Upgrade Your Qualification To Doctorate
-- Globally Recognized --
Doctorate In Business Administration (DBA) Program
Pick a specialization in your field
- Online Flexible Program
- Focused & Unique Curriculum
- Practical Project-Based Learning
- Mentorship by Industry Expert Faculty
- Specially Designed for Working Professionals
- Global Networking Opportunities
- Explore and Learn Industry Demand Skills
- Develop Real-Life Problem Solving Skills
- Flexible Payment Plan
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DBA Course - Program Highlights
Earn a globally recognized online Doctor of Business Administration and propel your career to the next level.

World-class Curriculum

100% Online Program

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Course Overview
The Doctor of Business Administration (DBA) program at the Florida Institute of Science and Management is designed for experienced professionals and executives seeking to advance their expertise in business leadership, strategy, and research. This rigorous, research-driven program combines theoretical knowledge with practical applications, enabling students to address complex business challenges with innovative solutions. Along with earning the highest level qualification, this program helps learners earn the skills to make strategic planning and decision-making and become influential players in the business industry.
Program Curriculum
The Doctoral programs at Florida Institute of Science and Management generally comprise mainly to three phases:-
1) Course Work: This phase generally is your first semester and comprises selection, and course work on different aspects of your program like research methods, quantitative and qualitative methods and techniques. This phase ends with the finalization of the topic of your research and the allocation of a supervisor or research faculty.
2) Research: This phase generally includes data collection and analysis. It includes synopsis submissions and monthly progress report submissions. This phase also includes multiple seminars and presentations.
3) Doctoral Thesis: This phase is generally your third to sixth-semester phase that includes thesis write-up, committee reviews, thesis re-write-ups, viva and award of the doctorate.
During each of these phases, the learner will be guided and supervised by a supervisor.
The proposed curriculum has these distinctive features:
- Progressively master and apply related concepts and theories.
- Provide cohesiveness within each semester, with an identified theme to connect learning and outcomes.
- A capstone project, typically a dissertation to demonstrate summative knowledge.
- A built-in curriculum with a clear pathway to program completion.
- Inputs from industry experts and experienced faculty.
Module 1: Thesis Management
Research
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
- Review of Literature
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
- 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:
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
- Exploring Quantitative Research Design
- Part 1:
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
Data Collection for Quantitative Research
Part 1:
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
Measurement and Sampling
Part 1:
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
Constructing Statistical Models
Part 1:
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
Enhancing Statistical Models
Part 1:
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
Multivariate Analyses
Part 1:
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
Writing a Quantitative Research Paper
Part 1:
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
Module 4: Qualitative Research Methods
- Introduction to Qualitative Research
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
- Data Collection in Qualitative Research
a. Sources of Evidence: A Comparative
b. Assessment (Forms-Strengths-Weaknesses)
c. Principles of Data Collection
d. Sampling
e. Reliability and Validity
- Interviews and Focus Groups
- Introduction to Data Analysis
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)
- Data Display and Exploration
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
- Data Analysis Process – Next Steps
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
- Verifying Conclusions
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
- Writing Report and New Technologies
a. Other methods in Qualitative Research
b. Audiences and Effects
c. Different aspects / apa
d. An Introduction to Mixed Methods Research
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