Research Methods Michael Wood

Research Methods
Michael Wood
michael.wood@port.ac.uk
http://userweb.port.ac.uk/~woodm/rm/rm.ppt
This file contains draft slides which will be updated.
30 November 2009
Reading
There are many books available – e.g.
• Saunders et al (2007)
• Robson (2002)
• Easterby-Smith et al (2002)
• And many others … browse in the library
These books vary a lot: some are better on the practical aspects, others on
the theoretical aspects. Sometimes you will get different advice from
different sources, so you need to consider the rationale behind the
advice. Robson is good on most aspects, although Saunders et al is
probably more student-friendly
Contents
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Overview of academic business research
What must be in a project plan and a project?
Formulating research aims
The design of research projects
Evaluating research
Statistical analysis for research
Qualitative data analysis
Analysing data and presenting results
Philosophy of research
Questionnaire design
Interview design and qualitative research
Reminders about the project
Interviews and qualitative research – more detail
More on literature reviews
Overview of academic
business research
• Reading: browse through a book on
research methods: e.g. Saunders et al
(2007), Robson (2002)
• These slides intended as a brief summary of
the important points
• Reread them when you are starting your
project
Advice on research methods
• Common sense – don’t forget this!
• Articles and books reporting similar
research – should be discussed in the project
• Books on research methods in general
– Focus on chapters relevant to your project.
Purpose and characteristics of
academic research
• Purpose:
– Discover truth about something; and/or
– Find a good way of doing something
• Must be
– Systematic and as thorough and trustworthy as possible
– Clearly written and with sufficient detail for readers to
check credibility
– Ethical
Types of research include …
• Large scale surveys (of people, organisations, events, etc)
analysed statistically
• Small scale surveys with emphasis on “qualitative” detail
• Case studies (to see how something works in detail)
• Experiments (change something to see what happens)
• Models can be set up, tested and used for …
• Participant observation (observe as participant)
• Action research (combine research and action)
• Evaluation
• … and may other possibilities …be imaginative!
Many projects combine several of these
Sources of data: many possibilities
• Interviews
– Including focus groups, Delphi technique (Robson,
2002:57), various approaches to eliciting comments
(e.g. “photo elicitation” – Sam Warren)
• Questionnaires, including via email (be careful …)
• Documents (minutes of meetings, company reports, etc)
• The web
• Databases – within organisation, of share prices, etc
• Observations of various kinds
• Etc …. Be imaginative!
Sources of literature is a different issue (Judith’s session is
very important for this)
Experiments (randomised controlled
trials)
• Put people (or whatever you investigating) in randomly
assigned groups, give the groups different treatments, and
compare groups to see what differences emerge.
• Used for testing drugs, diets (http://tinyurl.com/yp2t2o,
http://tinyurl.com/489hns), educational methods, different
designs for websites, social policies, etc. Lots of examples
in Ayres (2007)*.
• Advantages of experiments over non-interventionist
research
– Disentangle cause and effect. Can control variables you haven’t
even thought of. If done well evidence can be very convincing.
– Can investigate new things
* Ayres, Ian. (2007). Super Crunchers: how anything can be predicted. London: John
Murray.
But …
• Experiments are often impractical or unethical
• Difficulties include
– Hawthorne effect
– Failure to assign groups at random (this matters a lot
because …)
• So use less rigorous quasi-experiments instead (Grant &
Wall, 2008)* – e.g. in action research you may do a before
and after comparison. This is a sort of crude experiment but
it is not as convincing as a proper RCT.
* Grant, A. M. & Wall, T. D. (2008). The Neglected Science and Art of QuasiExperimentation: Why-to, When-to, and How-to Advice for Organizational Researchers.
Organizational Research Methods (published online, July 18, 2008).
Finding a suitable topic
•
•
•
•
Interest
Career
Feasibility
Usefulness
How to do research
•
•
•
•
•
•
•
•
Read about topic
Draft aims of research. Clear, simple, focused.
Draft literature review.
Draft research plan – check it is really likely to
meet your research aims. Check again.
Do research/analysis
Draft research/analysis and
recommendations/conclusions
Check it fits together and revise all sections
If it doesn’t fit together revise aims and …
Practical issues
• Timing
– Plan this remembering that your supervisor
may suggest extensive changes.
– Gantt chart may help.
• Ethics (remember the form!)
• Access to information.
– Take care: this is often difficult!
What must be in a project and
a project plan?
• Reading
– Project guidelines
– Proposal guidelines
– Saunders et al (2007), or another similar book
What must be in a project?
• Abstract (short summary of project including conclusions)
• Background and aims (what you’re trying to find out and why it’s
important)
• Literature review (of relevant previous research which you will build
on or extend)
• Research methods – plan and justification (what you did to meet the
aims, and why it was a sensible approach)
• Analysis (in detail, to convince sceptical readers and impress
examiners: important tables, diagrams etc must be in the text, only
details in appendix)
• Results, conclusions, recommendations, limitations, further research
• References (list works cited in text in alphabetical order)
• Appendices – Ethics form, extra details for the reader
Flexible designs can be more flexible – but everything must be there!
