Choice Set Research Articles

Fair subgraph selection for contagion containment (Brief Announcement)

We present a new class of problems where the goal is to select a “fair” subgraph H of a given graph G = (V,E), such that H decomposes into many small components. A subgraph Hc G is (P,d) fair if every vertex vϵ P has the same degree d in H, where PcV and d > 0 are input parameters.These problems arise when the goal is to allow individuals to equally participate in activities in such a way that the connected components within an interaction graph, which models potential interactions among people, are of the smallest possible size, so that the spread of the contagion, and the difficulty of contact tracing in case of infection, is minimized. Within a preference graph that models the set of preferred choices for each individual when selecting among available options of where to conduct any particular type of activity (e.g., which gym to attend), we seek to compute the fair subgraph of assignments of individuals to these options, so that the number of people in each connected component (“interaction community”) of the resulting subgraph is minimized, and everyone is given the same number of options for every activity.We show that the fair subgraph selection problem is NP-hard, even for very restricted versions. We then formulate the problem as an integer program, and give a polynomial time computable lower bound on the optimal solution.

Optimal pricing, production, and intelligentization policies for smart, connected products under two-level trade credit

The development of technologies such as the Internet of Things has transformed traditional physical products into smart connected products (SCPs) that combine hardware, sensors, data storage, microprocessors, software, and connectivity in myriad ways. SCPs raise a new set of strategic choices for creating value and pricing products, how relationships with business partners such as channels are redefined, and what role companies should play as industry boundaries are expanded. This study develops an inventory model that considers optimal pricing, production, and intelligent policies for SCPs. In this model, customer demand is assumed to increase as the selling price decreases and the effort to improve product intelligence (i.e., intelligent effort) increases. In addition, a two-level trade credit is included in the SCPs supply chain channel. The manufacturer often receives a permissible delay-in-payment (trade credit) from the supplier while also offering a delayed payment to end customers to attract more sales. Trade credit is particularly important for SCPs as it can act as a payment plan to reduce the product’s price barrier. This study aims to determine the optimal selling price, lot size, and level of intelligent effort while maximizing the manufacturer’s profit under a two-level trade credit. The optimal solution is clarified, numerical examples are provided, and a sensitivity analysis is performed to illustrate the theoretical results and solution approach. The results reveal that considering the level of intelligent effort as a decision can benefit the manufacturer. Notably, as the intelligent effort coefficient increases by 55%, the total profit increases by 65.8%.

Accurate Quality Elicitation in a Multi-attribute Choice Setting

Accurate Quality Elicitation in a Multi-attribute Choice Setting

Patient preferences do matter: a discrete choice experiment conducted with breast cancer patients in six European countries, with latent class analysis.

The evolution of breast cancer (BC) treatments has resulted in tailored therapies for the different types and stages of BC. Each treatment has a profile of benefits and adverse effects which are taken into consideration when planning a treatment pathway. This study examines whether patients' preferences are in line with what is considered important from decision makers viewpoint. An online discrete choice experiment was conducted in six European countries (France, Germany, Ireland, Poland, Spain, UK) with BC patients. Six attributes were included: overall survival (OS), hyperglycemia, rash, pain, functional well-being (FWB), and out-of-pocket payment (OOP). Sixteen choice sets with two hypothetical treatments and a "No treatment" option were presented. Data were analyzed with the use of heteroscedastic conditional, mixed logistic, and latent class models. Marginal rate of substitution (MRS) were estimated for OOP versus the rest of attributes to establish the ranking of preferences for each attribute. Two hundred and forty-seven patients with advanced or metastatic BC and 314 with early-stage BC responded. Forty-nine percent of patients were<44 years old and 65 percent had completed university education. The MRS of the analysis demonstrated that "severe pain" is the highest dis-preferred attribute level, followed by "severe impairment in FWB" and OS. Four classes of patients as "decision makers" were identified. This study suggests that there is heterogeneity in treatment preferences of BC patients depending on their sociodemographic and disease-related characteristics. In combination with clinical guidelines, patient preferences can support the selection and tailoring of treatment options.

Full-Information Selection Bias Correction for Discrete Choice Models with Observation-Conditional Regressors

We examine self-selection in polychotomous choice models that construct attribute values for each alternative conditioned on observed choices. Using observations made only when the alternative was chosen ignores private information which was a basis for the decision, biasing resulting estimates. We suggest a full-information maximum likelihood procedure that performs well at the extremes of the choice set in our sample, and use an “identification at infinity” weighting to identify levels. We apply the model to understanding fishing location choice in the economically significant Bering Sea pollock fishery, where expected catches at each location are constructed from harvests observed when that location is chosen.

