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. As with any type of academic paper, the most vital step is being clear on the main aim (or objective) of the paper. What do you want to say in your paper? What is new in your area? What does it add to the present state of knowledge? But also, what are the dependent and independent variables? What is the analytical procedure? The last paragraph in the introduction should state the objective of the manuscript. That is what reviewers or editors want to see in your paper.
  2. You must do a good critical literature review to know what your fellow researchers have found and concluded, and then predicate what else needs to be known about a specific topic or concept(s). This review hopefully provides a rationale for your research and answers the ‘so what?’ question.
  3. Your paper should communicate to the reader why the critical literature review is important in relation to your objectives and hypotheses. This stage is called framing the theoretical foundation of the quantitative paper.
  4. Your conceptual framework (the relationship between hypotheses) can be located either at the start of the paper or after developing the hypotheses. You should look at the targeted journal to see which approach is more popular. It is also about the nature of your study. This is the trickiest part of designing and writing up for any quantitative paper.
  5. Based on the theoretical foundation section, you can then develop your hypotheses. This is mainly about asking the right questions, and wording your hypothesis correctly. You need to be careful about using written terms, such as: what is influencing what; or positive or negative relationships; or mediating factors; or moderating and so on.
  6. The method section should be clearly stated; data collection, sample size assumptions, sampling methods explained; and criteria for selecting a particular analytical procedure (e.g., experiments or comparing groups (e.g., ANOVA) or exploring relationships (e.g., Regression) or Structural Equation Modelling (SEM) or Hierarchical Linear Modelling (HLM) and so on) included. Basically, how did you study the problem/the actual research? How did you collect your data? How did you plan to analyse/test your data?
  7. The results or findings section should describe the main findings of the research and normally present the raw data in tables and figures, or within the text; based on nature of the selected data analysis approach and your specific writing style. Essentially, what did you observe in your study?
  8. The discussion section should be a brief summary of your interpretation of the findings. This section is sometimes built into the results section; so it can be called ‘results and discussion’. Here, you should answer: How do your findings link to existing knowledge and built on it? You should follow the author’s guidelines from the targeted journal here.
  9. The conclusion and implications section is the most important part of the quantitative paper. Reviewers tend to read this section with extra attention. Basically, what are the main theoretical and practical implications? You should also explain the limitations of your study, particularly your methodological limitations, such as: How have you overcome the Common Method Variance (CMV) issue in your study? Is there any causality issue in your study? Finally, you should give suggestions for directions for further research. What particular question should next be followed? Remember, you cannot answer everything in your paper.
  10. Theory, theory and theory!! You should have a robust and interesting overarching theory from the start. Do not try to just test relationships without a good theoretical foundation: reviewers will notice this!
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Picture by Simon Cunningham under CC license.