Doctorate of Business Administration by Kennedy University

About This Course

What is Doctorate of Business Administration?

The Doctorate of Business Administration (DBA) represents the pinnacle of management expertise, empowering professionals to excel as consultants or academics. Guided by seasoned experts, candidates lead groundbreaking research and craft influential thesis. A DBA from Kennedy University is a testament to unmatched leadership and innovation in business.

Who Should Attend?

• Professionals seeking online learning and global career growth
• Skill-upgrading aspirants
• Aspirants pursuing a hands-on, future-proof degree
• Management/Commerce background
• Individuals seeking global exposure and in-demand skills
• Professionals aiming for international recognition
• Campus life seekers at top institutes 

Professional Experience: Candidates come with a significant amount of professional experience (usually 5-10 years).

Letters of Recommendation:  2 to 3 letters from professional or academic references confirming the credentials, capacity for original thought, potential for research, and academic aptitude.

Eligibility Criteria: Master's degree (such as an MBA) or a related field (e.g., Economic Policy, Startup Funding, Market Segmentation, Design). Strong academic record (minimum GPA of 3.0 or equivalent).

Key Offerings

• Training: 100 Hours of Two-Way Live Online Interactive Sessions
• Projects: Facility to undergo projects in Organizational Behavior, Strategic Management, Technology Management & more
• Masterclass: Access to 52+ Masterclass Sessions for essential soft skill development
• Learner Engagement & Events: Access to all student engagement & events throughout the doctorate
• Membership: 36 Months of Membership of Kodakco for Doctorate in Business Administration
• E-Learning: Free access to the E-learning Portal and future updates. Access PPTs, self-paced Video-based learning, library, practice tests, and doubt sessions.
• Certification: Earn a Doctorate from Kennedy University
• Entrepreneurship Mentorship: Mentorship from Young Successful Entrepreneurs to set up a sustainable & scalable Business from scratch at both Freelance & Entrepreneur level
• Placement: Get 3 in 1 Placement support through Placement Drives, Premium access to the Job portal & Personalized Job Consulting

Trainers at Henry Harvin®

• Most respected industry experts with 17+ years of working experience and recognized by numerous organizations over the years for their work
• They have delivered 450+ keynote classes for the Doctorate in Business Administration
• Have delivered 550+ lectures and are currently empaneled as domain experts with Kodakco

Gold Membership Benefits

• Avail 36 Months of Gold Membership of Kodakco that includes E-Learning Access through recorded Videos, Games, Projects, and CPDSPe Studies.
• Access to Masterclass Sessions
• Earn the Prestigious Kennedy University alumni Status and become one of the reputed 4,60,000+ Alumni globally
• Experience Industry Projects during the training

Key Takeaways

• Understand the principles of research and data collection methods
• Enhance your knowledge regarding dissertation
• Deepen the knowledge of specialized subjects
• Gain expertise in designing, conducting and publishing a high quality research
• Effectively write academic articles and convey complex ideas
• Gain skills required for quality presentation
• Enhance skills and expertise for efficiently grow in competitive market
• Learn about the process of publishing a good research 
• On completion of Doctorate of Business Administration (DBA), become eligible for various Job Roles

Module 1: Thesis Management

Research

• Scope and Significance
• Types of Research
• Research Process
• Characteristics of Good Research
• Identifying Research problem
• Meaning of Sampling Design
• Steps in sampling
• Criteria for good sample design
• Types of Sample Design
• Probability and non-probability sampling methods
• Meaning of Measurement
• Types of scales

Review of Literature

• Data Collection
• Types of Data
• Sources of Data Collection
• Methods of Data collection
• Constructing questionnaire
• Establishing, reliability and validity
• Data processing
• Coding, Editing and tabulation of data
• Meaning of Report writing
• Types of Report
• Steps of report writing
• Precautions for writing report
• Norms for using Tables
• Charts and diagram
• Appendix: - Index, Bibliography

Module 2: General Research Methodology

• Meaning and importance of Research
• Types of Research
• Selection and formulation of Research Problem
• Meaning of Research Design
• Need of Research Design
• Features of Research Design
• Inductive, Deductive and Development of models
• Developing a Research Plan
• Exploration, Description, Diagnosis, Experimentation
• Determining Experimental and Sample Designs
• Analysis of Literature Review
• Primary and Secondary Sources
• Web sources
• Critical Literature Review
• Hypothesis
• Different Types of Hypothesis
• Significance
• Development of Working Hypothesis
• Null hypothesis
• Research Methods: Scientific method vs Arbitrary Method
• Logical Scientific Methods: Deductive, Inductive, Deductive-Inductive
• Pattern of Deductive
• Inductive logical process
• Different types of inductive logical methods.