The benefits of deciding now and not later: The influence of the timing between acquiring knowledge and deciding on decision confidence, omission neglect bias, and choice deferral

Abstract Consumers often spend time searching before making a purchasing decision to acquire knowledge about products. If the purchasing decision is delayed, recall of acquired knowledge is likely to be impaired. Because products in the marketplace are rarely described completely, consumers who take too long to decide may fail to notice the absence of information relevant to a purchasing decision and fall prey to a phenomenon called ‘omission neglect’, an inability to detect missing information and form extreme and confidently held judgments. Omission neglect may be corrected by acquiring knowledge about the target product before making the choice. In the present research, we examine consumer decisions in the context of choice sets described incompletely and presented either immediately or a week after the acquisition of relevant information about a target product. Specifically, we investigate how the timing between product knowledge acquisition and decision-making affects the detection of missing information, decision confidence, and choice deferral. Across three experiments, we find that, after acquiring knowledge, when consumers have their decision delayed, they are less able to detect missing information, feel more confident, and defer choices less.

Rule selection invariance as a robustness check in collective choice and nonparametric statistical settings

Rule selection invariance as a robustness check in collective choice and nonparametric statistical settings

Does the paradox of choice exist in theory? A behavioral search model and pareto-improving choice set reduction algorithm

Does the paradox of choice exist in theory? A behavioral search model and pareto-improving choice set reduction algorithm

Developing an Australian utility value set for MacNew-7D health states.

A new preference-based measure (MacNew-7D) has recently been developed to allow condition-specific data to be used to capture the quality of life in health economic evaluations in cardiology; however, a general population value set has not yet been developed. This study developed a population utility value set for the MacNew-7D heart disease-specific instrument. The discrete choice experiments (DCE) technique was chosen as the preference-elicitation method. The DCE asked respondents to compare two options and to state their preferences. The survey was conducted using an online panel of respondents, with quota sampling using age groups, sex and jurisdictions to achieve representativeness of the Australian population. The total design consisted of 200 choice sets, of which each respondent answered eight. Additionally, each respondent answered two quality control choice sets. The best-fitting models were selected on the basis of consistency, parsimony, and goodness of fit. In total, 1903 respondents were included in the analyses. The MacNew-7D utility value set ranged from -0.4456 to 1.000 for health states defined by the classification system. The best-fitting model retained all levels for five dimensions and collapsed one adjacent level for the other two dimensions. Findings were robust to sensitivity analyses related to the inclusion or exclusion of dominancy and repeat tasks. Findings indicated that the MacNew-7D utility value set is likely suitable for estimating quality-adjusted life years derived from the MacNew heart disease health-related quality-of-life questionnaire. This value set was derived from an Australian population-based sample and may not be generalisable to dissimilar populations.

Estimation of Cross Classified Value of Travel Time Using Binary Logit Model on Egyptian Roads

Objective: In this study, cross-classified categories of Value of Travel Time (VOT) are estimated using the binary logit model for the users of both public and private vehicles who have diverse income levels and go on different trips. The travelers’ income level has a large impact on their VOT and on their willingness to pay regarding other factors that impact the travelers’ choice of the most suitable means of transport for them. Methods: The research uses the combined stated and the revealed preference survey and applies the logistic regression analysis to estimate the categorized VOT on Egyptian roads. The data sets consist of 1123 respondents who were approached to collect information related to the socio-economic factors and the trips’ characteristics. Each respondent was requested to choose an alternative to each of the choice sets’ levels. All data sets were collected in light of the Binary Logit analysis and recorded concerning the socio-economic factors. A total of 33 models were developed to predict the VOT. Results: According to the given analysis, VOT for private car owners (32.5 LE/HR about 2.06 $/ HR) is higher than that for public transport users (18.3 LE/HR about 1.16 $/ HR) in Egypt. As for the diverse income level groups, a positive correlation is found between each traveler and his/her income. To clarify, the travelers’ VOT increases when their income levels improve. Conclusion: Concerning the purpose of the trip, the VOT reaches its peak for travelers who travel for the sake of work as their VOT is approximately 38.82 LE/HR, about 2.47$/HR compared to the other travelers who have different traveling purposes other than doing business.

