RESEARCH METHOD Sessions 3: Analysing qualitative data

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RESEARCH METHODSessions 3: Analysing qualitative data

Saunders, Lewis and Thornhill, Research Methods for Business Students, 5th Edition, © Mark Saunders, Philip Lewis and Adrian Thornhill 2009

14/12/2015Phương pháp nghiên cứu_Mai Anh ([email protected])1

Anh MAI, [email protected]

Slide 13.2

The Business Research Process


14/12/20152Phương pháp nghiên cứu_Mai Anh ([email protected])

Slide 13.3

Analysing qualitative data

Definition

‘Qualitative data refers to all non-numeric data or

data that have not been quantified and can be a


data that have not been quantified and can be a product of all research strategies’

Saunders et al. (2009)


Slide 13.4

Analysing qualitative data

Distinctions between quantitative and qualitative data



Bảng 13.1 Các khác biệt giữa dữ liệu định lượng và định tính14/12/20154

Phương pháp nghiên cứu_Mai Anh ([email protected])

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Preparing data for analysis

Key issues

Transcribing qualitative data


Using electronic textual data including scanned documents

The interactive nature of the process


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Approaches to qualitative analysis

Main approaches

The deductive approach


The deductive approach

The inductive approach


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Types of qualitative analysis process

Main types

Summarising (condensation) of meanings


Categorising (grouping) of meanings

Structuring (ordering of meanings using narrative



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Types of qualitative analysis process

Dimensions of qualitative analysis



Hình 13.1 Các phương diện trong phân tích định tính14/12/20159


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Categorising data

Points to consider

Deriving categories

‘Unitising’ data

Recognising relationships and developing categories


Developing testable propositions

Qualifying your qualitative data


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Analytical aids

Types of analytical aids

Interim summaries


Self-memos

Researcher’s diary


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Deductively based analytical procedures

Procedures applicable to qualitative analysis

Pattern matching


Explanation building


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Inductively based analytical procedures

Procedures applicable to qualitative analysis

Data display and analysis

Template analysis


Analytic induction

Grounded theory – open, axial and selected coding

Discourse analysis

Narrative analysis


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Discourse analysis

A three-dimensional analytical framework for critical discourse analysis


Saunders et al. (2009)Hình 13.2 Mô hình phân tích ba chiều trong phân tích ngôn từ một cách có phê phán 14/12/201514


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Using CAQDAS for qualitative analysis

Summary of functions

Structure of work

Closeness to data and interactivity

Explore the data


Explore the data

Code and retrieve

Project management and data organisation

Searching and interrogating

Writing memos, comments and note

Output)


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Summary

Qualitative data result from the collection of non-standardised data that require classification and are analysed through use of conceptualisation

Qualitative analysis can involve summarising, categorising and structuring data

The process of data analysis and collection are necessarily interactive


necessarily interactive

Aids to analysis include interim summaries, self-memos and maintaining a researcher diary

Qualitative analysis procedures can be related to using either a deductive or inductive approach

Computer-assisted qualitative data analysis software (CAQDAS) can help with project management and data organisation


Slide 13.17Example of Analysing qualitative data process



Slide 13.18

Example

Darling ,

Where are you this time? What are you doing? The sky is turning dark and it’s still raining. I feel blue. I wish that I have you by my side this moment. We could go to the cinema or to the shopping centre, it would be so wonderful. And


shopping centre, it would be so wonderful. And you will buy a pair of Gucci shoes for me as you had promised, right.

I miss you.

your sincerely LyLy


Slide 13.19

Discussion

Case: Base on the Traphaco general director interview, aggregating and analyzing qualitative

Topics:

Topic 1: Research on corporate culture

Topic 2: Development strategy and business


Topic 2: Development strategy and business organization

Topic 3: Labor behavior management

Topic 4: Leadership style

Topic 5: Product development Strategy


Slide 13.20

Construction and development of case studies

1. Why do we need to develop case studies?

2. How do we construct a case study

3. Preparation for collecting data

4. collecting data


5. Analyzing outcomes

6. writing report


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Why do we need to develop case studies?

