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information/New folder/Bb Topic 10 Collecting Quantitative Data.pdf

WELCOME TO THE BUSINESS RESEARCH

PROJECT (BS3S86)

Topic 10: Collecting Quantitative Data

Module Leader: Dr. Louise Hung

© University of South Wales

Objectives

By the end of the session students should be able to:

Consider the use of Questionnaire, Quantitative Interview in collecting quantitative data

2

Reading  Collis, J. & Hussey, R. (2009). Business Research: A

practical guide for undergraduate & postgraduate students. Palgrave, Chapter 10

 Saunders, M., Lewis, P., and Thornhill, A. (2012) Research Methods for Business Students, 6th edition., Pearson Education Ltd, Chapter 9, 11.

 Plus any relevant chapter in a research methods textbook

 Bryman and Bell (2007) Business Research Methods, 2nd edition, Chapter 6

3

Research Process

4ebook is available on USW Library webpage

The Research ‘Onion’ (Saunders et al. 2012: 160)

Introduction ‘A significant part of the research process entails convincing others of the significance and validity of one's findings’ (Bryman and Bell, 2007)  Quantitative research will involve the use of

numerical data  Quantitative analysis might involve the creation of

simple tables or diagrams to show the frequency of occurrence to establishing relationships between variables

The Main Steps in Quantitative Research 1. Theory 2. Hypothesis (deductive stage) 3. Research design 4. Derive measures or concepts 5. Select research sites 6. Select research subjects/respondents 7. Administer research instruments/collect data 8. Process data 9. Analyse data 10. Findings/conclusions 11. Write up findings/conclusions

Main Preoccupations of Quantitative Researchers

1. Measurement

2. Causality

3. Generalization

4. Replication

Measurement Concerns:

 Operational definitions

 Mapping of properties or characteristics

 Following rules or procedures

 Generalizability of findings

 Establishing reliability & validity

Causality Concerns:

 Explanation  why things are the way they are

 Direction of causal influence  relationship between dependent and independent

variables

 Confidence  in the researcher's causal inferences

Generalization Concerns:

 Can findings be generalized beyond the confines of the particular context?

 Can findings be generalized from sample to population?

 How representative are samples?

Replication Concerns:

 Minimizing contamination from researcher biases or values

 Explicit description of procedures

 Control of conditions of study

 Ability to replicate in differing contexts

Criticisms of Quantitative Research

 Quantitative researchers fail to distinguish people and social institutions from `the world of nature'

 The measurement process possesses an artificial and spurious sense of precision and accuracy

 The reliance on instruments and procedures hinders the connection between research and everyday life

 The analysis of relationships between variables creates a static view of social life that is independent of people's lives

Questionnaires

 A questionnaire is a list of carefully structured questions which have been chosen after considerable testing

 It is essential that you pilot your questionnaire as fully as possible before distributing it

 The starting point will always be identifying the variables about which you need data so that you can address your research question

 Sample – how do you decide?  Questionnaire design

Theories from your literature review should inform the questions you asking in your questionnaire.

Why use a Questionnaire? Target large amount of people Use to describe, compare or explain Can cover activities, behaviour,

knowledge, attitudes, preferences Specific objectives, standardised and

highly structured questions Used to collect quantitative data –

information that can be counted or measured

Distribution Methods - Questionnaire

Questionnaire

Self- administered

Interview administered

Online/E-mail Postal Delivery

& Collection Telephone

Structured interview

(face to face)

Saunders, Lewis & Thornhill (2003), p. 283

Distribution Methods  Online Email SurveyMonkey Google form or other online software  Post Survey and covering letter Return envelope Cost Response rate of > 10%

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Distribution Methods  Telephone Requires a very large sampling frame Cost is {relatively} inexpensive Biased towards those that are available or willing to answer  Face-to Face Can be presented to respondents in variety of

scenarios On the street/at home/workplace etc... Time consuming Safety concerns

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Distribution Methods  Group Distribution Suitable for singular or limited locations Sample can be assembled in one room Quite precise Convenient Cost effective  Individual Distribution As above but undertaken on an individual basis

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Distribution Methods  Group Distribution Suitable for singular or limited locations Sample can be assembled in one room Quite precise Convenient Cost effective  Individual Distribution As above but undertaken on an individual basis

Types of Questions Closed questions (eg. Yes/No) Open questions with pre-coded

response categories Checklists Rankings Semantic Differential & Likert

scales Preferred statements Open questions eg. other comment

Questionnaire Design: Questions to avoid (Johns and Lee-Ross,1998:79-80)

Imprecision Loaded questions Two questions in one Double negatives Colloquialism Delicate and unclear Jargon Meaningless Poor communication

Open and closed questions (from Oppenheim, 1992)

Strength Limitation

OPEN Freedom & spontaneity of answer

Time-consuming

Opportunity to probe Coding more problematic

Useful for testing hypothesis about ideas or awareness

More effort from respondents

CLOSED Requires little time Loss of spontaneous responses

No extended writing Bias in answer categories

Low costs Sometimes too crude

Easy to process May irritate respondents

Make group comparisons easy

Useful for testing specific hypothesis

Questionnaire Design Process  Research aim and research questions  Specify information needed  Specify type of distribution method  Determine question content  Design questions to overcome inability and

unwillingness to respond  Choose question structure  Choose question wording  Determine order of questions  Design form/layout  PRETEST/Pilot

Maximising Response Rates for Online / Postal Questionnaires

Covering letter Design and layout of the

questionnaire is critical Initial mailing Follow-up

a) Strengths - Questionnaire Relatively simple Collect generalisable information  If highly structured, can produce high

amounts of data standardisation Large amounts of data at low cost, relatively

quickly Allows anonymity Questions can sometimes be clarified Presence of interviewer encourages

participation

b) Limitations - Questionnaire Data affected by personal

characteristics of respondent Respondents may not be honest The exercise may not be taken seriously Ambiguous questions may result in

inaccuracy Interviewers may affect outcomes Respondents may not feel confident

about anonymity Low response rates (especially

postal/online)

Quantitative Interviews

 In a quantitative methodology (Positivist) the questions in a structured interview are likely to be closed (eg. Yes/No) – remember you will want to input this data for analysis

Structured interview make it easy to compare (analyse) answers because each interviewee is asked the same question

Be aware of the need to eradicate interviewer bias as much as is possible (in the positivist paradigm)

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Quantitative Interviews - reducing interviewer bias

 Checklist for reducing interviewer bias in quantitative research 1. Read each question exactly as worded in the

questionnaire 2. Read each question slowly, using the same intonation and

emphasis 3. Ask the questions in the same order 4. Ask every question that applies 5. Record exactly what the respondent says 6. Do not answer the questions for the respondent 7. Show interest by paying attention when the respondent is

answering, but do not show approval or disapproval 8. Make sure you have understood each answer and that the

answer is adequate 9. Think about ethical considerations

29

And finally….. Focus on what you need to know Keep in mind your key research

question(s) Consider how you will analyse the

responses Consider the sensitivity of the question

e.g. Age, salary, religion etc Always consider the ethical concern of

questions/interviews Be aware of your personal safety

information/New folder/Bb Topic 11 Analysing Quantitative Data.pdf

WELCOME TO THE BUSINESS RESEARCH

PROJECT (BS3S86)

Topic 11: Analysing Quantitative Data

Module Leader: Dr. Louise Hung

© University of South Wales

Objectives  By the end of the session students should be able

to:

 understand the logic behind hypothesis testing;

 comprehend the steps involved in testing a hypothesis;

 apply the more commonly used hypothesis tests - tests of means and proportions;

 Understand significance

2

Reading  Burns, A. C., Bush, R. F. (2003) Marketing

Research: Online Research Applications. 4th ed. Pearson Education International, Chapter 15.

 Malhotra, N. K., Birks, D. F. (2003) Marketing Research: An Applied Approach. 2nd ed. Prentice Hall, Chapters 17 and 18.

 McGivern, Y. (2003) The Practice of Market and Social Research. Prentice Hall, Chapter 13

 Saunders, M. et al (2003) Research Methods for Business Students. FT Prentice Hall, Chapter 11

3

Definition  “A formal, objective, systematic process in

which numerical data are utilised to obtain information about the world"

(Burns and Grove cited by Cormack, 1991, p 140).

Assumptions Underlying Quantitative Methods

 Reality is objective, “out there,” and independent of the researcher -- therefore reality is something that can be studied objectively;

 The researcher should remain distant and independent of what is being researched;

 The values of the researcher do not interfere with, or become part of, the research -- research is value-free;

 Research is based primarily on deductive forms of logic and theories and hypotheses are tested in a cause-effect order;

 The goal is to develop generalizations that contribute to theory that enable the researcher to predict, explain, and understand some phenomenon.

Meeting Scientific Standards To meet the requirements of its underlying

positivist philosophy, Bell et al emphasise that " ... quantitative research must be scientifically 'respectable' — a requirement which entails rigorous design, administrative control and clerical accuracy" (Bell et al, 1984, p23).

Hypothesis Testing An assumption is drawn Data are collected from an appropriate

sample  Information from the sample of used to

decide how likely hypothesis is correct Purpose is to make judgement about

difference between sample statistic and hypothesised population

Establishing Hypothesis (for Quantitative Research only)

1) Business Research Project Aim / Research Question

2) Review relevant literature (ie. academic theories/concepts)

3) Identify variables (ie. from literature review)

4) Establishing hypothesis

8

 1) Research Aim Example: To investigate the impacts of

tourism on employment in Cardiff  2) Review relevant literature (ie.

Theory/concept)  Impacts: economic, social, technological,

environment, etc. Employment: training, qualification,

retail, hotel, catering, entertainment, etc. 9

Establishing Hypothesis (for Quantitative Research only)

 3) Identify variables  Impacts: economic, social,

technological, environment, etc. Employment: training, qualification,

retail, hotel, catering, entertainment, etc. 4) Establishing hypothesis Hypothesis 1: More impacts of tourism

will lead to higher employment in Cardiff.

10

Establishing Hypothesis (for Quantitative Research only)

4) Establishing hypothesis Hypothesis 1: More impacts of tourism will

lead to higher employment in Cardiff. Sub-hypothesis: More technological impacts of tourism

will lead to more training in Cardiff. More economic impacts of tourism will

lead to higher qualification level in Cardiff.

11

Establishing Hypothesis (for Quantitative Research only)

Analysing Data This phase in the research process depends a

great deal on statistics Computer packages:

MS Excel SPSS Econometric Approaches

When you have your data what do you do with it?

Working with the data (Don’t underestimate the time it takes!)

Data Cleaning Sorting  Initial descriptive statistics

Quantitative Data Analysis Data

Collection

Prepare data for analysis

Editing Coding

Create the file

Data Analysis

Feel of the data

Mean Std Dev

Correlation

Frequency

Distribution

Goodness of the data

Reliability Validity

Data Interpretation

Discussion

Research question

answered?

Test your hypothesis

14

Prepare Data for Analysis

15

1 = Money 2 = Teamwork 3 = Work/Life balance 4 = Respect

Question 1 Question 2 Question 3 Respondent 1 4 Respondent 2 3 Respondent 3 1 Respondent 4 1 Respondent 5 1 Respondent 6 3 Respondent 7 4 Respondent 8 4 Respondent 9 4 Respondent 10 1

Question 1: What can motivate you to work in this organisation ?

Exploratory Data Analysis  Prior to any detailed statistical analysis, you

should produce a set of diagrams to get an initial understanding of the data. This helps with identifying aspects such as:  highest and lowest values;  trends;  proportions; and  distributions.

0

5

10

15

20

25

30

35

40

Everyday 4-6 times in a week

1-3 times in a week

2-3 times in a month

Monthly 2-3 times in a year

Once in a year

Never

Female

Male

Exploratory Data Analysis

Descriptive Statistics

Frequency Distributions Measures of Central Tendency Measures of Dispersion Shape of Frequency Distribution

Frequency Please indicate your gender

Frequency Percent Valid

Percent Cumulative

Percent Valid Female 79 50.6 50.6 50.6

Male 77 49.4 49.4 100.0

Total 156 100.0 100.0

Descriptive statistics: Mode, Mean and Median

MODE: the value that occurs most often MEAN: effectively, the average of a set of numerical data MEDIAN: the middle value in order of size if n is odd, or the average of the two middle terms if the value is even

Task Consider this example: The respective ages of a class of students

are as follows: 22 24 22 21 29 19 19 26 25 26 20 19 28 24 23 25 26 19 23 23 22 26 22

25 19 1. What is the mean age of the group? 2. What is the mode? 3. What is the median?

20

Descriptive statistics: Mode, Mean and Median

19,19,19,19, 19, 20, 21, 22, 22, 22, 22, 23, 23, 23, 24, 24, 25, 25, 25, 26, 26,

26, 26, 28, 29

Mean = Σ/n = 577/25 = 23.08 Mode = 19

Median = (25/2 = 13th entry) = 23 21

Measures of Central tendency Statistics

Please indicate

your gender Do you work

as well?

