Structure Literature Review using QDA Miner Lite

QDA Miner Lite can turn a large pile of research articles into a structured literature review by letting researchers pull out specific sentences, code them by concept, and then export organized segments for writing. The workflow starts with the literature review’s blueprint—definitions, importance, and relationships among variables—so the software’s coding categories map directly onto the paper’s sections and subsections.

Using an example study on servant leadership, life satisfaction, and mediators such as knowledge sharing and self-efficacy, the process begins by creating categories for each variable and for the relationships between variables. For the “servant leadership” category, the first coding target is conceptual definitions. Researchers search within their document set for sentences that contain the concept term (“servant leadership”) alongside definitional cues (e.g., “Define,” “defined,” “refer,” “state,” “stated”). After running the search, they review the returned hits, delete irrelevant sentences, and then create a new code (e.g., “definitions”) under the servant leadership category. Once coded, those sentences become retrievable building blocks for the literature review’s “definition” subsection.

The same pattern is repeated to capture the construct’s value and importance. Instead of definitional keywords, the search uses variants that signal need or value (e.g., “value,” “need,” “why”). The software returns sentences that explicitly connect servant leadership to organizational or ethical demands, and those selected lines are coded under the existing servant leadership category (rather than creating a new section each time). This yields a curated set of quotations and paraphrasable evidence for the “importance” subsection.

Next comes the relationship work needed for hypothesis framing. Researchers search for sentences that link servant leadership with life satisfaction, using combinations such as “servant leadership” plus terms associated with life satisfaction or well-being (e.g., “life satisfaction,” “well-being,” “satisfaction”). The results can be large, so filtering and deletion are used to keep only the most relevant statements. Selected sentences are then coded into a dedicated category like “servant leadership and life satisfaction,” producing material for the argument about why the variables are connected.

Finally, researchers can add theory-based links by searching for statements that pair the variables with a named theoretical framing. For example, sentences that mention “theory” alongside servant leadership and satisfaction are coded as “servant leadership and life satisfaction—Theory,” helping identify what theoretical lenses existing studies use and where further testing may be needed.

Once the coding is complete, QDA Miner Lite supports exporting the coded segments into a Word-ready report. Researchers can right-click coded retrievals, generate coded-segment reports, and export only the relevant sections—an important step because the transcript emphasizes trimming unnecessary codes to avoid bloated outputs. The end result is a literature review assembled from evidence already organized by concept, relationship, and theoretical framing.