Transcript Document

EMBA Project
Methodology
Alexey Verbetsky
July 2013
Plan, research and write up a Project that improves
understanding of a significant Managerial, Business, or
Organisational matter and provides recommendations or findings
upon which Action can be determined
• Personal Interests & Strengths
• Own Organisation & Colleagues
• The Literature (journals, books & reports)
• EMBA Modules & Instructors
Is the Issue Important and
Coherent?
• Past Projects
 Discuss with Others: Colleagues,
Managers etc.
 Check the Literature: What Work
Have Others Done on the Issue
that Concerns You?
Define a Broad Area of Interest
e.g. ‘Strategy in Multinational Companies’
Current Problems or Difficulties Define Strategic
Questions
e.g. ‘What Should We do to Improve the Company’s
Competitive Position in International Markets?’
Your Job is to Identify Research Question(s)
e.g. ‘What are the Factors Influencing the Company’s
Competitive Position in International Markets?’
and ‘How do We Measure/Assess the Company’s
Competitive Position in International Markets?’
http://papers.ssrn.com/sol3/DisplayAbstractSearch.cfm
Usual roadmap – key stages
Problem definition, research scope and objectives
Finalizing the research questions and strategy
Literature review and initial conclusions
Data Collection
Data analysis and interpretation
Developing conclusions
Finalizing the document with logical links
Illustrative Structure
 15%
Introduction
 10% Background on the sector
 20% Literature review
 20% Methodology
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Data Description
 15% Data Analysis and Interpretation
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Summary conclusions
 10% Recommendations
 extra 2% Reflection
Introduction – sub-sections
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Rationale for the study
Research aims and objectives
Research strategy
Methodology - summary
Key results and conclusions
Practical aspect of the project
Limitations of the study
Possible research aims and
objectives
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Develop a system of practical recommendations
Design an algorithm (Action Plan) of process
implementation
Propose new methodology, framework, theory
Analyze the existing alternative methodologies
Compare the various approaches and theories
Study the best practices
Context of Research – Market Analysis
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Subsections (world – Russian economy –
sector)
“Rich picture” – the context (players, links,
expert views on developments etc)
PEST, SWOT – in Appendices
Quotations! Diagrams! Frameworks from
assignments!
Logical links: relevance and strategic/practical
importance of the study; focus of the literature
review, methods of data analysis
Literature review
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70+ sources recommended
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Both analytical/business reports and
research papers
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Well-structured sections with short
summaries
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Clear links to the study after each piece of
analysis/framework description
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Initial conclusions (summary section that is
directly linked to the next Chapter)
Methodology
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Sub-sections: research strategy, research
instruments, data collection process, research
novelty, limitations, suggestions for further research
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Research parameters: paradigm, qual/quant, etc
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Illustrate the use and the sequence of instruments
and approaches
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Clearly explained and possibly justified instruments
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Results of each stage of the study
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Clear links to literature review and data used
Developing the questionnaire
1. Formulating the expected results (what do we
need to get)
2. Identifying the sample (what groups are we
going to ask)
3. Structuring the questionnaire and detailing each
section
4. Choosing the type of survey administration
5. Choosing the measurement type and scale
6. Design of the questionnaire (plus the cover letter
to respondents)
7. Testing (e.g., pilot) and adjusting the instrument
Developing the questionnaire
Data: organization and processing
• Clearly explained sources and types of the data
used
• Structured section on data presentation (a table)
• Primary and secondary data
• Qualitative and quantitative data
• Instruments for data processing
• The analysis should clearly lead to the conclusions
and then to recommendations
Conclusions and Recommendations
• Two separate sections (or even chapters)
• No new ideas, sources, etc.
• Summary of the project findings
• Explaining how the research activities
helped achieve the results
• Recommendations structured according to your
propositions/research questions
• Clear links to the other parts of the document
Recommendations
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Structure by groups of users (top management,
owners, etc.)
• Be practical and specific (avoid phrases like
“look for synergies”, “increase efficiency”,
“establish good relations with…”)
• Assess feasibility (“hire additional consultants”,
“launch marketing campaign”)
• Whenever possible, provide an Action Plan
Important elements of the study
• Novelty of the research (link to the literature)
new data used
new research methods applied
new object studied
new criteria developed
• Practical aspect of the research
recommendations for implementation
feasibility
Action Plan
Practical results are extremely important –
please describe in details
Practical result…
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recommendations
model
action plan
strategy
solving specific problem
organizational structure
motivation system
methodology
etc.
…aimed to
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improve efficiency
increase productivity
ensure quality
achieve profits
optimization (reorganization)
develop corporate culture
create innovation potential
build image (brand)
etc.
