Energy Policy ] (]]]]) ]]]–]]]
Contents lists available at SciVerse ScienceDirect
Energy Policy
journal homepage: www.elsevier.com/locate/enpol
The structure of uncertainty in future low carbon pathways
Nick Hughes a,n, Neil Strachan b, Robert Gross c
a
b
c
Imperial College Centre for Energy Policy and Technology, Faculty of Natural Sciences, London SW7 2AZ, United Kingdom
University College London, UCL Energy Institute, 14 Upper Woburn Place, London. WC1H 0NN, United Kingdom
Imperial College Centre for Energy Policy and Technology, Faculty of Natural Sciences, London SW7 2AZ, United Kingdom
H I G H L I G H T S
c
c
c
c
c
Aims, uncertainties and challenges of low carbon scenarios/pathways summarized.
Importance of defining actors and describing sociotechnical evolution emphasised.
Categorisation of different kinds of future uncertainties explained.
A framework combining actors, institutions and co-evolving systems presented.
Process for strategically effective low carbon scenarios/pathways presented.
a r t i c l e i n f o
abstract
Article history:
Received 30 September 2011
Accepted 15 April 2012
Low carbon scenario and transition pathway analysis involves the consideration of uncertainties
around future technological and social changes. This paper argues that uncertainty can be better
understood, and the strategic and policy effectiveness of scenarios or pathways thereby improved,
through a systematic categorisation of the different kinds of certain and uncertain elements of which
the future is comprised. To achieve this, this paper makes two novel methodological contributions. First
it proposes a system conceptualisation which is based on a detailed description of the dynamics of the
actors and institutions relevant to the system under study, iteratively linked to a detailed representation of the technological system. Second, it argues that as a result of developing this actor-based low
carbon scenarios approach it is possible to characterise future elements of the system as either predetermined, actor contingent or non-actor contingent. An outline scenario approach is presented, based
on these two contributions. It emerges that the different categories of future element are associated
with different types of uncertainty and each prompt different strategic policy responses. This
categorisation of future elements therefore clarifies the relationship of scenario content to specific
types of policy response, and thus improves the policy tractability of resulting scenarios.
& 2012 Elsevier Ltd. All rights reserved.
Keywords:
Scenarios
Uncertainty
Actors
1. Introduction
Low carbon research and policy analysis entails the consideration of technological and social changes from the short- to the
long-term future. The purpose of thinking in advance about the
future, especially through some form of ‘scenario’ analysis, is in
general to inform and improve the decisions that we take in
respect of that future (Schwartz, 1991; Scearce et al., 2004; Godet,
1987). However, most statements about the future involve some
level of uncertainty. Higher levels of uncertainty about the future
n
Corresponding author. Tel.: þ44 020 7594 9306; fax: þ44 020 7594 9334.
E-mail addresses: [email protected] (N. Hughes),
[email protected] (N. Strachan), [email protected] (R. Gross).
present greater challenges to our abilities to make good strategic
decisions about that future.
A central contention of this paper is that, whilst uncertainty
about the future can never be entirely eliminated, nonetheless
future uncertainty is not homogenous. Rather, any future scenario
is comprised of a range of different elements, each associated
with different kinds of uncertainty. Distinguishing between these
different kinds of future element allows a more structured understanding of future uncertainty, which in turn better supports the
use of scenarios for strategic decision making. A distinction of
particular importance is of those future elements which, though
currently uncertain, can nonetheless be decisively influenced by
wilful actions of identifiable system actors. Key to achieving a
clear delineation of these elements is a scenario process rooted in
actor-dynamics, which can show how purposive actor actions can
contribute to future outcomes.
0301-4215/$ - see front matter & 2012 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.enpol.2012.04.028
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028
2
N. Hughes et al. / Energy Policy ] (]]]]) ]]]–]]]
Thus this paper builds on a recommendation from an earlier
review of low carbon scenarios (Hughes and Strachan, 2010), that
a clearer identification of the activities of system actors within
scenarios will improve their tractability for strategic policy making. This paper combines this recommendation with insights from
literature on sociotechnical transitions relating to the co-evolving
nature of social and technological systems, and institutional
theory, to propose a novel framework for considering the effects
of system actor activities within a sociotechnical system, using
both qualitative and quantitative methodologies. Further, synthesising insights from a range of actor-based scenario approaches,
the paper identifies different categories of future element relevant
to a strategic understanding of low carbon future scenarios. These
two contributions then form the basis of a suggested outline
scenario process.
This outline process has informed the development of pathways
within the Transition Pathways project, the subject of this special
issue. For a more detailed discussion of an example of applying this
process, see Foxon et al. (2012), Foxon (2011). The current paper
focusses on explaining the methodological underpinnings and justification of the proposed process, with reference to relevant literature.
The paper is structured as follows. Section 2 provides the background
to the paper by locating the aims of the Transition Pathways project
in the context of the broader scenario literature. Section 3 describes
limitations of the existing low carbon scenario literature in respect of
actor depiction and treatment of uncertainty. Section 4 returns to the
broader scenarios literature to examine the ways that future uncertainties are conceptualised and categorised in different types of
approaches, finding that ‘actor-based’ scenario approaches achieve a
more structured treatment of uncertainty than ‘trend based’
approaches. Section 5 refers to more recent literature on technological
transitions and sociotechnical scenarios to discuss the challenges of
integrating an actor based scenarios approach with important insights
concerning ‘co-evolutionary’ processes in sociotechnical transitions.
Section 6 brings these various insights together in the form of an
outline low carbon scenario development process which describes a
co-evolutionary sociotechnical system whilst retaining clarity about
key actor actions, thereby achieving policy tractability and a structured treatment of uncertainty. Section 7 summarises the outputs of
this paper and draws conclusions.
2. The purpose of thinking about the future the Transition
Pathways project in context
The Transition Pathways project, towards which the research
reported in this paper has contributed, has the aim of showing
‘how purposeful actions by actors within systems can give rise to
changes in technologies, institutions and infrastructures’, in
bringing about a low carbon electricity system in the UK. This
aim is ‘strongly driven by the desire from policy-makers and
industrial and wider stakeholders for conceptual frameworks that
enable the examination of plausible future pathways in ways that
will inform current decision-making’ (Foxon et al., 2010).
With these intentions, the Transition Pathways project establishes a strong connection to the intentions of practitioners within
the tradition of strategic scenario planning.
As Table 1 shows, there is a strong theme within the scenario
tradition that speculation about the future is not justified as an
activity or pastime in its own right, but should be purposefully
linked to near-term decision making, with the aim of improving
those decisions and thereby contributing to better future outcomes. Reviewing a broad range of past-war scenario exercises,
Hughes (2009a) classifies the kinds of decision making to which
scenarios can contribute as:
Protective decision making — by being aware of possible
future external threats, actors may be able to increase their
robustness against them;
Proactive decision making — by being aware of possible future
opportunities, actors will be better placed to proactively seize
such opportunities to improve their future prospects through
their own actions;
Consensus building — by being aware of how concerted action
by a number of actors may lead to outcomes desirable for all,
actors can create a clear case for action and a basis for building
societal consensus.
The balance between these objectives in any one scenario
exercise is related to the level of agency of the scenario user in the
context of the system under study (Hughes, 2009a). Scenario
users with a low level of influence over the system being explored
by the scenario, will tend to use the scenario to inform protective
decision making; scenario users with greater agency in the
system tend towards proactive or consensus building objectives.
