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Community Attitudes Toward Local Wind Energy Projects

Measures awareness, support, and concerns among residents near a wind energy project — covering noise, visual impact, trust in the developer, and perceived local benefits. An AI follow-up interview digs into the real reason behind each respondent's level of support, giving developers and utilities the qualitative context behind the numbers before community meetings or permitting decisions.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

13 questions · ~7 min
Q01
Message

Thanks for sharing your views on the wind energy project near you! This survey takes about 5 minutes and helps the project team understand what matters most to the community.

Q02
Multiple ChoiceRequired

Before today, how aware were you of the wind energy project planned or operating in your area?

  • Never heard of it until now
  • Heard about it but knew few details
  • Fairly informed about it
  • Very informed — I've followed it closely
Q03
Opinion ScaleRequired

Overall, how supportive are you of this wind energy project?

Scale: 0 – 10
Min:Strongly opposedMax:Strongly supportive
Q04
MatrixRequired

How concerned are you about each of the following potential impacts of the project?

6 rows × 5 columns
  • Noise from turbines
  • Visual impact on the landscape
  • Effect on local property values
  • Impact on birds and wildlife
  • Construction traffic and disruption
  • +1 more
Columns: Not concerned · Slightly concerned · Moderately concerned · Very concerned · Extremely concerned
Q05
Best–Worst Trade-off (MaxDiff)Required

Which of these potential community benefits matter most to you, and which matter least?

  • Lower local electricity bills
  • New local jobs during construction and operation
  • Increased tax revenue for the town or county
  • A community benefit fund or payments to nearby residents
  • Reduced reliance on fossil fuels
  • Investment in local infrastructure (roads, schools)
  • Improved local air quality
Pick best & worst per setBest:Matters mostWorst:Matters least
Q06
Multiple ChoiceRequired

How much do you trust (Replace with developer/utility name) to follow through on its commitments to the community?

  • Not at all
  • A little
  • A moderate amount
  • A lot
  • Not sure / no opinion
Q07
Rating Scale

How would you rate the clarity and frequency of communication you've received about this project so far?

Range: 1 – 5
Min:Very poorMax:Excellent
Q08
AI Interview

Explore the specific reason behind the respondent's support or opposition score, anchoring on which single factor — noise, visual impact, property values, wildlife, trust in the developer, or local benefits — weighs heaviest for them. If they scored near the middle, probe what would need to change to move them clearly toward support or opposition. If they mentioned low trust or poor communication, ask for a concrete example of what went wrong or what better communication would look like.

Q09
Long Text

Is there anything else about the project, the process, or the developer's communication that you'd like decision-makers to know?

Q10
Multiple Choice

About how far is your home from the nearest planned or existing turbine?

  • Less than 1 mile
  • 1 to 3 miles
  • 3 to 5 miles
  • More than 5 miles
  • Not sure
  • Prefer not to say
Q11
Multiple Choice

Which best describes your relationship to the local area?

  • Homeowner living here year-round
  • Renter living here year-round
  • Seasonal or part-time resident
  • Local business owner
  • Landowner leasing to the project
  • Prefer not to say
Q12
Multiple Choice

Which age group do you fall into?

  • Under 25
  • 25-34
  • 35-44
  • 45-54
  • 55-64
  • 65 or older
  • Prefer not to say
Q13
Message

That's everything — thank you for your time. Your responses will be compiled into a community feedback report shared with the project team to guide outreach and planning decisions.

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

How it compares

We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.

Why this template

  • Includes an AI follow-up interview that explores the specific reason behind each respondent's support or opposition score, giving developers qualitative context before permitting decisions or community meetings
  • Covers the full picture with a concern matrix (noise, visual impact, etc.), a max-diff exercise ranking which community benefits matter most, and a trust question specific to the developer/utility
  • Captures practical context like distance from the nearest turbine and relationship to the local area, plus an open-ended question on communication and process, so results segment by proximity and stake
  • Rating question on communication clarity and frequency turns the survey into an ongoing feedback loop developers can act on before the next meeting, not just a one-time snapshot

QuestionPro

Wind Energy Power Survey Questions Template

This is a static, fielding-ready survey template covering wind energy attitudes and awareness, built on QuestionPro's established survey platform. It's a reasonable starting point for basic sentiment tracking but reads as a fixed question set rather than one designed to surface the 'why' behind each respondent's score. There's no indication of adaptive interviewing or automated qualitative analysis on the page.

What it does well

  • Backed by an established, well-known survey research platform with broad question-type support
  • Ready-to-deploy template requiring no custom build for basic wind energy attitude tracking
  • Likely supports standard analytics and reporting dashboards typical of QuestionPro's toolset

Where it falls short

  • No adaptive AI follow-up interview to probe the specific reasoning behind a support/opposition score
  • No voice AI interview option for richer qualitative capture
  • No automated per-response quality scoring or transparent AI prompt methodology

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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