Analysis Of Choice Behavior Research Articles

Modeling Route Choice Behavior

Most route choice models are related to revealed choice behavior and are estimated by adding alternative paths to observed routes. This paper focuses on the effects of choice set composition in route choice modeling by designing an experimental analysis of actual route choice behavior of individuals driving habitually from home to work in an urban network. The numerical analysis concentrates on a qualitative perspective, by considering path sets built with different generation techniques, and a quantitative perspective, by accounting for path sets constructed with sample size reduction from each initial choice set. Comparison of prediction accuracy across different choice sets suggests that a recently developed branch and bound algorithm generates heterogeneous routes that allow for estimating models with better prediction abilities with respect to the outcomes of the drivers' actual choices. Further, comparison of route choice models across different choice set compositions indicates that nonnested structures, such as C-logit and path size logit, yield more robust parameter estimates.

Development of Household Discrete Choice Model Incorporating Multiple Decision-Marking Rules and Application to Analysis of Car Type Choice

This paper developed a household choice model incorporating heterogeneous group decision-making rules using latent class modeling approach. In addition, the model can consider correlation between alternatives by paired combinatorial logit modeling approach. This paper deals with the following three types of household choice rules: additive, max-min and maxmax rules, and applies the model to household car type choice behavior analysis. As a result, the model with additive and max-max roles has the highest model performance, and household characteristics and life stage are important factors explaining household decision-marking rules.

A Study on the Railway Routes Choice Sets for Commuters

The railway route choice behavior analysis involves into tow stages; first generating a choice set and then, modeling route choice behavior based on the given choice set. The main interest of the analysis, until now, has been placed on a choice model itself a certain choice set. On the other hand, the generation process of a choice set has not been analyzed yet sufficiently. Therefore the study focuses on the generation process of a choice set, and proposes the rule of generating route choice set.

Airport, airline and access mode choice in the San Francisco Bay area

Abstract. In this article, we present an analysis of air travel choice behaviour in the San Francisco Bay area. The analysis extends existing work by considering the simultaneous choice by passengers of a departure airport, an airline, and an access mode. The analysis shows that several factors, most notably flight frequency and in‐vehicle access time, have a significant overall impact on the attractiveness of an airport, airline and access mode combination, while factors such as fare and aircraft size have a significant effect only in some of the population subgroups. The analysis highlights the need to use separate models for resident and non‐resident travellers, and to segment the population by journey purpose. The analysis also shows that important gains can be made through the inclusion of airport‐inertia variables, and through using a nonlinear specification for the marginal returns of increases in flight frequency. In terms of model structure, the results suggest that the use of the different possible two‐level nested logit models leads to modest, yet significant gains in model fit over the corresponding multinomial logit models, which already exhibit very high levels of prediction performance.

Self-reported computer criminal behavior: A psychological analysis

The current research study replicated a study by Rogers et al. (Rogers M, Smoak ND, Liu J. Self-reported criminal computer behavior: a big-5, moral choice and manipulative exploitive behavior analysis. Deviant Behavior 2006;27:1–24) and examined the psychological characteristics, moral choice, and exploitive manipulative behaviors of self-reported computer criminals and non-computer criminals. Seventy-seven students enrolled in an information technology program participated in the web-based study. The results of the study indicated that the only significant variable for predicting criminal/deviant computer behavior was extraversion. Those individuals self-reporting criminal computer behavior were significantly more introverted than those reporting no criminal/deviant computer behavior. This finding is contrary to the findings of the previous study. The current study confirmed that the four psychometric instruments were reliable for conducting research in the field of criminal/deviant computer behavior. The impact of the findings on the field of digital forensic investigations is discussed as well as possible reasons for the apparent contradiction between the two studies.

Self-reported Deviant Computer Behavior: A Big-5, Moral Choice, and Manipulative Exploitive Behavior Analysis

The current study examined differences between individuals self-reporting computer-related deviant behaviors and those reporting no computer-related deviant behaviors. The study focused on the Big-5 personality characteristics, moral decision making, and exploitive manipulative amoral dishonesty characteristics. It was hypothesized that computer deviants would be more introverted, exploitive and manipulative, neurotic, less open to experience, and lower on social moral choice than individuals not reporting deviant computer-related behavior. As predicted, computer deviants scored lower on social moral choice and were more exploitive and manipulative. Implications of these findings and suggestions for further research in this area are discussed.

