1. Analysing qualitative data
BUSINESS RESEARCH
Lecture 9 Analysing qualitative data
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

2. Analysing qualitative data
Learning objectives
After studying this topic, you should be able to
Describe quantifying methods of analysis
Describe non-quantifying methods of analysis
Describe methods for detextualizing data
Compare the strengths and weaknesses of methods
Choose a method that reflects your paradigm
Independent study
Study Chapter 9
Activities and progress test as set
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

3. Analysing qualitative data
Introduction
If you have collected qualitative research data, your method of analysis depends on your paradigm
Positivists use various methods for quantifying the data
Interpretivists use non-quantifying methods
For interpretivists, there is a bewildering ‘array of interpretive techniques which seek to describe, decode, translate and otherwise come to terms with the meaning, not the frequency’ of ... phenomena in the social world’ (Van Maanen, 1983, p. 9)
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

4. Challenge of qualitative data analysis
Analysing qualitative data
Challenge of qualitative data analysis
Unfortunately some researchers fail to describe their methods of analysis in their published work, leading to the following criticisms
‘Despite the proliferation of qualitative research methodology texts ... the actual process of data analysis remains poorly described’ (Morse, 1994, p. 23)
‘Brief conversations, snippets from unstructured interviews, or examples of a particular activity are used to provide evidence for a particular contention ... [and] the representativeness or generality of these fragments is rarely addressed’ (Bryman, 1988, p. 77)
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

5. Main methods for analysing qualitative data
Quantifying methods
Informal methods
Content analysis
Non-quantifying methods
General approaches
Quasi-judicial method
Methods based on personal construct theory
Grounded theory
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

6. Analysing qualitative data
Quantifying methods
Informal methods for quantifying data include counting the frequency of occurrence of phenomena to examine ‘repetitive or patterned behaviours’ (Lindlof, 1996, p. 216)
If a phenomenon occurs very frequently, you may decide to designate some data as important (retain for analysis) or not important (discard) but do not lose the richness
In your methodology chapter, you will need to explain the criteria you have used to include/discard data and justify your decision to use an informal method of analysis rather than a formal method
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

7. Quantifying methods - content analysis
Analysing qualitative data
Quantifying methods - content analysis
Content analysis is ‘a method by which selected items of qualitative data are systematically converted to numerical data for analysis’ (Collis and Hussey, 2009, p. 165)
Usually associated with a positivist paradigm to analyse primary data (eg interview transcripts) or secondary data (eg text, images)
Eg Examine newspapers for articles on a business problem and analyse by name of newspaper, author, date, page number, length of article, main issues, industry, name of firm or people mentioned, etc
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

8. Procedure for content analysis
Analysing qualitative data
Procedure for content analysis
If you have a large amount of secondary data, determine basis for selecting a sample (eg certain sections)
Identify the coding units
Construct a coding frame and record the frequency of occurrence of each code
Positivists analyse the data using statistical methods
Interpretivists prefer to analyse the data for emerging themes and patterns and/or use linguistic analysis to explore the semantics, syntax and context
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

9. Examples of coding units
Analysing qualitative data
Examples of coding units
Coding unit
Example
Words/phrases
Examine minutes of meetings for the word ‘dispute’
Examine circulars and press releases to shareholders for the phrase ‘increased dividends’
Theme
Examine minutes of meetings for examples where agreement was reached
Examine circulars and press releases to shareholders for examples where increases in productivity are linked to increased profits
Item
Examine newspapers for articles on small businesses
Examine company reports for items on environmental issues
Time
Measure the time allocated to business news items on the news bulletins of different television channels
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

10. Exercise 1 Content analysis
Analysing qualitative data
Exercise 1 Content analysis
What are the advantages and potential problems of using content analysis?
Jot down a few notes
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

11. Solution 1 Content analysis
Analysing qualitative data
Solution 1 Content analysis
Advantages if you are analysing secondary data
You don’t have to spend time/money collecting data
It is a non-obtrusive method and you have a permanent population or sample which can be examined many times
Formal procedures should increase reliability and validity
Potential problems
Theoretical basis for the analysis is sometimes unclear
A large amount of data may be discarded
Secondary data prepared for another purpose/audience
Time consuming and tedious
Requires consistent approach and much concentration
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

12. Non-quantifying methods
Analysing qualitative data
Non-quantifying methods
Main features of non-quantifying methods
Reducing the data by finding a systematic way to select relevant data, often through the use of coding
Restructuring the data by using a pre-existing theoretical framework or one that emerges during the data collection stage to provide categories into which the data can be fitted
Detextualizing the data by summarizing it in the form of a diagram
Software such as NVivo or ATLAS.ti can aid some of these processes, but will not perform the analysis
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

