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Method of Analysis

The analysis of the results consists of two parts. In a first step, a frequency analysis is performed. In this way, the response rate of each individual question is assessed, making the identification of major trends possible. Moreover, the results of the 2016 survey are juxtaposed to those of 2005. This allows identifying potential development and changes over time. (Click here to jump directly to the respective results)

Furthermore, a qualitative analysis of the received comments in the open answers was conducted, providing the major trends within the comments. (Click here to jump directly to the respective results)

In a second step, the results of 2016 are evaluated with the intention of receiving further insights on the factors shaping the respondents' opinion on wind energy. However, such answer is not easily found through simply asking one question in a questionnaire as most interviewees do not know themselves exactly what makes their mind. Therefore different methods are used here in an attempt of understanding better this complex issue: subsampling, correlation analysis and statistical hypothesis test. This step was based on the findings of the synopsis' findings on the most considered factors (factors identfied in literature review) and thus also served as a preliminary empirical verification of literature's statements. The cited sources in this methodology thus all were part of the analysed literature.

Statistical Analysis - Subsampling and Correlation Analysis

In the first place, subsampling was applied in order to identify the existence of a group of particular attitude, e.g. NIMBY, and to better understand the reasons behind the level of acceptance of specific groups within the sample. Thus, by creating a subsample of the responses from either the group of opponents or of supporters of wind energy, an analysis of their singular reasons was possible.

Secondly, for correlation analysis, hypotheses were created based on the results of the previously created synopsis, so that they represent a selection of the main factors of influence on social acceptance from literature. Following this selection, the factors were chosen according to the availability of suitable questions in the questionnaire that allowed the respective analysis. The analysed factors were: landscape destruction, the factor of distance (Euclidian and perceived), supply of information, timing of information and direct benefits. The hypotheses are that the acceptance level depends on:

  • Perception of the destruction of the landscape by wind farms;
  • Distance and density of wind turbines in relation to settlements;
  • Scale and timing of information on the wind energy projects;
  • Receiving economic benefits from the wind energy projects.

For each, the question 7 on the general acceptance of wind energy is statistically evaluated against one or more questions on possible relations. The choice of questions is explained in detail below. This assessment is mainly conducted with the Chi-square test which can be applied to determine whether the sample is statically significant as well as whether there is a significant correlation between the variables. However, Chi-square testing does not tell how strong the correlation is. This requires correlation analysis that identifies the coefficient of correlation, which describes the strength of the correlation. For this analysis however, both variables have to be continuous (e.g. social acceptance ranging from “in favour” (5) to “against” (1)). This type of variables was only available for one analysis, so that most factors are analysed with Chi-square tests.

Due to the matter of better readability, the used questions here have been abbreviated. However, the entire questions can be found via the links behind the abbreviations or at the bottom of this page under: 'Questions behind the used abbreviations'. For a full overview of the questions, please refer to the questionnaire. For the purpose of analysis, the results have not been differentiated into the different municipalities, but it has been looked at all results from the rural area.


1) Beyond ‘Not-in-my-backyard’ (NIMBY)

The ‘Not-in-my-backyard’ (NIMBY) term is widely used within wind energy literature (e.g. Aitken 2010, Wolsink 2000, Cohen et al.2014 and see also factors found in literature review). The term describes the phenomenon of people who are generally not against wind energy and renewable energies but are opposing its development on the local level. They are thus against wind energy as soon as it interferes with their personal surrounding, described metaphorically with the term 'backyard' (Aitken 2010). More recently, this term has been criticised as a simplistic understanding of this phenomenon that actually hinders the understanding of the reasons and motivations of the people by merely blaming their ignorance (e.g.Burningham et al. 2006, van der Horst 2007, Devine- Wright 2009). Consequently the need for a more complex approach that allows a constructive debate about the topic has been addressed (e.g. Bidwell 2013, Aitken 2010).

