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Earn the prestigious Doctorate in Commerce (D.Com) from Dunster Business School | Attain the highest qualification in commerce with expert-led seminars, research opportunities, and entrepreneurial mentorship | Access free E-learning, 52+ Masterclass Sessions, and exclusive events | Unlock global career opportunities with a future-proof degree.
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There's a reason that 95% of our alumni undertake 3+ courses as a minimum with Henry Harvin®
The Doctorate in Commerce is designed for professionals aiming to advance their careers while contributing to management theory and practice. With a flexible part-time format, it can be completed in 2 to 4 years. The program is divided into two stages: 60 ECTS in Year One and 120 ECTS in Year Two and beyond.
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Module 1: Thesis management
a. Scope and Significance
b. Types of Research
c. Research Process
d. Characteristics of Good Research
e. Identifying Research problem
f. Meaning of Sampling Design
g. Steps in sampling
h. Criteria for good sample design
i. Types of Sample Design
j. Probability and non-probability sampling methods
k. Meaning of Measurement
l. Types of scales
a. Data Collection
b. Types of Data
c. Sources of Data Collection
d. Methods of Data collection
e. Constructing questionnaire
f. Establishing, reliability and validity
g. Data processing
h. Coding, Editing and tabulation of data
i. Meaning of Report writing
j. Types of Report
k. Steps of report writing
i. Precautions for writing report
m. Norms for using Tables
n. Charts and diagram
o. Appendix: - Index, Bibliography
Module 2: General Research Methodology
Module 3: Quantitative Research Methods
Session Overview
RQ Hypothesis Course Context Video
What is Quantitative Research?
Definition and Scope
Importance in Commerce Research
Applications in Business and Finance
Ethics of Quantitative Research
Ethical Considerations in Data Collection
Avoiding Data Manipulation
Ensuring Confidentiality and Compliance
Session Summary
Session Overview
Introduction to the Scientific Method of Research
Formulating Hypotheses
Testing and Validating Theories
Comparing Descriptive, Predictive, and Prescriptive Research
Application in Business and Economic Forecasting
Inductive and Deductive Approaches to Quantitative Research
Practical Examples in Commerce Research
Constructing Models
Theoretical and Empirical Models in Business Studies
Session Summary
Session Overview
Fundamentals of Research Design
Components of a Research Design
Characteristics of a Research Design
Session Summary
Session Overview
Research Design for Experimental Research Studies
Research Design for Quasi-Experimental Studies
Research Design for Non-Experimental Research Studies
Evaluating Quantitative Research Design
Session Summary
Session Overview
Defining Surveys
Exploring Survey Methods
Session Summary
Session Overview
The Process of Questionnaire Development
Designing a Questionnaire
Designing Rating Scales
The Art of Asking Questions
Session Summary
Session Overview
Tips to Conduct Effective Surveys
Ethics of Using Technology in Surveys
Session Summary
Session Overview
What is Measurement?
True Score Theory, Estimating Measurement Errors
Evaluating Validity of Measures
Evaluating Reliability of Measures
Session Summary
Session Overview
Basic Concepts of Sampling
Problems and Biases in Sampling
Probability Sampling
Non-Probability Sampling
Session Summary
Session Overview
Determining the Sample Size
Sampling Distribution and Statistical Inference
Demonstrations on Sampling
Session Summary
Session Overview
Significance of Comparing Means for Analysis
What is ANOVA?
Types of ANOVA
Calculating and Interpreting One-Way ANOVA
Session Summary
Session Overview
Building a Statistical Model
Effect of Moderating and Mediating Variables
Demonstration on Mediation and Moderation
Session Summary
Session Overview
What is Factor Analysis?
Conducting Factor Analysis
Demonstration on R: Factor Analysis
Interpreting Factor Scores
Session Summary
Session Overview
What is Factorial ANOVA?