Features of a good project
• Obviously important and interesting
• Difficult to disagree with because
– Arguments and analysis detailed, clear and obviously
valid
– Possible objections considered and if possible answered
• Fits together
– Aims met by methods (check this in your project plan)
– Conclusions follow from analysis
References and citations
• You must give references to publications which
you draw on or quote
• Exact (word for word) quotes must be in “…” and
the reference must be given
– Maximum about one paragraph
• Use one of the standard referencing systems –
preferably the Harvard (see university website)
• Copying word for word without “…” and
reference is treated as cheating and you will fail!
Harvard referencing system
• Very important to use this (or another established
system)
• Seems easy to me, but causes a lot of difficulty
• Check library website (search for Harvard) and/or
copy an academic article or book.
• All references in text like Smith (2001)
• Then alphabetical list of references at the end.
Should include everything referred to, and nothing
else.
What must be in your project
plan (proposal)?
See assignment description
• You may be able to put parts of it in your
project!
• You should describe and justify your
research methods in as much detail as
possible
Writing style (1)
• Keep it simple.
• Short sentences
• Clear, short paragraphs
• Clear subheadings
Read it through to make sure you can follow
it. Swap with a friend and check each
others’
Writing style (2)
1 I think the EMH was true in this situation…
2 In my opinion the EMH was true …
3 In the author’s opinion the EMH was true …
4 The evidence suggests that the EMH was true …
5 This shows that the EMH was true …
Use 4 or 5.
Avoid 1, 2 or 3 because it gives the impression that
it’s just your opinion and that other, even wiser,
people may see it differently.
Writing style (3)
I work for … and the problems are … / I
interviewed three managers.
2 The author works for … and the problems are
… / The author interviewed three managers.
3 Then problems of this organization are … /
Three managers were interviewed.
Opinions vary here. I (MW) prefer (1). Others
prefer (2) or (3).
Check with your supervisor.
1
Formulating research aims
• Reading – most research methods books,
e.g. Saunders et al, 2007
Research aims or questions
• Usually start from vague idea
• Then formulate a clear aim, or list of aims, that
your research will achieve. Think of these as
hoped-for outcomes.
• Alternatively…formulate a clear question or list of
questions.
• This process may require some creative thinking
• Techniques like brainstorming and mind maps
may be useful
Aims, objectives, questions
• You can formulate your research aims as
aims (or objectives if you prefer that word)
or questions.
– These are different ways of saying the same
thing. Doesn’t matter which you use, but don’t
confuse things by having aims and questions
– May be helpful to have a list or hierarchy of
aims, but keep it simple
Hypotheses
• Hypotheses are statements whose truth you want to test, or
“predicted answers” to research questions (Robson, 2002)
• Occasionally appropriate as a top level research aim
– e.g. to test the hypothesis that “Working at home
improves quality of life”
• Usually best to avoid hypotheses when formulating main
research aims because questions or aims tend to be more
flexible
– e.g. “How does working at home affect quality of life?”
• Null hypotheses have a (controversial) role in some
statistical analysis (… as you will see), but they are not
relevant to formulating your overall research aims
Research aims or questions
• Research aims or questions should:
– Be clearly and simply expressed
– Fit together (so that you have a coherent project)
– Clarify the intended outcome and scope of the research
• Your research aims or questions should also
– Be relevant to your degree
– Be achievable
– Present a reasonable level of challenge
Research aims or questions
• Must be research aims, not business or personal aims.
– However, business or personal aims may be part of the
background motivating your research aims, and
research aims would normally include the aim of
making recommendations to people or organisations.
• Should generally have a limited scope or focus.
– The danger with general aims is that they lead to
superficial research.
• May relate to theoretical issues. You may be aiming to test,
modify or create a theory
Theory
• “Theory” includes models, explanatory
frameworks, generalisations, recommendations …
• Examples ….
• Your research should link with any relevant
theory. It may
–
–
–
–
Use a theory
Demonstrate that a theory is useful
Test a theory
Modify a theory or create a new theory
Also ask yourself
• Is the research worth doing?
• Are there any ethical or political problems?
• Is it possible? Have you got access to the
necessary data?
Is it really going to be useful?
• What use do you want the results to be? This may
be a practical use – to find out how to make more
money, or to make life easier – or a contribution to
theory, but it should be something that is really
worth achieving. Must pass the “so what? test.
• May help to clarify your aims if you imagine you’ve
done the research and write down what you think your
conclusions and recommendations might be.
• Then work backwards from what you want to
achieve to the best methods to achieve it.
Example of research aims
The aims of this research are to
1 Describe the decision making strategies of
small investors
2 Determine the effectiveness of these
strategies
Any comments? Does this seem reasonable
for a Masters project?
Another example of research
aims
• The aims of this research project are to
– Evaluate Method X for planning
mountaineering expeditions
– If necessary propose and justify Amended
Method X for planning mountaineering
expeditions
Another example of research
aims
• What are the important quality problems in
Company X?
• How serious are these problems?
• What is the best strategy for reducing these
problems?
Any comments? Does this seem reasonable
for a Masters project? Does it matter that
they are expressed as questions?
Three more examples of research
aims
1. The aim of this research is to investigate the role
of the internet in banking.
2. This research project aims to explain activity
based costing.
