10Min Research - 29 - Points to Consider when Designing a Research Questionnaire

Designing a research questionnaire starts with treating each variable as a “latent construct” that must be measured through an instrument—typically a set of questionnaire items. Those items don’t just collect opinions; they operationalize abstract concepts so the hypothesis can be tested with structural equation modeling tools such as Smart PLS, SEM software, or SEM packages in R (including lavaan). Because items can be dropped during analysis, the questionnaire needs enough indicators per construct—at least three items for each construct—to keep the measurement model usable even after deletions.

The next critical checkpoint is alignment between conceptualization and operationalization. A construct’s definition in the literature must match what the questionnaire actually measures. For example, if corporate social responsibility (CSR) is conceptualized as a multi-dimensional construct covering economic, legal, ethical, and philanthropic responsibilities, but the questionnaire includes items only for the philanthropic/discretionary dimension, reviewers can flag the mismatch. That inconsistency undermines the credibility of the measurement because the instrument captures a different construct than the one described in the theory.

Once alignment is secured, the instrument must be both reliable and valid. A practical way to improve these properties is to draw items and scales from reputable journals—specifically journals listed in the Master Journal List referenced in earlier discussion. Reliability and validity aren’t just academic labels; they determine whether the items consistently measure the intended construct and whether they measure what they claim to measure.

Question clarity also matters. Items should be easy to understand for respondents; confusing wording can distort responses and damage data quality. When using existing questionnaires, researchers should distinguish between “adopt” and “adapt.” Adoption means using the questionnaire as-is with no changes. Adaptation means making small wording adjustments to improve comprehension or fit the respondent profile while keeping the core essence of the items intact.

Finally, the response scale must fit the analysis method. Dichotomous answers such as yes/no (or other non-metric formats like “yes/no” to a trust question) can create problems in SEM because they don’t behave like metric data. Instead, the guidance favors Likert-type scales—such as strongly disagree to strongly agree, or strongly dissatisfied to strongly satisfied—so each construct is measured through multiple items on a scale that supports quantitative modeling. The overall message is straightforward: questionnaire design is not a formality. It is the measurement foundation that determines whether the hypothesis test rests on sound, analyzable constructs.