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Discussion of combined results

1st Hypothesis

2nd Hypothesis

3rd Hypothesis

The findings of this overall comparison (of urban and rural areas together) indicate that the factor “age” is having an impact on the acceptance of wind energy. Among very young people (under 31 years) the of acceptance of wind energy seems to be generally high as the low level of acceptance is missing at all. The trend of a decrease of acceptance with an increase of age cannot be confirmed in the overall comparison as nearly 60% of the respondents of each elderly age class (above 40 years) shows a stable high level acceptance of wind energy still.

Even though the overall comparison shows that younger people tend to be more supporting of wind energy than elderly people, the conclusions from these results are subject to limitations. One reason, which could have influenced the results, could derive from the merging of the samples from urban and rural areas as both samples contain a huge disparity between the respondents of each area in terms of age classes. While the Potsdam sample contained mainly respondents with an age of 20 to 30 years and nearly no respondents from the age classes above 50 years Results of the survey in Potsdam, the sample of the Brandenburg region mainly contains people above 50 years old Results of the frequency analysis and comparison of the results to the 2005-survey. Hence it is most likely that residents of Potsdam represent the younger age classes only, while the elderly age classes mainly are represented by the residents of the rural areas of Brandenburg. This most likely leads to an overlapping of the factors “rural/urban area” and “age”. In other words it is not clear whether the acceptance is mainly influenced by the type of area (urban/rural), in which the respondents live in or rather determined by their age. Another limitation could also derive from “hidden factors”, which were not investigated in this project, like the social-psychological factor “place-attachment”. This factor describes that people are attached and or even identify themselves with the region they live in (Strazzera & Mura & Contu 2012, p.335). As a large number of younger respondents in the survey of Potsdam were students, they usually did not grow up in Potsdam or have been living there for a long time Results of the survey in Potsdam. This is in contrast to the elderly people of the rural areas, which mainly lived there for more than ten years Results of the frequency analysis and comparison of the results to the 2005-survey. Hence if the results show that there are some differences between these age classes in terms of acceptance it also could derive from the factor “place attachment”. Elderly people in this case usually lived longer in the regions investigated in this project and therefore their “place attachment”, which is stronger than among the students living in Potsdam, leads to less acceptance of wind energy besides their age.

  • Strazzera, E., Mura, M., Contu, D. 2012,’ Combining choice experiments with psychometric scales to assess the social acceptability of wind energy projects: A latent class approach’,Energy Policy, vol. 48, pp. 334–347.

4th Hypothesis

The results of the survey confirm the Hypothesis “The better people are informed the higher is their acceptance of wind energy”. To further verify the hypothesis, it got tested that nobody in Potsdam with a low acceptance of wind energy, within the sub sample of respondents, had a high level of information. This was the case in Potsdam but on the other hand not in Havelland Fläming. Here 27 respondents with a high or rather high level of information had a low acceptance of wind energy. This could be linked to the ongoing debate and rejection of wind turbines in the rural areas of Brandenburg. Recently a citizens' initiative against more wind mills and a higher distance to buildings got rejected (“Die Volksinitiative”, 2016).

It is further necessary to mention that this Hypothesis has limitation: it only indicates the personnel perception of how well the respondents feel informed and does not indicate the actual level of knowledge. It also depends on peoples interest or effort to get informed and therefore forms their attitude towards wind energy (Yuan et. al, 2014). Additionally there was only one question dealing with the level of information in both questionnaire, to be compared with. This again sets a limitation to the knowledge about the actual level of information of the respondents. To further test the information level of the respondents, the question “How well do you feel informed about wind energy?” (2.6 in the Havelland and 3.7 in the Potsdam) could be linked to the Matrix question, were general statemented of wind energy are made. The limitation here is that some statements are of subjected perspective and are for further scientific research (e.g. noise production, endangerment of wildlife).

