business research: principles and processes mgmt6794 · multiple case studies before and after case...

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Business Research: Principles

and Processes MGMT6794Workshop 5A: Preparing the literature review

Professor Tim Mazzarol – UWA Business School

UWA Business School DBA Program [email protected]



Important timelines

Assignment Exploratory analysis of the literature

Final literature review

Length: Max. 3,000 words (approx. 12 pages).

Max. 6,000 words (approx. 25 pages)

Due date: Friday 3 March (midnight) Initial draft – Friday 31 March

Final – Friday 28 April (Midnight)

Contribution to total mark:

40% 60%

Description: Exploratory analysis of the literature using NVivo and Leximancer software. Should aim to validate the research questions, identify patterns, gaps and future coding structure.

Critical analysis of the literature addressing the research questions, hypotheses or propositions. Should demonstrate good coverage of literature, logical synthesis of extant works, and assessment of theoretical, methodological and empirical findings.


Contribution of research to theory

No adding to the scientificpool of knowledge in termsof theory or researchmethodology. Stay Away !

Adding to the scientific poolof knowledge in terms of new theory. A defendableavenue for a doctoral project.

Adding to the scientific poolOf knowledge in terms of new research methodology.A defendable avenue for a doctoral project.

Adding to the scientific poolof knowledge in terms ofnew theory & methodology.A difficult avenue for a doctoral project; all is new. Stay Away !

Theory

Researc

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Old NewO

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Source: Lingreen, Vallaster & Vanhamme, 2001


Features of a good literature review

• An introduction providing an

overview of the focus & objectives

of the review plus a thesis statement

• A set of themes that categorize &

make sense of the sources reviewed

& develop the thesis

• Explanation & evaluation of key

conclusions from sources

• Conclusions, assumptions &

identified gaps

Source: Zorn & Campbell, 2006


Common errors when conducting a

literature review

• Collecting as many citations as

possible “playing a numbers

game” – quality is better than

sheer quantity.

• Claiming research is entirely

unique “nothing published on the

topic” – failing to think about a

topic in context.

• Citing only second and third-

hand accounts of the classics

– go to the original sources.

• Not focusing on both theoretical

and methodological streams:– Theoretical

• Findings and constructs

– Methodological • Methods of inquiry, measures, instruments,

ways of recording data. Source: CRQ, 2015


Desired outcomes

• Demonstrate you clearly understand the topic or field.

• Show you have identified all major studies related to the topic & discussed them.

• Develop from the review a clearly stated research problem.

• Draw clear & appropriate conclusions from the research.

• Establish & describe the various points of view related to your research topic.

• Propose valid recommendations based on analysis of the information cited in the literature review.

• Demonstrate you have a genuine research problem to address in your thesis.

Source: Baker, 2000


Format for the literature review

• The introduction– Road for the literature review section.

– Outlines the scope and focus.

– Differentiates planned research from extant literature cited.

• Background section– Why are these areas important to the study?

– How has the literature so far generated specific theories, models, hypotheses that are to be explored or used?

• Literature review search strategy– Explain how you have identified the literature and

justify your choices.

• Literature review grouped by hypotheses– Focus the literature review around dependent

variables of interest and how the hypotheses will relate to the dependent variables.

• Literature review grouped by importance– List studies of most importance first.

• Summary and conclusions– Summarise the most important studies in relation to

the hypotheses and show how this literature review will contribute.

Source: Garson (2013)


Suggested hierarchy of studies


Statistical Meta-analyses

Qualitative meta-analyses

Large national random studies

Smaller random sample studies

Multiple case studies

Before and after case studies

Point in time single case studies.

Rela

tive I

mp

ort

ance

“Part of the job of the literature review

is to indicate to the reader which

citations are more important and which

less. Within sections grouped by

hypothesis, the researcher should

indicate studies of importance.”


General considerations

• Do not undertake a literature review before

clearly defining your research question.

• The research questions not the topic, dictate

the parameters of the literature review.

• Use the literature review to make explicit how

your study will confirm, disprove, qualify,

extend or make an original contribution to the

extant literature.

• Relate your literature review directly towards

the generation of hypotheses that will be used

in your study.

• Keep in mind the overall “story line” of the

study as you write it.

• Rather than arrange the literature in date order

you are better to build it around your research

questions and the generation of your set of

testable hypotheses.



Follow a process

Problem Statement

Why is the study important?

What will it contribute to theory & practice?

What are the likely boundaries of the research project?

• Industry

• Time

• Location

• Field of study

• Units of analysis

Research Questions

What are the main questions your study needs to address?

Make sure you don’t have too many RQ’s

Make sure they are well designed

• Not “yes/no”

• Not leading

• Not too complex

Systematic Data Collection

Use a structured search process (i.e. keywords).

Focus on:

• Theoretical

• Methodological

• Empirical evidence.

Review all likely data sources

• Journals

• “grey” literature

• theses

Use multiple search engines

• Google Scholar

• Onesearch

• JSTOR

• ProQuest

Use database system

• Endnote

Data analysis

Read each source and make notes of its value.

Use data analysis tools:

• Nvivo

• Leximancer

• Meta-analysis

Develop a coding method:

• First cycle

• Second cycle

Use your RQ’s as a guide.

Make “analytic memos”

• Nvivo

Look for patterns and gaps.

