Our methods explained - Part 2: Quantitative experiments

Procedure

The approach to conducting these experiments is divided into the following steps:

1. Formulating questions and hypotheses: First, researchers establish a clear objective and develop theories that could explain specific behaviors or decision-making processes.
2. Experimental design: A structured experiment is then designed, focusing on variables, conditions and groups.
3. Data collection: Depending on the research question posed, researchers then collect the data. This can take the form of online surveys, experimental laboratory studies or field studies.
4. Data analysis: They then analyze the collected data to identify correlations, patterns and statistical significance. This includes the application of statistical tests and models to test the hypotheses.

Special features

Special features of quantitative behavioral economics experiments include:

• Controlled conditions: Experiments in controlled conditions minimize confounding factors and thus provide precise results.
• Manipulation of variables: By selectively adjusting variables, researchers can precisely examine their influence on users' behavior and decision-making processes.
• Objective data collection: By using quantitative measures and metrics, objective data is collected, which makes quantitative analysis possible in the first place.

Advantages and benefits

The advantages and benefits of quantitative behavioral economics experiments are manifold:

• Objective data: Objectively comprehensible data enables sound and meaningful analysis.
• Generalizability: Larger samples and statistical analysis allow research results to be extended to broader populations.
• Identification of behavioral patterns: These experiments allow experts to uncover specific decision-making processes and behavioral patterns.
• Validation of hypotheses: The scientific basis of the experiments ensures that the testing and validation of hypotheses is carried out according to precise standards.

Tools

A comprehensive survey tool is recommended for quantitative experiments. 

• LimeSurvey: LimeSurvey is also available free of charge and has many valuable features including conditional logic and multilingualism. 
• SurveyMonkey: SurveyMonkey also allows questions with conditional logic and has a powerful analysis tool. 
• Unipark: Unipark is primarily used in a scientific environment and therefore offers a wide range of sophisticated options. Further advantages: It meets the requirements of the GDPR, it offers an API for integration into other systems and software (e.g. CRM, CMS, ERP), as well as many customization options for visual design. 
• Qualtrics: Qualrics is a very comprehensive tool that can be customized very flexibly and offers extended functions for market research, such as A/B tests, as additional added value. 

Quellen

Kahneman, D., Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291.

Thaler, R. H., Sunstein, C. R. (2008). Nudge: Verbesserte Entscheidungen über Gesundheit, Wohlstand und Glück. Penguin Books.