Optimal designs for the measurement of consumer preferences..

Optimale Ontwerpen voor het Meten van Consumentenvoorkeuren Deze thesis handelt over het ontwerp van conjoint experimenten die gebru ikt worden om inzicht te verwerven in de afwegingen van consumenten bij het kiezen van producten en diensten. Marketing consultants en onderzoek ers voeren deze experimenten vaak uit om de voorkeuren voor toekomstige goederen te voorspellen. Op deze manier helpen ze bedrijven bij het lanc eren van innovatieve producten of diensten. Het complete proces vanaf he t verzamelen van gegevens met consumentenvoorkeuren tot het analyseren v an de gegevens en het nabootsen van de markt staat bekend als conjoint a nalyse. Conjoint analyse gaat uit van de veronderstelling dat een product of die nst kan ontbonden worden in een reeks van componenten of attributen die elk een bepaald niveau aannemen. Een goed wordt hierbij voorgesteld als een combinatie van niveaus voor elk van de attributen. Een wagen wordt b ijvoorbeeld gekenmerkt door de attributen prijs, transmissie, airbags, d eurvergrendeling en audiosysteem. Een mogelijk profiel of alternatief vo or een wagen is dan een wagen voor een prijs van 18.000, met manuele tr ansmissie, frontale en laterale airbags, automatische deurvergrendeling en radio en CD-speler. Door een aantal proefpersonen een reeks profielen voor te leggen en hen te bevragen naar de meest aantrekkelijke profiele n, kan met conjoint analyse het relatieve belang van elk attribuut en ni veau in de aankoopbeslissing bepaald worden. De waarde die respondenten hechten aan elk van de attribuutniveaus wordt weergegeven door zogenaamd e part-worths. Conjoint analyse is gebaseerd op het feit dat de part-w orths beter gemeten kunnen worden wanneer de attributen tezamen worden b eschouwd (in het Engels wordt dit vertaald als considered

Optimal designs for rating-based conjoint experiments.

The scope of conjoint experiments on which we focus embraces those experiments in which each of the respondents receives a different set of profiles to rate. Carefully designing these experiments involves determining how many and which profiles each respondent has to rate and how many respondents are needed. To that end, the set of profiles offered to a respondent is viewed as a separate block in the design and a respondent effect is incorporated in the model, representing the fact that profile ratings from the same respondent are correlated. Optimal conjoint designs are then obtained by means of an adapted version of the algorithm of Goos and Vandebroek (2004). For various instances, we compute the optimal conjoint designs and provide some practical recommendations.Conjoint analysis; D-Optimality; Design; Model; Optimal; Optimal block design; Rating-based conjoint experiments; Recommendations;

Comparing algorithms and criteria for designing Bayesian conjoint choice experiments.

The recent algorithm to find efficient conjoint choice designs, the RSC-algorithm developed by Sándor and Wedel (2001), uses Bayesian design methods that integrate the D-optimality criterion over a prior distribution of likely parameter values. Characteristic for this algorithm is that the designs satisfy the minimal level overlap property provided the starting design complies with it. Another, more embedded, algorithm in the literature, developed by Zwerina et al. (1996), involves an adaptation of the modified Fedorov exchange algorithm to the multinomial logit choice model. However, it does not take into account the uncertainty about the assumed parameter values. In this paper, we adjust the modified Fedorov choice algorithm in a Bayesian fashion and compare its designs to those produced by the RSC-algorithm. Additionally, we introduce a measure to investigate the utility balances of the designs. Besides the widely used D-optimality criterion, we also implement the A-, G- and V-optimality criteria and look for the criterion that is most suitable for prediction purposes and that offers the best quality in terms of computational effectiveness. The comparison study reveals that the Bayesian modified Fedorov choice algorithm provides more efficient designs than the RSC-algorithm and that the Dand V-optimality criteria are the best criteria for prediction, but the computation time with the V-optimality criterion is longer.A-Optimality; Algorithms; Bayesian design; Bayesian modified Fedorov choice algorithm; Choice; Conjoint choice experiments; Criteria; D-Optimality; Design; Discrete choice experiments; Distribution; Effectiveness; Fashion; G-optimality; Logit; Methods; Model; Multinomial logit; Predictive validity; Quality; Research; RSC-algorithm; Studies; Time; Uncertainty; V-optimality; Value;

Optimal two-level conjoint designs for large numbers of attributes.