Users of Transport Modes and Multimodal Travel Behavior Steps Toward Understanding Travelers' Options and Choices

Results are presented from analysis of individual mode choice behavior in the longitudinal section in Germany. The findings show that about half of German drivers also use public transport. Because they use different modes, they can be characterized as multimodals. This group will constitute an increasing share of the public transport clientele in coming decades because the decline of captive public transport riders is foreseeable. Therefore it is necessary to understand multimodal behavior because in an environment where travelers have increasing options, it is important to know how they make use of their options. It was found that multimodals employ public transport for specific purposes, whereas the car is universal. Less than 20% of multimodals use public transport on a regular basis, for example, to commute. Most multimodals use it occasionally. Multimodals opt for public transport in specific situations because it is the better option and not because there is no car available. Although for families ...

Users of Transport Modes and Multimodal Travel Behavior

Results are presented from analysis of individual mode choice behavior in the longitudinal section in Germany. The findings show that about half of German drivers also use public transport. Because they use different modes, they can be characterized as multimodals. This group will constitute an increasing share of the public transport clientele in coming decades because the decline of captive public transport riders is foreseeable. Therefore it is necessary to understand multimodal behavior because in an environment where travelers have increasing options, it is important to know how they make use of their options. It was found that multimodals employ public transport for specific purposes, whereas the car is universal. Less than 20% of multimodals use public transport on a regular basis, for example, to commute. Most multimodals use it occasionally. Multimodals opt for public transport in specific situations because it is the better option and not because there is no car available. Although for families the car is often the better choice, single persons tend to be more multimodal. Commuting by public transport was found to be a gateway to the use of public transport for other purposes.

A Method of Detecting Competitors of a Store and Evaluating their Attractiveness in Micro Scale Retail Environment

The availability of data set itself and the method of handling the data set are essential factors to achieve effective decision making in retail marketing, especially for small privately managed retail stores. In the field of retail and marketing geography, attractiveness of a store is analyzed with questionnaire survey and logit model in general. However, the problem is that huge cost is required for the process, which becomes more difficult under a micro scale retail environment. Considering the fact that small retail stores often have their own purchase history data of customers, the cost is reduced if an effective method exists that is applicable using purchase history data only. Hence, the purpose of this paper is focused on evaluating and detecting competitors of a small retail store, with limited data availability, to understand the status of its market area from the geographical aspect by clarifying where its own strong competitors are located. The method uses a probabilistic store choice model, which is usually estimated from the data of consumers' store choice behavior collected by a questionnaire survey. Instead of such detailed but costly data, this paper uses actual sales data of the target store to estimate the model. The method is applied to simulated choice behavior, then, to actual data based on the findings understood from the simulated choice behavior analysis. Results show that the method effectively detects strong competitors of a store. Furthermore, the result may provide a guideline for the store to establish an effective marketing strategy.

The Use of Stated Preference Model in Travel Itinerary Choice Behavior

This study uses the Stated Preference Method and Multinomial Logit Model to examine the choice behavior of a sample of consumers who chose between six tour alternatives that differed according to five variables: specifics of tour, price, duration of tour, types of flight, and arrangement of free time. The results indicate that most of the consumers were affected by the price of the travel product when they were selecting the package tour. The duration of tour and type of flight were important factors to respondents under 40 years old. The older the tourists were, the more attention they paid to the contents of the tours. After estimating by MNL, the results also showed that the goodness-of-fit of the model was reasonably good. By conducting a strategic simulation of the third tour alternative, which had a higher market share, the best strategy was to reduce the price by 5% in order to increase the market share. The study demonstrates the usefulness of the stated preference model in the analysis of choice behavior for travel itinerary.

On Adaptation, Maximization, and Reinforcement Learning Among Cognitive Strategies.

Analysis of binary choice behavior in iterated tasks with immediate feedback reveals robust deviations from maximization that can be described as indications of 3 effects: (a) a payoff variability effect, in which high payoff variability seems to move choice behavior toward random choice; (b) underweighting of rare events, in which alternatives that yield the best payoffs most of the time are attractive even when they are associated with a lower expected return; and (c) loss aversion, in which alternatives that minimize the probability of losses can be more attractive than those that maximize expected payoffs. The results are closer to probability matching than to maximization. Best approximation is provided with a model of reinforcement learning among cognitive strategies (RELACS). This model captures the 3 deviations, the learning curves, and the effect of information on uncertainty avoidance. It outperforms other models in fitting the data and in predicting behavior in other experiments.