3. The aim of this project is to
–
–
Test the efficient market hypothesis for the Athens
stock exchange, and
Determine how global warming will influence share
prices.
Any comments? These are not reasonable for an
Masters projects! Why not?
Possible research topics
• Research in a specific organisation
– Best if they are likely to implement any
recommendations
– Take care you have adequate access to data
– Easier if you have a recognised / paid job there and / or
know key players well.
• Research based on publicly available data
– Eg share prices, the www, published statistics
• Research based on surveys of the “public”
• These are just some possibilities. There are more
…
Design of research projects
• Design means deciding on the methods and
approaches which will best achieve your aims
– Needs thinking out carefully starting from your aims
– Check the proposed design will achieve all your aims
– The design may require the use of a theoretical
framework – which should be explained and its use
justified
– May incorporate several approaches (e.g. earlier slide)
– Some advocate “flexible” designs (E.g. Robson, 2002)
– E.g. Poppy Jaman’s summary. Any comments?
– E.g. check aims and designs of these projects.
Designing research is not easy!
• Think about how you can best achieve your
aims
• Consider all possible types of research
• Be imaginative
• Think about it again
• … and again
• Check you’ve found the best way you can
for meeting all your aims
Group exercise
Design a research plan for one of the projects below, and do
a pilot study for part of it. (You may find you need to
make the aims / questions more precise.)
Michael’s project. The provisional aims are:
1. To evaluate the suitability of the PBS website for
prospective PhD students
2. To suggest improvements to the website from this
perspective
Alison’s project on the impact of a Blackberry on
family/work-life balance. What are the problems and
opportunities, and what would you recommend?
… or …
Email project
How much time do “people” spend on emails, is it
time “well spent”, and if not how can things be
improved?
• Provisional method: Survey to find how much time
is spent on emails, and respondents’ opinions on
whether this is time “well spent”, and on
recommendations (is this a satisfactory method?)
• And / or other possibilities … ?
A general design for a typical
Masters degree project
If the aim is to find a good strategy to "improve" X
in org Y, then a possible design may be:
1. Survey/case studies of Org Y to investigate problems
and opportunities
2. Survey/case studies to see how other organisations do
X and which approaches work well
3. Based on (1), (2), the literature, and perhaps creative
inspiration, consultations within the organisation,
simulation or modelling, devise a strategy likely to
improve X
4. Try/test/pilot/monitor the proposed strategy, probably
in a limited domain
Take care with opinion surveys
• Suppose your research is about risk management
and its effectiveness. You decide to investigate by
means of a questionnaire and come up with:
1. 70% of people in the organisation think our risk
management is unsatisfactory
2. 60% think Method X is the best way of improving it
• You then present this as the rationale behind your
recommendations to improve risk management.
– But … how do they know?
– Surely the researcher should find out by rigorous and
sensible methods, rather than asking people who may
neither know nor care?
Exercise
• There are many problems with interviews and
questionnaires. Your respondents may
–
–
–
–
Not know the answers
Not understand the questions
Be too lazy to think about the issues
Want to deceive you
• Try to design the methods for a research project
without using interviews or questionnaires. (This
is not usually a good idea but it should help you to
consider alternatives.)
Then …
• Having designed your research get someone
to act as a devil’s advocate and tell you
– What’s wrong with it – why it may fail to
deliver what you are aiming for
– What may go wrong
– Would they trust the answer?
Evaluating research
• Relevant to
– Planning your own research. Use the following
slides to
• Check your proposal
• Check your final project
– Critically reviewing published research
• These slides are intended as a checklist for
your research and others’
Good research should be:
• As User-friendly as possible
– Simple as possible given the message?
• As Uncritisable (trustworthy) as possible
– Trustworthiness or credibility is particularly important.
Can you trust the conclusions? Do you believe them?
Are there any flaws? Essential to give readers enough
detail to check.
• As Useful or interesting as possible
– Clear implications for future? New results?
In groups …
• Choose one of the articles you have been
given
• Assess its
– User-friendliness
– Trustworthiness (pay particular attention to this)
– Usefulness
• Brief feedback session, then we will
compare your critiques with my slides
Trustworthiness of research:
main things to check
C
R
I
T
I
C
Each letter represents an issue you should
consider
Jargon
• Most of these checks are covered by technical
jargon, concepts and techniques – e.g. lots of types
of validity (internal, external, construct, face …),
lots of types of reliability, ideas about test and
scale construction (see Robson, 2002), etc
• Read up only those areas which you think are
relevant. I have largely avoided jargon here.
• Always check sampling – always necessary to
consider whether your sample is likely to be
representative of your area of interest.
Deciding what is Cause and what
is effect
• Important to try to work out what causes what, and how
strongly and under what circumstances, so that you know
what you should change to achieve a particular effect.
– Take care – may be more complicated than it appears (ISO 9000
and profitability; drinking and thinking, storks and babies).
– Variable you haven’t thought of may be the important cause!
– Experiments (randomised controlled trials) for definitive answers,
but may be difficult, so …
– Quasi-experiments (e.g. a before/after comparison of a trial of a
new innovation) insead, but …
– May be lots of causes. Be suspicious of simple explanations (see
Taleb, 2008).
