Should I Stay or Should I Go? Applying the Investment Model to College Commitment

This research explores the factors that contribute to undergraduate students either staying enrolled in their current institution or transferring to a new institution. Previous research exploring commitment has looked through the lens of romantic relationships to better understand the factors that determine staying or leaving. More recently, these behavioral theories have increasingly been applied to different sorts of relationships. Specifically, we apply Rusbult’s Investment Model for romantic relationships to the relationship between a student and their university. Traditionally, this theory measures level of investment, quality of available alternatives, and level of satisfaction in the context of romantic relationships. In our experiment, we randomly assign participants to different scenarios in which we manipulate their perceived level of investment, perceived quality of available alternatives, and perceived satisfaction with their current university. We then measure their likelihood to transfer to a new institution. Study 1 produced results suggesting students make commitment decisions to universities using the same pattern of factors people use more generally to evaluate their romantic relationships. Notably, first generation students weighed these factors differently than typical students. Study 2 was an attempt to replicate these findings using samples from other parts of the United States. For Study 2, we’ve collected over 300 participants at Metropolitan State University in Denver, Colorado, as well as more than 300 participants at Sam Houston State University in Texas. Data collection will be completed by mid-March with final analyses coming shortly after. These findings have important implications for student retention and enrollment.

Publication Details

Journal
Scholar Commons (University of South Carolina)
Published
2025-04-11
Primary Topic
Genetics, Bioinformatics, and Biomedical Research
Type
article
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article

Should I Stay or Should I Go? Applying the Investment Model to College Commitment

Scholar Commons (University of South Carolina)
Genetics, Bioinformatics, and Biomedical Research
article

Should I Stay or Should I Go? Applying the Investment Model to College Commitment

article en

Abstract

This research explores the factors that contribute to undergraduate students either staying enrolled in their current institution or transferring to a new institution. Previous research exploring commitment has looked through the lens of romantic relationships to better understand the factors that determine staying or leaving. More recently, these behavioral theories have increasingly been applied to different sorts of relationships. Specifically, we apply Rusbult’s Investment Model for romantic relationships to the relationship between a student and their university. Traditionally, this theory measures level of investment, quality of available alternatives, and level of satisfaction in the context of romantic relationships. In our experiment, we randomly assign participants to different scenarios in which we manipulate their perceived level of investment, perceived quality of available alternatives, and perceived satisfaction with their current university. We then measure their likelihood to transfer to a new institution. Study 1 produced results suggesting students make commitment decisions to universities using the same pattern of factors people use more generally to evaluate their romantic relationships. Notably, first generation students weighed these factors differently than typical students. Study 2 was an attempt to replicate these findings using samples from other parts of the United States. For Study 2, we’ve collected over 300 participants at Metropolitan State University in Denver, Colorado, as well as more than 300 participants at Sam Houston State University in Texas. Data collection will be completed by mid-March with final analyses coming shortly after. These findings have important implications for student retention and enrollment.

Scholar Commons (University of South Carolina)
Openalex Percentile: Top 51%
Genetics, Bioinformatics, and Biomedical Research
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