3. The low carbon scenario literature
A more recent addition to the scenario literature has been the
area of low carbon scenarios — scenarios which explore how a
given system (such as a multi-national area, a national economy
or a sector of a national economy) might look in the future if it
was operating in such a way as to have significantly reduced
carbon emissions. A number of these low carbon scenarios have
been reviewed by Hughes and Strachan (2010). The review finds
that low carbon scenarios tend to focus either on qualitative,
social trend based approaches to developing futures (trend based
studies), or on purely technological, engineering based views of
an energy ‘system’, thermodynamically consistent with meeting
specified energy demands within specified emissions constraints
(modelling and technical feasibility studies). Such technologically
focussed studies often operate explicitly or implicitly within a ‘backcasting’ framework (Robinson, 1982, 1988, 1990; Robinson et al.,
2011; Höjer and Mattsson, 2000), characterised by an exogenously
Table 1
The use of scenarios — the link to near term strategy.
Schwartz (1991)
Scearce et al., (2004)
Godet (1987)
Kahn and Wiener
(1967)
Wack (1985b)
Volkery and Ribeiro
(2009)
‘Scenario planning is about making choices today with an understanding of how they might turn out.’
‘Scenarios are designed to stretch our thinking about the opportunities and threats the future might hold, and to weigh those opportunities
and threats carefully when making both short-term and long-term strategic decisions.’
‘Despite the unknown horizons, we have to take decisions today that commit us for the futurey to create the future rather than submit to it.’
‘Scenarios are attempts to describe in some detail a hypothetical sequence of events that could lead plausibly to the situation envisaged. By the
use of a fairly extensive scenario, the analyst may be able to get a feeling for events and the branching points dependent upon critical choices.’
‘Do they lead to action? If scenarios do not push managers to do something other than that indicated by past experience, they are nothing
more than interesting speculation.’
‘Having an impact on the design and choice of policies remains a litmus test for the relevance of scenario planning.’
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028
N. Hughes et al. / Energy Policy ] (]]]]) ]]]–]]]
imposed emissions or energy reduction target (e.g., Anderson et al.,
2005; Svenfelt et al., 2011; Gomi et al., 2011). A key contribution of
the low carbon scenario literature to UK policy has been in relation to
the setting and revision of long term carbon reduction targets.
Strachan et al. (2009) discuss the iterative role of low carbon
scenarios in this regard, focussing on energy modelling studies.
They show how such studies supported an initial aspirational target
of 60% CO2 reductions by 2050, as well as subsequently supporting
efforts to strengthen the target to an 80% reduction across all
greenhouse gases, through demonstrating the technical feasibility
and economic viability of such targets. The latter target was established in UK law by the Climate Change Act 2008 (HM Stationery
Office, 2008).
Whilst long term targets are important to provide structure to
low carbon energy policy, the mere existence of a target does not
by itself guarantee the successful achievement of the objective.
In the UK it is already clear that a number of much nearer-term
concerns could have significant impacts upon the direction of
travel for the energy system. These include, for example, public
objections to particular energy technologies and energy infrastructure (Devine-Wright, 2011; Haggett, 2008; Gray et al., 2005),
changes in the political climate towards the desirability of the
long term low carbon transition (Guardian, 2011), and, no doubt
in relation to both of these, shifting attitudes on the part of large
market actors about the suitability of the UK as an investment
area (BBC, 2011). These issues represent a complex web of actions
and inter-actions of a variety of system actors, having critical
effects on real decisions to invest or not invest in low carbon
infrastructure. It is towards an understanding of these actor
actions and interactions which previous low carbon scenarios
have been less suited to contributing. Hughes and Strachan
(2010) find that each of the scenario approaches they review
has in common a description of a technological transition which is
generated primarily by the external hand of the operator of the
model, tool or calculator itself, through exogenously imposed
emissions constraints, or other exogenous decisions about technology preference, or broad social trends. Such levers are analogously comparable to deus ex machina devices deployed in
dramas to artificially engineer an unrealistic ‘happy ending’.
Foxon et al. (2010) concur, finding that previous low carbon
scenario work ‘does not illuminate how technological changes
arise through the dynamic interactions between a range of actors
with different perspectives and goals’. This paper therefore starts
from the conclusion that it would be useful to produce low carbon
scenarios which expand from the technologically deterministic, or
purely qualitative trend-based approaches, followed in previous
literature, to explore detailed technological system changes in
relation to the actor actions and interactions which bring them
about. It is argued that such approaches could make important
contributions in terms of more clearly aligning longer term goals
with nearer term policy priorities, and thus ensuring that low
carbon scenarios (or pathways) live up to the aspiration commonly found in the broader scenarios literature, of using speculation about longer term futures primarily as a means to
improving near term decisions. This aspiration in respect of low
carbon scenarios is reflected by a broader review of public policy
scenarios which finds that ‘a lot of progress needs to be madey
towards getting scenario planning more fully incorporated into
processes of policy design, choice and implementation’ (Volkery
and Ribeiro, 2009).
3.1. The challenge of uncertainty in low carbon futures thinking
Low carbon future scenarios experience particular challenges
with uncertainty, as in addition to any background change within
society and technological systems which might be expected to
3
take place over decadal time periods, the goal of decarbonisation
is in itself an additional driver of significant technological and
behavioural change in low carbon scenarios.
Most low carbon scenario studies, perhaps mindful of the ‘perils
of long range energy forecasting’ exposed by Smil (2000), present
their results with careful caveats to the effect that they are not
predictions or forecasts (Ault et al., 2008), nor are they even
‘expected to happen as stated’ (OST-DTI, 2001). All aspects of such
scenarios appear equally uncertain. Technologically focussed
energy system scenarios have an equally pervasive view of future
uncertainty, however they can to a certain extent sideline the
question of uncertainty by treating a vast range of conditions of
political, social and technological change as ‘off-model’ assumptions which drive and justify the implementation of different levels
within available quantitative parameters (e.g., Strachan et al.,
2007; Skea et al., 2010). The reasons why such causative conditions
might come about in the first place are external to the analysis.
An extensive and cautious view of uncertainty may of course
be regarded as highly prudent. However, it is also legitimate to
ask what strategic benefit can be derived from a view of the
future which regards every aspect of it as equally unknowable —
what basis can decision makers take to affect their planning from
a view of the future without even relative levels of uncertainty?
The following section refers to earlier scenario literature to
argue that the clear identification of system actors can in itself be
a key means of managing the inherent uncertainty involved in
low carbon futures thinking.
4. The treatment of uncertainty in the wider scenario
literature
Scenarios have been applied in a range of business, military
and public policy contexts (Bradfield et al., 2005). Several authors
have proposed typologies of the scenario literature (e.g., Huss and
Honton, 1987; van Notten et al., 2003; Bradfield et al., 2005;
Börjeson et al., 2006; Bishop et al., 2007), however the lack of
emergence of a single definitive typology testifies to the ongoing
diversity of the literature — indeed the perceived lack of methodological coherence is an issue of frustration for many in the
field (Marien, 2002; Hines, 2003).
One of the most interesting methodological debates concerns
whether scenarios are intended to highlight the ‘possible’ the
‘probable’, or the ‘preferable’ (Börjeson et al., 2006; Amara, 1981).
