{"693482":{"#nid":"693482","#data":{"type":"event","title":"PhD Defense by Ilsu Kim","body":[{"value":"\u003Cp\u003ESchool of Civil and Environmental Engineering\u003C\/p\u003E\u003Cp\u003EPh.D. Thesis Defense Announcement\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAdvancing the Practical Integration of Attitudes into Regional Travel Demand Models: Attitudinal Marker Variables, Systematic Model Specification, and Temporal Stability of Attitudes\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EBy\u003Cstrong\u003E\u0026nbsp;Ilsu Kim\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAdvisor:\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDr. Patricia Mokhtarian\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESchool of Civil and Environmental Engineering\u003C\/p\u003E\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\u003Cp\u003ECommittee Members:\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDr. Michael Hunter\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESchool of Civil and Environmental Engineering\u003C\/p\u003E\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\u003Cp\u003EDr. Sofia Perez-Guzman\u003C\/p\u003E\u003Cp\u003ESchool of Civil and Environmental Engineering\u003C\/p\u003E\u003Cp\u003ESchool of Industrial and Systems Engineering\u003C\/p\u003E\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\u003Cp\u003EDr. Subhrajit Guhathakurta\u003C\/p\u003E\u003Cp\u003ESchool of City and Regional Planning\u003C\/p\u003E\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\u003Cp\u003EDr. Ram Pendyala\u003C\/p\u003E\u003Cp\u003ESchool of Sustainable Engineering and the Built Environment\u003C\/p\u003E\u003Cp\u003EArizona State University\u003C\/p\u003E\u003Cp\u003EDate and Time:\u003Cstrong\u003E\u0026nbsp;Monday, November 9, 2026, at 3:00 PM EST\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ELocation: Mason 2119 or \u003Cstrong\u003Eonline via\u0026nbsp;\u003C\/strong\u003E\u003Ca href=\u0022https:\/\/teams.microsoft.com\/meet\/273006166487151?p=m2MW5rIwHiBygecHAl\u0022\u003E\u003Cstrong\u003EMicrosoft Teams\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003EFacing evolving work and commute patterns, shifting lifestyles, and\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eemerging travel options such as micromobility and self-driving vehicles, travel\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Edemand models (TDMs) need, and will continue to need, enhanced predictive\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eperformance. Transportation-related attitudes help explain why individuals and\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ehouseholds with similar socioeconomic, demographic, and residential\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Echaracteristics make different travel choices. However, integrating attitudes into\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eregional TDMs requires practical ways to measure them, incorporate them into\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Etravel behavior models, and forecast their shifts over time.\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003EThe goal of this dissertation is to support the practical integration of\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Etraveler attitudes into TDMs. The marker variable (MV) approach reduces\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Emeasurement burdens by using a small set of selected attitudinal statements.\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003EAttitudinal MVs can be used to impute attitudinal factor scores through functions\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Etrained on an attitude-rich donor dataset or included directly in travel behavior\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Emodels. The dissertation addresses three complementary questions: (1) What are\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ethe types and magnitudes of benefits obtained from incorporating MV-predicted\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eattitudinal factor scores or MVs into various travel behavior models? (2) How can\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eattitudinal MVs be best leveraged to improve the performance of individual travel\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ebehavior models within regional TDMs? and (3) How stable are transportationrelated\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eattitudes over time, and what factors are associated with attitudinal shifts?\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003EThe findings show that including attitudes yields meaningful benefits,\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eparticularly in predicting less-common alternatives, and can reveal additional\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Esignificant non-attitudinal explanatory variables. Segmenting the population and\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eincorporating attitudes into latent class membership further improve vehicle\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eownership models, especially for single-adult households, highlighting the value of\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eallowing model structures and attitudinal roles to vary across segments.\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003EAttitudinal stability differs across domains, with the pro-car-ownership attitude\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eshowing greater persistence than the pro-transit and pro-active-mode attitudes,\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ewhile within-person shifts remain largely unexplained by observed characteristics\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eand their changes. Overall, this dissertation supports the practical integration of\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eattitudes into regional TDMs by demonstrating the value of abbreviated\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Emeasurement, offering a structured model specification process, and providing\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Einsights into temporal stability. These findings inform how attitudes can be\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ecollected and used in modeling practice, while identifying further research needed\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eto assign attitudes to individuals and forecast their evolution over time.\u003C\/strong\u003E\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAdvancing the Practical Integration of Attitudes into Regional Travel Demand Models: Attitudinal Marker Variables, Systematic Model Specification, and Temporal Stability of Attitudes\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Advancing the Practical Integration of Attitudes into Regional Travel Demand Models: Attitudinal Marker Variables, Systematic Model Specification, and Temporal Stability of Attitudes"}],"uid":"27707","created_gmt":"2026-10-26 16:17:28","changed_gmt":"2026-10-26 16:18:26","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-11-09T03:00:01-05:00","event_time_end":"2026-11-09T17:00:00-05:00","event_time_end_last":"2026-11-09T17:00:00-05:00","gmt_time_start":"2026-11-09 08:00:01","gmt_time_end":"2026-11-09 22:00:00","gmt_time_end_last":"2026-11-09 22:00:00","rrule":null,"timezone":"America\/New_York"},"location":" Mason 2119 or online via Microsoft Teams","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}