Conjoint Analysis in Public Policy Preferences

Conjoint analysis is a powerful survey-experimental technique for eliciting the trade-offs citizens make when evaluating multi-attribute policy options. By presenting respondents with pairs of hypothetical policy profiles—each defined by a set of systematically varied attributes—researchers can isolate the relative importance of individual policy features, such as cost, fairness, effectiveness and target population. This approach has been widely adopted to inform the design of social, environmental and regulatory policies around the world. In recent years, methodological refinements have improved statistical power, addressed multiple-testing concerns and enhanced external validity. At the same time, applications have ranged from climate governance and rule-of-law measures to algorithmic public services, revealing how demographic characteristics, political ideology and contextual cues shape collective preferences. Conjoint analysis thus offers policymakers rigorous, granular insights into public support for complex interventions and helps bridge the gap between normative theory and empirical feasibility.

Research from Nature Portfolio

Recent studies have shown that multilateral framing of climate agreements significantly boosts public support. In two large-scale conjoint experiments conducted across diverse national samples, attributes such as the number of participating countries, anticipated policy efficacy and fairness norms were varied simultaneously. Findings reveal that participants are more inclined to endorse costly climate measures when they believe other states are also taking action, driven by enhanced perceptions of both effectiveness and distributive justice. These insights demonstrate the capacity of conjoint designs to disentangle complex policy trade-offs and inform strategies for securing broad-based cooperation on global challenges.

Conjoint Analysis in Public Policy Preferences publication trend

The graph below shows the total number of articles in conjoint analysis in public policy preferences across all publications each year (not limited to Nature Index journals).

Technical terms

Conjoint analysis: An experimental design technique that presents respondents with multi-attribute policy profiles to estimate the relative weight of each attribute in decision-making.

Attribute: A distinct characteristic or dimension of a policy profile that is systematically varied in a conjoint experiment.

Attribute level: A specific value or category assigned to an attribute within a policy profile.

Average marginal component effect (AMCE): The average change in the probability of selecting a profile associated with a shift in one attribute level, holding other attributes constant.

References

1. Multiple Hypothesis Testing in Conjoint Analysis. Political Analysis (2023).
2. Net versus relative impacts in public policy automation: a conjoint analysis of attitudes of Black Americans. AI & SOCIETY (2024).
3. How do citizens define and value the rule of law? A conjoint experiment in Germany and Poland. Journal of European Public Policy (2024).
4. Improving public support for climate action through multilateralism. Nature Communications (2022).