Consumer preference and willingness to pay for low-residue vegetables: Evidence from discrete choice experiments in China

IntroductionThis study aims to investigate consumers' cognition, preference and willingness to pay (WTP) for celery with low pesticide residues, and to provide evidence from a consumer perspective for government food safety regulation.MethodA survey was conducted on the population over the age of 18 in 6 provinces of Shanghai, Guangdong, Sichuan, Hunan, Hebei and Heilongjiang in China, in order to improve the representativeness of sample. The study carried out a survey of respondents' cognitive attitudes towards low-residue vegetables, and applied a discrete choice model (DCE) to simulate different scenarios of consumers buying vegetables. The DCE included residue level, appearance, taste, and price and finally constructed 24 choice sets. Respondents' preference for low-residue celery and WTP were analyzed using a mixed logit model.ResultA total of 1292 respondents were surveyed. The model results showed that consumers had the highest positive preference for pesticide-free celery. For the Chinese consumers, price was the most important attribute, followed by the residue level, taste, and appearance. Consumer WTP for pesticide-free celery was11.17CNY/500g. Factors affecting consumer preferences were age, gender, income, education, whether they had children, or paid attention to pesticide residue in vegetables, and related reports of pesticide residue exceed the standard in vegetables.ConclusionOur study is more finely divided at the residue level, and the findings provide useful information for producers and policy makers.

Exploring women's preferences for attributes of long-acting reversible contraceptive (LARC) methods: A discrete choice experiment

There is low LARC uptake in Nigeria and not much is documented about Nigerian women's preferences for these products and how these preferences affect women's choices. Therefore, the purpose of this study is to provide empirical evidence on the decision-making behavior of Nigerian women regarding LARCs. Three hypothetical LARCs were presented. Informed by results obtained from the review of relevant literature and focus group discussion held with selected family planning services providers, the identified attributes were effect on weight, cost, LARC effectiveness and effect on bleeding patterns, each at three levels. A d-optimal design was used to construct nine choice sets. An additional choice set was included to conduct the test-retest stability test. The choice sets and other socio-demographic questions formed the discrete choice experiment questionnaire. A random sample of 150 eligible women was selected from women who enrolled and attended family planning clinics in public healthcare facilities in Ibadan, Nigeria through a three-stage sampling technique. Mixed logit modeling was used to obtain estimates of the parameters and willingness to pay (WTP) for each attribute was calculated. The test-retest stability result showed that 76.7% of the respondents responded in a consistent and rational manner. The women preferred LARCs that have no effect on their weights compared to LARCs that cause either slight weight loss or gain. Also, they preferred LARCs that offer 1/1000 level of effectiveness in a year. The most preferred attribute level, ‘women experience infrequent bleeding’, increases WTP by NGN 13,984.584 (USD 33.68) while the least preferred level, ‘women experience frequent/prolonged bleeding’, has a negative mean WTP (-NGN 19,598.378 (-USD 47.20)) indicating dispreference for the level. Furthermore, women derived higher utilities from very cheap LARCs. Evidence-based information on women's preferences regarding LARC usage would help policymakers in the deployment of strategies that would ensure that preferred LARCs are procured and made readily available to women.

Why people keep watching: neurophysiologic immersion during video consumption increases viewing time and influences behavior.

Streaming services provide people with a seemingly infinite set of entertainment choices. This large set of options makes the decision to view alternative content or stop consuming content altogether compelling. Yet, nearly all experimental studies of the attributes of video content and their ability to influence behavior require that participants view stimuli in their entirety. The present study measured neurophysiologic responses while participants viewed videos with the option to stop viewing without penalty in order to identify signals that capture the neural value of content. A post-video behavioral choice was included to reduce the likelihood that measured neurophysiologic responses were noise rather than signal. We found that a measure derived from neurophysiologic Immersion predicted how long participants would watch a video. Further, the time spent watching a video increased the likelihood that it influenced behavior. The analysis indicates that the neurologic value one receives helps explain why people continue to watch videos and why they are influenced by them.

Quantifying the benefits of the introduction of the hybrid electric vehicle

This study models demand and supply in the market for new automobiles to estimate the economic benefits generated by the introduction of the hybrid electric vehicle. We estimate our model using all new vehicle registrations in California along with detailed demographic data. Our counterfactual analysis reveals that the addition of hybrids to the consumer choice set generates gains in social surplus that peak at roughly $1.2 billion annually in 2007, but environmental benefits make up 0.2% of the net benefits. We find that 31% of the social surplus in 2008 can be attributed directly to the hybrid vehicles independently from gains in fuel efficiency, with the remaining 69% attributed to the gains in fuel efficiency. We further show that all income groups benefit from the introduction of the hybrids, with the top 50% of the income distribution receiving the most.

