Stated Choice Experiment Research Articles

Fairness and the support of redistributive environmental policies

Exemptions from costly policy measures are frequently applied to alleviate financial burdens on specific market participants. Using a stated-choice experiment with around 6000 German household heads, we test how exemptions for low-income households and energy-intensive companies influence the political feasibility of additional cost for the promotion of renewable energies. We find that the policy support is substantially higher when low-income households are exempt rather than the industry. Introducing exemptions for low-income households on top of existing exemptions for the industry increases the acceptability of the policy. We show that the support for exemptions as one example of distributional policy design is associated with individual behavioral measures like inequality aversion and fairness perceptions.

Tax-Preferred Savings Vehicles: Can Financial Education Improve Asset Location Decisions?

Abstract In this study, we conduct a stated-choice experiment to analyze the decision to contribute to either a front- or back-loaded tax-preferred retirement savings account. Our experimental design includes a randomized financial education intervention that provides information on the tax implications of both types of account. Respondents who were exposed to the intervention have greater knowledge of these accounts and make contribution choices that increase their after-tax income. Using a well-defined benchmark, we show that on average, respondents who experienced the intervention increase their discounted welfare by about 4% of their contribution amount.

Coupling transport and electricity: How can vehicle-to-grid boost the attractiveness of carsharing?

Combining carsharing and vehicle-to-grid could result in synergies for decarbonizing transport and electricity systems. For carsharing operators, often experiencing financial difficulties, vehicle-to-grid service provision could generate additional revenues while supporting the integration of renewable energy. However, extant research has not yet studied customers’ interest in vehicle-to-grid carsharing. We therefore investigate whether and how vehicle-to-grid could improve the attractiveness of carsharing. Based on a stated-choice experiment in Germany and Switzerland, we compare the attractiveness of vehicle-to-grid, electric and conventional carsharing. We find that customers choose vehicle-to-grid over electric carsharing in 56.1% and over conventional carsharing in 74.2% of the choices. By estimating a multinomial, a mixed-logit, and a willingness-to-pay-space model, we find that costs show the highest relative importance for customers’ utilities despite the early adopter sample. Access and egress times as the second most important service characteristics, combined with free-floating as the preferred scheme, highlight the relevance of charging infrastructure. • Stated-choice experiment with vehicle-to-grid, electric, and conventional carsharing. • Vehicle-to-grid carsharing is more attractive to customers than current carsharing. • Costs, access and egress times are most important service attributes. • Operators and regulators need to thoroughly plan charging infrastructure.

The influence of latent lifestyle on acceptance of Mobility-as-a-Service (MaaS): A hierarchical latent variable and latent class approach

This paper aims to understand how people’s lifestyles are associated with their willingness to adopt a relatively new and innovative mobility solution, Mobility-as-a-Service (MaaS). The lifestyle is conceptualized as a combination of a mechanistic lifestyle manifested by an individual’s activity-travel patterns and a psychographic lifestyle depicted by an individual’s psychological traits. We propose a hierarchical latent variable and latent class model in which respondents are probabilistically allocated to one of the latent classes based upon mechanistic lifestyle, whereas psychographic lifestyle is incorporated in the model as values and personality traits exerting impact on attitudes which themselves are part of the utility function of MaaS subscription choice. The model is calibrated by the data emanated from a stated choice experiment and a lifestyle survey distributed among 1299 respondents in the Netherlands. The results confirm that psychographic lifestyles play a substantial role in people’s decision to subscribe to MaaS. Having positive attitudes towards multimodal travel increases the propensity to adopt MaaS, where the attitudes are moderated by values and personality traits significantly. Moreover, mechanistic lifestyles, having non car-oriented modality lifestyle in particular, enable to segment the respondents to two latent classes showing their preference heterogeneity.