Advantages - Disadvantages

Compared with other research methods



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Research methods comparison



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2. How do we construct a case studyDesigning questions

Assumptions

Analyzing units/respondents

Links between the results logic and assumptions

The criteria for interpreting the results


The criteria for interpreting the results


Slide 13.24Criteria for assessment the case study ’s quality



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The type of study design case studies



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Case study Method



26

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3. Preparation for collecting data

1. Interview’s preparation:

Know how to ask questions

Know how to listen to others

Flexible and adapted,

Understand the issue


Understand the issue

2. Learn to:

design case study

protocol development


Slide 13.28

Designing case study process

A. Introduction and objectives of the process:

Questions, hypotheses …

Theoretical framework

The role of the process in the researcher guide

B. Data collection process:


B. Data collection process:

The object name

Collecting data plan


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Designing case study process

C. Structuring the case study outline

D. Case study questions

Relate to research

Relate to research assessment



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4. Collecting data

Reviewing the literature

Archival record

Interview

Observation

Participant observation

Real sampling


Real sampling


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5. Analyzing data

Individual Analysis

Cross Analysis



Slide 13.33

RESEARCH METHODSessions 4: Analysing quantitative data



Duc Anh MAI, [email protected] Quốc tế, ĐHQGHN

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Quantitative data analysis

Key points

Data must be analysed to produce information

Computer software analysis is normally used for this process

Data should be carefully prepared for analysis


Data should be carefully prepared for analysis

Researchers need to know how to select and use different charting and statistical techniques

Slide 13.36

Main concerns

Preparing, inputting and checking data

Choosing the most appropriate statistics to describe the data

Quantitative data analysis


describe the data

Choosing the most appropriate statistics to examine data relationships and trends

Slide 13.37


Main considerations

Type of data (scale of measurement)

Data format for input to analysis software

Impact of data coding on subsequent analyses


Impact of data coding on subsequent analyses

Case weighting

Methods for error checking

Slide 13.38

Preparing, inputting and checking data Defining the data type

Saunders, Lewis and Thornhill, Research Methods for Business Students, 5th Edition, © Mark Saunders, Philip Lewis and Adrian Thornhill 2009Saunders et al. (2009)

Hình 12.1 Xác định dạng dữ liệu

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Preparing, inputting and checking data Defining the data type



Hình 12.1 Xác định dạng dữ liệu (Tiếp theo)

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A simple data matrix



Bảng 12.1 Ma trận dữ liệu đơn

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Main data categories for coding

Numerical data

Categorical data


Categorical data

Missing data

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Final stages of the process

Entering data – rubbish in = rubbish out!

Weighting cases

Always take time to check for errors – including


Always take time to check for errors – including illegitimate codes, illogical relationships and that rules were followed in filter questions

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Exploring and presenting data

Exploratory analysis can include:

Specific values

Highest and lowest values

Trends over time

Proportions


Proportions

Distributions

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Showing aspects of individual variables

Specific values


Trends


Proportions

Distribution of values

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Examples of diagrams

Bar Chart


Source: adapted from Eurostat (2007) © European Communities, 2007 Reproduced with permissionHình 12.2 Biểu đồ thanh / cột

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Examples of diagramsHistogram



Hình 12.4 Tổ chức đồ / biểu đồ tần số

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Examples of diagrams

Pie chart


Saunders et al. (2009)HÌnh 12.8 Biểu đồ hình quạt

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Comparing variables to show

Specific values and independence


Proportions


Proportions

Trends and conjunctions

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Comparing variables to show

Totals

Proportions and totals




Relationship between cases for variables

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Describing data using statistics

Statistics to describe a variable focus on two aspects

The central tendency


The dispersion

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Describing the central tendency

To represent the value occurring most frequently

To represent the middle value


To include all data values

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Describing the dispersion

To state the difference between values

To describe and compare the extent by which values differ from the mean


values differ from the mean

Slide 13.53Examining relationships, differences and trends

Using statistics to

Test for significant relationships and differences

Assess the strength of relationship


Assess the strength of relationship

Examine trends

Slide 13.54

Summary

Data for quantitative analysis can be collected and then coded at different scales of measurement