Deciding what is Cause and what
is effect – more examples
• A survey of organizations showed that those that used the balanced
scorecard were more profitable than those that didn’t.
– Does this show that the balanced scorecard makes firms more
profitable?
• A survey showed that the average job satisfaction score for a
department rose substantially and significantly between 2006 and
2008. In 2007 everyone was sent on a week’s computer course in the
Seychelles.
– Would you recommend a computer course for other departments?
• Does high staff turnover cause poor performance or vice
versa? (Glebbeek and Bax, 2004). Does extraversion help
people get promoted, or vice versa (Moutafi et al, 2007).
Does it matter?
• What caused the fall of the Berlin Wall?
To ensure results Representative …
check Sampling
Decide what you’re interest in – often called the
population or target population.
Usually this is too big to look at everything so take a
sample. Normally we want the sample to be
representative of the population or wider context—so
you must check if this is likely.
Need to consider how the sample is selected and its size.
Badly chosen samples can be biased and give very
misleading results.
1.
2.
3.
•
E.g. TV audience research, word length, NRE, non-response
bias in surveys, survivor bias in stock price samples
How to sample
•
Clarify target population (the whole group of interest)
–
•
May be a population of people, organisations or …
Decide sampling approach. There are many methods of
taking a sample from your target population, including
•
•
•
•
•
•
Random
Stratified
Purposive
Convenience (or opportunity, haphazard, accidental)
Cluster, snowball, quota, etc (see a book)
Decide size of sample – need to balance cost with
information obtained. If you analysis is statistical,
statistical theory can help …
Random sampling
• Make a numbered list of the target population (a
sampling frame)
• Use random numbers to choose sample
– Each member of population has the same chance of
being selected (and it’s independent of any biases)
– Each member of sample selected independently
– In practice, likely that some members of the sample
can’t be found or won’t help, so the sample may be
biased. Difficult to deal with this … possibilities …
• The principle is to ignore all variables and choose
at random. This allows for all “noise” variables.
Which sampling method?
•
•
Usually random samples are best for large samples, and
purposive samples for small samples analysed
qualitatively.
Done properly, with a large enough sample, random or
stratified samples (probability samples) should be
reasonably representative of the population. Can’t
assume this about purposive or convenience samples
(non-probability samples) because these are selected by
factors that are likely to bias the result in one direction or
another.
Sampling in practice
– Many samples are biased and so will not give a good
idea of the population – regardless of sample size.
• E.g. NRE, non-response bias in surveys, survivor bias in …
– Ideal for large samples is random sampling, but this is
often difficult to do properly.
• E.g. Iraq war death rate (see http://www.iraqbodycount.org/ for
another approach), TV audience research.
– Be suspicious of statistical results from purposive or
convenience samples
– Need to be especially careful with small, purposive
samples for detailed analysis – consider the purpose
and choose accordingly
Three surveys to check accuracy of
NRE phone service – which is right?
1. A Consumer’s Association survey used a sample of 60
calls, mainly about fares. The worst mistake was when
one caller asking for the cheapest fare from London to
Manchester was told £162 instead of the cheaper £52 fare
which was available via Sheffield and Chesterfield. The
percentage correct was …
32%
2. A reporter rang four times and each time asked for the
cheapest route from London to Manchester. The
proportion of the four answers which were correct was
25%
3. An NRE sponsored survey found that the answers were
97% correct
(Source: Breakfast programme, BBC1 TV, April 30 2002.)
More sampling problems
• An MBA student sends out 100 questionnaires to
100 organisations asking if they would be
interested in a particular service. Twenty are
returned, and of these 6 indicated they may be
interested in the service
– There are 650 firms in the relevant industry sector.
How big is the market for the service? Are you sure?
• Suppose you wanted to find out how common it is
for women aged 30-40 to enjoy running.
– How would you choose a sample to ask?
• Other examples and exercises attached
Measurements (Indicators)
• If you want to find out whether customer
satisfaction, or quality or profits have improved
you must have a sensible way of measuring them.
– Moreno-Luzon (1993) used managers’ “perceived
achievement of objectives” as a measure. Can you see
any problems with this?
– How would you measure quality of service in a casino?
• How would you check if your proposed measure is
valid / reliable / right / accurate?
Things to remember with
measurements (1)
• Conventional to distinguish between validity (are you
measuring the right thing?) and reliability (consistency)
• If possible use an existing measurement system (with
acknowledgement / permission). This has two advantages
– there may be evidence validating it, and you can compare
your results with previous results.
• Remember that some informants may be biased, or too
lazy to give good answers, or just ignorant.
• If possible use triangulation (check with information from
different sources)
• Ask yourself whether your proposed method of
measurement really measures the right thing
Things to remember with
measurements (2)
• Be especially careful with measures of value. This may
have several dimensions (Keeney, 1992)*. E.g. the success
of a firm might depend on profitability, worker satisfaction,
contribution to the community …
• If you are measuring the success of a change, remember
there may be several different criteria. E.g. …
• May be useful to use the average (mean) response to a
series of questions. Use your common sense to see if this is
reasonable, or if they should be kept separate. (See
literature on Tests and scales – e.g. Robson, 2002: 292308).
