Social Acceptance and Its Role for Planning Technology
Infrastructure
A Position Paper, Taking Wind Power Plants as an Example
Barbara S. Zaunbrecher and Martina Ziefle
Human-Computer Interaction Center, RWTH Aachen University, Campus-Boulevard 57, 52074 Aachen, Germany
Keywords: Social Acceptance, Energy Infrastructure, Renewable Energies, Planning Procedure, Energy Policy.
Abstract: It will be argued that there are major social gaps in the planning of complex energy infrastructure for public
spaces: the first "gap" concerns the question if social acceptance can be reliably measured. The second
“gap” refers to the lack of an integration of results from acceptance research into current planning
procedures. Taking wind farm planning as an example, both social gaps are discussed and an integrative
planning procedure is advocated. Finally, requirements for a user-centered planning process are formulated.
1 INTRODUCTION
Social acceptance of novel technologies has been a
popular research topic for more than a quarter of a
century. While former research concentrated mostly
on technological artefacts in the work context (e.g.
Davis, 1989), today, large technologies in the
context of energy supply are of utmost importance
with respect to sustainable technology diffusion.
Especially in the light of the turn towards renewable
energies, social acceptance of the associated infra-
structure such as wind power (WP) plants (on-
/offshore), (Devine-Wright, 2005; Zaunbrecher et
al., 2014), geothermal energy (Dowd et al., 2011,
Kowalewski et al., 2014) as well as transmission
lines (Devine-Wright and Batel, 2013, Atkinson et
al., 2004, Soini et al., 2011) received attention. For
infrastructures, e.g. WP plants or transmission lines,
the knowledge about technology acceptance is rich;
for others, e.g. storage technologies, detailed
analyses about perceived benefits or barriers are still
lacking. Though, what is mostly missing is a specific
call to action how to finally put these results from
social acceptance research into practice.
WP plants are chosen in this paper for two main
reasons: (1) For WP plants, a sound research basis
exists, providing a rich pool of acceptance-relevant
factors. (2) Wind farms currently being planned still
face considerable public resistance, showing that the
planning process can still be improved.
By conducting a literature review, the major
factors influencing the acceptance of a WP plant
project were summarized (cf. Appendix). Not only is
known how the physical appearance of WP plants
influences acceptance (size, color, distance), but also
how the relation between investors and operators
and the local community can help to foster public
perception. Further findings refer, e.g., to effects on
nature and the particular landscape in which the WP
plant is sited and how this can create support or
opposition towards the wind park.
Concerning the role of the public in the
technology acceptance discussion, two contradicting
positions are generally clashing. One is the public's
wish to be integrated into the planning process,
arguing that residents are the ones that “suffer” from
the infrastructure in the end, therefore requesting
participation as an inherent “right”. The other
traditional expert position is that lay peoples’
knowledge is too restricted to make reasonable or
reliable decisions. Also, it is often assumed that
public opinions are fuzzy so that they can neither be
patterned nor predicted. In addition, it is naturally
alleged that the more room for discussion is given to
the citizens in early stages of the developmental
process, the more space for developing a
contradictory position will be created (if you ask for
problems, you will receive them).
It will be pointed out that for the integration of
acceptance-relevant factors in the planning process,
two types of -what we term - “social gaps” are to be
addressed: (1) It is to be clarified what is under-
stood by the notion of “acceptance”, and how and if
60
S. Zaunbrecher B. and Ziefle M..
Social Acceptance and Its Role for Planning Technology Infrastructure - A Position Paper, Taking Wind Power Plants as an Example.
DOI: 10.5220/0005480600600065
In Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS-2015), pages 60-65
ISBN: 978-989-758-105-2
Copyright
c
2015 SCITEPRESS (Science and Technology Publications, Lda.)
it can be reliably measured, or even predicted
(Social Gap I). (2) It is to be addressed at which
stage in the planning process social acceptance
should be integrated (Social Gap II). These
questions will be discussed against the background
of wind farm planning and acceptance thereof, so as
to give concrete examples of acceptance-relevant
factors and milestones of the planning process.
2 SOCIAL GAP I:
IS ACCEPTANCE OF
COMPLEX INFRASTRUCTURE
MEASURABLE?
