모든 템플릿

Shift Scheduling Satisfaction Survey for Hourly Teams

Measures how predictable, swappable, and fair hourly employees find their work schedules, plus early burnout signals like clopening shifts and exhaustion. Includes an AI follow-up that reconstructs a specific recent scheduling incident — a denied swap or a last-minute change — instead of relying on general impressions.

샘플 질문

템플릿에 포함된 내용을 미리 확인해 보세요. 모든 질문은 설문 공개 전에 자유롭게 수정할 수 있습니다.

질문 13개 · 약 7분
Q01
메시지

Thanks for taking a few minutes for this! We want to understand how your work schedule actually feels week to week — predictability, swaps, fairness, and workload. Your responses are completely confidential and anonymized. Your honest answers help us fix real problems. About 5 minutes.

Q02
의견 척도필수

How predictable is your work schedule week to week?

척도: 17
최소:Very unpredictable최대:Very predictable
Q03
객관식필수

In the last month, how much advance notice did you typically get before a schedule was posted or changed?

  • Same day
  • 1-2 days
  • 3-6 days
  • 1-2 weeks
  • More than 2 weeks
Q04
평점 척도필수

How easy is it to swap a shift or find coverage when you need to?

범위: 15
최소:Very difficult최대:Very easy
Q05
객관식

In the last 30 days, how often did a shift-swap or coverage request you made get approved?

  • I didn't request any swaps
  • Never approved
  • Sometimes approved
  • Usually approved
  • Always approved
Q06
매트릭스필수

How much do you agree with each statement about how schedules are handled on your team?

4개 행 × 5개 열
  • Schedules are assigned fairly across the team
  • Preferred shifts and days off are distributed equitably
  • Favoritism affects who gets the best shifts
  • Managers explain the reasoning behind schedule changes
: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q07
의견 척도필수

In the last 30 days, how often has your work schedule left you feeling physically or mentally exhausted?

척도: 15
최소:Never최대:Always
Q08
객관식필수

In the last 30 days, how many times did you work a closing shift followed by an opening shift with less than 11 hours in between?

  • 0 times
  • 1-2 times
  • 3-5 times
  • 6+ times
Q09
최선·최악 선택형(MaxDiff)필수

Which of these would do the most, and least, to improve your satisfaction with scheduling?

  • More advance notice of my schedule
  • Easier shift swaps or coverage requests
  • More input on my preferred shifts
  • Fewer back-to-back closing/opening shifts
  • More consistent hours week to week
  • Better communication about schedule changes
  • More say over which days I get off
세트별 최선·최악 선택최선:Most improves my satisfaction최악:Least improves my satisfaction
Q10
AI 인터뷰

Get the respondent to walk you through one specific, recent scheduling incident — a shift change with little notice, a denied swap, or a clopening stretch — and reconstruct exactly what happened, how they found out, and what it cost them (missed plans, childcare scramble, sleep, etc). If they rated fairness low, probe for a concrete example of favoritism or inconsistency rather than a general complaint. If everything they describe is positive, ask what would have to change for scheduling to become a real problem for them.

Q11
객관식

Which best describes your usual shift?

  • Morning
  • Afternoon/evening
  • Overnight
  • Rotating/varies
  • Prefer not to say
Q12
객관식

How long have you worked in this role?

  • Less than 3 months
  • 3-11 months
  • 1-2 years
  • 3+ years
  • Prefer not to say
Q13
메시지

That's everything — thank you! Your responses are combined with your team's to spot patterns in predictability, swap access, fairness, and burnout, and to shape changes to how schedules are built.

포함된 기능

  • AI 후속 질문

    정형화된 설문이 놓치는 세부 내용을, 주관식 답변에 맞춰 AI가 심층 질문으로 끌어냅니다.

  • 주의력 확인 장치

    성의 없는 답변과 저품질 응답자를 걸러내는 내장 안전장치입니다.

  • AI가 작성한 문안

    문구, 질문 순서, 분기 로직까지 AI가 연구 목표에 맞춰 작성합니다.

  • 자동 리포트

    응답이 모이면 주요 주제, 인용문, 이해하기 쉬운 요약이 자동으로 작성됩니다.

다른 서비스와 비교

다른 설문 도구의 가장 유사한 템플릿을 검토했습니다. 그 도구들이 잘하는 점과, 이 템플릿이 한발 더 나아가는 지점을 정리했습니다.

이 템플릿을 선택하는 이유

  • Directly measures schedule predictability, advance notice, swap ease, and swap-denial frequency, not just whether a swap form exists
  • Includes explicit early-burnout signals via a clopening-shift frequency question and an exhaustion rating-scale item, which shift-swap forms don't touch
  • Uses a matrix to capture agreement across multiple fairness/handling statements and a best-worst trade-off to prioritize which fixes would most improve satisfaction
  • Features an AI follow-up interview step that gets the respondent to reconstruct one specific recent denied-swap or last-minute-change incident, rather than relying on general sentiment, then rolls everything into an auto-generated team report

Jotform

Burger Restaurant Shift Swap Request Form Template

This is an operational shift-swap request form for a restaurant setting, not a satisfaction or sentiment survey — its job is to route a swap request, not to measure predictability, fairness, or burnout. It's ready to field as-is but scoped narrowly to one industry vertical and one transaction type.

잘하는 점

  • Quick to deploy as a fillable, mobile-friendly request form
  • Drag-and-drop customization typical of Jotform's template library
  • Industry-specific starting point (food service) that's easy to relabel

아쉬운 점

  • Captures a swap request, not satisfaction, fairness, or burnout signals — no predictability, exhaustion, or clopening measurement
  • Static form fields only — no adaptive AI follow-up to reconstruct an incident in detail
  • No per-response quality scoring or automated analytical report generation

SurveySparrow

Employee Shift Swap Form Template

Another operational shift-swap request template, delivered in SurveySparrow's conversational form style, aimed at logging and processing swap requests rather than gauging how employees feel about scheduling fairness or burnout. Fielding-ready for the swap workflow itself, not for satisfaction research.

잘하는 점

  • Conversational, chat-like form UI that may feel less clunky to hourly staff filling it out on mobile
  • Built for a general employee audience rather than one narrow vertical
  • Simple to set up as a recurring operational request tool

아쉬운 점

  • No questions on schedule predictability, swap-denial rates, fairness perception, or physical exhaustion — it only logs the swap request itself
  • No adaptive AI probing to reconstruct a specific denied-swap or last-minute-change incident
  • No transparent scoring methodology or automated survey-level report output

설문을 공개할 준비가 되셨나요?

이 템플릿을 편집기에서 열어 보세요. 첫 응답자가 보기 전에 모든 부분을 원하는 대로 바꿀 수 있습니다.