What is your annual

budget? N Valid 156 156 156

Missing 0 0 0 Mean 1.49 2.02 1.63 Median 1.00 1.00 2.00 Mode 1 1 1 Std. Deviation .502 1.215 .746 Minimum 1 1 1 Maximum 2 5 4 Percentiles 25 1.00 1.00 1.00

50 1.00 1.00 2.00 75 2.00 3.00 2.00

Standard Deviation Standard Deviation represents an

average of the variance of data off its mean. In terms of the distribution curve, this effectively measures the breadth of the spread of the curve

 ‘Statistic that describes the extent of spread of data values around the mean for a variable containing quantifiable data’

Saunders et al, (2003:490)

23

Standard deviation

What is your overall comment at McDonald today?

Very unhappy Very Happy 1 -------------- 2 ------------ 3 -------------- 4 -------------- 5 -------------- 6

McDonald A: Average score: 4

McDonald B Average score: 4

25

Standard Deviation: 1 Standard Deviation: 2

Which McDonald has a better performance ?

Frequency distribution

0

10

20

30

40

50

60

70

80

90

no Yes, less than 10 hours per week

Yes, between 10 - 19.5 hours per week

Yes, between 20 - 30 hours per week

Yes, more than 30 hours per week

Conducting Data Analysis

How does one variable relate to another? This can be answered by testing

significance Helps rule out the possibility that the

results are due to random variations in your sample

Significance  We use the notion of probabilities to determine

levels of significance. The tools we use to calculate this in research include: Correlation analysis Chi-squared analysis T-Test analysis

 These tools are all relative to the distribution curve and are normally used to determine a relationship between sets of data

 If you test the probability that two (or more) variables have a relationship, you need to determine its ‘significance’ level. If this figure is very low (usually p = 0.05 or lower), then you have a statistically significant relationship

28

Inferential Statistics

Correlation Chi-Square T-Test Regression (R2)

Inferential Data Analysis Linear Regression (Bivariate analysis) For example: a Market Survey

Cross-tabulations First step to look for patterns in the

data Independent vs dependent variable

tabulations Dependent vs dependent variable

tabulations Chi-squares give you the goodness of

data by testing the statistical significance of the observed association in a cross-tabulation

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eg. Money vs. Staff Motivation

eg. Stress vs. Staff Motivation

Cross Tabulation - Example

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Q2) Tourism increases traffic jam Total

Strongly Disagree

Disagree Neutral Agree Strongly Agree

Missing

Tourism important to occupation

V. Imp Count 2 2 7 5 1 17

% 11.8% 11.8% 41.2% 29.4% 5.9% 8.3%

Imp. Count 1 2 1 11 6

21

% 4.8% 9.5% 4.8% 52.4% 28.6% 10.2%

Neutral Count 5 2 19 16 42

% 11.9% 4.8% 45.2% 38.1% 20.5%

Unimp. Count 1 6 5 29 18 59

% 1.7% 10.2% 8.5% 49.2% 30.5% 28.8%

V. Unimp

Count 1 4 6 24 31 66

% 1.5% 6.1% 9.1% 36.4% 47.0% 32.2%

Total Count 5 17 16 90 76 1 205

% 2.4% 8.3% 7.8% 43.9% 37.1% 0.5% 100%

Cross-tabulation Example

Q1

34

Software for Data Analysis  Free software is available from the IT Helpdesk located at

the library in Treforest Campus or from IT webpage. eg. NVIVO, SPSS, MS Office 365 .... etc.

 Qualitative data analysis:  NVIVO

 Quantitative data analysis:  SPSS  MS Office 365 (eg. MS Excel, the formula includes:

=average; =median; =mode; =correl; =stdeva  Free Online Survey:

www.surveymonkey.com Google Form: www.google.com/doc

 SNAP: http://www.snapsurveys.com/software/ eg. Mean, Median, Mode, Sum, Minimum, Maximum, Range, Standard Deviation, Standard Error of the Mean, Variance, Skewness and Kurtosis

Conclusion Draw your conclusions These should draw on your analysis

of the data Include some discussion on the

reliability and validity of your data Finally write it up, in a structured

report, be professional and businesslike

35

information/New folder/Bb Topic 4 Philosophy of Research(1).pdf

WELCOME TO THE BUSINESS RESEARCH

PROJECT (BS3S86)

Topic 4: The Philosophy of Research - Identifying your Research Paradigm

Module Leader: Dr. Louise Hung

© University of South Wales

Objectives

By the end of the session students should be able to:

1. Identify their own research paradigm and research approach

2

Research Process

3ebook is available on USW Library webpage

Reading • Alvesson, M. & Deetz, S. (2000) Doing Critical

Management Research SAGE Publications • Guba, E. G. (1990) The Paradigm Dialog SAGE

Publications • Jennings, G. (2001) Tourism Research John

Wiley & Sons Australia, Ltd • Saunders, M., Lewis, P., Thornhill, A. (2011)

Research Methods for Business Students FT Prentice Hall, Chapter 4

4

5

Philosophy of Research Design For the purposes of your business research

project, having an appreciation of the perspectives will: help identify the evidence required

and how it should be interpreted to answer research questions;

help avoid making too many mistakes;

may encourage creativity in research design.

The Research ‘Onion’ (Saunders et al. 2012: 160)  There are six layers in the Research Onion

including:

 1) Research Philosophy  2) Research Approach  3) Methodological Choice  4) Research Strategy  5) Time Horizon  6) Techniques and Procedures

6

The Research ‘Onion’ (Saunders et al. 2012: 160)

7

Deciding upon a Research Philosophy

• Your research philosophy depends upon your standpoint with regard to the development of knowledge.

• This will involve two key concepts: Ontology and Epistemology

8

Key Concept 1: Ontology

A concern with the very essence of what you are examining.

• Ontological standpoint:

• What should be looked at and what is irrelevant.

• What do we believe to be true?

(eg. Research Topic: ‘Staff Motivation + Red Dragon Cafe’)

(eg. Objective or Subjective ?)(Single reality or no single reality ?) 9

Key Concept 2: Epistemology • What kind of things count as knowledge

in a chosen field?

• What will establish it as knowledge?

• What counts as evidence or proof?

(Literature search: Research Topic: ‘Staff Motivation + Red Dragon Cafe’)

eg. Objective: facts, numbers, quantifiable ? How often ? How many ? What factors ? Which factors ? Subjective: words, people’s views, beliefs, ideas ?

eg. Experiment or Socially Constructed ?

10

Ontology and Epistemology

Ontology – What is the nature of reality ?

Epistemology – How do we know things ?

11

Research Philosophy

12

Ontology Epistemology Paradigm+ = (What is the nature

of reality ?) (How do we know things ?) (Your belief of how to

understand knowledge)

Research Paradigms More Objective More Subjective

 -----------------------------------------------------------------

eg. (1) Positivism eg. (2) Interpretivism (Constructivism)

eg. (5) Post-Positivism eg. (4) Critical Theory

eg. (3) Pragmatism

(More Quantitative) (More Qualitative)

13

Quantitative and Qualitative Quantitative: Largely concerned with gathering statistical data and analysing the data using statistical methods.

Qualitative: Collecting data using methods such as in-depth

interviews, focus groups or ethnographic studies. Analysis of the data is through interpretive methods

14

1) Positivism Ontology: What is the nature of reality?

Reality is ‘out there’ – an absolute that can be discovered and measured with work.

15

1) Positivism

16

 Epistemology: How do we know things ?  The knower is distinct from the objective known. We

measure and analyse. e.g. Biology, Mathematics

 Axiology and values of researcher: logic, disengaged, neutral and absolute

1) Positivism: Deductive Approach (Top down)

17

1) Theory

2) Hypothesis

3) Observation

4) Confirmation

1) Positivism - Example  What is London ? (How do we see the world ?)  “I see a city. I can measure the size of it, its location,

climate, population. I can describe the history of London by digging through archaeological record. I can chart its economic power, its demographics, and its physicality. With enough measurement, I can provide a complete picture of what London is – I just need better tools.”

 Ontology: What is the nature of reality ? Single reality

 Epistemology: How do we know things ? Measurement, Objective

18

2) Interpretivism (Constructivism)

Ontology: What is the nature of reality ?

 ‘Reality’ is made by people in social ways – it is a product of mutual understanding.

19

2) Interpretivism (Constructivism)

20

 Epistemology: How do we know things ?  Knowledge is co-constructed. We know by engaging

in building and sharing. e.g. education, sociology

 Axiology and value of researcher: Rationality, human, contextual

2) Interpretivism: Inductive Approach (Bottom up)

21

1) Observation

2) Identify Theme

3) Tentative Hypothesis

4) Theory

2) Interpretivism (Constructivism) - Example  What is London ? (How do we see the world ?)  “I see a city – a hub of human activity. Cities organise

the world, they are complex and multiple communities that give life meaning and purpose. It is a point in global exchange and culture. London has a lot of different functions for many people – it is a diverse city with a rich history, and is understood differently in different contexts.”

 Ontology: What is the nature of reality ? Multiple realities

 Epistemology: How do we know things ? Socially constructed, subjective

22

Positivism Constructivism

Approach Quantitative Qualitative

Ontology Single reality Multiple realities

Epistemology Independence of the

knower and the known Inseparability of the

knower and the known

Causality There is cause and

effect The cause and effect are indistinguishable

Logic Deductive Inductive

Positivism vs. Constructivism (Interpretivism)

3) Pragmatism  External, multiple, view chosen to best enable

answering of research question  Either or both observable phenomena & subjective

meanings can provide acceptable knowledge dependent upon the research question.

 Focus on practical applied research, integrating different perspectives to help interpret the data.

 Values play a large role in interpreting results, the researcher adopting both objective & subjective points of view

 Mixed or multiple method designs, quantitative & qualitative

24

3) Pragmatism Ontology: What is the nature of

reality ? Reality is constantly negotiated, debated, or interpreted.

Epistemology: How do we know things ? Knowledge should be examined using whatever tools are best suited to solve the problem.

25

4) Critical Theory

Ontology: What is the nature of reality?

 ‘Reality’ is a product of power relations – it is produced through these tensions.

26

4) Critical Theory Epistemology: How do we know things?

Knowledge is political and values-laden. We know through values and standpoint. e.g. (some) sociology, political economy

 ‘The philosophers have only interpreted the world in various ways; the point is to change it!’ -- Karl Marx --

27

4) Critical Theory  Axiology and values of researcher:

critique, social justice, transformative

 Determined by history/outside forces  Try to make a change

 Historical analysis  Mainly qualitative

28

4) Critical Theory- Example  What is London ? (How do we see the world ?)  “I see the city of London – a site of power. London is a

global megacity from which imperialism spread, and from which Western power continues to push out into the world. I see the inequity of rich and poor within the city, and between that city and the rest of the world. I see how London must change for the better.”

 Ontology: What is the nature of reality ? Product of power relations

 Epistemology: How do we know things ? Through values

29

5) Post-Positivism • A modified version of positivism – control

and prediction (however) continue to be the aim (Guba 1990)

• Trochim (2006: 2) “all observation is fallible and has error and that all theory is revisable”

• Post-positivist philosophy recognises that ‘pure objectivity’ is an absurd assumption

• Supports the use of multi measures and observations to overcome the fallible shortcomings of singular research methods

30

5) Post-Positivism

Ontology: What is the nature of reality?

Reality is ‘out there’, but there may be limits to our ability to accurately capture it.

31

5) Post-Positivism  Epistemology: How do we know things ?  A researcher builds an approximation of the object of

research. e.g. psychology, medicine

 Falsifiability:  Karl Popper helped with the switch in science from positive

proofs, to the ‘null hypothesis’.  eg. The presence of a single black swan disproves the theory

that ‘all swans are white’.

 Axiology and values of researcher: reason, dispassionate, neutral, universal

32

5) Post-Positivism - Example  What is London ? (How do we see the world ?)  “I see a city. I can measure its size, but I am aware that

it’s only an approximation: greater London is growing all the time. How we define and measure things is imperfect, and so the picture is never quite complete – even if I acknowledge that London is something objective and real. Sometimes, it is easier to say what London is not.”

 Ontology: What is the nature of reality ? Single reality  Epistemology: How do we know things ? Builds an

approximation of the object of research, measurement

33

Concept Map for Research Paradigms - Summary

34

Positivism Interpretivism (constructivism)

Pragmatism

Ontology: single reality

Epistemology: measurement

Ontology: multiple realities

Ontology: constantly negotiated, debated,

or interpreted

Epistemology: tools are best suited to solve the problem

Epistemology: Socially

constructed

Critical Theory

Ontology: multiple realities

What is London ? (ie. How do you see the world ?)

Post- positivism

Epistemology: value, social

justice, ethics Ontology:

single reality

Epistemology: measurement, approximation of the object of

research

Concept Map for Research Paradigms - Example Positivism Interpretivism

(constructivism)

Pragmatism

Ontology: single reality Epistemology:

measurement

Ontology: multiple realities

Ontology: constantly negotiated, debated, or interpreted

Epistemology: tools are best

suited to solve the problem

Epistemology: Socially

constructed What is staff

motivation and Red Dragon Café ? (ie. How do you see

the world ?)