Small community airport choice behavior analysis: A case study of GTR

The issue of airport selection attracts considerable attention. However, most studies focus on using advanced discrete choice models to analyze airport choice behavior in metropolitan areas with several closely located, competing airports. This paper addresses passengers’ choice behavior in selecting between local small community airports and more distant major commercial airport. It looks at factors affecting air travelers’ airport choice behavior in cities with small community air service. Data relating to the Golden Triangle Regional Airport in Mississippi is used in logistic regressions to identify the key factors that influence air travelers’ airport choices. Ticket price, experience with Golden Triangle Regional Airport and flight schedule were found to be the strongest effects.

Neural architecture of choice behaviour in a concurrent interval schedule.

Concurrent interval schedules are classic experimental paradigms that are traditionally employed in psychological research on choice behaviour. To analyse the neural basis of choice in a concurrent fixed interval schedule, pigeons were trained to peck on two response keys. Responses were differentially rewarded in key specific short or long time intervals (SI vs. LI). Using tetrodotoxin, we reversibly blocked the neostriatum caudolaterale (NCL, the avian functional equivalent of the prefrontal cortex), avian caudate-putamen and nucleus accumbens to examine their contribution. A detailed analysis of baseline choice behaviour revealed that response distribution and key affinity were determined by cued or time-related expectancy for rewards on the SI key. The pigeons' response frequency increased on the SI key and decreased on the LI key with increasing temporal proximity to the SI reward and pigeons switched to the LI key after reward delivery. Pecking bursts on the LI key were negatively correlated with bursts on the SI key. Neostriatum caudolaterale inactivation did not affect pecking activity per se but interfered with reward-related temporal modulation of pecking frequency, switching pattern and coupling of LI to SI pecks. Blockade of caudate-putamen resulted in a complete behavioural halt, while inactivation of nucleus accumbens diminished operant behaviour without affecting consummatory responses. These data suggest that the NCL is tuned via indirect striato-pallial projections to integrate cued or time-related reward expectancy into a response selection process in order to set, maintain or shift goals. The NCL possibly feeds forward the resulting motor commands to the caudate-putamen for execution.

An Analysis of Residential Location Choice Behaviour in Oxfordshire, Uk: A Combined Stated Preference Approach

This paper proposes and applies a combined stated preference approach in order to estimate residential location choice behaviour in Oxfordshire, UK. The estimation results demonstrate the potentials for the combined estimation of two stated preference experiments. Our findings show that the transport related attributes have significant impacts on residential location choice. The estimated monetary values of one minute of commuting time and one pence of commuting cost are equivalent to £6,339 and £883 with regard to house price, while the estimated value of time is 7.18 pence per minute. Higher quality of school has a significantly positive effect, while higher density and central city location have a significantly negative impact on residential location choice. The simulation results based on the model estimates suggest that the best location for new housing development varies with commuting patterns, spatial job distribution, and the changes of attributes influencing residential location choice.

A Sequential Method for Combining Random Utility Model and Fuzzy Inference Model

In the analysis of choice behavior problem, uncertainty can be divided into two different types: randomness and vagueness. Random utility model and fuzzy inference model have been widely used to consider the randomness and the vagueness, respectively. Despite the necessity of simultaneously considering both uncertainties in choice behavior analysis, few literatures have tried to combine the two types of choice behavior models. Therefore, the aim of this paper is to suggest a model combining the randomness and the vagueness in the context of driver’s route choice behavior under traffic information. To estimate the combined model, a sequential method is suggested as follows: First, a latent class multinomial logit model (LCML) is developed to consider the randomness of route choice behaviors and to analyze the heterogeneity among drivers. Second, a fuzzy inference model is developed to consider the vagueness. Finally, the combined model is established by combining the estimation results of the LCML and the fuzzy inference models. The empirical results in this paper show that the combined model can contribute to enhance the explanatory power of the LCML model by effectively incorporating the randomness and the vagueness uncertainty in the choice behavior model.

