Where are you “stuck” in the quantitative research process?

Not every PhD candidate struggles with data analysis.
In reality, each person is often “stuck” at a different link in the entire research process. Unfortunately, many only realize the problem after they have already started running SPSS or SmartPLS.

Below are the most common “bottlenecks”:

1. Not identifying the Research Gap correctly
   You read a lot of research papers but still do not know where the research gap lies.
   ➡If the Research Gap is not clear, the entire research topic will lack academic value from the very beginning.
2. The research model has no theoretical foundation
   Many PhD candidates build their models based on intuition or copy them from other research papers.
   ➡A strong model must be built on theory and explained through scientific reasoning.
3. The measurement scale is not properly designed
   Translating scales, modifying questions, or adding observed variables without evaluating their appropriateness.
   ➡Mistakes at this stage will lead to problems with Cronbach’s Alpha, CR, AVE, and convergent validity.
4. Collecting data without controlling its quality
   You have a sufficient sample size, but the data contains many careless responses, outliers, or imbalances.
   ➡Modern analysis does not only require a large amount of data, but also reliable data.
5. Running SmartPLS without understanding the results
   Many people only look at p-values or R² without knowing that they need to evaluate the measurement model first, and then move on to the structural model.
   ➡Software only performs calculations. The researcher is the one who develops the scientific reasoning.

The important thing is:
A quantitative study does not fail because of a lack of software. It usually fails because of flawed thinking or an incorrect research sequence.
If you know which step you are stuck at, you will know exactly what knowledge you need to strengthen instead of having to learn everything again from the beginning.
Which step are you most stuck at? Research Gap, research model, measurement scale, data collection, or SmartPLS? Share your experience so we can discuss it together and find a way forward.

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