Preference Heterogeneity Research Articles

Job preferences of master public health candidates in Northeast China based on discrete choice experiments

BackgroundThe shortage of health workers in rural and remote areas is a key issue for global health systems, including China. Public health undertakings in Northeast China face the risk of a talent gap. In September 2023, the National Development and Reform Commission (NDRC) held a symposium on promoting the comprehensive revitalization of Northeast China in the New Era, proposing to support the comprehensive revitalization of Northeast China with high-quality population development, strengthen the development and utilization of human resources, and increase policy support for the revitalization of talent.MethodsThe questionnaire was designed by discrete choice experiments, and 1208 Public Health Master’s candidates from six universities in Northeast China were investigated online via the Powercx system network survey platform in April 2024. The mixed logit model was used to analyze the job preferences of Master Public Health candidates.ResultsAll 7 attributes included in the study had statistically significant effects on the job preferences of public health master’s degree candidates (P < 0.05). They tended to choose jobs with higher monthly income (12,000 CNY/month), located in cities with good working environments and with Bianzhi when seeking jobs. There is heterogeneity in job preference, and different preference characteristics are displayed in different subgroups.ConclusionThis study revealed that public health master’s degree candidates in Northeast China were more willing to choose jobs with higher monthly incomes, working places in cities and better working environments. The way to formulate a combination of policy packages is more attractive than improving a single aspect alone. Since the preferences of each subgroup are different, the preference characteristics of the target population should also be considered when formulating the policy package to meet the challenges of talent attraction and retention.

Assessing personalized molecular portraits underlying endothelial-to-mesenchymal transition within pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a progressive and rapidly fatal disease with an intricate etiology. Identifying biomarkers for early PAH lesions based on the exploration of subtle biological processes is significant for timely diagnosis and treatment. In the present study, nine distinct cell populations identified based on gene expression profiles revealed high heterogeneity in cell composition ratio, biological function, distribution preference, and communication patterns in PAH. Notably, compared to other cells, endothelial cells (ECs) showed prominent variation in multiple perspectives. Further analysis demonstrated the endothelial-to-mesenchymal transition (EndMT) in ECs and identified a subgroup exhibiting a contrasting phenotype. Based on these findings, a machine-learning integrated program consisting of nine learners was developed to create a PAH Endothelial-to-mesenchymal transition Signature (PETS). This study identified cell populations underlying EndMT and furnished a potential tool that might be valuable for PAH diagnosis and new precise therapies.

The implications of digital school quality information for neighbourhood and school segregation: Evidence from a natural experiment in Los Angeles

A digital information explosion has transformed cities’ residential and educational markets in ways that are still being uncovered. Although urban stratification scholars have increasingly scrutinised whether emerging digital platforms disrupt or reproduce longstanding segregation patterns, direct links between one theoretically important form of digital information – school quality data – and neighbourhood and school segregation are rarely drawn. To clarify these dynamics, we leverage an exogenous digital information shock, in which the Los Angeles Times’ website revealed measures of a particularly important school quality proxy – schools’ value-added effectiveness – for nearly all elementary schools in the Los Angeles Unified School District. Results suggest that although the information shock had no detectable effects on residential sorting or neighbourhood racial segregation, it did exert modest effects on school sorting – particularly for Latino and Asian students – albeit not in ways that materially diminished school racial segregation because the racial compositions of high- and low-value-added schools were broadly similar both before and after the information shock. We conclude that the urban stratification implications of digital information may be more nuanced than often appreciated, with effects operating through mechanisms beyond residential segregation and reflecting racial heterogeneity in constraints and preferences vis-à-vis specific types of information.

Impacts of a sustainable aviation fuel mandate on airline competition — Full-service carrier vs. low-cost carrier

The aviation industry has proposed the collective goal of achieving net-zero carbon emissions by 2050. In addition to the existing market-based methods (MBMs), the use of renewable energies, in particular, sustainable aviation fuel (SAF), could be one of the most promising means for achieving this long-term target. This paper investigates how an SAF mandate from the government can lead to heterogeneous impacts on two types of airlines, namely, full-service carriers (FSCs) and low-cost carriers (LCCs), that compete in the same markets. A game-theoretic economic model is constructed that accounts for the different service quality levels and cost structures (i.e., fuel efficiency) between FSCs and LCCs. Our analytical results suggest that the SAF mandate favors LCCs over FSCs. The share of SAF blended into fuel raises the airfares of both types of airlines while reducing the traffic and profit of FSCs. The impacts on the LCC traffic and profit depend on its fuel efficiency relative to that of FSC. When LCCs are sufficiently fuel efficient, the SAF mandate can increase their traffic and profit. The government subsidy on airline's SAF use is also analyzed, deriving the optimal subsidy levels for FSC and LCC respectively to achieve pareto-improvement in social welfare and consumer surplus. We also examine how air passengers’ environmental awareness affects the outcomes of SAF mandate implementation. Our economic model also accounts for passengers’ heterogeneous preferences in terms of service quality and price sensitivity.