Acceptance deals with the approval, positive
reception and sustainable implementation of
technology. Acceptance research thus explores the
relation of usage motives and perceived barriers as
well as the attitudes toward the respective
technology, and the technological impact
assessment. Especially large-scale technologies are
viewed critical or at least ambivalent by the public
(Renn, 1998). They often escape from perceived
comprehensibility and controllability of people,
which in turn produces insecurity, fear or even
adverse aloofness (Siegrist et al., 2006, Ziefle and
Schaar, 2011). It has been shown that the perceived
risk of a novel technology and the probability of the
disapproval are negatively correlated with the
familiarity, the knowledge, and information depth
about a technology (Kowalewski et al., 2013, Arning
et al., 2013). Also, it was found that individual
factors (age, gender, technology generation,
personality) have a considerable impact on risk
perceptions and acceptance of large scale
technologies (Arning et al., 2013, Zaunbrecher et al.,
2014). Thus, social acceptance must be modelled as
a “product” of usage motives that militate in favour
of and against technology as well as situation-
specific evaluations, driven by individual needs and
demands. In short: Acceptance research has to
reflect the fragile trade-off between benefits and
barriers ascribed to a technology.
The question if this complex acceptance
“product” on the human side can be empirically
identified and reliably measured at all, can be clearly
answered with yes. This, however, requires a holistic
and integrative empirical methodology that allows
for a direct and practically oriented transfer of
acceptance research into early stages of the
development of a technology (Kowalewski et al.,
2013). Here, a combination of qualitative and
quantitative procedures is essential. While
traditional social science methods (focus groups,
stakeholder interviews on-site) properly reflect
users’ implicit and explicit knowledge as well as
generic attitudes, the determination of the decisive
trade-offs between conflicting motives and the
individual cognitive or affective weighing of factors
can be adequately captured by conjoint analyses
(Arning et al., 2013). In conjoint tasks, respondents
evaluate product profiles or scenarios, in order to
simulate decision-processes and to decompose the
preference of a product or scenario as a combined
set of attributes. Conjoint analyses thus show which
attribute influences the respondents’ choice the most
and which level of an attribute is valued the highest.
Thus, acceptance of large-scale technologies can
indeed be modelled and the decisive acceptance
“function” (balance between positive and negative
influencing factors) can be reliably determined.
3 SOCIAL GAP II:
HOW TO INTEGRATE
ACCEPTANCE IN
TECHNOLOGICAL PLANNING
The Social Gap II refers to the missing link between
insights from social science research (relevant
factors, acceptance modeling and decision
simulation) and the planning of siting of renewable
energy technologies. In the following, the existing
guidelines for planning WP plants are analyzed,
paying particular attention to the way in which
social acceptance and citizen participation are
represented.
The latest decree on planning and permit of WP
plants in in the federal state of North Rhine-
Westphalia (Germany) will be discussed as an
example for a framework for planning.
It is evident from these guidelines that the choice of
a location of a WP plant is solely based on technical,
legal, environmental, or economic factors such as
regulations on distance to housing and streets, or the
protection of natural reservoirs. Acceptance of wind
farms by the public is a topic that is only considered
in a very generic manner within these guidelines, in
the sense of “which measures can be taken to
increase acceptance” (Decree on Wind Power from
11th July 2011). However, these measures do not
focus on factors that might be valuable for the
citizens: the way of the planning process or the
design of the WP plant. Rather, they make a point of
creating added value for the local community.
SocialAcceptanceandItsRoleforPlanningTechnologyInfrastructure-APositionPaper,TakingWindPowerPlantsasan
Example
61
Measures to increase acceptance include designing
wind farms as “citizen wind farms”, in which local
residents can take part and also become
shareholders, the support of local social, cultural or
ecological projects by the operators, and the
introduction of reduced electricity prices. Citizen
participation is mentioned in the approach, but it is
only vaguely mentioned how this should be put into
practice (“Citizens should be included in the
planning and usage of wind power plants at an early
stage. This includes open discussions and
information events by the operators”, Section 2,
Decree on Wind Power from 11th July 2011).
In the literature, several models for the evaluation of
WP parks are presented. Wimmler et al. (2015)
provide an overview of multi-criteria decision
support methods for renewable energies, some of
which include “social acceptability” as an evaluation
criterion when it comes to the selection of the type
of energy. If social acceptability is included at all, it
is treated as a “stand alone” factor separated from
other factors such as visibility or costs. To explain
the shortcomings of such a model, the evaluation
criteria proposed by Cavallaro and Ciraolo (2005)
will be referred to. In their model, WP plants are
assessed according to different criteria such as
investment costs, fuel savings and realization time.
