No-choice Option Research Articles

Physicians\u2019 preferences and willingness to pay for artificial intelligence-based assistance tools: a discrete choice experiment among german radiologists

BackgroundArtificial Intelligence (AI)-based assistance tools have the potential to improve the quality of healthcare when adopted by providers. This work attempts to elicit preferences and willingness to pay for these tools among German radiologists. The goal was to generate insights for tool providers and policymakers regarding the development and funding of ideally designed and priced tools. Ultimately, healthcare systems can only benefit from quality enhancing AI when provider adoption is considered.MethodsSince there is no established market for AI-based assistance tools in radiology yet, a discrete choice experiment was conducted. Respondents from the two major German professional radiology associations chose between hypothetical tools composed of five attributes and a no-choice option. The attributes included: provider, application, quality impact, time savings and price. A conditional logit model was estimated identifying preferences for attribute levels, the no-choice option, and significant subject-related interaction effects.Results114 respondents were included for analysis of which 46% were already using an AI-based assistance tool. Average adoption probability for an AI-based tool was 81% (95% CI 77.1% − 84.4%). Radiologists preferred a tool that assists in routine diagnostics performing at above-radiologist-level quality and saves 50% in diagnostics time at a price-point of €3 per study. The provider is not a significant factor in the decisions. Time savings were considered more important than quality improvements (i.e., detecting more anomalies).ConclusionsRadiologists are overall willing to invest in AI-based assistance tools. Development, funding, and research regarding these tools should, however, consider providers’ preferences for features of immediate everyday and economic relevance like time savings to optimize adoption.

Where You Shop Affects How You Choose: Retailer Price Image and the Importance of Enriched versus Comparable Attributes

This research documents a novel influence of retailer price image (RPI): its effect on what consumers choose within the retailer. Because a high RPI is associated with a high likelihood of finding lower prices elsewhere, we propose that shopping at a retailer with a high RPI, relative to a low RPI, increases the salience of the option to defer choice (i.e., to leave the retailer and search elsewhere). We further propose that the increased salience of the no-choice option alters the importance consumers place on enriched attributes (e.g., brand, unique design) versus comparable attributes (e.g., megapixels, number of settings) when choosing an option (i.e., when they do not defer). The findings of seven experiments show that high-RPI settings increase the relative importance of enriched attributes, thereby making options dominating on enriched attributes more likely to be chosen in high-RPI settings than in low-RPI settings.

A Bayesian Dynamic Model for Incomplete Preferences with No-Choice Options in Conjoint Analysis

In the analysis of ranking data such as ranking based conjoint analysis, it is common that all preference ranks are obtained in each trial. However, if there is an no-choice option in alternatives such as conjoint profiles, the ranking ends there, and partial ranking data with a structure depending on the individuals and the trials is observed. We propose a rank-ordered logit model and Bayesian estimation method for partial ranking data with no-choice options that have different ranking structures for each individual and trial. In the model, we consider the latent variables that vary according to each individual and time and decompose them into individual and temporal heterogeneity. Specifically, we consider individuals' heterogeneities using a hierarchical Bayesian model, individuals' learning and evolution of preference using a dynamic linear model, and estimate parameters via the Markov chain Monte Carlo method. For empirical analysis, we apply the proposed model to the analysis of the ranking data obtained by the conjoint measurement method. From the results of conjoint data analysis for smartphones, it is confirmed that the preference or relative importance of the attributes change among trials.

Random Utility Models with Cardinality Context Effects for Online Subscription Service Platforms

A more general family of random utility models is developed to model a cognitive heuristic, known as consideration sets. These new models, denoted as Multinomial Logit Cardinality Effect models (MNL-CE), define perceived representative utility of items by assigning a penalty as a function of assortment cardinality to the representative utility of each item beyond a threshold value (except for the no-choice option). This definition of perceived representative utility of an item is context-dependent and thus a function of assortment attributes (cardinality), in addition to item and user attributes. The user’s net benefit is therefore a trade-off between the benefits and the costs of considering a certain number of items. A developed algorithm efficiently solves the subscription platform assortment optimization problem with equal profit when user selection is modeled via variants of the MNL-CE. The sensitivity of model parameters on the optimal assortment cardinality and no-choice probability is analyzed with the MovieLens dataset.

