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Journal of Choice Modelling最新文献

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Best, worst, and best&worst choice probabilities for logit and reverse logit models logit和反向logit模型的最佳、最差、最佳和最差选择概率
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-25 DOI: 10.1016/j.jocm.2023.100449
André de Palma , Karim Kilani

This paper builds upon the work of Professor Marley, who, since the beginning of his long research career, has proposed rigorous axiomatics in the area of probabilistic choice models. Our study concentrates on models that can be applied to best and worst choice scaling experiments. We focus on those among these models that are based on strong assumptions about the underlying ranking of the alternatives with which the individual is assumed to be endowed when making the choice. Taking advantage of an inclusion–exclusion identity that we showed a few years ago, we propose a variety of best–worst choice probability models that could be implemented in software packages that are flourishing in this field.

本文建立在Marley教授的工作基础上,Marley教授自其漫长的研究生涯开始以来,就在概率选择模型领域提出了严格的公理学。我们的研究集中在可以应用于最佳和最差选择缩放实验的模型上。我们关注的是这些模型中那些基于对个人在做出选择时被赋予的备选方案的基本排名的有力假设的模型。利用我们几年前展示的包含-排除身份,我们提出了各种最佳-最差选择概率模型,这些模型可以在该领域蓬勃发展的软件包中实现。
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引用次数: 0
Cube model: Predictions and account for best–worst choice situations with three choice alternatives 立方体模型:预测并说明三种选择方案的最佳-最差选择情况
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-20 DOI: 10.1016/j.jocm.2023.100448
Adele Diederich , Keivan Mallahi-Karai

The Cube model (Mallahi-Karai and Diederich, 2019) is a dynamic-stochastic approach for decision making situations including multiple alternatives. The underlying model is a multivariate Wiener process with drift, and its dimension is related to the number of alternatives in the choice set. Here we modify the model to account for Best–Worst settings. The choices are made in a number of episodes allowing the alternatives to be ranked from best to worst or from worst to best. The model makes predictions with respect to choice probabilities and (mean) choice response times. We show how the model can be implemented using Markov chains and test the model and a simpler variation of it on data from Hawkins et al. (2014b).

立方体模型(Mallahi Karai和Diederich,2019)是一种用于包括多个备选方案的决策情况的动态随机方法。基础模型是一个具有漂移的多元维纳过程,其维数与选择集中的备选方案数量有关。在这里,我们修改模型以考虑最佳-最差设置。这些选择是在多集中进行的,允许从最佳到最差或从最差到最佳对备选方案进行排名。该模型对选择概率和(平均)选择响应时间进行预测。我们展示了如何使用马尔可夫链来实现该模型,并在Hawkins等人的数据上测试了该模型及其更简单的变体。(2014b)。
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引用次数: 0
Outside good utility and substitution patterns in direct utility models 直接效用模型中的外部良好效用和替代模式
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-19 DOI: 10.1016/j.jocm.2023.100447
Chul Kim , Adam N. Smith , Jaehwan Kim , Greg M. Allenby

This paper investigates the role of the outside good utility function on admissible substitution patterns in multiple discrete/continuous demand models. We first present a set of novel results that characterize the functional form of quantity price effects within this class of models. The results highlight the relative inflexibility of many standard outside good utility functions. We then propose a new outside good utility function that admits more flexible marginal utility curves. Our empirical analysis uses household scanner panel data from the potato chip category, where we find empirical support for non-standard rates of satiation for the outside good. We then show how the restrictive substitution patterns induced by standard utility specifications may distort price elasticities and the evaluation of loyalty coupon targeting programs.

