Measurement and Modeling of Sustainable Food Choice and Purchasing Behavior: A Systematic Review of Methods and...

Area of Science:

• Consumer behavior research
• Sustainable food choices
• Behavioral economics

Background:

• Sustainable food behavior research struggles to predict actual purchasing decisions.
• Methodological fragmentation across psychometric, econometric, and behavioral approaches limits predictive validity.
• Existing studies often lack ecological validation against real-world purchasing data.

Purpose of the Study:

• To examine how methodological fragmentation affects the predictive validity of sustainable food choice and purchasing behavior.
• To diagnose the structural disarticulation between different research traditions.
• To propose solutions for improving the predictive accuracy of sustainable consumer behavior models.

Main Methods:

• Integrative systematic review of 62 empirical studies.
• Analysis of psychometric validation, discrete choice experiments (DCEs), trust and cognitive biases, and objective behavioral measurement.
• Comparison of self-report data with objective scanner data.

Main Results:

• Self-report studies show moderate attitude-behavior correlations (β ≈ 0.40-0.50), but this collapses to a null effect (β = 0.022) with objective scanner data.
• Psychometric instruments lack ecological validation, and DCEs remain isolated from psychological theory and real-world validation.
• No reviewed study integrated validated scales, DCEs, and objective behavioral data.

Conclusions:

• Methodological fragmentation is the primary cause of limited predictive validity in sustainable food behavior research.
• Integrating measurement paradigms, particularly through Hybrid Choice Models (HCM), is essential for ecologically valid and policy-relevant models.
• Future advances in predicting sustainable consumer behavior depend on unifying diverse research approaches.