Are the staff happy or not ? It is a simple question & objective. Yes or No.

Use questionnaire to measure staff satisfaction level.

If staff is happy or not, it is subjective as they have different culture & background.

Use in-depth interview to understand how do they see happiness in work.

Research aim has to adapt according to negotiation with the company, project team, or other factors.

The focus of research problem/aim is adapting, choose the most appropriate data collection methods e.g. mixed methods

Example A - Positivism - Identifying your Research Paradigm

 Research Topic: Staff Motivation & Red Dragon Cafe  What do we believe to be true ? Objective ?  Your group favoured Research Paradigm ? Positivism ?  Research Question: eg. What ? Which ? How much ?

 What motivating factors are important for staff in Coffee Shop Industry in South Wales ?

 Deductive or Inductive ? Deductive: Top down ?  Quantitative or Qualitative ? Quantitative ?  Data collection methods ? eg. large scale survey

questionnaire, structured interview, experiment, quantitative observation …

36

Example B - Interpretivism - Identifying your Research Paradigm

 Research Topic: Staff Motivation & Red Dragon Cafe

 What do we believe to be true? Subjective ?  Your team favoured Research Paradigm ?

Interpretivism  Research Question: eg. Why ? How ?

 How to improve staff motivation at Coffee Shop Industry in South Wales ?

 Deductive or Inductive ? Inductive: Bottom up ?  Quantitative or Qualitative ? Qualitative ?  Data collection methods ? eg. face to face semi-

structured interview, focus group, qualitative observation ...

37

Example C - Pragmatism - Identifying your Research Paradigm

 Research Topic: Staff Motivation & Red Dragon Cafe  What do we believe to be true? Both Objective & Subjective?  Your team favoured Research Paradigm ? Pragmatism ?  Research Question: eg. What ? Which ? How much ? Why ?

How ?  What motivating factors are important for staff in Coffee

Shop Industry in South Wales ?  Or, How to improve staff motivation at Coffee Shop Industry

in South Wales ?  Deductive or Inductive ? Deductive or Inductive ?  Quantitative or Qualitative ? Both Quantitative &

Qualitative ?  Data collection methods ? Mixed Methods ? eg. large scale

survey questionnaire, structured interview, experiment, quantitative observation, face to face semi-structured interview, focus group, qualitative observation … 38

Conclusion: So why a Philosophy? • Saunders et al (2003) when considering selection of

research philosophy suggest that “it would be easy to fall into the trap of thinking that one research approach is better than another…they are better at doing different things” (p.85).

 It is not the question of whether one is better than the others ! The question should be which paradigm is more suitable for some types of research questions than others.

• Research philosophies help the researcher to conceptualise the problem, select a philosophical position, challenge that position and “then if we think it is appropriate, behave in a different way” (Saunders et al 2003: 85).

39

Week 4: Homework (Group Discussion Board) (Research Paradigm, Methodological Choice, Approach, Method)

• Task 1: Refer to your pre-recorded lecture and slides (Topic 4: Research Philosophy) for examples. Use the table on next slide to complete your Week 4 Homework (Research paradigm).

• Task 2: Write down your improved Research Question and Research Aim • Task 3: What is your group favoured Research Paradigm? Why? • Task 4: Methodologically, would your research be deductive or inductive ? • Task 5: Do you intend to use a qualitative or a quantitative approach or both ?

Why ? • Task 6: What data collection method(s) would you then think are the most

appropriate for your research topic? • Task 7: Discuss & agree with your team, then post 1 copy of your completed

homework to your blackboard [Online Workshop (on the left hand side of your menu)  Group  Group Tools - Group Discussion Board -Week 4: Homework - (Research Paradigm, Methodological Choice, Approach, Method]

• Task 8: Respond to the posts by other teams. eg. what they did well, what can you suggest them to improve, or others … etc.

40

Group Name: Topic 4: Identifying your Research Paradigm

Write down your improved Research Question & Aim. eg. 1) Objective: What, Which, How much ? 2) Subjective: Why, How ? 3) Objective & Subjective: What, Which, How much, Why, How ?

Task 1: What is your group favoured Research Paradigm ? Why ? eg. Positivism (more objective) <------Post-positivism <--- Pragmatism -- Critical Theory -----> Interpretivism (more subjective)

Task 2: Methodologically, would your research be Deductive or Inductive ? Why ? eg. Deductive (Top down/Objective) or Inductive (Bottom up/Subjective)

Task 3: Do you intend to use a Quantitative, a Qualitative approach or both ? Why ?

Task 4: What method(s) would you then think are the most appropriate for your research topic? Why ? eg. 1) Objective (quantitative): large scale survey questionnaire, structured interview, quantitative observation, experiment. 2) Subjective (qualitative): face to face semi-structured interview, focus group, qualitative observation ..., etc. 3) Objective & Subjective: mixed methods

41

information/New folder/Bb Topic 5 Formulating Research Design(1).pdf

WELCOME TO THE BUSINESS RESEARCH

PROJECT (BS3S86)

Topic 5: Formulating your Research Design

Module Leader: Dr. Louise Hung

© University of South Wales

Objectives By the end of the session students

should be able to:

Understand the process of Research Design

Identify their own Research Strategy

Research Process

3ebook is available on USW Library webpage

Reading

• Saunders, M. et al (2012) Research Methods for Business Students FT Prentice Hall, Chapter 5

Introduction (1/2) When you complete your research process,

your research will be assessed on if it answered the research questions and if it was consistent.

Need to ensure these will be achieved at the beginning by designing your research.

The design should chart your path through the layers of the ‘Research Onion’.

Introduction (2/2) Unlikely that any research will include all

the theories mentioned in the ‘Research Onion’ but all research should probably cover at least one theory or method from each layer.

Putting some thought into your design will also give you more insight into the issues you are dealing with and this in turn will strengthen your research.

The Research ‘Onion’ (Saunders et al. 2012: 160)

Research Design – Methodological Choice  The type of data you collect is a decisive factor on what

kind of outcome you can achieve.  1) Quantitative and involves numeric data.

- related to the positivist philosophical perspective - deductive approach

2) Qualitative, involves non-numeric data eg. words - interpretive philosophy - inductive approach

3) Multimethod or mixed methods (eg. multimethod = several qualitative methods or several quantitative methods, mixed methods = both quantitative and qualitative methods)

Research Design – Methodological Choice

Saunders et al, 2012, p.165

Research Design – Methodological Choice

Choice of a particular philosophical orientation (ie. positivism, interpretivism or pragmatism) and approach (ie. deductive vs. inductive) is the key driver for the overall methodology, this decision alone will not get you very far !

 Your methodology needs to be further clarified in relation to the research design & thereafter in relation to the research methods or techniques that you will use to collect empirical data. (Guba and Lincoln, 1998)

Research Strategies When considering research strategies, it is

important to remind that (Saunders et al, 2009):

 1) These research strategies should not be thought of as mutually exclusive; this means that they can be combined if and when necessary (Creswell, 2006; Saunders et al., 2009).

 2) Each of them has specific advantages and disadvantages.

Choosing your Research Strategy The most popular research strategies are the

following:

 1) Survey  2) Case study  3) Action Research  4) Ethnography  5) Grounded Theory

More Quantitative Data

More Qualitative Data

More Quantitative or Qualitative Data

1) Research Strategy: Survey  A common misconception surrounds

questionnaires and surveys.  A questionnaire is a method, whereas a survey is

a research strategy.  This is because a survey can employ different

methods, including structured interviews, structured observation and, most commonly associated with this research strategy, questionnaires.

 This strategy is usually associated with deductive reasoning.

1) Research Strategy: Survey Questions used: multiple choice or closed

questions (eg. questionnaire); open or open- ended questions (eg. ‘Other comments’).

Data can be analysed by quantitative or qualitative methods.

A large amount of data from a sizable sample should normally be collected.

 It offers a good balance between cost in terms of time and money and the number of participants that can be reached.

Data collection method: e.g. questionnaire

2) Research Strategy: Case Study Case study design involves an extensive study

of one or more individuals or organisations in the entirety of the reality, and it involves collecting such data by watching certain behaviour types, conducting interviews with participants and identifying records of good or bad performance in history.

 The focus is on identifying the particular relevance and importance of an individual(s) or organisation(s) to the area of study and the topic.

2) Research Strategy: Case Study  A case study takes a single, or a number of cases to

study.  These cases can be communities, social groups,

employers, events or organizations.  This method is very popular across social sciences.  Usually involves qualitative data.  Very popular in management research especially

when looking at organizations.  Could be challenging as there are decisions about

what to include and what to leave out.  Data collection methods: e.g. in-depth interview,

observation, questionnaire

3) Research Strategy: Action Research  This research occurs when researcher and participants

collaborate to solve problems and implement solutions. Examples might arise in organisational contexts in consultancy or in change programmes.

 The researcher collaborates with participants and so gains practical insights into the process, procedures and problem-solving activities.

 The great benefit of this process is that it enables the researcher to have hands-on experience of working within the environment and tackling real problems that arise.

 However, similar to ethnography research strategy, this process can be time-consuming and may require a level of travel and cost.

3) Research Strategy: Action Research  It can also be difficult to gain access/sponsorship.

Conflicts of interest might arise between researcher and sponsor/participants.

 Researcher is active within their research.  ‘Learning by doing’.  Researcher identifies a problem, attempts to

resolve it, and evaluates the results after potential solution implemented.

 This process may be repeated a number of times  Data collection methods: e.g. interview, focus

group, observation, questionnaire

4) Research Strategy: Ethnography  The term 'ethnography' refers to folk (ethno)

description (graphy).  The ethnographer's method is to live among the

people in the study & record their way of life (frequently using modern media, such as digital audio/visual recording).

 Adopt a more interpretive & naturalistic focus by using the language of those being studied in writing cultural accounts of their shared beliefs, behaviours, interactions, language, rituals & the events that shaped their lives (Cunliffe, 2010) eg. full-time or part-time work

4) Research Strategy: Ethnography  The most common ways of conducting this

process are through observation, note-taking and using modern media to record events.

 This provides rich insights into life and unfolding events as they occur.

A great benefit of the process is also that the data is recorded for later analysis.

However, it is quite time-consuming and requires a certain amount of travel and cost.

Data collection method: e.g. participant observation, in-depth interview

5) Research Strategy: Grounded Theory  This is an approach to the analysis of qualitative

data that aims to generate new theory from the data.

 This method is often associated with case study research.

 The method requires the researcher to observe and follow a series of steps to gather, analyse and present the data.

 This step enables the researcher to outline a series of steps that can be followed to add rigour and robustness into the research process.

5) Research Strategy: Grounded Theory Developed as a process to analyse, interpret

and explain the meanings that social actors construct to make sense of their everyday experiences in specific situations. (Charmaz, 2006; Glaser & Strauss, 1967; Suddaby, 2006)

 Researcher collects and analyses data simultaneously, developing analytical codes as these emerge from the data in order to reorganise these data into categories.

Moving between induction and deduction (Strauss & Corbin, 1998; Suddaby, 2006)

5) Research Strategy: Grounded Theory A great benefit of following a grounded theory

approach is that it enables a logical sequence of cross-checking the data with theory, consequently providing more accurate analysis of the results.

 The biggest downfall of the process is that it has been subject to abuse and modification, with researchers claiming to follow a grounded theory approach but not following closely the protocols and procedures.

Date collection method: e.g. in-depth interview, participant observation

Time Horizon  The term ‘time horizon’ refers to whether the research

will be conducted over a prolonged period of time or will offer a snapshot of the situation at a specific point in time.

 Your decisions in this respect will be largely governed by the time available to complete the business research project.

 The short timeframe involved will likely lead you towards a cross-sectional approach, which involves studying an issue at a particular point in time.

 Cross-sectional approach is perfect for studying, eg. the attitudes concerning a particular event but is not so suitable for research that seeks to monitor change over a particular period of time.

 Longitudinal approaches are far more suited towards studies that seek to monitor change or the development and implementation of a strategy.

Conclusion 1/2  Research design is the way a research

question and objectives are operationalised into a research project.

 The research design process involves a series of decisions that need to combine into a coherent research project.

 Research design will be informed by your research philosophy.

A choice has to be made between using a mono method, multimethod or mixed methods.

Conclusion 2/2

A decision will be made to use one or more research strategies, related to the nature of the research question and objectives and to ensure coherence with the other elements of your research design.

Research strategies discussed were: Survey, Case Study, Action Research, Ethnography, Grounded Theory.

Week 5: Homework (Group Discussion Board)

 Task 1: Discuss what Methods you will use to collect data eg. quantitative, qualitative, mixed, or multimethod

 Task 2: Discuss which Research Strategy is most appropriate for your Research Project eg. Survey, Case Study, Action Research, Ethnography or Grounded Theory.

 Task 3: Explain the reasons for your choice(s) of research strategy eg. benefits or limitations of your choice(s) to your participants, your team, or the organisation ... etc.