本文研究了外部良好效用函数在多个离散/连续需求模型中对可容许替代模式的作用。我们首先给出了一组新的结果,这些结果描述了这类模型中数量-价格效应的函数形式。结果突出了许多标准外部良好效用函数的相对不灵活性。然后,我们提出了一个新的外部良好效用函数,它允许更灵活的边际效用曲线。我们的实证分析使用了薯片类的家用扫描仪面板数据,在那里我们发现了对外部商品的非标准满足率的实证支持。然后,我们展示了标准公用事业规范引发的限制性替代模式如何扭曲价格弹性和忠诚度优惠券目标计划的评估。
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引用次数: 0
Evaluating the gap choice decisions of pedestrians in conflict situations in mass religious gatherings and controlled experimental setup – A pilot study 在大规模宗教集会和对照实验设置中,评估冲突情况下行人的间隙选择决策——一项试点研究
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-18 DOI: 10.1016/j.jocm.2023.100450
Karthika P S , Ashish Verma

Previous studies on modelling the microscopic behaviour of pedestrians have focused on conflict resolution among pedestrians in pedestrian-pedestrian interactions. Many of these models propose alternate mechanisms to avoid conflicts by introducing repulsive forces between pedestrians or a set of predefined rules stating the precedence of movements to sidestep obstacles and other pedestrians. However, the possibility of formulating the decision-making mechanism pedestrians use to overcome conflicts as a gap-seeking behaviour has not been explored. In this study, resolving conflicts between opposing pedestrians is modelled as gap choice decisions made by individuals. Pedestrians looking for gaps or spaces in a crowd to facilitate their movement form the basis for such an analysis. The study compares pedestrians' gap acceptance behaviour across two scenarios: pedestrian movement in a field setup (Kumbh Mela) and a controlled experiment. Multiple gap choice decisions of individuals are modelled to understand the effect of individual-level heterogeneity on gap choices. Apart from the gap duration, spacing, position of gap, linear density, age, and presence of luggage significantly influenced the gap choices. Model validation is done using appropriate methods for both field and experimental data. The bootstrap method of internal validation and holdout validation is used to assess the performance of the estimated model on field data and experimental data, respectively. It is seen that the models have reasonable predictive and discriminative abilities. The analysis results also indicate that pedestrians tend to force gaps to facilitate movement in their natural state. Consequently, controlled experiments might have limitations in reproducing or motivating the participants to behave like a crowd.

先前对行人微观行为建模的研究主要集中在行人与行人互动中行人之间的冲突解决。这些模型中的许多提出了替代机制,通过在行人之间引入排斥力或一组预先定义的规则来避免冲突,这些规则规定了避开障碍物和其他行人的动作的优先级。然而,将行人用来克服冲突的决策机制制定为一种寻求差距的行为的可能性尚未得到探索。在这项研究中,解决对立行人之间的冲突被建模为个人做出的间隙选择决策。行人在人群中寻找空隙或空间以方便他们的移动,这构成了这种分析的基础。这项研究比较了两种场景下行人的间隙接受行为:野外设置(大壶节)和对照实验中的行人运动。对个体的多重差距选择决策进行建模,以了解个体水平异质性对差距选择的影响。除了间隙持续时间外,间隙的间距、位置、线密度、年龄和行李的存在显著影响间隙的选择。模型验证是使用适当的方法对现场和实验数据进行的。内部验证和保留验证的bootstrap方法分别用于评估估计模型在现场数据和实验数据上的性能。可以看出,这些模型具有合理的预测和判别能力。分析结果还表明,行人在自然状态下倾向于强行设置间隙以便于移动。因此,对照实验在再现或激励参与者表现得像一群人方面可能存在局限性。
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引用次数: 0
Sample size selection for discrete choice experiments using design features 利用设计特征进行离散选择实验的样本量选择
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-08 DOI: 10.1016/j.jocm.2023.100436
Samson Yaekob Assele , Michel Meulders , Martina Vandebroek

In discrete choice experiment (DCE) studies, selecting the appropriate sample size remains a challenge. The question of the required sample size for a DCE is addressed in the literature in two distinct approaches: a rule-of-thumb approach and an approach based on the statistical error of the parameter of interest. The former is less accurate and does not depend on the desired power and significance level, whereas the latter requires knowing the complete design which may not be known at the planning stage. This paper proposes a new rule of thumb as well as a new regression-based method that requires knowing certain design characteristics rather than the complete design and takes into account the power and significance level. We compare the sample size estimated using the proposed methods with the true required sample size based on the statistical error of the parameter of interest and the approximations given by the existing rules of thumb. The results show that both the new rule of thumb and the regression-based approach improve the magnitude and proportion of underestimation compared to the most commonly used rule of thumb of Orme. Though the proposed approaches perform in general similarly to Tang’s rule which improves Orme’s rule, they seem to do better for large settings in terms of the number of choice sets and the number of alternatives per choice set in reducing underestimation. Moreover, we have demonstrated the possibility to adapt the regression-based approaches to take into account other scenarios and choice set complexity.

