An Ultimate Guide to Writing a Dissertation in Business Studies: A Step-by-Step


The Ultimate Guide to Writing a Dissertation in Business Studies: A Step-by-Step Assistance

By John Dudovskiy

July 2016 edition
Price:  $14.50
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“Of all the research books I have read, this is the easiest to understand. I now feel like I know exactly what I need to do”
– Jonathan, Pittsburgh, USA


Why this e-book?

The Ultimate Guide to Writing a Dissertation contains step-by-step guidance derived from the experience of assisting hundreds of students who have successfully completed dissertations in business studies.

Unlike many other books devoted to this topic, The Ultimate Guide to Writing a Dissertation explains the whole process starting from the selection of the research area to the completion of the final draft in simple words.

The e-book can be used by students on both levels – Bachelors and Masters, as it explains the underlying principles and rules of writing dissertation in business studies, and these principles are equally effective for Bachelors and Masters Dissertations.


“Research process thoroughly explained in simple words.”
– Kate, Leicester, UK


Writing a research project can prove to be one of the most challenging experiences in life. Experience shows that for the majority of students writing a dissertation as a final part of studies for a degree is the first engagement in a research that involves primary data collection.

Collecting a primary data and analyzing the primary data, regardless of the method chosen, can prove to be a very challenging task for students to accomplish, mainly due to the lack or absence of the previous experience. To put it simply, it may not be easy to find a gap in the research area of your interest or identify a practical problem to address in an organization of your choice. More importantly, selecting the most suitable method of primary data collection, collecting the primary data and analyzing the data to find answers to your research questions or to test hypotheses are not straightforward tasks for the many business students.

Even for desk-based studies that do not require primary data collection, formulating research aims and objectives or developing hypotheses and critically analyzing a wide range of relevant literature appears as overly difficult for inexperienced writers.

However, no need to panic. Millions of dissertations have been written up to now and many millions of dissertations are going to be written in the future. You have a chance of turning the next several months of your life, during which you will be writing your dissertation into a rewarding and satisfying period and this e-book will be your assistant to achieve this.

This e-book aims to assist students to deal with these challenges in an effective and enjoyable manner. The process of writing a dissertation is explained in this e-book in step-by-step and challenges likely to be faced in each step and the ways of dealing with these challenges are explained as well.


“Comprehensive is the right word for this guidance.”
– Rajendra, New Dehli, India

1. Getting Started 

1.1 Selecting Research Area
1.2 Formulating Research Aims and Objectives
1.3 Writing the Proposal

2. Introduction Chapter
2.1 Writing a Research Background
2.2 Explaining Rationale for the Study
2.3 Providing the Research Structure

3. Literature Review Chapter 
3.1 Structure for Literature Review Chapter
3.1.1 Introduction.
3.1.2 Explanation of the Search Strategy for the Literature
3.1.3 Definitions
3.1.4 Classifications
3.1.5 Presentation and discussion of major theoretical frameworks and models
3.1.6 Discussion of contradictions in the research area
3.1.7 Conclusions
3.2 Sources for the literature
3.3 Referencing

4. Methodology 
4.1 Research Process
4.2 Research Philosophy
4.2.1 The Essence of Research Philosophy Axiology Epistemology Ontology Phenomenology
4.2.2. The Choice of Research Philosophy Pragmatism Positivism Realism Interpretivism
4.3 Types of Research Methods
4.3.1 Applied Research
4.3.2 Fundamental Research
4.3 Research Approach
4.3.1 Deductive Approach
4.3.2 Inductive Approach
4.3.3 Abductive Approach
4.4 Research Design
4.4.1 Exploratory Research
4.4.2 Conclusive Research
4.5 Data Collection Methods
4.5.1 Secondary Data Collection
4.5.2 Primary Data Collection Quantitative Data Collection Methods Questionnaires with Closed-Ended Questions Methods of Correlation and Regression Mean, Mode and Median Qualitative Data Collection Methods Interviews Questionnaires with open-ended questions Focus Groups Observation Case Studies
4.6 Sampling
4.6.1 Probability Sampling Simple Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling
4.6.2 Non-Probability Sampling Convenience Sampling Multi-Stage Sampling Purposive Sampling Quota Sampling Snowball Sampling
4.7 Methods of Data Analysis
4.8 Reliability and Validity
4.9 Ethical Considerations