 Task 4: Refer to the Week 5 pre-recorded lecture and slides for examples, post your ‘Week 5 Homework’ to blackboard. Online Workshop (on the left hand side of your menu) - Group Tools - Group Discussion Board -Week 5: Homework (Research Design & Strategy)

 Task 5: Respond to the posts by other groups. eg. what they did well, what can you suggest them to improve, or others … etc.

27

information/New folder/Bb Topic 6 Sampling.pdf

WELCOME TO THE BUSINESS RESEARCH

PROJECT (BS3S86)

Topic 6: Probability & Non-probability Sampling Techniques

Module Leader: Dr. Louise Hung

© University of South Wales

Objectives  By the end of the session students should be able to:

 understand the need for sampling in business and management research;

 identify a range of probability and non- probability sampling techniques;

 select and use appropriate sampling techniques for a variety of research scenarios; and

 assess the representativeness of respondents.

Research Process

3ebook is available on USW Library webpage

Reading  Assael, H. and Keon, J. (1982) Non-Sampling vs

Sampling Error in Sampling Research. Journal of Marketing. Spring, 114-23.

 Fink, A. (1995) How to Sample in Surveys. Thousand Oaks, CA: Sage.

 Henry, G. T. (1995) Practical Sampling. Thousand Oaks, CA: Sage.

• Saunders, M. et al (2012 or latest) Research Methods for Business Students FT Prentice Hall, Chapter 7

The Research ‘Onion’ (Saunders et al. 2012: 160)

Introduction  ‘How do you select your sample?’ is

an important issue to be considered before data is collected.

Many dangers may cause problems, so it is useful to learn ways to minimize the risks, learn the types of sampling & how to decide on the sampling size.

Sampling

Saunders, Lewis and Thornhill, Research Methods in Business, 4th Edition © Pearson Education Limited 2007

A population refers to a group of people or objects which form the subject of study. The sample is smaller than the general population, but the information drawn from the sample is considered as though it applies to the whole universe. A sample occurs when a number of cases or elements (called the sampling unit) is drawn from a population and examined in some detail.

The need to sample  Should a sample be taken? (The

alternative is to collect data from the whole population: a census)

 If so, what process should be followed?  What kind of sample should be taken?  How large should it be?  What can be done to control and adjust

for non-response error?

The process of sampling Define population

Define frame for population

Select sampling unit

Choose sampling method

Decide of sample size

Define sampling plan

Select sample

Defining the population

Elementary sampling unit (ESU): e.g. individual elements within population (male/female, teenager), define with questions (e.g. who, where, how ….), define key characteristics, operational (pragmatic) definitions

Extent

Time

Defining frame for population

11

 Include each element once only

Don’t exclude any element

Must cover whole population

Up-to-date and accurate

Convenient to use

Sampling Methods

Types of Non-probability Sampling

1) Convenience Sampling 2) Quota Sampling 3) Purposive Sampling 4) Snowball Sampling

1) Non-probability Sampling: Convenience Sampling

Data collection from population members who are conveniently available to participate in study.

See example on next page

1) Non-probability Sampling: Convenience Sampling - Examples

Choosing 5 people from a class or choosing last 5 names from a list of students.

For conducting surveys, online questionnaires could be sent to acquaintances (to the researchers) via Social Media eg. Facebook, Twitter.

Continue on next page

1) Non-probability Sampling: Convenience Sampling – Advantages & Disadvantages

Advantages  1. Relatively easy to

get a sample  2. Inexpensive,

compared to other techniques

 3. Participants are readily available.

4. Cheap & Quick

Disadvantages 1. Selection bias or influences beyond the control of the researcher. 2. Sampling error. 3. Misrepresentation of data.

2) Non-probability Sampling: Quota Sampling

The sample is derived based on some knowledge of the important characteristics of the population as a whole e.g. age, socio-economic status, ethnicity.

A quota for each category is then selected to form the samples.

Continue on next page

2) Non-probability Sampling: Quota Sampling – Advantages & Disadvantages

Advantages:  1. Allows researchers to

sample a subgroup that is of great interest to the study.

 2. Sample can be controlled for certain characteristics.

 3. Low cost  4. Fast  5. No sampling frame

required

Disadvantages: 1. Cannot be assumed that the sample is representative 2. Difficult to assess sampling error 3. Sample not randomly selected, could have bias.

3) Non-probability Sampling: Purposive Sampling

 Purposive sampling also known as judgemental, selective or subjective sampling.

 Researcher relies on his or her own judgement when choosing members of population to participate in the study.

 Choose people whom you are sure could correspond to the objectiveness of your study. Like selecting those with experience or interest in your study. See example on next page

3) Non-probability Sampling: Purposive Sampling - Example

 In a study where in a researcher wants to know what it takes to graduate quantity surveyor in university, the only people who can give a researcher first hand advise are the individuals who graduated quantity surveyor.

With this very specific & very limited pool of individuals that can be considered as a participant, the researcher must use purposive sampling.

Continue on next page

3) Non-probability Sampling: Purposive Sampling – Advantages & Disadvantages

 Advantages:  1. Cost-effective & time-

effective  2. May be the only appropriate

method available if there are only limited number of primary data sources who can contribute to the study.

 3. No special knowledge of statistic required.

 4. The approach is understood & has been refined by the experience of researcher.

Disadvantages: 1. Errors in judgement by researcher in selecting samples 2. Difficult to generalise research findings. 3. Samples selected could be very large. 4. Lack of logic in the selection of sample or its size. 5. Not randomly selected, could be biased.

4) Non-probability Sampling: Snowball sampling

This technique seeks to develop a sample of respondents by gaining referrals from known or existing participants.

 eg. network, chain or reputational referral.

When should we use it ? When participants are hard to find eg.

special characteristics, experience, sensitive research topics

4) Non-probability Sampling: Snowball Sampling – Example 1/2

 This is John the cat.  One day, John was eating fish at a restaurant when

John was murdered.

 A policeman came to the restaurant for this case.

 He asked the Chef: ‘Did you witness the murder ?’

 Chef replied: ‘No, I was cooking in the kitchen. Why don’t you ask the waitress ?’

4) Non-probability Sampling: Snowball Sampling – Example 2/2

 The policeman asked the waitress: ‘Did you witness the murder ? What did the murderer look like ?’

 Waitress replied: ‘He was a young man wearing a blue shirt. I think he lives next door. Try asking the landlord.’

 And so, the investigation went on until the suspect was found.

 In this scenario, the policeman used a sampling technique called ‘Snowball Sampling’. Continue on next page

4) Non-probability Sampling: Snowball Sampling – Advantages & Disadvantages

Advantages:  1. Helps you discover

characteristics about a population that you weren’t aware existed.

 2. Allows for studies to take place otherwise it’s impossible to conduct – due to lack of participants.

Disadvantages: 1. No guarantee about the representativeness of samples. 2. Difficult to determine the sampling error & make generalisation. 3. Existing participants may be hesitant to provide names which raises ethical concern. 4. Could lead to bias

Types of Probability Sampling

You now have 4 options: 1) Simple random sampling 2) Systematic sampling 3) Stratified sampling 4) Cluster sampling

1) Probability Sampling: Simple Random Sampling

Everyone has an equal chance of being selected.

Anyone who meets the inclusion criteria will be assigned a number.

List of the population must be available and a randoming device used e.g. lottery method, luck draw machine in Christmas party, computer generated numbers.

2) Probability Sampling: Systematic Sampling

Not entirely random but contains a random element

Operates on the basis of randomly selecting the first item & then systematically selecting the remainder of the sample at intervals determined by the size of the population & the size of the sample required

 eg, if a sample of 50 were required from a population of 1000, the first item would be chosen at random up to 20 (1000 ÷ 50). Thereafter, the twentieth value after that item would be selected.

3) Probability Sampling: Stratified Sampling

Dividing the population into groups (or strata), groups selected on basis they share characteristics relevant to the study (based on a review of the literature and/or pilot study) eg. race, gender, age & functional level.

Might be undertaken to ensure that adequate representation of the population is achieved.

See example on next page

3) Probability Sampling: Stratified Sampling - Example

Reasons: Ensure either the sample reflects the

population (proportionate sampling) or Ensure that there is some (or all)

representation of particular groups (disproportionate sampling).

 Example: If a sample of 30 workers were to be interviewed from a population comprised of 80% males & 20% females (& this was an important variable), then the sample should reflect this.

 ie. 24 males + 6 females = 30 workers

4) Probability Sampling: Cluster Sampling

The population is divided into discrete groups or clusters prior to sampling.

A random sample (systematic or simple) of these clusters is drawn.

Probability Sampling: Other Determinants of Sample Size

 Budget available  Constrains accuracy possible

 Rules of thumb  Guessed by client / researcher based on

previous studies eg. learn from ‘Research Method’ section in an academic journal article

 Number of sub-groups to be analysed  Sample must be large enough to contain

reasonable numbers of each sub-group. Sample Size Calculator: www.raosoft.com/samplesize.html

Sample Size  Sample size is governed by:

 The confidence required in the data (the level of certainty that the sample findings represent the characteristics of the total population)

 The margin of error that can be tolerated (the accuracy required for any estimates made from the sample)

 The types of analyses that will be undertaken, (statistical methods) in particular the number of categories into which the data will be subdivided (size per cell)

 The size of the total population from which the sample is drawn

 Judgement  Cost Sample Size Calculator: www.raosoft.com/samplesize.html 

Typical Sample Sizes Type of Study

Minimum Size

Typical Range

Problem identification research (e.g. market potential)

500 1000- 2500

Problem-solving research (e.g. pricing) 200 300-500

Product Test 200 300-500

Test marketing studies 200 300-500

TV, radio, or print advertising (per commercial /ad tested)

150 200-300

Test-market audits 10 stores 10-20 stores

Focus Groups 2 groups 4-12 groups

Malhotra & Birks "Marketing Research", 2003, pg 361

Defining the sampling plan Objectives

maximising amounts of relevant information

minimising error

Defining operational sampling policies

eg coding issues

eg non-response

Sampling errors

Response Rates Non-response is due to four inter-

related problems: Refusal to respond Ineligibility to respond Inability to locate respondent Respondent located but unable to

make contact

Response rate formulae

 The total response rate can be determined as:

 The active response rate can be determined as:

Activity  Hans has decided to undertake a telephone survey of

people who had left his company's employment over the past five years. He obtained a list of the 1,034 people who had left over this period and selected a 50 per cent sample. Unfortunately, he could obtain current telephone numbers for only 311 of the 517 ex- employees who made up his total sample. Of these 311 people, he obtained a response from 147. In addition, his list of people who had left the company was inaccurate. Nine of those he contacted had left the company over five years earlier.

 Total number in population?  Total number in sample?  Number of those unreachable?  Number of those ineligible?

Answers

 Total Response Rate = 147 / (517 - 9) = 28.9%  Active Response rate = 147 (311 - 9) = 48.7%

Response Expectations

Postal – 30 per cent (Owens & Jones, 1994)  Interviews – 50 per cent (Kevin, 1992)

Expect variability

More about Sampling ?

 https://www.youtube.com/watch?v=be9e-Q-jC-0

information/New folder/Bb Topic 7 Ethical consideration for research project(1).pdf

WELCOME TO THE BUSINESS RESEARCH

PROJECT (BS3S86)

Topic 7: Ethical Considerations for Research Project

Module Leader: Dr. Louise Hung

© University of South Wales

Objectives

By the end of the session students should be able to:

1. Evaluate the issues of ethics in research 2. Consider the strategies for dealing with

ethical issues

2

Research Process

3ebook is available on USW Library webpage

Reading

Saunders, M., Lewis, P., Thornhill, A. (2012) Research Methods for Business Students FT Prentice Hall, Chapter 6

4

Introduction

Primary Research ...  ... Brings you into close contact with your

topic, so such research involves a range of complex ethical challenges.

 It is your responsibility as a researcher to strive to meet ethical standards in research.

5

What do ‘Ethical’ and ‘Legal’ actually mean in research ?

 a) Ethics is concerned with a set of social and moral principles that guide research. Norms for conduct that distinguish between acceptable and unacceptable behaviour.

b) Legal refers to the law. Thus, research, which is both ethical and

legal, is research that follows the ‘guiding principles’ and stays within the confines of the law. 6

7

What are the ethical principles to adhere to in Research ?  1. Informed consent  2. Protection from physical

and psychological harm  3. Confidentiality and anonymity 4. Data protection  5. Right to withdraw 6. Deception

8

1. Ethical Principle: Informed Consent

A signed declaration from someone agreeing to do something when they have been explained the details of what they have been asked to do and the purposes of the study/investigation.

So participants can make an informed decision about whether to participate.