Module 3: Quantitative Research Methods

Introduction to Quantitative Research

Part 1:

• Session Overview
• RQ Hypothesis Course Context Video
• What is Quantitative Research?
• Ethics of Quantitative Research
• Session Summary

Part 2:

• Session Overview
• Introduction to the Scientific Method of Research
• Comparing Descriptive, Predictive and Prescriptive Research
• Inductive and Deductive Approaches to Quantitative Research
• Constructing Models
• Session Summary

Exploring Quantitative Research Design
Part 1:

• Session Overview
• Fundamentals of Research Design
• Components of a Research Design
• Characteristics of a Research Design
• Session Summary

Part 2:

• 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

Data Collection for Quantitative Research
Part 1:

• Session Overview
• Defining Surveys
• Exploring Survey Methods
• Session Summary

Part 2:

• Session Overview
• The Process of Questionnaire Development
• Designing a Questionnaire
• Designing Rating Scales
• The Art of Asking Questions
• Session Summary

Part 3:

• Session Overview
• Tips to Conduct Effective Surveys
• Ethics of Using Technology in Surveys
• Session Summary

Measurement and Sampling
Part 1:

• Session Overview
• What is Measurement?
• True Score Theory, Estimating Measurement Errors
• Evaluating Validity of Measures
• Evaluating Reliability of Measures
• Session Summary

Part 2:

• Session Overview
• Basic Concepts of Sampling
• Problems and Blases in Sampling
• Probability Sampling
• Non-Probability Sampling
• Session Summary

Part 3:

• Session Overview
• Determining the Sample Size
• Sampling Distribution and Statistical inference
• Demonstrations on Sampling
• Session Summary

Constructing Statistical Models
Part 1:

• Session Overview
• Significance of Comparing Means for Analysis
• What is ANOVA?
• Types of ANOVA
• Calculating and Interpreting One-Way ANOVA
• Session Summary

Part 2:

• Session Overview
• Building a Statistical Model
• Effect of Moderating and Mediating Variables
• Demonstration on Mediation and Moderation
• Session Summary

Enhancing Statistical Models
Part 1:

• Session Overview
• What is Factor Analysis?
• Conducting Factor Analysis
• Demonstration on R: Factor Analysis
• Interpreting Factor Scores
• Session Summary

Part 2:

• Session Overview
• What is Factorial ANOVA?
• Dealing with Interaction Effects in Factorial ANOVA
• Calculating and Interpreting Factorial ANOVA
• Session Summary

Multivariate Analyses
Part 1:

• Session Overview
• Multivariate regression
• MANOVA
• Logistic Regression
• Structural Equation Modeling
• Tree Structured Methods
• Conjoint Analysis
• Session Summary

Part 2:

• Session Overview
• Time Series
• Cluster Analysis
• Session Summary

Writing a Quantitative Research Paper
Part 1:

• 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 Supplimentary Findings
• Outlining your Conclusions and Reccomendations
• Making Appendices
• Session Summary

Part 2:

• Session Overview
• Writing Different Types of Quant Papers
• Guidelines for Fine Tuning your Research Presentation
• Session Summary

Module 4: Qualitative Research Methods

Introduction to Qualitative Research

• Key Elements of Qualitative Research
• Writing Qualitative Research Question
• Qualitative Research: Framework
• Steps to Write a Qualitative Research Paper
• Ethics for Qualitative Research and IRB
• Introduction to Design Strategies
• Data-Collection and Analysis Strategies
• Introduction to research design
• Major aspects of research design

Data Collection in Qualitative Research

• Sources of Evidence: A Comparative
• Assessment (Forms-Strengths-Weaknesses)
• Principles of Data Collection
• Sampling
• Reliability and Validity

Interviews and Focus Groups

Introduction to Data Analysis

• An Introduction to Data Analysis
• First Cycle Coding (Description +Demo)
• Second Cycle Coding (Description +Demo)
• Jottings and Analytic Memoing (Description +Demo)
• Assertions and Propositions (Description +Demo)
• Within Case and Cross-Case Analysis (Description+Demo)

Data Display and Exploration

• Matrix and Networks
• Timing, formatting
• Extracting Inferences and Conclusions
• Exploring Fieldwork in Progress
• Exploring Variables
• Exploring Reports in Progress

Data Analysis Process - Next Steps

• Describing Participants
• Describing Variability
• Describing Action
• Ordering by time
• Ordering by process
• Explaining Interrelationship-Change
• Explaining Causation
• Making Predictions

Verifying Conclusions

• Tactics to achieve integration among diverse pieces of data
• Tactics to sharpen understanding by differentiation
• Tactics of seeing relationships in data abstractly
• Tactics to assemble a coherent understanding of data
• Tactics for testing or confirming findings
• Standards for quality of conclusions

Writing Report and New Technologies

• Other methods in Qualitative Research
• Audiences and Effects
• Different aspects / apa
• An Introduction to Mixed Methods Research