scholarly journals A Stated Choice Model of Sequential Mode and Destination Choice Behaviour for Shopping Trips

1996 ◽  
Vol 28 (1) ◽  
pp. 173-184 ◽  
Author(s):  
H J P Timmermans
Keyword(s):  
Choice Model ◽  
Stated Preference ◽  
Destination Choice ◽  
Sequential Choice ◽  
Design Strategies ◽  
Choice Behaviour ◽  
Research Findings ◽  
Shopping Trips ◽  
Sequential Mode ◽  
Complex Forms

Stated preference and choice models currently used in urban planning are focused on predicting single choices. In this paper the intention is to extend these modelling approaches to the case of sequential choice behaviour. Design strategies and model specifications that allow one to predict sequential choice are discussed. The approach is illustrated in a study of sequential mode and destination choice behaviour for shopping trips. The research findings suggest that the proposed approach may be a valuable extension of currently available stated preference and choice methods to analyse more complex forms of decisionmaking.

scholarly journals Modelling Sequential Choice Processes: The Case of Two-Stop Trip Chaining

1992 ◽  
Vol 24 (10) ◽  
pp. 1483-1490 ◽  
Author(s):  
H Timmermans ◽  
P van der Waerden
Keyword(s):  
Discrete Choice ◽  
Choice Experiments ◽  
Discrete Choice Experiments ◽  
Sequential Choice ◽  
Choice Behaviour ◽  
Suggested Approach ◽  
Shopping Centre ◽  
Trip Chaining ◽  
Choice Sequence ◽  
Research Findings

Traditional decompositional preferences and choice studies are focused on the prediction of single choices, such as choice of shopping centre or transport mode. Discrete choice experiments are used to derive choice models that predict the probability of choosing a choice alternative as a function of its attributes. In this paper these traditional models are extended by addressing the problem of sequential choice behaviour. It is demonstrated how discrete choice experiments and universal logit models may be used to predict a choice sequence. The approach is illustrated for the problem of trip chaining. The research findings support the suggested approach.

Exploring the Effect of Sequentially Receiving Airline and Destination Information on the Choice Behavior of Tourism Destinations

2020 ◽  
Vol 60 (2) ◽  
pp. 251-266 ◽  
Author(s):  
Pedram Keshavarzian ◽  
Cheng-Lung Wu
Keyword(s):  
Choice Behavior ◽  
Choice Model ◽  
Stated Preference ◽  
Destination Choice ◽  
Efficient Design ◽  
Final Destination ◽  
Destination Choices ◽  
Using Data ◽  
Airline Tickets ◽  
Airline Ticket

This article reports the results of a holiday destination choice model of domestic travelers in Australia. Although destination choices have been studied before, travelers’ behavior when choosing an airline ticket is less well investigated, in particular the effect of the choice of airline ticket and tourism features on each other and on the final destination choice. Multinomial logit (MNL) models were estimated using data from a Stated Preference (SP) choice experiment based on a D-Efficient design. Following the leader-driven primacy phenomenon, the article also tests whether destination choices are influenced by sequentially receiving information about airline tickets and tourism features. Results show that when airline ticket information is presented first, the destination choice behavior could be affected. In this context, the information sequencing effect is clear. However, the influence of tourism features is not as clear on the final choice when travelers are first exposed to tourism features and then airline tickets.

Incorporating Variety Seeking and Seasonality in Stated Preference Modeling of Leisure Trip Destination Choice: Test of External Validity

2002 ◽  
Vol 1807 (1) ◽  
pp. 67-76 ◽  
Author(s):  
Astrid Kemperman ◽  
Aloys Borgers ◽  
Harry Timmermans
Keyword(s):  
External Validity ◽  
Choice Model ◽  
Stated Preference ◽  
Destination Choice ◽  
Choice Test ◽  
Variety Seeking ◽  
Preference Modeling ◽  
Preference Model ◽  
Preference Models ◽  
Stated Preference Models

The results of a test to assess the external validity of a stated preference model of destination choice in the context of leisure trips are reported. This model differs from conventional stated preference models in transportation in that it incorporates variety seeking and seasonality in specification of the choice model. The results indicate that the model performed reasonably well; seasonality is predicted quite well, but in some specific situations the model overpredicts observed variety-seeking choices.

