How to Analyze Information Systems Research – Key Methods

Knowing and analyzing Information Systems (IS) research can feel overwhelming at first. With its mix of technical, organizational, and human-focused elements, IS is a truly interdisciplinary field. But once you know the core methods and what to look for, analyzing IS research becomes a structured, insightful process.

This guide breaks down the key approaches used in IS research, explains how to interpret findings, and shows you how to evaluate studies like a seasoned researcher.

Overview

Information Systems research investigates how people, organizations, and technology interact. It spans topics like system design, data use, business processes, digital transformation, and IT strategy. To analyze IS research effectively, you need to understand both what the study aims to achieve and how it goes about doing that.

Broadly, IS research methods fall into two categories:

• Quantitative – Focused on numbers, measurements, and statistical analysis
• Qualitative – Focused on meanings, processes, and human experience

Some studies combine both in what’s called mixed-methods research.

Frameworks

One of the first steps in analyzing any IS study is identifying the research framework. A good framework clarifies the study’s structure and variables.

Common theoretical frameworks in IS research include:

• Technology Acceptance Model (TAM)
• Diffusion of Innovations Theory
• Resource-Based View (RBV)
• Socio-Technical Systems Theory
• Actor-Network Theory (ANT)

Look at how the authors explain their framework. Does it fit the research question? Does it guide the data collection and interpretation?

Quantitative

Quantitative IS research uses numerical data to test hypotheses or measure relationships between variables.

Key components to analyze:

Component	What to Look For
Hypotheses	Are they clearly stated and logically structured?
Variables	Are they measurable and well-defined?
Sample Size	Is it large and diverse enough to be reliable?
Data Collection	Surveys, experiments, usage logs, etc.
Analysis Method	Regression, SEM, ANOVA, etc.
Results	Are findings statistically significant and clear?

Also check whether the authors addressed validity (accuracy) and reliability (consistency). Without these, the findings may not be trustworthy.

Qualitative

Qualitative IS research explores how people experience systems and processes. It often uses open-ended data and builds theory from observation.

Key elements to analyze:

• Research Design – Case study, ethnography, interviews, etc.
• Context – Is the setting clearly described (organization, users, etc.)?
• Data Collection – Interviews, documents, observations
• Coding and Analysis – Thematic analysis, grounded theory
• Trustworthiness – Look for credibility, transferability, dependability

Ask yourself: Does the study present a rich, believable story? Is it supported with quotes or examples from real users?

Mixed

Mixed-methods research combines both numerical and descriptive data. This approach can provide a fuller picture of a research problem.

What to evaluate:

• How are the methods integrated?
• Are the findings from both methods compared or contrasted?
• Does one method explain or validate the other?
• Are the insights deeper than what either method could produce alone?

Mixed-methods studies are powerful, but only if the integration is thoughtful and purposeful.

Critical

Critical IS research goes beyond just describing or explaining. It challenges systems of power, inequality, or ethics in technology use.

Focus points:

• What assumptions is the research questioning?
• Whose voices are included or excluded?
• Are ethical or societal implications discussed?
• Is the goal to improve practice or promote change?

This type of research often uses qualitative approaches, but its strength lies in its reflexive and transformative goals.

Evaluation

Once you understand the method, take time to evaluate the research’s overall quality.

Ask these questions:

• Is the research question clear and relevant?
• Are the methods appropriate for the question?
• Is the data sufficient and well-analyzed?
• Are conclusions supported by evidence?
• Does the study discuss limitations and future research?

Strong IS research is transparent, methodologically sound, and contributes something new – either to theory, practice, or both.

Analyzing IS research isn’t about finding flaws – it’s about understanding how the study works and how it fits into the bigger academic picture. With the right lens, you’ll be able to identify solid research, spot gaps in the literature, and even design your own studies more effectively.

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