First Advisor

Kathryn Wuschke

Term of Graduation

January 2026

Date of Publication

6-1-2026

Document Type

Thesis

Language

English

Subjects

Big-box stores, Portland Oregon, QGIS, Shoplifting, Spatial Analysis, Temporal Analysis

Physical Description

1 online resource ( pages)

Abstract

Shoplifting has contributed to significant losses in Oregon, reaching nearly $956 million in 2022 (Capital One Shopping, 2025). While overall property crime in Portland, Oregon, dropped between 2023 and 2024, reported shoplifting incidents increased by 50.0% (Portland Police Bureau, 2023; 2024). In Oregon, stealing property worth $100 or less is third-degree theft and a Class C misdemeanor (Lounsbury, 2025). Second-degree theft involving stealing property between $100 and $1,000 is a Class A misdemeanor (Lounsbury, 2025). Although often classified as petty or minor theft, shoplifting imposes strain on retailers, consumers, and communities, which raises questions about the spatial and temporal distribution of this crime. This study uses Portland Police Bureau (PPB) offense data to analyze spatial and temporal patterns of shoplifting across seven big-box store chains and 22 store locations in Portland, Oregon, between 2022 and 2025. The findings indicate that shoplifting incidents are concentrated at specific store locations and during particular time periods. These findings highlight where and when shoplifting occurred, providing context for understanding theft in large stores in urban environments. Due to the underreporting nature of shoplifting, the dataset likely does not capture the full extent of shoplifting activity, so the observed patterns should be interpreted as an estimate of reported shoplifting rather than a complete measure of all events. Overall, this study contributes to understanding shoplifting patterns and offers implications for retailers, law enforcement, and policymakers in developing crime prevention strategies.

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Available for download on Saturday, June 26, 2027

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