* Keeney, R. L. (1992). Value-focused thinking: a path to creative decisionmaking.
Cambridge, Massachusetts: Harvard University Press.
Reliability of measurements
– Same answer at different times?
– If anything depends on subjective judgments, check
agreement between different judges
• Eg – marking projects
– If you’re asking a number of questions to get at the
same information, check the relationship between
answers to these questions – with two questions use a
correlation coefficient, with more than two use
Cronbach’s Alpha (if you are keen on stats!) – see
http://www.statsoft.com/textbook/stathome.htm
Exercise: how would you measure
• … ??
Theoretical assumptions
• If the research uses a theory, is the theory
right for the purpose? And is it a “valid”
theory? (Some theories, of course, are
stupid or wrong!) You need a critical
evaluation in your literature review.
• A questionnaire or interview plan may be
based on assumptions about what is
relevant. Are these assumptions OK?
Is the research sufficiently
Imaginative?
• Imagination helpful in
– Thinking of hypotheses to explain things …
– Thinking of new methods for researching …
– Thinking of new ways of doing things …
• Many recommendations for boosting imagination
and thinking creatively – e.g.
– Brainstorming
– Doing something else and coming back to the task
– etc
Making sure that you are not
being misled by Chance
• Could your results just be due to chance?
– Have you taken account of sampling error? (If
you repeated your research with another sample
are you sure the answer would be the same?)
– Is the sample large enough?
Null hypothesis tests or confidence intervals can
be used to answer these questions.
– Are the measurements reliable?
The first CRITIC
– Cause and effect assumptions OK?
– Representative sample?
– Indicators (measurements) OK?
– Theoretical assumptions OK?
– Imaginative enough?
– Chance ruled out as explanation?
(Checks needed are mostly common sense – except for
Chance.)
The second CRITIC
•
•
•
•
•
•
C Claim?
R Role of the claimant?
I Information backing the claim?
T Test?
I Independent testing?
C Cause proposed?
Teaching skepticism via the CRITIC acronym and the
skeptical inquirer
Skeptical Inquirer, Sept-Oct, 2002 by Wayne R. Bartz
Two extra checks
• Use of a devil’s advocate or critical friend.
Remember the problem of confirmation bias – you
are likely to be more enthusiastic about evidence that
confirms your pet ideas than about evidence that
undermines it! Get someone to try and be critical and
find difficulties with your research – then fix or (if
unfixable) discuss the problems.
• Triangulation – compare results from different
sources. Applies to data, methods, observers, theories
(Robson, 2002: 174).
Anything else…?
• Is this list complete?
• Does it address all the flaws you noticed in
the paper you looked at?
• What would you add or change?
Checklist: the 3 U’s, the CRITIC
and Extra checks
• User-friendly?
• UnCRITICisable (trustworthy)?
– CRITIC
• Useful?
• Extra checks
– Triangulation
– Devils advocate (critical friend)
Another measurement problem
• Andy had answers from lots of questions on a SD, D, N,
A, SA scale
• He wanted a measure to tell him which questions produced
responses which gave a a clear overall view (COV) from
his respondents
• His defined his measurement as
COV = abs(SD+D–A–SA) – N
(where SD is the number of SD responses, etc, abs = absolute value)
• He then highlighted questions for which COV > 0
• Do you think this is a sensible measurement?
Critique of an article
• Do you accept what the article says, or are there
flaws in the research?
• Think about the article! Use your common sense.
• Check the CRITIC.
• Is it worth publishing? Could you do better?
• Read round the subject – e.g. other research on the
same theme.
• Would the research benefit from some qualitative
work, p values or confidence intervals, case
studies, different perspectives, experiments…
Statistical data analysis
• Go to
http://userweb.port.ac.uk/~woodm/stats/StatNotes0.ppt
Qualitative data analysis
• Aim is detail and depth of understanding
• Demonstrate and understand possibilities, but not
how frequently they occur
• Use direct quotes (“…”) as evidence and to reduce
danger of imposing your perspective
• Sometimes may be helpful to
– Summarise in a table or similar
– Use coding scheme to analyse statistically (but be
careful if the sample is very small!)
– Further possibilities in Saunders et al, Robson,
www.qual.auckland.ac.nz/, Thorpe and Holt (2008)
Analysing data and presenting
results
• Questionnaires and interview plans, and possibly
some data, in appendix
• Graphs and tables and important quotes from
interviewees etc in the main text
• Focus on your research aims, not the questions in
your questionnaire
– Readers want an analysis which shows how your aims
are met. They don’t want to know the answers to all the
questions in your questionnaire!
• Use appropriate summaries – e.g. tables of
averages, or of main points from interviews
Literature review
•
•
•
•
See Saunders et al (2003) Chapter 3
Focus on relevant books, articles and theories
Brief on general points
More detailed on research of particular relevance
to your project – you will need to search for
articles using the library databases
• Critical
• Should lead into your method and analysis
• Must be properly referenced!
Philosophy of research
•
•
•
•
•
•
In the textbooks you will find discussions of positivism, social constructivism,
phenomenology, etc, etc.
In my view, Robson (2002) is the best research methods text for philosophical
concepts.
Almost all concepts and distinctions here open to serious criticism – see
Robson (2002). Most management research articles don’t mention philosophy.