(see next slide and blackboard Topic 7 for USW consent form)

9

Consent Form (see blackboard Topic 7 for an e-copy)

10

2. Ethical Principle: Protection from physical and psychological harm

During a research study, participants should not experience negative psychological or physiological effects.

eg. potential risk and harm: eg. embarrassment, anxiety, self esteem, resentment, disturbance, intrusion

11

3. Ethical Principle: Confidentiality and Anonymity

Ensuring that no one except the researcher(s) knows the participants’ identities & that their info is kept private unless permission is granted by the participant. Names of participants sometimes are replaced by their job titles to protect their identity.

12

4. Ethical Principle: Data Protection

The process of securing all information collected so that it is only seen by the people in which it was originally agreed to be seen by. This often involves the locking-away of files or the use of passwords on electronic devices to ensure this.

13

5. Ethical Principle: Right to withdraw

As all participation in research should be voluntary, participants should never be forced to take part in something against their wishes. Participants wishing to cease data collection should be allowed to do so with no negative consequences. They also have the right to refuse permission for the researcher to use their data.

14

6. Ethical Principle: Deception

A participant is not told the true aims of the study (eg. what participation will involve) and thus cannot give truly informed consent. eg. ‘fake’ treatment

15

Have this ‘energy drink’ before the gym & you will run for longer!

6. Ethical principle: Deception

 In this example. The ‘energy drink’ was simply water with food colouring. The participant was told that the drink would help him run for longer than he usually can, however the drink was no different to his usual drinks; he was just told that it was and that it would help, which he believed and subsequently ran for longer.

16

Strategies for dealing with ethical issues

Strategy 1: Cost and benefit Analysis

Strategy 2: Using ethical guidelines

17

Strategy 1: Cost and Benefit Analysis A systematic approach to estimating the

negatives (cost) & positives (benefit) of any research.

 Benefit – Cost = more than zero ?  negatives = Cost: eg potential risk or harm on

participants ... etc.  eg. embarrassment, anxiety, self esteem,

resentment, disturbance, intrusion  positives = Benefit: eg. increase social

good/reduce social harm on society, business, industry, academic world ... etc.

 eg. promote social good/prevent social harm

18

Strategy 2: Using ethical guidelines A set of principles designed to help

professionals behave honestly with integrity.

 1. Ethical clearance,  2. Informed consent,  3. Protection from harm,  4. Confidentiality,  5. Right to withdraw,  6. Debriefing

(Refer to USW General Ethical Guidelines for more details) 19

Strategy 2: Using ethical guidelines 1. Ethical Clearance  Is obtained prior to data collection

commencing. This is the process that requires researchers to give due consideration to what it is like to be a participant in the given story. Clearance is usually awarded by an Ethics Committee, eg. USW Ethics Committee. (Refer to the last page of your Research Proposal form for ‘Ethical Declaration’)

20

Strategy 2: Using ethical guidelines

2. Informed consent Get a formal written consent

from the participant. (except anonymous questionnaire) (see blackboard Topic 7 for USW consent form)

21

Strategy 2: Using ethical guidelines 3. Protection from harm Avoid any risks that are greater than

experienced in everyday life. Stop the study if harm is suspected.

 eg. risk & harm: eg. embarrassment, anxiety, self esteem affected, resentment, disturbance, intrusion

 *** You can’t avoid all these issues. You must balance all these concerns against the potential benefits of your research.

22

Strategy 2: Using ethical guidelines

4. Confidentiality Researchers should not record the

names of any participants in their final report; they should use either numbers or fake names. eg. Restaurant Manager, Marketing Manager, Supervisor A, B, C … etc.

23

Strategy 2: Using ethical guidelines

5. The right to withdraw Participants should be informed at the

beginning of the study that they have the right to withdraw. eg. consent form

24

Strategy 2: Using ethical guidelines

6. Debriefing Re-explaining the purpose of the study and

encouraging the participant(s) to ask any questions that they may have. Also, the researcher will address any harm to the participant(s) that arose during the study and remind participant(s) of their anonymity & confidentiality.

25

Conclusions

Awareness of ethics in research Strategies for dealing with ethical

issues *** Question ethics when

undertaking your research ***

26

Week 6: Homework (Group Discussion Board)  Task 1: Discuss with your team what are the Costs and

Benefits of doing your research project ?  Task 2: Costs and Benefits ? Which one is bigger for your

project ?  Task 3: What would you do to minimize the potential risk

or harm on your participants ?  Task 4: Refer to the Week 6 pre-recorded lecture and slides for

examples, post your ‘Week 6 Homework’ to blackboard. Online Workshop (on the left hand side of your menu) - Group Tools - Group Discussion Board -Week 6: Homework (Research Ethics)

 Task 5: Respond to the posts by other groups. eg. what they did well, what can you suggest them to improve, or others … etc.

 ***************************************************************************************************************************************************************************************************************

 TIPS: Strategy 1: Cost and Benefit Analysis:  Benefit – Cost = more than zero ?  Cost = potential Risk, Harm eg. embarrassment, anxiety, self esteem,

resentment, disturbance, intrusion.  Benefit = promote social good/prevent social harm on society, business,

industry, academic world ... etc. 27

information/New folder/Bb Topic 8 Collecting Qualitative Data.pdf

WELCOME TO THE BUSINESS RESEARCH

PROJECT (BS3S86)

Topic 8: Collecting Qualitative Data Module Leader: Dr. Louise Hung

© University of South Wales

Objectives

By the end of the session students should be able to:

Consider the use of Qualitative Interview, Focus Group and Qualitative Observation in collecting qualitative Data

Research Process

3ebook is available on USW Library webpage

Reading

• Bryman and Bell (2003) Business Research Methods, 2nd edition, Chapter 16

• Saunders, M., Lewis, P., and Thornhill, A. (2012) Research Methods for Business Students, 6th edition, Pearson Education Ltd, Chapter 10.

The Research ‘Onion’ (Saunders et al. 2012: 160)

Introduction Qualitative Research:

Collecting data using methods such as interviews, focus groups or ethnographic studies. Analysis of the data is through interpretive methods

 ‘… qualitative research subsumes several diverse research methods that differ from each other considerably ...’ (Bryman and Bell, 2003)

Merits of Qualitative Methods  Correspond to the qualitative nature of

experiences.  Brings people into social research.  Results understandable to people who are not

statistically trained.  Able to encompass personal change over time.  Suited to investigating face-to-face interaction

between people (symbols, gestures, etc.).  Suited to providing an understanding of

people's needs and aspirations.

Features of Qualitative Research • An inductive view of the relationship between theory and

research, whereby the former is generated out of the latter

• An epistemological position described as interpretivist, meaning that, in contrast to the adoption of a natural scientific model in quantitative research, the stress is on the understanding of the social world through an examination of the interpretation of that world by its participants; and

• An ontological position described as constructionist, which implies that social properties are outcomes of the interactions between individuals, rather than phenomena `out there' and separate from those involved in its construction

Main Research Methods Associated With Qualitative Research

Ethnography/participant observation Qualitative interviewing Focus groups Language-based approaches: conversation

analysis; discourse analysis Collection and qualitative analysis of texts

and documents

Common Contrasts Between Quantitative and Qualitative Research

Quantitative Qualitative Numbers Words Point of view of researcher Points of view of participants Researcher distant Researcher close Theory testing Theory emergent Static Process Structured Unstructured Generalization Contextual understanding Hard, reliable data Rich, deep data Macro Micro Behaviour Meaning Artificial settings Natural settings

The Main Steps in Qualitative Research

1. General research questions

2. Selecting relevant site(s) and subjects

3. Collection of relevant data

4. Interpretation of data

5. Conceptual and theoretical work

6. Writing up findings/conclusions

5b. Collection of further data

5a. Tighter specification of the research question(s)

Qualitative Interview Each method of collecting data has

different advantages and disadvantages and they are better suited for different situations and goals.

The qualitative interview is one of the popular methods used in research. It mirrors actions that all people do in their everyday lives but it is implemented in a more scientific way.

Types of Interview 1/3  The interview is essentially a conversation where the

researcher tried to make clear the relevant questions and record the responses. There are a number of different types of interviews.

 The choice depends both on the goals but also the limitations.

 The level of structure of the interview also depends on the overall purpose of the research. For example,  1. Structured interview: suitable for descriptive or

explanatory research. (Quantitative data)  2. Semi-structured interview: suitable for exploratory

and explanatory (Qualitative data)  3. Unstructured interview: suited for exploratory

(Qualitative data)

Types of Interview 2/3  In some research the priority is to have an in depth

interview with a small number of participants, face to face.

 In other cases, a large number of participants are required. In such cases, telephone & internet interviews are carried out.

 The phone interview is very efficient in reaching large numbers of participants with very low costs in time & money for the researcher. The limitations are that the limited contact between the researcher and the participant may cause limited effort and reliability from the participant.

(Saunders et al, 2012, p.375)

Types of Interview 3/3 Qualitative Interview

Quantitative Interview

Electronic interviews  Electronic interviews have similar advantages to

phone interviews. They may be synchronous or asynchronous. The information is usually typed by the participant and this avoids the need to transcribe.

Tools for Electronic Interviews  Microsoft Teams  Zoom  Whatsapp  Skype  Facebook messanger  FaceTime  Blackboard Collaborate  WeChat  Or, others you are familiar with

1. Qualitative Interview: In-depth/Semi-Structured Interview

 Characterised by: Length – 30 mins to several hours

Depth – more in-depth than a typical questionnaire-based interview

Structure – fluid, informal structure

1. Qualitative Interview: In-depth/Semi-Structured Interview

 Used when: Number of subjects/interviewees

relatively small Information is expected to vary

considerably, and in complex ways from subject to subject

Or, a topic is to be explored as a preliminary stage in planning a larger, possibly quantitative study.

Recording in-depth interviews  Tape-recording or mobile phone voice

recording preferable.  Notes (taken during or immediately after

interview) also used.  Transcribing tape-recorded interview, word-

for-word, produces a verbatim transcript.  Manual transcribing can be a time-consuming

process. Microsoft ‘Speech to Text’ service can save time by converting spoken audio to text.

 Analysis of notes and transcripts – see topic ‘Analysing qualitative data’.

1. Qualitative Interview: In-depth/Semi-Structured Interview

Face to face Interviews: Advantages & Disadvantages (adapted from Finn et al, 2001:75)

Type of interview

Advantages Disadvantages a. Structured

(Quantitative)

1. Answers to same questions increase comparability

2. Data easily analysed

1. Little flexibility.

2. Pre-determined questions might not be relevant.

3. Standardised wording might inhibit

b. Semi- structured

(Qualitative)

1. Combines flexibility with comparability

1. Bias may increase as interviewer selects questions to probe & might inhibit comparability

c. Unstructured

(Qualitative)

1. Interviewer can adapt, interviewee is allowed to express in own words.

2. Interviewer’s role minimal

1. Comparability reduced, data analysis more difficult.

2. Data quality depends on listening & communicating skills of interviewer

 Similar to in-depth interviews but conducted with a group (typically 8 – 12 members).

 ‘Facilitator’ (rather than interviewer) guides discussion.

 Interaction between subjects takes place as well as between interviewer/facilitator and subject.

 Joint construction of meaning  Emphasis on questioning on a

particular, fairly tightly defined topic

2. One to many Interview: Focus group/Group Interview

 Used when:  .. a group is small in number so would not

be adequately represented in a general community survey – eg. some minority ethnic groups or people with disabilities

 … the interaction/discussion process itself is of interest – eg. testing reactions to a proposed new product

 … it may not be practical to arrange for individual in-depth interviews but people are willing to be interviewed as a group.

2. One to many Interview: Focus group/Group Interview

Advantages:  So that people known to have had a certain

experience can be interviewed about it in a relatively unstructured way

 Allows the researcher to develop an understanding about why people feel the way they do

 So that participants are able to bring issues to the fore in relation to a topic that they deem to be important and significant

 To offer the researcher the opportunity to study how individuals collectively make sense of a phenomenon and construct meanings around it

2. One to many Interview: Focus group/Group Interview

Disadvantages: The researcher probably has less

control over proceedings than with the individual interview

The data may be more difficult to organize and analyse

Recordings may be more time- consuming to transcribe than recordings of individual interviews

2. One to many Interview: Focus group/Group Interview

3. What is an Observation ?  An observation describes facts, qualities, &

quantities about an object, phenomena, or living things.

 Observations are made using the 5 senses or using a tool.

 Systematic description of:  Events  Behaviours  Objects

 in the social setting chosen for the study. 26

3. Qualitative & Quantitative Observation ?

Observations can be: qualitative or quantitative

A qualitative observation describes a quality. eg. the pizza has pepperoni.

A quantitative observation involves a measurement or a quantity. eg. the pizza has 7 pepperoni slices.

27

3. Types of Observation  1) Non-participant Observation Observing behaviours in their natural

setting, without awareness or any manipulation or intervention.

 2) Participant Observation Observing behaviours in a natural setting,

through active participation in the situation and/or manipulation of the environment.

28

3. Observation

An observation is a fact. You can prove it using your 5 senses.

29

3. Observation – Example (Hamburger)

30

It has a bun.

There are 3 tomato slices.

The bun has seeds.

There is 1 hamburger patty.

These are all things I could prove. Therefore, they are all observations.