Flying with climate liability? Economic valuation of voluntary carbon offsets using forced choices

This study aims to examine how key aspects of voluntary climate action influence economic values of aviation carbon offsets using an Australian case study, where voluntary carbon offset programs for the aviation sector were active under a carbon tax between July 01, 2012 and July 17, 2014. An online survey was administered during the period using choice experiments. This rare and short-lived Australian experience is useful to gain insights into how individuals respond to the new public policy in terms of the perceived economic value of voluntary offsets for air travel. According to the estimation results, supporters of the mandatory tax policy held a welfare value of voluntary carbon offsets for their domestic flights that is three times larger than non-supporters (i.e., $AU27.83 vs. $AU9.40). It is $AU12.27 on average per ton of carbon offsets per person for domestic flights and $AU0.92 for international long-haul flights. The findings endorse that individuals seem to attach personal responsibility for carbon emissions (i.e. climate liability or carbon conscience) to frequent domestic flights, but not so much to intercontinental flights. Furthermore, reported flight frequencies by respondents did not place any significant impact on economic values of voluntary carbon offsets in both domestic and international frameworks. A coupled approach between forced choices and certainty responses was adapted, where no-choice options were retrieved, potentially improving choice experiments. Results suggest that airlines should consider simplifying their carbon offset programs to fixed levels (e.g. £3, £10, and £20 as in the case of British Airways), regardless of geographical boundaries, while governments should promote both mandatory and voluntary climate measures in tandem.

Examining the No-Choice Option in Conjoint Analysis

Conjoint analysis is a survey-based method used to measure consumer preferences and predict demand for products that may not yet exist in the marketplace. The most frequently used form of conjoint analysis involves having respondents choose from among a relatively small set of offerings with each described by a relatively small number of features. The validity of the resulting data rests on the inclusion of each alternative’s brand name, which proxies for the attributes not mentioned in the study, and the inclusion of an outside “no-choice” option that accounts for brands not explicitly included. Respondents selecting the no-choice option have determined that some other offering, not included in the survey, is preferred to those included in the survey, and that is better for them to hold onto their money and not make a purchase at this time. Thus, selecting the no-choice option assumes that respondents have some knowledge of the prices and features of the outside goods not included in the study. In this paper, we examine the effect of providing respondents with information about the prices and features of outside goods on conjoint preference estimates. Using a national sample of respondents in the tooth whitening category, we find that conjoint estimates are surprisingly robust to the information provided about the outside no-choice options.

Random Utility Models with Cardinality Context Effects for Online Recommendations

This work creates new random utility models able to capture a cognitive heuristic known as consideration set theory. These choice models, which capture cardinality context effects in addition to item and user attributes, are ideal for recommending personalized assortments in online subscription service platforms. In such situations, users may be overwhelmed by a large amount of options, increasing their no-choice probability. Our new models modify the multinomial logit model by subtracting from an item’s perceived representative utility a disutility caused by the cardinality of the recommended assortment. Because this disutility does not affect the no-choice option, the user’s net benefit from evaluating a certain number of items is captured as a trade-off between the benefits and the costs of considering those items. Using an empirical data set capturing changing no-choice probabilities for different assortment sizes, a gradient descent algorithm estimates model input parameters. An algorithm is presented to efficiently solve the optimal assortment problem under cardinality context effects with equal profit margin. Computational experiments and statistical tests using the MovieLens dataset analyze the sensitivity of model parameters on the optimal assortment cardinality and no-choice probability.