Some practitioners argue that probabilistic assessments of future
outcomes are vital to a coherent and strategic view of the future
(Godet and Roubelat, 1996; Godet, 2000), whilst others maintain
that probability becomes viewed as prediction and closes down
perceptions of what is possible, and thus is antithetical to the
scenario approach (Wilson, 2000). Other practitioners however
emphasise the role of scenarios in assisting in the attaining of
desirable futures, emphasising that the likelihood of any future
scenario occurring is at least partly dictated by choices of present
actors (Massé, 1966; de Jouvenel, 1967; le Roux et al., 1992).
In general, ‘trend based’ approaches, which often use the
‘2 2’ matrix to organise scenarios (e.g., Berkhout et al., 1999;
OST-DTI, 2001), present themed alternative futures which deliberately avoid probabilistic ranking, or description of more or less
likely scenario elements. On the other hand, Hughes (2009a) finds
that scenarios which perceive future system outcomes as resulting from interactions of actors, are more likely to produce a
ranked view of uncertainty — with some aspects of future
scenarios emerging as more certain than others. A small number
of such actor-based scenarios are briefly reviewed in this section.
The scenarios developed by Shell just prior to the 1972 oil
shocks (Wack, 1985a; 1985b), are characterised by a high degree
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028
4
N. Hughes et al. / Energy Policy ] (]]]]) ]]]–]]]
of certainty about some aspects of the future. Shell’s head of
scenario planning, Wack describes how the team categorised
future elements according to the degree of uncertainty associated
with them (Wack, 1985a). Specifically, he separated ‘pre-determined’ from ‘uncertain’ elements. It was the strength of conclusions surrounding the ‘pre-determined’ elements which gave the
scenarios their particular urgency — that based on current actor
motivations an oil shock was inevitable. Wack’s ability to identify
the ‘pre-determined’ elements depended on assessments of the
motivations of the actors involved, and critically upon the
assumption that these motivations were fixed. In particular, he
assumed oil producing companies to be profit maximising and to
act in their own national interest. The outcomes of such motivations were concluded intuitively — ‘if we were Iranian, we would
behave the same way’ (Wack, 1985a).
The Shell process explored the implications of fixed actor
motivations using largely qualitative discussion and role-playing
techniques. A similar actor-focussed perspective underlies the
approach developed by Michel Godet for business sector scenarios,
though more formal, mathematical and matrix based methods are
deployed to explore the possible interactions between system
actors (Godet, 1987; Godet and Roubelat, 1996). Godet’s probabilistic presentation of outcomes is ultimately possible due to a
similar fundamental assumption about the motivations of actors:
‘over time, people show disturbing similarities in their behaviour,
which leads them to react, when faced with comparable situations,
in an almost identical way, viz predictably.’ (Godet, 1987).
Another important actor-based scenario process was undertaken in post-apartheid South Africa (le Roux et al., 1992).
Though, similarly to the Shell process, using qualitative discussions around actor motivations, a key difference was that these
discussions were conducted not by a closed scenarios team, but
with the participation of representatives of the key actor groups
themselves. Four different scenarios were developed, each representing the outcomes of different sets of actor choices. It was
shown that ‘the future is not fixed but can be shaped by the
decisions and actions of individuals, organisations and institutions’ (le Roux et al., 1992). In other words a key difference to the
above two approaches was in the perception that actor motivations are not fixed but can evolve — in particular that once actors
perceive the potential significance of actions they themselves
could take, they may be inspired to act differently, in pursuit of a
commonly shared goal. In this case a probabilistic ranking of the
scenarios would not in fact be appropriate. Each scenario is
contingent upon a different set of actor actions arising from
different actor motivations, not from the assumption that all
actors’ behaviour is predictable.
This latter process suggests that a refinement can be made to
Wack’s two-fold categorisation of future elements as ‘pre-determined’ or ‘uncertain’. Wack’s pre-determined elements include
those which result from actor motivations regarded as fixed. If we
allow a world in which actor motivations could change and
evolve, it is important to also allow a category of future elements
which are contingent upon alternative future choices of system
actors. These remain uncertain as actors are still at present free to
choose between different options; however this kind of actor
contingent uncertainty is importantly different from future elements which lie beyond the control of system actors, or whose
causes are so complex as to be not easily associated with any
particular system actor.
In his extended discussion of futures thinking, de Jouvenel
(1967) draws an important distinction between ‘dominating’ and
‘masterable’ elements of the future, where ‘the masterable future
is what I can make other than it now presents itself’, but notes
that whether an element is masterable or dominating depends on
the agency of the actor from whose perspective the future is
viewed. This distinction is important in establishing which actors
within the system have agency to bring about aspects of the
future — some actors may have greater agency than others. It is
also possible to imagine elements of the future which could
impact upon a given system, but over which no internal system
actor has agency or influence. Berkhout et al. (2004) in their
typology of transitions pay particular attention to emphasise that
dynamics within a system can be driven both by internal as well
as external elements, and the notion of the ‘landscape’, or external
context to the sociotechnical regime, is crucial to the multi-level
perspective and the sociotechnical scenario approaches which
have developed from it (e.g., Rip and Kemp, 1996; Kemp et al.,
1998; Geels, 2002; Hofman and Elzen, 2010). Indeed, as identified
by Börjeson et al., 2006, some scenarios, particularly those
employed in business environments, focus entirely on external
factors ‘beyond the control of the relevant actors’.
Thus, even when a future scenario taken as a whole may
appear profoundly uncertain, uncertainty is rarely entirely homogenous. The future scenario can be divided into different kinds of
future element, each associated with different levels of uncertainty. Bringing together the different categorisations of Wack
and de Jouvenel, alongside distinctions between internal and
external, or regime and landscape dynamics, suggests three broad
kinds of future element:
Pre-determined elements: including developments regarded
as inevitable due to fixed actor motivations
Actor contingent elements: developments which are within
the power of system actors to change or bring about, if they
so choose
Non-actor contingent elements: developments which are possible,
but uncertain, and beyond the control of system actors to
influence
The three elements suggest different responses from system
actors and scenario users, which can be related to the three aims
of scenario building defined by Hughes (2009a). Pre-determined
elements are certain to be part of any future, therefore plans must
simply be built around these; non-actor contingent elements are
not certain, but their occurrence or otherwise cannot be controlled by system actors, and must be prepared for. Thus these
two types of element would prompt the need for protective
decision making on the part of scenario users. Actor contingent
elements can be affected by conscious choices of system actors
and thus suggest the potential for proactive decision making to
positively influence the future, or where the outcome is dependent on concerted action of multiple system actors, suggest the
need for consensus building, if that outcome is to be achieved.
The categorisation of future elements in this way is important to
enable policy relevant insight to emerge from scenarios, which
cannot be achieved by scenarios which have a homogenous view
of future uncertainty. Critically, from a policy perspective there is
an important difference between a future element which remains
profoundly or scientifically uncertain, and therefore beyond the
agency of any identifiable actor to purposefully influence; and one
which is within the potential of system actors to influence, and
therefore remains uncertain only because a decision to act has not
yet been taken. The latter may suggest important potential roles
for certain system actors in actually creating greater certainty
about the future, through the actions they can commit to take.
In such a case, as de Jouvenel again writes, ‘the future is known
not through the guesswork of the mind, but through social efforts,
more or less conscious, to cast ’’jetties’’ out from an established
order and into the uncertainty ahead. The network of reciprocal
commitments traps the future and moderates its mobility. All this
tends to reduce uncertainty.’ (de Jouvenel, 1967).
