Background: The outbreak of COVID-19 was followed by an unprecedented package of measures to protect public health. Over 150 countries mandated school closures to reduce the risk of transmission. Decisions on whether to close schools involve trade-offs between important effects on public health, learning outcomes, well-being of children, productivity of parents. Objectives: Investigate Peruvian citizens’ preferences for schools opening during a public-health crisis such as the COVID-19 pandemic in two scenarios: (i) when the threat from COVID-19 is low and schools are open; and, (ii) when the threat from COVID-19 is high and schools are closed. Methods: We conducted a Participatory Value Evaluation (PVE) from 22 September to 17 October 2022, on which 2007 respondents assessed which policy measures to implement in the two scenarios. (i) In Scenario 1 “Schools are open”, children go to school, teachers and parents go to their jobs, but children still experience learning deficits from previous school closures. (ii) In Scenario 2 “Schools are closed”, children cannot go to school and do not receive any formal teaching, leading to learning losses; many teachers must change careers; and, many parents have to stay at home to take care of their children and lose income. Respondents were shown a range of policy measures in each of the scenarios and received information about the effects of each measure on public health, children's well-being and learning loss. Results: We found that most respondents in Scenario 1 preferred mandatory vaccination for teachers and quarantine measures. In Scenario 2 we found that most respondents were positive towards reopening school policies. In both Scenarios respondents prioritized mandatory vaccination and quarantine measures over other mitigation measures. In Scenario 2, most respondents from the Highland region selected opening schools with 100% on-location teaching while hybrid teaching was mostly selected in the Coast region. Most respondents (82%) evaluated PVE as a good method to involve citizens in policy decision-making. Conclusions: Policies that focus on prevention (e.g. mandatory vaccination for teachers and quarantine measures) can count on substantial support in a scenario when schools are open. The strong preference for opening schools with a noticeable difference in the way classes are provided (e.g. teaching on location most preferred by respondents from the Highlands and hybrid teaching by respondents from the Coast) show the importance of introducing differentiated strategies among regions.

Objective: In many countries, the incidence of skin cancer is growing rapidly, resulting in a substantive health and economic burden. While the wide range of available skin cancer prevention policies may have large individual and societal benefits, many countries still lack a policy strategy, and little is known about public preferences for collective prevention policy measures. We elicited these preferences using a discrete choice experiment (DCE) in Austria, the Netherlands, and Spain to inform policy action. Methods: Respondents were asked to choose twelve times between two packages of different prevention policies. Each package was described by its estimated effectiveness and costs. Before and after the DCE, respondents were asked for their support for any policy action. We quota-sampled adult citizens in each of the countries from an online panel (N = 2,442). The choice data were analyzed using multinomial logit (MNL) and mixed multinomial logit (MMNL) models. Results: Almost all attributes significantly influenced respondents’ choices, with the tax attribute being most influential in each country. Among the six policy measures, information campaigns and a price reduction of sunscreen were the most preferred policy measures, and the prohibition of solar bed sales and solaria the least preferred. Preference structures were largely consistent across the countries. Finally, most respondents supported policy action, particularly after the DCE. Conclusions: Citizens in the three countries recommended their governments to take policy action against the increasing incidence of skin cancer. The results provide policymakers with directions for publicly supported policy action, which should be complemented with additional information on preference heterogeneity, citizens' argumentation, and policies’ relative (cost-)effectiveness. The suggestion that preferences for policy action adapted over the course of completing the DCE survey should be further examined.

Since the 1940’s, job evaluation methods are being used to establish the relative value of jobs within organizations in order to determine salaries. Job evaluation methods have been studied, but there has not been much systematic reflection on the research conducted so far. This scoping review of 199 articles demonstrates that topics changed over decades, starting with methodological questions in the 1940’s, reflecting a start-up period. Historic overviews on wage policies appeared in the 1960’s, and the topic of gender wage inequality in the 1980’s. Guidelines were published in the 1990’s. From 2000 onwards, the main topic was adapting job evaluation methods to specific contexts. Research declined since 2010. There was hardly any research on appending changes in job evaluation methods and criteria. Given the ever-changing nature of work and the upcoming demographic changes, we recommend to revive scientific research on job evaluation and propose an agenda with research questions.

