lecture 5 methodologies part 1

7/28/2019 Lecture 5 Methodologies Part 1

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Lecture 5: Methodologies (Part 1)

Professor Mark Palmer

Queens Management School

Queens University Belfast


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Lecture aimto provide students with an outline of the processof data gathering from the preparation andorganization stage to the actual carrying out ofthe research fieldwork.


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Lecture Outcomes

To outline the importance of the methodological

choice for the research topic To identify and explain the various suitable for

research topics

To outline the merits and demerits of various

methodologies

To gain an appreciate of how to execute various

research methods


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Learning outcomes (Continued)

To facilitate understanding in the different aspects and stages in the

process of data collection.

Preparing for the physical and mental tasks involved in preparing for

and actually gathering the data

To provide an opportunity for consideration of these issues in the

context of chosen research requirements


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Priming Exercise

Jot down how you might research your

objectives.

Do they involve primary data collection?

How might you research the objectives?


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Research Design

Why this research design?

E.g. cohorts is a small numbers phenomenon Respondents (in)appropriate?

Units of analysis?

Operational measurement (confounding?)

Sparse reporting, scale validity

Include design controls (e.g. firm size)


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Recall Lordes (1984) famous line:

The masters tools can never dismantle the

masters house.

What does this mean (and for the selection of a

methodology-in-practice?)

Research design must address the research

problem


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Method is dependent on The Nature ofthe Problem: E.g. Investigating culture

Cultural pluralism

Cultural dominance

Cultural entrenchment


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Nature of the problem: Investigating

marketing impact on financial markets

Share Price

Analyst Notes

(Buy/Sell)Investor Relations

InvestorConferences

Institutionalrelations

Other venture

capitalists


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What is a research design?


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Research Design Strategies


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Access!


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Context and situational versus cross-

sectional


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Adopted from Tashakkori and Teddlie

(1998), Greene et al. (1989), and Howe

and Eisenhart (1990)

Example of a Research Design


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Example of a Research Design

Two Phases (i) Network analysis (i.e. issue crawler) (ii) Rhetorical strategies(IT artefacts and 28 indepth interviews).

In stage one we employed a network sampling method to locate and map

authoritative sites on the World Wide Web, which are involved issue

debates concerning the case company under investigation Tesco.

To do this, we used a software tool called IssueCrawler(http://issuecrawler.net) to identify the authoritative actor network websites

associated with the firms activism on the Web (this methodology has been

used in political science projects, see for example http://www.govcom.org).

Significantly, not only does it seek relevanceas defined by the issue but it also made on the basis of network representation (Rogers, 2002;

Rogers and Marres, 2002; Rogers and Ben-David, 2008).

This sweep resulted in IssueCrawler yielding fifty one websites, using the

prescribed URL. This allowed the researcher to produce an issue network of

sufficient scope and transdiscursivity (Rogers and Marres, 2002).


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Phase 1: Identifying Extra-institutional entrepreneurs


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Phase 1: Extra-institutional entrepreneurs (cont.)


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Phase II findings: Rhetorical Strategies Deployed


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So how does that relate to methodologies?


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Research Designs


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Quantitative Methods


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Quantitative Methods

A precise level of measurement

The greater the range of analytical techniques

Impact of data coding on subsequent analyses

Existing measurement scales pretested items

in for example the Handbook of MarketingScales.

Testing of hypotheses or predictions

Relationships between variables Exogenous dynamics

Endogenous dynamics

Easy with analysis software to generate

statistics from your data


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Typical Quantitative Research


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Quantitative Analysis Data Analysis andInterpretation Module (Dr Puthusserry)


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Software tools to assist

SPSS

Stata

R

Listeral


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1) Experiments


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Experimental


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Limitations


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2) Survey


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Planning a survey (Gill and Johnson)

Planning a Survey (Gill and Johnson)

Conceptualise and Structure the Research Problem

a) consider the aims of researchb) review the current literaturec) assess the various resources known

Analytic Survey? Descriptive Survey?