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028
N. Hughes et al. / Energy Policy ] (]]]]) ]]]–]]]
5. Conceptualising an actor-based system for low carbon
scenarios
The previous section identified significant advantages to an
actor-based scenario approach, in particular that it facilitates the
categorisation of future elements by levels of uncertainty and
relation to actor choices, and as a result provides clearer information to scenario users regarding the appropriateness of proactive,
protective or consensus building strategies with respect to each
possible element of the scenario future.
While Hughes and Strachan (2010), and Foxon et al. (2010)
criticise the lack of actor specification in low carbon scenarios,
nonetheless it is clear that for scenarios which aim to explore
questions of how to reduce carbon emissions from energy and
other services, a detailed depiction of technologies, fuels and
emissions remains of critical importance.
It becomes clear that in order to maximise the usefulness and
policy tractability of low carbon scenarios, the description of the
system they are considering must encompass both actor motivations actions and dynamics, and the technological systems in
which these actor dynamics take place. This conclusion is further
supported by insights from the technological transitions literature
which through examining past case studies shows the co-evolutionary dynamics between societal and technological systems
(Rip and Kemp, 1996; Kemp et al., 1998; Geels, 2002). Technologies and technological systems are evidently not autonomously
self-assembling — they are the result of sequences of actor
decisions. However, the influence is two way — technological
systems once constructed can constrain and influence subsequent
actor behaviour. Thus, technological systems ‘are both socially
constructed and society shaping’ (Hughes, 1987).
It is therefore important for the overall plausibility of low
carbon scenarios as descriptions of possible sequences of future
events, that they should account for and represent something of
this interaction. An important contribution was made in this
regard by Elzen, Hofman and others through their concept of
sociotechnical scenarios (Elzen et al., 2002; Hofman et al., 2004;
Elzen and Hofman, 2007; Hofman and Elzen, 2010). Hofman and
Elzen (2010) argue that sociotechnical scenarios should show
how ‘transition paths may unfold in a process of interaction
between a range of actors and the rules they act upon’, and should
also ‘describe the co-evolution of technology and its societal
embedding (a continuous action-reaction dynamic of technical
and societal change)’ (Hofman and Elzen, 2010). Their approach
describes plausible pathways for the evolution of technological
systems alongside actors and institutions, rooted in the ‘multi-level
perspective’ (Geels, 2002) of niches, regime and landscape.
The scenarios are constructed around a three-fold taxonomy of
transition pathways defined by Geels and Schot (2007). This
taxonomy provides the basic underlying structure of each scenario.
A potential disadvantage of this is the sense that it is this predetermined structure which is defining the content of each scenario,
rather than an open exploration of actor motivations and dynamics.
Further, according to their narratives each of the scenarios is
dependent on the fulfilment of a number of very contrasting
elements, including internal actor decisions, but also external (EUlevel) conditions, and technological developments (such as the
availability of hydrogen and CCS technologies). The analysis does
not draw out which of these various elements can be directly
influenced by specific system actors, and which cannot. This makes
it difficult to draw specific policy insight from the scenarios.
Drawing on the insights from the broader scenario tradition
summarised in Section 4, this paper aims to continue Hofman and
Elzen (2010)’s successful exploration of ‘co-evolutionary’ sociotechnical dynamics within a scenario context, but, for the reasons
argued above, to propose an approach which is based on a clearer
5
depiction of the motivation, roles and actions of specific system
actors, and to draw clearer distinctions between elements of
future scenarios which are potentially within the control of
system actors, and those elements outside of their control.
It then proposes that this detailed depiction of system actors
should be ‘soft-linked’ to an appropriate technological system
model, so that the implications of actor decisions upon the
technological system, as well as the implications of technological
system developments upon subsequent actor decisions, can be
clearly represented.
5.1. Representing the web of actors and institutions
In institutional theory, an actor can be an individual, or a coherent
conglomeration of individuals, such as a firm — however, whether
defined at individual or organizational level, a key feature of actors is
that they have strategies, and make choices (Jackson, 2010).
The accumulated effect of various actor choices in respect of their
strategies is to create a web of interrelated demands and reciprocal
expectations between a constellation of actors. These are the institutions, or ‘sets of rules, decision making procedures, and programs that
define social practices, assign roles to the participants in these
practices, and guide interactions among the occupants of individual
roles’ — that is, the ‘rules of the game’ which govern interactions
between actors (Young, 2002).
Fig. 1 represents a constellation of actors which could pertain to a
system under study with relevance to a low carbon scenario process.
Fig. 1 shows the broad actor types whose actions would affect
developments within a low carbon scenario, as market actors,
civil society actors and government actors. It shows the relations
and reciprocal demands and pressures which could operate
between these actor types in the context of an energy system.
The actor types are the same as those found within the ‘action
space’ developed elsewhere in the Transition Pathways project
(Foxon et al. (2012), this volume). The action space provides a
means of considering shifts between the ‘logics’ of different
system actors, in order to provide structure for generating pathway narratives. Fig. 1 also emphasizes that such shifts occur
as the net result of the actions of all actors within the system.
That is, they occur both as a result of proactive actions of actors
whose ‘logic’ is being upheld or enforced, but also as a result of
the passiveness, agreement or coercion of the other actor types.
In each case, the relative agency of each actor type is additionally
a critical factor affecting the outcome. As Godet writes, ‘the actual
Fig. 1. Example of actor interactions and networks of influence (adapted from
Hughes (2009b)).
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028
6
N. Hughes et al. / Energy Policy ] (]]]]) ]]]–]]]
future will be the outcome of the interplay between the various
protagonists in a given situation and their respective intentions’
(Godet, 1987). However, ‘certain actors are ’more equal’ than
others. From this we may conclude that although several futures
are possible, the one which actually transpires will arise out of the
conflict of unequal human forces, tempered by the ’inequalities’’
(Godet, 1987). This dynamic is explored within the Transition
Pathways project in terms of how succesfully different types of
actor can ‘enrol’ the others into their ‘logic’, or ‘view of the world’
(Foxon et al. (2012), this volume).
In other words, overall system outcomes can be thought of as a
net result arising from all activities within a web of actors and
institutions. The institutional expression of the collective or
aggregated actions and motivations of all actors in society is a
function both of the motivations of the various actors, and the
relative agency of the actors that hold them, or, the degree of
power that any one actor has to realise his/her/its priorities.
As such, actors can be ‘rule takers’ but also ‘rule makers’, for
‘institutional rules must be ‘enacted’ by actors, but institutions
themselves are produced and reproduced through these actions’
(Jackson, 2010). A network in which these rules of the game are
no longer challenged, can be thought of as operating under
conditions of ‘institutional lock-in’ (Unruh, 2000). Alternatively,
actors may continue to disagree over and question the appropriate ‘rules of the game’ (Young, 2002), and to continue to be
‘rule makers’, as a result of which new sets of rules may continue
to emerge.
5.2. Interactions between actors, institutions and
the technological system
The net result of these actor interactions could in some cases
include new investments in technological infrastructure which
can be measured in terms of altered means of producing energy in
the system, resulting in changes in overall carbon emissions.
However, drawing on Hughes (1987) insight that technological
systems ‘are both socially constructed and society shaping’, it is
important to consider also the reciprocal effects of altered
technological systems upon subsequent actor motivations and
decisions. Table 2 shows some examples of this two-way relationship from historical and prospective UK electricity system
transitions.
Fig. 2 schematically represents a co-evolutionary model of
socio-technical change through this two-way interaction, but one
in which the motivations of and actions of actors remain identified (Table 2).