In this first step of analysis it shall thus be verified whether the concept of NIMBY is able to capture the attitude of the interviewed people in rural Brandenburg. The first subsample shall identify the group of people displaying a NIMBY attitude by assessing the answer behaviour of the respondents with regard to three filtering questions. Those respondents will be selected that consider themselves as generally in favour of wind energy (Q.7: answers 1, 2 or 3), but also oppose wind energy on the local level (Q.11: answers 5 or 6 and Q.18: answers 4 or 5). After having identified this subgroup it will be assessed which disadvantages they see in wind energy (Q.6: every answer) and under which conditions they would favour or accept wind energy facilities within their neighbourhood (Q.12: every answer).

The results of this approach are limited in their reliability or rather transferability on other cases as it is based on a narrow concept of NIMBY. It thus cannot explore the NYMBY phenomenon in its total complexity, but it may serve as a step forward in the research about social acceptance and wind energy.


Q.7: answers 1, 2 or 3 vs. Q.11: answers 5 or 6 and Q.18: answers 4 or 5

- Click here to jump directly to the respective results

2) Preferences of wind energy opponents vs wind energy supporters

For ten years this area in Brandenburg has been characterised by development of wind energy. Furthermore, according to the national energy policy objectives new facilities are going to be realized in the area, as planned in the actual regional plan (Regionalplan 2020, 2015). Although a part of the population welcomes this development, some residents express a clear dissent, which is most often voiced within the organisational structure of citizen initiatives, “Bürgerinitiativen” (Zilles & Schwarz 2015; e.g. the initiators of the recently failed petition for a referendum Volksinitiative Rettet Brandenburg, or Waldkleeblatt). It is therefore fundamental to face this discontent by identifying the conditions that could increase social acceptance. This is assessed by the juxtaposition of wind energy opponents and supporters with their respective preferences. To assess this, the opponents and the supporters are first to be identified, through the analysis of the question 7 results, which inquired whether the interviewee was for or against wind energy. In the next step it is measured how the identified sub groups answered the question 12, where the interviewee chose the conditions under which they would perceive wind energy as reasonable within their neighbourhood.

Subsampling: Q.7: answers 4 or 5 or Q.7: answers 1 or 2 and Q.12: every answer

- Click here to jump directly to the respective results

Correlation analysis

3) The influence of landscape destruction on social acceptance

The landscape of Brandenburg has since long been shaped by human activity, starting with the exploitation of land for agriculture, forestry and livestock, and later by industrialisation and urbanisation. The wind energy development is yet another change that introduces an artificial vertical element into the flat landscape of the region. From literature (e.g. Caporale & De Lucia 2015, Hübner et al. 2013) as well as from the results of the questionnaire (see frequency analysis' results for Q.6 and Q.15.4) emerges that landscape destruction is perceived as one of the major negative aspects of wind energy. Therefore, is significant for the goal of our research to evaluate if supporters and opponents have a different opinion on the issue. For this analysis the general acceptance of wind energy (Q.7) was linked to the perception of the impact on landscape Q.6.10. The relation's significance was then checked with a Chi-square test.

Chi-square test:

Impact on landscape: Q.7 vs. Q.6.10

- Click here to jump directly to the respective results

4) The influence of distance to wind parks and density of wind parks on social acceptance

We have seen that the installation of wind energy turbines is frequently met with resistance at local level. Some studies have proofed since though that greater distance does not increase social acceptance (Wüstenhagen et al. 2007; Jones & Eiser 2010; Petrova 2016). As the topic of distance to settlements nevertheless remains a controversial topic (e.g. Volksentscheid Rettet Brandenburg) it seemed valuable to review the results of the present survey under this perspective. Furthermore, the acceptance may also depend on the perceived distance (Fast 2013; Huesca et al. 2016), which could be influenced by the density of wind turbines in the vicinity.