Measuring respondent uncertainty in discrete choice experiments via utility suppression

Discrete choice experiments (DCEs) are an important methodology in survey research. Although DCEs assume that respondents know their true preferences and can make choices precisely, in reality, respondents may be uncertain. Respondent uncertainty has long been recognized as an issue in the DCE context, but unfortunately, its explicit modelling has received only limited attention. This paper proposes using hierarchical Bayes multinomial probit models to construct respondent uncertainty measures based on the utility difference and a concept called utility suppression, which is quantified by the derivative of the inverse Mills ratio. Two empirical studies with different DCE design formats are conducted to assess and compare the performance. The first includes a no-choice option, and the second is forced-choice formatted with a simpler design. The hold-out validation shows that the utility difference and our proposed measure, which are consistent with the random utility maximization assumption, have better overall performance, particularly in identifying the high-uncertainty respondents. We further show how the information about respondent uncertainty can be utilized in practice.

The Effect of Color on Preference for a No-choice Option

본 연구는 제품 정보의 배경색에 따라 소비자가 선택을 연기(choice deferral)하는 확률이 달라지는 가를 탐구하고 있다. 기존 연구에 따르면 선택 연기는 소비자가 선택에 어려움을 느낄 때 주로 발생한다. 선택의 어려움을 증가시키는 상황은 대안 간 매력도가 비슷하거나 대안의 수가 너무 많을 때이다. 하지만 정보 제시 방법에 따라서도 선택을 연기하는 확률이 증가할 수 있다. 본 연구에서는 제품 정보의 배경색이 수축색이냐 팽창색이냐에 따라 비선택 옵션(no-choice option)에 대한 선호가 달라질 수 있음을 보여주고 있다.BR 동일한 물체라 하더라도 그 크기를 크게 또는 작게 보이게 하는 색이 존재한다. 전자를 팽창색이라 하고 후자를 수축색이라고 한다. 이러한 색은 공간의 크기를 지각하는 데도 영향을 미쳐 팽창색으로 칠해 진 공간이 수축색으로 칠해 진 공간보다 더 넓게 느껴진다. 이러한 결과를 바탕으로 본 연구는 팽창색 또는 수축색에 노출되기만 해도 사람들은 자신을 둘러싼 공간의 크기를 심리적으로 크게 또는 작게 지각한다고 주장한다. 즉 팽창색 보다 수축색에 노출된 소비자는 공간의 제약을 강하게 느끼고 그 결과 심리적 밀폐감이 높아진다. 이러한 밀폐감은 개인의 통제(control)나 자유(freedom)가 훼손된 것으로 이해되고, 이를 복원하기 위해 개인은 저항행동(reactance behavior)을 보이게 된다. 이 때 비선택 옵션은 주어진 대안을 거절하는 직접적인 저항행동부터 새로운 대안을 추구하려는 간접적인 저항행동까지를 모두 포함하고 있으므로 수축색에 노출된 소비자는 저항행동의 일환으로 비선택 옵션을 선호하게 된다.BR 이러한 가설은 세 개의 실증연구를 통해 검증되었다. 연구 1과 2에서는 수축색이 심리적 밀폐감을 높이고 비선택 옵션에 대한 선호를 증가시킨다는 가설을 검증하였다. 연구 3은 본 연구의 일반화 가능성을 높이기 위해 연구 1, 2와는 다른 제품군을 사용하여 효과를 재확인 하였다. 또한 비선택 옵션의 프레이밍을 변화시켜도 저항행동의 범위 안에 들어간다면 수축색 조건에서 비선택 옵션에 대한 선호도가 일관되게 상승한다는 결과를 얻었다.

How important is local food to organic-minded consumers?

The study deals with German consumers' attitudes towards organic food and local food, their food purchase behaviour and their personal characteristics. The purpose is to investigate the differences in attitudes and willingness-to-pay values between consumers who consider the organic production of food (very) important and those who consider it less important.This study combines a consumer survey with an in-store, discrete choice experiment. In the analysis, findings from the consumer survey were related to the choices made by consumers in the experiment. Consumers' preferences and willingness-to-pay values were estimated through random parameter logit modelling.Organic-minded consumers (i.e. those who regarded organic food production as (very) important in the survey) have stronger preferences and estimated willingness-to-pay values for organic as well as local products. Locally produced food, as opposed to food from neighbouring countries or non-EU countries, is preferred over organically produced food by both consumer groups which demonstrates that organic-minded consumers do not only consider organic food production as important, but also value local food production in a purchase situation. Hence, it can be assumed that local food production complements organic food production for the group of organic-minded consumers.This contribution is the first study dealing with local and organic food purchase behaviour in Germany that examines four different products and is carried out in rural as well as urban locations in four different regions. Due to the application of a choice experiment including no-choice options and binding purchase decisions, the results are expected to be closer to real purchase situations than results of direct questioning and choice experiments in online applications.

