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1.
This study adopts a dwelling unit level of analysis and considers a probabilistic choice set generation approach for residential choice modeling. In doing so, we accommodate the fact that housing choices involve both characteristics of the dwelling unit and its location, while also mimicking the search process that underlies housing decisions. In particular, we model a complete range of dwelling unit choices that include tenure type (rent or own), housing type (single family detached, single family attached, or apartment complex), number of bedrooms, number of bathrooms, number of storeys (one or multiple), square footage of the house, lot size, housing costs, density of residential neighborhood, and commute distance. Bhat’s (2015) generalized heterogeneous data model (GHDM) system is used to accommodate the different types of dependent outcomes associated with housing choices, while capturing jointness caused by unobserved factors. The proposed analytic framework is applied to study housing choices using data derived from the 2009 American Housing Survey (AHS), sponsored by the Department of Housing and Urban Development (HUD) and conducted by the U.S. Census Bureau. The results confirm the jointness in housing choices, and indicate the superiority of a choice set formation model relative to a model that assumes the availability of all dwelling unit alternatives in the choice set. 相似文献
2.
Recent developments in residential location choice models have considered the individual as the basic unit of analysis and have attempted to model the actual choice process used by individuals in selecting residential location sites. This paper demonstrates that the choice model derived from these studies is a more general form of many macroscopic models of location used in the past. The prime difference between the two classes of model is seen to be the much wider range of factors and geographic settings which can be accounted for in disaggregate behavioural models of residential location choice. 相似文献
3.
Residential mobility and location choice: a nested logit model with sampling of alternatives 总被引:1,自引:0,他引:1
Residential mobility and relocation choice are essential parts of integrated transportation and land use models. These decision
processes have been examined and modeled individually to a great extent but there remain gaps in the literature on the underlying
behaviors that connect them. Households may partly base their decision to move from or stay at a current location on the price
and quality of the available alternatives. Conversely, households that are on the market for a new location may evaluate housing
choices relative to their previous residence. How and the degree to which these decisions relate to each other are, however,
not completely understood. This research is intended to contribute to the body of empirical evidence that will help answer
these questions. It is hypothesized that residential mobility and location choice are related household decisions that can
be modeled together using a two-tier hierarchical structure. This paper presents a novel nested logit (NL) model with sampling
of alternatives and a proposed procedure for sampling bias correction. The model was estimated using full-information maximum
likelihood estimation methods. The results confirm the applicability of this NL model and support similar findings from other
empirical studies in the residential mobility and location choice literature. 相似文献
4.
This paper introduces a vehicle transaction timing model which is conditional on household residential and job relocation
timings. Further, the household residential location and members’ job relocation timing decisions are jointly estimated. Some
researchers have modeled the household vehicle ownership decision jointly with other household decisions like vehicle type
choice or VMT; however, these models were basically static and changes in household taste over time has been ignored in nearly
all of these models. The proposed model is a dynamic joint model in which the effects of land-use, economy and disaggregate
travel activity attributes on the major household decisions; residential location and members’ job relocation timing decisions
for wife and husband of the household, are estimated. Each of these models is estimated using both the Weibull and log-logistic
baseline hazard functions to assess the usefulness of a non-monotonic rather than monotonic baseline hazard function. The
last three waves of the Puget Sound Panel Survey data and land-use, transportation, and built environment variables from the
Seattle Metropolitan Area are used in this study as these waves include useful explanatory variables like household tenure
that were not included in the previous waves. 相似文献
5.
This paper presents a system of hierarchical rule-based models of trip generation and modal split. Travel attributes, like
trip counts for different transportation modes and commute distance, are among the modeled variables. The proposed framework
could be considered as an alternative for several modules of the traditional travel demand modeling approach, while providing
travel attributes at the highly disaggregate level that can be also used in activity-based micro-simulation modeling systems.
Nonetheless, the modeling framework of this study is not considered as a substitute for activity-based models. The explanatory
variables set ranges from socio-economic and demographic attributes of the household to the built environment characteristics
of the household residential location. Another important contribution of the study is a framework in which travel attributes
are modeled in conjunction with each other and the interdependencies among them are postulated through a hierarchical system
of models. All the models are developed using rule-based decision tree method. Moreover, the models developed in this study
present a useful improvement in increasing the practicality and accuracy of the rule-based travel data simulation models. 相似文献
6.