Preference estimation under bounded rationality: Identification of attribute non-attendance in stated-choice data using a support vector machines approach

Stated-choice experiments have been useful in helping to make a number of operations management decisions. Many recent advances in this area have raised questions about estimating consumers’ preferences when they partially ignore the information provided in discrete choice experiments, a problem introduced as attribute non-attendance (ANA). This line of research explores the consequences of assuming that consumers consider all available information concerning attributes to evaluate product alternatives, when in fact, they might ignore some attributes completely. Diverse choice models, such as latent class models, have been developed to accommodate ANA using choice data. Due to the combinatorial nature of such an approach, researchers typically explore a limited number of specifications. Furthermore, although diverse modeling approaches have been proposed to accommodate ANA, no research has investigated the capability of these approaches to correctly identify ANA at the individual level. In this work, we propose the use of a machine learning approach based on support vector machines to identify ANA at the individual level and to predict consumer choices in conjoint experiments. We conduct an extensive simulation study varying the degree of non-attendance and the noise in the choice data to investigate the performance of the proposed approach. Our results with simulated data show good performance in terms of the identification of attended and non-attended attributes. We test our approach in two empirical applications and compare it to state-of-the-art benchmarks in the field. We demonstrate the usefulness and the alternative insights derived from our method.

Driver perceptions on taxi-sharing and dynamic pricing in taxi services: Evidence from Athens, Greece

The taxi industry has changed dramatically during the last decade, as ride-sourcing applications, ride-sharing and alternative pricing schemes have emerged, either as complementing or competitive services and strategies. After some years of familiarity with such trends, it is interesting to explore where the taxi industry stands with respect to possible service innovations. This paper explores behavioral patterns of drivers, focusing on issues such as their preferred way of conducting business, and their views on introducing taxi-sharing and dynamic pricing. Data collected from a face-to-face questionnaire survey in Athens, Greece are exploited, and appropriate econometric models are developed for the purposes of the study. The analysis shows that young and/or educated drivers, as well as those who are familiar with new technologies are more willing to accept innovations in taxi services. Results from a stated choice experiment show that on average 3.5 euros is the extra charge that the taxi market would accept to offer a taxi-sharing service. However, results reveal that the value of taxi-sharing varies across different groups of drivers. Overall, findings indicate that in the years to come, competition by other services, (e.g. ridesharing) will force the taxi industry to adopt new models of operation and pricing.

A Comparative Study of Urban Park Preferences in China and The Netherlands.

Urban parks play an important role in tackling several urban challenges such as air pollution, urban heat, physical inactivity, social isolation, and stress. In order to fully seize the benefits of urban parks, it is important that they are attractive for various groups of residents. While several studies have investigated residents’ preferences for urban park attributes, most of them have focused on a single geographical context. This study aimed to investigate differences in park preferences, specifically between Dutch and Chinese park users. We collected data in the Netherlands and China using an online stated choice experiment with videos of virtual parks. The data were analyzed with a random parameter mixed logit model to identify differences in preferences for park attributes between Chinese and Dutch citizens, controlling for personal characteristics. Although the results showed a general preference for parks with many trees, several differences were found between the Dutch and Chinese respondents. These differences concerned vegetation (composition of trees and flowers), the presence of benches and play facilities, and could probably be explained by differences in park use, values of nature, and landscape preferences. The findings of this study can be used as design guidelines by urban planners and landscape designers to design attractive and inclusive parks for different target groups.

Preferences for using the London Underground during the COVID-19 pandemic.

The COVID-19 pandemic has drastically impacted people’s travel behaviour and introduced uncertainty in the demand for public transport. To investigate user preferences for travel by London Underground during the pandemic, we conducted a stated choice experiment among its pre-pandemic users (N = 961). We analysed the collected data using multinomial and latent class logit models. Our discrete choice analysis provides two sets of results. First, we derive the crowding multiplier estimate of travel time valuation (i.e., the ratio of the value of travel time in uncrowded and crowded situations) for London underground users. The results indicate that travel time valuation of Underground users increases by 73% when it operates at technical capacity. Second, we estimate the sensitivity of the preference for the London Underground relative to the epidemic situation (confirmed new COVID-19 cases) and interventions (vaccination rates and mandatory face masks). The sensitivity analysis suggests that making face masks mandatory is a main driver for recovering the demand for the London underground. The latent class model reveals substantial preference heterogeneity. For instance, while the average effect of mandatory face masks is positive, the preferences of 30% of pre-pandemic users for travel by the Underground are negatively affected. The positive effect of mandatory face masks on the likelihood of taking the Underground is less pronounced among males with age below 40 years, and a monthly income below 10,000 GBP. The estimated preference sensitivities and crowding multipliers are relevant for supply–demand management in transit systems and the calibration of advanced epidemiological models.