Buyer Valuation of Angus Bull Attributes in Wisconsin

Abstract Hedonic analysis of Wisconsin Beef Improvement Association Bull Sale and Development Program data revealed buyer preferences for calving ease, growth, production weight, and carcass merit traits. Attributes like calving ease direct Expected Progeny Differences (EPD), average daily gain, birth to yearling gain EPD, and rib-eye area consistently ranked higher and significantly influenced the bull’s sale price. Further analysis using a 2-Class Finite Mixture Model indicated distinct groups of buyers in the region who prioritized measured bull attributes and others who did not, confirming heterogeneity in buyer preferences.

The Gender Investment Gap over the Life Cycle

Abstract Single women invest less in risky assets than do single men. This paper analyzes the determinants of the “gender investment gap” based on a structural life-cycle framework. The model can rationalize the gender investment gap without gender heterogeneity in preferences. Rather, lower deterministic income and larger household sizes shift the composition of single women toward poorer households that invest less risky (composition effect). Additionally, future outcomes of both variables (which cannot easily be controlled for in regressions) make single women more vulnerable to financial shocks and decrease their optimal equity share even conditional on state variables (policy effect). (JEL E21, G11, G50, J16)

The expectations humans have of a pleasurable sensation asymmetrically shape neuronal responses and subjective experiences to hot sauce.

Expectations shape our perception, profoundly influencing how we interpret the world. Positive expectations about sensory stimuli can alleviate distress and reduce pain (e.g., placebo effect), while negative expectations may heighten anxiety and exacerbate pain (e.g., nocebo effect). To investigate the impact of the (an)hedonic aspect of expectations on subjective experiences, we measured neurobehavioral responses to the taste of hot sauce among participants with heterogeneous taste preferences. By identifying participants who "liked" versus those who strongly "disliked" spicy flavors and by providing contextual cues about the spiciness of the sauce to be tasted, we dissociated the effects of positive and negative expectations from sensory stimuli (i.e., visual and gustatory stimuli), which were the same across all participants. Our results indicate that positive expectations lead to modulations in the intensity of subjective experience. These modulations were accompanied by increased activity in brain regions previously linked to information integration and the placebo effect, including the anterior insula, dorsolateral prefrontal cortex, and dorsal anterior cingulate cortex, as well as a predefined "pleasure signature." In contrast, negative expectations decreased hedonic experience and increased neural activity in the previously validated "Neurological Pain Signature" network. These findings demonstrate that hedonic aspects of one's expectations asymmetrically shape how the brain processes sensory input and associated behavioral reports of one's subjective experiences of intensity, pleasure, and pain. Our results suggest a dissociable impact of hedonic information: positive expectations facilitate higher-level information integration and reward processing, while negative expectations prime lower-level nociceptive and affective processes. This study demonstrates the powerful role of hedonic expectations in shaping subjective reality and suggests potential avenues for consumer and therapeutic interventions targeting expectation-driven neural processes.

Modelling the complementarity and flexibility between different shared modes available in smart electric mobility hubs (eHUBS)

eHUBS are physical locations that integrate two or more electric shared mobility modes. As they provide transport users easier access to a wide range of transport modes, multimodal behaviour is expected to be more common. However, this issue has not been addressed in previous stated preference studies on mode choices involving innovative transport modes. In this study, multimodal behaviour is explicitly addressed both in measurement and in modelling by adopting the multiple discrete–continuous (MDC) modelling framework in contrast to discrete choice models. Instead of asking transport users to indicate the most preferred alternative, they were allowed to choose more than one alternative by allocating trips between several modes. This study aims to answer two questions: 1) whether there is complementarity between the multiple shared modes offered in eHUBS and 2) how would transport users adapt when one of the shared modes that they plan to use becomes unavailable. Using stated mode choice data of non-commuting trips from transport users whose current mode is driving a private car in Manchester, UK, several models under the MDC framework were estimated including Multiple Discrete-Continuous Extreme Value (MDCEV) model, mixed MDCEV model, and the extended Multiple Discrete Continuous (eMDC) model. The results show that there is complementarity between shared electric vehicle (EV) and electric bike (e-bike) offered in the eHUBS. In addition, the research show that the flexibility between those two shared modes is stronger than assumed in the MDCEV model, and common preference heterogeneity cannot fully account for this phenomenon.