I wouldn’t suggest focusing on these ideas unless you are interested – in which
case be critical of what you read!
If you do want to go into philosophy, use a book like the Penguin Dictionary
of Philosophy (Mautner, 2005) or Thorpe and Holt (2008) to check what the
words mean.
Also note that there are arguments against being prescriptive about research
methods and philosophy in books with titles like
– After method: mess in social science research (Law, 2004), and
– Against method: outline of an anarchistic theory of knowledge (Feyerabend, 1993)
Further reading and references
• http://userweb.port.ac.uk/~woodm/qualquant.pdf
Some ideas which are worth mulling
over
• Detailed study of a small sample vs less
detailed study of a large sample
• Induction vs the Hypothetico-deductive
method (Popper) vs Following a framework
/ paradigm / theory vs Deduction
• Subjective vs Objective; Facts vs Values
Some misguided platitudes
The following are often assumed (I think wrongly):
• There are two distinct kinds of research:
– Quantitative (=positivist=hypothetico-deductive), and
– Qualitative (=phenomenological=inductive).
Instead …
• Positivist research (only) starts from hypotheses.
Instead ...
Academics tend to disagree about many of these issues. If you
do decide to go into them, please think hard, and don’t
accept everything you read in the textbooks uncritically!
Qualitative vs quantitative
• Quantitative usually means statistical – often with largish
samples
• Qualitative means focusing on qualities – usually with
smallish samples studied in depth
• Disadvantage with statistical approaches is that the data on
each case is often very superficial
• Disadvantage with qualitative approaches is that case(s)
studied may be untypical and can’t be used for statistical
generalisation
• Often best to use both approaches. This is known as
“mixed methods” – search for this keyword in library.
This distinction often confused with other distinctions …
Regrettable tendency to reduce
things to a simple dichotomy
If you’re a soft and cuddly person:
• Soft and cuddly (e.g. interpretivist, qualitative,
inductivist …) … is good
• Hard and spiky (e.g. positivist, quantitative,
deductivist, …) … is bad
But if you are a hard person you will probably
reverse good and bad above. There are really
many different dichotomies. Reducing them all to
one is neither right nor useful.
And …
• To hard and spiky people, soft and cuddly
research is lacking in rigour
• To soft and cuddly people, hard and spiky
research is naïve and lacking in richness
Induction vs hypotheticodeductive method
• Generalise from the data without preconceptions
(induction)
– Grounded theory. Rigour is in process used to generate theory
from data
Versus
• Use data to test hypotheses or theories (hypotheticodeductive method)
– Karl Popper. Rigor is in the testing.
Theory building vs theory testing is much the same
distinction (see Saunders et al, 2007, pp 117-119)
However, I don’t think these are the only choices …
Other useful approaches besides
induction and hypothetico-deduction
• Use a framework or theory or “paradigm” (Kuhn, 1970) to define
concepts, questions, and measurements, but without trying to test the
theory
– Arguably what most scientists do most of the time (c.f. Kuhn,
1970). Rigour is in ensuring the theory is a good one, and in using
it properly.
• Deduction from data, theories and framework. E.g. the differences
between two quality standards can be deduced.
– Rigour is in checking the deduction and the info you start with
– Differs from the hypothetico deductive method in that the result is
the deduction itself, not a confirmation, rejection or revision of a
hypothesis or theory
Note that this contradicts the assumption in Saunders et al (2007: 117119) that there are just two approaches – “deductive” and
“inductive”. I think they mean “hypothetico-deductive”, and they
omit the two very important possibilities above.
An example …
• How would these four approaches work
with a project of interest to you …
Karl Popper’s ideas (1)
• Science works by putting forward bold
theories (or hypotheses) and then testing
them as thoroughly as possible
• Provisionally accept theories that have
withstood this testing process
• Theories must be sufficiently precise to be
falsifiable – otherwise not proper science
(eg Freud’s theories are too vague…)
Karl Popper’s ideas (2) - eg
• Einstein’s theory of general relativity predicts that
light from a distant star will be bent by a small
amount by passing close to the sun. Newton’s
theory predicts the light will not be bent.
• Only possible to check during a total eclipse of the
sun. In an eclipse in 1918 light was bent as
Einstein’s theory predicted
• Newton’s theory is falsified; Einstein’s lives on
and seemed much more credible.
Karl Popper’s ideas (3)
• Theories can come from anywhere – guesswork,
intuition, other theories, etc
• The process of criticising theories and trying to
show they are wrong is vital for science
• The method applies to both natural and social
sciences
• How would you apply Popper’s ideas to a
management research project? … in practice, has
elements in common with a “critical” attitude …
Critical attitude
• Try to anticipate and discuss criticisms
• Get a friend to act as a devil’s advocate
• Your work should be so convincing that it can’t be
disputed!
• Think of any criticisms you have of articles you
have read. Make sure the same faults don’t apply
to your work.
Word “critical” sometimes used in a slightly
different, more specific, sense.
Questionnaire design:
summary
• Read a (chapter of a) book on questionnaires
• Develop a pilot. Remember questionnaires are far
more difficult to design than they appear! Check
with your pilot respondents:
– Is it clear?
