Lecture note on Document and Content Analysis as a secondary research method: for MBA students

Lecture note on Document and Content Analysis as a secondary research method: for MBA students

In MBA dissertation projects, Document and Content Analysis as a secondary research method enables systematic, theory-driven examination of existing texts and records to generate evidence without primary data collection. Below are five main ideas central to its application in this context.

1. Use of pre-existing, non-reactive data sources

Document and content analysis relies on materials already produced by others—such as annual reports, sustainability disclosures, policy documents, news articles, social media posts, and corporate websites—rather than data collected by the researcher. This is especially valuable in MBA research where access to managers or customers may be limited, but rich corporate documentation is available. It allows longitudinal and cross-sectional analysis while saving time and cost.

2. Systematic, transparent coding and sampling procedures

Rigorous application requires a clear codebook (defining dimensions, categories, and rules) and a defensible sampling strategy (which documents, time periods, and media types). For example, an MBA study on CSR communication might sample annual and sustainability reports from a defined set of firms over five years, then code for themes like “environment,” “governance,” and “community.” Transparency in coding enhances reliability and replicability.

3. Quantitative and/or qualitative orientations (manifest vs latent content)

Content analysis can be quantitative (counting frequencies of words, themes, or categories) or qualitative (interpreting meanings, narratives, and underlying assumptions). In MBA dissertations, researchers often combine both: e.g., counting how often “innovation” appears in CEO letters (manifest content) while also interpreting how “innovation” is framed strategically (latent content). This dual approach supports pragmatic research designs common in business studies.

4. Triangulation and contextual interpretation

Document analysis is strengthened when used alongside other secondary sources or methods (e.g., financial data, media coverage, policy texts) to triangulate findings and reduce bias from any single source. Context matters: researchers must understand how documents were produced, by whom, and for what purpose (e.g., regulatory compliance vs marketing), since this shapes content and omissions.

5. Ethical and validity considerations unique to secondary textual data

Even though documents are public, ethical issues arise around representation, consent (for social media), and the “dark figure” of unrecorded or omitted information. Validity threats include selective reporting, ecological fallacy (inferring individual behavior from aggregate data), and changes in categorisation over time. MBA researchers should explicitly address these limitations and justify how their coding and interpretation mitigate them.

These five ideas make Document and Content Analysis a powerful, pragmatic secondary method for MBA dissertations—particularly in marketing, strategy, CSR, and finance topics where corporate and media texts are abundant and analytically rich.

** A collection of lecture notes on the subject of research methods for MBA students, 2026 June

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