Laws of Attraction is a SEEK research study drawn from a comprehensive survey of nearly 6,000 job candidates in Australia.
The information and graphs provided in connection with the Laws of Attraction research study are drawn from the responses to that survey.
Research methodology:
- SEEK commissioned GfK, an independent research agency, to conduct the Laws of Attraction research study
- The respondents were sourced from the SEEK database of over 6 million individuals
- Total sample size = 5,775 (see chart below for breakdown of total sample size by industry and diversity subsets)
- Respondents were:
- aged 18 or over
- living in Australia
- individuals who has indicated that they were looking to change jobs within the next 2 years
- actively SEEKING or MONITORING the jobs market
- looking for a job in 1 of 20 nominated industry classifications: Accounting, Banking/Financial Services, Call Centre & Customer Service, Community Services & Development, Construction, Education & Training, Engineering, Government & Defence, Healthcare & Medical, Hospitality & Tourism, Human Resources & Recruitment, Information & Communication Technology, Manufacturing, Transport & Logistics, Retail & Consumer Products, Mining, Resources & Energy, Retail & Consumer Products, Sales, Science & Technology, Data Science/Analytics, Digital
- using online job boards
- Respondents completed an online questionnaire which took approximately 15-20 minutes to complete
- Respondents completed the survey between November 11 and December 8, 2016.
- Upon completion of the survey respondents had a chance to win 1 of 3 $500 vouchers using a game of skill.
Sample size detail:
Please note: This data is not ‘nationally representative’ of the total population, as the data reflects those who are ‘in the market for a new job’ and not the ‘total population’ of Australia. This is because the sample is targeted to those who are actively seeking a job, or monitoring the job market and looking to change jobs within the next 2 years. The biggest impact, as to be expected, to this study is a greater proportion of 25-34 year olds (31% vs. 21% nat rep) and a smaller proportion of those aged 65 – 74 (1% vs. 12% of the population).
The industries chosen reflect a diverse range of blue (e.g. Construction, Manufacturing, Mining) and white (e.g. Government & Defence, Accounting, Banking & Financial Services) collar jobs, in order to be representative of the Australian Labor Force, and allow for specific differences to be seen across industries and groupings.
Total sample size: 5,775
INDUSTRY |
SAMPLE SIZE (n=) |
Accounting |
280 |
Banking/Financial Services |
296 |
Call Centre & Customer Service |
256 |
Community Services & Development |
354 |
Construction |
209 |
Education & Training |
349 |
Engineering |
275 |
Government & Defence |
295 |
Healthcare & Medical |
385 |
Hospitality & Tourism |
199 |
Human Resources & Recruitment |
314 |
Information & Communication Technology |
298 |
Manufacturing, Transport & Logistics |
291 |
Marketing and Communications |
293 |
Mining, Resources & Energy |
310 |
Retail & Consumer Products |
284 |
Sales |
211 |
Science & Technology |
269 |
Data Science/ Analytics |
310 |
Digital |
297 |
The survey also identified respondents’ demographic profile including but not limited to gender, age, location, job level, parental status, place of birth, languages spoken and disability (see chart below for breakdown of total sample size by diversity subsets).
DIVERSITY |
CATEGORY |
SAMPLE SIZE (n=) |
Gender |
Male |
2,808 |
|
Female |
2,967 |
Life stages |
Gen Y Millennials (Under 34) |
2,403 |
|
Generation X (35-54) |
2,742 |
|
Baby boomers (55+) |
630 |
Location |
Metropolitan |
4,460 |
|
Regional |
1,315 |
Job level |
Senior |
1,508 |
|
Mid |
2,615 |
|
Junior |
1,652 |
Household |
With Children |
2,345 |
|
Without Children |
3,430 |
Place of birth |
Born in Australia |
3,588 |
|
Born outside Australia and migrated |
1,896 |
Languages |
English only |
4,059 |
|
Speak other languages at home |
1,716 |
Disability |
With disability |
283 |
|
Without disability/Prefer not to say |
5,281 |
Work type |
Full time |
3,706 |
|
Part time |
887 |
|
Contract |
1018 |
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