– Is it interesting / appealing / user-friendly / not too
long? Would you answer it?
– Does it provide (only) the information you want?
• Are you still sure a questionnaire is a good idea?
Questionnaire design (1)
Write down what you want to find out
• Closed questions
– Tick boxes
– Rating (Likert) scales
• Open questions
Pros and cons of each …
Check your questions will enable you to find
out what you need to for your research
Questionnaire design (2)
• Covering letter
• Pilot it
– 3-4 nice friendly people to tell you what’s wrong with it
– Pilot the analysis too
• Consider sample to send it to
– Anonymity / confidentiality
– How to send it / get it back (email?)
• What to do about non-response?
Questionnaire design (3)
• Far too many questionnaires about - many of them
very silly. What is the response rate likely to be?
Would you fill it in?
• Are you sure a questionnaire is necessary???
• Many companies have a policy of not responding
to questionnaires
• Are there any alternatives?
• Check with your supervisor before sending it out
Take care with opinion surveys
• You can ask someone
– What she did last week
– What she does in general terms
– Her opinion of what she does
– What she thinks other people do
– Her opinion of what she thinks other people do
– How she thinks things can be improved
– What she thinks about particular suggestions about how things can
be improved
– What she likes / wants / values
Etc
Think about what type of question you are using and whether it is really
useful
Interview design: in brief (1)
• Read a (chapter of a) book on interviews
• Follows, or precedes questionnaire, or stands
alone
• Be clear what you want to find out
• Consider telephone interviews
• Small sample. Don’t do too many interviews.
• Plan your questions. Should be open-ended and
flexible, and aim for a detailed understanding
• Probes and prompts
Interview design (2)
• Ask for permission to tape record
• Transcribe interesting bits to get quotes for your
project
• Get interviewee relaxed. Anonymity /
confidentiality (take care here!)
• Check you’ve covered everything
• Send interviewee transcript afterwards?
• Some transcripts or parts of transcripts in
appendix?
Reminders about the project
• Research aims should be simple, explicit, focussed, motivated, useful
• Literature review should focus on relevance to your project
– References should be complete and in order
• Methods should be the best which are feasible.
• Analysis chapter should show how hard and skilfully you’ve worked,
and why readers should believe you. You need to convince a
sceptical reader who may want to know details of how your data was
obtained – e.g. source of samples, location of interviews (pub or
office?), etc, etc – and analyzed.
• Conclusions and recommendations should summarise what you have
found, and clearly meet the research aims. Also discuss limitations.
• Changing your mind is to be expected – if necessary rewrite aims
after doing the research!
Reminders (2)
• Docs/links at http://userweb.port.ac.uk/~woodm/projects
• Keep to the 15,000 word limit. You can get a good mark with
13,000 words but not with 17,000 words.
• Remember the ethics form – no form, no pass!
• Be particularly careful about NHS ethics clearance
• Make use of your supervisor (see Project Guidelines)
• Plan the timescale (Gantt chart) – allow time for delays
• Allow time at the end for your supervisor to read it for you to
make any necessary amendments
• If it’s good, consider publishing a summary in a journal. Ask
your supervisor.
When starting your project you
should …
• Have a clear aim, and a rough idea of your methods and the relevant
literature, and a few ideas about problems
• Make an appointment with your supervisor and discuss what you will
do and the timescale. Take your proposal and comments
• Remember your supervisor may have a holiday planned … agree when
you will meet / email. Usual to send drafts of chapters when completed
• Remember the deadline and plan back from this. Send your supervisor
a draft of the project at least a month before the deadline
• Project guidelines at http://userweb.port.ac.uk/~woodm/rm
• Practical guidelines on statistical analysis at
http://userweb.port.ac.uk/~woodm/stats/statnotes0.pdf
• Any questions to michael.wood@port.ac.uk
Interviews and qualitative
research: more detail
I am grateful to Alan Rutter for the next few
slides, some of which I have edited slightly
Primary data collection: interviewing
Useful for accessing peoples’ perceptions, meanings,
definitions of situations, eliciting their
constructions of reality, etc.
• Alternative types
– structured
– semi-structured
– in-depth
• Ethical considerations
F
Forms of qualitative interviews
F
f
Qualitative interviews
One to one
Face to face
interviews
Telephone
interviews
After Saunders, et al, 2000
One to many
Focus
group
interviews
Interview respondents
• Who will be interviewed and why?
• How many will be interviewed and how many times?
• When and for how long will each person be interviewed?
• Where will each person be interviewed?
• How will access to the interview situation be organised?
Sampling for small sample
qualitative research
• Usually best to use theoretical (purposive)
sampling - the selection of individuals who you
think will best contribute to the development of a
theory
• Results apply to immediate situations
• May be tentatively generalised, but the small
sample means …
Difficulties with interviews
• Mistrust by respondents
– e.g. researcher is a management spy
• Loyalty to organisation/colleagues
• Adherence to stereotypical views rather than their own
inner feelings and knowledge
• Complete indifference
• An opportunity for respondent to ‘sell’ their ideas
Managing the interview
• Preparation for the interview
– the interview schedule
• Beginning the interview - establishing rapport
• Communication and listening skills
• Asking questions
– sequence and types of questions
• Closing the interview
Verifying interview data
• Body language
• Material evidence
– e.g. company/factory tour
• Writing notes
– as soon as possible after interview
• Use informant verification and
secondary sources
Remember
• Need to demonstrate rigour
• Good research acknowledges bias and the
need to expose it.
