The Mediating Effect of Representativeness Heuristic on Neurofinance and SME's Financial Decision Making

Authors

  • Nurazleena Ismail Faculty of Business and Management, Universiti Teknologi MARA, Malaysia
  • Nik Maheran Nik Muhammad Global Entrepreneurship Research and innovation Centre, Universiti Malaysia Kelantan, Malaysia
  • Wan Zakiyatussariroh Wan Husin Faculty of Science Computer and Mathematics, Universiti Teknologi MARA, Malaysia
  • Aini Ismafairus Ab Halim Department of Neuro, Universiti Sains Malaysia, Malaysia

DOI:

https://doi.org/10.6000/1929-4409.2020.09.255

Keywords:

Neurofinance, financial decision-making, heuristic, emotion, Small-Medium Entreprises (SMEs).

Abstract

Financial decision-making is a crucial part of business survival, especially among SMEs. About 95% of the business are facing failures within five-year time. The financial decision making failure happened due to psychology and behavioural. This research aims to determine the mediating effect of representativeness heuristic on emotions and financial decision making. A pre-test and post-test experiment analyzes emotions, financial decision-making, and representativeness heuristic behaviour. In pre-testing, emotions and financial decision-making questionnaires are measured using questionnaires distributed to forty-two SMEs. Then, the video clips with 12 to 16 minutes duration are used in manipulating the emotions from neutral emotion to positive and negative emotions. Lastly, in post-testing, the data are gathered by repeating answered emotion and financial decision-making questionnaires, followed by the representativeness heuristic questionnaire. The data were analysed using General Linear Regression. The results showed that representativeness heuristic is partially effect on negative emotion towards financial decision making. From the analysis, neuro-behavioural of financial decision-making model has been proposed. The proposed models are incorporating with the brain components and working memory. It shows that System 1 and System 2 of the dual-process theory are activated for negative and positive emotions.

References

Artinger, F., Petersen, M., Gigerenzer, G., & Weibler, J. (2015). Heuristics as adaptive decision strategies in management. Journal of Organizational Behavior, 36(S1), S33-S52. https://doi.org/10.1002/job.1950 DOI: https://doi.org/10.1002/job.1950

Baddeley, A. D. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4, (11): 417-423. https://doi.org/10.1016/S1364-6613(00)01538-2 DOI: https://doi.org/10.1016/S1364-6613(00)01538-2

Baddeley, A. D., & Hitch, G. (1974). Working memory. In G.H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 8, pp. 47–89). New York: Academic Press. https://doi.org/10.1016/S0079-7421(08)60452-1 DOI: https://doi.org/10.1016/S0079-7421(08)60452-1

Baddeley, M. (2010). Herding, social influence and economic decision-making: socio-psychological and neuroscientific analyses. Philosopical Transaction of the Royal Society B, 281-290. https://doi.org/10.1098/rstb.2009.0169 DOI: https://doi.org/10.1098/rstb.2009.0169

Baker, H., & Nofsinger, J. R. (2010). Behavioral finance: investors, corporations and markets. New Jersey: Wiley. https://doi.org/10.1002/9781118258415 DOI: https://doi.org/10.1002/9781118258415

Bothma, J. P., Norstad, M. R., Alamos, S., & Garcia, H. G. (2018). LlamaTags: A Versatile Tool to Image Transcription Factor Dynamics in Live Embryos. Cell. https://doi.org/10.1016/j.cell.2018.03.069 DOI: https://doi.org/10.1016/j.cell.2018.03.069

Bryman, A., & Bell, E. (2015). Business Research Methods. United Kingdom: Oxford University Press.

