are fulfilled and that the technology is proven and reliable, as long as there is no secure market formation, the technology will not break through.

The case of biomass co-firing in the Netherlands, 1990-2004
The case of biomass co-firing is somewhat different as it has a head start in comparison to the other biomass case studies. Co-firing means that biomass is added as fuel to existing coal fired power plants. For biomass digestion, gasification and combustion the Innovation System has to be built up from scratch. In the case of biomass co-firing the actors, (coal fired power) plants and infrastructures are already partly in place, being part of the incumbent system. Nonetheless, the dynamics and sequence of events are interesting and provide some lessons for the other case studies. The sequence of events starts with guidance of the government and the energy companies of the incumbent system (F4) to reduce CO2 emissions, which leads to knowledge development (F2). Co-firing is a very promising option and favourable guidance (F4) and resources (F6) are provided and as a result entrepreneurial activities are set up (F1). Around 2000 there is a temporary vicious cycle, as the institutional conditions are not fully aligned with the needs of the technology and the entrepreneurs (-F4), which leads to a delay in projects (-F1). However due to lobby activities by the energy companies (F7) agreements with the government are finalised (F4), which result that favourable institutional conditions are provided and a market is formed (F5). This is the final trigger to implement co-firing in all coal plants (F1). This case shows that nonetheless the so-called head start, where most of the structural elements were in place, the System Functions need to be fulfilled and that also in this case a Technological Innovation System has to build up around the particular technology before it is successfully diffused and implemented. The crucial factor that leads to the final breakthrough of the technology is also in this case the formation of a market.

Conclusions

The process study was applied in an approach that proved to be a good compromise between completeness and workability with respect to the amount of data collected. The events are mainly collected from archives consisting of newspapers, magazines, and reports etc. from 1980-2004. The events are then ordered into a database and allocated by using a classification scheme to the individual System Functions. From the database, graphical patterns (the sum of events per year per System Function) that represent the individual fulfilment over the years, and a narrative, that illustrates the circumstances that result in the twist and turns of the individual System Functions as well as the interactions between them, are provided. In addition several validation steps (i.e. interviews with experts and intercoder reliability) were taken throughout the data collection and analysis to reduce bias and check on completeness of data. This method is described in detail in Chapter 3 and provides the answer to this research question: How can the process study approach be applied in order to analyse System Functions and the dynamics of Technological Innovation Systems?

The System Functions approach helped to structure the vast amount of data and by graphical representations, to highlight crucial breaking points within the narrative. The amount and nature of data collected showed that no System Function was irrelevant (i.e. events were allocated to each System Function) and that no events that could represent an additional System Function were found (i.e. events that could not be allocated to System Function were doubles, external factors or technical or general information categorised as context). Thus, the list of seven System Functions proved to be a good starting point for creating insights in the system dynamics. This provides an answer to the research question: How suitable is the set of System Functions to describe and analyse the dynamics of the TIS?

The following findings provide an answer to the third research question: What do functional patterns tell us about the dynamics of Biomass Innovation Systems?
The results from the case studies showed that several functional patterns occurred for the Biomass Innovation Systems. These can be divided into virtuous and vicious cycles.
Virtuous cycles occur when several System Functions are fulfilled, interact and reinforce each other and therefore trigger other System Functions to be fulfilled as well. In the case of biomass digestion in Germany and biomass co-firing in the Netherlands, a typical sequence of a virtuous cycle start with the positive fulfilment of Guidance of the Search (F4), with respect to clear and consistent regulations, which triggers entrepreneurial activities (F1) to occur by setting up projects and improving the technology. In addition entrepreneurs lobby (F7) for better regulations and feed-in tariffs. Once these tariffs are introduced (F4), a market is formed (F5) and the number of plants constructed increases rapidly (F1).
On the other hand, when vicious cycles occur either a negative fulfilment of the System Functions occur which results that the System Functions interact and reinforce each other negatively, or that some System Functions are not fulfilled at all and are lacking. In the case of biomass digestion the System Functions are not continuously fulfilled and do not manage to build-up. The main reason is the inconsistent and negative guidance (-F4) that hampers any development or diffusion of biomass digestion technology (-F2, -F1). In addition a lack of resources (-F6) and market formation (-F5) give entrepreneurs a hard time to further develop the technology or to lobby for better conditions. The lack and negative fulfilment of the System Functions results that the diffusion is still small after twenty years, i.e. only about four digestion plants are running in 2004.
For biomass gasification a virtuous cycle turns within a few years into a vicious cycle that makes the biomass gasification innovation system collapse. Due to the liberalisation of the energy market in 1998, most of the System Functions are no longer fulfilled and all activities stop. Mainly the lack of guidance (-F4), resources (-F6) and market formation (-F5) are responsible for the lack in entrepreneurial activities (-F1), so that hardly anymore activities occur after 2000.
Finally for biomass combustion a built-up of System Functions occurs, however the final trigger for breakthrough is missing. As long as no market formation occurs (-F5), only a few small-scale plants are implemented. Once the feed-in tariff system is introduced (F5) an increase of plants and size are observed (F1).

Thus in addition to the necessity of System Function to interact with each other for a built up to occur, two System Functions is identified that play a crucial role as final trigger for implementation. The influence of Guidance of the Search (F4) is significant in triggering or hampering the further fulfilment of other System Functions. When guidance is negative or lacking, most of the other System Functions are not fulfilled or collapse (see biomass digestion and gasification in the Netherlands), whereas the contrary is true when positive or continuous guidance is provided (biomass co-firing in the Netherlands and biomass digestion in Germany).

Another System Function that is revealed as very critical by the case studies is System Function 5: Market Formation, which shows to be the final trigger that leads to the breakthrough of a technology. Due to the lack of a market, the Biomass Innovation Systems often did not manage to move from a development phase to a breakthrough phase.

Finally, the last question is answered by the following insights.
RQ 4: What can we learn from the approach applied and findings obtained, in terms of options to accelerate the diffusion of biomass in particular and renewable energy in general? The lessons learned are that biomass technologies go through a long-term trajectory (10-30 years) of development, diffusion and implementation. This asks from a government to develop long-term policy goals and to stick to these policies. In other words, what is needed is a reliable and visionary government. Innovation is a time-consuming search process with many risks. Not taking these dimensions of innovation into account is a guarantee for failure.
From the biomass cases studied it becomes clear that current policy making too often has a too short time horizon. Within long-term policies ample room should be provided for learning and experimenting for technological problems to be resolved, where System Functions need to contribute to this process to occur. This includes providing room for the necessary competences of the actors to develop. Furthermore, this also accounts for policy makers that till now too often (implicitly or explicitly) act from a linear model perspective and should acquire the competences necessary to develop more systemic policies.
Based on the analyses of the systems under development, government should in particular focus on removing barriers hampering virtuous cycles (i.e. inconsistent, contradictory and unstable regulations) and to develop and stimulate the further development of already existing virtuous cycles (i.e. market formation, stable and continuous guidance). Thus, the fulfilment of System Functions such as Guidance of the Search and Market Formation play a crucial role in this context.
In addition entrepreneurs should also take a more active role and realise that they are not innovating in isolation but in the context of a system. They should get involved in processes of guidance, facilitate knowledge exchange and join forces to strengthen their lobby activities. In addition they should avoid competition among each other with respect to one technology and between technologies. Finally, they should turn into an actor that government cannot ignore any longer.