In addition, “social acceptability” is introduced next
to these objective criteria. Acceptance is treated as a
qualitative variable, ranging from “bad” to
“moderate”. Although the importance of social
acceptance and an early integration of the public are
basically acknowledged, it remains unclear on which
(data) basis the acceptability of the example projects
is determined. By treating social acceptability
separately, it is implied that it is independent from
other factors, although research proved the close
interrelationship between acceptance and e.g. costs
(cf. Appendix). Recapitulating, social acceptance in
WP planning is either
a. represented in the fuzzy concept of “information
and communication”, running parallel, but
separated from the planning phase (Figure 1), or
b. used as “black box” evaluation for possible
scenarios, without a common understanding what
contributes to acceptance (Figure 2).
Both procedures have conceptual disadvantages.
In the planning procedure (Figure 1), information on
the planning is given to the public, but the planning
is not influenced by acceptance issues raised,
because these are not scheduled as possible factors
to determine e.g. the plant’s location.
Leaving no room for alterations in the planning may
even lead to frustration because the public might feel
they have no real impact to influence decisions that
are more or less imposed in a top-down manner. A
process like this might look like an “alibi public
consultation” that seeks to gain agreement to already
fixed plans rather than openly discussing options.
Figure 1: Planning procedure according to the German
Federal Association of Wind Power (www.wind-
energie.de/themen/planung-und-repowering/planung).
Figure 2: Example set of criteria to assess WP plant
scenarios (Cavallaro and Ciraolo, 2005).
In the second model (Figure 2), social acceptability
is treated separately from other factors (investment
costs, visual impact etc.). However, because many of
these factors influence acceptance (cf. Appendix), it
makes no sense to treat social acceptance as a stand-
alone factor next to the other factors.
It has become obvious that social acceptance of
wind parks from a planning point of view is mainly
characterized by an ex-post perspective in
combination with a mandatory need to “inform”
citizens. If acceptance is considered at all in today’s
planning of technology infrastructure, it is at the
very end of the process when plans are more or less
fixed. Any amendments to the final plan are costly,
lead to delays and can only be realized in a very
limited way. What is lacking is the integration of
acceptance factors as early as in the design and
planning phase of the project. In order to have
sustainable planning solutions, we advocate a
planning model which integrates citizens, and, this
SMARTGREENS2015-4thInternationalConferenceonSmartCitiesandGreenICTSystems
62
way, knowledge from acceptance studies already in
early stages of an iterative planning process.
The idea of integrating social acceptance,
demands, and wishes early in the development
process has already been proposed for cell towers in
mobile communication development (Kowalewski et
al., 2013). Rather than treating acceptance as a
separate factor, we propose instead to integrate
social acceptance studies in the planning phase for
location and layout of WP plants by using the model
of a feedback loop (Figure 3). By integrating a
communicative feedback loop in the planning,
potential pitfalls (e.g. in choosing a location) can be
avoided. Next to distance and environmental
regulations, results from social acceptance studies on
WP plant locations can be taken into account in the
very beginning of the process. If planners know
early enough about locally important issues, main
argumentation lines for and against the infrastructure
as well as possible compensations, they can timely
adapt plans, rather than being confronted with
citizen protests when the precise plans are decided
upon. Because the literature analysis has shown that
acceptance is a complex phenomenon, and that some
factors can be operationalized qualitatively, others
quantitatively, the types of factors determine where
and how they can be integrated in the development
process. The acceptance-relevant factors were thus
grouped in thematic categories and in two categories
defining the type of factor (cf. Appendix). Examples
for thematic categories are “physical appearance”,
which refers to the outward appearance of a WP
plant or “environment”, taking into account those
factors that deal with the effect of the WP plant on
its natural surroundings. At this stage, acceptance as
a whole cannot be adequately represented in a model
or a simulation for the siting of wind farms as a
single “value” that ranges between two predefined
poles, e.g. 0 and 1. To come closer to a solution for
the integration, the factors were grouped into two
categories, “physical” and “latent”. Physical refers
to factors that, considered on their own, can be
represented by a numerical value, because they are
observable and can thus be quantified. Example
factors are the size of a wind farm, the distance to it,
financial benefits to the local community, the effect
on property values etc. Latent refers to factors such
as "perceived health risks", "place attachment" or
"local network of support" that cannot be
represented by a numerical value because of their
qualitative nature.
Simulations, e.g. for the siting of WP plants,
work with numerical variables such as potential
analysis, square meters of suitable surfaces etc. An
integration of latent, qualitative factors is thus
difficult should the model remain limited to
numerical variables. Nonetheless, acceptance factors
play an equally, if not more, important role and
should thus be considered in planning. What is
therefore needed is a model allowing for the
integration of qualitative next to quantitative factors.
