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ACOMS+ 및 학술지 리포지터리 설명회

  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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  • P-ISSN1738-3110
  • E-ISSN2093-7717
  • SCOPUS, ESCI

An Experiment : Distribution of the Adversity Quotient as a Reduction of Bias in Estimating Earnings

An Experiment : Distribution of the Adversity Quotient as a Reduction of Bias in Estimating Earnings

The Journal of Distribution Science(JDS) / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2023, v.21 no.6, pp.99-106
https://doi.org/https://doi.org/10.15722/jds.21.06.202306.99
Riza PRADITHA (STIE Tri Dharma Nusantara)
Lasty AGUSTUTY (STIE Tri Dharma Nusantara)
Robert JAO (Universitas Atmajaya Makassar)
Andi RUSLAN (IAIN Bone)
Nur AISYAH (STIE Tri Dharma Nusantara)
Diah Ayu GUSTININGSIH (STIE Tri Dharma Nusantara)

Abstract

Purpose: This study aims to analyze the distribution of the role of adversity quotient in the estimation bias of future earnings. Adversity quotient is a cognitive ability that can be distributed as a reducer of bias effects that occur in profit forecasting or investment decision making. Research design, data and methodology: The study designs a full factorial within-subject 2×3 as a laboratory experiment. The study subjects are 30 accounting students who are proxied as investors. Results: The results show that the estimated earnings made by investors experience anchoring-adjustment heuristic bias which means the initial value becomes a basic belief that influences the decisions taken by investors. However, this study also provides evidence that heuristic bias can be reduced by the presence of adversity quotient. Investors who have high adversity ability are abler to reduce the estimation bias when compared to investors who have medium and low adversity ability so the higher the difficulty ability possessed by investors, the less likely the occurrence of bias in decision making. Conclusion: Thus, the adversity quotient is proven to be distributed as a reducing opportunity from the bias that will occur in estimating future earnings or making investment decisions.

keywords
Earnings estimates, Adversity quotient, Anchoring-adjustment, Heuristic bias, Distribution

The Journal of Distribution Science(JDS)