1,720,981 research outputs found
A COPULA-BASED JOINT MODEL OF COMMUTE MODE CHOICE AND NUMBER OF NON-WORK STOPS DURING THE COMMUTE
No full textIn this paper, in the spirit of a tour-based frame of analysis, we examine the commute mode choice and the number of non-work stops during the commute. Under- standing the mode and activity stop dimensions of weekday commute travel is impor- tant since the highest level of weekday traffic congestion in urban areas occurs during the commute periods. The paper employs a copula-based joint multinomial logit – ordered modeling framework in which commute mode choice is modeled using a multinomial logit formulation and the number of commute stops is modeled using an ordered response formulation. The data used in this study are drawn from the “Time use” multipurpose survey conducted between 2002 and 2003 by the Turin Town Council and the Italian Na- tional Institute of Statistics (ISTAT) in the Greater Turin metropolitan area of Italy. The re- sults highlight the importance of accommodating the inter-relationship between commute mode choice and commute stops behavior. The results also point to the stronger effect of household responsibilities and demographic characteristics in the Italian context compared to the US context
A Comparative Analysis of Weekday Time Use and Activity Patterns Between Italy and the United States
No full textA Cross-Clustered Model of Home-Based Work Participation Frequency During Traditionally Off-Work Hours
No full textA study was done to shed light on the determinants of working from home beyond the traditional office-based work hours. The frequency of work participation from home was examined for individuals who also have a traditional work pattern of traveling to an out-of-home workplace and a fixed number of work hours at the out-of-home workplace. The sample for the empirical analysis was drawn from the 2002 to 2003 Turin, Italy, survey of time use, which was designed and administered by the Italian National Institute of Statistics. The methodology recognizes both spatial and social clustering effects by using a cross-clustered ordered response structure to analyze the frequency of work participation from home during off-work periods. The model is estimated through the use of the inference technique of composite marginal likelihood, which represents a conceptually, pedagogically, and implementationally simpler procedure relative to traditional frequentist and Bayesian simulation techniques
A Multivariate Ordered Response Model System for Adults’ Weekday Activity Episode Generation by Activity Purpose and Social Context
No full textThis paper proposes a multivariate ordered-response system framework to model the interactions in non-work activity episode decisions across household and non-household members at the level of activity generation. Such interactions in activity decisions across household and non-household members are important to consider for accurate activity-travel pattern modeling and policy evaluation. The econometric challenge in estimating a multivariate ordered-response system with a large number of categories is that traditional classical and Bayesian simulation techniques become saddled with convergence problems and imprecision in estimates, and they are also extremely cumbersome if not impractical to implement. We address this estimation problem by resorting to the technique of composite marginal likelihood (CML), an emerging inference approach in the statistics field that is based on the classical frequentist approach, is very simple to estimate, is easy to implement regardless of the number of count outcomes to be modeled jointly, and requires no simulation machinery whatsoever.
The empirical analysis in the paper uses data drawn from the 2007 American Time Use Survey (ATUS) and provides important insights into the determinants of adults’ weekday activity episode generation behavior. The results underscore the substantial linkages in the activity episode generation of adults based on activity purpose and accompaniment type. The extent of this linkage varies by individual demographics, household demographics, day of the week, and season of the year. The results also highlight the flexibility of the CML approach to specify and estimate behaviorally rich structures to analyze inter-individual interactions in activity episode generation
A copula-based joint multinomial discrete-ordered model of commuting mode choice and number of non-work stops during the commute
No full textSpatial and social interdependencies in work participation during traditionally off-work hours
No full textThe effect of personal cap-and-trade mileage policies on individual activity-travel patterns
No full textCross-Clustered Model of Home-Based Work Participation Frequency During Traditionally Off-Work Hours
No full textA Joint Model of Residential Neighborhood Type Choice and Bicycle Ownership: Accounting for Self-Selection and Unobserved Heterogeneity
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