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on Discrete Choice Models |
| By: | Grashuis, Jasper; Parcell, Joe; Gao, Lijing |
| Abstract: | Consumers of products from food animals in general have a positive attitude toward the animal welfare attribute. However, animal welfare has various dimensions (e.g. cage-free, grass-fed, pain management), and there is little research to inform if the animal welfare attribute and its dimensions are complements or substitutes. We address the gap in the literature with a choice experiment to elicit preferences for the animal welfare attribute and the pain management attribute from 704 beef steak and 1, 261 milk consumers in the United States. Using WTP-space mixed logit models, we find that (1) in isolation animal welfare and pain management each capture a positive and significant WTP, and (2) in combination animal welfare and pain management are complementary and raise total WTP. Additionally, we find certification of the pain management attribute by private or public institutions is of importance to the magnitude of the WTP. |
| Keywords: | Agribusiness |
| Date: | 2025–09–07 |
| URL: | https://d.repec.org/n?u=RePEc:ags:umcowp:369046 |
| By: | Akshay Vij; Stephane Hess |
| Abstract: | The link between attitudes and behaviour has been a key topic in choice modelling for two decades, with the widespread application of ever more complex hybrid choice models. This paper proposes a flexible and transparent alternative framework for empirically examining the relationship between attitudes and behaviours using latent class choice models (LCCMs). Rather than embedding attitudinal constructs within the structural model, as in hybrid choice frameworks, we recover class-specific attitudinal profiles through posterior inference. This approach enables analysts to explore attitude-behaviour associations without the complexity and convergence issues often associated with integrated estimation. Two case studies are used to demonstrate the framework: one on employee preferences for working from home, and another on public acceptance of COVID-19 vaccines. Across both studies, we compare posterior profiling of indicator means, fractional multinomial logit (FMNL) models, factor-based representations, and hybrid specifications. We find that posterior inference methods provide behaviourally rich insights with minimal additional complexity, while factor-based models risk discarding key attitudinal information, and fullinformation hybrid models offer little gain in explanatory power and incur substantially greater estimation burden. Our findings suggest that when the goal is to explain preference heterogeneity, posterior inference offers a practical alternative to hybrid models, one that retains interpretability and robustness without sacrificing behavioural depth. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.08373 |
| By: | Thomas O. Hancock; Stephane Hess; Charisma F. Choudhury |
| Abstract: | Choice models for large-scale applications have historically relied on economic theories (e.g. utility maximisation) that establish relationships between the choices of individuals, their characteristics, and the attributes of the alternatives. In a parallel stream, choice models in cognitive psychology have focused on modelling the decision-making process, but typically in controlled scenarios. Recent research developments have attempted to bridge the modelling paradigms, with choice models that are based on psychological foundations, such as decision field theory (DFT), outperforming traditional econometric choice models for travel mode and route choice behaviour. The use of physiological data, which can provide indications about the choice-making process and mental states, opens up the opportunity to further advance the models. In particular, the use of such data to enrich 'process' parameters within a cognitive theory-driven choice model has not yet been explored. This research gap is addressed by incorporating physiological data into both econometric and DFT models for understanding decision-making in two different contexts: stated-preference responses (static) of accomodation choice and gap-acceptance decisions within a driving simulator experiment (dynamic). Results from models for the static scenarios demonstrate that both models can improve substantially through the incorporation of eye-tracking information. Results from models for the dynamic scenarios suggest that stress measurement and eye-tracking data can be linked with process parameters in DFT, resulting in larger improvements in comparison to simpler methods for incorporating this data in either DFT or econometric models. The findings provide insights into the value added by physiological data as well as the performance of different candidate modelling frameworks for integrating such data. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.18068 |
| By: | Catalina Posada-Borrero (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier); Driss Ezzine-De-Blas (UPR Forêts et Sociétés - Forêts et Sociétés - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Cirad-ES - Département Environnements et Sociétés - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement); Emmanuelle Lavaine (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier); Sébastien Roussel (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier) |