A public transport-based crowdshipping concept as a sustainable last-mile solution: Assessing user preferences with a stated choice experiment

In this study, we analyse user preferences for a public transport based crowdshipping concept, where users carry parcels along on their ride. The concept offers potential economic, environmental and social benefits over other last-mile solutions. We set up a stated choice experiment in which respondents indicate whether they would be willing to bring a parcel along on their ride, while varying the number of parcels, their size, weight, the compensation and required extra time. Based on data from 524 public transport passengers in the Greater Copenhagen Area, we estimate a mixed logit model and find all main effects to be significant. Our results indicate that young(er) individuals, students and (to a lesser extent) employed and self-employed individuals are more likely to participate in the crowdshipping concept, while old(er) individuals (60 + ) are less willing to participate. Our findings further show that the marginal disutility of time spent retrieving and dropping off parcels is higher for old(er) respondents and individuals with high(er) income, while it is lower for individuals with a short-term education. Finally, we find the value of time to be slightly higher than the official Danish value for waiting time but lower than the value of travel time delay. Findings can inform the design of a crowdshipping system as well as related engagement efforts.

Do older homebuyers prefer dwellings with accessibility and adaptability features? Findings from an exploratory study

Demographic changes have prompted the development of ‘age-friendly’ housing design standards in several countries, but there has been limited exploration of whether older prospective homebuyers would prefer to purchase homes with accessible and adaptable features. This exploratory study used a stated choice experiment to explore whether prospective homebuyers in England aged 50 and over would prefer homes with accessibility and adaptability attributes. Respondents were significantly more likely to select dwellings with step-free access and adaptable bathrooms than properties without these features and were willing to pay significantly more to purchase them.

Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands.

With a few exceptions, public transport ridership around the world has been hit hard by the COVID-19 pandemic. Travellers are now likely to adapt their behaviour with a focus on factors that contribute to the risk of COVID-19 transmission. Given the unprecedented spatial and temporal scale of this crisis, these changes in behaviour may even be sustained after the pandemic. To evaluate travellers’ behaviour in public transport networks during these times and assess how they will respond to future changes in the pandemic, we conduct a stated choice experiment with train travellers in the Netherlands at the end of the first infection wave. We specifically assess behaviour related to three criteria affecting the risk of COVID-19 transmission: (i) crowding, (ii) exposure duration, and (iii) prevalent infection rate. Observed choices are analysed using a latent class choice model which reveals two, nearly equally sized latent traveller segments: ‘COVID Conscious’ and ‘Infection Indifferent’. The former has a significantly higher valuation of crowding, accepting, on average 8.75 min extra waiting time (average total travel time in the choice scenarios was about 40 min) to reduce one person on-board. Moreover, this class indicates a strong desire to sit without anybody in the neighbouring seat and is quite sensitive to changes in the prevalent infection rate. By contrast, the Infection Indifferent class has a value of crowding (1.04 waiting time minutes/person) that is only slightly higher than pre-pandemic estimates and is relatively unaffected by infection rates. We find that older and female travellers are more likely to be COVD Conscious while those reporting to use the trains more frequently during the pandemic tend to be Infection Indifferent. Further analysis also reveals differences between the two segments in attitudes towards the pandemic and self-reported rule-following behaviour. We believe that the behavioural insights from this study will not only contribute to better demand forecasting for service planning but will also inform public transport policy decisions aimed at curbing the shift to private modes.

Heterogeneity in job application decisions in two-adult households under social influence: A latent class mixed logit model

Work schedules with their start and end times substantially affect traffic flows, particularly during peak hours. Therefore, the study of work schedules is important to understand daily activity travel patterns. Particularly adults in households with children need to trade-off the number of working hours versus their time expenditure on child care, household tasks and leisure. Work schedule preferences are reflected in job application decisions in the sense that people are less likely to apply if the job profile is incongruent with their time use preferences. Job application decisions may also be influenced by attitudes of members of a household’s social network and peer groups. The aim of this study is to analyze unobserved heterogeneity and the effects of job properties and social influence on the decision to apply for a job in two-adult households with children. To that end, a stated choice experiment, in which respondents are asked whether they would apply for a job of a particular profile and a certain set of attitudes of members of their social network, is constructed and implemented. A latent class mixed logit model with two latent classes is applied to estimate the effects of work schedule attributes, social influence and socio-demographic characteristics on the probability of applying for a particular job. Results show that in both classes the effects of job attributes are more significant than social influence, and that the effects of the number of working hours and salary differ show considerable unobserved heterogeneity.