Dealing with Interaction Effects in Factorial ANOVA
Calculating and Interpreting Factorial ANOVA
Session Summary
Session Overview
Multivariate Regression
MANOVA
Logistic Regression
Structural Equation Modeling
Tree-Structured Methods
Conjoint Analysis
Session Summary
Session Overview
Time Series Analysis
Cluster Analysis
Session Summary
Session Overview
Introduction to Formatting the Research Project for Quantitative Research
Components of a Quantitative Research Paper
Writing the Summary, Background, and Purpose of Quantitative Research
Writing the Literature Review
Detailing Your Research Design/Methodology
Curating Your Results, Analysis, and Supplementary Findings
Outlining Your Conclusions and Recommendations
Making Appendices
Session Summary
Session Overview
Writing Different Types of Quantitative Research Papers
Guidelines for Fine-Tuning Your Research Presentation
Session Summary
Module 4: Qualitative Research Methods
a. Key Elements of Qualitative Research
Definition and importance of qualitative research in commerce
Differences between qualitative and quantitative research
Philosophical foundations: constructivism, interpretivism, and pragmatism
Subjectivity and researcher reflexivity
b. Writing Qualitative Research Questions
Developing research questions for commerce-related studies
Characteristics of effective qualitative research questions
Linking research questions with methodology and framework
c. Qualitative Research: Framework
Conceptual vs. theoretical frameworks in commerce research
Grounded theory, case study, ethnography, phenomenology, and narrative research
Applications of qualitative research in commerce disciplines
d. Steps to Write a Qualitative Research Paper
Structuring a research paper (Introduction, Literature Review, Methodology, Findings, Discussion, and Conclusion)
Developing a strong thesis statement
Identifying and citing relevant literature in commerce
e. Ethics for Qualitative Research and IRB
Ethical considerations in commerce research
Role of Institutional Review Boards (IRB) and obtaining approvals
Informed consent, confidentiality, and anonymity
f. Introduction to Design Strategies
Choosing the right qualitative design for commerce research
Case studies vs. action research in commerce
g. Data Collection and Analysis Strategies
Observation, in-depth interviews, and focus groups in commerce research
Coding and thematic analysis
h. Introduction to Research Design
Components of a strong qualitative research design
Aligning research design with commerce objectives
i. Major Aspects of Research Design
Trustworthiness and rigor in qualitative research
Sampling strategies in commerce research
a. Sources of Evidence: A Comparative Assessment
Types of data sources (documents, interviews, observations)
Strengths and weaknesses of different sources
b. Principles of Data Collection
Techniques for ensuring credibility and reliability
Strategies for minimizing bias in commerce research
c. Sampling
Purposeful sampling techniques for commerce studies
Determining sample size for qualitative research
d. Reliability and Validity
Ensuring reliability in qualitative commerce research
Validity in interpretive research
Conducting interviews with business professionals, consumers, and stakeholders
Developing effective interview guides
Ethical considerations in qualitative interviews
a. An Introduction to Data Analysis
Data reduction, coding, and interpretation in commerce research
b. First Cycle Coding (Description + Demo)
Open coding and initial categorization
c. Second Cycle Coding (Description + Demo)
Axial and selective coding for commerce research
d. Jottings and Analytic Memoing (Description + Demo)
Reflective notes and thematic analysis
e. Assertions and Propositions (Description + Demo)
Formulating business-related insights from data
f. Within-Case and Cross-Case Analysis (Description + Demo)
Comparative analysis of different business case studies
a. Matrix and Networks
Organizing qualitative data for commerce research
b. Timing, Formatting
Structuring qualitative findings effectively
c. Extracting Inferences and Conclusions
Interpreting qualitative data in a business context
d. Exploring Fieldwork in Progress
Challenges in real-time commerce data collection
e. Exploring Variables
Identifying key variables and their relationships
f. Exploring Reports in Progress
Preparing research reports for academic and business audiences
a. Describing Participants
Creating detailed participant profiles in commerce studies
b. Describing Variability
Identifying patterns and variations in business practices
c. Describing Action
Examining consumer behavior and decision-making processes
d. Ordering by Time and Process
Chronological and procedural analysis in commerce research
e. Explaining Interrelationship-Change
Analyzing market trends and organizational changes
f. Explaining Causation
Establishing cause-effect relationships in commerce
g. Making Predictions
Using qualitative findings to forecast business trends
a. Tactics to Achieve Integration Among Diverse Pieces of Data
Combining different qualitative data sources
b. Tactics to Sharpen Understanding by Differentiation
Distinguishing between key themes in commerce research
c. Tactics of Seeing Relationships in Data Abstractly
Conceptual mapping in qualitative analysis
d. Tactics to Assemble a Coherent Understanding of Data
Structuring qualitative findings for business implications
e. Tactics for Testing or Confirming Findings
Triangulation and member checking in commerce research
f. Standards for Quality of Conclusions
Ensuring credibility and trustworthiness in research outcomes
a. Other Methods in Qualitative Research
Digital ethnography and virtual focus groups in commerce research
b. Audiences and Effects
Adapting qualitative research reports for academia, business, and policy-makers
c. Different Aspects / APA
APA guidelines for qualitative commerce research
d. An Introduction to Mixed Methods Research
Integrating qualitative and quantitative approaches in commerce
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