Quantitative/Qualitative research
Quantitative
research
Relatively more objective
Measuring the parameters that describe the
phenomenon under study
Numerical data collected and processed with
statistical instruments
Qualitative
research
Relatively more subjective
The personality of the researcher influences the
results obtained
Understanding and interpreting phenomenon under
study
Positivist and Interpretivist Paradigms
Positivist (Objectivist)
Quantitative data are usually used
Large samples
Related to hypotheses testing
The data are concrete and objective
The research is done in artificial environment
High level of reliability
Potentially low level of validity
Generalization: from sample to universe
Interpretivist (Subjectivist)
Qualitative data are usually used
Small samples
Related to generation of theories
Data are unstructured and subjective
The research is done in natural environment
Low level of reliability
High level of validity
Generalization: from one sample to another
sample
Triangulation as a source of objectivity
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Triangulation of data:
time of collection, various sources
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Triangulation of views:
research participants could have different opinions
depending on the focus
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Triangulation of theoretical base:
using more than one theory (model, framework) tin your project
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Triangulation of methodological approach:
using more than one method of data collection and processing
(secondary vs. primary data, quantitative and qualitative methods,
etc.)
Project Methodology:
Quantitative data
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Exploratory work – data identification
Data collection
Data description - Methodology
Data processing
Conclusions and Recommendations
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Quantitative research is concerned with
counting and measuring things, producing in
particular estimates of averages and
differences between groups
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Quantitative research is "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)
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Objectivity, deductiveness, generalisability
and numbers are often associated with
quantitative research
Deduction – researcher starts with a
theory, generates hypotheses and formally
tests these with data
 Positivism – dominant philosophy
underlying quantitative scientific methods
 It assumes that phenomena are
measurable using the deductive principles
of the scientific method
 Methodologies under this paradigm are
referred to as quantitative
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Methodological
Choices
research
paradigm
positivism
deductive
experiment
survey
research
approaches
research
strategies
time
horizons
data collection
methods
cross
sectional
sampling
secondary data
observation
interviews
questionnaires
case
study
grounded
theory
longitudinal
action
research
inductive
adapted from
Saunders et al. (2002, p. 83)
Development of a theory
that is subjected to a
rigorous test
Hypothesis
Researcher independence
Get a feel of what is
going on
Interview
Try to make sense of
findings
Develop theory
interpretivism
Data validity and reliability
• Validity:
determines whether the research truly measures
what it was intended to measure
• Reliability:
• the degree to which a measurement, given repeatedly,
remains the same
• the stability of a measurement over time
• the similarity of measurements within a given time
period
Other characteristics of data
• Relevance
• Level of disaggregation
• Dynamics
• Comparability
• Consistency
Successful data analysis requires
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Understanding a variety of data analysis methods
Planning data analysis early in a project and
making revisions in the plan as the work develops
Understanding which methods will best answer the
study questions posed, given the data that have
been collected
Once the analysis is finished, recognizing how
weaknesses in the data or the analysis affect the
conclusions that can properly be drawn
Secondary data – any information
collected for the purposes not related to
your research
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Documents (both published and
unpublished) – articles, Internet-reviews,
etc.
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Business and government reports, official
statistics, etc.
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Results of specific past surveys, numerical
data (e.g., company database, cash
receipts)
Primary data
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Information collected specifically for the
research under the project
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Qualitative data collection – focus groups,
in-depth interviews, observation with
protocols
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Quantitative data collection –
questionnaires (surveys); documenting the
views of the respondents on the issues
illustrated within the questionnaire (both
face-to-face and distant)
Clearly organize the presentation of
data processing results – e.g., by
groups of respondents
Sales volume goes down
External reasons
Economic crisis
Changes
in customer
preferences
Internal reasons
Improper
strategy
Inefficient
management
Lack of skills and
competences
Activities by
competitors
Operational
problems
Activities by
state/regulators
Marketing
mistakes
Ishikawa (fishbone) diagram
How to measure attitude
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Ranking
Rating
Sorting
Choice
Measuring attitude
Ranking – respondents put the objects in order
by a factor proposed within the questionnaire
Rating – respondents assign specific numerical
value to a statement or an object
Sorting – grouping the objects by a factor
proposed by the researcher
Choice – choosing among two or more
alternatives
Types of variables
• Nominal (classifying) - e.g., color, town
• Ordinal - e.g. larger/smaller
• Interval (Relative) - e.g. length, duration
Histogram as the simplest way to
describe the distribution
Horizontal bar chart
Examples of nominal data collection
1. Please state your gender
male
female
Daily turnover of consumer is…
[ ] Between 100 – 200
2. Please indicate your favorite brand:
Sony
Panasonic
Samsung
Sharp
[ ] Between 200 – 300
[ ] Above 300
3. Do you agree that the image of the company is important for your choice:
agree
disagree
Ordinal scales
Rank the following attributes (1 - 5), on their importance in
a microwave oven
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Company Name
Functions
Price
Comfort
Design
 The most important attribute is ranked 1 by the
respondents and the least important is ranked 5
 Instead of numbers, letters or symbols too can be used
to rate in a ordinal scale
 Such scale makes no attempt to measure the degree of
favorability of different rankings
Interval or Rating scales: Thermometer
How do you rate your present refrigerator for the
following qualities
Company Name
Less Known
1
2
3
4
5
Well
Known
Functions
Few
1
2
3
4
5
Many
Price
Low
1
2
3
4
5
High
Design
Poor
1
2
3
4
5
Good
Overall
Satisfaction
Very dissatisfied
1
2
3
4
5
Very
satisfied
Likert Scales
Survey administration
Survey
Self-administered
By the researcher
Filling the e-form
Phone
By fax
Face-to-face
structural interview
Personal mailing
Sampling
■ When undertaking any survey, it is
essential that you obtain data from people
that are as representative as possible of the
group that you are studying
■ Your survey data will only be regarded as
useful if it is considered that your
respondents are typical of the population as
a whole
Sample size depends on:
■ Methodology selected
■ Degree of accuracy required for the study (how
much error can be tolerated)
■ Extent to which there is variation in the
population with regard to key characteristics of the
study
■ Likely response rate (which itself will depend on
sampling method selected)
■ Time and money available
Reliability – consistency of response
■ A person would answer the same way, if given
the question on different occasions
■ Ambiguous wording may produce unreliable
responses
Validity - A valid question is one that measures
what we think it does
■ Does the question actually measure what we are
asking? Or is it affected by other factors?