→ mention results from Havelland-Fläming concerning Information


“Die Volksinitiative”, 2016: 'VolksInitiative – Rettet Brandenburg', Märkische Heide, Online at:

Yuan, X.; Zuo, J.; Huisingh, D.: 2014, Social acceptance of wind power: a case study of Shandong Province, China. Journal of Cleaner Production 92 (2015) 168-178

5th Hypothesis

(Q3.7/Q2.6) How well do you feel informed about wind energy?

(Q5/Q5) Opinion on renewable energies in general

This question is related to the overall assumption that people in urban areas have a higher acceptance of wind energy than people living in rural areas. Although this question asked about renewable energies in general, wind energy is indirectly related to that and could play a big role for respondents in rural areas when answering with “rather against” or “against” (compare to Question five in Havelland-questionnaire). This could be explained with the different spatial relation to wind turbines in rural and urban areas. In our case people from Potsdam tend to be more positive about renewable energies in general because their points of contact with renewable's such as wind turbines are less intensive than of people who are living in direct vicinity to them. Because of that urban residents might also know less about disturbing effects of renewable energies, such as noise, visual constraints or disturbing shade, and therefore tend to be more neutral as well. Nevertheless it must be interpreted with caution because the question was not directly related to wind energy. There might also be more factors – such as the age of respondents – than the urban-rural comparison influencing the attitude towards renewable energy in this question.

Matrix questions (only those, which are comparable)

(Q7a/Q6.8/Q4.8) Wind energy as an alternative to nuclear energy?

(Q7b/Q6.1/Q4.1) Wind energy - the future of the next generations?

(Q7c/Q6.3/Q4.3) Wind energy creates jobs, strengthens economy?

(Q7d/Q6.11/Q12.2) Wind turbines produce noise?

(Q7e/Q6.5/Q4.5) Wind energy is a technical progress?

(Q7f/Q6.18/Q12.9) Saving energy is better than promoting wind energy ?

(Q7g/Q6.15/Q12.6) Wind turbines endanger due to ice falling from the blades?

(Q7h/Q6.9/Q4.9) Wind turbines are a possibility for capital investment?

(Q7i/Q6.12/Q12.3) Wind turbines are reflecting the sun?

(Q7j/Q6.2/Q4.2) The use of wind energy slows down climate change?

(Q7.k/Q6.7/Q4.7) Wind energy conserves the fossil energy sources?

(Q7l/Q6.14/Q12.5) Wind turbines endanger the wildlife?

(Q7m/Q6.10/Q12.1) Wind turbines destroy the landscape?

(Q7n/Q6.13/Q12.4) Wind turbines produce a flickering shade?

(Q14/Q13/Q20) Age of respondents

The age groups of both urban and rural areas are contradictory. While the majority of respondents from urban areas are between 20 and 40 years, most of the respondents from rural areas are between 51 and 70 years old. This age tendency is approximately similar to the average age of both areas. In Potsdam the average age in 2015 was 42 years and the main age group is between 27 and 50 years (Statistischer Informationsdienst, 2012). Figure x displays the age distribution in Potsdam in 2011 and shows a big proportion in the age groups of 20 to 35 years and 40 to 55 years.

Whereas current prognoses state a out-migration and shrinkage of the younger generation in the region of Havelland-Fläming (Regionale Planungsgemeinschaft, 2006). Table x presents the development of age groups in the region from 1990 to 2020. Here it is obvious that especially the amount of younger generation tend to shrink while the amount of the more seasoned generation becomes bigger.


Regionale Planungsgemeinschaft, 2006:“Region Havelland-Fläming”, Landesamt für Bauen und Verkehr, Brandenburg Regional 2006

Statistischer Informationsdienst, 2012: “Bevölkerungsprognose der Landeshauptstadt Potsdam 2011 bis 2030”, 4/2012, Bereich Statistik und Wahlen, Potsdam

overall_discussion.txt · Last modified: 2016/08/01 17:35 by markus.guenther