Yosef Sheffi 《Transportation Research Part B: Methodological》1979,13(3):189-205
In several travel choice situations (e.g. automobile ownership level and trip frequency) the alternatives available to an individual randomly chosen from the population exhibit some internal choice-related ranking: the choice of a given alternative implies that all lower-ranked alternatives have been chosen. Such alternatives are referred to as “nested”. This paper presents a model for estimating choice probabilities among nested alternatives. The model is devised from the well known logit model and uses existing logit maximum-likelihood estimation techniques (and computer packages). The approach is shown to be more attractive than the multinomial logit and linear regression models, from a theoretical point of view, yet cheaper than the multinomial probit model. The model is developed in a disaggregate, utility maximization framework. An example application, estimating probabilities of trip frequencies by elderly individuals is presented. 相似文献
7.
M. William Sermons Natalya Seredich 《Transportation Research Part D: Transport and Environment》2001,6(6):417-428
In this paper, a joint multinomial logit (MNL) model of residential location and vehicle availability choice is formulated and estimated using a sample of households from the San Francisco, CA area Metropolitan Transportation Commission's 1990 household travel survey. Subsequently, models of travel intensity (number of daily household trips and vehicle-miles traveled) are estimated as a function of household characteristics and of attributes derived from the joint residential location and auto availability choice model (number of vehicles, percent land developed). A policy test shows that reducing the cost of locating in the densest areas of the metropolitan area is likely to have only marginal impact on vehicle availability and household trip making. 相似文献
8.
《Transportation Research Part A: General》1986,20(4):319-330
Based on the theoretical model of complex travel behavior developed in a companion paper (Recker et al., 1986), an operational system of models, STARCHILD (Simulation of Travel/Activity Responses to Complex Household Interactive Logistic Decisions), has been developed to examine the formation of household travel/activity patterns. The system employs a simulation approach in combination with techniques of pattern recognition, multiobjective optimization and disaggregate choice models. Initial empirical verification of the system of models is presented based on results obtained from a sample data set. 相似文献
9.
John R. Roy 《Transportation Research Part B: Methodological》1981,15(3):159-164
In using entropy maximization models to forecast locational and travel behaviour, one is confronted with the problem of delineating the choice process as precisely as possible. In addition to defining a fine-grain choice structure implying individuals seeking distinct location sites within residential zones and travelling to distinct jobs or shops within destination zones, this note also accounts for the fact that the location choice is of a site for a household or firm, but the corresponding travel choices are by individual members of a household. In conjunction with disaggregation across quantities with large variance, the above principles are applied to formulate improved versions of residential and shopping location models. 相似文献
10.
Amaya Vega Aisling Reynolds-Feighan 《Transportation Research Part A: Policy and Practice》2009,43(4):401-419
The aim of this paper is to contribute to the methodological questions that arise from the study of the simultaneous choice of residential location and travel-to-work mode under central and non-central or suburban employment patterns. Geographic information system (GIS) visualisations and network analysis are used to generate a choice set based on the definition of spatially aggregated alternatives. Discrete choice models specified as cross-nested logit (CNL) are estimated for each of the two different types of employment patterns and direct and cross elasticities are presented. The analysis is carried out for the Greater Dublin Area, a metropolitan region that is a recent example of rapid employment suburbanisation and residential sprawl in a European context. A simulation exercise, tracing the extent of mode switching and location switching behaviour is undertaken using the framework developed. 相似文献
11.
The purchase of an automobile involves significant transaction costs in addition to the purchase price. Therefore, the assumptions implied by static car holding models are invalid. This paper describes a dynamic approach to the modeling of level-of-ownership and auto-type choice, based on a transaction choice model which utilizes information on past car ownership. The cost or disutility of a transaction depends on the attributes of the household and the purchased car, as well as on past car-ownership characteristics. A set of assumptions underlying the incorporation of transaction costs in the model is presented. The paper discusses the econometric implications of omitting the dynamic attributes (i.e., past ownership characteristics). A disaggregate model was estimated, using a choice-based sample consisting of a random sample of households enriched with a sample of households which transacted in the car market during the study period. This sampling method combined with a random choice of a subset of the car alternatives provides for a cost-effective method to estimate a transaction model. 相似文献
12.