Several studies examined what drives citizens’ support for COVID-19 measures, but no works have addressed how the effects of these drivers are distributed at the individual level. Yet, if significant differences in support are present but not accounted for, policymakers’ interpretations could lead to misleading decisions. In this study, we use XGBoost, a supervised machine learning model, combined with SHAP (Shapley Additive eXplanations) to identify the factors associated with differences in policy support for COVID-19 measures and how such differences are distributed across different citizens and measures. We use secondary data from a Participatory Value Evaluation (PVE) experiment, in which 1,888 Dutch citizens answered which COVID-19 measures should be imposed under four risk scenarios. We identified considerable heterogeneity in citizens’ support for different COVID-19 measures regarding different age groups, the weight given to citizens’ opinions and the perceived risk of getting sick of COVID-19. Data analysis methods employed in previous studies do not reveal such heterogeneity of policy support. Policymakers can use our results to tailor measures further to increase support for specific citizens/measures.

This study explores perceived accessibility specific to air transportation in the Dutch context through a focus group study. Five focus group sessions were held with a total of 24 participants with air travel experience within the past five years. Online focus groups were held during the period that the COVID-19 pandemic travel restrictions were in effect, specifically around 12 months after the travel restrictions were implemented globally. In terms of the importance of activities accessible by flight, we observe that travelers particularly attach importance to visiting family and relatives, while the importance attached to the business and recreational activities accessible by flight varies among participants. As far as the transport component of accessibility is concerned, we find that, in addition to conventional variables in air transportation research, such as cost and travel times, unconventional variables such as uncertainty during flight schedule disruptions or the mood of staff and other passengers contribute to perceived accessibility by air transportation. Based on the results, we further discuss characteristics specific to perceived accessibility by air transportation, directions for further qualitative and quantitative research regarding perceived accessibility by air transportation, and implications for policy and planning.

Participatory value evaluation (PVE) is a novel method aiming at the evaluation of projects from a societal perspective. It aims at establishing which investment projects or investment portfolios (with a portfolio containing multiple investment projects) are likely to be favored by the population, given a limited budget. The approach emulates the decision-making problem faced by policy-makers. The ultimate end of PVE is to evaluate and establish how individuals value attributes of public projects in order to construct social trade-offs between different attributes and investments projects. However, it is important to consider that when investment portfolios consist of more than one investment project, significant synergies (positive and negative) may exist among the projects. This paper proposes a new evaluation framework that allows addressing synergies among projects in the context of PVE, while also offering a highly flexible structure. The approach is tested making use of one synthetic and two real datasets. Results show that neglecting synergies among the utilities of the projects included in the chosen portfolio majorly reduces the model fit and biases the estimators.

Bert van Wee, professor in Transport Policy at Delft University of Technology, the Netherlands, faculty Technology, Policy and Management, is retiring. Given his large contributions to EJTIR as Editor-in-Chief, editorial board member, author and reviewer, this Editorial Note is dedicated to his work for EJTIR. Over 25 years, van Wee published 18 papers and 1 book review in EJTIR covering a wide range of topics from road pricing to urban rail transport, vehicle automation and port throughput. What his studies have in common is that they explore how transport policies affect land-use and travel behaviour, as well as the economic and wider societal impacts of those policies. Bert van Wee’s generalist view on the transport system is rare, but, given the rising complexity of the system, increasingly needed to indeed be able to address the future challenges.

Background: The stage of the pandemic significantly affects people’s preferences for (the societal impacts of) COVID-19 policies. No discrete choice experiments were conducted when the COVID-19 pandemic was in a transition phase. Objectives: This is the first study to empirically investigate how citizens weigh the key societal impacts of pandemic policies when the COVID-19 pandemic transitions into an endemic. Methods: We performed two discrete choice experiments among 2181 Dutch adults that included six attributes: COVID-19 deaths, physical health problems, mental health problems, financial problems, surgery delays and the degree to which individual liberties are restricted. We used latent class choice models to identify heterogeneous preferences for the impacts of COVID-19 measures across different groups of respondents. Results: A large majority of the participants in this study was willing to accept deaths to avoid that citizens experience physical complaints, mental health issues, financial problems and the postponement of surgeries. The willingness to tolerate COVID-19 deaths to avoid these societal impacts differed substantially between participants. When participants were provided with information about the stringency of COVID-19 measures, they assigned relatively less value to preventing the postponement of non-urgent surgeries for 1–3 months across all classes. Conclusions: Having gone through a pandemic, most Dutch citizens clearly prefer pandemic policies that consider citizens’ financial situations, physical problems, mental health problems and individual liberties, alongside the effects on excess mortality and pressure on healthcare.