Residents' perceptions of what makes feedback valuable in workplace-based learning: A discrete choice experiment.

Research on feedback has shifted emphasis away from its 'delivery' to consideration of the interaction between individual learners and their 'feedback provider'. The complexity inherent in determining whether feedback is perceived as valuable by learners, however, can quickly overwhelm educators if every interaction must be considered completely idiosyncratic. We, therefore, require a better understanding of variability in the ways in which feedback is perceived. To that end, we ran a discrete choice experiment aimed at determining residents' preferences and whether discernible patterns exist across learners regarding factors that influence perceptions of feedback's learning value. We performed a discrete choice experiment in which respondents were asked to read a clinical case and select repetitively between two feedback scenarios that differed according to six attributes identified from the literature as influencing feedback credibility: Dialogue, Focus, Relationship, Situation, Source and Valence. By systematically varying the levels of each attribute contained in the scenarios and asking residents to choose which from each pair they deemed more valuable for learning, a mixed logit model and latent class analysis could be applied to determine learners' feedback preferences and whether clusters of preference exist. Ninety-five elderly care medicine residents in the Netherlands completed the questionnaire. Their responses indicated that Valence, Dialogue, Relationship and Focus each accounted for about 20% of their preferences regarding the type of feedback perceived to offer the most learning value. Source and Situation were less influential, each accounting for 11% of the choices made. A latent class model with three clusters of respondents best accounted for the heterogeneity in feedback preferences. A total of 62% of respondents could be assigned to one of the three profiles with at least 80% probability. None of the respondents' characteristics (seniority, residency programme nor sex) were related to the feedback preference profile. Our findings suggest that 'how' feedback is provided has a greater influence on perceived learning value than who provides it. That said, variability exists in resident perceptions with no evidence (as yet) of factors that predict individual preferences. As such, tailoring to the needs and reactions of individual learners is likely to require open and ongoing conversations, and we recommend using the learner profiles generated through this study as a starting point because they provide classifications that could facilitate effective connections for the majority of residents.

Nurses' preferences for working in Uber-style ‘Internet plus’ nursing services: A discrete choice experiment

BackgroundChina's ‘Internet Plus’ nursing services, which are Uber-style home care services with an ‘online application, offline service’ approach, have been evolving over the past five years. Registered nurses' preference for these Uber-style Internet Plus nursing services are crucial for improving human resource management and service efficiency, yet research in this area remains scarce. ObjectiveThis study aimed to explore registered nurses' preferences for Uber-style Internet Plus nursing services and provide optimization recommendations from a supply-side perspective. DesignA cross-sectional study utilising a discrete choice experiment. Setting(s)Two public tertiary hospitals located in Tianjin, China, which have implemented Internet Plus nursing services. Participants211 registered nurses who participated in Internet Plus nursing services. MethodsThe survey was conducted anonymously using an online survey platform. Respondents were presented with choices between two alternatives, based on five key attributes: income, safety and security, patient and family cooperation, commute time, and service type. Mixed logit models estimated the stated preferences for attributes. Relative importance scores, willingness-to-pay estimates, and simulations of service-type uptake rates were calculated. Subgroup analysis and seemingly unrelated regression estimation were performed to examine heterogeneity in preferences. ResultsA total of 3202 choice observations were generated. When sorted by the strength of preference, the five attributes related to registered nurses' choice of Uber-style Internet Plus nursing services, measured by their relative importance scores, are as follows: safety and security (30.89 %), income (27.41 %), patient and family cooperation (18.47 %), service type (11.96 %), and commuting time (11.27 %). Elevating safety and security from low to high levels has the same utility as a 31.81 % increase in monthly income, equivalent to 2586.14 yuan. Subgroup analysis showed that senior nurses place more value on safety and security than junior nurses (β = 1.421 vs.β = 0.725; P = 0.011), and unmarried nurses had a stronger preference for family and caregiver cooperation (β = 1.105 vs.β = 0.314; P = 0.023). ConclusionsThe strength and heterogeneity of registered nurses' preferences should be highlighted in the dispatch algorithms model of Uber-style Internet Plus nursing services, thereby enhancing the efficiency and humanity of Uber-style Internet Plus nursing services. Tweetable abstractRegistered nurses prioritise safety and security, acknowledging heterogeneous preferences in Uber-style Internet Plus nursing services.

