A Techno-Institutional Analysis of Energy Systems in Transition

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A Techno
Institutional Analysis of Energy Systems in Transition

The Dutch Case of Biomass Gasification


TEER 2005 Jyväskylä, Finland

Roald Suurs (MSc)
, Simona Negro (MSc)
, Dr. Marko Hekkert

Department of Innovation Studies

ernicus Institute for Sustainable Development and Innovation

University of Utrecht

PO box
80125, NL
3508 TC

Utrecht, Heidelberglaan 2

Tel: +31 (0)30 2532782 / 1625

Fax: +31 (0)30 2532746




The abstract and paper have been written with equal contribution by both authors.


Once the awareness about the negative effects of fossil energy consumption increased, progress was
made with developing renewable energy technologies. However, despite the t
echnical potential and
the positive long
term opportunities for industry, the developments faded when compared to the
continuing growth of the conventional energy sector. The main reason for this, is the dual complexity
that resides in the energy system, b
eing a large technological system (LTS):


Besides technological components, any LTS consists of various interacting actors; this
dynamic network of actors constitutes a so
called Technology Specific Innovation System
(TSIS). The activities within the TSIS,

determine the development of new technology,
however these are strongly conditioned by the rules and routines, or

enable and constrain their actions. Hence, LTS are techno
institutional systems and
technological change implies institutio
nal change, i.e. a change within the TSIS.


Within LTS, innovation often has systemic effects in a so
called pleiotropic sense. This
implies that a mutation in one part of the system (some institution or technology), has
effects on the functionality of (mu
ltiple) other parts of the system. The energy system
transition can be regarded as the redesign of a complex system. Intervention in the
workings of this system requires insight in its pleiotropy. This holds for both, institutional
changes and technical ch

Institutions constitute the Innovation System (IS) structure. Technological innovation depends on the
IS structure, but on the other hand, the IS structure also depends on technology. In a dynamic sense,
it can be said that the IS co
evolves with t
he technology it brings forth. As a result, the IS around a
particular technology has features specific to that technology and its state of development. Policy
makers should take into account these features.

The main purpose of our project is to develop a

theoretical understanding on the occurrence of
technological innovations, that could support a transition to sustainability, within the energy system, by
studying and comparing the co
evolutionary dynamics (longitudinal) of technology and institutions in
several cases. Within this paper we will present our first case study: the technological trajectory of
biomass gasification in The Netherlands.


With respect to theory, this paper draws from institutional theory and IS studies; more specifically, w
depart from the framework of Technology Specific Innovation Systems
(Carlsson and Stankiewicz
. The TSIS approach should enable us to understand complex technologica
l change, within a
specific domain, in terms of institutional structure. After all, the scope of the system is limited
compared to a national innovation system. Still, within the traditional approach, institutional structure
itself is often regarded as som
ething rigid. As a result, the IS approach tends to be static rendering it
unfit to deal with techno
institutional systems in transition.

In order to allow for a more dynamic approach, it is fruitful to focus the analysis on
, in
addition to inst
itutions only. Here, we follow up on recent work by Jacobsson
, Johnson
and Edquist
(2001; 2004)
, who developed the concept of ‘
functions of innovation systems

. Functions,
in this sense, should be regarded as the

within the IS that contribute to its goal. The goal of
an IS, is defined as ‘to develop, diffuse and utilise innovations’
(Carlsson and Stankiewicz 1991)
. A
main assumption here, is that for different IS, the functions vary less across IS, than do the actors and
institutions that make up the system structure
(Edquist 2004)

Functions enable us to:


to guide our search for relevant variable
s, as a heuristic tool;


to systematically analyse types of IS activities in terms of performance;


to study these activities and their complex interrelatedness in the course of history;


to deliver a clear set of policy targets, related to institutiona
l AND technological features.

The set of functions as applied, was distilled from a huge collection of literature on IS by Johnson

and Rickne
; a variation on their li
sts is given below. Currently we are still working on the
composition of a definitive version; insights from empirical work are crucial in this respect.

Methodology and Data: Sequence Event Analysis

Until now, the research in IS studies tends
to remain unsystematic when it comes to the measurement
and validation of concepts. In order to contribute to the IS framework, we aim to reinforce the
approach with systematic empirical data gathering and analysis. The methodology of the case study
ts of using ‘sequence event analysis’, as applied by Van de Ven et al.

In our case the
sequence event analysis is applied to system level. The procedure can be divided into several steps:


Literature search.

The first step is to carry out a thorough literature search of Dutch periodicals
about renewable energy from 1980 until

2003. All the events are chronologically listed in a
database. Moreover, an overview of the most relevant institutions is made where the focus will
be on formal government regulation.


Database classification.

The events within the database are then classi
fied into event


Allocation to functions.

Once, the events are ordered into their corresponding event
categories, they are allocated to the functions. Each function is operationalised in terms of a
set of indicators that allows a coherent alloca
tion of the event categories to the function.


Database analysis.

The database is evaluated and analysed by giving a complete description
of the functions, the institutions and the relations between them.


Triangulation of results.

The results are verified a
nd completed by doing interviews with
experts of the field.

Expected Results

We expect that the ‘functions of innovation systems approach’ enables us to gain insight in the
dynamics of complex technological systems. The transition process of biomass gasif
ication will be
described and explained in terms of functional interrelatedness and function fulfilment through time.
The functions will also be related to the (technology) specific institutions, as well as the actors in the
IS. This increases insight in t
he pleiotropic complexity of the IS and creates a starting point for
systemic policy design. After having studied multiple cases in the same way, we expect to identify a
set of functions that needs to be present in any IS to perform in an effective manner.


Carlsson, B., and R. Stankiewicz. 1991. On the nature, function and composition of
technological systems.
Journal of Evolutionary Economics

1 (2):93

Edquist, C. 2001. The Systems of Innovation Approach and Innovation P
olicy: An Account of
he State of the Art. Paper read at Paper prepared for the Druid conference, at Aalborg.

. 2004. The Systemic Nature of Innovation. In
Oxford Handbook of Innovation
, edited
by J. Fagerberg, D. Mowery and R. Nelson. New York: Oxford U
niversity Press.

Jacobsson, S., and A. Johnson. 2000. The Diffusion of Renewable Energy Technology: An
Analytical Framework and Key Issues for Research.
Energy Policy

28 (9):625

Johnson, A. 2001. Functions in Innovation System Approaches. Paper read a
t Nelson and
Winter Conference, juni 2001, at Aalborg, Denmark.

Rickne, A. 2001. Assessing the Functionality of an Innovation System. Paper read at Paper
prepared for the Druid conference, at Aalborg.

Van de Ven, A.H., D.E. Polley, R. Garud, and S. Venkata
The Innovation
: Oxford University Press.

Functions List Utrecht (FLU)


Creation of Technological Knowledge


Exchange of Information through Networking


Articulation of Demand;


Regulation and Formation of Markets;


Supply of Resources for Innovation;


Prioritizing the Allocation of Public and Private Resources;


Development of Advocacy Coalitions for Processes of Change.