Qualitative research project.

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September 30, 2019

Qualitative research project.

Task:

You and your business partners have a goal to open a restaurant. You have undertaken preliminary analysis and have identified that you would be eligible for funding. You are now at the stage where you need to consider the cuisine options for your restaurant and need to undertake additional research to assist you in identifying potential and preferred cuisine options.

You will need to conduct research on people’s preferences, needs and wants relating to food, and in particular cuisine options.

Step:

Step 1: Gather your data

From the secondary data at https://www.tripadvisor.com.au/Restaurants obtain data relating to people’s food preferences, their needs and wants, and in particular their preferred cuisine options.

Analysis questions:

  1. Gather demographic/background data about your ‘participants’, in other words, the reviewers. This might include gender, approximate age, location etc.
  2. Select four (4) different cuisine options from the dataset and at least two (2) cuisine options that are the same.
  3. Review the feedback provided by participants:
    1. What was their favourite cuisine?
    2. Did they describe WHY they selected this cuisine option as their favourite cuisine?
    3. Did they describe WHAT they really liked about their identified favourite cuisine?
    4. Did they explain WHAT they enjoyed about eating out in a restaurant. Did they elaborate? Did others contribute to the post and ask any probing questions?

Step 2: Analyse and present your findings

Analyse the data you have gathered in Step 1 above.

  1. Briefly describe your participants: Use a table format to provide some brief background information on your participants.
  2. Create 2-3 NVivo Memos to help you reflect on the data gathered from in Step 1 above highlight the main points (1-2) said by each participant. Remember, reflexivity is a critical aspect of doing good qualitative research.
  3. Identify 2-3 key themes arising from your analysis and create a Mind Map on NVivo to graphically depict your findings.

Synthesise your findings and present an executive summary on your analysis.

 

Important information:

  1. Please choose Brisbane, Queensland as research location
  2. Pick Italian, Malaysian, French, Chinese, Chinese

(that is:  4 cuisines types, of which 2 are the same – this was the design)

  1. Save the the process of analysis, for example: the screen shot of the review, copy the text to word documents
  2. Highlight the main points on data reflexivity, and identify few key themes.

Tips:

  1. 1.the sample (ie dataset)the 4 cuisines and 2 same – yes the reviews are from 4 different cuisines and at least 2 from one type of cuisine.  a) select at least a few from each and a few more for the ‘same’ one – so perhaps a dozen or so in total. A few more will assist the analysis, but this takes time; b) select reviews with a reasonable amount of text and information.  The 3 or 4 line ones will not yield a sufficient amount of information.
  2. the content – general– it is challenging to ascertain the choices in questions, thus you can use the review as the unitof analysis.  This does not mean you can’t use reviewers, but there are more challenges in this approach.  The reviews can be filtered by cuisine (obviously); neighbourhood (ie location); ‘traveller type’ ie families, couples, solo, etc; price range.  And there are some details of reviewers (number of reviews; but more usefully a general idea of their residence – eg Sydney, London, etc).  From this basic demographic data can be assembled for the reviews.
  3. the content – questions
    – the what and why of favourite cuisine is challenging to ascertain.  Some of this may be inferred, but this will be limited
    – the question of what and why they liked a cuisine is much easier to obtain (differences by traveller type, residence, etc may be interesting)
    – it may well be the case that non-cuisine issues where as, or more, salient as the food.  Again look at by the general variable(s)