1.1 Critically evaluate various research approaches that are available for solving a problem.

Advanced Research Design and Methodologies

Unit Reference Number


Unit Title

Advanced Research Design and Methodologies

Unit Level


Number of Credits


Total Qualification Time (TQT)

400 hours

Guided Learning Hours (GLH)

200 hours

Mandatory / Optional


Sector Subject Area (SSA)

15.3 Business Management

Unit Grading Structure

Pass / Fail

Unit Aims

Gathering and Analysing data is an integral part of the DBA programme. This module is designed to advance the existing knowledge of research methods and aims to introduce complex research design and advanced methods for analysing and interpreting literature, higher level methods for analysing complex qualitative and quantitative data. There will be special focus on the tools that are available for data analysis and learners will be introduced to a wide range of data analysis tools applicable to business research.

Learning Outcomes, Assessment Criteria and Indicative Content

Learning Outcomes – The learner will:

Assessment Criteria – The learner can:

Indicative contents

1. Be able to analyse various research approaches and propose appropriate methodology for solving the problem.

1.1  Critically evaluate various research approaches that are available for solving a problem.

1.2  Demonstrate understanding of research philosophies and its influence in data collection process.

1.3  Justify the choice of research design, strategy and choice of research method.

  • Research Design: Types of research design – Descriptive, Analytical, Longitudinal, Cross Sectional, Experimental research designs
  • Methodologies: Qualitative, Quantitative and Mixed Method research, Triangulation and Multi Method, Data Collection Methodologies and Methods.
  • Surveys: Sampling – purpose of sampling, probability and non-probability sampling, estimating the sample size, sampling methodologies, Questionnaire Design – descriptive and analytical questionnaire design, piloting – importance of piloting and process of doing a pilot, types of survey – Online, E-Mail, Phone, Face to Face

2. Be able to evaluate various data collection methodologies and justify the choice of methodology for a given scenario.

2.1  Identify appropriate methods for gathering data that aligns with the research design.

2.2  Analyse various methods in terms of its advantages and weakness.

2.3  Evaluate data collection methods in terms of reliability and validity of research.

2.4  Justify a data collection method for a given scenario.

  • Case Study Design
  • Determining unit of analysis

Developing case study research questions Determining the boundaries of case study Single, Multiple, Holistic and Embedded case study designs

Type of case studies – Explanatory, Exploratory, Descriptive, Multiple, Intrinsic, Instrumental and Collective case studies

Data collection techniques in a case approach Reporting a case study

  • Interviews:

–    Structured, Unstructured and Semi Structured Interviews,

  1. Art of questioning during the interviews Conducting interviews face to face, video chat and by phone
  2. Action Research:
  3. Models and definitions of action research Positivistic, Interpretive and Critical action research
  4. Types of action research – Individual, Collaborative and Organisational
  5. Key characteristics of action research Action research process
  6. Conducting action research
  7. Removing personal bias while conducting action research
  • Data Analysis
  • Qualitative data analysis techniques: Line by line coding, grounded theory approach,

Tools for analysing qualitative data such as NVivo

  • Quantitative Data Analysis, Analytical and Descriptive data analysis techniques

– Regression, Correlation, SEM

  1. Tools such as Qualtrics, Survey Monkey, SPSS
  2. Best practices related to research process

Ethical issues related to data collection, storage, reporting the findings, completing the form.

3. Be able to demonstrate capability to analyse wide range of quantitative data and make meaningful interpretations.

3.1  Extract, Transform and Load quantitative data into specialised software packages such as SPSS.

3.2  Identify dependant, independent, intervening, moderator, control and extraneous variables.

3.3  Develop hypothesis for a given research context.

3.4  Evaluate various statistical test for a given scenario and justify the chosen test.

3.5  Test the hypothesis with the most appropriate and draw meaningful conclusions.

  • Variables in a research study
  • Dependant, independent, confounding, control, mediator and moderator variables
  • Sources for quantitative data
  • Types of Hypothesis and steps involved in developing hypothesis
  • Descriptive and Inferential statistics
  • Experimental and Quasi Experimental research designs
  • Confidence Intervals, Sample Sizes, Statistical Significance
  • Correlation and Regression
  • Pearson, Spearman, Chi-Square, T-Test, ANNOVA

Simple and Multiple Regression

  • Factor Analysis – Exploratory and Confirmatory Factor Analysis
  • Cluster Analysis

4. Be able gain advanced understanding and capabilities to analyse qualitative data.

4.1  Evaluate the range of qualitative approaches that are available for undertaking qualitative research.

4.2  Appreciate the challenges associated in undertaking qualitative research and the implications in research design.

4.3  Demonstrate high level understanding of various qualitative analysis techniques and tools.

  • Qualitative Research Designs
  • Case Study, Secondary Data Analysis, Ethnography, Grounded Theory and Action Research
  • Types of qualitative data
  • Structured and Unstructured Qualitative data
    • Data Collection Techniques
    • Interviews, Secondary data analysis, Observations, Diary entries, heat maps, focus groups, data generated from technologies such as mobile apps
    • Analysis techniques
    • Grounded Theory, Thematic Analysis, Content Analysis, Cross Case Analysis

5. Be able to demonstrate advanced understanding about the ethical issues related to research.

5.1  Appreciate the importance of research ethics and its contribution to generation of new knowledge.

5.2  Identify ethical issues that can arise for a given research scenario and provide relevant recommendations.

5.3  Develop an argument and counter arguments on the ethical issues related to data collection, storage, analysis and reporting.

  • Ethical issues related to research
  • Importance of ethical issues
  • Impact of research ethics on research quality
  • Ethical issues that can arise while gathering data through interviews, observations, surveys, ethnography, social media, experiments and other data collection techniques
  • Ethical approval process in research institutions
  • Security and privacy issues related to data collection
  • Techniques for protecting, storing and analysing data in an ethical way
  • Role of GDPR in research

6. Be able to develop a detailed report by undertaking a systematic analysis of a given dataset.

6.1  Undertake qualitative and quantitative data analysis for a given dataset.

6.2  Develop a report presenting the findings after making appropriate interpretations.

6.3  Identify the potential limitations from the analysis.

6.4  Highlight the ethical issues that might have occurred during the data collection stage.

  • Developing research report
  • Typical structure of a research report
  • Steps involved in writing a report
  • Techniques for structuring an argument
  • Writing in academic English
  • Referencing styles


To achieve a ‘pass’ for this unit, learners must provide evidence to demonstrate that they have fulfilled all the learning outcomes and meet the standards specified by all assessment criteria.

Learning Outcomes to be met

Assessment Criteria to be covered

Assessment type

Word count (approx. length)

LO1, LO2, LO3, LO5, LO6

AC 1.1, 1.2, 1.3, 2.1, 2.4, 3.1, 3.4, 3.5

5.1, 5.3, 6.1, 6.2, 6.3, 6.4


3000 words

LO2, LO4, LO5, LO6

AC 2.1, 2.4, 4.1, 4.2, 4.3, 5.1, 5.3, 6.1,

6.2, 6.3, 6.4


2000 words

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