Anchoring effect in managerial decision-making in accountants and managers: an experimental study
DOI:
https://doi.org/10.7213/rebrae.v11i3.24210Palabras clave:
Anchoring. Decision-making. Cognitive biases. Behavioral finance. Behavioral economy ics.Resumen
The objective of this work was to analyze, by means of an experiment, if the type (positive or negative) and the level (simple or complex) of economic-financial information influence the anchoring effect of accountants and managers in a process of managerial decision-making. To do so, an experimental methodology targeting a sample of 86 Accountants, 68 Managers and 118 people with different professional activities (control group) was used. The results showed, in the first test without differentiation of factors (type and level), that about 96% of the participants have the anchoring effect, leaning towards minimum and maximum estimates of sales revenue, operating expenditure and result. In addition, the ANOVA and the Approximate Permutation Test brought significant evidence that the anchoring effect in minimum projections can be influenced by the type of information, not being significant for anchoring in maximum projections and for the level of information on both estimates (minimum and maximum). Finally, the conclusion is that positive information increases the anchoring effect and negative information decreases the anchoring effect in minimum estimates in relation to the low anchor.
Descargas
Citas
BIRNBERG, J. G., GANGULY, A. R. Is neuroaccounting waiting in the wings? An essay. Ac-counting, Organizations and Society, 37(1), 1-13. 2012. doi: http://dx.doi.org/10.1016/j.aos.2011.11.004
BUSENITZ, L. W., BARNEY, J. B. Differences between entrepreneurs and managers in large organizations: Biases and heuristics in strategic decision-making. Journal of Business Venturing, 12(1), 9-30. 1997. doi: http://dx.doi.org/10.1016/S0883-9026(96)00003-1
CAPUTO, A. Relevant information, personality traits and anchoring effect. International Journal of Management and Decision Making, 13(1), 62-76. 2014. doi: 10.1504/IJMDM.2014.058470
CONOVER, W. J., JOHNSON, M. E., JOHNSON, M. M. A COMPARATIVE-STUDY OF TESTS FOR HOMOGENEITY OF VARIANCES, WITH APPLICATIONS TO THE OUTER CONTINENTAL-SHELF BIDDING DATA. technometrics, 23(4), 351-361. 1981. doi: 10.2307/1268225
COSTA, D. F., CARVALHO, F. d. M., MOREIRA, B. C. d. M. Behavioral Economics and Behav-ioral Finance: A Bibliometric Analysis of the Scientific Fields. Journal of Economic Sur-veys, n/a-n/a. doi: 10.1111/joes.12262. 2018.
COSTA, D. F., CARVALHO, F. d. M., MOREIRA, B. C. d. M., PRADO, J. W. d. Bibliometric analy-sis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias. Scientometrics, 111(3), 1775-1799. 2017. doi: 10.1007/s11192-017-2371-5
DEAN, A., VOSS, D. Design and Analysis of Experiments. New York: Springer. 1999.
EDWARDS, W. The theory of decision making. Psychological bulletin, 51(4), 380. 1954.
EPLEY, N., GILOVICH, T. Putting adjustment sack in the anchoring and adjustment heuristic: Differential processing of self-generated and experimenter-provided anchors. Psychological science, 12(5), 391-396. 2001. doi: 10.1111/1467-9280.00372
EPLEY, N; GILOVICH, T. The anchoring-and-adjustment heuristic : Why the adjustments are insufficient. Psychological science, 17(4), 311-318. 2006. doi: 10.1111/j.1467-9280.2006.01704.x
EVERITT, B. S., SKRONDAL, A. The Cambridge Dictionary of Statistics: Cambridge Univer-sity Press. 2010.