This paper examines network design where OD demand is not known a priori, but is the subject of responses in household or user itinerary choices to infrastructure improvements. Using simple examples, we show that falsely assuming that household itineraries are not elastic can result in a lack in understanding of certain phenomena; e.g., increasing traffic even without increasing economic activity due to relaxing of space–time prism constraints, or worsening of utility despite infrastructure investments in cases where household objectives may conflict. An activity-based network design problem is proposed using the location routing problem (LRP) as inspiration. The bilevel formulation includes an upper level network design and shortest path problem while the lower level includes a set of disaggregate household itinerary optimization problems, posed as household activity pattern problem (HAPP) (or in the case with location choice, as generalized HAPP) models. As a bilevel problem with an NP-hard lower level problem, there is no algorithm for solving the model exactly. Simple numerical examples show optimality gaps of as much as 5% for a decomposition heuristic algorithm derived from the LRP. A large numerical case study based on Southern California data and setting suggest that even if infrastructure investments do not result in major changes in link investment decisions compared to a conventional model, the results provide much higher resolution temporal OD information to a decision maker. Whereas a conventional model would output the best set of links to invest given an assumed OD matrix, the proposed model can output the same best set of links, the same daily OD matrix, and a detailed temporal distribution of activity participation and travel from which changes in peak period OD patterns can be observed. 相似文献
13.
《Transportation Research Part A: General》1983,17(4):283-299
The nested logit (NL) model is a generalisation of the well-known multinomial logit (MNL) model which copes with its “independence from irrelevant alternatives” problem, at the expense of more difficult calibration and use. Mixed-mode movements (i.e. park-and-ride) are by nature not independent of competing single-mode options and have, therefore, traditionally been inadequately modelled in most empirical applications. This paper reports on the specification, estimation, testing and comparison of MNL and NL models using disaggregate data of work trips in an urban corridor, where choice was among several alternatives including mixed-mode options. It was found that the more general NL model was more adequate, not only in theory but in practice. The paper concludes by comparing the disaggregate NL model with previously calibrated aggregate NL models for the same corridor using a different data set. 相似文献
14.
Stated choice experiments are designed optimally in a statistical sense but not necessarily in a behavioural choice making sense. Statistical designs, and consequently model estimation, assume that the set of alternatives offered in the experiment are processed by respondents with a specific processing strategy. Much has been studied about attribute processing using discrete choice methods in travel choice studies, but this paper focuses more broadly on processing of alternatives in the choice set offered in the experiment. This paper is motivated by the primary idea that the distribution of predicted choice probabilities associated with a set of alternatives defining a given choice set might provide strong evidence on the strategies that agents appear to use when choosing a preferred alternative. In an empirical setting of a choice set of size three, four model specifications are considered including a model for the selection of the best alternative in the full choice set and three variants of a best–worst regime. Using state choice data on road pricing reform, the empirical analysis examines which model specification delivers the most accurate prediction of the chosen alternative. The results suggest which alternatives really matter in choice making and hence the alternatives that might be included in a choice set for model specification. 相似文献
15.
Gopindra Sivakumar Nair Sebastian Astroza Chandra R. Bhat Sara Khoeini Ram M. Pendyala 《Transportation》2018,45(6):1623-1637
Surveys of behavior could benefit from information about people’s relative ranking of choice alternatives. Rank ordered data are often collected in stated preference surveys where respondents are asked to rank hypothetical alternatives (rather than choose a single alternative) to better understand their relative preferences. Despite the widespread interest in collecting data on and modeling people’s preferences for choice alternatives, rank-ordered data are rarely collected in travel surveys and very little progress has been made in the ability to rigorously model such data and obtain reliable parameter estimates. This paper presents a rank ordered probit modeling approach that overcomes limitations associated with prior approaches in analyzing rank ordered data. The efficacy of the rank ordered probit modeling methodology is demonstrated through an application of the model to understand preferences for alternative configurations of autonomous vehicles (AV) using the 2015 Puget Sound Regional Travel Study survey data set. The methodology offers behaviorally intuitive model results with a variety of socio-economic and demographic characteristics, including age, gender, household income, education, employment and household structure, significantly influencing preference for alternative configurations of AV adoption, ownership, and shared usage. The ability to estimate rank ordered probit models offers a pathway for better utilizing rank ordered data to understand preferences and recognize that choices may not be absolute in many instances. 相似文献
16.