Observation – Other Examples (5 Senses)

The heart makes a “thump” noise.  hearing The money is green.  seeing The latte feels hot.  smelling, tasting, touching The star shines brightly.  seeing

31

Qualitative Observation Research Topic: Catering Services at McDonald

Restaurants, Cardiff 1. Use the 5 observations in below as evidence, 2. Analyse the observation data & present the result about the

Quality of Catering Services at McDonald Restaurants, Cardiff eg. Product choices & quality, Environment, Price, Location, Customer Service, etc

 1) Seeing: Not many choices for vegetarian, vegan on the menu

 2) Hearing: Prices are rising  3) Smelling: The coffee smell is good  4) Tasting: Food is freshly cooked  5) Touching: Tables & chairs are not clean

32

3. Advantages of Observation Access to “backstage” culture. Rich detailed descriptions. Ability to witness or participate in

unplanned events. Improves data collection. Facilitates the development of new

research.

33

3. Disadvantages of Observation Observation is made only at the time

of occurrence of the appropriate events.

Researchers may be biased depending on how they present the events they observe.

Observers are not full participants and may affect actions of those being observed.

34

Considerations for Successful Research

35

Quantitative Research Qualitative Research

Validity Does an instrument measure what it is supposed to measure?

Has the researcher gained full access to the knowledge and meanings of informants?

Reliability Will the measure yield the same results on different occasions (assuming no real change in what is to be measured)?

Will similar observations be made by different researchers on different occasions?

Generalisability What is the probability that patterns observed in a sample will also be present in the wider population from which the sample is drawn?

How likely is it that ideas and theories generated in one setting will also apply in other settings?

Conclusions  Qualitative research allows the researcher to get

closer to data  Range of methods associated with qualitative

research  Understanding the broader social constructions

and meanings  Complex  Difficult to quantify (unlike quantitative research)  Rich data

information/New folder/Bb Topic 9 Analysing Qualitative Data.pdf

WELCOME TO THE BUSINESS RESEARCH

PROJECT (BS3S86)

Topic 9: Analysing Qualitative Data Module Leader: Dr. Louise Hung

© University of South Wales

Objectives

By the end of the session students should be able to:

Consider different approaches and methods to analysing qualitative data

 Deductive vs. Inductive  Thematic Analysis  Coding

2

Reading

Bryman & Bell, Business Research Methods, 2nd edition, Chapter 22

Collis & Hussey, Business Research, 3rd edition, Chapter 9

Saunders et al., Research Methods for Business Students, 7th edition, Chapter 12

3

Introduction

Qualitative data analysis

‘Finding a path through the thicket of prose that makes up your data is not an easy matter and is baffling to many researchers confronting such data for the first time’

(Bryman and Bell, 2007)

4

5

What are the examples of qualitative data?

 Interview transcripts Notes from observations (field

notes/diaries/memo) Published texts (policy documents,

material posted on the web, company reports, advertising brochures /leaflet /poster, social media [eg. Facebook, Twitter, Instagram, Just Eat], etc.)

 Images/sounds/expressions Open ended survey responses.

6

Examples of Images and Sounds: Burberry Advertisement in China to celebrate Chinese New Year

7

Example of Images and Sounds: Burberry Advertisement in China to celebrate Chinese New Year

8

Comment on Social Media: Burberry Advertisement in China to celebrate Chinese New Year

9

Comment on Social Media:

Burberry Advertisement in

China to celebrate

Chinese New Year: -

‘Addams Family’

10

Preparing data for qualitative analysis

Organisation of data is essential

Try to get all the material into a similar format eg. MS Word file

Collate the data in a way which enables your notes or comments to be added e.g. leaving a wide margin, MS Word ‘Review’

Give each piece of ‘raw data’ a unique code or number. eg. for each participant

Approaches to qualitative data analysis

Deductive approach – “where you seek to use existing theory to shape the approach that you adopt.”

Inductive approach – “where you seek to build up a theory that is adequately grounded in a number of relevant cases.”

(Saunders et al., 2016, p.625)

11

Implications of approaches to qualitative data analysis (1/2)

Deductive approach: (from theme to data) - Can commence your data collection with a well

defined research question based on theory you have used

- The use of theory and literature will shape the data collection questions and sample choice

- This approach will provide you with a set of codes and categories to guide your analysis

- (Saunders et al., 2016, p.626) 12

Implications of approaches to qualitative data analysis (2/2)

Inductive approach: (from data to theme) - Generating a large number of code labels from

small units of data (e.g. highlighter pens) - Exploratory – recognising significant themes and

explanations in actual data you have collected - Being rigourous in use of procedures in order to be

able to produce a research report (and explain your analysis techniques)

- (Saunders et al., 2016, p.626) 13

Tools for Qualitative Data Analysis: Highlighter Pens

14

Thematic Analysis

“Thematic analysis….is a method for identifying, analysing and reporting patterns of meaning”

(Braun & Clarke (2006) “Using thematic analysis in psychology” Qualitative Research in Psychology, 3, 77-101)

Not just a question of how many times a theme is identified but how relevant the theme is to the research question.

15

Process of Coding (Saldana, 2009) Saldana (2009) describes the overall process of coding as follows:

 “A code in qualitative inquiry is most often a word or short phrase that symbolically assigns a summative, salient, essence-capturing and/or evocative attribute for a portion of language-based or visual data”

(Saldana, p.3)

 “To codify is to arrange things in a systematic order, to make something part of a system or classification, to categorise” (Saldana, p.8)

 “Coding is thus a method that enables you to organise and group similarly coded data into categories and families, because they share characteristics” (Saldana, p.8)

(Saldana, J., 2009, The Coding Manual for Qualitative Research) 16

Thematic Analysis:

Concept Card: Example of analyzing one main theme

17

Impacts of computerization in a hospital

Levels of Coding 1. Basic coding:

• simple verbal statements

2. More awareness of the content of what is said: • the language the interviewee uses • the kinds of issues with which the interviewee

is concerned

3. Moving away from a close association with what the respondent says:  concerned with broad analytic themes

18

Steps and Considerations in Coding 1. Code as soon as possible 2. Read through your initial set of transcripts,

field notes, documents, etc. 3. Do it again 4. Review your codes 5. Consider more general theoretical ideas in

relation to codes and data 6. Any one item or slice of data can and often

should be coded in more than one way 7. Do not worry about generating what seem to be

too many codes 8. Keep coding in perspective

19

Problems with Coding Losing the context of what is said Fragmentation of data Some forms of data may be unsuitable for

the coding method

But remember: Your work can acquire significance only

when you theorize in relation to it

20

21

Methods of Qualitative Data Analysis (Robson,1995: 401)

 Counting - categorising data and measuring frequency  Patterning - noting recurring patterns or themes  Clustering - groupings of objects, persons, activities,

settings etc. with similar characteristics  Factoring - grouping of variables into a small number of

hypothetical factors  Relating variables - explaining the type of relationship

between two variables (if any)  Building causal networks - chains or webs of linkages

between variables  Relating findings to general theoretical frameworks -

find general propositions that account for the particular findings in the study.

You can also have a combination of different methods in above.

22

The use of software in qualitative data analysis

 NVIVO - Non-numerical Unstructured Data Indexing, Searching and Theory-building.

 (Note: more appropriate for analysing a large number of qualitative data eg. qualitative interview)

- Software assisting in Data Management -DOES NOT replace the researcher or do the analysis for you!! (NVivo You Tube Tutorial: https://www.youtube.com/watch?v=eXCsA175Ga0&list=PLNjHMR gHS4Fcx3NfpKsaqXuGdcxI9y-Qa&index=1)

Free software is available from the IT Helpdesk located at the library in Treforest Campus, or downloading from their webpage. eg. NVIVO, SPSS, MS Office 365 .... etc.

Example: Using NVivo for Qualitative Data Analysis

23

24

Presenting your findings: ask yourselves  Is what I claim as the participants

understood it? (Would they agree with my interpretations?)

Have I been objective in the collection? (Did I justify the sample used and use a theoretical sampling framework?)

Have the categories real validity? - Am I reporting findings objectively or only picking out positive cases?

Conclusions “A qualitative approach involves commencing your research from a deductive or inductive perspective”

(Saunders et al., 2016, page 618)

1. There is a general under-estimation of the complex skills that high quality, qualitative research involves

2. There is a need to combat the assumption that it is an easy alternative for those who ‘can’t do statistics’

3. Formulate a strategy to improve areas where you need development concentrating on training/reading/ or opportunities for experience

25

information/New folder/CONSENT FORM(2)(1).docx

CONSENT FORM

University of South Wales

CONSENT FORM

Title of research project:

_____________________________________________________________________________

Name and position of the researcher:

_____________________________________________________________________________

Please initial box

1. I confirm that I have read and understood the information sheet

for the above study and have had the opportunity to ask questions.

2. I understand that my participation is voluntary and that I am free

to withdraw at any time without giving a reason.

3. I agree to take part in the study.

Please tick box

Yes No

4. I agree to the interview being audio recorded.

5. I agree to the use of anonymised quotes in publications

Name of participant: _________________ Date: ___/___/____ Signature: __________________

Name of project researcher: ________________ Date: ___/____/___ Signature: ______________

information/New folder/CONSENT FORM(2).docx

CONSENT FORM

University of South Wales

CONSENT FORM

Title of research project:

_____________________________________________________________________________

Name and position of the researcher:

_____________________________________________________________________________

Please initial box

1. I confirm that I have read and understood the information sheet

for the above study and have had the opportunity to ask questions.

2. I understand that my participation is voluntary and that I am free

to withdraw at any time without giving a reason.

3. I agree to take part in the study.

Please tick box

Yes No

4. I agree to the interview being audio recorded.

5. I agree to the use of anonymised quotes in publications

Name of participant: _________________ Date: ___/___/____ Signature: __________________

Name of project researcher: ________________ Date: ___/____/___ Signature: ______________

information/New folder/topic7.pdf

1

General Ethical Guidelines for Research and

Consultancy

1

Introduction

2 General Ethical Responsibilities

3 What You Should Do Next

This version of this handbook may be subject to amendment as ethical

review systems develop.

January 2015

2

1. Introduction

1.1 Scope of these guidelines

These guidelines identify the general ethical issues which should be

considered by all researchers and consultants within the University - whether

they are members of staff, post-graduate or undergraduate students. They

should also be considered by those engaged in teaching and learning activities

which involve research on human or animal subjects. There is a companion

document Ethical Issues in Teaching and Learning, available on the

Research Office’s web pages..

Definition of research

'Research for the purpose of the RAE is to be understood as original

investigation undertaken in order to gain knowledge and understanding. It

includes work of direct relevance to the needs of commerce and industry, and

to the public and voluntary sectors; scholarship*; the invention and

generation of ideas, images, performances, artefacts including design,

where these lead to new or substantially improved insights; and the use of

existing knowledge in experimental development to produce new or

substantially improved materials, devices, products and processes, including

design and construction.

* scholarship for the RAE is defined as the creation and development and

maintenance of the intellectual infrastructure of subjects and discipline s in

forms such as dictionaries, scholarly editions, catalogues and contributions to

major research databases

In these guidelines “research” includes:

- market and corporate research

- undergraduate and postgraduate dissertations - Masters by Research, MPhil/Ph.D and Professional Doctorates

and postdoctoral projects

- staff research projects

Research and consultancy in some areas may also be subject to the ethical

guidelines of specialist and professional bodies, such as the British

Psychological Society, the British Computing Society and the Royal

Institution of Chartered Surveyors. These University guidelines are not

intended to take precedence over such specialist guidelines.

Whatever your area of work, you should first ascertain whether any specialist

codes are relevant to it. You should also ascertain whether you need to seek

approval for your work from a specialist body as well as from your Faculty

Research Programme Committee (FRPC) or your Faculty Research &

Scholarship Committee..

3

1.2 Responsibility for complying with relevant ethical and legal guidelines

Ethical responsibilities

Members of staff with responsibility for undergraduate, postgraduate or post-

doctoral research projects, as well as for their own research and consultancy,

are responsible for ensuring that everyone involved in their projects is aware

of and agrees to abide by, the relevant guidelines.

Since these guidelines are expressed as general ethical concerns, individuals

must judge how best to apply them to their own situations. To help them the

University has appointed Faculty Ethics Champions (FECs) in each Faculty

who can discuss how the guidelines may relate to particular circumstances.

Ethics Champions are not, however, responsible for giving ethical approval to

proposals – that is the responsibility of Faculty Research Programmes

Committees (FRPCs) or Faculty Research & Scholarship Committees

(R&SC).

Staff engaged in research are required to have read the appropriate guidelines

and to undertake necessary action. For information on how to do this see

section 3: “What you should do next”. Section 3 also explains what to do to

secure approval for consultancies.

Once a proposal for research or consultancy has been approved, someone -

consultant, research supervisor, research leader or individual researcher,

depending on who is in the best position to monitor procedures – should take

responsibility for identifying and addressing ethical issues in the continuing

project. They should contact their FEC, FRPC or R&SC if they need advice,

but FECs are not in a position to monitor projects.