How to attract employees back to the office? A stated choice study on hybrid working preferences

It is expected that most office workers will work from home more often after COVID-19, but it remains unclear who is inclined to go back to the office and who is not when hybrid working becomes reality. Existing studies lack insights how (design) characteristics of the available office and home workspace influences workspace choice behavior. This survey-based stated choice experiment identifies two employee segments: one that intends to re-embrace the office and one that prefers to stay home a lot. Especially the expected crowdedness on the floor and availability of private spaces for concentration and meetings determined these employees’ choices. Also, the office workers segment contained relatively more male, highly educated, full-time workers with communication as an important component of their work and a short commute, while the home workers segment contained relatively more females, part-time employees, and administrative roles, plus employees with more individually focused work and a long commute.

Frying nemo? Experimental evidence on anthropomorphism, animal ethics, and food choice

Recently, it has been suggested that a shift towards diets with a lower carbon footprints, especially ones that emphasize the consumption of plants, is necessary to keep global heating below 2 °C. To address demand for animal-based products, we analyze if the effectiveness of anthropomorphic food labeling as a strategy for promoting plant-based diets is contingent on strong animal ethical beliefs. To this end, we conduct a stated choice experiment with Chilean university students (N = 1538). We manipulate the visual display of the main component of the dish attribute of the choice tasks, using anthropomorphic and non-anthropomorphic icons to frame the choice of meal options. Our results, which are based on a mixed logit model of the choice data and a linear regression analysis of its individual random parameters, suggest that displaying anthropomorphic icons reduces the likelihood of choosing beef or chicken over vegetables. However, the data provides insufficient evidence to claim an influence on the choice of fish over vegetables. The ethical intuitions that anthropomorphic animals evoke are related to a reduction in the consumption of beef and chicken but do not appear to affect preferences for fish. Our findings support the hypothesis that strong ethical concerns reinforce the effect of anthropomorphic nudges on beef consumption. The results for chicken and fish were inconclusive.

The influence of ergodicity on risk affinity of timed and non-timed respondents

Expected values are the metric most often used to judge human decision-making; when humans make decisions that do not optimize expected values, these decisions are considered irrational. However, while convenient, expected values do not necessarily describe the evolution of an individual after making a series of decisions. This dichotomy lies at the core of ergodicity breaking, where the expected value (ensemble average) differs from the temporal average of one individual. In this paper, we explore whether the intuition behind human decision-making optimizes for expected values or instead takes time growth rates into account. We do this using several stated choice experiments, where participants choose between two stochastic bets and try to optimize their capital. To evaluate the intuitive choice, we compare two groups, with and without perceived time pressure. We find a significant difference between the responses of the timed and the control group, depending on the dynamic of the choices. In an additive dynamic, where ergodicity is not broken, we observe no effect of time pressure on the decisions. In the non-ergodic, multiplicative setting, we find a significant difference between the two groups. The group that chooses under time pressure is more likely to make the choice that optimizes the experiment’s growth rate. The results of this experiment contradict the idea that people are irrational decision-makers when they do not optimize their expected value. The intuitive decisions deviate more from the expected value optimum in the non-ergodic part of our experiment and lead to more optimal decisions.

Response Times and Subjective Complexity of Food Choices: A Web-Based Experiment Across 3 Countries

Accurate collection of response times is one of the main advantages of web-administered stated choice experiments and it can be thought of as a behavioral indicator of cognitive effort. We use data from a food choice experiment administered across three countries and estimate a panel Mixed Multinomial Logit Model to obtain individual-specific utility weights. These are used to construct two utility-based measures of contextual choice complexity, which are combined with subjective measures of cognitive resources as well as indicators of opt-out selection. We first develop and then test hypothesized effects of complexity at the level of single choice task and choice sequence on response times. By using a log-linear random effects model with choice task response-time as dependent variable, we isolate these effects from other background variables. Results suggest that as our measures of complexity increase, so do response times and such effects are robust across the three countries. We argue that these results broadly support the validity of web-based choice surveys to measure food preference. We suggest that computers can help improve survey design by implementing algorithms to improve the overall efficiency of choice tasks design, for example, by using adaptive design algorithms that control cognitive challenges in accordance with the respondent’s predicted ability to tackle cognitive effort.