In order to check the significance of influence of distance to wind turbines on acceptance in the rural Brandenburg first a GIS analysis was needed. Through GIS, the distance from the centre point of each village to the nearest wind turbine as well the median distance in each village was identified. The data for the analyse is from the Landwirtschafts- und Umweltinformationssystem des Landes Brandenburg (LUIS-BB) concerning immission control (Landesamt für Umwelt Brandenburg, 2016). However, only those wind turbines which were under construction or already in operation at the time of the survey were considered, not those that had only been authorized or were still in the approval procedure. For the calculation of the median distance, all wind turbines within a 5km radius from each village’s centre point were considered.

The density was calculated by two different ways, varying with the two different scales that were looked at. For the analysis of the municipality scale, the number of turbines within the municipality’s boundaries was counted and then divided by the area of the municipality. For assessing the relation on the scale of the villages, the turbines within the above-mentioned 5km radius around the villages were counted and the number divided by the area of this buffer, which is in fact the same size for all villages (78,54km2). The 5km buffer was arbitrarily defined trying to considering not only the field of view that people have from their houses but also whenever they go for a walk.

For the perceived distance, the question 17 was used, where the interviewees were asked to indicate how far they live from the next wind turbines.


Perceived distance: Q.7 vs. Q.17

- Click here to jump directly to the respective results

5) The influence of the quality and timing of information on social acceptance

In the past years the call for more qualitative public participation has become increasingly frequent throughout many public sectors - including the planning context (e.g. Friedl & Reichl 2016). Participation can take different forms, usually categorized in information, consultation and participation (Arbter & Handler 2005). The specific choice of public participation depends to large extents but not only on the legal framework. It is moreover a matter of suitability of a specific form of participation within the respective decision-making process. Not all public policy decisions require or even allow for participation but may rather be dealt with exclusively by the public institution or authority. Nevertheless, in participation research it is often presumed that generally participation does not only increase legitimacy of state activities but also helps to increase social acceptance and create an active political citizenry (e.g. Newig 2012).

On that account it seemed valuable to examine the participation in the project region. Unfortunately, it was not possible to assess participation in a broader sense as the questionnaire did not contain but two questions analysable for this topic. Consequently, it had to be focused on the information management. Therefore, it is looked at the linkage between the acceptance of wind energy and the citizens' perception about first the timing of the information (Q.9) and second the scale of information received on the wind projects (Q.10). These relations are then tested with the chi-square test on their significance.

Chi-square test:

a) Timing: Q.7 vs. Q.9

b) Scale: Q.7 vs. Q.10

- Click here to jump directly to the respective results

6) The influence of direct benefits on social acceptance

Research on social acceptance has not only recently discovered that local acceptance of renewable energy projects is linked to economic gains that reach the local population (e.g. Khorsand et al. 2015, Guo et al. 2015,Zoellner et al. 2005). This can be in the form of job creation or socio-economic benefits (Caporale & De Lucia 2016) but also for example lower electricity prices (e.g. Petrova 2016). It is thus a question of direct benefits for the population that also bears the costs of the new projects in terms of a change to their familiar surroundings. Consequently, it appeared interesting to verify whether in the actual case study a link could be distinguished between the perception that a positive benefit sharing takes place and acceptance of wind energy. In other words, it is to assess whether those that do feel that the benefits from the wind energy projects reach the vicinity are more positive towards wind energy or not. This analysis was performed by conducting several chi-square tests between the acceptance question 7 and several results from questions on local job creation, on income generation for the municipalities and on the general economic profitability of wind energy. For the creation of local jobs the results of the question 6.3 that asked for general views on wind energy could be compared to the those of question 12.6 that inquired after reasons making wind energy reasonable. The same comparison was possible for the topic income generation for local municipalities with the results of question 6.6 and question 12.5. The link of general economic profitability of wind energy and acceptance was assessed only via the question 6.4