Assortment Optimisation Under a General Discrete Choice Model: A Tight Analysis of Revenue-Ordered Assortments

A central problem in revenue management, known as the assortment problem, consists in deciding which subset of products to offer to consumers in order to maximise revenue. A simple and natural strategy is to select the best assortment out of all those that are constructed by fixing a threshold revenue r and then choosing all products with revenue at least r. This is known as the revenue-ordered assortments strategy. The main contribution of this paper is a precise analysis of how well revenue-ordered assortments approximate the optimum revenue when customers are rational in the following sense: the probability of selecting a specific product (including the no-choice option) from the set being offered cannot increase if the offer set is enlarged. The corresponding discrete choice models form a broad class of models which includes all discrete choice models based on random utility. Our analysis of revenue-ordered assortments match and unify known results for certain models, and improves the best known results for others, such as for the Mixed Multinomial Logit model recently studied by Rusmevichientong et al (2014). An appealing feature of our analysis is that it is simple and relies only on the above-mentioned rationality property, and yet it is best possible even for very specific models within the class. We also show that a large class of problems known as envy-free pricing problems can be seen as assortment problems for a specifically constructed discrete choice model that satisfies the rationality property. In this context, revenue-ordered assortments turn out to be equivalent to the well-studied uniform pricing strategy.

The moderating effect of a no-choice option on risky framing effect

Risky framing effects refer to changes in risk preferences as a result of how choices are verbally presented, such as in terms of gains or losses. Prior research on framing has produced mixed results, with only some showing reliable framing effects. We argue that this is because different framing studies have created different levels of between-alternative conflict. Two studies were conducted to examine how different levels of between-alternative conflict and the inclusion of a no-choice option influence framing effects using both between- and within-individuals experimental designs. These studies found that high levels of between-alternative conflict were associated with framing effects, and that high levels of between-alternative conflict were moderated by including the no-choice option in the choice set. Taken together, these two studies demonstrated that the inclusion of a no-choice option provides an alternative way of resolving difficult choices regarding decision frames that are not available when individuals are forced to choose. It is concluded that between-alternative conflict makes people influenced by decision frames and determines the appearance of the framing effect.

Deep brain stimulation of the subthalamic nucleus: All that glitters isn't gold?

With the silver anniversary of deep brain stimulation (DBS) behind us, this would seem to be a good juncture to consider its successes and unanswered questions. Bilateral subthalamic nucleus (STN) stimulation has changed the clinical perspective of several thousand Parkinson's disease (PD) patients worldwide. A recent reappraisal animates the field with strong arguments in favor of an anticipation of the stereotactic approach in patients with as little as 5 to 6 years of disease history if they manifest motor complications. From what was once a no-choice option, STN-DBS is now becoming more and more attractive to neurologists dealing with movement disorders. Despite the development of new pharmacological treatment and renewed rehabilitation programs able to modify the severity of drug-related complications, a resurgence of stimulation therapy reminiscent of an old era of medicine with an attendant blinkered mindset has emerged. Yet, the DBS-mediated effects are modest on critical aspects such as gait impairment and extremely variable depending on the clinical phenotype and individual clinical profile. Hence, the indication for DBS should become more, and not less, individually tailored. Those physicians considering deep brain stimulation (DBS) as a therapeutic option need to evaluate results beyond short-term quality of life, giving the correct weight to the direct and indirect costs over the longer term as well as to life prognosis. Unequivocal recourse to early-stimulation surgery necessitates investigations not limited to a mere comparative assessment versus drug-mediated benefits, but instead showing evidence of a clear degree of disease-modifying effect or a rescue of basal ganglia plasticity.