| Abstract: | This paper investigates the preferences of smallholder farmers residing in the agricultural frontier of the Colombia Amazon's Forest, specifically in the department of Guaviare, regarding interventions aimed at promoting the adoption of sustainable land-use systems. We focus on the transition from extensive livestock systems to sustainable livestock systems and agroforestry systems. The adoption of silvopastoral systems presents a significant opportunity for sustainable development, offering land-saving advantages that can be leveraged by programs to encourage other sustainable value chains, such as timber in agroforestry systems. Through a discrete choice experiment, we examine farmer preferences concerning land allocation, cash bonuses for permanence, and technical assistance. Additionally, we assess how socioeconomic factors influence farmers' decision-making in participating in such programs. Our findings indicate that while farmers exhibit a preference for allocating land to silvopastoral systems over agroforestry, they also show considerable interest in interventions involving a small proportion of timber in agroforestry systems. Furthermore, our analysis reveals that permanence bonuses tied to individual effort can enhance participation, while collective goals may hinder it. |
| Keywords: | Discrete choice experiment : Incentive programs, Payments for Ecosystem Services (PES), Silvopastoral systems (SPS), Agroforestry, Cash bonus, Colombia, Guaviare |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05234900 |
| By: | Kira Lancker (Department of Food and Resource Economics, University of Copenhagen); Christopher B. Barrett (Charles H. Dyson School of Applied Economics and Management, Cornell University; Jeb E. Brooks School of Public Policy, Cornell University); Kathryn J. Fiorella (Department of Public & Ecosystem Health, Cornell University); Christopher M. Aura (Kenya Marine and Fisheries Research Institute, Kisumu); Hezron Awandu (Kenya Marine and Fisheries Research Institute, Kisumu); Fonda J. Awuor (Kenya Marine and Fisheries Research Institute, Kisumu); Patrick Otuo (Kenya Marine and Fisheries Research Institute, Kisumu) |
| Abstract: | Fish consumers are often challenged by tradeoffs between nutritional benefits and contaminant risks, which increase due to environmental pollution. Health campaigns and labeling initiatives can guide decision-making by providing information both on contaminant risk and nutritional value of a product, but it is not well understood how consumers react to such complex dual labels. We use data from a stated choice experiment in Kenya’s Lake Victoria region to study how consumers respond to dual labels on fish products, and how their responses to each label interact. We focus on the tradeoff between polyunsaturated fatty acids and contamination with microcystin, a toxin that accumulates in fish during harmful algae blooms. Our findings suggest that, faced with a dual information policy, consumers react rationally to dual health attribute labeling, and that nutrient labels and contaminant warnings can function concurrently, indeed even be mutually reinforcing, but pose a risk of inadvertently concentrating unhealthful consumption in less responsive subpopulations. |
| Keywords: | food labels, fish consumer behavior, interdependent preferences, choice experiment, polyunsaturated fatty acids, algal blooms, Lake Victoria |
| JEL: | D12 I18 Q22 Q18 Q51 O13 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:foi:wpaper:2025_01 |
| By: | Mohamed Khalafalla; Tejal Mulay; Shonda L Bernadin |
| Abstract: | Change orders (COs) are a common occurrence in construction projects, leading to increased costs and extended durations. Design-Bid-Build (DBB) projects, favored by state transportation agencies (STAs), often experience a higher frequency of COs compared to other project delivery methods. This study aims to identify areas of improvement to reduce CO frequency in DBB projects through a quantitative analysis. Historical bidding data from the Florida Department of Transportation (FDOT) was utilized to evaluate five factors, contracting technique, project location, type of work, project size, and duration, on specific horizontal construction projects. Two DBB contracting techniques, Unit Price (UP) and Lump Sum (LS), were evaluated using a discrete choice model. The analysis of 581 UP and 189 LS projects revealed that project size, duration, and type of work had a statistically significant influence on the frequency of change orders at a 95% confidence level. The discrete choice model showed significant improvement in identifying the appropriate contract type for a specific project compared to traditional methods used by STAs. By evaluating the contracting technique instead of project delivery methods for horizontal construction projects, the use of DBB can be enhanced, leading to reduced change orders for STAs. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.00281 |
| By: | Alonso Alfaro-Ureña (Department of Economic Research, Central Bank of Costa Rica); Paolo Zacchia (Charles University, Czech Academy of Sciences, IZA) |