13. Analysing qualitative data
General approaches
Miles and Huberman (1994) describe a systematic and rigorous general analytical procedure that is not tied to a particular methodology
Convert field notes into written record
Ensure all primary and secondary data is references
Start coding the data as soon as possible
Group codes into small categories
At various stages, write summaries of your findings
Use your summaries to construct generalizations
Continue until your generalizations are sufficiently robust to confront existing theories or construct a new theory
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

14. Analysing qualitative data
Data displays
Miles and Huberman (1994) also provide a comprehensive guide to using data displays
A network which has a series of labelled nodes with links representing relationships
Eg An events flow network used to show sequence of events and relationships between events, and forms the basis of a causal analysis
A matrix which is a table with defined columns and rows and appropriate headings
Eg An effects matrix used to summarize the effect of organizational change on people, relationships, etc
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

15. Quasi-judicial method
Analysing qualitative data
Quasi-judicial method
The quasi-judicial method ‘involves the use of rational argument to interpret qualitative data’ (Collis and Hussey, 2009, p. 174)
Main rules (Bromley, 1986)
Investigator reports results truthfully
Aims and objectives of investigation are stated explicitly
Achievement of aims and objectives is assessed
Investigator is properly trained
The person is placed in his or her physical, cultural, social and symbolic context
The account is written in good plan English
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

16. Repertory grid technique (Kelly, 1955)
Analysing qualitative data
Repertory grid technique (Kelly, 1955)
Repertory grid technique is ‘a method based on personal construct theory that generates a mathematical representation of a participant’s perceptions and constructs’ (Collis and Hussey, 2009, p.150) during a structured interview
The grid shows the interviewee’s notions of the concepts under discussion (the elements) and attributes of the elements (the constructs) and rating scores of the pairings
Interpretivists prefer to analyse the explanations given by the interviewees when generating the grid
Positivists analyse the scores using statistical methods
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

17. Exercise 2 Repertory grid technique
Analysing qualitative data
Exercise 2 Repertory grid technique
What are the advantages and potential problems of using repertory grid technique?
Jot down a few notes
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

18. Solution 2 Repertory grid technique
Analysing qualitative data
Solution 2 Repertory grid technique
Advantages
Scores can be analysed using statistical methods for ordinal data (more in a later lecture)
Potential problems
Interviewees may not be able to compare and contrast the triads of dyads of elements or describe the constructs
Time consuming
May be difficult to aggregate data from individual grids
If hypothesised relationships are not based on a theoretical framework or deductive reasoning, a significant results may be entirely spurious (more in a later lecture)
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

19. Analysing qualitative data
Cognitive mapping
Cognitive mapping is ‘a method based on personal construct theory that structures a participant’s personal constructs in the form of a diagram’ (Collis and Hussey, 2009, p. 177)
Goes beyond the use of repertory grid technique and can
Used to structure, analyse and make sense of written or verbal accounts of problems
Can also be used to summarize interview transcripts and other documents or as a tool for taking notes during an interview
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

20. Main stages in cognitive mapping
Analysing qualitative data
Main stages in cognitive mapping
The text is broken down into phrases (± 10 words) which represent the concepts, which are linked in a non-linear diagram that reveals the pattern of reasoning about the problem
Pairs of phrases can be united in a single concept
Meaning is retained through contrast
The concepts are linked to form a hierarchy of means and ends (explanations) leading to consequences
Meaning is retained through the context
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

21. Analysing qualitative data
Example of a cognitive map Adapted from Cropper, Eden and Ackermann, (1990, p. 350)
3 share experiences... No communication about one another’s work
73 clear the air from time to time
8 encourage synergy
63 make time to talk about work, performance etc... snatched conversation
14 write joint papers... write solo papers
15 develop mechanisms for cross fertilization
2 share experiences... no joint working on projects
17 people are protective of their area of research... look for links across
56 involved in stimulating teamwork... all too busy to work together
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

22. Analysing qualitative data
Grounded theory
Grounded theory is ‘a methodology in which a systematic set of procedures is used to develop an inductively derived theory about phenomena’ (Collis and Hussey, 2009, pp. 157 and 179)
Based on a hierarchical system of coding
Open coding (identifying simple categories), axial coding (connecting categories and sub-categories on the more conceptual level) and selective coding (selecting the core category and systematically relating it to other categories)
Relationships should result from the data or from deductive reasoning that is verified within the data
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

23. Analysing qualitative data
Conclusions
You can analyse primary or secondary research data using method(s) associated with your paradigm
You need to justify your choice of methods for collecting and analysing your research data in your research proposal and subsequently in the methodology chapter of your dissertation or thesis
Your methods must have a good fit with your paradigm and methodology, be feasible and allow you to investigate your research questions
Now read Chapter 9
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009