바로가기메뉴

본문 바로가기 주메뉴 바로가기
 

logo

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

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

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

Reference

1.

Bahník, Š., Englich, B., & Strack, F. (2017). Anchoring Effect. In Rudiger F. Pohl (Ed.), Cognitive Illusions: Intriguing Phenomena in Judgement, Thinking and Memory (Second Edition, pp. 223–241). Routledge.

2.

Beach, L. R., & Mitchell, T. R. (1987). Image Theory: Principles, Goals, And Plans In Decision Making. Theory and Decision, 66, 201–220.

3.

Bergman, O., Ellingsen, T., Johannesson, M., & Svensson, C. (2010). Anchoring and cognitive ability. Economics Letters, 107(1), 66–68.

4.

Bloomfield, R., Libby, R., & Nelson, M. W. (2003). Do Investors Overrely on Old Elements of the Earnings Time Series? Contemporary Accounting Research, 20(1), 1–31.

5.

Brav, A., & Heaton, J. B. (2002). Competing Theories of Financial Anomalies. Review of Financial Studies, 15(2), 575–606.

6.

Chin, P.-L., & Hung, M.-L. (2013). Psychological Contract Breach and Turnover Intention: The Moderating Roles of Adversity Quotient and Gender. Social Behavior and Personality: An International Journal, 41(5), 843–859.

7.

De Bondt, W. F. M., & Thaler, R. (1985). Does the Stock Market Overreact? The Journal of Finance, XL(3), 793–805.

8.

Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic Decision Making. The Annual Review of Psychology, 62(1), 451–482.

9.

Gilovich, T., & Epley, N. (2006). The Anchoring-and-Adjustment Heuristic. Why the Adjustments Are Insufficient. Psychological Science, 17(4), 311–318.

10.

Habbe, A. H. (2017). Estimation Error of Earnings Information: A Test of Representativeness and Anchoring-adjustment Heuristic. International Journal of Economics and Financial Issues, 7(1), 224–233.

11.

Habbe, A. H., & Mande, H. (2016). the Effect of Information Sequential and Personality on the Investor Belief Revision (an Experimental Study in Decision Making). PONTE International Scientific Researchs Journal, 72(10), 150–166.

12.

Musthofa, & Ancok, D. (2005). Hubungan antara bias keputusan dengan adversity quotient dan anchor dalam pengambilan keputusan. Sosiosains, 18(2), 179–192.

13.

Parvathy, U., & M Praseeda, M. (2014). Relationship between Adversity Quotient and Academic Problems among Student Teachers. IOSR Journal of Humanities and Social Science, 19(11), 23–26.

14.

Phoolka, S., & Kaur, N. (2012). Literature review: service quality in higher education institutions in Malaysia. International Journal of Contemporary Business Studies, 3(4), 67-78.

15.

Pompian, M. M. (2012). Behavioral finance and investor types : managing behavior to make better investment decisions. Wiley.

16.

Praditha, R., Haliah, H., Habbe, A. H., & Rura, Y. (2020). Do investors experience heuristics in earnings forecasting? Business: Theory and Practice, 21(2).

17.

Praditha, Riza, Haliah, H., Habbe, A. H., & Rura, Y. (2019). Earnings Estimation : Cognitive Psychology and Investor Reaction. American International Journal of Business Management, 2(11), 89–95.

18.

Richie, M., & Josephson, S. A. (2017). Quantifying Heuristic Bias: Anchoring, Availability, and Representativeness. Teaching and Learning in Medicine, 30(1), 67–75.

19.

Stanovich, K. E., & West, R. F. (2008). On the Relative Independence of Thinking Biases and Cognitive Ability. Journal of Personality and Social Psychology, 94(4), 672–695.

20.

Stoltz, P. G. (2000a). Adversity Quotient - Turning Obstacle into Opportunities. Wiley.

21.

Stoltz, P. G. (2000b). Adversity Quotient Work: Putting the Principles of AQ into Action (William Morrow (ed.); First Edition). Collins Publisher.

22.

Sundari, S., & Habbe, A. H. (2018). Heuristic of Representativeness and Anchoring-Adjustment in Budgeting. International Journal of Academic Research in Accounting, Finance and Management Sciences, 8(4), 52–60.

23.

Tversky, A., & Kahneman, D. (1973). Judgements under uncertainty: Heuristics and biases. Oregon Research Institute Research Bulletin, 13(1), 201–210.

24.

Wahyuni, S., Hartono, J., Supriyadi, S., & Nahartyo, E. (2018). The Information Disclosure Strategy of Single versus Benchmarks in Earnings Announcements. The Indonesian Journal of Accounting Reserach, 21(3). 321–346.

The Journal of Distribution Science