The need for engaging citizens in climate policymaking is increasingly recognised. Despite indications that the form of expert involvement can strongly influence participatory processes, this remains scarcely researched. We analysed two unique and contrasting cases of citizen engagement in national climate mitigation policy: (1) the Irish Citizens’ Assembly (ICA), the first national climate assembly involving live expert presentations and face-to-face deliberations; and (2) the Participatory Value Evaluation (PVE) on Dutch climate policymaking, where more than 10,000 citizens compared policy options in an online environment based on expert-based information on policy effects. Taking a dramaturgical approach, we found that the opening up and closing down of policy options and perspectives was influenced by the setting, staging and scripting of expertise. Apart from providing information on policy options, experts had significant roles in design choices and formulating recommendations, which shaped citizens’ deliberations and policy advice. In deliberative processes, citizens’ deliberations can be further influenced by putting experts in a privileged spot and emphasising their authority, whereas in the setting of an online tool, experts’ design choices may be masked by the fact-like presentation of expertise. Future research should further investigate the role of experts and expertise across a wider range of practices. Nevertheless, we conclude that the high degree of required technical knowledge in climate mitigation policy naturally implies strong expert involvement, which concomitantly steers the results. Alternatively, we may search to enhance citizens’ engagement in guiding climate policymakers by focusing on citizens’ normative perspectives.

This paper presents a micro-econometric framework to analyse choice data from participatory value evaluation (PVE) surveys. In a PVE survey respondents receive, similar to stated choice surveys, information on the social impacts of public sector projects before choosing the best policy portfolio according to their preferences. Respondents’ choices are limited by governmental and private budget constraints. The PVE data format is characterised by a mixture of discrete and continuous choice data. Building on recent literature of Kuhn–Tucker models, particularly the MDCEV model, a range of methodological and econometric contributions are provided facilitating model estimation and policy evaluation. We derive a set of closed form choice probabilities explaining the choice for the optimal portfolio with public projects, private consumption levels and whether to spend the public budget in full or not. The proposed policy evaluation framework is centred around the notion of social welfare maximisation. The parameter estimates are used to derive the optimal public sector budget and the corresponding portfolio maximising social welfare, but also to rank the set of feasible portfolios given a restricted budget, including sensitivity analyses. The proposed framework is illustrated using an empirical example on urban mobility investments in Amsterdam, The Netherlands.

Objective: Increasing healthcare expenditures require governments to make difficult prioritization decisions. Considering public preferences can help raise citizens’ support. Previous research has predominantly elicited preferences for the allocation of public resources towards specific treatments or patient groups and principles for resource allocation. This study contributes by examining public preferences for budget allocation over various healthcare purposes in the Netherlands. Methods: We conducted a Participatory Value Evaluation (PVE) choice experiment in which 1408 respondents were asked to allocate a hypothetical budget over eight healthcare purposes: general practice and other easily accessible healthcare, hospital care, elderly care, disability care, mental healthcare, preventive care by encouragement, preventive care by discouragement, and new and better medicines. A default expenditure was set for each healthcare purpose, based on current expenditures. Respondents could adjust these default expenditures using sliders and were presented with the implications of their adjustments on health and well-being outcomes, the economy, and the healthcare premium. As a constraint, the maximum increase in the mandatory healthcare premium for adult citizens was €600 per year. The data were analysed using descriptive statistics and a Latent Class Cluster Analysis (LCCA). Results: On average, respondents preferred to increase total expenditures on all healthcare purposes, but especially on elderly care, new and better medicines, and mental healthcare. Three preference clusters were identified. The largest cluster preferred modest increases in expenditures, the second a much higher increase of expenditures, and the smallest favouring a substantial reduction of the healthcare premium by decreasing the expenditure on all healthcare purposes. The analyses also demonstrated substantial preference heterogeneity between clusters for budget allocation over different healthcare purposes. Conclusions: The results of this choice experiment show that most citizens in the Netherlands support increasing healthcare expenditures. However, substantial heterogeneity was identified in preferences for healthcare purposes to prioritize. Considering these preferences may increase public support for prioritization decisions.

