The objectives of this study were to obtain a deeper understanding of the donor behavior characteristics of young affluent individuals; and to ascertain whether young affluent women differed significantly from young affluent males in their approaches to philanthropy. Two hundred and seventeen investment bankers, accountants, and corporate lawyers, aged under 40 years, earning more than £50,000 annually and working in the City of London were questioned about their attitudes and behavior in relation to charitable giving. Significant differences emerged between the donor behavior characteristics of males and females. A conjoint analysis revealed that whereas men were more interested in donating to the arts sector in return for “social” rewards (invitations to gala events and black-tie dinners, for example), women had strong predilections to give to “people” charities and sought personal recognition from the charity to which they donated.

In the face of the discourse about the democratic deficit and declining public support for the European Union (EU), institutionalist scholars have examined the roles of institutions in EU decision making and in particular the implications of the empowered European Parliament. Almost in isolation from this literature, prior research on public attitudes toward the EU has largely adopted utilitarian, identity and informational accounts that focus on individual‐level attributes. By combining the insights from the institutional and behavioural literature, this article reports on a novel cross‐national conjoint experiment designed to investigate multidimensionality of public attitudes by taking into account the specific roles of institutions and distinct stages in EU decision making. Analysing data from a large‐scale experimental survey in 13 EU member states, the findings demonstrate how and to what extent the institutional design of EU decision making shapes public support. In particular, the study finds a general pattern of public consensus about preferred institutional reform regarding powers of proposal, adoption and voting among European citizens in different countries, but notable dissent about sanctioning powers. The results show that utilitarian and partisan considerations matter primarily for the sanctioning dimension in which many respondents in Austria, the Czech Republic, Denmark and Sweden prefer national courts to the Court of Justice of the EU.

Most charity organizations depend on contributions from the general public, but little research is conducted on donor preferences. Do donors have geographical, recipient, or thematic preferences? We designed a conjoint analysis experiment in which people rated development aid projects by donating money in dictator games. We find that our sample show strong age, gender, regional, and thematic preferences. Furthermore, we find significant differences between segments. The differences in donations are consistent with differences in donors’ attitudes toward development aid and their beliefs about differences in poverty and vulnerability of the recipients. The method here used for development projects can easily be adapted to elicit preferences for other kinds of projects that rely on gifts from private donors.

This paper analyzes how social venture capitalists evaluate the integrity of social entrepreneurs. Based on an experiment with 40 social venture capitalists and 40 students, we investigate how five attributes of the entrepreneur contribute to the assessment of integrity. These attributes are the entrepreneur’s personal experience, professional background, voluntary accountability efforts, reputation and awards/fellowships granted to the entrepreneur. Results indicate that social venture capitalists focus largely on voluntary accountability efforts of the entrepreneur and the entrepreneur’s reputation when judging integrity. For an overall positive judgment of integrity, it seems to be sufficient if either voluntary accountability efforts or reputation of the entrepreneur are high. By comparing social venture capitalists with students, we show that experience leads to a simpler decision model focusing on key attributes.

The study of subjective democratic legitimacy from a citizens’ perspective has become an important strand of research in political science. Echoing the well‐known distinction between ‘input‐oriented’ and ‘output‐oriented’ legitimacy, the scientific debate on this topic has coined two opposed views. Some scholars find that citizens have a strong and intrinsic preference for meaningful participation in collective decision making. But others argue, to the contrary, that citizens prefer ‘stealth democracy’ because they care mainly about the substance of decisions, but much less about the procedures leading to them. In this article, citizens’ preferences regarding democratic governance are explored, focusing on their evaluations of a public policy according to criteria related to various legitimacy dimensions, as well as on the (tense) relationship among them. Data from a population‐based conjoint experiment conducted in eight metropolitan areas in France, Germany, Switzerland and the United Kingdom is used. By analysing 5,000 respondents’ preferences for different governance arrangements, which were randomly varied with respect to their input, throughput and output quality as well as their scope of authority, light is shed on the relative importance of different aspects of democratic governance. It is found, first, that output evaluations are the most important driver for citizens’ choice of a governance arrangement; second, consistent positive effects of criteria of input and throughput legitimacy that operate largely independent of output evaluations can be discerned; and third, democratic input, but not democratic throughput, is considered somewhat more important when a governance body holds a high level of formal authority. These findings run counter to a central tenet of the ‘stealth democracy’ argument. While they indeed suggest that political actors and institutions can gain legitimacy primarily through the provision of ‘good output’, citizens’ demand for input and throughput do not seem to be conditioned by the quality of output as advocates of stealth democratic theory suggest. Democratic input and throughput remain important secondary features of democratic governance.