A Study of the Importance of Generalized Attributes in Shopping Choice Behaviour

1980 ◽  
Vol 12 (11) ◽  
pp. 1269-1286 ◽  
Author(s):  
P S McCarthy
Keyword(s):  
San Francisco ◽  
Choice Model ◽  
San Francisco Bay Area ◽  
Central City ◽  
Destination Choice ◽  
Logit Analysis ◽  
Choice Behaviour ◽  
Bay Area ◽  
Shopping Area ◽  
Qualitative Characteristics

The research reported in this paper focuses upon the qualitative characteristics associated with a traveler's shopping activity, and examines the role which these factors have in determining destination choice behaviour. By exploiting factor analytic methods to generate a set of qualitative or generalized attribute indices, interest is centred not only upon the significance of these indices, but also upon the components of each index. With data obtained from a San Francisco Bay Area Travel Survey, multinomial logit analysis is employed to estimate the model. Moreover, to identify the differential influence of generalized attributes, the model is separately estimated for suburban and central city subsamples and, in the latter case, a simultaneous destination–mode choice model is developed. The results demonstrate that generalized attributes derived from attitudinal information are significant inputs into an individual's choice of shopping area. In addition, policies which focus upon the time, safety, and parking availability components vis-à-vis comfort aspects of the shopping excursion will be more effective in obtaining desired changes in the existing pattern of travel.

scholarly journals Did Attitudes Interpret and Predict “Better” Choice Behaviour towards Innovative and Greener Automotive Technologies? A Hybrid Choice Modelling Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Stefano de Luca ◽  
Roberta Di Pace
Keyword(s):  
Latent Variables ◽  
Psychological Factors ◽  
Choice Model ◽  
Combustion Engine ◽  
Innovative Technology ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
Model Framework ◽  
Main Research ◽  
Automotive Technology

It is common opinion that traditional approaches used to interpret and model users’ choice behaviour in innovative contexts may lead to neglecting numerous nonquantitative factors that may affect users’ perceptions and behaviours. Indeed, psychological factors, such as attitudes, concerns, and perceptions may play a significant role which should be explicitly modelled. By contrast, collecting psychological factors could be a time and cost consuming activity, and furthermore, real-world applications must rely on theoretical paradigms which are able to easily predict choice/market fractions. The present paper aims to investigate the above-mentioned issues with respect to an innovative automotive technology based on the after-market hybridization of internal combustion engine vehicles. In particular, three main research questions are addressed: (i) whether and how users’ characteristics and attitudes may affect users’ behaviour with respect to new technological (automotive) scenarios (e.g., after-market hybridization kit); (ii) how to better “grasp” users’ attitudes/concerns/perceptions and, in particular, which is the most effective surveying approach to observe users’ attitudes; (iii) to what extent the probability of choosing a new automotive technology is sensitive to attitudes/concerns changes. The choice to install/not install the innovative technology was modelled through a hybrid choice model with latent variables (HCMs), starting from a stated preferences survey in which attitudes were investigated using different types of questioning approaches: direct questioning, indirect questioning, or both approaches. Finally, a comparison with a traditional binomial logit model and a sensitivity analysis was carried out with respect to the instrumental attributes and the attitudes. Obtained results indicate that attitudes are significant in interpreting and predicting users’ behaviour towards the investigated technology and the HCM makes it possible to easily embed psychological factors into a random utility model/framework. Moreover, the explicit simulation of the attitudes allows for a better prediction of users’ choice with respect to the Logit formulation and points out that users’ behaviour may be significantly affected by acting on users’ attitudes.

scholarly journals User Automotive Powertrain-Type Choice Model and Analysis Using Neural Networks

2021 ◽  
Vol 13 (2) ◽  
pp. 585
Author(s):  
Fabio Luis Marques dos Santos ◽  
Paolo Tecchio ◽  
Fulvio Ardente ◽  
Ferenc Pekár
Keyword(s):  
Internal Combustion Engine ◽  
User Behavior ◽  
Choice Model ◽  
Combustion Engine ◽  
Stated Preference ◽  
Operating Cost ◽  
Internal Combustion ◽  
Ann Model ◽  
Purchase Cost ◽  
Artificial Neural Network Ann

This paper presents an artificial neural network (ANN) model that simulates user’s choice of electric or internal combustion engine automotive vehicles based on basic vehicle attributes (purchase price, range, operating cost, taxes due to emissions, time to refuel/recharge and vehicle price depreciation), with the objective of analyzing user behavior and creating a model that can be used to support policymaking. The ANN was trained using stated preference data from a survey carried out in six European countries, taking into account petrol, diesel and battery electric automotive vehicle attributes. Model results show that the electric vehicle parameters (especially purchase cost, range and recharge times), as well as the purchase cost of internal combustion engine vehicles, have the most influence on consumers’ vehicle choices. A graphical interface was created for the model, to make it easier to understand the interactions between different attributes and their impacts on consumer choices and thus help policy decisions.