在离散选择实验(DCE)研究中,选择合适的样本量仍然是一个挑战。文献中用两种不同的方法解决了DCE所需的样本量问题:经验法则方法和基于感兴趣参数统计误差的方法。前者不太准确,不取决于所需的功率和重要性水平,而后者需要了解完整的设计,而这在规划阶段可能是未知的。本文提出了一个新的经验法则和一种新的基于回归的方法,该方法需要了解某些设计特征,而不是完整的设计,并考虑到功率和显著性水平。我们将使用所提出的方法估计的样本量与基于感兴趣参数的统计误差和现有经验法则给出的近似值的真实所需样本量进行比较。结果表明,与最常用的奥姆经验法则相比,新的经验法则和基于回归的方法都提高了低估的幅度和比例。尽管所提出的方法总体上与改进了Orme规则的Tang规则类似,但就选择集的数量和每个选择集的备选方案数量而言,它们似乎在减少低估方面对大型设置做得更好。此外,我们已经证明了调整基于回归的方法以考虑其他场景和选择集复杂性的可能性。
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引用次数: 0
A cross-sectional exploration of labor supply, gender, and household wealth in urban China 中国城市劳动力供给、性别和家庭财富的横断面调查
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-01 DOI: 10.1016/j.jocm.2023.100433
Xuehui Han , Tao Zhang , John K. Dagsvik , Yuan Cheng

We propose a modeling framework that uses only cross-sectional data to disentangle labor supply and demand choices simultaneously. This modeling framework extends the labor-market analytical toolkits to adapt to environments where data are limited, flexibility in working hours is lacking, or structural changes are present, as is the case in most emerging and low-income countries. We showcase our model by using the 2011 China Household Finance Survey to decipher labor market choices in urban China. We find that the main discrepancies in labor supply between males and females are driven by the number and age of children, the lower utility of working rather than fewer job opportunities for females, and larger impacts of education and work experience on females’ job opportunities. Household wealth in the form of ‘cash inflow’ incentivizes individuals not to work, while wealth in the form of ‘stock’ induces higher utility to work for both males and females. The interpretation of empirical findings hinges on particular assumptions that might be disputed.

我们提出了一个建模框架,只使用横截面数据来同时理清劳动力供应和需求选择。该建模框架扩展了劳动力市场分析工具包,以适应数据有限、工作时间缺乏灵活性或存在结构变化的环境,就像大多数新兴和低收入国家的情况一样。我们通过使用2011年中国家庭金融调查来解读中国城市劳动力市场的选择,展示了我们的模型。我们发现,男性和女性劳动力供应的主要差异是由子女的数量和年龄、女性工作的效用较低而不是工作机会较少以及教育和工作经验对女性工作机会的较大影响所驱动的。家庭财富以“现金流入”的形式激励个人不工作,而财富以“股票”的形式诱导男性和女性工作的效用更高。对实证研究结果的解释取决于可能存在争议的特定假设。
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引用次数: 0
One or two-step? Evaluating GMM efficiency for spatial binary probit models 一步还是两步?空间二元probit模型的GMM效率评估
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-01 DOI: 10.1016/j.jocm.2023.100432
Gianfranco Piras , Mauricio Sarrias

In this article we propose two-step generalized method of moment (GMM) procedure for a Spatial Binary Probit Model. In particular, we propose a series of two-step estimators based on different choices of the weighting matrix for the moments conditions in the first step, and different estimators for the variance–covariance matrix of the estimated coefficients. In the context of a Monte Carlo experiment, we compare the properties of these estimators, a linearized version of the one-step GMM and the recursive importance sampler (RIS). Our findings reveal that there are benefits related both to the choice of the weight matrix for the moment conditions and in adopting a two-step procedure.

