Methodological Approaches: Quantitative, Qualitative, and Mixed

Connection Between Philosophy and Methodology

The choice of methodological approach is not an arbitrary decision—it logically follows from the researcher's philosophical position. Ontological and epistemological beliefs define which methods are considered appropriate for obtaining knowledge. A positivist, believing in an objective measurable reality, naturally gravitates towards quantitative methods. An interpretivist, recognizing the multiplicity of subjective realities, turns to qualitative methods. A pragmatist selects methods based on the research question rather than philosophical preferences.

This connection is often described through the model of the "research onion" by Saunders (Saunders' Research Onion): from the outer layer (philosophy) to the inner (methods and data collection techniques), each subsequent layer is defined by the previous one.

Quantitative Methodology

Main Characteristics

Quantitative methodology is based on a deductive approach: the researcher starts with a theory, formulates hypotheses, and tests them using numerical data. Key features:

• Objectivity — the researcher seeks to minimize their influence on the results
• Measurability — all variables are operationalized and measured with numerical scales
• Large samples — to ensure statistical significance and the possibility of generalization
• Statistical analysis — the use of descriptive and inferential statistics
• Replicability — another researcher should get similar results under the same conditions

Typical Data Collection Methods

Statistical Analysis

Quantitative data are analyzed using statistical methods:

• Descriptive statistics — mean, median, standard deviation, frequencies
• Correlation analysis — relationship between two variables (Pearson, Spearman coefficient)
• Regression analysis — prediction of the dependent variable based on independents
• t-test, ANOVA — comparison of means between groups
• Chi-square — analysis of categorical data

Qualitative Methodology

Main Characteristics

Qualitative methodology is based on an inductive approach: the researcher collects data, analyzes them, and builds theory "from the ground up." Key features:

• Subjectivity as a resource — the researcher's personal understanding enriches interpretation
• Depth of understanding — emphasis on meanings, experience, and context
• Small samples — a small number of participants, but deep immersion in each case
• Non-numerical data — texts, images, observations, narratives
• Design flexibility — the research plan can adapt during data collection

Typical Data Collection Methods

Thematic Analysis

Thematic analysis (Braun & Clarke, 2006) is one of the most widespread methods of analyzing qualitative data. It includes six stages:

1. Familiarization with the data — repeated reading of transcripts, immersion in the material
2. Generating initial codes — systematic identification of meaningful text fragments
3. Searching for themes — grouping codes into potential themes
4. Reviewing themes — checking themes against the data, combining or splitting themes
5. Defining and naming themes — clarifying the essence of each theme
6. Writing the report — presenting results with data quotes

Mixed Methods

Pragmatist Approach

Mixed methods combine quantitative and qualitative approaches in a single study. The philosophical basis is usually pragmatism, which asserts that method choice should be determined by the research question, not by philosophical beliefs.

Main Mixed Methods Designs

Sequential Explanatory Design
First, the quantitative stage is conducted, followed by a qualitative stage to explain and deepen quantitative results.

• Example: A survey of 300 employees revealed low engagement in a certain department → then interviews were conducted with 10 employees from that department to understand the reasons.

Sequential Exploratory Design
First, the qualitative stage is conducted to study the phenomenon, followed by the quantitative stage to test the identified patterns.

• Example: Interviews with 15 consumers revealed key factors for making choices → then a survey of 500 consumers was conducted to quantitatively assess the significance of each factor.

Convergent Design
Quantitative and qualitative data are collected simultaneously and compared at the analysis stage.

• Example: Simultaneous survey (questionnaires) and focus groups with company clients, results are compared for a complete picture.

Case Study

Yin's Approach

Case study is an in-depth study of one or several cases in their real context. Robert Yin (2018) defines case study as an empirical research, which studies a contemporary phenomenon in its real life context, especially when the boundaries between phenomenon and context are not clear.

Types of Case Studies

Deduction, Induction, and Abduction

Deductive Approach

Deduction moves from the general to the particular: from theory to observations. The researcher starts from an existing theory, derives hypotheses from it, and tests them empirically.

Logic of deduction: Theory → Hypothesis → Data collection → Confirmation/refutation of the hypothesis

Example: Herzberg's motivation theory predicts that hygiene factors prevent dissatisfaction → Hypothesis: employees with better working conditions leave less often → Checked on data from 200 companies.

Inductive Approach

Induction moves from the particular to the general: from observations to theory. The researcher collects data, identifies patterns, and formulates theoretical generalizations.

Logic of induction: Observations → Identification of patterns → Formulation of theory

Example: Interviews with 20 successful entrepreneurs were conducted → Common features of their behavior were identified → A model of entrepreneurial resilience was developed.

Abductive Approach

Abduction combines elements of deduction and induction. The researcher starts with a "surprising fact" or anomaly and seeks the best explanation, moving between theory and data.

Logic of abduction: Surprising fact → Search for the best explanation → Checking and refinement

Example: A company with low wages has high employee loyalty (anomaly) → The researcher proposes several possible explanations → Checks them, combining qualitative and quantitative data.

Choice of Approach for the Research Question

When choosing an approach, it is necessary to consider:

1. Nature of the research question — "how much?" and "what is the relationship?" indicate a quantitative approach; "why?" and "how?" — a qualitative one
2. Degree of topic exploration — little-studied topics require qualitative research; well-studied ones allow quantitative hypothesis testing
3. Availability of data and participants — large samples for quantitative approach are not always possible
4. Practical constraints — time, resources, researcher skills
5. Philosophical position — the researcher's beliefs about the nature of knowledge

Practical Exercises

Task 1: Determining the Approach

For each research question, determine the most appropriate methodological approach and justify your choice:

a) "What is the relationship between leadership style and team performance?"
b) "How do employees experience organizational change?"
c) "What factors influence the decision to buy eco-friendly products and how do consumers explain their choice?"

Solutions:

a) Quantitative approach — The question aims to measure the relationship between variables. Standardized questionnaires can be used to assess leadership style (e.g., MLQ) and performance indicators, then a correlation or regression analysis can be performed.

b) Qualitative approach — The question "how do they experience" implies studying subjective experience and meanings. Suitable methods include in-depth interviews or diary entries followed by thematic analysis.

c) Mixed methods (sequential exploratory design) — The question includes both a quantitative component ("what factors influence") and a qualitative one ("how do they explain"). One might start with interviews to identify the factors, then conduct a survey to quantitatively evaluate their significance.

Task 2: Research Logic

Determine which type of logical reasoning (deduction, induction, or abduction) is used in each scenario:

a) The researcher noticed that some startups grow faster than competitors despite less funding. He decided to study these cases and find an explanation for this phenomenon.
b) Based on the resource-based view of the firm, the researcher hypothesized that companies with a stronger corporate culture have a higher market value, and tested this hypothesis on a sample of 150 companies.
c) The researcher conducted 25 interviews with remote workers and discovered that they use specific strategies for building trust with colleagues, leading to the formulation of a new model of virtual trust.

Solutions:

a) Abduction — The researcher starts with an anomaly (rapid growth with little funding) and seeks the best explanation.

b) Deduction — The researcher starts with theory, formulates a hypothesis, and tests it on empirical data.

c) Induction — The researcher starts with data (interviews), identifies patterns, and builds theory "from the ground up."