The Doctor of Business Administration (DBA) is a professional doctorate focused on advanced business and management studies. The course is designed for experienced professionals who aim to enhance their knowledge, research skills, and leadership abilities.
Doctor of Business Administration focuses on the practical application of theoretical knowledge to solve complex business issues. The DBA course is practice-oriented and ideal for executives, consultants, and business leaders who wish to drive innovation and strategic change within organizations.
a. Session Overview
b. RQ Hypothesis Course Context Video
c. What is Quantitative Research?
d. Ethics of Quantitative Research
e. Session Summary
Part 2:
f. Session Overview
g. Introduction to the Scientific Method of Research
h. Comparing Descriptive, Predictive and Prescriptive Research
i. Inductive and Deductive Approaches to Quantitative Research
j. Constructing Models
K. Session Summary
a. Session Overview
b. Fundamentals of Research Design
c. Components of a Research Design
d. Characteristics of a Research Design
e. Session Summary
Part 2:
f. Session Overview
g. Research Design for Experimental Research Studies
h. Research Design for Quasi Experimental Studies
i. Research Design for Non-Experimental Research Studies
j. Evaluating Quantitative Research Design
k. Session Summary
a. Session Overview
b. Defining Surveys
c. Exploring Survey Methods
d. Session Summary
Part 2:
e. Session Overview
f. The Process of Questionnaire Development
g. Designing a Questionnaire
h. Designing Rating Scales
i. The Art of Asking Questions
j. Session Summary
Part 3:
k. Session Overview
l. Tips to Conduct Effective Surveys
m. Ethics of Using Technology in Surveys
n. Session Summary
a. Session Overview
b. What is Measurement?
c. True Score Theory, Estimating Measurement Errors
d. Evaluating Validity of Measures
e. Evaluating Reliability of Measures
f. Session Summary
Part 2:
g. Session Overview
i. Basic Concepts of Sampling
j. Problems and Blases in Sampling
k. Probability Sampling
l. Non-Probability Sampling
m. Session Summary
Part 3:
n. Session Overview
o. Determining the Sample Size
p. Sampling Distribution and Statistical inference
q. Demonstrations on Sampling
r. Session Summary
a. Session Overview
b. Significance of Comparing Means for Analysis
c. What is ANOVA?
d. Types of ANOVA
e. Calculating and Interpreting One-Way ANOVA
f. Session Summary
Part 2:
g. Session Overview
h. Building a Statistical Model
i. Effect of Moderating and Mediating Variables
j. Demonstration on Mediation and Moderation
k. Session Summary
a. Session Overview
b. What is Factor Analysis?
c. Conducting Factor Analysis
d. Demonstration on R: Factor Analysis
e. Interpreting Factor Scores
f. Session Summary
Part 2:
g. Session Overview
h. What is Factorial ANOVA?
i. Dealing with Interaction Effects in Factorial ANOVA
j. Calculating and Interpreting Factorial ANOVA
k. Session Summary
a. Session Overview
b. Multivariate regression
c. MANOVA
d. Logistic Regression
e. Structural Equation Modeling
f. Tree Structured Methods
g. Conjoint Analysis
h. Session Summary
Part 2:
i. Session Overview
j. Time Series
k. Cluster Analysis
l. Session Summary
a. Session Overview
b. Introduction to Formatting the Research Project for Quantitative Research
c. Components of a Quantitative Research Paper
d. Writing the Summary, Background and Purpose of Quantitative Research
e. Writing the Literature Review
f. Detailing your Research Design/Methodology
g. Curating your Results, Analysis and Supplimentary Findings
h. Outlining your Conclusions and Reccomendations
i. Making Appendices
j. Session Summary
Part 2:
k. Session Overview
l. Writing Different Types of Quant Papers
m. Guidelines for Fine Tuning your Research Presentation
n. Session Summary
a .Key Elements of Qualitative Research
b. Writing Qualitative Research Question
c. Qualitative Research: Framework
d. Steps to Write a Qualitative Research Paper
e. Ethics for Qualitative Research and IRB
f. Introduction to Design Strategies
g. Data-Collection and Analysis Strategies
h. Introduction to research design
i. Major aspects of research design
a. Sources of Evidence: A Comparative
b. Assessment (Forms-Strengths-Weaknesses)
c. Principles of Data Collection
d. Sampling
e. Reliability and Validity
a. An Introduction to Data Analysis
b. First Cycle Coding (Description +Demo)
c. Second Cycle Coding (Description +Demo)
d. Jottings and Analytic Memoing (Description +Demo)
e. Assertions and Propositions (Description +Demo)
f. Within Case and Cross-Case Analysis (Description +Demo)
a. Matrix and Networks
b. Timing, formatting
c. Extracting Inferences and Conclusions
d. Exploring Fieldwork in Progress
e. Exploring Variables
f. Exploring Reports in Progress
a. Describing Participants
b. Describing Variability
c. Describing Action
d. Ordering by time
e. Ordering by process
f. Explaining Interrelationship-Change
g. Explaining Causation
h. Making Predictions
a. Tactics to achieve integration among diverse pieces of data
b. Tactics to sharpen understanding by differentiation
c. Tactics of seeing relationships in data abstractly
d. Tactics to assemble a coherent understanding of data
e. Tactics for testing or confirming findings
f. Standards for quality of conclusions
a. Other methods in Qualitative Research
b. Audiences and Effects
c. Different aspects / apa
d. An Introduction to Mixed Methods Research
As a DBA student, you will develop advanced skills in strategic analysis, critical thinking, leadership, research methodologies, and problem-solving.
Yes, DBA is widely recognized as a professional doctorate globally. Its focus on practical application makes it valuable in global business environments.
Exams typically include case studies, projects, and open-ended questions
DBA programs cover areas such as advanced strategic management, leadership, organizational behaviour, research methodologies, global economics, digital transformation, ethics, and corporate governance.