The boom in survey experiments in international relations has allowed researchers to make causal inferences on longstanding foreign policy debates such as democratic peace, and audience costs. However, most of these experiments rely on mass samples, whereas foreign policy is arguably more technocratically driven. We probe the validity of generalizing from mass to elite preferences by exploring preferences of ordinary U.S. citizens and foreign policy experts (employees of the U.S. Department of State) in two identical conjoint experiments on democratic peace. We find that experts are not only more opposed to military actions against other democracies than members of the public—but also that overall preferences about the matters of war and peace are stronger among foreign policy professionals.

The literature in political science considers (sometimes inaccurate) perceptions of immigrants as a factor in anti-immigration attitudes among natives, but much less is known about perceptions regarding immigrants from specific regions. In this paper, I explore Americans’ perceptions about immigrants from Africa, Asia, Europe, Latin America, and the Middle East. To measure these perceptions, I apply a conjoint experiment with a multinomial outcome, in which respondents are asked to categorize hypothetical immigrants as coming from one of the five regions. Results from a nationally diverse sample demonstrate that immigrants from all regions other than Europe are associated with speaking poor English. Immigrants from Latin America are also associated with welfare dependency and rule-breaking behavior, while the opposite is true for immigrants from Asia. These negative perceptions may at least partly explain opposition to non-European, and specifically Latin American, immigration in the United States.

Researchers in the field of conjoint analysis know the index-of-fit values worsen as the judgmental error of evaluation increases. This simulation study provides guidelines on the goodness of fit based on distribution of index-of-fit for different conjoint analysis designs. The study design included the following factors: number of profiles, number of attributes, algorithm used and judgmental model used. Critical values are provided for deciding the statistical significance of conjoint analysis results. Using these cumulative distributions, the power of the test used to reject the null hypothesis of random ranking is calculated. The test is found to be quite powerful except for the case of very small residual degrees of freedom.

Recent research reflects a growing awareness of the value of using structural equation models to analyze repeated measures data. However, such data, particularly in the presence of covariates, often lead to models that either fit the data poorly, are exceedingly general and hard to interpret, or are specified in a manner that is highly data dependent. This article introduces methods for developing parsimonious models for such data. The underlying technology uses reduced-rank representations of the variances, covariances and means of observed and latent variables. The value of this approach, which may be implemented using standard structural equation modeling software, is illustrated in an application study aimed at understanding heterogeneous consumer preferences. In this application, the parsimonious representations characterize systematic relationships among consumer demographics, attitudes and preferences that would otherwise be undetected. The result is a model that is parsimonious, illuminating, and fits the data well, while keeping data dependence to a minimum.

Societies are experiencing deep and intertwined structural changes that may unsettle perceptions European citizens have of their economic and employment security. In turn, such perceptions likely alter people’s political positions. For instance, those worried by labour market competition may prefer greater social protection to compensate for the accrued risk, or prefer more closed economies where external borders provide protection (or perceived protection). We develop expectations about how such distinct reactions can emerge from distinct labour-market risks of globalization, or automation, or migration. We test these expectations using a conjoint experiment in 13 European countries on European-level social policy. Results broadly corroborate our expectations on how different concerns about sources of labour market competition yield support for different features of European-level social policy.

Survey experiments are an important tool to measure policy preferences. Researchers often rely on the random assignment of policy attribute levels to estimate different types of average marginal effects. Yet, researchers are often interested in how respondents trade-off different policy dimensions. We use a conjoint experiment administered to more than 10,000 respondents in Germany, to study preferences over personal freedoms and public welfare during the COVID-19 crisis. Using a pre-registered structural model, we estimate policy ideal points and indifference curves to assess the conditions under which citizens are willing to sacrifice freedoms in the interest of public well-being. We document broad willingness to accept restrictions on rights alongside sharp heterogeneity with respect to vaccination status. The majority of citizens are vaccinated and strongly support limitations on freedoms in response to extreme conditions—especially, when they vaccinated themselves are exempted from these limitations. The unvaccinated minority prefers no restrictions on freedoms regardless of the severity of the pandemic. These policy packages also matter for reported trust in government, in opposite ways for vaccinated and unvaccinated citizens.

