Browsing by Subject "multivariate modeling"
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Item A Joint Household Level Analysis of Work Arrangement Choices of Individuals(Transportation Research Board of the National Academies, 2012) Khan, Mubassira; Paleti, Rajesh; Bhat, Chandra R.; Pendyala, Ram M.This paper presents a comprehensive multi-dimensional multivariate binary probit model system capable of simultaneously representing multiple aspects of individual work arrangement decisions, while also accounting for interactions among household members in individual employment related choices. The model system is estimated on a survey sample drawn from the San Francisco Bay Area where a rich set of accessibility measures is available to account for built environment influences on work related decisions. Model results show that a host of demographic, socio-economic, built environment, and attitudinal variables influence individual choices regarding work arrangements; more importantly, the model shows that there is considerable interaction among household members in matters related to employment. The model system can be used to predict employment choices of individuals within larger microsimulation model systems of activity-travel demand.Item On modeling telecommuting behavior: Option, choice, and frequency(Springer, 2013) Singh, Palvinder; Paleti, Rajesh; Jenkins, Syndney; Bhat, Chandra R.The current study contributes to the already substantial scholarly literature on telecommuting by estimating a joint model of three dimensions- option, choice and frequency of telecommuting. In doing so, we focus on workers who are not self-employed workers and who have a primary work place that is outside their homes. The unique methodological features of this study include the use of a general and flexible generalized hurdle count model to analyze the precise count of telecommuting days per month, and the formulation and estimation of a model system that embeds the count model within a larger multivariate choice framework. The unique substantive aspects of this study include the consideration of the “option to telecommute” dimension and the consideration of a host of residential neighborhood built environment variables. The 2009 NHTS data is used for the analysis, and allows us to develop a current perspective of the process driving telecommuting decisions. This data set is supplemented with a built environment data base to capture the effects of demographic, work-related, and built environment measures on the telecommuting-related dimensions. In addition to providing important insights for policy analysis, the results in this paper indicate that ignoring the “option” dimension of telecommuting can, and generally will, lead to incorrect conclusions regarding the behavioral processes governing telecommuting decisions. The empirical results have implications for transportation planning analysis as well as for the worker recruitment/retention and productivity literature.