Assessing the Feasibility of Employing Transportation Utility Fee: Need to Overlay Landmark Court Decisions on State-Level Determinants

There is a growing interest nationwide in employing a transportation utility fee (TUF). The extant literature discusses ways to make TUF legally defensible by maintaining its fee-like features, so that it is not considered a tax. However, courts consider the context of state law while determining the legality of a TUF; hence, the need to consider the takeaways from landmark TUF-related court cases and state-specific determinants while designing a TUF program. The paper begins to fill this research gap by demonstrating how court decisions can be overlaid on state-specific determinants to identify a set of choices for levying TUF.

Patients' Preferences for Sodium-Glucose Cotransporter 2 Inhibitors and Glucagon-Like Peptide-1 Receptor Agonists.

To determine patients' preferences for sodium-glucose cotransporter 2 inhibitors (SGLT-2is) and glucagon-like peptide-1 receptor agonists (GLP-1RAs). A cross-sectional, web-based discrete choice experiment was conducted among US adults with type 2 diabetes mellitus (T2DM) in May 2021. Six attributes-the route and frequency of administration, the chance of reaching target HbA1c in six months, the percentage reduction in the risk of major adverse cardiovascular events (MACE), the chance of gastrointestinal side effects, the chance of genital infection, and out-of-pocket cost per month-were identified from literature review and consultation with patients and clinicians. A Bayesian efficient design was used to generate choice sets. Each choice set contained two hypothetical SGLT-2i and GLP-1 RA alternatives described by the attributes and an opt-out alternative. A total of 176 patients were asked to select the most preferred option from each choice set. Mixed logit (ML) and latent class (LC) models were developed. The conditional relative importance of each attribute was determined. The ML model showed the out-of-pocket cost had the highest conditional relative importance, followed by the chance of reaching the target HbA1c. The best LC model revealed two patient classes. All attributes were significantly important to the patients in both classes, except the chance of genital infection in class 2. Compared to the patients in class 2, the patients in class 1 were older (approximately 65 vs 56 years) and had a higher number of comorbidities (approximately three vs two). T2DM patients placed different preference weights or importance across SGLT-2i and GLP-1 RA attributes. Preference heterogeneity was found among patients with different ages and numbers of comorbidities.

PP32 Assessment Of Preferences For Treatment: A Discrete Choice Experiment Among Italian Patients With Prostate Cancer

IntroductionThe integrated patient-centered, evidence-based approach to care recognizes the role of patient preferences. A discrete choice experiment (DCE) was developed with the aim of identifying the preferences of men with prostate cancer in Italy regarding the different risk-benefit factors of various treatment options.MethodsThe DCE was developed with the support of prostate cancer patients and oncologists and was based on a targeted scoping review. The final DCE included 26 choice sets divided into two blocks. The first block focused on all prostate cancer patients (both metastatic and non-metastatic), while the second block aimed to assess preferences for patients with metastatic hormone-sensitive prostate cancer (mHSPC). Patients were asked to choose from ten attributes in the first block and six in the second block. The aim was to identify attributes and levels with a statistically significant impact on patient preferences. Preference estimates were calculated using a conditional logit regression model and the results were stratified by cancer stage (metastatic or non-metastatic) in the first block.ResultsA total of 202 patients (mean age 72 years) completed the DCE. In the first block, the most important attribute was quality of life (QoL), particularly for patients with metastatic cancer. The other three attributes found to be significant, in order of relevance to patients, were the risks of experiencing cognitive impairment, hematologic complications, and fatigue. For patients with mHSPC, QoL was the strongest determinant of preference. The risk of experiencing fatigue was also a relevant attribute, followed by skin irritation.ConclusionsThis study shows that the effect of treatment on QoL was the most important attribute for patients diagnosed with prostate cancer. Specific risk factors play a different role in the choice of treatment depending on cancer type, with the risk of experiencing fatigue being valued by all groups. Identifying and understanding patients’ preferences related to treatments for prostate cancer will help physicians identify the best treatment strategy.

The Money Chase: The Role of Racial Innuendo and Marketized Discourse in Courting Private Dollars