Inner conflict between nuclear power generation and electricity rates: A Japanese case study

Since the March 11 earthquake, Japanese households have been facing a trade-off problem between decreasing dependency on nuclear power generation and avoiding an increase in electricity rates. We analyze this inner conflict quantitatively, adopting two economic–psychological approaches: First, we note that the trade-off causes cognitive dissonance after making a choice that results in a wider desirability gap between the chosen and rejected alternatives. Second, the consumer surplus improves by 11.2% with a no-choice option for suspending judgment in the presence of cognitive dissonance. Third, individual characteristics such as gender and annual household income are significantly correlated with both cognitive dissonance and a preference for the no-choice option.

Staying the Course

Individuals regularly face adversity in the pursuit of goals that require ongoing commitment. Whether or not individuals persist in the face of adversity greatly affects the likelihood that they will achieve their goals. We argue that a seemingly minor change in the individual’s original choice set—specifically, the addition of a no-choice option—will increase persistence along the chosen path. Drawing on self-perception theory, we propose that choosing from a set that includes a no-choice (do nothing) option informs individuals that they both prefer the chosen path to other paths and that they consider this path alone to be worth pursuing, an inference that cannot be made in the absence of a no-choice option. This unique information strengthens individuals’ commitment to, and increases their persistence on, their chosen path. Three studies employing incentive-compatible designs supported our predictions and ruled out several rival accounts.

Rejectable Choice Sets: How Seemingly Irrelevant No-Choice Options Affect Consumer Decision Processes

To date, research on no-choice options has primarily examined the conditions that foster choice deferral, thus focusing on the frequency with which consumers select the no-choice option. In this article, the authors argue that even if the no-choice option is not selected, its mere presence in the choice set may alter consumers' choices. More specifically, they investigate how decision processes and preferences change when consumers have a no-choice option versus when they are forced to choose from a given choice set. They propose that the inclusion of a no-choice option in a choice set affects preferences by leading consumers to determine not only which alternative is best, but which, if any, are acceptable (i.e., meet the consumer's minimum needs). Accordingly, the authors demonstrate that the inclusion of a no-choice option in the choice set (1) leads to more alternative- (rather than attribute-) based information processing, (2) increases the importance of attributes that are more meaningful when alternatives are evaluated one by one (i.e., enriched attributes), and (3) increases the importance of attributes with levels that are closer to the consumer's minimum needs (thresholds). They demonstrate that such changes influence consumers' preference structures and ultimate choices. They conclude with a discussion of the theoretical, methodological, and managerial implications of these findings.

Where have all the flowers gone? Forecasting green trends in the automobile industry with a choice-based conjoint adoption model

With rising gas prices, global warming, and green thinking, all-electric vehicles are currently considered the automobile technology of the future. However, besides their advantages electric drive trains also exhibit several disadvantages. Moreover, history shows several failed attempts to establish electric vehicles. Thus, a reliable forecasting model is needed that predicts if the current trend is sustainable. We develop and empirically test a choice-based conjoint adoption model that uses individual-level preferences as a basis for prediction. Predictions are mapped to the time of the next planned purchase in order to establish the adoption process. The model extends existing research in several ways. First, no prior information, e.g., historical market data or a functional form of the adoption process, has to be integrated. Second, the model allows dynamic modifications of product specifications or competition at different points in time. Third, a no-choice option can be integrated so that a technology switch is not forced by the model itself and switching costs can be considered. The empirical results reveal different critical factors for the adoption of all-electric vehicles, such as purchase price, range, timing of the market entry, or environmental evolution, which could lead to a solid base of consumers preferring this option.

The Effect of Common Features on Consumer Preference for a No-Choice Option: The Moderating Role of Regulatory Focus

Abstract This study researches the effects of common features on a no-choice option with respect to regulatory focus theory. The primary interest is in three factors and their interrelationship: common features, no-choice option, and regulatory focus. Prior studies have compiled vast body of research in these areas. First, the “common features effect” has been observed by many noted marketing researchers. Tversky (1972) proposed the seminal theory, the EBA model: elimination by aspect. According to this theory, consumers are prone to focus only on unique features during comparison processing, thereby dismissing any common features as redundant information. Recently, however, more provocative ideas have attacked the EBA model by asserting that common features really do affect consumer judgment. Chernev (1997) first reported that adding common features mitigates the choice gap because of the increasing perception of similarity among alternatives. Later, however, Chernev (2001) published a critically develop...