■ For example, does an IQ test actually measure
intelligence? (or is the score affected by cultural
background, social class etc)
Qualitative data collection and processing
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Focus groups - informal discussions in which a
moderator probes peoples' attitudes on a specific
topic; the group is “typical” in accordance with the
desired socio-demographic parameters
In-depth interviews – unstructured personal
conversation with respondent with detailed
discussions (recording recommended)
Protocol analysis – placing a respondent in a
decision-making situation; respondent is asked to
provide detailed description of factors that have
been considered during the process
Observation – describing and registering various
types of data by observing the process
Case study
■ Intensive analysis of an individual unit (e.g., a company,
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team, or project) – practical, problem-solving orientation;
generation and testing of hypotheses; holistic approach that
uses multiple theories and methods
Content analysis
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■ Research methodology that examines words or phrases
within a wide range of texts. Researchers quantify and
analyze the presence, meanings and relationships of such
words and concepts, then make inferences about the
messages within the texts
Key methods of quantitative analysis
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Tables with shares/distribution of data;
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Correlation analysis (e.g., calculating Pierson
correlation coefficients measuring
interdependencies between variables);
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Regression analysis that provides quantification
of dependencies (with the ultimate goal of
modeling these dependencies in order to
forecast certain variables);
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Analysis of variation - comparing means for
groups
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Cluster Analysis - justifying the classification of
objects by groups (clusters)
Example of model construction
1. Document the assumptions on how the factors
influence the parameter under study
Demand
P
Parameter under study
Factors
=
f (x, y, z, …)
Independent variables
2. Compile a detailed list of possible factors – use the
results of the literature review
3. Identify the factors relevant in your case (either
through expert opinion or statistically)
Factors influencing consumer choice
Demand
Usefulness
Quality
Social value
Entertainment
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Image
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Indicators – questions for the interviews/surveys
Price
…
Linear regressions
Regression modeling: looking for
dependencies
X3
Y
X2
X1
Y = b0 + b1X1 + b2X2 + . . . + bnXn+
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Y – dependent variable, Xi – independent variables,  - error
Factor analysis
Main applications:
■ To reduce the number of
variables
■ To detect structure in the
relationships between
variables (to classify them)
■ Note that cluster analysis
groups cases; factor
analysis groups variables
Hypotheses
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Hypotheses are propositions about
relationships between variables or
differences between groups
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For example: do patients treated with drug A
show greater improvement than those treated
with Drug B
Creating a testable hypothesis
We tend to start from a general, vague
question
 Need to turn this into something specific
and appropriate
 Two things we need to specify:
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 Independent variable (the aspect of the
environment that we are interested in)
 Dependent variable (the behaviour that we
are interested in)
A framework for assessing the quality of
qualitative research
Credibility
Does the way you present your
findings give the impression that
they are well grounded?
Validity
Does the work reflect the
reality of the issue or
situation being investigated?
Quality of
your
findings
Reliability
Would it be possible for the
work to be repeated and
obtain the same or similar
results?
Generalisability
How applicable are the
findings to the wider world
outside the one you have
considered?
Checklist
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Обоснуйте актуальность планируемого исследования (для кого и
почему)
В чем состоит научное и практическое значение данного
исследования?
В чем будет заключаться основной вклад планируемого
исследования?
Объясните, как планируемого исследование связано с
существующими знаниями в области менеджмента, экономики и
т.д.;
Каким образом литературный обзор связан с целями и задачами,
а также с методологией исследования?
Какая ключевая гипотеза была выдвинута и почему?
Обоснуйте выбор методологии и информационной базы
исследования;
Какие методы или процедуры анализа информации Вы
планируете применить и почему?
Что Вы планируете получить в результате исследования (прогноз
результатов)?
Какие допущения и ограничивающие обстоятельства присущи
данному исследованию и как это повлияло на выбор
методологии исследования?