Seal of approval: Public preferences for the conservation of endangered Saimaa ringed seal

In species conservation, various options for conservation measures typically exist, yet their implementation may lead to conflicts among different population groups. Heterogenous preferences toward conservation measures often stem from the utilization of natural resources, whether for livelihood or recreational purposes. This study, focusing on the Saimaa ringed seal, a symbol of nature conservation in Finland, examines both population size and conservation measures. We distinguish the stated preferences between recreational visitors to Lake Saimaa, fishers at the lake, and individuals residing in other parts of Finland without direct use of the lake. To measure preferences, we utilize a choice experiment that incorporates both population size and the most promising conservation measures as attributes. The findings reveal significant variations in willingness-to-pay estimates between visitors and non-visitors, as well as between fishers and non-fishers. Interestingly, all population groups expressed a preference for a moderate increase in the seal population and a fair extension of conservation measures, rather than opting for a robust extension of measures. This insight emphasizes the importance of considering diverse stakeholder perspectives when designing and implementing species conservation strategies.

Preferences for pre-exposure prophylaxis delivery via online pharmacy among potential users in Kenya: a discrete choice experiment.

Oral pre-exposure prophylaxis (PrEP) is highly effective, but coverage remains low in high HIV prevalence settings. Initiating and continuing PrEP remotely via online pharmacies is a promising strategy to expand PrEP uptake, but little is known about potential users' preferences. We conducted a discrete choice experiment (DCE) to assess preferences for online pharmacy PrEP services. We partnered with MYDAWA, an online pharmacy in Nairobi, Kenya. Eligibility criteria were: ≥18 years, not known HIV positive, interested in PrEP. The DCE contained four attributes: PrEP eligibility assessment (online self-assessed, guided), HIV test type (provider administered, oral HIV self-test [HIVST], blood-based HIVST), clinical consultation (remote, in-person) and user support options (text messages, phone/video call, email). Additionally, participants indicated whether they were willing to uptake their selected service. The survey was advertised on MYDAWA's website; interested participants met staff in-person at a convenient location to complete the survey from 1 June to 20 November 2022. We used conditional logit modelling with an interaction by current PrEP use to estimate overall preferences and latent class analysis (LCA) to assess preference heterogeneity. Overall, 772 participants completed the DCE; the mean age was 25 years and 54% were female. Most participants indicated a willingness to acquire online PrEP services, with particularly high demand among PrEP-naive individuals. Overall, participants preferred remote clinical consultation, HIV self-testing, online self-assessment and phone call user support. The LCA identified three subgroups: the "prefer online PrEP with remote components" group (60.3% of the sample) whose preferences aligned with the main analysis, the "prefer online PrEP with in-person components" group (20.7%), who preferred in-person consultation, provider-administered HIV testing, and guided assessment, and the "prefer remote PrEP (18.9%)" group who preferred online PrEP services only if they were remote. Online pharmacy PrEP is highly acceptable and may expand PrEP coverage to those interested in PrEP but not accessing services. Most participants valued privacy and autonomy, preferring HIVST and remote provider interactions. However, when needing support for questions regarding PrEP, participants preferred phone/SMS contact with a provider. One-fifth of participants preferred online PrEP with in-person components, suggesting that providing multiple options can increase uptake.

Perspectives and Preferences of People with Type 2 Diabetes for the Attributes of Weekly Insulin.