Write the literature review

Validate or revise:

• Problem statement

• Research Questions

Synthesize the literature:

• Show patterns

• Explain evolution

• Find gaps

Highlight the key issues:

• Theoretical

• Methodological

• Empirical

Suggest future directions:

• Research model

• Hypotheses

• Methodology


Group Exercise

• In groups discuss your current state of progress.

• How much has your project changed since the completion of the initial unit?

• Consider your:

– Research problem

– Research questions

– Data collection process

– Data analysis using Nvivo / Leximancer

– Directions for future action

• Make a list of the main areas that you need to address going forward.


Coding in Qualitative Analysis

• What is a code?– “In qualitative analysis, a code is a researcher-

generated construct that symbolizes or ‘translates’

data”.

• Coding is NOT a precise science

• Coding is a search for patterns– “A pattern is a repetitive, regular, or consistent

occurrence of action/data that appears more than

twice”.

• A pattern can be identified as:– Similarity (things happen the same way)

– Difference (things happen in predictably different

ways)

– Frequency (they happen often or seldom)

– Sequence (they happen in certain order)

– Correspondence (they happen in relation to other

activities)

– Causation (one appears to cause the other).

• Coding is analysis and is cyclical– Coding requires multiple cycles

– Code and re-code until it is done.

– Themes emerge from the coding but are not

coded.

Sources: Saldana, 2016

Coding is not just labeling, it is linking. “It

leads you from the data to the idea and

from the idea to all the data pertaining to

that idea”. (Richards & Morse, 2013 p. 154)


Questions to consider as you code

• What is your research

problem?

• What are your research

questions?

• What are the theoretical

foundations of your study?

• What are your goals and

objectives?



Analytic Memo Writing

• What is an Analytic Memo?

– Analytic memos are a place to “dump your brain”.

– “Memos are sites of conversation with ourselves about our data”.

– Memos are “roughly equivalent to a lab notebook in experimental research”.

• Analytic Memos allow you to:

– Personally reflect on the data.

– Discuss and explain your coding process.

– Comment on emergent ideas, patterns and theories.

– Highlight concerns and limitations.

– Map out future directions for the research.

– Suggest initial answers to your research questions.

– Scope out the final structure of your thesis.Sources: Saldana, 2016


Video – Cycles of Coding


Coding Cycles


1st Cycle

Coding2st Cycle

Coding

3st Cycle

Coding

Initial coding of data:1. Grammatical

2. Elemental

3. Affective

4. Literary & Language

5. Exploratory

6. Procedural

7. Themeing the data

Analytical coding of data:1. Pattern coding

2. Focused coding

3. Axial coding

4. Theoretical coding

5. Elaborative coding

6. Longitudinal coding

Transitioning to the thesis1. Analytical memos

2. Identification of key themes &

concepts

3. Interrelationships between these

4. “Codeweaving” – building the

narrative

5. Coding to Theorizing


Group Exercise

• In groups discuss your current

progress with coding the literature

review.

• Consider the following:

– Do you have a coding structure?

– Has the structure been guided by

your research questions?

– What common approaches have

you used in coding sources?

– Have you progressed through first,

second and even third cycle

coding?


Using NVivo for Literature Reviews

• Read the literature – Write analytical memos in NVivo “proxy

documents”.

– Develop a coding structure with Nodes.

• Organise the literature– Attributes and Classifications

• Classification = Methodology

• Attributes = qualitative, quantitative

• Aggregate data into themes– Coding into nodes

• Parent – Child “Tree Structure”

• Build arguments from the literature– Use NVivo analysis tools:

• Word clouds

• Framework Matrices

• Links

• Maps

• Charts

Source: di Gregorio, 2000


Video – Using NVivo for Literature Review


Why use NVivo for literature reviews

• Assists with the management of large amounts of data.

• Can analyse a wide range of file formats (e.g. PDF, WORD, audio, video).

• Reduces the risk of researcher bias or error.

• Provides an auditable trail to allow for future review and revision.

• Avoids risk of plagiarism.

• Finds links and patterns not easily identified with “naked eye”.

• Can build the foundation of a future coding system for the study.

• Enhances “academic credibility” and opportunity to publish findings.

Source: Sweet, 2014


Stages of the NVivo analysis

Source: Sweet, 2014

Step 1: Create an NVivo project for the literature review.

Step 2: Create sub-folders for different types of data sources:

• Internals – original sources

• Memos – observations (text)

Step 3: Format PDFs in ENDNOTE using OCR to permit later coding, consider what you need to import.

Step 4: Export selected ENDNOTE references as XML file and import into NVivo.

Step 5: Use NCapture to import a web page into NVIVO.

Step 6: Set up a coding system with predetermined Nodes.

Steps 7 to 9: Commence coding sources to nodes.

• Code source – all data

• Code selection – selected data

• Code In-Vivo – captures all text

Step 10: Conduct a text search in NVivo and save the results.

Steps 11 & 12: Conduct a word frequency analysis.

• Take care to limit words to between 4 and 100.

• Locate & remove “Stop Words”.

Steps 13 & 14: Explore the data:

• Create case nodes for articles.

• Create a framework Matrix for your literature.


Group Exercise

• In groups discuss your current

progress with using NVivo for the

literature review.

• Consider the following:

– Managing sources in ENDNOTE &

NVivo.

– Coding source data into Nodes.

– Identification of any patterns using

word clouds, word frequency,

framework matrices.


End of presentation

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