在本文中,我们提出了一个空间二进制Probit模型的两步广义矩方法(GMM)过程。特别地,我们提出了一系列基于第一步中矩条件的加权矩阵的不同选择的两步估计量,以及估计系数的方差-协方差矩阵的不同估计量。在蒙特卡洛实验的背景下,我们比较了这些估计量的性质,一步GMM的线性化版本和递归重要性采样器(RIS)。我们的研究结果表明,在力矩条件下选择权重矩阵和采用两步程序都有好处。
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引用次数: 0
How to ask twenty questions and win: Machine learning tools for assessing preferences from small samples of willingness-to-pay prices 如何提出20个问题并获胜:从支付价格意愿的小样本中评估偏好的机器学习工具
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-01 DOI: 10.1016/j.jocm.2023.100418
Konstantina Sokratous, Anderson K. Fitch, Peter D. Kvam

Subjective value has long been measured using binary choice experiments, yet responses like willingness-to-pay prices can be an effective and efficient way to assess individual differences risk preferences and value. Tony Marley’s work illustrated that dynamic, stochastic models permit meaningful inferences about cognition from process-level data on paradigms beyond binary choice, yet many of these models remain difficult to use because their likelihoods must be approximated from simulation. In this paper, we develop and test an approach that uses deep neural networks to estimate the parameters of otherwise-intractable behavioral models. Once trained, these networks allow for accurate and instantaneous parameter estimation. We compare different network architectures and show that they accurately recover true risk preferences related to utility, response caution, anchoring, and non-decision processes. To illustrate the usefulness of the approach, it was then applied to estimate model parameters for a large, demographically representative sample of U.S. participants who completed a 20-question pricing task — an estimation task that is not feasible with previous methods. The results illustrate the utility of machine-learning approaches for fitting cognitive and economic models, providing efficient methods for quantifying meaningful differences in risk preferences from sparse data.

长期以来,主观价值一直使用二元选择实验来衡量,但支付价格的意愿等反应可能是评估个体差异风险偏好和价值的有效方法。Tony Marley的工作表明,动态随机模型允许从二元选择之外的范式的过程级数据中对认知进行有意义的推断,但其中许多模型仍然难以使用,因为它们的可能性必须通过模拟来近似。在本文中,我们开发并测试了一种使用深度神经网络来估计其他棘手行为模型参数的方法。一旦经过训练,这些网络就可以进行准确和即时的参数估计。我们比较了不同的网络架构,并表明它们准确地恢复了与效用、响应谨慎、锚定和非决策过程相关的真实风险偏好。为了说明该方法的有用性,然后将其应用于对完成20个问题定价任务的美国参与者的大量人口统计学代表性样本的模型参数估计,这一估计任务在以前的方法中是不可行的。结果说明了机器学习方法在拟合认知和经济模型方面的效用,为从稀疏数据中量化风险偏好的有意义差异提供了有效的方法。
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引用次数: 1
Integrating a choice experiment into an agent-based model to simulate climate-change induced migration: The case of the Mekong River Delta, Vietnam 将选择实验整合到基于代理的模型中,以模拟气候变化引发的移民:以越南湄公河三角洲为例
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-01 DOI: 10.1016/j.jocm.2023.100428
Tra Thi Trinh , Alistair Munro

Forecasting the future impact of climate change on migration is difficult, for many reasons, including the interactive and dynamic nature of many decisions and the heterogeneity of behavior. One popular solution, agent-based models (ABM) cope well with dynamics and heterogeneity, but often lack rigorous foundations in terms of individual behavior. Moreover, given limited exposure to actual climate change, it can be a challenge to build adequate behavioral models of migration choice based on historical data. To tackle this issue, we build an ABM of future migration using a bespoke choice experiment (CE) designed to examine intention to migrate among farmers living in the Vietnamese Mekong Delta (VMD). In the CE, respondents are asked to make migration choices for scenarios constructed using six attributes: drought intensity, flood frequency, income gain from migration, migration networks, neighbors' choice, and crop choice restriction. The simulation runs to 2050 and is based on two scenarios of future global emissions of greenhouse gases—Representative Concentration Pathway (RCP) 4.5 and RCP8.5. The results suggest potentially high levels of migration as a result of climate change and the particular importance of positive feedback from pre-existing migration and neighbor's choices. The results also suggest that crop-restriction regulations have a significant impact on migration for coastal provinces of VMD. Finally, we find that migration drivers vary significantly across provinces, which suggests the policymakers point to targeted action for each province. In summary, the study demonstrates how integrating CE into ABM can foster the predictive modeling of climate-induced migration.

