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Summary Business Research Methods Qualitative (E_IBA2_BRML)

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The BRM qualitative summary provides a comprehensive overview of key concepts, methods, and techniques used in qualitative research for business research purposes. It covers topics such as research design, sampling techniques, data collection, and data analysis methods. The summary emphasizes the importance of using appropriate qualitative research designs and techniques that align with the research question and objectives, as well as the importance of selecting appropriate participants and ensuring data quality. The summary highlights the unique strengths of qualitative research, such as the ability to explore complex and nuanced experiences, perceptions, and behaviors that are difficult to capture through quantitative methods. It also covers different data collection techniques such as in-depth interviews, focus groups, and observational methods, and how to analyze and interpret qualitative data using coding, thematic analysis, and other qualitative data analysis techniques. Overall, the summary equips readers with the knowledge and skills needed to conduct successful qualitative research projects in BRM. It provides valuable insights into the strengths and limitations of qualitative research, and offers practical guidance for designing and conducting effective qualitative research studies. By understanding the unique contributions of qualitative research, readers can make informed decisions about which research approach to use in different business research contexts, and develop a deeper understanding of the phenomena they are investigating.

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BRM 2 Exam (Module D, E, F)


Module D



Readings:

Tracy (2013). Chapter 9: Data Analysis Basics
General concept
- Data analysis basics
- A pragmatic iterative approach

Notes:

ORGANIZING AND PREPARING THE DATA

● Different organizing schemes
○ Chronologically - by their date of collection or construction
■ This is the most popular one
○ Type of data - Having a particular file for the different types of data
■ Field notes one file, interviews another
○ Source - Organizing data according to different attributes
■ For example, age, race, religion and so on.

DATA IMMERSION AND PRIMARY-CYCLE CODING

● Data immersion phase
○ “Submerge yourself in the entire breadth of the data by reading and re-reading
them, listening to them, and thinking about them”
■ Happens about three quarters through the data collection

● Primary cycle coding
○ Initial cycles trying to open up meaning in the data
■ Begins with an examination of the data and assigning words or phrases
that capture their essence
■ May also make use of the actual words or phrases within the datum
itself

● First level codes
○ Focus on “what” is present in the data. They are descriptive, showing the basic
activities and processes in the data.

, ■ The goal is to detail the “who, what, and where”, not to provide an
analysis of why

● Constant comparative method
○ Used throughout the coding process, to compare the data applicable to each
code, and modify code definitions to fit new data.
■ For example, you begin with LAUGHTER because everyone laughed,
however, when you revisit the interview, you see that this was not the
case, hence you code ATTEMPTED HUMOR




SECONDARY CYCLE CODING: SECOND-LEVEL ANALYTIC AND
AXIAL/HIERARCHICAL CODING

● Secondary cycle coding
○ The researcher critically examines the codes already identified in primary
cycles and begins to organize, synthesize, and categorize them into
interpretive concepts
■ Moves beyond first level descriptive codes into analytical and
interpretive

● Axial coding
○ Process of resembling data that was fractured during open coding (primary
level coding)
■ These lead to hierarchical codes - systematically grouping together
various codes under a hierarchical “umbrella” category that makes
conceptual sense




SYNTHESIZING AND MAKING MEANING FROM CODES

● Negative case analysis
○ Asks researchers to actively seek out deviant data that do not appear to support
the emerging hypothesis

, Keywords from Article 1:

● Iterative analysis
○ An analysis that alternates between emic, or emergent readings of the data and
an etic use of existing models, explanations, and theories
■ Essentially, alternating emic/etic approach
○ It encourages reflection upton the active interests, current literature, granted
priorities, and various theories the researcher brings to the data
● Coding
○ Refers to labeling and systematizing the data
■ Both manual and computer aided approaches with softwares
■ Active process of identification as belonging to, or representing, some
type of phenomenon
● Codes
○ Words or short phrases that capture a “summative, salient, essence-capturing,
and/or evocative attribute for language-based or visual data”.
● In vivo codes
○ They use the language and terms of the participants themselves
■ For example, someone uses the word RETARDED. You code that.
■ Particularly useful if researchers are interested in, for example, slang in
a local community.
● Codebook
○ A data display that lists key codes, definitions, and examples that are going to
be used in your analysis.
● Second level codes -
○ Serve to explain, theorize, and synthesize first level codes
■ Second level codes often draw from disciplinary concepts
● Analytic memos
○ Sites of conversation with ourselves about our data
■ Focused on the meaning of the codes and on the connections among
them


ARTICLE 2 - Kelle, U. (1997). Theory building in qualitative research and computer
programs for the management of textual data. Sociological research online
General concept - Computer-Aided Qualitative Data Analysis is “bad” for your research

Notes

● Concern
○ The increasing use of specific computer software could lead researchers to
adopt a new orthodoxy for qualitative analysis
■ Orthodoxy -
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