Chi-square test:

a) Creation of jobs: Q.7 vs. Q.6.3 AND Q.7 vs. Q.12.6

b) Income for the municipality: Q.7 vs. Q.6.6 AND Q.7 vs. Q.12.5

c) Economic profitability: Q.7 vs. Q.6.4

- Click here to jump directly to the respective results

Summing up

Certainly, the results of the conducted survey and the analysis have to be regarded while considering their limitations; be it the relatively small sample, the restricted questionnaire that allowed only a simplified analysis of otherwise complex factor networks or the limited applicability of advanced statistical verification methods (for a detailed discussion of the limitations, see Limitations). Nevertheless, does this combination of a basic frequency analysis with a statistical analysis of specific questions enable a first empirical verification of not only publicly proclaimed concerns about the public attitude on wind energy but also widely-used arguments in the literature. The results can therefore be of valuable use for practitioners in the field as well as scholars working on the topic of public acceptance of wind energy.


Aitken, M 2010,' Why we still don’t understand the social aspects of wind power: A critique of key assumptions within the literature’, Energy Policy, vol. 38, pp. 1834–1841.
Arbter, K, Handler, M et al. 2005, 'Das Handbuch. Öffentlichkeitsbeteiligung. Die Zukunft gemeinsam gestalten', Österreichische Gesellschaft für Umwelt und Technik (ed.).
Bidwell, D 2013, 'The role of values in public beliefs and attitudes towards commercial wind energy', Energy Policy, vol.58, pp. 189-199.
Burningham, K, Barnett,J, Thrush,D 2006, 'The Limitations of the NIMBY Concept for Understanding Public Engagement with Renewable Energy Technologies: A Literature Review', Working Paper 1.3, School of Environment and Development/University of Manchester, Manchester.
Caporale, D & De Lucia C 2015,' Social acceptance of on-shore wind energy in Apulia Region (Southern Italy)', Renewable and Sustainable Energy Reviews, vol. 52, pp. 1378-1390.
Cohen, J.J., Reichl, J.,Schmidthaler, M. 2014, 'Re-focussing research efforts on the public acceptance of energy infrastructure: a critical review', Energy, vol. 76, pp. 4–9.
Devine-Wright, P 2009, 'Rethinking NIMBYism. The role of place attachment and place identity in explaining place-protective action,' Journal of Community and Applied Social Psychology, vol. 19(6), pp.426–441.
Friedel, C & Reichel, J 2016, 'Realizing energy infrastructure projects - A qualitative empirical analysis of local practices to address social acceptance', Energy Policy, vol. 89, pp. 184-193.
Guo, Y; Ru, P; Su, J & Anadon L 2015,' Not in my backyard, but not far away from me: Local acceptance of wind power in China', Energy, vol. 82, pp. 722-733.
Hübner, G & Löffler, E 2013,' Wirkungen von Windkraftanlagen auf Anwohner in der Schweiz: Einflussfaktoren und Empfehlungen', Abschlussbericht, Halle.
Hübner, G & Pohl, J 2015, 'Mehr Abstand - mehr Akzeptanz? Ein umweltpsychologischer Studienvergleich', Fachagentur Wind an Land, Berlin.
Huesca, M E; Sheinbaum-Pardo, C & Köppel, J 2016, 'Social implications of siting wind energy in a disadvantaged region – The case of the Isthmus of Tehuantepec, Mexico', Renewable and Sustainable Energy Reviews, vol. 58, pp. 952–965.
Jones, C & Eiser, R 2010, 'Understanding local opposition to wind development in the UK - How big is a backyard', Energy Policy, vol. 38 pp. 3106–3117.
Khorsand, I; Kormos, C; MacDonald, E; Crawford, C 2015, 'Wind energy in the city. An interurban comparison of social acceptance of wind energy projects', Energy Research & Social Science 8, pp. 66–77.
Peters, J 2013, 'Landschaftsveräderungen im Spiegel der Gesischte - Wie gravierend ist die Transformation von Engergielandschaften', in Bernd Demuth et al., Energielandschaften - Kulturlandschaten der Zukunft?, Bundesamt für Naturschutzt, Bonn, pp. 138-157.
Petrova, M 2013, 'NIMBYism revisited: public acceptance of wind energy in the United States', Wiley Interdisciplinary Reviews: Climate Change, vol. 4 (6), pp. 575-601.
Petrova, M 2016, 'From NIMBY to acceptance: Toward a novel framework - VESPA - For organizing and interpreting community concerns', Renewable Energy, vol. 86, pp. 1280–1294.
Newig, J 2012,’More effective natural resource management through participatory governance? Taking stock of the conceptual and empirical literature – and moving forward’, in Hogl, K, Kvarda, E, Nordbeck, R & Pregernig, M (eds), Environmental Governance, Edward Elgar Publishing Limited, Cheltenham, pp. 46-69.
Landesamt für Umwelt Brandenburg, 2016, Windkraftanlagen des Landes Brandenburg, (10.07.2016).
van der Horst, D 2007, 'NIMBY or not? Exploring the relevance of location and the politics of voiced opinions in renewable energy siting controversies', Energy Policy, vol. 35, pp. 2705–2714.
WindTechKnow (Regional Wind Technology And Knowledge Transfer Strategies) (2005): Einstellung-en und Meinungen zur Windenergie Befragung unter betroffenen Bürgern in der
Region Havelland-Fläming - Ergebnisbericht Oktober 2005.
Wolsink, M 2000, 'Wind power and the NIMBY-myth: institutional capacity and the limited significance of public support, Renewable Energy, vol. 21, pp. 49–64.
Wüstenhagen, R; Wolsink, M & Bürer, M J 2007, 'Social acceptance of renewable energy innovation - An introduction to the concept', Energy Policy, vol. 35, pp. 2683–2691.
Zilles, J & Schwarz, C 2015, 'Bürgerproteste gegen Windkraft in Deutschland', Informationen zur Raumentwicklung, vol. 6, pp. 669-679.
Zoellner, J, Ittner, H, Schweizer-Ries, P 2005, 'Perceived Procedural Justice as a Conflict Factor in Wind Energy Plants Planning Processes', St. John’s College, Oxford.

