Individual differences in escalation of commitment: a multi-level adaptive learning perspective

Abstract Previous studies have found stable individual differences in decision-making under escalation situations. Conventionally, the differences have been attributed to dispositional factors. In this paper, we offer multi-level adaptive learning as an alternative, positing that stable individual differences can develop (a) from an equal starting point at which there are no individual differences among all simulated learners, and (b) without the presumption of influences from dispositional factors. The results of three computer simulation studies showed that after sufficient learning trials, simulated individuals developed the key characteristics of stable individual differences in escalation of commitment: (a) a stable escalation tendency, (b) stable individual differences in escalation tendency, (c) decreases in stability of individual differences as more learning occurs, and (d) decreases in test–retest correlation as the test–retest interval increases. The findings suggest that adaptive learning can explain the emergence and development of individual differences in escalation of commitment without the assumption of dispositional factors.

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Publication Details

Journal
Journal of Computational Social Science
Published
2024-12-07
DOI
https://doi.org/10.1007/s42001-024-00339-7
Citations
3
Primary Topic
Experimental Behavioral Economics Studies
Type
article
Field-Weighted Citation Impact
1.58

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article

Individual differences in escalation of commitment: a multi-level adaptive learning perspective

Jessica Y. Y. Kwong, Michelle Yik, Kin Fai Ellick Wong
3 citations
Journal of Computational Social Science
Experimental Behavioral Economics Studies
1.58
article

Individual differences in escalation of commitment: a multi-level adaptive learning perspective

Jessica Y. Y. Kwong, Michelle Yik, Kin Fai Ellick Wong
article en
3 citations

Abstract

Abstract Previous studies have found stable individual differences in decision-making under escalation situations. Conventionally, the differences have been attributed to dispositional factors. In this paper, we offer multi-level adaptive learning as an alternative, positing that stable individual differences can develop (a) from an equal starting point at which there are no individual differences among all simulated learners, and (b) without the presumption of influences from dispositional factors. The results of three computer simulation studies showed that after sufficient learning trials, simulated individuals developed the key characteristics of stable individual differences in escalation of commitment: (a) a stable escalation tendency, (b) stable individual differences in escalation tendency, (c) decreases in stability of individual differences as more learning occurs, and (d) decreases in test–retest correlation as the test–retest interval increases. The findings suggest that adaptive learning can explain the emergence and development of individual differences in escalation of commitment without the assumption of dispositional factors.

Journal of Computational Social ScienceVol. 8(1)
Chinese University of Hong Kong (HK), Hong Kong University of Science and Technology (HK), University of Hong Kong (HK)
Hong Kong University of Science and Technology, Hong Kong Government
Peace, Justice and strong institutions
Openalex Percentile: Top 13%
Experimental Behavioral Economics Studies
1.58
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Individual differences in escalation of commitment: a multi-level adaptive learning perspective — Jessica Y. Y. Kwong, Michelle Yik, et al. · Journal of Computational Social Science (2024) | TGRS Research Map | TGRS