“I take the green one”: The choice of regional green electricity contracts in the light of regional and environmental identity

Most studies that focus on the choice of electricity contracts rely on the concept of utility-maximizing agents. However, since electricity is a low-involvement good and choosing an electricity contract is cognitively demanding, these studies may be misguided. Therefore, we investigate whether the choice of an electricity contract is instead driven by decision heuristics. Based on a stated choice experiment on electricity contracts, we find a willingness to pay for regional and green electricity that is causally affected by environmental and regional identity. Moreover, we find that about 40% of electricity contract choices are guided by the heuristic of choosing the greenest electricity mix. Decision heuristics based on regional contract characteristics occur less frequently. However, their use increases significantly when regional identity is salient. Thus, environmental and regional identity is a channel that can be used by policy makers and electricity providers for targeted marketing or information campaigns to increase demand for regional electricity products.

Consumer preferences for innovative and traditional last-mile parcel delivery

PurposeThe purpose of this research is to reveal consumer preferences towards innovative last-mile parcel delivery and more specifically unmanned aerial delivery drones, in comparison to traditional postal delivery (postie) and the recent rise of parcel lockers in Australia. The authors investigate competitive priorities and willingness to pay for key attributes of parcel delivery (mode, speed, method and time window), the role of contextual moderators such as parcel value and security and opportunities for logistics service providers in the growing e-commerce market.Design/methodology/approachA survey involving stated choice experiments has been conducted among 709 respondents in urban Australia. The authors estimated panel error component logit models, derived consumer priorities and deployed 576 Monte Carlo simulations to forecast potential delivery mode market shares.FindingsThe study results suggest that people prefer postie over drone delivery, all else equal, but that drone deliveries become competitive with large market shares if they live up to the premise that they can deliver faster and cheaper. Both drone and postie become less attractive relative to parcel lockers when there is no safe place to leave a parcel at a residence, highlighting the importance of situational context and infrastructure at the receiving end of last-mile delivery. The authors identified opportunities for chargeable add-on services, such as signature for postie and 2-h parcel deliveries for drones.Originality/valueThe authors offer timely and novel insights into consumers preferences towards aerial drone parcel deliveries compared to postie and lockers. Going beyond the extant engineering/operations research literature, the authors provide a starting point and add new dimensions/moderators for last-mile parcel delivery choice analysis and empirical evidence of market potential and competitive attributes of innovative versus traditional parcel delivery alternatives.

Supporting carbon taxes: The role of fairness

While the economic case for carbon pricing is compelling, public support for it remains low. Using a stated-choice experiment with a sample of 6000 German household heads, we examine how their fairness preferences influence support for carbon taxes under different revenue uses. We find that respondents who prefer green spending are more likely to support a carbon tax, but the support diminishes considerably for higher tax rates – in contrast to respondents who support social cushioning. When restricted to options for direct revenue redistribution, Germans prefer lump-sum payments over directing payments to the poorest or the most affected. Preferences over these options depend both on genuinely different concepts of fairness and economic circumstances. Our findings have implications for advancing carbon pricing, as its support can be increased substantially when designed according to citizens' fairness preferences.

Consumer preferences for parcel delivery methods

In the Netherlands, as in many other densely populated countries, home delivery is the dominant way of delivering online ordered parcels. This is mainly because big retail companies offer this delivery option for free. Due to the expansion of e-commerce, home delivery that typically makes use of diesel vans puts increasing pressure on logistics service providers, their employees, traffic, and the environment. Increased use of service points or parcel lockers could relieve some of this pressure, but these delivery alternatives are barely used by Dutch consumers. The goal of this paper is to better understand how consumers can be stimulated to use pick-up points and in particular parcel lockers. To achieve this goal, a stated choice experiment was conducted among Dutch e-commerce consumers, in which they made choices between home delivery, service point, and parcel locker alternatives that systematically varied in costs, delivery moment, and distance. The application of the model to predict choices under a number of scenarios makes clear that even a small increase in home delivery costs together with an expansion of parcel lockers that decreases the distance to the parcel lockers, could severely reduce the choice for home delivery: home delivery is predicted to reduce from 71% to only 7%. This suggests that there is potential for breaking through the dominance of home delivery.