JOURNAL ARTICLE
Debtors at Play: Gaming Behavior and Consumer Credit Risk.
Published In: Management Science (INFORMS), 2024, v. 70, n. 9. P. 5691 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Gong, Shuaishuai; Levine, Ross; Lin, Chen; Xie, Wensi 3 of 3
Abstract
This article investigates how impulsivity, proxied by individual video gaming behavior, influences consumer financial decisions following a relaxation of credit constraints, specifically after receiving a credit card. Using a unique high-frequency dataset from a large Chinese financial firm covering over 80,000 credit card applicants, the study constructs incentive-compatible measures of impulsivity based on gaming expenditures and frequency in the 30 days prior to credit card application. The findings reveal that higher precard gaming intensity is strongly associated with increased probabilities of credit card default, greater postcard spending on luxury and addictive items, immediate surges in consumption after card receipt, and rapid debt accumulation. These relationships persist after controlling for demographics, income, education, financial literacy, and overall spending propensity, and are further supported by analyses of gaming timing, volatility, and the diversity of game apps installed. The results align with neurological and behavioral theories linking excessive gaming to impulse control deficiencies and suggest that impulsivity significantly shapes borrowing and spending behaviors when liquidity constraints are eased.
Additional Information
- Source:Management Science (INFORMS). 2024/09, Vol. 70, Issue 9, p5691
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2024
- ISSN:0025-1909
- DOI:10.1287/mnsc.2023.4931
- Accession Number:179339493
- Copyright Statement:Copyright of Management Science (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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