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Research Ecosystem

Foundation

Desighn

Methods

CURIOSITY / REAL-WORLD PROBLEM

                 ↓

DOMAIN IDENTIFICATION

(Discipline & Sub-discipline)

                 ↓

KNOWLEDGE CONTEXT

(What is already known?)

                 ↓

┌───────────────┐

│ LITERATURE ORIENTATION                  

│ • Key theories                                           

│ • Seminal works                                     

│ • Schools of thought                                

│ • Debates & contradictions                      

└───────────────┘

                 ↓

PHILOSOPHICAL FOUNDATIONS

(How knowledge is viewed?)

                 ↓

┌───────────────────┐

│ ONTOLOGY (Nature of reality)                 

│ • Objectivism                                

│ • Subjectivism                            

│                                             

│ EPISTEMOLOGY (Nature of knowledge)            

│ • Positivism                                 

│ • Interpretivism                             

│ • Critical realism                          

│ • Pragmatism                                

│                                              

│ AXIOLOGY (Role of values)                    

│ • Value-free                               

│ • Value-laden                                

└───────────────────┘

                 ↓

THEORETICAL FOUNDATIONS

(Why phenomena occur?)

                 ↓

┌──────────────────┐

│ • Existing theories                         

│ • Conceptual lenses                         

│ • Interdisciplinary borrowing               

│ • Theoretical gaps                         

└──────────────────┘

                 ↓

PROBLEM FORMULATION

(What exactly is the issue?)

                 ↓

┌──────────────────┐

│ • Research problem statement               

│ • Research gap identification               

│ • Justification & significance              

└──────────────────┘

                 ↓

RESEARCH OBJECTIVES & QUESTIONS

(What will be answered?)

                  ↓

┌───────────────────┐

│ • Research objectives                       

│ • Research questions                      

│ • Propositions / Hypotheses (if applicable) 

└───────────────────┘

                 ↓

CONCEPTUAL FRAMEWORK

(How concepts relate?)

                 ↓

┌───────────────────┐

│ • Key constructs                            

│ • Expected relationships                   

│ • Mediators / Moderators                   

│ • Boundary conditions                      

└───────────────────┘

                 ↓

ASSUMPTIONS & SCOPE

(What is taken as given?)

                 ↓

┌─────────────────┐

│ • Theoretical assumptions                   

│ • Contextual boundaries                    

│ • Unit of reasoning                       

└─────────────────┘

                 ↓

ETHICS & INTEGRITY FOUNDATIONS

(Should this research be done?)

                 ↓

┌─────────────────┐

│ • Academic honesty                     

│ • Plagiarism avoidance                     

│ • Ethical approval                         

│ • Responsible research principles         

└─────────────────┘

                 ↓

FOUNDATION READINESS CHECK

(Ready for design stage)

Click here for Research Design

​

 

How do we believe knowledge is created?

Includes:

  • Positivism

  • Interpretivism

  • Critical Realism

  • Pragmatism

  • Constructivism

It Comes BEFORE research design

​

​

How theory and data interact?

Includes:

  • Deductive

  • Inductive

  • Abductive

Often confused with design

— but conceptually distinct.

RESEARCH PROBLEM / IDEA

                 ↓

NATURE OF RESEARCH QUESTION

(What am I trying to understand?)

                 ↓

┌───────────────────┐

│ PURPOSE OF THE STUDY                         

│                                             

│ • Exploratory   → Discover patterns          

│ • Descriptive   → Describe characteristics  

│ • Explanatory   → Test relationships         

│ • Predictive    → Forecast outcomes          

│ • Evaluative    → Assess impact              

└───────────────────┘

                 ↓

LOGIC OF INQUIRY

(How knowledge is built?)

                 ↓

┌──────────────────┐

│ • Deductive (theory → data)                  

│ • Inductive (data → theory)                  

│ • Abductive (theory ↔ data)                  

└──────────────────┘

                 ↓

RESEARCH APPROACH

(Overall orientation)

                 ↓

┌─────────────────┐

│ • Quantitative                               

│ • Qualitative                                

│ • Mixed-Methods                              

│ • Review-Based                               

│ • Computational / Data-Driven                

└─────────────────┘

                 ↓

DESIGN STRATEGY SELECTION

(WHAT type of study?)

                 ↓

┌─────────────────┐

│ REVIEW-BASED DESIGNS                                     

│ • Narrative Review                                      

│ • Systematic Literature Review (SLR)                     

│ • Meta-analysis                                         

│ • Bibliometric Analysis                                 

│                                                          

│ EMPIRICAL DESIGNS                                       

│ • Survey-based                                          

│ • Experimental / Quasi-experimental                     

│ • Case Study                                            

│ • Archival / Database-based                             

│                                                          

│ OBSERVATIONAL DESIGNS                                   

│ • Cross-sectional                                       

│ • Longitudinal                                          

│ • Panel                                                 

│                                                          

│ MODEL-BASED / ANALYTICAL DESIGNS                         

│ • Econometric modeling                                  

│ • Simulation-based                                      

│ • Predictive modeling                                  

└───────────────────┘

                 ↓

TIME HORIZON

(When is data observed?)

                 ↓

┌────────────────┐

│ • Cross-sectional (one point in time)        

│ • Longitudinal (over time)                   

│ • Panel (entities × time)                    

└────────────────┘

                 ↓

LEVEL OF CONTROL

(Researcher intervention?)