FURNHAM, A., BOO, H. C. A literature review of the anchoring effect. The Journal of Socio-Economics, 40(1), 35-42. 2011. doi: http://dx.doi.org/10.1016/j.socec.2010.10.008
GARCÍA, M. J. R. Financial education and behavioral finance: New insights into the role of information in financial decisions. Journal of Economic Surveys, 27(2), 297-315. 2013. doi: 10.1111/j.1467-6419.2011.00705.x
GOSLING, S. D., MASON, W. Internet Research in Psychology. Annual Review of Psycholo-gy, 66(1), 877-902. 2015. doi: doi:10.1146/annurev-psych-010814-015321
GREEN, D., JACOWITZ, K. E., KAHNEMAN, D., McFADDEN, D. Referendum contingent valua-tion, anchoring, and willingness to pay for public goods. Resource and Energy Economics, 20(2), 85-116. 1998. doi: http://dx.doi.org/10.1016/S0928-7655(97)00031-6
HAYES, A. F. SPSS procedures for approximate randomization tests. Behavior Research Methods, Instruments, & Computers, 30(3), 536-543. 1998. doi: 10.3758/bf03200687
HIRSHLEIFER, D., TEOH, S. The Psychological Attraction Approach to Accounting and Dis-closure Policy. Contemp. Account. Res., 26(4), 1067-+. 2009. doi: 10.1506/car.26.4.3
HURD, M. D. Anchoring and Acquiescence Bias in Measuring Assets in Household Sur-veys.(Author abstract). Journal of Risk and Uncertainty, 19(1 3), 111. 1999.
JACOWITZ, K. E., KAHNEMAN, D. MEASURES OF ANCHORING IN ESTIMATION TASKS. Personality and Social Psychology Bulletin, 21(11), 1161-1166. 1995. doi: 10.1177/01461672952111004
KAHNEMAN, D. Reference points, anchors, norms, and mixed feelings. Organizational Behavior and Human Decision Processes, 51(2), 296-312. 1992. doi: http://dx.doi.org/10.1016/0749-5978(92)90015-Y
KAHNEMAN, D., SMITH, V. Foundations of Behavioral and Experimental Economics. Nobel Prize in Economics Documents, 1. 2002.
KAUSTIA, M., ALHO, E., PUTTONEN, V. How much does expertise reduce behavioral biases? The case of anchoring effects in stock return estimates. Financial Management, 37(3), 391-411. 2008. doi: 10.1111/j.1755-053X.2008.00018.x
LUPPE, M. R., FÁVERO, L. P. L. Anchoring heuristic and the estimation of accounting and financial indicators. International Journal of Finance and Accounting, 1(5), 120-130. 2012.
NEUMANN, B. R., ROBERTS, M. L., CAUVIN, E. Stakeholder value disclosures: Anchoring on primacy and importance of financial and nonfinancial performance measures. Review of Managerial Science, 5(2), 195-212. 2011. doi: 10.1007/s11846-010-0054-1
POMPIAN, M. Behavioral finance and wealth management: how to build optimal portfo-lios that account for investor biases (Vol. 667): John Wiley & Sons. 2012.
R CORE TEAM. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. 2017. from https://http://www.r-project.org
REIPS, U.-D. Internet-Based Psychological Experimenting: Five Dos and Five Don’ts. Social Science Computer Review, 20(3), 241-249. 2002a . doi: 10.1177/089443930202000302
REIPS, U.-D. Standards for Internet-Based Experimenting. Experimental Psychology, 49(4), 243-256. 2002b . doi: doi:10.1026/1618-3169.49.4.243
RUSSO, J. E., SCHOEMAKER, P. J. Managing overconfidence. Sloan Management Review, 33(2), 7-17. 1992.
SCHADE, C., KOELLINGER, P. Heuristics, biases, and the behavior of entrepreneurs. In M. Minniti (Ed.), Entrepreneurship: The Engin of Growth (Vol. 1, pp. 41-63). Westport, Con-necticut, London, USA: Praeger. 2007.
SERFAS, S. The impact of cognitive biases on capital investments - Empirical evidence re-garding the anchoring heuristic. Zeitschrift fur Planung und Unternehmenssteuerung, 1-20. 2011. doi: 10.1007/s00187-011-0120-0
SHAPIRA, Z., SHAVER, J. M. Confounding changes in averages with marginal effects: How anchoring can destroy economic value in strategic investment assessments. Strategic Man-agement Journal, 35(10), 1414-1426. 2014. doi: 10.1002/smj.2165
SKITKA, L. J., SARGIS, E. G. The Internet as Psychological Laboratory. Annual Review of Psychology, 57(1), 529-555. 2006. doi: doi:10.1146/annurev.psych.57.102904.190048
TVERSKY, A., KAHNEMAN, D. Judgment under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124-1131. 1974. doi: 10.1126/science.185.4157.1124
WHEELER, B., TORCHIANO, M. Permutation tests for linear models in R. R package version 2.1.0. 1, 2016, 2016-08-02. from https://cran.r-project.org/web/packages/lmPerm/index.html