Questions behind the used abbreviations

(For a full overview of the questions, please refer to the questionnaire)

  • With which statements regarding wind power do you agree or not agree?
  • Wind energy promotes the economy and creates jobs. Do you agree or not agree?
  • The use of wind energy is economically viable and profitable. Do you agree or not agree?
  • Wind turbines lead to higher revenue for the municipalities. Do you agree or not agree?
  • Wind turbines destroy the landscape. Do you agree or not agree?

  • Are you generally for or against the use of wind energy?
Q.7: answers 1 or 2
  • 'in favour' or 'rather in favour'
Q.7: answers 1, 2 or 3
  • 'in favour', 'rather in favour' or neutral
Q.7: answers 4 or 5
  • 'rather against' or 'against'

  • According to your opinion when did you hear about the wind energy projects in your neighbourhood?
  • Answers' range: Early - Just in time - Too late - Only when everything was already decided

  • According to your opinion to what extent were you informed about the wind energy projects in your neighbourhood?
  • Answers' range: Completely - Enough - Too little - Not at all

  • How did you react when you learned that in your neighbourhood wind turbines are planned?
Q.11: answers 5 or 6
  • 'I spoke against it' or 'I tried to stop the project'

  • Under what conditions would you consider the use of wind energy as meaningful in your


  • If the municipality would earn more from it. Yes or no?
Q. 12.6
  • If jobs would be created in the region. Yes or no?

  • According to your estimate how far is the distance from your house to the next wind turbine?
  • Answers' range: approx. 800m - approx. 1.000m - approx. 1.600 m - approx. 3.000m - More than 3.000m - Do not know

Q. 18
  • According to your opinion how fare shall wind turbines be at least away from homes?
Q.18: answers 4 or 5
  • 'approx. 3.000m' or 'more than 3.000m'


research/rural_areas/common_methodology/analysis.txt · Last modified: 2017/02/02 16:48 by admin