Business Research Design Flashcards
Criticisms of Quantitative Research
- Items may not be understood or interpreted differently by respondents
- Difficult concepts such as motivation or job satisfaction are treated as if they are easily measurable
Characteristics of Qualitative Research
- Regarded by some as less valid and reliable
- Qualitative data are open to multiple interpretations
- Themes that emerge are verified with informants
- Focuses on how people act and why
Deciding on a Sampling Strategy for experimental and quasi-experimental research
- Representativeness
- Probability sampling
- The goal is to generalize to the population
- Uses large, random samples
Deciding on a Sampling Strategy for qualitative research
- Information-rich cases
- Non-probability sampling
- Maximum variation sampling
- The goal is to generate a deep understanding
- Uses smaller, purposeful samples
- Data saturation
Probability Sampling
Each member of the population has an equal chance to be selected to be part of the sample.
Types of probability sampling
- Random Sampling
- Systematic Sampling
- Stratified Random Sampling
- Cluster Sampling
Types of non-probability sampling
- Quota sampling
- Purposive sampling
- Snowball sampling
- Convenience sampling
What are data collection methods?
- Questionnaires
- Interviewing
- Observation
- Focus groups
- Unobtrusive measures
What are unobtrusive measures?
Measures that do not require the researcher’s presence
Why do we use unobtrusive measures?
- Interactive measures may lead to bias
- Data collection methods may have questionable validity and reliability
Why do we use monitoring technology?
To understand:
- Flow of customers
- Effect of store refits
- Dwell-time
- Nature of interactions between staff and customers and between customers
- Staff behaviour
- Staff productivity
What is Random Sampling?
- Taking a completely random sample of the population
- Used when it is believed that the population is relatively homogeneous with respect to the research questions of interest.
What is Stratified Random Sampling?
- A method for achieving a greater degree of representativeness and for reducing the degree of sampling error
- Consists of taking a random sample from various strata
- Used to avoid over-sampling and under-sampling
What are the advantages of using Stratified Random Sampling?
An advantage of stratified random sampling is that it increases the likelihood of key groups being in the sample while still ensuring an element of random selection.
What are the disadvantages of using Stratified Random Sampling?
The disadvantage is that very often the researcher will not have sufficient information on which to base the strata.