Identify the independent, dependent and other Identify the phenomena that you wishvariables to describeEg relationship between accounting controls and eg what motivates employees in a

business strategy particular context?

Determine the sampling strategy by defining the research problemAnd designing a means of accessing a (representative) sample.

Is the data to be collected through one approach to respondents?

Interviewer administered Respondent completed/Questionnaire/ Schedule e-mail/postal questionnaire


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..continued:

Alternatively the use of surveys to explore asubstantive area, or

Descriptive surveys

Inductive approach

Use of open-ended questions Merges the survey approach with styles ofresearch which are more ethnographic

Much survey design may begin with an unstructuredinvestigation using overtly ethnographic methods

Theory developed inductively to be tested laterusing a more structured questionnaire as a part ofthe main study


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Consideration must be given to examiningrelationships between and among data: Types of variable :

nominal or categorical,

ordinal interval/ratio

dichotomous

Independent (X) and dependent (Y) variables

Causality

Mediation Moderation

Univariate, bivariate or multi-variate analysis

Trends

correlation


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Selecting the most appropriatesampling technique

If the population is small, there is norequirement to sample

Probability or representative sampling: mostlyused in survey based strategies when trying toestimate the characteristics of the population

Non-probability or judgemental sampling:impossible to make statistical inferences about thepopulation, but can often generalise. Mostly usedwhen adopting a case study strategy eg


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Approach to sampling

For a positivistic study, sampling is afundamental element

For a social contructionist study, sampling is

less important. You may well only gather datafrom one person, such as the chairman of the

company


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Overview of sampling techniques

sampling

probability non-probability

Simple random

systematic

Stratified random

cluster

Multi-

stage

quota snowball Conven-ience

purposiveSelf-

selection

Extreme to typical case


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Probability sampling

Seeking a REPRESENTATIVE sample

Select the sampling frame

Decide on a suitable sample size Statistical inference and margin of error Main techniques:

Simple random

Systematic

Stratified random

Cluster

Multi-stage


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Non-probability sampling (or non-randomsampling)

Quota sampling- seeks to represent the population as awhole and sample size reflects probability sampling.

Purposive sampling -where you use your judgement

Snowball sampling-technique used when it is difficult to gainaccess to individuals

Convenience and Self- selection samplingtechniques- where sample size is ambiguous as there are no rules


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Main decisions when using questionnaires

Sample size

Type of quest ions Wording o f intel l ig ib le and unamb iguous

quest ions

Impo rtance of pi lot test ing

Instru ct ions and design o f quest ionnaire

Any accom panying letter

Method of distr ibut ion and return

Tests fo r rel iabi l i ty and val idi ty

Collat ion and analysis o f data

Any act ion for non-response


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Importance of pilot testing

To avert problems in respondents answering thequestions and to ensure there will be no problems inrecording the data.

To assess the validity of the questions asked

And the likely reliability of the data

To check that the coding system works

Reassurance on the content validity. Ie the data answers

the research questions/objective The pilot should involve a subset of the sample to be

included. Minimum number 10 respondents


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Methods of Distribution Self-administered

Internet-mediated (Surveymonkey) etc

Postal Delivery and collection

Interviewer-administered Telephone

Structured interview


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Advantages DisadvantagesOn-line questionnaire Large geog area

Easy to administer

Can use internet tools

Only include IT literate

respondentsAvoid complex

questions

Low/moderate

response rate

Delivery and collection Similar advantages topostal

Collection increases

response rate

Time consumingExpensive

Postal Wide geog area

Sample selection easyRespondents have own

time

Anonymity preserved

Token incentives

increase responses

Low response rates

Self selection can leadto bias

Clarification of

questions not provided

Non-respondents need

chasing

Expensive


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Deciding what data needs to be collected

Questionnaire demands a precise request for data, and only one

chance to receive the correct information For descriptive research, essential to understand theorganisations, countries and cultures in which the research isbeing undertaken

For explanatory research to test a theory or theories, must beclear about the relationships

Variable can be dependent

or independent

Or extraneous- ie it might also cause changes in dependentvariables


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Eg Research question= To establish existing employees

attitudes towards the introduction of a no-smoking

policy in the workplace.