Conjoint analysis is widely used for estimating the effects of a large number of treatments on multidimensional decision-making. However, it is this substantive advantage that leads to a statistically undesirable property, multiple hypothesis testing. Existing applications of conjoint analysis except for a few do not correct for the number of hypotheses to be tested, and empirical guidance on the choice of multiple testing correction methods has not been provided. This paper first shows that even when none of the treatments has any effect, the standard analysis pipeline produces at least one statistically significant estimate of average marginal component effects in more than 90% of experimental trials. Then, we conduct a simulation study to compare three well-known methods for multiple testing correction, the Bonferroni correction, the Benjamini–Hochberg procedure, and the adaptive shrinkage (Ash). All three methods are more accurate in recovering the truth than the conventional analysis without correction. Moreover, the Ash method outperforms in avoiding false negatives, while reducing false positives similarly to the other methods. Finally, we show how conclusions drawn from empirical analysis may differ with and without correction by reanalyzing applications on public attitudes toward immigration and partner countries of trade agreements.

For the purposes of farm animal welfare assessment, Farm Assurance Schemes and enforcement of animal welfare legislation, a requirement arises for a unitary welfare score which may be the amalgamation of several animal welfare measures. In amalgamating measures, weighting to reflect the importance of the individual measures for animal welfare is desirable. A study is described in which conjoint analysis was used to collect and evaluate expert opinion to weight a number of welfare assessment measures for the importance of each to broiler welfare in UK husbandry systems. The statistically combined opinion of the experts consulted revealed the weighting factors of the welfare assessment measures selected, with respect to the importance for bird welfare, to be: 0.26 for mortality levels on the growing unit; 0.24 for the level of leg weakness; 0.16 for the level of hock burn; 0.14 for stocking density; 0.10 for enrichment provision; and, 0.10 for the level of emergency provision. Criteria for selection of welfare assessment measures for use in the field, and level of agreement between experts consulted for the study, are discussed. It is concluded that weightings of welfare assessment measures by expert opinion, using conjoint analysis, might be used in the construction of a welfare index for assessment of broiler welfare on-farm. Such an index should not be considered as a ‘gold standard’ for welfare measurement but as an evolving standard for welfare assessment, based on current knowledge.

A large range of variables can affect the welfare of the dairy cow, making it difficult to assess the overall ‘level of welfare’ of the individual animal. Two groups of individuals completed a questionnaire based upon the ‘five freedoms’: 26 respondents had expertise either in the field of dairy cow welfare or as practicing veterinary surgeons, and 30 were veterinary students in their penultimate year of study. Conjoint analysis was used to calculate the average importance scores (AIS) for 34 variables presented to the respondents as 52 ‘model cows’ in the form of grouped questions, phrases and pictures. Conjoint analysis identified the most important factors for each ‘freedom’: access to forage, body condition score, foot conformation, hock lesions, and the encouragement required for a dairy cow to walk into the parlour. There was a significant difference between the expert and student groups for seven out of 34 factors, which may be attributed to individual variation of opinion, knowledge, experience and expectation. The factors were ranked within each ‘freedom’ using the experts' AIS but it was not assumed that each freedom had equal ‘weight’; therefore, the factors within each freedom were compared only with factors within the same freedom. These scores produced a weighting scale, which was applied on-farm, in a preliminary exercise comparing ‘model’ and ‘perceived’ welfare scores.

Standard preference models in consumer research assume that people weigh and add all attributes of the available options to derive a decision, while there is growing evidence for the use of simplifying heuristics. Recently, a greedoid algorithm has been developed (Yee, Dahan, Hauser & Orlin, 2007; Kohli & Jedidi, 2007) to model lexicographic heuristics from preference data. We compare predictive accuracies of the greedoid approach and standard conjoint analysis in an online study with a rating and a ranking task. The lexicographic model derived from the greedoid algorithm was better at predicting ranking compared to rating data, but overall, it achieved lower predictive accuracy for hold-out data than the compensatory model estimated by conjoint analysis. However, a considerable minority of participants was better predicted by lexicographic strategies. We conclude that the new algorithm will not replace standard tools for analyzing preferences, but can boost the study of situational and individual differences in preferential choice processes.