Usually quantitative research involves a lot more use of statistical tests but for analyzing consumer behavior and relevance of pivotal factors based on purchase decision, what are the ways a researcher can adopt to strengthen his research findings in qualitative research?
Hi there, I have heard of some use qualitative-comparitive analysis. May require some form of coding of your qualitative data into binary (like yes/no).
Hi Harpreet Singh , I don't know a lot about using statistical tests for qualitative research, but, besides Christopher suggestion, I think Ashlee Humphreys' paper is also a good example to do it (here is a link to access the paper I'm talking about: https://static1.squarespace.com/static/51814d96e4b0337a302d4f20/t/5182e297e4b0580e0003eeb6/1367532183318/Humphreys+JCR+2010.pdf).
In this case, she codified articles (she used archival data, but it works with any kind of qualitative data) and created a dictionary that was automatically coded by a computer program called WordStat. What she did was comparing the counts between time periods, but, researching about WordStat, I found that this software can also do "topic modeling, clustering, multidimensional scaling, proximity plots, quickly extract themes and automatically identify patterns"(https://provalisresearch.com/products/content-analysis-software/).
I hope it can help you.
Christopher McLaughlin , thanks for your time to answer. Yes/No coding is for only a limited set of questions, can you elaborate on answers involving multiple variables and factors. Also some questions cannot be coded as per Likert Scale. So their answers are 4 to 5 multiple options (for each question related to purchase decision) from which customers have to select.
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