Bursztyn, L., Ederer, F., Ferman, B., & Yuchtman, N. (2014). Understanding mechanisms underlying peer effects: Evidence from a field experiment on financial decisions. Econometrica, 82(4), 1273-1301. https://doi.org/10.3982/ECTA11991 DOI: https://doi.org/10.3982/ECTA11991

Chai, W. J., Abd Hamid, A. I., & Abdullah, J. M. (2018). Working memory from the psychological and neurosciences perspectives: A review. Frontiers in psychology, 9, 401 https://doi.org/10.3389/fpsyg.2018.00401 DOI: https://doi.org/10.3389/fpsyg.2018.00401

D'Esposito, M., & Postle, B. R. (2015). The cognitive neuroscience of working memory. Annual review of psychology, 66, 115-142. https://doi.org/10.1146/annurev-psych-010814-015031 DOI: https://doi.org/10.1146/annurev-psych-010814-015031

Dorow, A., Da Costa Jr, N., Takase, E., Prates, W., & Da Silva, S. (2018). On the neural substrates of the disposition effect and return performance. Journal of Behavioral and Experimental Finance, 17, 16-21. https://doi.org/10.1016/j.jbef.2017.12.003 DOI: https://doi.org/10.1016/j.jbef.2017.12.003

Dunn, L., & Hoegg, J. (2014). The impact of fear on emotional brant attachment. Journal of Consumer Research, 152-168. https://doi.org/10.1086/675377 DOI: https://doi.org/10.1086/675377

Duxbury, D. (2015). Behavioral finance: insights from experimnets II: biases, moods and emotions. Review of Behavioral Finance, 151-175. https://doi.org/10.1108/RBF-09-2015-0037 DOI: https://doi.org/10.1108/RBF-09-2015-0037

Eagle, M. & Barnes, T. (2009). Experimental Evaluation of an Educational Game for Improved Learning in Introductory Computing. Conference Paper in ACM SIGCSE Bulletin. https://doi.org/10.1145/1508865.1508980 DOI: https://doi.org/10.1145/1539024.1508980

Efimova, O. V. (2018). Integrating Sustainability Issues into Investment Decision Evaluation. Journal of Reviews on Global Economics, 7, 668-681. https://doi.org/10.6000/1929-7092.2018.07.61 DOI: https://doi.org/10.6000/1929-7092.2018.07.61

Efremidze, L., Sarraf, G., Miotto, K., & Zak, P. J. (2017). The Neural Inhibition of Learning Increases Asset Market Bubbles: Experimental Evidence. Journal of Behavioral Finance, 18(1), 114-124. https://doi.org/10.1080/15427560.2016.1238372 DOI: https://doi.org/10.1080/15427560.2016.1238372

Egidi, M., & Sillari, G. (2017). The Psychology of Financial Choices: From Classical and Behavioral Finance to Neurofinance. https://doi.org/10.2139/ssrn.3078670 DOI: https://doi.org/10.2139/ssrn.3078670

Friedman, H. H. (2017, June 30). Cognitive biases that interfere with critical thinking and scientific reasoning: a course module. https://doi.org/10.2139/ssrn.2958800 DOI: https://doi.org/10.2139/ssrn.2958800

Frydman, C. (2015). Relative wealth concerns in portfolio choice: neural and behavioral evidence.

Frydman, C., & Camerer, C. F. (2016). The psychology and neuroscience of financial decision making. Trennd in Cognitive Sciences, 20(9), 661-675. https://doi.org/10.1016/j.tics.2016.07.003 DOI: https://doi.org/10.1016/j.tics.2016.07.003

Gál, P., Mrva, M., & Meško, M. (2013). Heuristics, biases and traps in managerial decision making. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis , 2117-2122. https://doi.org/10.11118/actaun201361072117 DOI: https://doi.org/10.11118/actaun201361072117

Garrison, K. E., & Schmeichel, B. J. (2019). Effects of emotional content on working memory capacity. Cognition and Emotion, 33(2), 370-377. https://doi.org/10.1080/02699931.2018.1438989 DOI: https://doi.org/10.1080/02699931.2018.1438989

Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling [White paper].

Hayes, A. F., & Preacher, K. J. (2014). Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 451-470. https://doi.org/10.1111/bmsp.12028 DOI: https://doi.org/10.1111/bmsp.12028

Hayes, A. F., & Rockwood, N. J. (2017). Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behaviour research and therapy, 98, 39-57 https://doi.org/10.1016/j.brat.2016.11.001 DOI: https://doi.org/10.1016/j.brat.2016.11.001

Ho, D. E., & Imai, K. (2008). Estimating causal effects of ballot order from a randomized natural experiment. Public Opinion Quarterly, 216-240. https://doi.org/10.1093/poq/nfn018 DOI: https://doi.org/10.1093/poq/nfn018

Jiao, P. (2014). Essays on Behavioral Finance and Neurofinance (Doctoral dissertation, The Claremont Graduate University).