5.3. Choosing tools to represent actor, institutional and
technological system dynamics
Thus far the discussion in this section has focussed on presenting a
theoretical understanding of actors, institutions and their relationship
to technological systems. Some words may also be said about the
practicalities of representing these dynamics in a scenarios process.
We do not propose that there is one specific tool that could achieve
this. Rather we emphasise the utility of combining insights from
contrasting tools for the representation of the different aspects of the
system. The left hand side of Fig. 2 shows the web of actors and
institutions described in Fig. 1 and Section 5.1. The impact of
changing dynamics, or different ‘rules of the game’ must be read
across in terms of their implications for technologies, to the right
hand side of Fig. 2, which represents a technical system. The effects of
changes to the technical system must then be read back in terms of
their implications for subsequent actor decisions. Clearly contrasting
methodologies will be required to represent each side of the system.
The choice of which tools to apply within this framework will depend
on the precise question being considered (e.g., considering electricity
vs transport vs. whole energy systems), as well as the capabilities and
available tools of the scenario builders themselves. Approaches to
representing the actor-institution system could include cross-impact
matrices (Helmer, 1972; Godet, 1987), agent based models
(An, 2011), or more intuitive techniques (Wack, 1985a; le Roux
et al., 1992). Approaches to representing the technical system could
draw on energy system models (Strachan et al., 2007), electricity
market models (Foley et al., 2010), power flow or other network
models (Gerber et al., 2012; Strbac et al., 2010) building sector models
(Johnston et al., 2005), or numerous other models of technical
systems as appropriate. Clearly, in low carbon scenarios it would be
important that the technical model could quantify carbon emissions
arising from the system. What is equally important is the ability to
‘soft link’ insights from the actor based tool or approach to the
technical system model. The integration and feedback of insights
between contrasting tools will be one of the key methodological
challenges of representing the system in this way. Nonetheless, such
integration is unavoidable in such a cross-disciplinary area as low
carbon policy, and indeed cross-disciplinary approaches have been
consistently argued as being a key area of added value within
scenario techniques (Wack, 1985b; Börjeson et al., 2006; van
Notten et al., 2003).
6. Process for constructing low carbon scenarios under
uncertainty
Section 5 developed a view of a co-evolving sociotechnical
system, but one which retains clarity about the role that specific
wilful actions of system actors can play in contributing to the
generation of ‘action-reaction’ dynamics of sociotechnical change
(Hofman and Elzen, 2010).
The following section describes an outline scenario process
which draws on the actor based system conceptualisation developed in Section 5, and the three-fold categorisation of future
scenario elements developed in Section 4. The process aims to
produce scenarios which develop clear links between future
outcomes and near term decisions of system actors, which are
therefore able to produce clearer policy recommendations and
achieve a more constructive view of future uncertainty.
6.1. Define the focal question
Fig. 2. Co-evolving, actor based model of sociotechnical change.
Low carbon scenarios can involve consideration of multiple
complex and interrelated systems, each of which produce greenhouse
gases and are therefore of relevance to questions of decarbonisation
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028
N. Hughes et al. / Energy Policy ] (]]]]) ]]]–]]]
7
Table 2
Reciprocal effects between actor-institutional systems and technological systems: Historical and prospective examples.
Initial actor action
Historical examples (see Hannah, 1979)
1892: Electrical Lighting act allows municipalities
to break up streets for cable laying
1900–1925: Disputes between municipalities and
private actors, lack of coordination
1926: Creation of Central Electricity Board and
decision to build high voltage network
Prospective examples
Government actors take strategic decision to
promote investment in North Sea offshore grid
Policies strongly promote decentralized
generation
Effect on technological system
Effect of technological change on subsequent actor decisions
Potential for more extensive local distribution
networks
Increasingly fragmented system, with low load
factors
High capacity network availability and
aggregation of previously fragmented demands
Municipalities and entrepreneurs see increased opportunities to
promote and sell electricity
Political actors increasingly sympathetic to merits of central
coordination
Market actors motivated to invest in higher capital, larger, but
more efficient plant
High capacity network available with demand
aggregated from several countries
Significant uptake of DG presents technical
challenges to distribution networks
Market actors given greater motivation to make large scale
offshore renewable investments
Opportunities for innovative distribution network companies, or
IT firms developing technologies to facilitate smart grids
(IPCC, 2007). A tractable scenario process inevitably involves drawing
boundaries around subsets of the many interrelated systems which
could pertain to the question at a global level. The focal question for a
low carbon scenario process should therefore address the specific
challenges for which the scenario process is intended to provide
insights, which may include a carbon emissions reduction target for a
given (and perhaps narrowly defined) system. Thus, the precise
definition of the focal question helps to determine the necessary
scope of the system to be studied, and the actors who must be
considered within that system.
6.2. Define and describe the current system
The scope of the system should be sufficiently wide to include
aspects which are significant to answering the focal question.
In particular, clearly defining the scope of the technological
system to be included in the study is relevant when comparing
scenario outcomes against externally set emissions reduction
targets. However, the system scope will also be affected by
practical considerations of the tools and resources available, and
how these relate to a trade-off between internal scenario complexity and external uncertainty. Greater system scope entails
greater complexity for consideration within scenarios — a larger
technological system, and a larger number of actors affected by it;
smaller system scope entails a less complex system but a larger
number of external factors affecting the outcome.
System scope must also be defined in terms of the actors who
make up that system, their current motivations for acting, their
agency and their networks of influence in respect of other actors. This
highlights iterative actor interactions which lock in particular sets of
relationships (of the kind summarised in Fig. 1). Having defined both
the technological scope and the actor-institutional scope of the
system, this initial process should also identify linkages between
them, i.e., which actors might affect technological systems through
investment, and at which points systems can constrain actor actions.
These will be the ‘soft-linking’ points between the models or tools
used to describe the actor-institution system, and those used to
describe the technological system (Fig. 2).
6.3. Identify pre-determined and actor contingent elements within
the system
Following the scoping of the current system, it is subsequently
possible to identify pre-determined and actor contingent elements, which could influence its evolution into the future.
6.3.1. Pre-determined elements
Drawing on Wack (1985a; 1985b) a key starting point for future
scenarios should be to explore the possibility that some aspects of the
future may be already pre-determined. A detailed scoping of the
current system may reveal elements which are ‘locked-in’ for certain
periods of time. These are pre-determined elements and should as
such be included as part of each individual scenario which is explored
within a given process, for the relevant time period. In low carbon
scenarios key candidates for these are the technologies and technological infrastructures which have already been invested in and which
have lifetimes which extend into the scenario period.
As with Wack’s original ‘pre-determined elements’ (Wack,
1985a), it is possible in low carbon scenarios that as well as long
lived infrastructure investments providing pre-determined elements, assumptions of fixed actor motivations could also be seen
as delivering pre-determined elements at least within relatively
near term periods of the scenario horizon. However, over longer
term time frames, the low carbon transition must as a prerequisite involve changes in actor motivations — be they investment practices of firms, governmental attitudes towards regulation, public acceptance and behavioural change in respect of
energy services and technologies. Low carbon scenarios must also
therefore explore the effects of changing actor motivations, as
shall be discussed in the next section.
6.3.2. Actor-contingent elements
The scoping of the current system should also however
identify potentially mobile elements — elements which are not
yet decided but contingent upon actor decisions yet to be taken,
and actor motivations which could conceivably shift over time.
An actor contingent element should be considered as occurring
as a result of two stages: first the motivation of the actor which
inspires him/her/it to act; and second the actual effect of that
action within the system, acknowledging that no single actor has
complete control over that system. Rather the actual impact of
the actions of any actor is dependent on their agency in relation to
the other actors in the system.
