Dr Babak Taheri is an Associate Professor in Marketing and Programmes Director in MSc International Marketing Management pathways at Heriot-Watt University. He has extensive experience in quantitative studies including: scale development and scale validation, structural equation modelling (SEM), path analysis using partial least squares (PLS), experimental design and intervention, multiple regression, testing for mediation and moderation).
  1. Select a suitable ‘problem’ or ‘aim or objectives’ in relation to your conceptual framework (i.e., the relationship between different concepts) before selecting the appropriate method with which to study that problem. Then, in the method chapter, you need to describe the exact steps that will be used to address your hypotheses in relation to the research problem.

  2. The method chapter should contain enough detail to enable the reader to evaluate the appropriateness of your quantitative method. If you do not know about particular methodology terms either read more about them or do not mention them. Do not get too excited about different terms, it is all about what is the best means to achieve the aims of the research. Your external and internal examiners will notice this!

  3. As with any piece of academic research, it is important to select an appropriate research paradigm. You should be able to justify your choice of ontology, epistemology and answer any methodological questions. Typically, the most suitable paradigms for using quantitative approach are: positivism, critical realism and pragmatism.

  4. It is also important to think about a ‘pilot study’ before conducting the main quantitative mode. This might be small interviews, focus groups, or uncooked survey. Spend a good amount of time on this. It is very important! Based on your research questions, you could take the pilot stage as your exploratory stage or even consider it part of mixed-methods mode.

  5. You should justify the methodological choices made as the most feasible given the research objectives, the nature of the target population and available resources. BUT do not offer resource constraints as your only reasoning! You should also mention other leading papers in your field that have used different or similar approaches, and then justify your quantitative approach (normally using survey or experimental research) as the most appropriate. Do not ignore this critical approach; again, your external and internal will notice this!

  6. Sample size and representativeness of your sample are important for the quantitative study. The majority of analysis tools are sensitive to sample size. Also, the smaller the sample the less generalisable are the findings. Please, read quantitative textbooks and articles carefully with regards to this.

  7. Your experiment scenario (or intervention) and questionnaire wording and formation should be clearly explained. You should translate the research objectives into specific measurable questions to provide data for hypothesis testing. Use simple and precise language and avoid using double-barrelled, dead give-away and ambiguous questions.

  8. In a questionnaire, constructs are the building blocks of theories and they help you to explain the different components of theories and measure their behaviour. You should use constructs/scales previously tested for reliability and validity. You cannot come up with your own questions for the constructs…well…you could(!), but then you need to go through the ‘scale development’ methodological process. However, you could modify the wording of previous constructs slightly.

  9. You need to follow appropriate statistical techniques for hypothesis testing based on fundamental characteristics of your data and expected outcomes. The level of measurement and criteria for statistical tests are vital and are the first step in selecting appropriate statistical tests. There are either metric (parametric test) or nonmetric (non-parametric). Here, you should test for normal distribution, homogeneity of variance, independence of measure and interval data.

  10. Finally! You may finish your quantitative method chapter with methodological limitations. For example, some limitations might be the omission of important variables. Another potential shortcoming might be common method bias (i.e., using one single questionnaire to measure all constructs).

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