Dunster Business School

Doctor of Business Administration

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.

Benefits of the Course
  1. Gain in-depth expertise and knowledge
  2. Get career growth and leadership opportunities
  3. Learn to focus on practical, real-world solutions
  4. Build a robust network for collaborative opportunities
Learning Outcomes
  • Focus on advanced theory and practical applications to address complex business challenges.
  • Get a deep understanding of organizational theory, strategic management frameworks, and contemporary business models.
  • Get trained in qualitative and quantitative research methodologies.
  • Acquire leadership and change management skills.
  • Explore ethical decision-making, corporate governance, and sustainability.

Contact Information

Dunster Business School

ZA La Pièce 5 Bât A6

CH-1180 Rolle

+41784610905
contact@dunster.ch

Social Info

Shape Your Tomorrow ,Today

Applications Open for the year 2024-2025

Curriculum

  • 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.
  • 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.
    • 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

  • 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

Key Features
  • 100 Hours of Instructor-Led Interactive Sessions
  • Industry Case Studies
  • Assignments and Mini Projects
  • Self-Paced Learning
  • Guided Hands-On Exercises
  • Auto-Graded Assessments
  • Exclusive Access to Our Premium Job Portal
  • Globally Recognized Professional Certification
Skills Covered
  • Management Consultation
  • Business Management
  • Management Analyst
  • Article Dissertation
  • Action Research
  • Traditional Dissertation

Certification

Reviews

“The DBA program pushed me to rethink how I approach leadership and strategy. Dunster Business School’s emphasis on sustainability and innovation resonated deeply with my goals. The program helped me transition from operational success to thought leadership in my industry.”
 
 
Dr. Sofia Travez
Senior Manager
“Through the DBA program, I gained not just theoretical insights but also practical frameworks that I could apply directly to my business. The program’s rigorous curriculum and networking opportunities gave me the confidence to scale my ventures internationally.”
 
 
Mr. Louise Thomas
Advisor & Consultant
“The DBA program at Dunster Business School was a life-changing experience. The mentorship from renowned faculty members made my journey rewarding and impactful. The curriculum is focused on innovation and leadership which has enabled me to approach challenges with fresh perspectives.”
Johnson Clever
Founder & CEO, New Tech

Frequently Asked Questions

What skills will I gain from a DBA program?

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.