‘Trend based’ scenarios have in general been creative about
hypothesising major shifts in actor motivation: the 2 2 axis
provides a means for hypothesising major attitudinal shifts. However,
such scenarios promote such attitudinal shifts immediately to a
society-wide end point state for each scenario, without rigorously
exploring how attitudinal shifts which originate amongst one set of
actors would transmit to the rest of society, and the resistance that
these ideas could encounter along the way. Within an actor-based
scenario process, a wide range of actor motivation shifts may
legitimately be freely hypothesised; the key thing is that in each case
society-wide implications cannot be immediately assumed, but must
rather be tested against the constraints of the existing social and
technical systems.
Another important distinction to make in relation to actor
motivations is that there is a difference between an actor changing
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028
8
N. Hughes et al. / Energy Policy ] (]]]]) ]]]–]]]
behaviour as a result of an internal motivation shift, and one doing
so in response to the altered behaviour of another actor in the
system. The former might be called a prime mover, the latter a
secondary mover. For example, in a case where the government
increases the rate of financial support available for a certain class
of renewable technology, as a result of which a company increases
its deployment plans for that technology, the government is a
prime mover, the company a secondary mover.
6.4. Describe possible system evolution paths and points of fulcrum/
branching points
The characterisation of the current system undertaken above
describes a dynamic process of interactions between various
kinds of actors, with different motivations and levels of agency
and influence (Fig. 1), which results in the construction and
maintenance of energy technologies and infrastructures — all of
which in combination provides a description of the operation
of the current sociotechnical system (Fig. 2). It is now possible to
generate alternative scenarios which describe the evolution of
this system based on contrasting assumptions about the fixed or
mobile nature of the motivations of key system actors.
As de Jouvenel writes, ’what is important is to find points of
fulcrum on which we can exert pressure, thereby deflecting
the course of events in one direction rather than another’
(de Jouvenel, 1967). These ‘points of fulcrum’, in our system
description must correspond to changes in motivations and resulting actions of key system actors. Thus, these ‘points of fulcrum’ — or
as described by Kahn and Weiner (1967) ‘branching points dependent upon critical choices’ — create actor contingent scenarios
leading towards alternative systems, as illustrated in Fig. 3.
Clearly, in a low carbon scenario a technical assessment of the
emissions associated with the technological system is a key input to
assessing how successful a scenario has been in relation to this
normative objective. However, these emissions levels are not pre-set
end points. Rather, each new system development must be shown to
result from an action that is consistent with the agency of the actor
who carries it out, within the constraints of the socio-technical
system. — not exogenously imposed upon the system. This approach
which begins from the current system and explores its potential to
evolve prospectively, within realistic constraints of actor agency, is in
contrast to ‘backcasting’ approaches which set a desired goal as a
deterministic end point (Hughes and Strachan, 2010).
changes in motivations of key actors. However, it is still possible
and important to compare scenarios in terms of how challenging
they appear to be to bring about. Such a comparison can be
qualitatively accessed by considering the number and type of
altered actor motivations and actions upon which the scenarios
are predicated. For any particular actor action or motivation —
which is critical to a branching point — it can be asked how great
a change in its behaviour this would represent from that which it
exhibits in the current system. For example, Suurs et al. (2004)
develop an approach whereby the actors who would be involved
in the transition are interviewed, and a measure of their
‘willingness to participate’ is assessed. Another important question is the number of simultaneous actor changes which would be
required to effect a certain branching point. A branching point
which can be brought about by the action of a single prime mover
might be considered less challenging to bring about than one
requiring consensus between multiple actors. Thus, a less challenging actor contingent scenario would be characterised by a
smaller number of prime mover actions, representing a lesser
degree of change from their current motivations, than a more
challenging one. A further key consideration should be that of
costs, at what point of the transition and by which actors they are
experienced.
6.6. Assess actor contingent scenarios against non-actor contingent
elements
Thus far, the process has considered only the dynamics which
can be brought about by wilful actions of internal system actors.
However, as noted in section 4, the effects that events and
developments external to a given system can have upon that
system are also significant and cannot reasonably be ignored or
discounted.
This paper has therefore developed the category of non-actor
contingent elements to include those which can be less directly
attributed to wilful actions of actors within the system under
study, but that nonetheless could have a significant effect on the
evolution of the system. This could be because they are clearly
external to the system; however the category could also include
events which cannot be attributed to purposeful actions of any
particular actor, internal or external to the system.
Examples of such ‘non-actor contingent’ elements could therefore include:
6.5. Assess challenges of actor contingent scenarios
Global events and dynamics such as resource price spikes,
As discussed above, comparing scenarios through probabilistic
ranking is not appropriate where they are based on hypothesised
Political events, conflicts, diplomatic crises
Growth in intensity of climate change impacts
Unplanned or unexpected technological failure or breakthrough
Fig. 3. Schematic representation of ’branching point’ scenarios approach.
economic growth or downturn
The clear separation within the scenario structure of actor
contingent and non-actor contingent developments is proposed
due to the increased clarity of policy recommendations which will
result. As noted in Section 4, actor contingent elements suggest
opportunities for proactive decision making or consensus building, non-actor contingent elements require a more protective
policy mode.
As non-actor contingent events are not intrinsically connected
to the actor dynamics described by the scenarios, they are not
inherently connected with one scenario or another. It follows that
the effect of a non-actor contingent event should be considered
across all scenarios.
Selection of the most important or significant non-actor contingent events may be required. Whereas considering the probability of
the actor contingent scenarios would not be appropriate, as they are
contingent upon acts of human free will, probability may be a useful
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028
N. Hughes et al. / Energy Policy ] (]]]]) ]]]–]]]
additional test for considering the importance of non-actor contingent
events. For example an actor contingent scenario may be found to be
plausible and to have several beneficial characteristics, though it is
vulnerable to a particular non-actor contingent event. However if this
event has a low probability it might be felt that the other beneficial
aspects of this scenario could justify this risk. In this way scenarios
can be compared both in terms of potentially ’controllable’ (actor
contingent) events, and ’uncontrollable’ (non-actor contingent) events
whose potential impact is balanced against their probability.
9
social developments in a multi-actor environment with existing
characteristics, ambiguous boundaries, long time scales and external
pressures. Characterising and assessing uncertainties in such futures
thinking is a key element to make scenarios/pathways tractable and
informative for policy making. This is critically true for low carbon
scenarios/pathways where extreme external pressures and potential
socio-technical lock-in will only be successfully addressed with the
concerted and conscious efforts by many societal actors within the
system under study. Following a structured process on uncertainty
will assist analysts in efforts to ‘create the future rather than submit
to it’ (Godet, 1987).
7. Conclusions
The clearer definition of the activities of system actors in low
carbon scenarios has in a previous paper been argued to be useful
for increasing their policy tractability (Hughes and Strachan,
2010). The current paper shows that actor based approaches are
more specifically useful in assisting a constructive view of future
uncertainty, in particular because there is an important difference
between something which is uncertain because it lies beyond the
control of system actors, and something which is uncertain
because system actors have not yet decided upon their strategies
in respect of it.