Johnson, H. (1972). Macroeconomics and Monetary Theory. New York: Routledge.

Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58(9), 697–720. https://doi.org/10.1037/0003-066X.58.9.697 DOI: https://doi.org/10.1037/0003-066X.58.9.697

Kahneman, D., & Tversky, A. (1974). Judgment under uncertainty: heuristics and biases. Science, 1124-1131. https://doi.org/10.1126/science.185.4157.1124 DOI: https://doi.org/10.1126/science.185.4157.1124

Kahneman, D., & Tversky, A. (1979). Prospect theory: an anlysis of decision making under risk. Econometrica, 47(2). https://doi.org/10.2307/1914185 DOI: https://doi.org/10.2307/1914185

Kahneman, D., & Tversky, A. (1984). Choices, Values, and Frames. American Psychologist, 39(4), 341–350. https://doi.org/10.1037/0003-066X.39.4.341 DOI: https://doi.org/10.1037/0003-066X.39.4.341

Kannan, G. (10 December, 2016). What's holding you back? 11 factors that derail an SME's track to success. Retrieved from www.leaderonomics.com

Kapustina, N. V., Rjachovskaya, A. N., Rjachovskij, D. I., & Gantseva, L. V. (2018). External Risk Factors Influence on the Financial Stability of Construction Companies. Journal of Reviews on Global Economics, 7, 726-730. https://doi.org/10.6000/1929-7092.2018.07.68 DOI: https://doi.org/10.6000/1929-7092.2018.07.68

Karni, E. & Schmeidler, D. (2016) Theory and Decision: An expected utility theory for state-dependent preferences 81: 467. https://doi.org/10.1007/s11238-016-9545-0 DOI: https://doi.org/10.1007/s11238-016-9545-0

Knoll, M. (2010). The role of behavioural economics and behavioral decision making in Americans' retirement saving decisions. Social Security Bulletin, 1-23.

Levy H. (2016) Expected Utility Theory. In: Stochastic Dominance. Springer, Cham https://doi.org/10.1007/978-3-319-21708-6_2 DOI: https://doi.org/10.1007/978-3-319-21708-6_2

Lindquist, K. A., Satpute, A. B., Wager, T. D., Weber, J., & Barrett, L. F. (2015). The brain basis of positive and negative affect: evidence from a meta-analysis of the human neuroimaging literature. Cerebral Cortex, 26(5), 1910-1922. https://doi.org/10.1093/cercor/bhv001 DOI: https://doi.org/10.1093/cercor/bhv001

Mateu, C., Read, J. I., & Kawata, D. (2017). Fourteen candidate RR Lyrae star streams in the inner Galaxy. Monthly Notices of the Royal Astronomical Society, 474(3), 4112-4129. https://doi.org/10.1093/mnras/stx2937 DOI: https://doi.org/10.1093/mnras/stx2937

McDermott, R. (2001). Risk-taking in international politics.

Miendlarzewska, E. A., Kometer, M., & Preuschoff, K. (2019). Neurofinance. Organizational Research Methods, 22(1), 196-222. https://doi.org/10.1177/1094428117730891 DOI: https://doi.org/10.1177/1094428117730891

Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the structure of behavior. https://doi.org/10.1037/10039-000 DOI: https://doi.org/10.1037/10039-000

Murray, J. D., Jaramillo, J., & Wang, X. J. (2017). Working memory and decision-making in a frontoparietal circuit model. Journal of Neuroscience, 37(50), 12167-12186. https://doi.org/10.1523/JNEUROSCI.0343-17.2017 DOI: https://doi.org/10.1523/JNEUROSCI.0343-17.2017

Nadler, A., Jiao, P., Johnson, C. J., Alexander, V., & Zak, P. J. (2017). The bull of wall street: experimental analysis of testosterone and asset trading. Management Science. https://doi.org/10.2139/ssrn.2557094 DOI: https://doi.org/10.2139/ssrn.2557094