Delay discounting of self-determined and experimenter-determined commodities.

Self determination has long been a concept of great interest to psychologists. For instance, self determination was a critical concept in the person-centered therapy and theory of personality that was forwarded by Carl Rogers (Patterson & Joseph, 2007). More recently, self-determination theory has emerged (e.g., Deci & Ryan, 2008) as a general theory of human behavior and motivation that has been applied in a wide variety of situations (e.g., education, Kaufman & Dodge, 2009; worker satisfaction & productivity, Kuvaas, 2009). The common theme related to self determination is that it is a good thing; people are happier, more motivated, and more productive when they can exercise self determination than when they cannot. Although behavioral psychologists have historically eschewed internal or personality variables as explanations for behavior, they too have explored the idea that situations that involve self determination are functionally different than situations that do not involve self determination. For instance, Graff, Libby, and Green (1998) found that participant-selected reinforcers maintained higher rates of free-operant responding, and produced less challenging behaviors, than did experimenter-selected reinforcers in two male participants with severe developmental disabilities. Geckeler, Libby, Graff, and Ahearn (2000) failed to replicate this effect on free-operant responding in three boys with Autism, but did find that when participant-and experimenter-selected reinforcers were available in a concurrent-choice procedure, all three boys showed a response preference for the alternative that allowed them to choose their own reinforcer. These results replicated those of a previous study (i.e., effect of self-determined choice only in the concurrent-schedule situation; Graff & Libby, 1999), which had studied four boys with either developmental disabilities or attention-deficit disorder. More recently, Tiger, Hanley, and Hernandez (2006) studied the effect of reinforcer choice on the behavior of preschool children. Results indicated that five of the six children showed an initial preference for choosing their own reinforcer, although this preference did not persist throughout the entire condition for several of the children. Tiger et al.'s fourth study demonstrated that the children continued to choose the reinforcer-choice option despite the fact that the response requirement for doing so was higher than the no-choice reinforcer option. Overall, these studies support the idea that an outcome that allows the individual to determine his/her own reinforcing consequences can be a more effective or preferred reinforcer than the identical outcome that is not chosen by the individual. Determining whether outcome choice is indeed a more powerful reinforcing consequence than a predetermined outcome has a number of potential implications, especially if that outcome can be demonstrated in an adult sample. For instance, the implication for individuals in the field of marketing would be that offering potential customers a self-chosen prize for visiting a business or website might be a more effective promotion than simply offering a predetermined prize. Instructors might find that students' work improves if their efforts result in a self-chosen outcome rather than an instructor-chosen outcome. Researchers who employ human participants in laboratory studies with the incentive of winning a prize (e.g., a gift card) for good performance may find improved performance if participants are offered a self-determined reward rather than an experimenter-chose one. The study of delay discount affords one measure of the value of an outcome or commodity. Delay discounting occurs when the value of an outcome is devalued because it is delayed in time. For instance, if someone owed you $100 but was not going to be able to pay you for a month, you might accept $95 immediately rather than waiting a month for the full amount. …

Formula omitted]-optimal conjoint choice designs with no-choice options for a nested logit model

Despite the fact that many conjoint choice experiments offer respondents a no-choice option in every choice set, the optimal design of conjoint choice experiments involving no-choice options has received only a limited amount of attention in the literature. In this article, we present an approach to construct D-optimal designs for this type of experiment. For that purpose, we derive the information matrix of a nested multinomial logit model that is appropriate for analyzing data from choice experiments with no-choice options. The newly derived information matrix is compared to the information matrix for the multinomial logit model that is used in the literature to construct designs for choice experiments. It is also used to quantify the loss of information in a choice experiment due to the presence of a no-choice option.