In support of this argument, this paper has offered two new
methodological contributions. First, the paper offers a system
conceptualisation which draws on insights on co-evolutionary
processes from the technological transitions literature, but also
emphasises the role of actor choices via institutional theory and
actor-based scenario literature, and considers the actor-institution web as having an iterative relationship with the technical
network. Second, the paper identifies a categorisation of future
elements by synthesising insights from scenario literature, and
other conceptualisations of technological transitions such as the
multi-level perspective, and applies this categorisation in the
context of low carbon scenarios. The paper argues that distinguishing between pre-determined, actor contingent and nonactor contingent elements, will assist with policy tractability
and management of uncertainty.
On the basis of these contributions the paper then presents an
outline scenario process.
The proposed process may be summarised as:
Define the focal question
Define and describe the current system
Identify pre-determined and actor contingent elements within
the system
Describe possible system evolution paths and points of fulcrum/branching points
Assess challenges of actor contingent scenarios
Assess actor contingent scenarios against non-actor contingent
events
The differentiation of actor contingent elements and their
effects within the sociotechnical system, from pre-determined
and non actor contingent elements, helps to demonstrate in
greater detail the sequence of actions and events by which the
present system is transformed into a future one, and the role of
purposive actions of specific system actors. This powerful sequential aspect is captured in the use of the term ‘pathway’ — which
may indeed be preferred to the more traditional term ‘scenario’
for this reason. A detailed example of such a ‘transition pathway’
— for the possible evolution of a low carbon electricity sector in
the UK — is discussed in detail in subsequent chapters of this
Special Issue (Foxon et al. (2012), this volume).
Low carbon scenario and transition pathway analysis inevitably involves making conjectures about pervasive technical and
Acknowledgements
The authors would like to thank Dr. Tim Foxon, Professor Peter
Pearson, and participants in an E.ON/EPSRC Transition Pathways
project workshop, held at King’s College London in July 2009, for
their comments on earlier drafts of this paper.
References
Amara, A., 1981. The futures field: searching for definitions and boundaries.
The Futurist 15 (1), 25–29.
An, L. (2011) Modeling human decisions in coupled human and natural systems:
Review of Agent-Based Models, Ecological Modelling, In Press.
Anderson, K., Shackley, S., Mander, S., Bows, A., 2005. Decarbonising the
UK-Energy for a Climate Conscious Future. Tyndall Centre, Manchester.
Ault, G., Frame, D., Hughes, N. (2008) Electricity Network Scenarios for Great
Britain in 2050. Final Report for Ofgem LENS Project. /www.ofgem.gov.uk/
Networks/Trans/ElecTransPolicy/lens/Pages/lens.aspxS.
BBC (2011) Longannet carbon capture scheme scrapped. BBC News Online,
19th October 2011. Available at: /http://www.bbc.co.uk/news/uk-scotlandnorth-east-orkney-shetland-15371258S Last accessed 27.01.12.
Berkhout, F., Skea, J., Eames, M., 1999. Environmental Futures. Office of Science
and Technology/Foresight Programme, London.
Berkhout, F., Smith, A., Stirling, A., 2004. Socio-technical regimes and transition
contexts. In: Elzen, B., Geels, F., Green, K. (Eds.), System Innovation and the
Transition to Sustainability: Theory, Evidence and Policy. Edward Elgar,
Cheltenham.
Bishop, P., Hines, A., Collins, T., 2007. The current state of scenario development:
an overview of techniques. Foresight 9 (1), 5–25.
Börjeson, L., Höjer, M., Dreborg, K., Ekvall, T., Finnveden, G., 2006. Scenario types
and techniques: towards a user’s guide. Futures 38, 723–739.
Bradfield, R., Wright, G., Burt, G., Cairns, G., Van Der Heijden, K., 2005. The origins
and evolution of scenario techniques in long range business planning. Futures
37, 795–812.
Devine-Wright, P. (2011) Power, pylons and protest: a critical analysis of the role
of place and scale in contested energy infrastructure projects. Paper
to conference: Energy and People, Futures, Complexity and Challenges,
21st September 2011, Oxford, UK.
Elzen, B., Geels, F., Hofman, P. (2002) Sociotechnical scenarios — development and
evaluation of a new methodology to explore transitions towards a sustainable
energy supply. Report for NOW/NOVEM, University of Twente.
Elzen, B. and P.S. Hofman (2007), Transition paths towards a sustainable electricity
system: An exploration using socio-technical scenarios. Final Report for
Programme ’Transitions and Transition Paths’, funded by NWO/SenterNovem,
Enschede, Netherlands: University of Twente, CSTM.
Foley, A.M., Ó Gallachoir, B.P., Hur, J., Baldick, R., McKeogh, E.J., 2010. A strategic
review of electricity systems models. Energy 23, 4522–4530.
Foxon, T. (2011) Transition pathways for a UK low carbon electricity future. Paper
4 in ‘Transition Pathways to a Low Carbon Electricity Economy’ — Energy
Policy Special Issue.
Foxon, T.J., Hammond, G.P., Pearson, P.J.G., 2010. Developing transition pathways
for a low carbon electricity system in the UK. Technological Forecasting and
Social Change 77 (8), 1203–1213.
Foxon, T.J., Pearson, P.J., Arapostathis, S., Carlsson-Hyslop, A. and Thornton,
J. (2012) Branching points for transition pathways: assessing responses of
actors to challenges on pathways to a low carbon future. Paper 12 in
‘Transition Pathways to a Low Carbon Electricity Economy’ — Energy Policy
Special Issue.
Geels, F., 2002. Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and case study. Research Policy 31,
1257–1274.
Geels, F.W., Schot, J., 2007. Typology of sociotechnical transitions pathways:
refinements and elaborations of the multi-level perspective. Research Policy
36, 399–417.
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028
10
N. Hughes et al. / Energy Policy ] (]]]]) ]]]–]]]
Gerber, A., Qadran, M., Chaudry, M., Ekanayake, J., Jenkins, N., 2012. A 2020 GB
transmission network study using dispersed wind farm power output. Renewable Energy 37, 124–132.
Godet, M., 1987. Scenarios and Strategic Management (Translated from the French
by David Green and Alan Rodney). Butterworths, London.
Godet, M., 2000. The art of scenarios and strategic planning: tools and pitfalls.
Technological Forecasting and Social Change 65, 3–22.
Godet, M., Roubelat, F., 1996. Creating the future: the use and misuse of scenarios.
Long Range Planning 29 (2), 164–171.
Gomi, K., Ochi, Y., Matsuoka, Y., 2011. A systematic backcasting on low-carbon
society policy in case of Kyoto city. Technological Forecasting and Social
Change 78 (5), 852–871.
Gray, T., Haggett, C., Bell, D., 2005. Wind farm siting — the case of offshore wind
farms. Ethics, Place and Environment 8 (2), pp127–pp140.
Guardian (2011) George Osborne reveals his true colours on emissions — and they
are not green. Guardian Online, Monday 3rd October, 2011. Available at:
/http://www.guardian.co.uk/environment/damian-carrington-blog/2011/oct/
03/george-osborne-carbon-emissions-conservativesS.
Haggett, C., 2008. Over the sea and far away? A consideration of the planning,
politics and public perception of offshore wind farms. Journal of Environmental Policy and Planning 10 (3), 289–306.
Hannah, L., 1979. Electricity before Nationalisation. Macmillan, London &
Basingstoke.
Helmer, O., 1972. Cross-impact gaming. Futures 4 (2), 149–167.
Hines, A., 2003. The futures of futures: a scenario salon. Foresight 5 (4), 28–35.
HM Stationery Office (2008) Climate Change Act 2008. Available at: /http://www.
legislation.gov.uk/ukpga/2008/27/pdfs/ukpga_20080027_en.pdfS Last accessed:
27.01.12.