Data type constrains the presentation, summary and analysis techniques that can be used

Data are entered for computer analysis as a matrix and recorded using numerical codes

Codes should be entered for all data values


Codes should be entered for all data values

Existing coding schemes enable comparisons

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Summary

Data must be checked for errors

Initial analysis should use both tables and diagrams

Subsequent analyses involve describing data and exploring relationships by using statistics


Longitudinal data may necessitate different statistical techniques

Slide 13.56Example: The steps to verify the economic model

Step 1: Purification of variables (analysis PCA)

Reduce variable

Shift measurement elements (items) from variable to another variable

Index Threshold

KMO and Barlett's test of SphericityKMO ≥ 0.60



KMO and Barlett's test of SphericityBarlett's test significant at p = 0.05

Communality At least 0.40

Correlation item/factor

(the factor loading)

At least 0.60

Items should not be substantially loaded on

more than one factor

Internal Consistency (Alpha) At least 0.60

Total Value Explained >1

Slide 13.57Example: Steps to verify the economic model

Step 2: Analysis of the reliability of the scale

The ability to measure a known component of the elements (items)

Using Cronbach Alpha coefficients

Step 3: Describe the variable component


Step 3: Describe the variable component

Mean

standard deviation value as small as possible


Slide 13.58Example: Steps to verify the economic model

Step 4: Verify the measurement

Inspection of the normal distribution Skewness

close to 0 and Kurtosis (less than -2 and greater than +2 is not normal distribution)

• Cronbach Alpha coefficients

• face/content validity: variable proven yet


• face/content validity: variable proven yet

• Unidimensionality: Alpha, item-total-correlation

• correlation


Slide 13.59

Step 5: Testing the hypothesis and research model

Linear regression univariate and multivariate

R2 determining factor represents the proportion of total variability

the dependent variable can be explained by variation of independent variables 0<= R2 <=1

Example: Steps to verify the economic model


independent variables 0<= R <=1

Ad. R2 determining adjustment coefficients: when new variables

F: All independent variables related to the dependent variable or not


Model SummaryModel

R R Square Adjusted R SquareStd. Error of the

Estimatedimension0

1 .666a .444 .343 .27484

a. Predictors: (Constant), WRK.TIME, Extrinsic Motivation, EDU.LEVEL, Intrinsic Motivation, SEX, AGE

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ANOVAb

ModelSum of Squares df

Mean Square F Sig.

1 Regression 1.990 6 .332 4.392 .002a

Residual 2.493 33 .076

Total 4.483 39

a. Predictors: (Constant), WRK.TIME, Extrinsic Motivation, EDU.LEVEL, Intrinsic Motivation, SEX, AGEb. Dependent Variable: Perceived Human Performance

Coefficientsa



CoefficientsModel Unstandardized

CoefficientsStandardized Coefficients

t Sig.B Std. Error Beta1 (Constant) -1.176 .809 -1.452 .156

Intrinsic Motivation

.233 .149 .228 1.565 .127

Extrinsic Motivation

.752 .188 .558 4.002 .000

AGE .229 .169 .325 1.357 .184SEX .109 .183 .093 .595 .556EDU.LEVEL .089 .149 .095 .597 .554WRK.TIME -.004 .017 -.050 -.220 .827

a. Dependent Variable: Perceived Human Performance

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Step 5:

Inspection of moderator variable

D = f (control variables)

D= f (I, M, CV)

D= f(I, M, IxM, CV)

Example: Steps to verify the economic model


Inspection of intervening variables

M= f (I, CV)

D= f(I, CV)

D= f(I, M, CV)


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RESERCH METHODSESSION 5: Writing and presenting your project report



Duc Anh MAI, [email protected]

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Getting start with writing

Practical hints

Create time for your writing

Write when your mind is fresh

Find a regular writing place


Find a regular writing place

Set goals and achieve them

Use word processing

Generate a plan for the report

Finish each writing session on a high point

Get friends to read and comment on your work

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Structuring your research report