Figure 3: Proposed framework for WP planning.
As shown in Figure 3, we propose to integrate
quantitatively measurable acceptance criteria at the
same stage as decision criteria which are based on
laws and regulations (distance to housing etc.).
Together, this data based input can be used for
simulations and planning scenarios. The added value
lies in the fact that certain siting and layout
scenarios, which would meet environmental and
other criteria set by laws, but not acceptance criteria,
would be ruled out from the very beginning. This
would result in scenarios which fulfill basic
acceptance criteria and in which acceptance is given
the same value over environmental and feasibility
criteria. In a next step, the proposed scenarios should
then be discussed with a representative group of
citizens, so public perception and acceptance factors
can be taken into account and fed back into the
scenario building. It is likely that the results will
have to pass this cycle iteratively in order to come to
a solution that is feasible and agreed upon.
4 CONCLUSIONS
A new process model for wind farm planning was
discussed to improve the integration of acceptance-
relevant factors. This process will require openness
from the side of the planners, not only to
SocialAcceptanceandItsRoleforPlanningTechnologyInfrastructure-APositionPaper,TakingWindPowerPlantsasan
Example
63
acknowledge the importance of social acceptance,
but also to give room to suggestions and
amendments to the scenarios. Besides, a thoroughly
planned communication and information concept is
needed, so that citizens can gain information and
competences to contribute to the decision-process.
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APPENDIX
Table 1: Acceptance factors in wind power plants (based on Devine-Wright, 2005 and Graham et al., 2009, extended).
Thematic area Type Specification Examplary sources
Physical
appearance
physical number of WP plants and height Dimitropoulos and Kontoleon (2009)
physical movement Bishop and Miller (2007)
physical color Lee (1989)
physical farm size and shape Sustainable Energy Ireland (2003)
Context and
landscape
physical location Ek (2005)
physical distance Bishop and Miller (2007), Swofford and Slattery
(2010), Sustainable Energy Ireland (2003)
physical cumulative effects (neighboring projects),
proximity to important features
Graham et al. (2009)
latent local impact of construction (building site) Graham et al. (2009)
latent fit in landscape, former use and perception of site Jobert et al. (2007)
physical visibility Jobert et al. (2007), Johansson and Laike (2007)
physical ownership of territory (communal/ private) Jobert et al. (2007)
latent local experience with wind power Krohn and Damborg (1999)
Environment physical loss of landscape, habitat and fauna Álvarez-Farizo and Hanley (2002)
latent impact on specific location (cliffs) Álvarez-Farizo and Hanley (2002)
latent environmental characteristics of siting area Dimitropoulos and Kontoleon (2009)
physical effects on local environment Graham et al. (2009)
Economic reasons physical costs Álvarez-Farizo and Hanley (2002)
physical economic benefits Baxter et al. (2013), Dimitropoulos and Kontoleon
(2009), Graham et al. (2009), Jobert et al. (2007)
latent economic fairness Baxter et al. (2013)
physical effect on property values Graham et al. (2009)
latent effect on tourism Jobert et al. (2007)
physical ownership of the park, financial participation Jobert et al. (2007), Sustainable Energy Ireland
(2003)
Health latent health risks Baxter et al. (2013), Songsore and Buzzelli (2014)
latent sound Pedersen et al. (2009)
Social reasons latent intra-community conflict Baxter et al. (2013), Graham et al. (2009)
latent community benefits Cowell et al. (2011)
latent effect on personal daily quality of life Johansson and Laike (2007)
latent place attachment Vorkinn and Riese (2001)
Decision-making
and stakeholders
latent Patterns, in which decision-making and planning
processes are carried out
Dimitropoulos and Kontoleon (2009)
latent fairness of the process and outcome Gross (2007), Songsore and Buzzelli (2014)
latent information and participation Jobert et al. (2007), McLaren Loring (2007)
latent energy policy support Wolsink (2000)
latent local integration of the developers and network of
support from local actors
Jobert et al. (2007)
latent perception of developer Graham et al. (2009)
Demographics physical age, income Ek (2005)
latent interest in environmental issues Ek (2005)
latent attitude towards wind power in general Graham et al. (2009)
Ethics and Values latent national good/ security of supply Graham et al. (2009)
Symbolism latent representation of wind turbines Pasqualetti (2000)
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