E 43 Johan Brink, IIE 22 November Quantitative research Lecture

Agenda Chapter 6 Indicators Reliability & Validity Causality Chapter 7 Sampling, Replication Chapter 9 Questionnaires Chapter 10 Asking questions Open closed

The Quantitative research process 1.Theory 2.Hypothesis 3.Research design 4.Devise measurements 5.Select research site 6.Select research subjects/respondents 7.Collect data 8.Process data 9.Analyze data 10.Conclusions 11.Write up

Operationalization Concept (e.g. intelligence) Measure (e.g. IQ) Indicator (e.g. different test) Multiple indicators of a concept One doesn’t capture all individual interpretations Too narrow or too broad Different dimensions of a concept (such as culture, performance…)

Constructs Construct Item IQ

Reliability & validity Reliability – Stability over time – Internal reliability: the coherence of multiple indicators – Inter-observer consistency: effected by subjective judgment Validity – Face validity: getting the focus of attention – Concurrent and predictive validity – check with known criterion – Construct & convergent validity: valid measure of the concept, misinterpretations of constructs from theory. Triangulation with other methods

Causal studies Symmetrical – Both dependent on another Reciprocal – Reinforce each other Asymmetrical – Reinforce only one Mill’s method of agreement Mill’s method of difference ABCZ CBEZ CZ ABCZ ABCZ CZ

Unit of analysis The bits and pieces: ‘countries’, ‘legal system’, ‘payment systems’ Independent and dependent variables Individual or collective constructs – Culture

Types of variable Interval variables The distance between categories are identical A wide range of statistical techniques can be applied E.g. Temperature Ratio variables Classification, order. Distance and unique origin E.g.Age in years Ordinal variables Classification & order -but no equal distance or origin E.g. Doneness of meat (well –medium-rare) Nominal/categorical & Dichotomous variables No order, no distance & no origin Two categories – either or E.g. Gender (M/F)

Sampling Relevant sample Representative sample Sampling error – Under & over representation Non-response analysis Stratified and quota sampling Firm MarketingOperationsSales

Size – Time and cost – Depends on the variation (standard error) – Diminishing improvement in precision 68% of all sample means will be +/- 1* times standard error The 95% confidence interval: = Mean -/+ [1,96*standard error]

Generalizations Sample Population ?

Quantitative research CRITIQUE Phenomenological: – Do all individual interpret the world alike? How good is the operationalization? Constructivistic – Does it capture the real –daily behavior/social context- or just the constructed research situation

Questionnaires Pros Cheap and quick No interviewer effect Cons Short & clear Self explained No additional information – closed questions Response rate ok > 50% Cover letter /introduction – Why, who, how… – Confidentiality – Follow up Piloting Test Interpretations Do not include in the sample!

Research diaries Intrusive Attention gradually drops Expansive

Open & Closed questions Open - Reply as they wish + Their own terms + Unusual responses + Do not suggest any answer + Exploring topics + Generate closed questions -Time consuming -Have to be coded -Great effort from respondents Closed -Fixed alternatives + Easy process to analyze + Comparability of answers, limited # answers -No spontaneity -Force in the answers -Not exhaustive, eventually irritating

Types of questions Factual Personal information About others Informants (such as size of firm. Test knowledge about) Attitudes, Beliefs, values… Vignette Scenarios Filter questions

Likert scale Suitable for attitudes, beliefs & values Types: Yes -No 1-5, 1-10 Strongly agree – Undecided - Strongly disagree Do not mix type of questions Always keep you RQ in mind! What do you want to know? Is it open for interpretations? How would you answer it? General to specific No threatening questions early Avoid ambiguous terms: ‘often’, ‘management’… Avoid long questions Avoid negative questions: ‘not’ included Avoid double negotiations Avoid ‘and’ Avoid general questions Avoid leading questions: ‘do you agree Avoid technical terms