Daily insulin administration can be burdensome for people with type 2 diabetes (PwT2D) and can impact treatment adherence. This study investigated preferences for once-weekly, long-acting basal insulin for treatment of PwT2D. An online discrete-choice experiment was administered to PwT2D in the USA. Qualitative interviews informed the selection of six attributes: reduction in A1c level after 6months, amount of time spent in optimal blood sugar range each day, number of serious low blood sugar events, number of nighttime low blood sugar events, change in weight because of the insulin over 6months, and frequency of administration. Each participant completed eight questions offering a choice between two long-acting insulins; questions varied according to an experimental design. A fixed treatment choice question asked about preferences for daily versus weekly insulin, holding other treatment features constant. Data were analyzed using random-parameters logit models, and heterogeneity was explored through subgroup analyses. Four hundred sixty-six PwT2D completed the survey (mean age, 57; mean A1c, 7.5%; 59.0% female); 33.3% of these were currently on a basal/bolus regimen, 34.3% used basal only, and 32.4% were insulin naive. Respondents placed the most importance on avoiding a 10-pound weight change and equal importance on the largest change in the number of serious and nighttime low blood sugar events per year and achieving the longest time in range included in the choice questions. There was significant heterogeneity in preferences by experience: insulin-naive respondents had stronger preferences for scheduled and flexible weekly insulin over daily insulin; 67.6% preferred flexible weekly over daily insulin, all else being equal. PwT2D valued insulin efficacy and reducing treatment-related adverse events, with heterogeneity in the relative importance of administration frequency. All else being equal, respondents preferred weekly over daily basal insulin. These findings provide insights into the preferences of PwT2D considering weekly long-acting insulin.

Personalised electric vehicle charging stop planning through online estimators

AbstractIn this paper, we address the problem of finding charging stops while travelling in electric vehicles (EVs) using artificial intelligence (AI). Choosing a charging station is challenging, because drivers have very heterogeneous preferences in terms of how they trade off the features of various alternatives (for example, regarding the time spent driving, charging costs, waiting times at charging stations, and the facilities provided at the charging stations). The key problem here is eliciting the diverse preferences of drivers, assuming that these preferences are typically not fully known a priori, and then planning stops based on each driver’s preferences. Our approach to solving this problem is to develop an intelligent personal agent that learns preferences gradually over multiple interactions. This study proposes a new technique that utilises a small-scale discrete choice experiment as a method of interacting with the driver in order to minimise the cognitive burden on the driver. Using this method, drivers are presented with a variety of routes with possible combinations of charging stops depending on the agent’s latest belief about their preferences. In subsequent iterations, the personal agent will continue to learn and refine its belief about the driver’s preferences, suggesting more personalised routes that are closer to the driver’s preferences. Based on real preference data from EV drivers, we evaluate our novel algorithm and show that, after only a few queries, our method quickly converges to the optimal routes for EV drivers [This paper is an extended version of an ECAI workshop short paper (Shafipour Yourdshahi et al., in: ECAI 2023 workshops, Kraków, Poland, 2023)].

The effect of second screening on repeat viewing: Insights from large-scale mobile diary data

AbstractThis paper examines the effect of second screening, the common practice of using another digital device while watching a television show, on repeat show viewing. We leveraged large-scale individual-level data from mobile diaries of 1,702 US TV viewers on 2,755 prime time shows. We used causal forest analysis for estimation, focusing on the moderating role of viewing preferences and show loyalty, and captured heterogeneity in viewer preferences using latent-class segmentation. We found that overall, show-related second screening has a positive effect on the attitude toward the show, as well as on actual repeat viewing. Show-unrelated second screening diminishes the viewer’s attitude. These effects are especially pronounced in the heavy viewer segment and among infrequent show viewers. Interestingly, our analysis did not provide evidence that second screening harms actual repeat viewing, countering potential concerns of negative distraction effects.

An exploratory research on bioplastic use in Nigeria: employing a green nudge approach

Bioplastics serve as good alternatives to conventional plastics, but their production and adoption globally remain generally low. This paper sought to determine the consumer preference for bioplastics due to the urgent need for an invention on plastic pollution in Nigeria. This was achieved by employing green nudges on consumers' choice experiments on bioplastic products. The study used a sample size of 327 respondents employing the snowball sampling approach. We discovered that there was high preference heterogeneity among respondents probably due to cultural diversity and attitudinal differences. Moreover, respondents preferred to stick with their preferences instead of opting for a change in their decisions. This may have been because Nigerians are known to be brand loyalists. Our results showed that the Text treatment group thought that bioplastic labels were innovative and useful compared to the control group. This perception was probably because of the concise text on the advantages of bioplastics. We conclude that although respondents were exposed to various green nudges, there was little effect of the green nudges on their purchasing decisions. We recommend that further studies be carried out to understand why price effect was not effective in Nigeria against theory and as compared to developed countries.

