Date of Award

8-2024

Document Type

Open Access Thesis

Degree Name

Doctor of Philosophy (PhD)

Department

Business Administration

First Advisor

Josephine Namayanja

Second Advisor

Shan Jiang

Third Advisor

One-Ki Daniel Lee

Abstract

This dissertation presents an in-depth investigation into collective anomalies—complex patterns of data that deviate from the norm when considered as a group, rather than individually. It encompasses three pivotal studies that explore the intricacies of identifying and analyzing these anomalies within online customer reviews and urban traffic patterns. The research initially focuses on the subtle shifts in consumer feedback patterns, highlighting the challenges of detecting early signs of collective anomalies. It then advances to the analysis of urban traffic, emphasizing the detection of anomalous trajectory patterns and their implications for urban planning. The final study introduces a spatio-temporal framework to uncover microtransit bottlenecks, aiming to enhance urban mobility. This body of work offers insights into the nuanced manifestation, detection and implications of collective anomalies, providing a significant contribution to the field of data-driven decision-making.

Comments

Free and open access to this Campus Access Thesis is made available to the UMass Boston community by ScholarWorks at UMass Boston. Those not on campus and those without a UMass Boston campus username and password may gain access to this thesis through resources like Proquest Dissertations & Theses Global (https://www.proquest.com/) or through Interlibrary Loan. If you have a UMass Boston campus username and password and would like to download this work from off-campus, click on the "Off-Campus UMass Boston Users

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