10Min Research Methodology - 12 - What are the First Steps in Identifying Research Gaps?

Identifying a research gap in servant leadership starts with a practical sequence: pull the most recent studies, then screen them for quantitative models that already name variables, hypotheses, and relationships. In human resource management, servant leadership is treated as a key variable—often framed around questions like how servant leadership affects organizational outcomes. From there, the next step isn’t to randomly add more variables; it’s to determine whether servant leadership influences other variables directly, whether it affects a variable that then affects other outcomes (mediation), or whether its effect depends on another condition (moderation).

The workflow begins by searching for the latest research on servant leadership rather than relying on older papers. When searching, it’s common to find many results, but older studies (for example, from the early 2000s) are less useful for gap-finding because they may not reflect current theory, methods, or organizational contexts. A recommended move is to narrow the search by year—such as focusing on 2022—to see what new work is currently being published and to reduce noise from outdated findings.

Quality control comes next. Not every journal is equally reliable, so the transcript emphasizes using indexing and reputable database ecosystems. For social sciences, journals indexed in sources like the Social Sciences Citation Index, or listed in Master Journal List and Scopus, are treated as higher-quality targets. Common databases named include Emerald, Sage, Springer, ScienceDirect, Wiley, Taylor & Francis, and Oxford Academic/Cambridge. If a journal’s indexing status is unclear, the guidance is to check it via Master Journal List or Scopus by searching the journal name.

Once a promising recent paper is selected, the gap-finding process turns into a targeted scan for quantitative indicators. The transcript advises focusing on papers that explicitly use variable language and hypothesis structures—especially terms like influence, role, impact, moderator, mediator, empirical, and similar phrasing. Quantitative research is identified through the presence of measurable constructs and numeric data collection methods, such as structured questionnaires with scaled responses (e.g., options on a 1–5 scale). The paper’s research framework also matters: diagrams or text that include hypotheses and directional relationships (often shown with arrows from one variable to another) signal a model that can be adapted.

A concrete example is described: servant leadership appears as a moderating variable, shaping the strength or direction of the relationship between an independent variable and outcomes. The model may also include mediators—where one variable transmits the effect of another variable—leading to multiple dependent variables. The takeaway is that these elements—IVs, mediators, moderators, hypotheses, and the model diagram—provide a blueprint for what variables are already being tested and where new combinations or extensions might create a genuine research gap.

The next phase, reserved for later sessions, is to build on such an existing model: add variables to an established framework or develop a new model based on recommendations drawn from the selected paper.