Analysis of wheat traits that determine female farmers’ preferences for wheat varieties: Gender insight from southern tigray, ethiopia

BackgroundWheat productivity has been constrained by changing agroecological and socio-economic conditions, coupled with a lower uptake of new farm technologies. Gender difference is one major social category that needs systematic estimation to distinguish the adoption of technology and the preference between male and female farmers. Hence, this study analyzes wheat traits that determine female farmers’ preferences for wheat varieties in southern Tigray, Ethiopia.MethodsThe primary data was collected by using semi-structured interviews, focus group discussions, and key informant interviews from 169 female farmers who were selected by using a two-stage sampling procedure. This study used descriptive statistics and a multinomial logit model to estimate the wheat traits that determine the wheat variety preference of female farmers.ResultThe result obtained from descriptive statistics shows the existence of heterogeneity in trait preference of female farmers among bread wheat, durum wheat, and local wheat variety types. The result indicates that risk-averting traits were the most frequently selected traits for both wheat types. Furthermore, the result of multinomial logit model indicates that wheat variety traits such as yield difference, marketability, resistance to drought, and resistance to frost and disease significantly influenced female farmers’ choice of wheat variety to grow.ConclusionThis study aims to fill the current knowledge gaps and tackle the significant issues faced by wheat-growing female farmers by examining the wheat traits that influence the wheat variety choice of these farmers. The finding scrutinized that even though the female farmers’ choices of wheat variety traits were heterogeneous, the majority of their decisions on the choice of wheat variety were primarily guided by risk-averting and yield traits. This evidence provides significant insight for developing gender-sensitive variety traits in crop breeding programs. Moreover, the findings significantly help policymakers, input suppliers, breeding programs, and extension workers to become more gender-responsive, to increase the productivity of wheat-growing female farmers.

Exploring tourist preferences for local food: a Best-Worst Scaling analysis and market segmentation approach

PurposeLocal food impacts tourist satisfaction and drives the choice of a tourist destination. However, it is not clear which attributes of local food products drive tourists’ preferences. More specifically, little is known about potential segments in the tourist market. Acknowledging consumers’ divergent inclinations, we explore tourist preferences toward local food attributes through a market segmentation approach.Design/methodology/approachThis study uses the Best-Worst Scaling method to examine the preferences of 311 tourists for attributes of local food products that are known to affect their choices. We employ a Latent Class Analysis to identify market segments with distinct preferences.FindingsResults indicate that tourists prioritize taste, quality, authenticity, healthiness, connection to local culture and tradition and environmental friendliness over price, appearance, enhancement of local economy, availability and packaging. We further identify three segments: Sensory Seekers, Cultural Experiencers, and Price Conscious. The largest segment, Sensory Seekers, is driven by taste and quality attributes, while Cultural Experiencers prioritize connection to local culture and authenticity. The Price Conscious segment places a greater emphasis on price than the other segments. Cultural Experiencers demonstrate the highest willingness to pay for local food products.Practical implicationsThe positioning of local products should target Cultural Experiencers. Agri-firms and state agencies promoting a tourist destination internationally can also use the connection to local culture and authenticity in their marketing campaigns.Originality/valueOur research contributes to food marketing literature by showing which local food attributes drive tourist preferences. Moreover, we uncover unobservable heterogeneous preferences among tourists.

Heterogeneous effects of monetary and non-monetary job characteristics on job attractiveness in nursing

We apply a novel methodological approach described by Chernozhukov et al. (2018), to analyze preference heterogeneity regarding non-monetary job characteristics and trade-offs between wage and non-monetary job characteristics. Using this approach, we can describe preference heterogeneity more concise than with subgroup analysis. Analyzing data from a self-conducted factorial survey experiment on nurses, we find significant effect heterogeneity regarding non-monetary job characteristics and their trade-off with wages. We also find positive interaction effects between wage and other job characteristics. We further analyze which factors are associated with effect heterogeneity. Working hours and gender appear to be the main drivers of these effects. We also find differences regarding the sources of a nurse’s motivation to initially choose the nursing occupation. Differentiation of job characteristics (job offers) to fit different preferences can therefore be a more effective and efficient way to attract workers than a “one size fits all” solution.

Random Discounted Expected Utility

Abstract This paper introduces the random discounted expected utility (R-DEU) model, which we have developed as a means to deal with heterogeneous risk and time preferences. The R-DEU model provides an explicit linkage between preference and choice heterogeneity. We prove it has solid comparative statics, discuss its identification, and demonstrate its computational convenience. Finally, we use two distinct experimental datasets to illustrate the advantages of the R-DEU model over common alternatives for estimating heterogeneity in preferences across individuals.