RFM

Explanation of observed regularities

1.) Theory
2.) Hypothesis
3.) Data Collection
4.) Findings

1.) Preliminary Assumptions
2.) Datal Collection
3.) Hypothesis
4.) Theory

Understanding of Reality
 - is objective vs. is socially constructed

Methods
 - deductive, testing of hypothesis, explanators vs. Inductive, Developing Hypothesis, Understand

Analysis
 - Controlled conditions, fixed procedures, narrow and precise, focus on numbers vs. Natural conditions, flexible, comprehensive, little measuring

 

 - Experimental Design

 - Cross-Sectional Design

 - Longitudinal Design

 - Case Study Design

 - Comparative Design

guides the execution of a research method and the analysis of the data
 

 Qualitative Interviews
 - Narrative
 - Problem-Centered
 - Expert
 - Focus Group

Observation

Documents as Data
 

 - dominant communication style
 - suggestive questions
 - problems with passive listening
 - too rigid handling of interview guide

 - Structering
 - Gentle
 - Clear
 - Open
 - Steering
 - Critical

 - seeing through other's eyes
 - learning the native language
 - access to hidden activities
 - naturalistic emphasis
 

 - More ethically defensible
 - Less intrusive
 - Specific focus
 - 

 - companies
 - own interest
 - Problems from practise
 - literature

1.) Management Dilemma (rising costs)
2.) Management Question (how can they reach targets?)
3.) Research Question
4.) Investigative Question (What do we need to know?)
5.) Measurement Question (What should be asked?)
6.) Management Decision

Reliability
 - Study repeatable?
 - Measures consistent?
 - often an issue with quant.

Validity
 - concerned with integrity
 - measurement / internal / external / ecological

Objectivity
 - independent of researcher

Trustworthiness
 - How believable
 - apply to other context
 - apply at other times
 
Relevance
 - importance in the field
 - contribution to the literature

Strategic

Snowball Sampling

Theoretical Sampling

 - large data base
 - richness of data makes it difficult to find analytic paths
 - no clear-cut rules

 choice of method depends on type of problem and type of data

Coding and Categorizing (Daten in Kategorien aufsplitten)
 - Theoretical Coding
 - Thematic Coding

Narrative and Hermaneutic Coding (trying to conduct sense of narrative, read btw. the lines)
 - Narrative Analysis
 - Objective Hermaneutics

 Conversation Analysis
 - 
 

Analysis of latent (verborgen) meaning
- Wörtlichkeit ist wichtig, meaning btw. the lines

Analysis of apparent meaning
 - often large amounts of data, computer aided procedures

 - disputable whether theory-neutral observation is feasible
 - often required to build studies on what is already known
 - results may end in concepts, but not in theory
 - unclear difference between concepts and categories

 - Capturing Complexity
 - Linking with Practise
 - Putting life into well-established fields
 - facilitating theoretical work in areas that have not been well researched

 - Theoretical Sampling
 - Coding
 - Theoretical Saturation
 - Constant Comparison

 - Concepts
 - Categories
 - Properties
 - Hypothesis
 - Theory

 - Cose as soon as possible
 - Make as many notes as possible
 - Review the codes
 - While you read the transcript for the first time, do not make notes

 - Substantive Theory, based on research on a specific area, näher an Praxis

 - Formal Theory, more general and has more absolute validity

Universal explanations of phenomena by pursuing the collection of data until no cases incosistent with hypothesis are found

Theory is driven from data. Data collection and analysis proceed in tandem, repeatedly referring back to each other

1.) Categories for topics
2.) Sub-Categories and typical characteristics
3.) structure topics with respect of importance
4.) similarities and differences between interviews
5.) answer research question

Quntitative, Qualitative, Equal Weight (priority)
 - Quan -> qual (sequence)
 - Qual --> Quan
 - Concurrent (gleichzeitig)

 1.) Qualitative research facilitates (erleichtern) quantatitive research

 - Providing Hypothesis
 - Theorie aufstellen und dann messen (induktiv -> deduktiv)

2.) Quantitative Research facilitates Qualitative
 - mit Survey alle fragen und dann die spannendsten noch einzeln befragen

3.) Filling the Gaps

4.) Static and Processual Features
 - vergleich über Jahre, da hilft eine Statistik

5.) Solving the problem of generality
 - Qualitative kann sehr generell sein

6.) Facilitation of Interpretation
 - Qualitative kann helfen quantitative zu interpretieren