| Abstract: | We build a model of production network formation that enables econometric estimation of the determinants of supplier choice, like trade costs or matching frictions. The model informs an estimator obtained from a transformation of the multinomial logit likelihood function that conditions on two network statistics: the out-degree of sellers (a sufficient statistic for the seller marginal costs) and the in-degree of buyers (which is pinned down by technology and by “make-or-buy” decisions). In an empirical application about the network effects of a major Costa Rican highway, this estimator registers much smaller estimates than those of a (biased) naive multinomial logit. ***Resumen: Desarrollamos un modelo de formación de redes de producción que permite la estimación econométrica de los determinantes en la elección de proveedores, tales como los costos de comerciar o las fricciones de emparejamiento. El modelo guía un estimador obtenido a partir de una transformación de la función de verosimilitud del logit multinomial, que está condicionado por dos estadísticas de red: el grado de salida de los vendedores (una estadística suficiente para los costos marginales del vendedor) y el “grado de entrada” (in-degree) de los compradores (determinado por la tecnología y las decisiones de “hacer o comprar”). En una aplicación empírica sobre los efectos en red de una importante carretera en Costa Rica, este estimador arroja estimaciones considerablemente menores que las de un logit multinomial ingenuo (y sesgado). |
| Keywords: | Production network, Supplier choice, Conditional logit, Infrastructures, infraestructura, logit condicional, elección de proveedores, redes de producción |
| JEL: | C25 L11 R12 R15 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:apk:doctra:2502 |
| By: | Elżbieta Babula (UG - University of Gdańsk); Juhyun Park (LaMME - Laboratoire de Mathématiques et Modélisation d'Evry - ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise) |
| Abstract: | Tversky and Kahneman's cumulative prospect theory assumes symmetric probability cumulation with regard to the reference point in decision weights. Theoretically, this model should be fixed despite a change in the direction of probability cumulation. We investigate this phenomenon by proposing an alternative model with one-direction probability cumulation. By doing so, we create a reference model that allows us to verify the parameter interactions in cumulative prospect theory specifications. We apply the simultaneous parametric fitting of utility and weighting functions using binary choice data from our own incentivized choice experiment (N = 70). We consider two parametric forms of probability weighting functions, namely, the one-parameter Tversky–Kahneman and two-parameter Prelec functions. We find that the Prelec function is sufficiently flexible to make these two models equivalent, thereby preserving the stability of the utility parameters. We also observe parameter interactions in the other specifications, especially with the Tversky–Kahneman weighting function. |
| Keywords: | parameter interactions, rank-dependent utility, decision weights, cumulative prospect theory |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05231129 |
| By: | Daniel Montoya Herrera (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier); Marc Willinger (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier) |
| Abstract: | Based on a representative sample of the French population (n = 1, 154), we show that there is a positive association between risk tolerance and trust. We rely on, the World Value Survey WVS binary trust measure, and a '0 -10' scale that we decline in three domains: trust in general, family, and co-workers. We also vary the measure of risk tolerance, by considering an incentivized investment task, and a '0 -10' stated preference scale that we decline in three domains: risk tolerance in general, in finance, and health. These variations allow us to test 16 different relations, by crossing four dependent trust variables with four different risk tolerance covariates. After adjusting for multiple testing, we found nine combinations with a strong positive link between risk tolerance and trust in the general population, and that stated risk tolerance measures predict stated trust better than elicited risk measures. |
| Keywords: | risk-aversion, preferences, generalized trust, Behavioral economics |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05234962 |
| By: | Shawn Berry |
| Abstract: | The process of consumer decision-making is multidimensional, and price perception is a very important but still not well-understood dimension for both marketers and consumers. Although heuristics or mental shortcuts are seen as biased and can cause decision errors, consumers tend to use price knowledge heuristics for purchase decisions, sometimes relying on old information. This study examined the effects of individual attitudinal and demographic factors on the ability of 351 respondents to correctly guess the prices of 13 products and services using ANOVA and the development of a seven-factor price perception model using latent variable analysis. While most respondents preferred to either research prices first or compare prices to a similar product, they either systematically underestimated or overestimated the prices of the products. In the ANOVA, brand loyalty, importance of substitute products and knockoff products, how financially well-off the respondent household was growing up, product quality importance, haggling tendency, and level of income were statistically significant predictors of price perception error. Latent variable analysis revealed that demographics, decision making, and price sensitivity factors had the greatest influence on price perception error. Level of education and income, frequency of regret, coupon importance, and how respondents chose to save or spend money were significant latent variables. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.19953 |