Characteristic Analysis of Flipped Homes in Upper Arlington, Ohio: Average Square Footage, Duration and Year Built

House “flipping” is a trend that has caught the widespread attention of the public in recent years. Research papers and quality articles are currently available to potential house flippers are quite limited. There is very little scholarly research on house flipping. Many of the existing articles on the subject are low-level and not particularly useful (McLaughlin &Jobe, 2018). A study conductedby Depken, Hollans, and Swidler (2009)serves as a foundational model in academic research on information that relates to house flipping, while a corporate replication and expansion later conducted by McLaughlin andJobe(2018) further built upon their model. While both of these studies are very useful, they are difficult for the public to access, and the complexity of the information given makes them difficult for the average potential property investor to use. This paper attempts to rectify some of the current issues in the resources available to both researchers, as well as aspirational home flippers. This work includes an overview of house flipping, providing potential and current property investors with key information about issues of relevance to residential property investing today. This work then transitions to discussing a research study conducted by the authors that explore key characteristics of a home flip and explores property data in a midwestern suburb. This work reaffirms that the average flip property is smaller and older than the average non-flip home, and identifies an average ownership duration given the dataset and predetermined definition of a flip.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-05
DOI
https://doi.org/10.5281/zenodo.17130458
Primary Topic
Housing Market and Economics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characteristic Analysis of Flipped Homes in Upper Arlington, Ohio: Average Square Footage, Duration and Year Built

Douglas Ruml
Zenodo (CERN European Organization for Nuclear Research)
Housing Market and Economics
article

Characteristic Analysis of Flipped Homes in Upper Arlington, Ohio: Average Square Footage, Duration and Year Built

Douglas Ruml
article en

Abstract

House “flipping” is a trend that has caught the widespread attention of the public in recent years. Research papers and quality articles are currently available to potential house flippers are quite limited. There is very little scholarly research on house flipping. Many of the existing articles on the subject are low-level and not particularly useful (McLaughlin &Jobe, 2018). A study conductedby Depken, Hollans, and Swidler (2009)serves as a foundational model in academic research on information that relates to house flipping, while a corporate replication and expansion later conducted by McLaughlin andJobe(2018) further built upon their model. While both of these studies are very useful, they are difficult for the public to access, and the complexity of the information given makes them difficult for the average potential property investor to use. This paper attempts to rectify some of the current issues in the resources available to both researchers, as well as aspirational home flippers. This work includes an overview of house flipping, providing potential and current property investors with key information about issues of relevance to residential property investing today. This work then transitions to discussing a research study conducted by the authors that explore key characteristics of a home flip and explores property data in a midwestern suburb. This work reaffirms that the average flip property is smaller and older than the average non-flip home, and identifies an average ownership duration given the dataset and predetermined definition of a flip.

Zenodo (CERN European Organization for Nuclear Research)
Marymount University (US)
Openalex Percentile: Top 100%
Housing Market and Economics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.