Investigative questions Variables required Detail in which data

measured

How do employees feel about

the introduction. (attitude)

Attitude of employee as to their

rights

Feel.. No strong views to very

strong views against

Do employees wish to see a

smoking room set aside for

smokers?

Attitude of employee to such a

provision

Feel.. From to very strongly

that it should be provided to

very strongly that it should not

Do employeesviews differaccording to Age?

Whether a smoker?

Age of employee

Smoker

To nearest 5years 18-70

Non-Smoker, smokes little,

smokes lot>20 perday

How representative are the

responses?

Age of employee

Gender

Job/Role

(included above)

Male/ Female

Senior

management,supervisory,other

E l f di S d t l (2009) A t t


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Example of coding: Saunders et al (2009) Accountants

as sources of business advice for small firms:

questionnaire administered by telephone from research byGooderham in Norway

Variable Codes

Degree to which a small firm uses its

authorised accountant as business advisor

Scale from 1 to 6

1=not at all, 6=to a very large degree

Long-term relationship with accountant 1=changed accountant within last 5 years

2=have not changed accountant within last 5 years

Perceived competence of accountant in

statutory accounting services

Scale from 1 to 6

1=very limited competence 6=very high

competence

Firm size (No. of employees) 1=1employee,3=2-4 employees, 7=5-9

employees, 15=10-20 employees

Degree of interest in authorised accountants

attempts to sell them advisory services

Scale from 1 to 6

1=very little interest 6=very large interest

Upper hourly billing rate the firm is willing to

pay for business advisory services

1=do not know or under NKr 300,

2= NKr300-450,3=NKr451-650,4=NKr651ormore

Degree of competition Scale from 1 to 6

1=negligible,6=very tough


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Steps in the logic of the deductive method

1/ Deducing a hypothesis ( a testable proposition

between two or more events or concepts) from the

theory. (H1,..H2)

2/ Expressing the hypothesis in operational terms

(indicate exactly how the variables are to be measured)

Show how the variables relate.

3/ Test the operational hypothesis (e.g. experiment)


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4/ Examine the specific outcome of the inquiry.

a / Predicted outcome (from hypothesis)

supports the theory

b / Contrary outcome (to hypothesis)

contradicts the theory,

or fails to support the theory,

or

may be explained by poor research design.


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5/ If necessary, modifying the theory

in the light of its findings.Verify the revised theory by going

back to stage 1/ and repeat the cycle.



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Deduction: testing theory

If theory is true X will occur

X does occur -

theory supported

X does not occur -theory challenged

Test X


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A hypo thesis s tates that there is a relat ionsh ip

between two concepts and speci f ies the

direct ion o f that relat ionsh ip.

Age Gross annual

income


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Key terms explained

The elements in the boxes are called concepts.

The lines between the boxes are called relationships.

Theories are composed of concepts linked by

relationships.


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Variables

A positive sign shows a positive relationship, e.g.

(hours o f stud y rises, exam grades rise)

A negative sign shows a negative relationship, e.g.(Pr ice of houses rises, demand fal ls)


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Variables

A variable is a characteristic which has more than one

category or value. e.g. Age

The effect is called a dependent variable (Y);The assumed cause is called an independent

variable (X)

An intervening variable (Z) is the means by whichX affects Y..

D d ti t ti thResearch approaches


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You needto be able to operationalise variables

i.e. to make them measurable and quantifiable.

e.g Professionalism product quality or Job satisfaction

cannot be measured directly.

Research approaches

D d ti t ti th


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There can be more than one indicator or variable or value:

CONCEPTS: Poverty

INDICATORS: poor living conditions

VARIABLES: provision of sanitary facilitiesVALUES: Numbers of people per bathroom, WC

.