5. Presentation of Findings 
5.1 Presentation of Quantitative Data
5.1.1 Tabulation
5.1.2 Pie-Charts
5.1.3 Bar Charts
5.1.4 Histograms
5.1.5 Line Graphs
5.1.6 Scatterplots
5.2 Presentation of Qualitative Data

6. Data Analysis 
6.1 Quantitative Data Analysis
6.2 Qualitative Data Analysis

7. Conclusions 
7.1 Achievement of Research Aim and Objectives
7.2 Limitations of the Study
7.3 Personal Reflection

8. Time Management 
8.1 Fighting procrastination
8.2 Breaking Down Tasks into Smaller Components
8.3 Prioritizing
8.4 Dealing with Distractions/Distractors
8.5 Getting Adequate Amounts of Sleep
8.6 Pursuing Hobbies and Socializing

9. Interactions with Supervisor 

Appendix A: Referencing Systems
Harvard Referencing System
APA Referencing System
Vancouver Referencing System
Appendix B: Resources
Recommended Texbooks
Online Resources

List of Tables
Table 1 Examples of SMART research objectives
Table 2 Axiology of research philosophies and relevant data collection techniques
Table 3 Epistemology of popular research philosophies in business research
Table 4 Constructivism and other philosophical approaches
Table 5 Ontology of research philosophies
Table 6 Advantages and disadvantages of positivism and phenomenology
Table 7 Research philosophies and data collection methods
Table 8 Positivism, interpretivism and epistemologies
Table 9 Differences between positivism and social constructionism
Table 10 Positivist and phenomenology paradigms
Table 11 Assumptions and research philosophies
Table 12 Differences between applied and fundamental research
Table 13 Differences between dedictive, inductive and abductive approaches
Table 14 Choice between deductive and inductive approaches
Table 15 Research approach and research methods
Table 16 Research approach and research attributes
Table 17 Major differences between exploratory and conclusive research design
Table 18 Examples for descriptive research design
Table 19 Examples for studies with causal design
Table 20 Main characteristics of research designs
Table 21 Advantages and disadvantages of popular sampling techniques
Table 22 Application of stratified sampling
Table 23 Sizes of non-probability sampling
Table 24 Tabulation data presentation
Table 25 Advantages and disadvantages of popular quantitative analytical software
Table 26 Qualitative data coding
Table 27 Dissertation timetable Gantt-Chart
Table 28 Time Management Matrix

List of Figures
Figure 1 Research philosophy in the ‘research onion’
Figure 2 Impact of research philosophy on the choice of research method
Figure 3 Deductive process in research
Figure 4 Inductive process in research
Figure 5 Difference between abductive reasoning and alternative approaches
Figure 6 Survey Monkey as a popular platform for primary data collection
Figure 7 Population, sample and individual cases
Figure 8 Categorisation of sampling techniques
Figure 9 Simple random sampling
Figure 10 Random number table
Figure 11 Systematic sampling
Figure 12 Stratified sampling
Figure 13 Cluster sampling
Figure 14 Convenience sampling
Figure 15 Multi-stage sampling
Figure 16 Purposive sampling
Figure 17 Theoretical sampling and generation of grounded theory
Figure 18 Linear snowball sampling
Figure 19 Exponential non-discriminative snowball sampling
Figure 20 Exponential discriminative snowball sampling
Figure 21 Pie-chart data presentation
Figure 22 Bar Chart data presentation
Figure 23 Histograms data presentation
Figure 24 Line Graphs data presentation
Figure 25 Scatter Plot data presentation

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