• Devil’s advocates are useful for revealing bias
and other problems, but are seldom used.
…Is all research is biased?
More on Literature reviews
• I am grateful to Andreas Hoecht for the next
16 slides
• Don’t forget the literature should be clearly
focused on your research aims, and it
should be critical in the sense that you
should point out strengths and weaknesses
where appropriate
Research methods: writing a
literature review (Andreas Hoecht)
•
•
•
•
1.Finding material
2. Mapping relevant literatures
3. Evaluating literature
4.Some practical hints
Writing a literature review
Finding material
• There is no prescribed number of sources you
should use, it depends on the topic
• Be wary if you feel that you are drowning in
material you found for your topic, it probably
means you have not narrowed it down enough
• Be wary if you find no sources or very little
sources. You normally need some academic
sources to be able to write a meaningful literature
review
What secondary sources should
you use?
• Books:
• Use textbooks only to get an overview over a topic
• Academic monographs (edited books with
chapters by different authors) can be very useful.
They often explore a topic from different angles or
cover different aspects of a topic
• Don’t use “airport bookstall” books as serious
sources
Secondary sources
• Journals:
• Peer-reviewed academic journal articles should
normally be the backbone of your literature review
• They provide up-to date discussions of topics and
are usually more narrowly focused than textbooks
• “Trade journals” (non peer-reviewed) can provide
good introductions to topics and overviews of
developments but carry considerably less
academic “weight” than academic journals.
(Secondary) sources
• Sometimes you may be able to find article titles
like “ …:A review of the literature” in academic
journals. They can save you lots of work
• Internet:
• Make sure you are able to distinguish between
credible sources and Joe Block’s unsubstantiated
views
• Reputed organisations’ websites can be good
sources of information (but may have a bias/selfinterest). (gov. Agencies, internat. Organisations)
(Secondary) sources
• Dissertations and PhDs:
• Checking dissertations stocked in the library
may help you to get a feel for what is
expected in a dissertation as well as provide
information on a topic
• Government reports/EU reports/other
organisations’ reports can be very useful
(but are sometimes biased).
Searching for literature
• The key is the use of electronic databases
• Some databases are full text (you can download
articles directly), others are bibliographic
databases (you need to check with library or use
inter-library loan requests)
• Business Sources Premier/Emerald Full
Text/Econlit/Science Direct are all recommended
• Be patient and creative in the use of keywords
Searching for literature
• CD-Rom newspaper databases (FT,
Economist) can be useful tools
• Financial Data and Marketing databases
mainly provide primary data
Mapping out relevant literatures
• Don’t put everything you find or everything you
read in your literature review
• Time spent on familiarising yourself with and
assessing literature for relevance is never wasted
• Only after you have gained a good overview over
the literature will you be able to decide on your
particular “angle” and your research questions
Mapping out relevant literature
• Your database search should tell you how much
and what type of literature is available
• For some well-researched topic you will be able to
concentrate on the literature directly dealing with
your specific topic
• For other research ideas, you may need to think
about “related areas” or similar experiences in
other industries or possible insights from other
subject disciplines for enlightenment
Mapping out relevant literature
• An simple example: If you are interested in TQM
and small firms you may wish to
• Look at the TQM literature in general for the pros
and cons, constraints and motives
• Identify success and failure factors from the TQM
literature
• Check the small business literature for general
business conditions and constraints
• Check the small business literature to find out if
these success factors apply there
Mapping out relevant literature
• You can draw this as a conceptual map of
overlapping circles or as a flow diagram if
this suits your learning style
• Brainstorming and drawing conceptual
maps is best done after you have gained a
feel for the literature from your literature
search
Evaluating literature
•
•
•
•
•
This becomes easier with experience
When reading literature:
identify the key arguments that are made
The reason(s) for the conclusions drawn
They should be either derived from logical
deduction (a conclusion following
necessarily from premises) and /or based on
empirical evidence
Evaluating literature
•
•
•
•
Check the logic of the arguments made
Does this necessarily follow?
Check the supporting evidence
Is this data relevant? Is it meaningful and
accurate? Could it be interpreted in another way?
Which data would I need to challenge this?
• Check for flaws: tautologies, simplistic analogies,
redefinition of terms, moral judgements (ought to)
Some practical hints
• Make sure you refer to key texts that are
frequently cited in the literature
• Find out whether there are different “schools” or
“camps” in the literature and cover their positions.
• Use your research questions to structure your
literature review
• Check the validity (logic, empirical evidence) of
arguments made
• Make clear on what basis you decide to side with a
“camp” or author or why you remain unconvinced
or oppose a judgement
Some practical hints
• Don’t overstate your case and be realistic about
what you can conclude
• Be particularly fair to views and arguments you
don’t agree with (avoid to be seen as biased)
• Don’t be shy to critique established “trade
names”(academic gurus)
• Write your literature review for non-specialists
and avoid jargon
• Write it well structured and easy to read