                 ↓

┌──────────────┐

│ • Experimental                               

│ • Quasi-experimental                         

│ • Non-experimental                           

└──────────────┘

                 ↓

UNIT OF ANALYSIS

(Who or what is studied?)

 ───────────────┐

│ • Individual                                

│ • Group / Team                              

│ • Organization / Firm                      

│ • Industry / Market                         

│ • Country / System                          

│ • Document / Publication                    

└──────────────┘

                 ↓

DESIGN VALIDITY CONSIDERATIONS

(Built into design)

                 ↓

┌───────────┐

│ • Internal validity                         

│ • External validity                         

│ • Construct validity                        

│ • Ecological validity                       

└───────────┘

                 ↓

FINALIZED RESEARCH DESIGN

(Ready for method selection)

Click for Research Methods

Research Methods

   ├── Data Collection

   │            ├── Primary Data

   │            └── Secondary Data

   ├── Data Preparation

├── Data Cleaning

│   ├── Missing value treatment

│   ├── Outlier detection

│   ├── Data consistency checks

│

├── Data Transformation

│   ├── Scaling & normalization

│   ├── Log / differencing

│   ├── Dummy coding

│

└── Data Integration

    ├── Merging datasets

    ├── Panel construction

    └── Time alignment

   ├── Data Analysis

├─── ─ Descriptive Analysis

│   ├── Central tendency

│   ├── Dispersion

│

├── Inferential Statistics

│   ├── Hypothesis testing

│   ├── Confidence intervals

│

├── Regression & Econometric Models

│   ├── OLS / Logistic

│   ├── Panel data

│   ├── Time-series

│

├── Multivariate Analysis

│   ├── Factor analysis

│   ├── PCA

│   ├── Cluster analysis

│

├── Qualitative Analysis

│   ├── Thematic coding

│   ├── Content analysis

│

└── Bibliometric & Network Analysis

    ├── Co-citation

    ├── Co-authorship

    └── Keyword networks

   ├── Validation & Robustness

├── Assumption Testing

│   ├── Normality

│   ├── Multicollinearity

│

├── Robustness Checks

│   ├── Alternative models

│   ├── Sub-sample tests

│

├── Sensitivity Analysis

│   ├── Parameter variation

│   ├── Scenario analysis

│

└── Reliability & Validity Testing

    ├── Cronbach’s alpha

    ├── Construct validity

   ├── Interpretation & Inference

   ├── Reporting & Reproducibility

   └── Impact & Knowledge Translation

Research Ecosystem

A complete map of how research actually works

​

Research is not a single step—it is an interconnected system of ideas, designs, methods, data, tools, and outcomes. The Research Ecosystem brings all these components together in one structured framework so that students, scholars, and faculty can clearly understand what comes next, why it matters, and how each choice shapes research quality.

This page acts as a navigation hub, helping you move confidently from research curiosity to rigorous publication.

​

1. Research Foundations

Every strong study begins with sound foundations. This section focuses on:

  • Research philosophy and logic

  • Theory building and conceptual frameworks

  • Research questions, objectives, and hypotheses

  • Ethics, originality, and academic integrity

You will learn how research thinking is formed before any data is collected.

​

2. Research Design

Research design is the blueprint of a study—it explains how you plan to answer your research question.

Here you will find structured guidance on:

  • Bibliometric design

  • Systematic Literature Review (SLR)

  • Meta-analysis

  • Exploratory, descriptive, and causal designs

  • Cross-sectional vs longitudinal studies

Each design is explained with use-cases, strengths, limitations, and examples.

​

3. Research Methods

Research methods are the execution tools that bring a design to life. This section covers:

  • Primary data methods (surveys, interviews, experiments)

  • Secondary data methods (databases, reports, archival data)

  • Mixed-methods research

  • Qualitative, quantitative, and computational approaches

You will understand which method fits which design—and why.

​

4. Data & Measurement

Data is the backbone of research quality. This section explains:

  • Types of data and their sources

  • Measurement scales and constructs

  • Instrument design and validation

  • Reliability, validity, and bias control

Designed to help you avoid common measurement errors.

​

5. Analysis, Tools & Software

Modern research is tool-driven. Here you will explore:

  • Statistical and econometric tools

  • Bibliometric software and visualization tools

  • AI-assisted research tools

  • Coding, automation, and reproducibility

Each tool is positioned within the research workflow, not in isolation.

​

6. Interpretation, Writing & Publication

Research is incomplete until it is communicated. This section supports:

  • Result interpretation and inference

  • Academic writing and structuring papers

  • Journal selection and submission strategy

  • Ethical publishing and impact measurement

Focused on helping researchers publish with confidence and clarity.

​

7. Research Growth Path

Research evolves with experience. This ecosystem supports:

  • Undergraduate researchers

  • Postgraduate and PhD scholars

  • Early-career faculty and senior researchers

Each stage has tailored guidance, resources, and best practices.​

​

Why This Research Ecosystem Matters

  • Eliminates confusion between design, methods, and data

  • Reduces trial-and-error in research planning

  • Encourages responsible, high-quality research

  • Works across commerce, management, HR, marketing, finance, operations, and social sciences

 Think of this as a Google Maps for Research—showing where you are, where you need to go, and the best route to get there.

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