Background/Context: The business and philanthropic sectors have been a persistent force in shaping U.S. schools. Recently, they have used their resources to advance policies that embody newer principles of industry—reforms that suggest that competition, choice, and deregulation can spur improvement and effectiveness. This has most notably included deep investments in the proliferation of charter schools, surfacing questions as to the sector’s reliance on private dollars as well as the equitable and democratic impact of advancing this manifestation of neoliberal reform. Purpose/Objective/Research Question/Focus of Study: While scholars have elucidated the role of business and philanthropic funding in promoting charter schools, less is known about how the well-substantiated connections between charters and the private sector have been facilitated or how discourse—the ideas, representations, and argumentation conveyed in acts of communication—is mobilized to create a rationale for support. To date, research has typically examined the discourse and messaging intended for families navigating choice settings. Yet, how these depictions are crafted for donors, who typically inhabit positions of economic and social power and are critical actors in charter growth, remain comparatively less understood. Research Design: This study fills this empirical gap and investigates the tactics used to solicit donor investment by charter management organizations (CMOs). It uses a conceptual framework that synthesizes tenets from the research on neoliberal policy networks and the sociology of race to enable a multifaceted analysis of the discursive tactics used to secure donor support while attending to the often-nuanced ways in which race may be invoked in those efforts. Methodologically, this study follows an embedded case study design to investigate the tactics deployed by a population of CMOs in Northern California and relies on observational and documentary data to examine how CMOs design and execute donor outreach and the resonant messages they aim to elevate. Conclusions/Recommendations: I find that CMOs elevated business-friendly themes related to workforce preparation, impact, and return on investment in their outreach and at times commodified their constituents by offering their labor as exchangeable resources to elevate donor profiles. Simultaneously, CMOs advanced color-evasive discourse, relying on deficit-laden racial narratives to create a reinforcing and complementary rationale for intervention. These findings suggest that CMOs relied on market and racialized logics as the persuasive fodder for donor investment, leaving the economic and racial status quo—and the democratic and equity implications it perpetuates—unchallenged.

OP03 Patient Characteristics Affect Their Treatment Choice: A Discrete Choice Experiment With Breast Cancer Patients In Six European Countries

IntroductionThe evolution of breast cancer treatments over the last decade has resulted in tailored therapies for the different types and stages of breast cancer. Each treatment has a profile of benefits and adverse effects which are taken into consideration when planning a treatment pathway. The objective of this study is to examine whether patients’ preferences are in line with what is considered important from policy-makers viewpoint.MethodsAn online discrete choice experiment (DCE) was conducted in six European countries (France, Germany, Ireland, Poland, Spain, UK) with breast cancer (BC) patients. The DCE comprised of six attributes: overall survival (OS), hyperglycaemia, rash, pain, functional well-being (FWB) and out-of-pocket payment (OOP). Sixteen choice sets with two hypothetical treatments and a “no treatment” option were presented. Sociodemographic and disease related data were collected. Heteroscedastic conditional and mixed logistic models accounted for scale and preference heterogeneity between countries and patients respectively. Latent class analysis categorized patients in classes. Marginal rates of substitution (MRS) were estimated for OOP versus the rest of attributes to establish the ranking of preferences for each attribute.ResultsTwo hundred and forty-seven patients with advanced or metastatic BC and 314 with early-stage BC responded. Forty-nine percent of patients were less than 44 years old and 65 percent had completed university education. The MRS of the analysis demonstrated that “severe pain” is the highest dis-preferred attribute level, followed by “severe impairment in FWB” and OS. Four classes of patients as “decision-makers” were identified. Additionally, there is sensitivity in preferences for both levels of pain and FWB depending on the stage of the disease.ConclusionsThis study suggests that there is heterogeneity in treatment preferences of breast cancer patients depending on their sociodemographic and disease related characteristics. In combination with clinical guidelines, patient preferences can support the selection and tailoring of treatment options.

The heterogeneity of public preferences for the first healthcare visit: A discrete choice experiment in the context of Vietnam.

Primary healthcare is critical in addressing the main health problems of communities. In Vietnam, the increasing healthcare demands cause major challenges, especially overcrowding. This study identified public preferences regarding the selection of healthcare facilities for first visit. A discrete choice online survey was generated from five attributes including visit duration, travel time, personal connection with medical staff, doctors' experience, and health insurance. A Dz -efficient design constructed 36 choice sets, divided into three blocks of 12 choice sets. Each block formed one version of the questionnaire, which was randomly distributed to the participants. Heterogeneity in participant preferences was analysed by a latent class model with socio demographic characteristics and experiences of the last visit. 822 participants valued doctors' experience for both minor and severe symptoms. Preference heterogeneity for minor symptoms was quick service provision, highly experienced doctors, and payment through health insurance for the first (44.18%), second (32.17%), and third classes (23.66%), respectively. Regarding severe symptoms, they favoured all five attributes, quick health service, and reduced travel time for the first, second, and third classes, respectively (heterogeneities of 58.16%, 27.79%, and 14.05%, respectively). Predictions of choice from the worst to optimal healthcare facility scenario were 8.91%-61.91% and 10.16%-69.83% for minor and severe symptoms, respectively. Knowledge regarding public preference heterogeneity supports policymakers increase public acceptance in choosing primary healthcare facilities. Visit duration and doctors' experience should be considered a priority in decision making.