Legal responsibilities

These guidelines should not be seen as a guide to legality.

Although you are generally likely to be acting legally if you give due regard to

the ethical concerns outlined here, this cannot be assumed. For example,

although you may take into account ethical points about confidentiality and

the use of data, any research which involves the processing of personal data

will also have to comply with the Data Protection Act, in which ‘processing’

includes obtaining, recording and holding information and data, carrying out

operations on them, and using, disseminating and destroying them. When

dealing with data on human subjects you should consult the University’s Data

Protection Policy, or contact the University’s Data Protection Officer to

ensure compliance with the Data Protection Act. You should also take account

of the following documents, some of which set out the University’s policies

for compliance with legal requirements:

 Research Good Practice Policy

 RAE Code of Practice

4

 Research Misconduct Policy

 Equality and Diversity Policy

 Race Equality Policy

 Staff Complaints and Public Interest Disclosure Procedures

 Academic Policy and Regulations

 Environmental Policy Statement

 Equal Opportunities

 Equal Opportunities Statement

 Health and Safety Statement

The University is in the course of producing further legal guidelines for

researchers and consultants, especially for those who may become aware of

illegal activities during the course of their work. Until these legal guidelines

are available, if you think your research or consultancy may raise legal issues

you should refer to the University Secretary.

2. General Ethical Concerns

Ethics is a complex subject, but in professional contexts its four

central concerns are:

 to treat people fairly

 to respect the autonomy of individuals

 to act with integrity

 to seek the best results - by avoiding or minimising harm and by using resources as beneficially as possible

Mnemonic: f a i r

Sometimes more than one of these ethical concerns may be relevant to

a situation. Dilemmas occur when they conflict and when this

happens their different demands have to be weighed against each

other. Only then can we decide whether to aim for a compromise

between them or to give priority to one over the others. In some

situations, for instance, it may be impossible to achieve beneficial

outcomes without causing some harm.

For example, research into pain management may not be able

to achieve its objectives without first causing pain which can

then be controlled by experimental means. Causing such harm

may be ethically justified, but only if certain conditions are

met, such as individuals volunteering to undergo the pain and

making an informed choice not only to enter the project but

also to continue with it. Moreover, the beneficial outcomes of

the research must be expected to be considerable.

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There are, then, situations in which we may be justified in not

acceding totally to the demands of all the ethical concerns, or in not

regarding the demand of any one of them as absolute. But we can only

decide to which concern to give priority, or how to balance the

demands of the concerns, after considering what they each require in

particular circumstances. In such situations there may be no

objectively ‘correct’ decision, only the one we decide is ethically

appropriate and defensible. In this way staff and students are asked to

exercise their discretion in the spirit of these guidelines and to be

accountable for the way they exercise that discretion.

While all research and consultancy must be considered in relation to

the four concerns, especial care must be given when research and

consultancy may involve:

- deception - intrusive interventions - working with vulnerable groups - sensitive topics - groups whose members can only be accessed through a gatekeeper - access to records of personal or confidential information

The following paragraphs indicate how the four concerns relate to research

and consultancy.

2.1 Treat everyone fairly

The basic principle of fairness can be summed up as:

- treat alike people who are alike in relevant respects - treat differently people who are different in relevant respects.

We treat people fairly by treating them alike unless there is a sound

reason for treating them differently. There is a sound reason for

treating people differently only when there is a difference between

them or their situations which is relevant to the way we might treat

them. Differences which are irrelevant to the way they might be

treated do not justify treating them differently.

For example, if a research project affects people of different

cultural traditions their various sensitivities should be given

equal consideration by the researchers. Greater sensitivity

should not be shown to those whose cultural background

happens to be the same as that of the researchers, since the

fact that some participants share their background is

irrelevant to the appropriate treatment of participants by

researchers.

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Generally speaking, we treat people fairly if we:

 provide everyone with the same consideration and respect

 do not allow any personal views or sympathies we may have to affect the quality of our treatment of each individual

 treat individuals differently from each other only when there are differences between them which are relevant to our

treatment of them

 when there are relevant differences between individuals, treat

them in ways which are appropriate to those differences

2.1.1 To be fair we should meet the needs of everyone involved in or affected by a project

Researchers and consultants should ensure that the needs of everyone

who is involved in, or may be affected by, their work are met as far as

possible.

“Needs” include sufficient information, guidance, equipment, support

and other resources to:

 participate fully in the project

 deal with the effects of the project. These effects may occur while the project is in operation, after it has been completed,

and after the dissemination of its findings.

Communities as well as individuals may be affected by projects and so

have needs arising from their execution and consequences.

2.1.2 To be fair we should protect the interests of everyone affected

Researchers and consultants should protect the interests of everyone

affected by their work. It is easy to regard the interests of people

peripheral to a project – eg the relatives and friends of participants - as

of little concern. If people could be affected - however minimally – by

your work you should take steps to protect their interests.

Some questions to consider:

Do all researchers have equal access to resources necessary to carry out the

research?

Do research subjects and people affected by the research have equal access

to whatever support is provided to help them deal with its effects?

Do arrangements ensure that students have equal access to research

supervisors with appropriate specialisms?

Do arrangements ensure research supervisors are available for at least an

agreed minimum for all students?

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Do supervisors take care not to incorrectly pass on legal/ethical

responsibilities to their research students?

2.2 Respect the autonomy of all individuals

We respect autonomy when we:

 equip individuals – participants, subjects, researchers and clients - to make informed decisions about what they do and how they wish

to be treated

 provide individuals with opportunities for making informed decisions

 do not prevent individuals from acting in accord with their informed decisions.

Respecting autonomy does not mean, however, allowing everyone to

do whatever they wish, for two main reasons:

 sometimes individuals do not have sufficient understanding to make informed choices

 sometimes if an individual were to carry out his/her wishes it would infringe the autonomy of others. It might also raise other

ethical issues.

It is the responsibility of researchers and consultants to respect the autonomy

of everyone involved in a project, including clients, researchers, subjects and

those who may not be actively involved in the project but about whom data is

used.

Respecting autonomy normally requires:

obtaining informed consent

avoiding practices and methodologies which involve:

- deceit - dishonesty - invasion of privacy - breaking confidentiality - using data for purposes not clearly explained to participants.

If researchers or consultants wish to deviate from these norms, the onus is on

them to justify doing so and to specify what safeguards they will put in place

to prevent harm to people’s interests..

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2.2.1 Informed consent

The Data Protection Act is based on the idea that “informed consent” is

“Any freely given, specific and informed indication of wishes by

which the data subject signifies his/her agreement to personal data

relating to him/her being processed.” This general definition is

appropriate when taking account of the following ethical points:

a) Research should be based on the freely given informed consent

of those under study.

b) It is the responsibility of researchers and consultants to explain as fully

as possible, and in terms meaningful to those being asked to be

participants:

i. the aims and the nature of the project ii. who is undertaking it

iii. who is funding it iv. its likely duration v. the possible consequences of it

vi. all likely disclosures of personal data vii. how the results are to be disseminated.

viii. If participants are unlikely to receive any benefits as a result of the project this should be made clear to them

ix. Procedures by which participants may make complaints about the conduct and nature of the work should also be made clear

x. It should be made clear how far participants will be afforded anonymity and confidentiality.

c) If there is a likelihood of data being shared with or divulged to

researchers or other people involved in the project, this must be

explained and the reasons for it given. The potential uses of the data

should also be discussed with the participants and their agreement to

such uses obtained.

d) While a researcher or consultant should take every practicable measure

to ensure the confidentiality and anonymity of participants, s/he should

also take care not to give unrealistic assurances or guarantees of

confidentiality. Participants with easily identifiable characteristics or

positions within an organisation should be reminded that it may be

difficult to disguise their identity without distorting the data.

e) Participants should be given the option of rejecting the use of data-

gathering devices which make sound and vision recordings.

f) Where participants are young children or other vulnerable groups such

as older, disabled or sick people or people with learning difficulties,

whose understanding is impaired in some way so that they are unable

to give full informed consent, it may be necessary to use a proxy in

order to gather data. In this case great care must be taken not to intrude

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upon the privacy of the vulnerable participants. Researchers and

consultants should discuss the issue with relevant professionals,

parents/guardians, relatives, partners or significant others as

appropriate. They should attempt to obtain the informed consent of

children and their parents and, in relation to school children, of those in

loco parentis.

g) The power imbalance between researcher and researched, consultant

and others, should be addressed.

i. Care should be taken to ensure that the latter are not pressured or coerced into participation

ii. Participants should be made aware that they have a right to refuse participation whenever and for whatever

reason and should not be given the impression that they

are required to participate.

iii. It should be recognised that a project may involve a lengthy data-gathering period and that it may be

necessary to regard consent not as obtained once and for

all, but subject to renegotiations over time

2.2.2 Confidentiality and Anonymity

a) The anonymity and privacy of research participants should be respected and personal information relating to participants should be

kept confidential and secure. Researchers and consultants must

comply with the provision of the Data Protection Act and should

consider whether it is proper or appropriate even to record certain

kinds of sensitive information.

b) Please note that in certain circumstances researchers may have a legal obligation to break confidentiality.

If there is a possibility that a proposed project may reveal knowledge

of illegalities you should consult the University’s Data Protection

Officer or the Secretary of the University before submitting the

proposal for ethical approval to your FRPC or R&SC..

c) Researchers and consultants should anticipate any likely threats to the confidentiality and anonymity of data and should normally keep

confidential the identities and research records of participants, whether

or not an explicit pledge of confidentiality has been given.

d) Where possible researchers and consultants should anonymise personal data such that it would not be possible for the University, its staff,

students or researchers, to identify an individual from that data and any

other data held or likely to be obtained.

e) Studies which involve data about non-volunteers based upon observation or records (whether or nor explicitly confidential) must

respect the privacy and well-being of the subjects

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2.2.3 Covert Methods in Research and Consultancy

With the exception of medical research, or other research for which

there is a substantial public interest, it is difficult to see whether any

research or consultancy involving covert methods could be legal under

the Data Protection Act. The Act specifies that for personal data

obtained on the data subject to be fair, it is necessary to take account of

whether any person from whom the data is obtained has been misled or

deceived as to the purpose of the processing.

a) It is recognised that there is a continuum of covert-overt methods and

therefore difficulty in defining a project as entirely covert or overt.

Researchers and consultants should, however, endeavour to avoid the

use of deception since this violates the principle of informed consent

and may invade the privacy of those under study, particularly in non-

public places. If it seems to researchers and consultants that the

employment of covert methods is the only means to obtain data

required, they should consult the University’s Data Protection Officer.

Covert research in non-public places or experimental manipulation of

research participants without their knowledge should be a last resort

when it is impossible to use other methods to obtain the required data.

In such cases it is particularly important to safeguard the anonymity of

participants and to consult the University’s Data Protection Officer.

b) In all cases in which it is considered necessary to use covert methods

researchers and consultants should consider whether the likely benefits

of the project justify the ethical unacceptability of doing so. One

justification might be that the research is in the substantial public

interest.

Some questions to consider:

Do the objectives or methodology of a research project respect the

autonomy of human subjects, researchers and respondents?

Do the objectives or methodology of a research project fail to respect the

autonomy of others because they involve deceit, dishonesty, invasion of

privacy or breaking confidentiality?

Are all likely participants - subjects and researchers - fully informed of the

nature of the research before deciding whether to participate or to allow

information about themselves to be used?

Is the situation in which people are invited to take part in research such that

they will not feel pressured or coerced to do so?

Will the consent of participants be gained before research proceeds?

Is written consent to take part in research ethically appropriate?

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If it is not intended to obtain written consent, are there reasons which

justify not obtaining it?

Are appropriate arrangements made for obtaining consent of vulnerable

adults and children or their representatives when relevant?

You may wish to refer to the guidance for researchers produced by the

National Children’s Bureau which can be found in the “research” section

of the NCB website: www.ncb.org.uk

Can participants withdraw from the project at any time without feeling

they might be penalised?

Are procedures for complaint easily accessible and made clear to

participants?

Are research data to be used in ways not clearly stated to researchers and

subjects? (‘Subjects’ may include people who are not actively involved in

the research but about whom data is used)

Do supervisors enable students to choose their topics for research as far as

possible?

These questions on research are not only concerned with respecting

autonomy but with requirements of the Data Protection Act, which should

be referred to.the appropriate member of staff in LCSS

2.3 Carry out research and consultancy with integrity

We have integrity when our actions are integrated with our stated

values and objectives such that there is no discrepancy between them

– ie when we are honest, and try to do what we say we will do.

Research and consultancies are carried out with integrity when

researchers and consultants genuinely strive to achieve the objectives

of sound research by ensuring valid methodology, availability of all

necessary resources, objective research processes and well-grounded

findings. Research which lacks integrity is ethically unacceptable as it

not only misrepresents what it claims to be but also mis-uses

resources

The objectivity and impartiality of research can be threatened if it is in

any way dependent on a sponsor, institution or participants who have

particular interests or values. Researchers should therefore ensure that

the objectives of all parties are clearly articulated at the outset, that

any potential conflicts of interest are made clear and that the project is

set up in such a way that it is independent of any special interests. It

will then avoid being invalidated by “hidden agendas”. Consultants

should make clear to participants who is paying for the project and the

objectives of all parties involved.