预测气候变化对移民的未来影响很困难,原因有很多,包括许多决策的互动性和动态性以及行为的异质性。一种流行的解决方案是基于代理的模型(ABM),它能很好地处理动态和异构性,但在个体行为方面往往缺乏严格的基础。此外,鉴于实际气候变化的影响有限,根据历史数据建立适当的移民选择行为模型可能是一项挑战。为了解决这个问题,我们使用定制选择实验(CE)建立了未来移民的ABM,该实验旨在研究生活在越南湄公河三角洲(VMD)的农民的移民意向。在CE中,受访者被要求为使用六个属性构建的情景做出移民选择:干旱强度、洪水频率、移民收入收益、移民网络、邻居的选择和作物选择限制。该模拟将持续到2050年,基于未来全球温室气体排放的两种情景——代表性浓度路径(RCP)4.5和RCP8.5。研究结果表明,气候变化可能会导致高水平的移民,而先前存在的移民和邻居选择的积极反馈尤为重要。研究结果还表明,作物限制条例对VMD沿海省份的移民有显著影响。最后,我们发现各省的移民驱动因素差异很大,这表明政策制定者针对每个省份采取了有针对性的行动。总之,该研究表明,将CE纳入ABM可以促进气候引发移民的预测建模。
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引用次数: 0
NP4VTT: A new software for estimating the value of travel time with nonparametric models NP4VTT:一种用非参数模型估计旅行时间值的新软件
IF 2.4 3区 经济学 Q1 ECONOMICS Pub Date : 2023-09-01 DOI: 10.1016/j.jocm.2023.100427
José Ignacio Hernández, Sander van Cranenburgh

Two-attribute-two-alternative stated choice experiments are widely used to infer the Value-of-Travel-Time (VTT) distribution. Two-attribute-two-alternative stated choice experiments have the advantage that their data can be analysed using nonparametric models, which allow for the inference of the VTT distribution without having to impose assumptions on its shape. However, a software package that enables researchers to estimate nonparametric models promptly is currently lacking. As a result, nonparametric models are underused. This paper aims to fill this software void. It presents NP4VTT, a Python package that enables researchers to estimate and compare nonparametric models in a fast and convenient way. It comprises five nonparametric models for estimating the VTT distribution from data coming from two-attribute-two-alternative stated choice experiments. We illustrate the use of NP4VTT by applying it to the Norwegian 2009 VTT data. We hope this software package will help researchers studying the VTT make more informed decisions concerning the shape of the VTT distribution and encourages the use and development of nonparametric models for choice behaviour analyses.

二属性二选择陈述选择实验被广泛用于推断旅行时间值(VTT)分布。双属性两种可选陈述选择实验的优点是,可以使用非参数模型来分析它们的数据,这允许推断VTT分布,而不必对其形状强加假设。然而,目前还缺乏一个使研究人员能够及时估计非参数模型的软件包。因此,非参数模型没有得到充分利用。本文旨在填补这一软件空白。它介绍了NP4VTT,这是一个Python包,使研究人员能够以快速方便的方式估计和比较非参数模型。它包括五个非参数模型,用于根据来自两个属性的两个备选陈述选择实验的数据来估计VTT分布。我们通过将NP4VTT应用于挪威2009年VTT数据来说明它的使用。我们希望这个软件包将帮助研究VTT的研究人员对VTT分布的形状做出更明智的决定,并鼓励使用和开发用于选择行为分析的非参数模型。
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引用次数: 0
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Journal of Choice Modelling
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