Quantitative Research

Question 1

Why is business research needed?

Answer 1

Reflection on literature leads to open questions (gaps, inconsistencies)
Reflection on development of business and management practices (e.g.: employee motivation…)

Question 2

Quantitative vs. Qualitative

Answer 2

Quantitative: deduction (test hypothesis with collected data), large sample, objective and distances researcher, meaning derived from numbers, generalisable findings
Qualitative: induction (derive theories etc. from observations), smaller sample, subjective and involved researcher, meaning derived from words, particular findings

Question 3

Steps of Quantitative Research

Answer 3

1. Theory
2. Hypothesis
3. Research design
4. Operationalization
5. Population and Sampling
6. Pretest
7. Process data
8. Analyse data
9. Write up findings/conclusions

Question 4

Research question

Answer 4

precise description what the researcher wants to know

Guides: literature review, methodology, research design, preparation and analysis of data…

Question 5

Research design vs. research method

Answer 5

Design: plan how to answer research question –> framework for collection and analysis of data
Method: techniques of collecting data

Question 6

Survey

Answer 6

standardised collections of questions, allow collection of large amounts of quantitative data, analysis with statistical methods

Question 7

Operationalisation

Answer 7

Make something measurable
Directly observable variables: e.g.: number of people in a room
Indirectly observable: e.g.: satisfaction, motivation

–> indirectly observable is difficult to measure, we use multiple indicators (directly observable phenomena) to measure indirectly observable variables

Structure tree: Construct, Dimensions, Categories, Indicators

Question 8

Questions

Answer 8

• Open or closed, Filtering questions, control questions, ice-breaker, socio-demographic data…
• Sequence: From general to specific (Intro, Ince-breaker, general, specific, socio-demographics)
• Important questions in the middle, questions concerning same topic in the same block

Question 9

Scaling

Answer 9

• Nominal, ordinal, interval, ratio
• Likert scale –> metric
• Middle category? –> can reduce number of “I don’t know”, but eliminates possibility to consciously choose middle answer
• Scale effects: scales with different numbering or naming influence people’s responses

Question 10

Coding

Answer 10

• To analyse answers to items, they need to be recorded on a numeric scale (text difficult to analyse)
• For items without numerical scale, specific value is assigned to each answer

Question 11

Research methods

Answer 11

Structure observation
Interviews
Self-completion questionnaire
…

Question 12

Sampling

Answer 12

Population: set of elements of interest of a study
Sample: subset of population (should possibly be representative)

Probability sampling: randoms sample selection, can draw inferences about whole population (simple random, stratified, random, cluster, systematic)
Non-probability: no inferences possible, subjective judgement (snowball, convenient, positive…)

Sample size

• the more heterogeneous, the large sample size should be
• depends on kind of analysis (e.g.: min. 30 for normal distribution)
• large sample increases likelihood that it is more precise (lower sampling error)

Question 13

Pretesting

Answer 13

Investigate quality of the survey (mistakes, validity, reliability)
Classic: carried out in the field, protesters passive
In-house: carried out in-house or laboratory, active role
Without target person: theoretically or practically (expert ratings…)

Question 14

Data preparation

Answer 14

Plausibility check: data must be free of any errors

• Missing values: delete or keep, maybe separate analysis
• Measurement level: all variables coded correctly
• Label for variables
• Inversely coded: recoding into new variable

Question 15

Data analysis

Answer 15

Descriptive: central tendency, dispersion, tables, graphs
Inductive: correlations, regressions, cross tabs, hypothesis tests