Capturing Residential Preference Changes through Perception Detections of Rationally Inattentive Decision Makers

This dissertation focuses on the changes in aggregate residential trends and disaggregate perturbations in residential location choice behaviour. The empirical investigation uses the contexts of the COVID-19 pandemic in the Greater Toronto Area (GTA). Two conceptual models are presented in the study, each providing a unique perspective on analyzing residential preferences and forming the foundation of the research. The study delves into both the short- and long-term effects of the pandemic on residential location choice behaviour and aims to understand how preferences differ across various demographic groups. The research is based on Stated Preference (SP) surveys collected in July 2020 and July 2021 and housing price data for different dwelling attributes from January 2019 to August 2021. The dissertation proposes a new Efficient Adaptive Stated Preference (EASP) survey design that detects respondents’ tastes while doing the survey and integrates present information in choice experiment designs to improve the quality of SP data collection. The effectiveness of the EASP design is evaluated using a data-driven Neural Network model. The thesis also introduces an empirical model of rational inattention discrete location choice based on latent preferences and attention span. This model contributes to explaining the heteroskedasticity of different demographics in decision-making. The proposed methodology is validated by comparing its performance with comparable classical discrete choice models. Overall, the dissertation highlights the importance of high-quality data collection in the context of residential location choice and how the proposed survey design and empirical models can help improve data collection accuracy and inform policy decisions. The research has theoretical and practical implications for the planning of residential neighbourhoods, especially in the context of pandemics and other unexpected demand shocks.

Department dc:contributor.department

Civil Engineering

Year dc:date.issued

2023

Author dc:creator

• Shakib, Saeed

Advisor dc:contributor.advisor

• Habib, Khandker M. N.

• Adaptive Survey
• Conjoint Analysis
• Discrete Choice Modelling
• Rational Inattention
• Residential Location Choice
• Stated Preference

Statement dc:rights

• Attribution-ShareAlike 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by-sa/4.0/

Handle dc:identifier.uri

http://hdl.handle.net/1807/129971

OAI identifier oai:identifier

oai:utoronto.scholaris.ca:1807/129971