《Transportation Research Part A: General》1984,18(1):1-11
This paper presents the results of an application of a non-tradeoff decision making model to residential location choice. The model, referred to as an Elimination-by-Aspects model, provides a behaviourally acceptable mechanism for new residents to sift through the large number of alternatives and attributes that are present in residential location decisions. The mechanism deals with complex multi-attribute choices, by following a tree like decision making process. Using the most important attributes first, the decision maker successively eliminates alternatives which fall below a certain level. The model was applied to the location decisions of a number of new residents in outer suburban Melbourne. It was found to provide a good explanation of the decisions. Furthermore the residents' decisions were found to be sensitive to variations in the accessibility to schools, shops and the type of dwelling the respondent could afford. 相似文献
17.
Modeling residential sorting effects to understand the impact of the built environment on commute mode choice 总被引:5,自引:2,他引:3
Abdul Rawoof Pinjari Ram M. Pendyala Chandra R. Bhat Paul A. Waddell 《Transportation》2007,34(5):557-573
This paper presents an examination of the significance of residential sorting or self selection effects in understanding the
impacts of the built environment on travel choices. Land use and transportation system attributes are often treated as exogenous
variables in models of travel behavior. Such models ignore the potential self selection processes that may be at play wherein
households and individuals choose to locate in areas or built environments that are consistent with their lifestyle and transportation
preferences, attitudes, and values. In this paper, a simultaneous model of residential location choice and commute mode choice
that accounts for both observed and unobserved taste variations that may contribute to residential self selection is estimated
on a survey sample extracted from the 2000 San Francisco Bay Area household travel survey. Model results show that both observed
and unobserved residential self selection effects do exist; however, even after accounting for these effects, it is found
that built environment attributes can indeed significantly impact commute mode choice behavior. The paper concludes with a
discussion of the implications of the model findings for policy planning.
相似文献
Paul A. WaddellEmail: |
18.
19.
Nazneen Ferdous Abdul Rawoof Pinjari Chandra R. Bhat Ram M. Pendyala 《Transportation》2010,37(3):363-390
This paper proposes a multiple discrete continuous nested extreme value (MDCNEV) model to analyze household expenditures for
transportation-related items in relation to a host of other consumption categories. The model system presented in this paper
is capable of providing a comprehensive assessment of how household consumption patterns (including savings) would be impacted
by increases in fuel prices or any other household expense. The MDCNEV model presented in this paper is estimated on disaggregate
consumption data from the 2002 Consumer Expenditure Survey data of the United States. Model estimation results show that a
host of household and personal socio-economic, demographic, and location variables affect the proportion of monetary resources
that households allocate to various consumption categories. Sensitivity analysis conducted using the model demonstrates the
applicability of the model for quantifying consumption adjustment patterns in response to rising fuel prices. It is found
that households adjust their food consumption, vehicular purchases, and savings rates in the short run. In the long term,
adjustments are also made to housing choices (expenses), calling for the need to ensure that fuel price effects are adequately
reflected in integrated microsimulation models of land use and travel. 相似文献
20.
We propose a methodology to achieve consistency, asymptotic normality and efficiency, while sampling alternatives in Multivariate Extreme Value (MEV) models, extending a previous result for Logit. We illustrate the methodology and study the finite sample properties of the estimators using Monte Carlo experimentation and real data on residential location choice from Lisbon, Portugal. Experiments show that the proposed methodology is practical, that it outperforms the uncorrected model, and that it yields acceptable results, even for relatively small samples of alternatives. The paper finishes with a synthesis and an analysis of the impact, limitations and potential extensions of this research. 相似文献