In this article, the affiliation details for author Jose Ignacio Hernandez were incorrectly given as ‘Center of Economics for Sustainable Development (CEDES), Faculty of Economics and Government, Universidad San Sebastian, Lientur 1457, Concepción, Chile ' but should have been ‘Center of Economics for Sustainable Development (CEDES), Faculty of Economics and Government, Universidad San Sebastian, Concepción, Chile. The affiliation ‘Transport and Logistics Group, Faculty of Technology, Policy and Management, Delft University of Technology, Delft, Netherlands’ for authors Jose Ignacio Hernandez and Niek Mouter was missing. The original article has been corrected.

Objective: Here we investigate public preferences for coronavirus disease 2019 (COVID-19) certificates in the Netherlands, and whether these preferences differ between subgroups in the population. Methods: A survey including a discrete choice experiment was administered to 1500 members of the adult population of the Netherlands. Each participant was asked to choose between hypothetical COVID-19 certificates that differed in seven attributes: the starting date, and whether the certificate allowed gathering with multiple people, shopping without appointment, visiting bars and restaurants, visiting cinemas and theatres, attending events, and practising indoor sports. Latent class models (LCMs) were used to determine the attribute relative importance and predicted acceptance rate of hypothetical certificates. Results: Three classes of preference patterns were identified in the LCM. One class a priori opposed a certificate (only two attributes influencing preferences), another class was relatively neutral and included all attributes in their decision making, and the final class was positive towards a certificate. Respondents aged > 65 years and those who plan to get vaccinated were more likely to belong to the latter two classes. Being allowed to shop without appointment and to visit bars and restaurants was most important to all respondents, increasing predicted acceptance rate by 12 percentage points. Conclusions: Preferences for introduction of a COVID-19 certificate are mixed. A certificate that allows for shopping without appointment and visiting bars and restaurants is likely to increase acceptance. The support of younger citizens and those who plan to get vaccinated seems most sensitive to the specific freedoms granted by a COVID-19 certificate.

We use Value Sensitive Design for the development of an ethical framework for autonomous systems in Defence in the Australian context. Two novel empirical data gathering methods are deployed for mining stakeholder's values, namely Group Decision Room (GDR) and Participatory Value Evaluation (PVE). GDR findings reveal a general concern for environmental values, geo-political and economic stability. A PVE based on these and other values is designed around an autonomous mine counter underwater vessel and an autonomous drone that drops bombs.

We propose three procedures based on association rules (AR) learning and random forests (RF) to support the specification of a portfolio choice model applied in data from complex choice experiment data, specifically a Participatory Value Evaluation (PVE) choice experiment. In a PVE choice experiment, respondents choose a combination of alternatives, subject to a resource constraint. We combine a methodological-iterative (MI) procedure with AR learning and RF models to support the specification of parameters of a portfolio choice model. Additionally, we use RF model predictions to contrast the validity of the behavioural assumptions of different specifications of the portfolio choice model. We use data of a PVE choice experiment conducted to elicit the preferences of Dutch citizens for lifting COVID-19 measures. Our results show model fit and interpretation improvements in the portfolio choice model, compared with conventional model specifications. Additionally, we provide guidelines on the use of outcomes from AR learning and RF models from a choice modelling perspective.

Participatory value evaluation (PVE) has recently been introduced in the field of health as a new method to elicit stated preferences for public policies. PVE is a method in which respondents in a choice experiment are presented with various policy options and their attributes, and are asked to compose their portfolio of preference given a public-resource constraint. This paper aims to illustrate PVE’s potential for informing healthcare decision making and to position it relative to established preference-elicitation methods. We first describe PVE and its theoretical background. Next, by means of a narrative review of the eight existing PVE applications within and outside the health domain, we illustrate the different implementations of the main features of the method. We then compare PVE to several established preference-elicitation methods in terms of the structure and nature of the choice tasks presented to respondents. The portfolio-based choice task in a PVE requires respondents to consider a set of policy alternatives in relation to each other and to make trade-offs subject to one or more constraints, which more closely resembles decision making by policymakers. When using a flexible budget constraint, respondents can trade-off their private income with public expenditures. Relative to other methods, a PVE may be cognitively more demanding and is less efficient; however, it seems a promising complementary method for the preference-based assessment of health policies. Further research into the feasibility and validity of the method is required before researchers and policymakers can fully appreciate the advantages and disadvantages of the PVE as a preference-elicitation method.