Do Agritourism Visitors Care about Landscapes? An Examination with Producer-Level Data

2017 ◽  
Vol 57 (3) ◽  
pp. 360-369 ◽  
Author(s):  
Richard T. Melstrom ◽  
Cassandra Murphy
Keyword(s):  
Choice Model ◽  
Destination Choice ◽  
Random Utility ◽  
Utility Model ◽  
Cross Section Data ◽  
Section Data ◽  
Conditional Logit ◽  
Level Data ◽  
Tourist Demand ◽  
Landscape Attributes

This article develops a random utility model of tourist demand for agritourism destinations. Prior research has largely focused on modeling the effect of visitor characteristics and demographics on the demand for agritourism. In contrast, we analyze cross-section data on producer-reported visits to measure the effects of destination attributes. This allows us to examine whether tourists choose destinations based on landscape attributes. The destination choice model is applied to agritourism demand in Oklahoma. We calculate elasticities from both conditional logit and Poisson interpretations of the model. The results provide no evidence that landscapes affect the demand for single-day sites, but do suggest local land use plays a role in the demand for overnight destinations.

scholarly journals Characteristics Analysis of Freight Mode Choice Model According to the Introduction of a New Freight Transport System

2019 ◽  
Vol 11 (4) ◽  
pp. 1209 ◽  
Author(s):  
Seungjin Shin ◽  
Hong-Seung Roh ◽  
Sung Hur
Keyword(s):  
Travel Time ◽  
Transport System ◽  
Choice Model ◽  
Stated Preference ◽  
Statistical Significance ◽  
Explanatory Power ◽  
Service Level ◽  
Freight Transport ◽  
Transport Cost ◽  
Transport Mode

The purpose of this study is to identify the characteristics of freight mode choices made by shippers and carriers with the introduction of a new freight transport system. We set an area in which actual freight transport takes place as the analysis scope and performed a survey of the shippers and carriers that transport containers to identify their stated preference (SP) regarding the new freight mode. The SP survey was carried out through an experimental design and this study considered the three factors of transport time, transport cost, and service level. This study compared and analyzed the models by distance using an individual behavior model. The results of estimating the model showed that the explanatory power of the model classified by distance and the individual parameters have statistical significance. The hit ratio was also high, which confirms that the model was estimated properly. In addition, the range of elasticity and the value of travel time analyzed using the model were evaluated to be appropriate compared to previous studies. The findings of the elasticity analysis show that strategies for reducing the transport cost are effective to increase the demand for the new transport mode. The value of travel time of freight transport was found to be higher than the current value generally applied in Korea. Considering that the value of travel time currently used is based on road freight transport, further research is required to apply a new value of travel time that reflects the characteristics of the new transport mode in the future.

scholarly journals Mode choice analysis using discrete choice model from transport user (Case study: Jakarta LRT, Indonesia)

2018 ◽  
Vol 181 ◽  
pp. 03001
Author(s):  
Dwi Novi Wulansari ◽  
Milla Dwi Astari
Keyword(s):  
Discrete Choice ◽  
Public Transportation ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Light Rail ◽  
Choice Analysis ◽  
Mode Choice Model

Jakarta Light Rail Transit (Jakarta LRT) has been planned to be built as one of mass rail-based public transportation system in DKI Jakarta. The objective of this paper is to obtain a mode choice models that can explain the probability of choosing Jakarta LRT, and to estimate the sensitivity of mode choice if the attribute changes. Analysis of the research conducted by using discrete choice models approach to the behavior of individuals. Choice modes were observed between 1) Jakarta LRT and TransJakarta Bus, 2) Jakarta LRT and KRL-Commuter Jabodetabek. Mode choice model used is the Binomial Logit Model. The research data obtained through Stated Preference (SP) techniques. The model using the attribute influences such as tariff, travel time, headway and walking time. The models obtained are reliable and validated. Based on the results of the analysis shows that the most sensitive attributes affect the mode choice model is the tariff.

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