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2.3.1 Conflicts of interest

A conflict of interest is a conflict between the private interests and the official

responsibilities of a person in a position of trust. The initial responsibility for

managing a conflict of interest rests with the researcher who is experiencing

the conflict. It is important that any conflicts of interest, whether potential or

valid, are identified, declared, resolved, and in some cases reported to satisfy

internal and external requirements. These may include legal, financial, moral,

ethical, personal or academic issues and should be disclosed in a timely

manner that does not undermine the time required to consider it appropriately.

The University expects all staff and students engaged in research to

acknowledge and report conflicts of interest as soon as they are suspected or

realised.

Some questions to consider:

Will up-to-date resources be available during the course of this research or

consultancy?

Will the methodology achieve its stated objectives?

Is the impartiality of the project at risk of being compromised by

dependence on a sponsor or an institution with particular interests?

Is it clear that the research is not a “cover” for commercial activity?

Are the contacts gained through the project likely to be used at a later date

for commercial activity?

Do staff, researchers and participants get promised facilities and support to

carry out the project and cope with its impact, not merely during its

execution, but after its completion?

2.4 Seek the best results - (1) minimise harm

Whether students or staff, we are ethically obliged to anticipate as far

as possible any harm which research and consultancy activities could

cause and should then take every reasonable step to ensure they do not

do so. If there are unavoidable risks to participants these should be

clearly stated in advance.

What counts as harm may be a matter of debate, but most frequently it

is seen as whatever damages the interests of individuals – students,

staff, subjects, researchers etc, and the interests of universities,

professions and communities in which projects takes place.

2.4.1 Avoid harm

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a) A primary ethical responsibility of researchers and consultants is to avoid causing harm. This consideration should be an over-riding factor

at all stages in a project, such as the formulation of objectives, design

and development of methodology, conduct of research, and

presentation, dissemination and use of findings.

b) Harmful effects may occur some time after cessation of the project and publication of results. The possible consequences of every stage should

be assessed and every measure taken to ensure safety and prevent

adverse effects on researchers, clients, subjects, individuals about

whom data is used, others in the community in which the work occurs

and those who could be affected by its results.

c) Harm to individuals includes physical harm, psychological harm - such as unreasonable stress - invasion of their privacy, damage to their self-

esteem, damage to the social fabric of their community and

commercial harm of those involved in business or entrepreneurial

activity.

d) Distress can be caused to research subjects when physiological or psychological data is collected about them which could indicate an

aberration from the norm. If this is possible it is ethically important to

make individuals aware of this and give them an opportunity to

withdraw from the activity in question.

e) Harm may also include damage to the reputation of the research discipline and University and damage to the interests of future research

and consultancy. Such damage can be caused by a project which is ill-

conceived, carelessly executed or irresponsibly used.

f) If the objectives of a project cannot be achieved without risk of harm researchers and consultants should consider abandoning the project.

They should only apply for approval to continue if they can provide an

overwhelming justification for doing so. Should approval be granted,

they must make clear to all who may be involved in or affected by the

project that the risk exists, and must ensure every effort is made to

reduce it. This may include providing counselling, if subjects may

become distressed by the project, and providing information about

services or help which people affected by the project may seek if they

have unmet needs or expectations.

g) If a project becomes more stressful than anticipated, researchers and consultants should stop the process and consult colleagues.

h) There are helpful suggestions for identifying risk in the Economic and Social Science Research Council’s (ESRC) Research Ethics

Framework, Section 2

i) N.B 1 If you think there is a possibility of harm occurring during the

course of a project you should consult the University’s Data

Protection Officer. If harm occurs the research exemptions

under the Data Protection Act cannot be used.

2 If there is a possibility that a proposed project may reveal

knowledge of illegalities you should consult the University’s

Data Protection Officer or the Secretary of the University

before submitting the proposal for ethical approval to your

FRPC or other appropriate body.

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Some questions you might find useful when considering the

importance of minimising harm

Has sufficient care been given to anticipating any physical or

psychological harm or unreasonable stress which research and consultancy

activities might cause to students, human or animal subjects, staff and

clients?

Have all measures been taken to eliminate possible harm or to reduce it as

far as possible?

Has research methodology been designed to eliminate as far as possible

any adverse effects on subjects, researchers, institutions or communities

from the conduct of research or publication of its findings?

Is research supervision designed to minimise harm to all concerned as

much as possible?

In research will measures be in place to protect the confidentiality of

research participants?

If some adverse effects may be caused by proposed research or

consultancy, are they ethically justified?

Should a research or consultancy project be rejected or discontinued if its

objectives cannot be achieved without the risk of harm? What is the

justification for continuing it?

If risk of harm is foreseeable, is this clearly stated to participants as soon as

possible?

2.4.2 Seeking the best results – (2) use resources as beneficially

as possible

We have an ethical obligation is to use available resources –

including the time, expertise and energy of ourselves and

others, and the facilities, budget and reputation of the

University, to achieve the best possible outcomes.

Researchers and consultants should consider how to produce

the most valuable outcomes they can from the resources at

their disposal.

For example, opportunities for sociological or anthropological

research in a remote community may be strictly limited. For,

once such a community has been the focus of a research

project, it may be changed by contact with people from outside

and so lose some of its value as a resource. Researchers should

therefore consider whether their proposed project is the best

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use of the resources that community affords, as well as taking

into account the possible impact of their research on the

community.

There may be other limits on resources: access to an archive

may be restricted, people involved in research may experience

‘research fatigue’ and there may be few grants for projects in a

particular area. It is therefore important to ask of any research

whether it is focused on the most valuable aspects of the

available material, and whether it is likely to make the best use

of the opportunity for research in that area. It may be that

identifying different objectives or redesigning the project

could produce greater benefits

The best outcomes are those which as far as possible meet the

needs of individuals, the University and society at large. Since

these needs often conflict, decisions have to be taken about

which to prioritise, or about how best to achieve a compromise

between them. The obligation to use resources beneficially

may itself also have to be balanced against the ethical

concerns to avoid harm, respect autonomy, treat people fairly

and act with professional integrity.

2.4.2.1 Use resources as beneficially as possible

(a) Resources include funding, institutional and client facilities, the

input of researchers and subjects and sources of material – such

as archives, experimentation and data about individuals and

communities. Resources also include opportunities for research

and consultancy: funding may be available for only a limited

number of projects in a particular area and there may be a limit

to how many times projects can be carried out in a particular

locus.

(b) It is the responsibility of researchers and consultants to obtain

the greatest benefits they can from the resources they use. In

general terms benefits may be seen as whatever promotes the

welfare of living beings. In practical terms most projects

contribute to this by aiming for more limited objectives.

Projects should be designed to achieve the most beneficial use

of resources. If it becomes clear that a particular project will

not do this consideration should be given to using fewer

resources or putting forward an alternative project.

Some questions to consider

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Is the project the most beneficial use of resources - the potential research

data, budgets, facilities and participant's input and sponsor's resources?

If not, should an alternative project be put forward, or fewer resources

used?

Do research supervision practices make the best use of students’

opportunity for research and the time given to it by staff?

3. What should you do next?

Postgraduate Research level proposals

If you have a proposal for research which involves a postgraduate

research student undertaking the research you are asked to participate

in the following:

Proposals for research must be considered by a Faculty Research Programmes

Committee (FRPC) before the project begins. Evidence that ethical aspects of

the research have been addressed will be required by FRPC for

registration/transfer purposes. As Faculties have different arrangements for

facilitating this, your Faculty Ethics Champion will inform you what these

are. It may be that your research proposals must be first considered by a

Subject/Division, research group or centre, Faculty Ethics Sub Group (or

appropriate Committee) or Faculty Ethics Champion before being sent to

your FRPC.

An FRPC may give staged approval for a research project, or may make

approval conditional upon further approval by outside professional bodies.

Once a research proposal has been approved by FRPC, research supervisors

and their research students are responsible for identifying and addressing

ethical issues in the continuing project and returning to the faculty provision

for advice where required, and approval where also required.

3.1 Research Proposals

If you have a proposal for research (including research being carried out

by undergraduate students) you should consider whether your research

meets the criteria below to be considered as low risk. If your research

proposal is considered low risk, consideration by you and/or your

Faculty Ethics Champion may be sufficient.

Staff research – Faculty Ethics Champions should be approached in the first

instance who will advise on the requirements of your project against faculty

arrangements. In some faculties standard ethics review may involve the

completion of an ethics application form and review at a committee meeting.

3.2 Types of review

It is likely that a Standard Ethics Review of your proposal will be required

and this will apply to most research projects where human subjects are

involved.

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In order for an application to qualify for ‘light touch’ scrutiny, the research

must not fall into any of the following categories (which replicate research

described in the ESRC Research Governance Framework as involving more

than minimal risk):

 Research involving vulnerable groups – for example, children and young people, those with a learning disability or cognitive impairment or

individuals in a dependent or unequal relationship.

 Research involving sensitive topics – for example, participants’ sexual behaviour, their illegal or political behaviour, their experience of

violence, their abuse or exploitation, their mental health or their gender or

ethnic status.

 Research involving groups where permission of a gatekeeper is normally required for initial access to members – for example, ethnic or

cultural groups, native peoples or indigenous communities.

 Research involving deception or which is conducted without participants’ full and informed consent at the time the study is carried out.

 Research involving access to records of personal or confidential information, including genetic or other biological information concerning

identifiable individuals.

 Research which would induce psychological stress, anxiety or humiliation or cause more than minimal pain.

 Research involving intrusive interventions – for example, the administration of drugs or other substances, vigorous physical exercise or

techniques such as hypnotherapy. Participants would not encounter such

interventions, which may cause them to reveal information which causes

concern, in the course of their everyday life.

Low risk research should, therefore, be characterised by the absence of all of

the above components. It should be noted than no category of research (e.g.

undergraduate research dissertations) will always meet the low risk criteria.

N.B. The ESRC guidance adopted above is consistent with other recognised

UK funding bodies/councils or societies. You should, however, check with

your Faculty Ethics Champion or relevant Faculty Committee to ensure that

there are no further subject specific guidance that you should be aware of and

which may affect your research proposal.

3.3 Consultancy

Consultancy contracts will be noted as low risk if they do not fall into any of

the categories listed in section 6.2 above. Faculty representatives will be

made aware of all consultancy projects, whether low risk or not. All contracts

with a value of more than £3,000 will have a full contract review as part of

the contract acceptance procedures, which will check contract terms and

conditions, resourcing, insurance issues, authorization procedures and areas

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of concern/ambiguity. A more detailed risk assessment is carried out for high

value projects.

Projects which are deemed to be higher risk will be escalated to senior

management within both the Faculty and to the Director of Business

Development, and where appropriate to the University insurers. High risk

projects will be regularly monitored at the Innovation and Commercial

Engagement Executive Group and USW Commercial Services Ltd. It is likely

that a Standard Ethics Review of high risk consultancy projects will be

required where human subjects are involved.

Ethical issues relating to the reputation and activities of the funding

organisation (client) also need to be examined. Ethical concerns about clients

and potential clients should be raised at the earliest possible stage in project

development, so that the necessary company or funder checks can be carried

out.

These concerns should be raised with the Research and Business

Development Department.

3.4 Teaching and lecturing

Lecturers are asked to follow the following procedures:

 All teaching proposals – whether for new work or work that is to be revalidated - must be approved by a Faculty Quality Assurance Committee

(FQAC). Subject/Divisions must consider the ethical aspects of proposals

when developing the work and if possible design courses/modules which do

not cause ethical concerns.

 When courses or module descriptors are sent for approval to FQAC, or a validation panel acting on a FQAC’s behalf, they must explicitly state if

the courses/modules have ethical issues and if such issues have been

identified how the team intend to address them. Your Faculty Ethics

Champion can advise you of more detailed procedures.

 Once a teaching proposal has been approved by an FQAC the current module/course leader is responsible for reviewing and monitoring the ethical

aspects of its operation and contacting the Faculty Ethics Champion if there

are concerns.

 If you are involved in learning and teaching procedures which includes research on human or animal subjects, or with supervising or

conducting research projects at undergraduate/ postgraduate or postdoctoral

level, or your own staff research, you should read the USW General

Guidelines for Research and Consultancy and the guidelines of relevant

professional bodies.

Forms and advice are available from your Faculty Ethics Champion and

the Research Office. All ethics related documents published by the

University are also available on the USW research web pages.

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Further reading: If you are interested in considering more fully how these four principles relate to professional

practice, please refer to: Working Ethics – how to be fair in a culturally complex world

by R Rowson, Jessica Kingsley Publishers, London, 2006, copies of which are in University

library.

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Appendix 1

Flowchart outlining ethical approval processes for research