Hofman, P., Elzen, B., Geels, F., 2004. ’’Sociotechnical scenarios as a new tool to
explore system innovations: co-evolution of technology and society in the
Netherlands’ energy system’’. Innovation: Management, Policy and Practice 6,
2, 344–360.
Hofman, P., Elzen, B., 2010. ’’Exploring system innovation in the electricity system
through sociotechnical scenarios’’. Technology Analysis and Strategic Management 22 (6), 653–670.
Höjer, M., Mattsson, L., 2000. Determinism and backcasting in future studies.
Futures 32 (7), 613–634.
Hughes N. (2009a), A historical overview of strategic scenario planning, and
Lessons for Undertaking Low Carbon Energy Policy, A joint working paper of
the EON/EPSRC Transition Pathways Project (Working Paper 1) and the UKERC,
/www.lowcarbonpathways.org.ukS.
Hughes, N. (2009b) Using scenarios to bring about low carbon energy transitions:
lessons from transitions theory and the scenario building tradition, A working
paper of the EON/EPSRC Transition Pathways Project (Working Paper 3)
/www.lowcarbonpathways.org.ukS.
Hughes, N., Strachan, N., 2010. Methodological review of UK and international low
carbon scenarios. Energy Policy 38, 6056–6065.
Hughes, T., 1987. The evolution of large technological systems. In: Bijker, W.,
Hughes, T., Pinch, T. (Eds.), The Social Construction of Technological Systems.
Massachussetts Institute of Technology, Massachussetts, USA. 1987.
Huss, W.R., Honton, E.J., 1987. Scenario planning — what style should you use?
Long Range Planning 20 (4), 21–29.
IPCC (2007) Climate Change 2007 — The physical science basis. contribution of
working group I to the Fourth Assessment Report of the Intergovernmental
Panel on Climate Change, 2007. Cambridge University Press, Cambridge UK
and New York, USA.
Jackson, G., 2010. Actors and Institutions. In: Morgan, G., Campbell, J., Crouch, C.,
Pedersen, O.K., Whitley, R. (Eds.), The Oxford Handbook of Comparative
Institutional Analysis, Oxford University Press, Oxford, UK., pp. 63–86.
Johnston, D., Lowe, R., Bell, M., 2005. An exploration of the technical feasibility of
achieving CO2 emission reductions in excess of 60% within the UK housing
stock by the year 2050. Energy Policy 33 (13), 1643–1659.
de Jouvenel, B., 1967. The Art of Conjecture (Translated from the French by Nikita
Lary). Weidenfeld and Nicolson, London.
Kahn, H. and Weiner, A. (1967) The Year 2000: A Framework for Speculation on
the Next 33 Years, Collier-Macmillan, Toronto, Canada.
Kemp, R., Schot, J., Hoogma, R., 1998. Regime shifts to sustainability through
processes of niche formation: the approach of strategic niche management.
Technology Analysis and Strategic Management 10 (2), 175–195.
Marien, M., 2002. Futures studies in the 21st Century: a reality based view. Futures
34, 261–281.
Massé, P., 1966. Les attitudes envers l’avenir et leur influence sur le présent
In: Darcet, J. (Ed.), Étapes de la Prospective. Presse Universitaires de France, Paris.
van Notten, P.W.F., Rotmans, J., van Asselt, M.B.A., Rothman, D.S., 2003. An updated
scenario typology. Futures 35, 423–443.
OST-DTI (2001) Energy for Tomorrow- Powering the 21st Century, Report of the
Energy Futures Task Force.
Robinson, J.B., 1982. Energy backcasting — a proposed method of policy analysis.
Energy Policy 10 (4), 337–344.
Robinson, J.B., 1988. Unlearning and backcasting: rethinking some of the questions
we ask about the future. Technological Forecasting and Social Change 33,
325–338.
Robinson, J., 1990. Futures under glass. a recipe for people who hate to predict.
Futures 22 (8), 820–842.
Robinson, J., Burch, S., Talwar, S., O’Shea, M., Walsh, M., 2011. Envisioning
sustainability: recent progress in the use of participatory backcasting
approaches for sustainability research. Technological Forecasting and Social
Change 78 (5), 756–768.
le Roux, Pieter, et al., 1992. The mont fleur scenarios. Deeper News 7 (1).
Emeryville: Global Business Network.
Rip, A. and Kemp, R. (1996) Towards a theory of socio-technical change. Report for
Batelle Pacific NorthWest Laboratories, University of Twente.
Scearce, D., Fulton, K. and GBN (2004) What If? The art of scenario thinking for
non-profits. Global business network. /http://www.gbn.com/consulting/arti
cle_details.php?id=27S.
Schwartz, P., 1991. The art of the long view: the path to strategic insight for
yourself and your company. Doubleday, New York.
Smil, V., 2000. Perils of long-range energy forecasting: reflections on looking far
ahead. Technological Forecasting and Social Change 65, 251–264.
Skea, J., Ekins, P., Winskel, M. (Eds.), 2010. Earthscan, London.
Strachan N., Kannan R. and Pye S., 2007, Scenarios and Sensitivities on Long-term
UK Carbon Reductions using the UK MARKAL and MARKAL-Macro Energy
System Models, UKERC Research Report 2, /www.ukerc.ac.ukS.
Strachan, N., Pye, S., Kannan, R., 2009. The iterative contribution and relevance of
modelling to UK energy policy. Energy Policy 37, 850–860.
Strbac, G., Gan, C.K., Aunedi, M., Stanojevic, V., Djapic, P., Dejvises, J., Mancarella, P.,
Hawkes, A., Pudjianto, D., Le Vine, S., Polak, J., Openshaw, D., Burns, S., West, P.,
Brogden, D., Creighton, A. and Claxton, A. (2010) Benefits of Advanced Smart
Metering for Demand Response based Control of Distribution Networks.
Summary Report. Imperial College London / Energy Networks Association,
/www.energynetworks.orgS.
Suurs, R., Hekkert, M., Meeus, M., Nieuwlaar, E., 2004. Assessing transition
trajectories towards a sustainable energy system: a case study on the Dutch
transition to climate-neutral transport fuel chains. Innovation: management,
policy and practice 6 (2), 269–285.
Svenfelt, A., Engström, R., Svane, Ö., 2011. Decreasing energy use in buildings by
50% by 2050 — a backcasting study using stakeholder groups. Technological
Forecasting and Social Change 78 (5), 785–796.
Unruh, G., 2000. Understanding carbon lock-in. Energy Policy 28, 817–830.
Volkery, A., Ribeiro, T., 2009. Scenario planning in public policy: understanding
use, impacts and the role of institutional context factors. Technological
Forecasting and Social Change 76, 1198–1207.
Wack, P., 1985a. Scenarios: unchartered waters ahead. Harvard Business Review
September–October 1985, 73–89.
Wack, P., 1985b. Scenarios: shooting the rapids. Harvard Business Review,
November–December 1985, 139–150.
Wilson, I., 2000. From scenario thinking to strategic action. Technological Forecasting and Social Change 65 (1), 23–29.
Young, O.R., 2002. The Institutional Dimensions of Environmental Change:
Fit, Interplay and Scale. Massachussetts Institute of Technology, US.
Please cite this article as: Hughes, N., et al., The structure of uncertainty in future low carbon pathways. Energy Policy (2012), http://d
x.doi.org/10.1016/j.enpol.2012.04.028