Abstract:We develop a general framework that extends choice models by including an explicit representation of the process and context of decision making. Process refers to the steps involved in decision making. Context refers to factors affecting the process, focusing in this paper on social networks. The extended choice framework includes more behavioral richness through the explicit representation of the planning process preceding an action and its dynamics and the effects of context (family, friends, and market) on … Show more
“…Then, two methods based on modelling: discrete choice and hybrid choice models. The latter including attitudes and perceptions seems to be a more powerful tool for integrating the economical variables with a deep attitudinal construct, that is latent variable (Ben-Akiva et al, 2012). This paper approaches the question of the acceptability of road pricing by examining the collected primary data and integrating socioeconomic and psychological considerations using hybrid model.…”
Section: State Of Research Methods On the Acceptability Of Road Pricingmentioning
Several international studies have analyzed the acceptability of road pricing schemes by means of an attitude survey in combination with the results of a stated choice experiment using both a descriptive analysis and a discrete-choice model with binary choice ("accept" or "not accept" the toll). However, the use of hybrid discrete choice models constitutes an innovative alternative for integrating subjective attitudes and perceptions deriving from the survey of attitudes with the more objective variables from the stated choice experiment. This paper analyzes the results of applying these models to measure the acceptability of interurban road pricing among different groups of stakeholders (road freight and passenger operators, highway concessionaires, and associations of private car users) with qualitatively significant opinions on road pricing measures. Our results show that hybrid models are better suited to explaining the acceptability of a road pricing scheme by different groups of stakeholders than a separate analysis of the survey of attitudes and a discrete-choice model applied on a stated choice experiment. A particular finding was that the strong psycho-social latent variable of the perception of fairness explains the rejection or acceptance of a toll scheme by road stakeholders.
“…Then, two methods based on modelling: discrete choice and hybrid choice models. The latter including attitudes and perceptions seems to be a more powerful tool for integrating the economical variables with a deep attitudinal construct, that is latent variable (Ben-Akiva et al, 2012). This paper approaches the question of the acceptability of road pricing by examining the collected primary data and integrating socioeconomic and psychological considerations using hybrid model.…”
Section: State Of Research Methods On the Acceptability Of Road Pricingmentioning
Several international studies have analyzed the acceptability of road pricing schemes by means of an attitude survey in combination with the results of a stated choice experiment using both a descriptive analysis and a discrete-choice model with binary choice ("accept" or "not accept" the toll). However, the use of hybrid discrete choice models constitutes an innovative alternative for integrating subjective attitudes and perceptions deriving from the survey of attitudes with the more objective variables from the stated choice experiment. This paper analyzes the results of applying these models to measure the acceptability of interurban road pricing among different groups of stakeholders (road freight and passenger operators, highway concessionaires, and associations of private car users) with qualitatively significant opinions on road pricing measures. Our results show that hybrid models are better suited to explaining the acceptability of a road pricing scheme by different groups of stakeholders than a separate analysis of the survey of attitudes and a discrete-choice model applied on a stated choice experiment. A particular finding was that the strong psycho-social latent variable of the perception of fairness explains the rejection or acceptance of a toll scheme by road stakeholders.
“…The output of the decision-making process is determined by an interaction between impulsive or emotionally based systems responding to potential rewards and losses, and reflective or cognitive control systems controlling long-term goals (Visser et al 2011). The description of choice behavior can be given more structure by describing choice behavior as a decision making process involving two dimensions: process and context (Ben-Akiva et al 2012). Process refers to the steps involved in decision-making, while context refers to the factors affecting the process.…”
The aim of this paper is to develop a methodological framework for the incorporation of social interaction effects into choice models. The developed method provides insights for modeling the effect of social interaction on the formation of psychological factors (latent variables) and on the decision-making process. The assumption is based on the fact that the way the decision maker anticipates and processes the information regarding the behavior and the choices exhibited in her/his social environment, affects her/ his attitudes and perceptions, which in turn affect her/his choices. The proposed method integrates choice models with decision makers' psychological factors and latent social interaction. The model structure is simultaneously estimated providing an improvement over sequential methods as it provides consistent and efficient estimates of the parameters. The methodology is tested within the context of a household aiming to identify the social interaction effects between teenagers and their parents regarding walking-loving behavior and then the effect of this on mode to school choice behavior. The sample consists of 9,714 participants aged from 12 to 18 years old, representing 21 % of the adolescent population of Cyprus. The findings from the case study indicate that if the teenagers anticipate that their parents are walking lovers, then this increases the probability of teenagers to be walking-lovers too and in turn to choose walking to school. Generally, the findings from the application result in: (a) improvements in the explanatory power of choice models, Transportation (2014) 41:1263-1285 DOI 10.1007 (b) latent variables that are statistically significant, and (c) a real-world behavioral representation that includes the social interaction effect.
“…The integrated choice and latent variable (ICLV) model is an extended discrete choice model, in which next to preferences, these constructs are modelled to account for heterogeneity in preferences. It offers a general econometric framework to supplement economic theory with concepts or theories from social sciences Walker et al, 2007;Ben-Akiva et al, 2012). Some of the process (steps involved in decision making) and context (factors affecting the process) are taken into account, and so enhance the behavioural representation in economic models.…”
Section: Methodsmentioning
confidence: 99%
“…The application of an integrated choice and latent variable model approach from marketing and transport economics in chapter 6 is novel to the agricultural and animal health economics literature. This model is based on generalised random utility theory (Walker, 2001;Walker and Ben-Akiva, 2002;Ben-Akiva et al, 2012) and offers a general econometric framework to supplement economic theory with concepts or theories from social sciences. The idea of integrating social-psychological constructs into choice models to explain preference heterogeneity is not new (e.g.…”
Section: Main Scientific Contributionsmentioning
confidence: 99%
“…Here, farmers' behaviour in the ABM is modelled using the integrated choice and latent variable model (ICLV) framework. The ICLV model offers a general econometric framework to supplement economic theory with concepts or theories from other social sciences Ben-Akiva et al, 2012). Such models are seen as a promising way to model individual behaviour in ABM (Bruch and Atwell, 2015;Klabunde and Willekens, 2016).…”
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