Port choice behaviour--from the perspective of the shipper

A good or bad points of ports service system may affect the user's port choice behaviour, or even influence the cost of the whole fleet or shipper, so port choice is an important part of port transportation demand behaviour. There are three regions from north, centre to south in the west coast of Taiwan. There are three international container ports (northern, central and southern) on the west coast of Taiwan, with 229 kilometres between the northern and southern ones. This paper focuses one aspect of shippers' port choice behaviour. Through the collection and analysis of data and setting up the model, one knows the preference of shippers' choice. In the past, the method of research on port choice behaviour can be divided into four types, namely descriptive statistics analysis, multi-objective decision analysis, multi-variate analysis and multiple choice analysis. Each method has its characteristics and restriction to make the analysis research differently. This paper first describes the methodology and brings the result of port choice. Using the revealed preference multinomial logical model, the writer proceeds to the analysis of shippers' choice behaviour. In the analysis model, not only the basic choice model was set up, but also the experienced and competitive port choice models were derived. So, it will be easier to understand the affection of the past and present time experience on port choice. It will also know whether the differences of routes, frequencies and port service will make a competition.

Analysis of Shipper's Port Choice Behavior and Domestic Transportation Patterns of Foreign Container Cargo

Analysis of Shipper's Port Choice Behavior and Domestic Transportation Patterns of Foreign Container Cargo

Daniel McFadden and the Econometric Analysis of Discrete Choice

This article describes the contributions of Daniel McFadden to the econometric analysis of discrete choice. Section I overviews the main elements of McFadden's research on discrete choice analysis, and notes some of his other contributions to economics. Section II addresses the fundamental methodological breakthrough that McFadden made in Conditional Logit Analysis of Qualitative Choice Behavior [III, 1974].1 Section III discusses the subsequent development of discrete choice analysis into one of the foundations of modem econometrics. Section IV concludes.

Analysis of Time Allocation, Departure Time, and Route Choice Behavior Under Congestion Pricing

Driver behavior under congestion pricing is analyzed to evaluate the effects of alternative congestion pricing schemes. The analysis, which is based on stated preference survey results, focuses on time allocation, departure time choice, and route choice when a congestion pricing scheme is implemented on toll roads in Japan. A unique feature of the model system of this study is that departure time choice and route choice are analyzed in conjunction with the activities before and after the trip. A time allocation model is developed to describe departure time choice, and a route and departure time choice model is developed as a multinomial logit model with alternatives representing the choice between freeways and surface streets and, for departure time, the choice from among before, during, or after the period when congestion pricing is in effect. The results of the empirical analysis suggest that departing during the congestion pricing period tends to have higher utilities and that a worker and a nonworker have quite different utility functions. The comparative analysis of different congestion pricing schemes is carried out based on the estimated parameters. The results suggest that the probability of choosing each alternative is stable even if the length of the congestion pricing period changes, but a higher congestion price causes more drivers to change the departure time to before the congestion pricing period.

Signal Detection Analysis of Choice Behavior and Aging

The primary research question was whether older adults respond to the contingencies of reinforcement such that they allocate their behavior as predicted by the reinforcement contingencies and discriminative stimuli programmed by the experimenters. Six subjects, ranging in age from 62 to 74 years, participated in 15 experimental sessions. Subjects were instructed to press the “F1” key when they saw a white circle, and to press the “F12” key when they saw a red letter “A.” Responses on the F1 key were reinforced on a variable interval (VI) 30-s schedule (i.e., a VI schedule of reinforcement with 11 arithmetically spaced intervals with a mean of 30 s); F12 key responses were reinforced on a VI 60-s schedule (i.e., a VI schedule of reinforcement with 11 arithmetically spaced intervals with a mean of 60 s). Reinforcers included monetary units (10 cents) and verbal praise. Results indicated positive effects of stimulus control of behavior. Collective false alarms and miss rates represented only 0.05% of the total responses. Also, two thirds of the subjects allocated behavior consistent with the second hypothesis that a denser reinforcement schedule (i.e., the VI 30-s) would cause subjects to respond more quickly to this condition. Implications of the present results for clinical studies of Alzheimer's Disease and dementia, as well as behavior modification strategies with aging individuals, are discussed.