In this paper, we propose a simple strategy to construct D-, A-, G- and V-optimal two-level multi-attribute designs for rating-based conjoint studies. Our approach combines orthogonal designs and balanced or partially balanced incomplete block designs. In order not to overload respondents with complicated tasks, the designs hold one or more attributes at a constant level. The designs are variance-balanced meaning that they yield an equal amount of information on each of the part-worths. Some examples are provided to illustrate the method.Balanced and partially balanced incomplete block designs; D-,A-,G- and V-optimality; Orthogonal designs; Two-level conjoint designs; Strategy; Design; Studies; Order; Yield; Information;

Covid Economics: Who should get it first? Public preferences for distributing a COVID-19 vaccine.

Once a safe COVID-19 vaccine will become available, there will not be enough supply of it to vaccinate the entire population. Policy makers at national and international level are currently developing vaccine prioritization strategies. However, it is important that these strategies have sufficient levels of public support. We conducted a ranking exercise and a discrete choice experiment on a representative sample of 2,000 Belgians in order to elicit their preferences regarding how to distribute the COVID-19 vaccine across the population. We identified that three sub-groups had similarly high levels of support for access priority: the chronically ill, essential professions, and individuals likely to spread the virus the most. We identified two clusters of respondents. While both wanted to vaccinate essential professions, cluster one (N=1058) primarily wanted to target virus spreaders whereas cluster two (N=886) wanted to prioritize the chronically ill. Prioritizing those over 60 years of age was remarkably unpopular. Other strategies such as allocating the vaccine using a ‘lottery’, ‘first-come, first-served’ approach or willingness-to-pay received little support. Public opinion is a key variable for a successfully engaged COVID-19 policy. A strategy simultaneously prioritizing medical risk groups, essential professions and spreaders seems to be most in line with societal preferences. When asked to choose, people agree to vaccinate essential professions but disagree whether to prioritise people with high-medical risk or virus spreaders

VoxEU column: Public preferences for prioritising a COVID-19 vaccine

With the news of promising Covid-19 vaccines on the horizon comes a new challenge. The initial supply will not be sufficient to vaccinate everyone and choices will need to made over distribution. This column presents the results of an experiment in Belgium investigating people’s preferences regarding the distribution of a scarce vaccine. There was no one single strategy that was considered best by a large majority, but three strategies were ranked first by between 20-30% of respondents: prioritising essential workers, the chronically ill, and older people. Libertarian-inspired approaches (such as highest willingness-to-pay or ‘first-come, first served’) and a strict egalitarian approach (such as a lottery) were clearly the least preferred options

No such thing as a free-rider? Understanding multicountry drivers of childhood and adult vaccination

Background Increased vaccine hesitancy and refusal negatively affects vaccine uptake leading to vaccine preventable disease reemergence. We aimed to quantify the relative importance of characteristics people consider when making vaccine decisions for themselves, or for their child, with specific attention for underlying motives arising from context, such as required effort (accessibility) and opportunism (free riding on herd immunity). Methods We documented attitudes towards vaccination and performed a discrete choice experiment in 4802 respondents in The United Kingdom, France and Belgium eliciting preferences for six attributes: (1) vaccine effectiveness, (2) vaccine preventable disease burden, (3) vaccine accessibility in terms of co-payment, vaccinator and administrative requirements, (4) frequency of mild vaccine-related side-effects, (5) vaccination coverage in the country’s population and (6) local vaccination coverage in personal networks. We distinguished adults deciding on vaccination for themselves (‘oneself’ group) from parents deciding for their youngest child (‘child’ group). Results While all six attributes were found to be significant, vaccine effectiveness and accessibility stand out in all (sub)samples, followed by vaccine preventable disease burden. We confirmed that people attach more value to severity of disease compared to its frequency and discovered that peer influence dominates free-rider motives, especially for the vaccination of children. Conclusions These behavioral data are insightful for policy and are essential to parameterize dynamic vaccination behavior in simulation models. In contrast to what most game theoretical models assume, social norms dominate free-rider incentives. Therefore policy-makers and healthcare workers should actively communicate on high vaccination coverage, and draw attention to the effectiveness of vaccines, while optimizing their practical accessibility

The Impact of Remittances on Saving Behaviour and Expenditure Patterns in Vietnam

We examine the effects of receiving remittances on household saving behaviour and expenditure patterns in Vietnam. We consider the amount of saving, the saving rate, and the share of expenditure, as well as per capita expenditure on education, health, assets, house repairs, food, non-food, and utilities. We apply propensity score matching to data from the Vietnam Household Living Standard Survey (VHLSS) of 2012. We find that remittances have a positive impact on household savings and increase both the amount of saving and the saving rate. As far as expenditure patterns are concerned, our results indicate that receiving households spend more on health, assets, and house repairs, and less on food. This finding suggests that households tend to use remittances productively, with receiving households increasing their investments in human and physical capital. For the economy as a whole, remittances can create more opportunities for the development of services provided by banks, financial institutions, hospitals and healthcare centres, and give incentives to the production of building materials and tangible assets