What is the Impact of Non-Randomness on Random Choice Models?

2019 ◽  
Author(s):  
Ruxian Wang
Author(s):  
Ruxian Wang

Problem definition: This paper examines the impact of nonrandomness on random choice models and studies various operations problems under the new discrete choice models. Academic/practical relevance: The literature often assumes that the random utility components follow some independent and identically distributed distribution. This assumption is too restrictive in some real-world scenarios, because, for example, consumers may have known well about the attribute values for the product that they have repeatedly purchased. Methodology: We adopt the random utility maximization framework and characterize the choice probabilities when the utility of some alternative is deterministic. The log-likelihood function is jointly concave in the attribute coefficients under the linear utility-attribute assumption; an expectation-maximization algorithm is developed to overcome the missing data issue in estimation. Results: Surprisingly, if the utility of a particular product is deterministic, the assortment problem is still polynomial-time solvable, whereas if the utility of the no-purchase option is deterministic, the decision problem corresponding to the assortment optimization is NP-complete. We show that the price minus the reciprocal of price sensitivity is product invariant at optimality, which helps to simplify the multiproduct pricing problems. Managerial implications: Empirical study on real data shows that incorporating nonrandomness into random choice models can increase model fitting and prediction accuracy. Failure of accounting for the impact of nonrandomness may result in substantial losses.


Author(s):  
Eleonora Sottile ◽  
Francesco Piras ◽  
Italo Meloni

There is ample consensus that, besides objective characteristics, psycho-attitudinal factors play a key role in influencing people’s mode choice. Hybrid choice models use these theoretical frameworks so as to include latent constructs for capturing the impact of subjective factors on mode choice. But recent work in transportation research raised the question about the ability of hybrid choice models to derive policy implications that aim to change travel behavior, given the focus on cross-sectional data. To address this problem we designed a survey for collecting longitudinal data (socio-economic and psycho-attitudinal) to evaluate, on the one hand, the long-term effects on travel mode choice of the implementation of a new light rail line in the metropolitan area of Cagliari (Italy), on the other to detect any changes in the psycho-attitudinal factors and socio-economic characteristics after implementation of those measures. In particular, the objective of the study is to analyze whether these changes in individual characteristics are able to affect mode choice from a modeling perspective, through the specification and estimation of hybrid models. Our results show that latent variables were not significantly different over waves, showing that the impact of the psychological construct remained stable over time, even after the introduction of the new light rail. Additionally, we found some evidence that the variables that explain the latent variables could change over time.


2009 ◽  
Vol 5 (2) ◽  
pp. 177-193
Author(s):  
Vojislav B. Mišić ◽  
Jelena Mišić

Cognitive radio technology necessitates accurate and timely sensing of primary users' activity on the chosen set of channels. The simplest selection procedure is a simple random choice of channels to be sensed, but the impact of sensing errors with respect to primary user activity or inactivity differs considerably. In order to improve sensing accuracy and increase the likelihood of finding channels which are free from primary user activity, the selection procedure is modified by assigning different sensing probabilities to active and inactive channels. The paper presents a probabilistic analysis of this policy and investigates the range of values in which the modulation of sensing probability is capable of maintaining an accurate view of the status of the working channel set. We also present a modification of the probability modulation algorithm that allows for even greater reduction of sensing error in a limited range of the duty cycle of primary users' activity. Finally, we give some guidelines as to the optimum application ranges for the original and modified algorithm, respectively.


2021 ◽  
Author(s):  
Lissy La Paix ◽  
Abu Toasin Oakil ◽  
Frank Hofman ◽  
Karst Geurs

AbstractStudies on the impact of changes in travel costs on car and public transport use are typically based on cross-sectional travel survey data or time series analysis and do not capture intrapersonal variation in travel patterns, which can result in biased cost elasticities. This paper examines the influence of panel effects and inertia in travel behaviour on travel cost sensitiveness, based on four waves of the Mobility Panel for the Netherlands (comprising around 90,000 trips). This paper analyses the monetary costs of travel. Panel effects reflect (within wave) intrapersonal variations in mode choice, based on three-day trip diary data available for each wave. The impact of intrapersonal variation on cost sensitiveness is shown by comparing mode choice models with panel effects (mixed logit mode choice models with error components) and without panel effects (multinomial logit models). Inertia represents variability in mode choice between waves, measured as the effect of mode choice decisions made in a previous wave on the decisions made in the current wave. Additionally, all mode choice models include socio-economic and spatial variables but also mode preferences and life events. The effect of inertia on travel cost elasticities is measured by estimating mixed logit mode choice models with and without inertia effects. The main conclusion is that the inclusion of intrapersonal effects tends to increase cost sensitiveness whereas the inclusion of inertia effects decreases travel cost sensitiveness for car and public transport modes. Car users are identified as inert travellers, whereas public transport users show a lower tendency to maintain their usual mode choice. This paper reveals the inertia effects over four waves of repeated respondent’s data repeated yearly.


1979 ◽  
Vol 16 (1) ◽  
pp. 102-110 ◽  
Author(s):  
Paul W. Miniard ◽  
Joel B. Cohen

Behavioral intentions often have been used as a surrogate for actual behavior in choice models and to reflect the impact of marketing variables. The Fishbein behavioral intentions model posits two determinants of behavioral intentions: a personal or attitudinal component and a social influence or normative component. The authors use an experimental methodology to examine aspects of this model's construct validity. Certain operational problems are identified and related to underlying conceptual difficulties in separating these two components.


2021 ◽  
Vol 13 (5) ◽  
pp. 2993
Author(s):  
Gustavo García-Melero ◽  
Rubén Sainz-González ◽  
Pablo Coto-Millán ◽  
Alejandra Valencia-Vásquez

In recent years, sustainable mobility policy analysis has used Hybrid Choice Models (HCM) by incorporating latent variables in the mode choice models. However, the impact on policy analysis outcomes has not yet been determined with certainty. This paper aims to measure the effect of HCM on sustainable mobility policy analysis compared to traditional models without latent variables. To this end, we performed mode choice research in the city of Santander, Spain. We identified two latent variables—Safety and Comfort—and incorporated them as explanatory variables in the HCM. Later, we conducted a sensitivity study for sustainable mobility policy analysis by simulating different policy scenarios. We found that the HCM amplified the impact of sustainable mobility policies on the modal shares, and provided an excessive reaction in the individuals’ travel behavior. Thus, the HCM overrated the impact of sustainable mobility policies on the modal switch. Likewise, for all of the mode choice models, policies that promoted public transportation were more effective in increasing bus modal shares than those that penalized private vehicles. In short, we concluded that sustainable mobility policy analysis should use HCM prudently, and should not set them as the best models beforehand.


2005 ◽  
Vol 35 (4) ◽  
pp. 691-712 ◽  
Author(s):  
THOMAS GSCHWEND ◽  
DIRK LEUFFEN

In this article the impact of voters' regime preferences, i.e. their preferences for either divided or unified government, on their voting behaviour, is analysed. The theory expounded, combining behavioural as well as institutional approaches, predicts that voters weigh their regime against their partisan preferences to derive their vote choice. This theory and its implications are tested on the 2002 French legislative elections using a multinomial logit set-up. The results indicate that regime voting adds to the explanatory power of traditional vote-choice models. Statistical simulations provide further evidence that regime preferences play a decisive role in the voting booth, especially for voters who are not politically ‘anchored’.


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