While several governmental and research efforts are set upon mobility-as-a-service (MaaS), most of them are driven by individual travel behavior and potential usage. However, considering only individuals’ preferences carries the risk of neglecting societal benefits going beyond individual travel behavior. This study addresses the valuation of different features of MaaS-services from a social desirability perspective as compared to social investments in biking infrastructure and in public transport, and aims at eliciting trade-offs between different features of such projects. This analysis is conducted on the basis of Participatory Value Evaluation (PVE). In PVE-experiments, individuals select their preferred portfolio of government projects given a constrained public budget and societal preferences for (the impacts of) government projects can be determined based on these choices. The results show that the population of Rotterdam exhibits a willingness to allocate public resources to all types of investment projects considered in the analysis. However, the willingness to allocate resources to bike infrastructure projects and public transport seems to be higher than the willingness to dedicate resources to MaaS subsidies. Within the different types of MaaS subsidies considered, subsidies aimed at sustainability exhibit a larger social valuation. Strong negative synergies among similar projects exist, signalizing that individuals prefer diversifying the use of public resources across different types of investment projects.

The COVID-19 pandemic has led to the introduction of transport-related policy measures worldwide. In this paper, we review the literature on factors that are important for the design of those measures, and their effects on safety, physical and mental health, economy and environment. We conclude that factors underlying the introduction of transport related measures are related to the broader discussion on COVID-19 measures (e.g. on social distancing). This makes it impossible to determine the independent influence of determinants aimed at transport on the effects (virus spread, economy, well-being). Furthermore, the effects of measures appear to differ strongly between countries. Important determinants for these effects are (1) socio-economic factors, (2) cultural factors, (3) political factors and (4) individual factors. In addition, the extent to which people can work at home appears to be very important for the introduction and effectiveness of COVID-19 measures. In the category of 'cultural factors', the degree to which people have a 'sense of civic responsibility' and trust in the government and institutions plays a major role in the compliance with advice and coercive measures. Furthermore, experiences with previous viruses appear to have made a positive contribution to COVID-19 policies that are successful at containing the virus. Finally, individual factors play a role in the compliance with COVID-19 measures. For example, a pro-social attitude is associated with better compliance. And: if people rate the effectiveness of such measures higher, they are more likely to act on them. The paper also provides recommendations for policy and further research.

Achieving energy efficiency in the built environment requires extensive efforts in the renovation and adaptation of housing stock. A promising design solution is the heat pump. While gas boiler systems are commonly used in Dutch non-profit housing stock, the share of dwellings with a heat pump grew from 1.6% in 2017 to 3.2% in 2021. However, building characteristics and the energy consumption of dwellings with a heat pump are unclear. Therefore, a dataset of 69,422 dwellings with different types of heat pumps has been examined and compared to dwellings with a traditional HR107 condensing gas boiler. This research reports average characteristics and the average actual energy consumption of dwellings with all-electric, hybrid and gas absorption heat pump systems. Dwellings with a heat pump system are on average of higher building quality, their gas consumption is lower and their electricity consumption is higher than dwellings with an HR107 condensing gas boiler. Detailed insight is provided for dwellings with different heat pump systems and for dwellings with different building characteristics. Further research to determine the energy performance of dwellings with specific heat pump configurations is recommended in light of the energy transition in the built environment.

Benchmarking is a method that can be used to measure progress and create awareness about the performance of organisations. Benchmarking the housing stock energy performance of Dutch housing associations can be used to measure and assess progress towards the decarbonisation of the housing stock. A new national climate agreement was signed in 2019, and in 2021 a new method to determine the theoretical energy performance of dwellings came into force in the Netherlands. To benchmark energy performance, a set of indicators is created that adequately represents the performance of Dutch housing associations according to the changed policies. A process involving key stakeholders is presented here to identify, assess and combine possible indicators. These were then integrated into four integrated models, which led to a final benchmark model. A model was chosen that consists of three indicators covering the energy performance of Dutch housing associations. The process and arguments that led to this final model are presented. While applicable within the Dutch context, the method and research results provide generalisable insights for the creation of energy performance benchmarks for building stocks.