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Example 1

E l 2


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Example 2

Q tit ti D i


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Quantitative Design

Hypothesis Exogenous variable Endogenous variable

H1a Productive tension Functional conflict

H1b Productive tension Dysfunctional conflict

H2a Unproductive Tension Functional conflict

H2b Unproductive Tension Dysfunctional conflict

H3 Productive tension Interorganizational

performanceH4 Unproductive Tension Interorganizational

performance

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Testable ModelHypotheses


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Standard quantitative procedures

Before analysing the data, cleaning the data

(e.g. outliers, missing data) Descriptive statistics (e.g. mean, distribution,

standard deviation)

T-Tests, correlation, regressions, strength of

associations (R2)

O i f i iti l l i


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Overview of initial analysis


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E l f t t


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Example of outputs

E l f t t


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Example of outputs

Example of Listeral- Quantitative Data Analysis


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Example of Listeral Quantitative Data Analysis

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The standardized direct relations between PT, UT and FC, DC, PER

Examples of Quantitative Fit Statistics


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Examples of Quantitative Fit Statistics

Model Goodness of Fit Results

The X2 p value is significant with X2 = 316.122 and df

= 113. However, the X2/df ratio is 2.798, which is

below 3:1 ration suggested by Carmines and McIver

(1981) and (Schumacker and Lomax, 2004).

Results

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Parameter Estimate Lower Upper P

FC


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Summary of Quantitative Results

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Hypothesis Relationship Result

H1a PT FC Accepted

H1b PT DC Insignificant

H2a UT DC Rejected

H2b UT FC Insignificant

H3 PT PER Rejected

H4 UT PER Accepted

Additional Post hoc Analyses


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Interaction between PT and UT: combined effect oftension types have significant impacts on functionalconflict (FC) (-.188, =.019, significant at p


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Results

Research objectives, theory and findings must

be congruent?

Findings overly descriptive?

Findings overly narrow additional robust tests

for different types of relationships?

Results?


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Results?

Exercise


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Exercise

Sketch out your research design for datacollection.

Are you exploring or examining?

If you are examining, jot down the sources ofyour measures for your research

What are you control measures?

If you are exploring, jot down the boundary

conditions of your research?

Reflection Questions


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How will the proposed methodology achieveresearch objectives

What other research methodologies might be

employed?

Why were these methodologies rejected?

How do you go about assembling the data

collected during your fieldwork?

How to recognise any gaps in the datacollection?

What is the overall object when carrying out data

analysis?



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How do you consider the practical andoperational aspects of gathering data for your

dissertation and prepare an outline.

How can you anticipate and plan for the possiblebarriers to the completion of your fieldwork?

What do you do when co-operation is not

forthcoming from key respondents?

References


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References

Gill, J. and Johnson, P. (2010) Research Methods forManagers, London, Paul Chapman

Collis, J and Hussey, R. (2009) Business Research a

practical guide for undergraduates and postgraduate

students, London, Macmillian Kahn, R. and Cannell, C. (1957) The dynamics of

interviewing, New York, Wiley

Saunders M. et al (2009) Research Methods for

Business Students, Harlow, Prentice Hall Grant, A. M., & Wall, T. D. 2009. The neglected science

and art of quasi-experimentation: Why-to, when-to, and

how-to advice for organizational researchers.

Organizational Research Methods, 12: 653-686.

References


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References

Bell J (1999) Doing your research project (3rdEdn) Buckingham:Oxford UnivPress

Bryman A and Bell E (2003) Business Research Methods New York:OxfordUniv Press

Easterby-Smith M et al(2002) Management Research: An IntroductionLondon:Sage Publications

Robson C.(2002) Real World Research (2nd Edn) Oxford:Blackwell

Saunders M. et al (2009) Research Methods for Business Students, (Edn4) Harlow, Prentice Hall

Sekaran V (2000) Research Methods for Business: A skills buildingapproach (3rd Edn) New York:Wiley

Ticehurst GW and Veal AJ (2000) Business Research methods: amanagerial approach NSW: Pearson Education

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