Suggested structure

Abstract

Introduction

Literature review


Method

Results

Discussion

Conclusions

References

Appendices

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Writing for different audiences

Key differences between an ‘Academic’ reportand a ‘Consultancy’ or ‘Management’ report

The academic report:

Tends to be longer

Will be marked and graded


Will be marked and graded

Will contain contextual descriptions

The consultancy report:

Has less focus on the development of theory

Contains recommendations relating to the organisation’s business

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Report structure

The abstract

04 short paragraphs that answer the questions:

What were my research questions and why were they important?


they important?

How did I go about answering the research questions?

What did I find out in response to these questions?

What conclusions can be drawn?

Adapted from Saunders et al. (2009)

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Report structure

Introduction - include

The research questions(s) and a clear statement of research objectives

Brief background and a guide to the storyline


Literature review - purpose

To set your study in the wider context

To show how your study supplements existing work

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Report structure

Results chapter(s) - purpose

To report the facts your research discovered

To support the facts with quotes from participants


Discussion chapter- purpose

To interpret results and relate the findings to the original research goals and objectives

To indicate implications of the research

Slide 13.70

Report structure

Using a matrix in the planning of the content for the results and conclusions chapters




Hình14.1 Sử dụng ma trận để lập dàn ý viết nội dung cho các chương kết quả và kết luận

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Report structure

Conclusion chapter – purpose

To answer the research question(s)

To meet the research objectives


To meet the research objectives

To consider the findings

To present any contributions to the topic displayed in the literature

To reflect on any implications for future research

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Report structure

References

Use a convention that is accepted by your university (e.g. Harvard, APA)

Cite all sources referred to in the text

Check all citations to prevent plagiarism


Check all citations to prevent plagiarism

Appendices

Include only essential supporting material

Include copies of interview schedules

Keep appendices to a minimum

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Organising the report content

Main points to consider

Choosing the title

Telling a clear story

Helping the reader by-

• Dividing your work


• Dividing your work

• Previewing and summarising chapters

• Using suitable tables and graphics

• Writing in a suitable style

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Writing style

Key points

Clarity and simplicity – avoid jargon

Checking grammar and spelling

Preserving anonymity


Regularly revising each draft

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Oral presentation

Three key stages

Planning and preparation

Use of visual aids

Presenting


Presenting

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Summary

Writing is a creative process and a powerful way to clarifying your thinking

A project report needs a clear structure that helps to develop the storyline

All the information should be readily accessible to


the reader

Use a clear writing style free and check for spelling and grammatical errors

Be prepared to rewrite the first draft several times

Remember to check the assessment criteria

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Summary

Failing to prepare for your presentation is preparing to fail

Visual aids help the audience understand your presentation


Remember to Tell them what you're going to say

Say it

Tell them what you said

Slide 13.78

References

Nguyễn Hải Thanh. 2010. (dịch sang tiếng Việt và biên tập), Bài giảng về phương pháp nghiên cứu trong kinh doanh (powerpoint slides).

Vũ Cao Đàm. 2006. Phương pháp luận nghiên cứu khoa học, Nxb. Khoa học và Kĩ thuật.

Nguyễn Duy Bảo. 2007. Phương pháp luận nghiên cứu khoa học và thực hiện đề tài nghiên cứu khoa học, Nxb Bưu Điện.


và thực hiện đề tài nghiên cứu khoa học, Nxb Bưu Điện.

Nguyễn Hùng Phong, Bài giảng về Phương pháp nghiên cứu (powerpoint slides)

Ang Eng Sieng. 2011. Business Research (MGT203), HELP-VNUIS- Bachelor of Business.

Yap Kim Len. 2010. Phương pháp luận nghiên cứu, HELP-VNUIS MBA.

78Phương pháp nghiên cứu_Mai Anh ([email protected]) 14/12/2015

RESEARCH METHOD Sessions 3: Analysing qualitative data

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