Nigam, R. M., Srivastava, S., & Banwet, D. K. (2018). Behavioral mediators of financial decision making – a state-of-art literature review. Review of Behavioral Finance, 2-41. https://doi.org/10.1108/RBF-07-2016-0047 DOI: https://doi.org/10.1108/RBF-07-2016-0047

Peterson, R. (2007). Affect and financial decision-making: how neuroscience can inform market participants. The Journal of Behavioral Finance, 8(2), 70-78. https://doi.org/10.1080/15427560701377448 DOI: https://doi.org/10.1080/15427560701377448

Peterson, R. (2010). Neuroeconomics and neurofinance. New York: Wiley. https://doi.org/10.1002/9781118258415.ch5 DOI: https://doi.org/10.1002/9781118258415.ch5

Rocha, A. F., Vieito, J., & Rocha, F. T. (2013). Neurofinance: how do we make financial decisions. Investor Education and Financial Behaviour Conference (pp. 1-19). Rio de Janeiro: Research on Artificial and Natural Intelligence.

Sahi, S. K. (2012). Neurofinance and investment behaviour. Studies in Economics and Finance, 29(4), 246-267. https://doi.org/10.1108/10867371211266900 DOI: https://doi.org/10.1108/10867371211266900

Schwarz, N. (1990). Feelings as information: Informational and motivational functions of affective state. In E. Higgins, & R. Sorrentino, Handbook of motivation and cognition: Foundations of social behavior (pp. 527-561). New York: NY: Guilford Press.

Schwarz, N., & Bless, H. (1991). Happy and mindless, but sad and smart? The impact of affective states on analytic reasoning. In J. Forgas, Emotion and social judgments (pp. 55-71). Oxford, England: Pergamon. https://doi.org/10.4324/9781003058731-4 DOI: https://doi.org/10.4324/9781003058731-4

Sen A. (2008) Rational Behaviour. In: Palgrave Macmillan (eds) The New Palgrave Dictionary of Economics. Palgrave Macmillan, London https://doi.org/10.1057/978-1-349-95121-5_1568-2 DOI: https://doi.org/10.1057/978-1-349-95121-5_1568-2

Seshan, G., & Yang, D. (2014). Motivating migrants: A field experiment on financial decision-making in transnational households. Journal of Development Economics, 108, 119-127 https://doi.org/10.1016/j.jdeveco.2014.01.005 DOI: https://doi.org/10.1016/j.jdeveco.2014.01.005

Sewwandi, W. (2015). Behavioral biases in investment deciison making: a review. 6th International Conference on Business & Information. Sri Lanka: Faculty of Commerce and Management Studies, University of Kelaniya.

Simon, H. (1959). Theories of decision-making in economics and behavioral science. The American Economic Review, 253-283.

Stinjak, E. L. M., & Ghozali, I. (2012). The Investor Indonesia Behavior on Stock Investment Decision Making: Disposition Effect, Cognition and Accounting Information. psychology, 3(8).

Storbeck, J., & Maswood, R. (2016). Happiness increases verbal and spatial working memory capacity where sadness does not: Emotion, working memory and executive control. Cognition and Emotion, 30(5), 925-938 https://doi.org/10.1080/02699931.2015.1034091 DOI: https://doi.org/10.1080/02699931.2015.1034091

Tartidi, C., Hahnel, U. J., Jeanmonod, N., Sander, D., & Brosch, T. (2018). Affective Dilemmas: The Impact of Trait Affect and State Emotion on Sustainable Consumption Decisions in a Social Dilemma Task. Environment and Behavior, 0013916518787590. https://doi.org/10.1177/0013916518787590 DOI: https://doi.org/10.1177/0013916518787590

Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect schedule (PANAS). Journal of Cross-Cultural Psychology, 227-242. https://doi.org/10.1177/0022022106297301 DOI: https://doi.org/10.1177/0022022106297301

Tisdell, C. A. (2014). Rational Behaviour as a Basis for Economic Theories'. Rationality and the Social Sciences (RLE Social Theory): Contributions to the Philosophy and Methodology of the Social Sciences, 196-220.

Venkatapathy, R., & Sultana, A. H. (2016). Behavioural finance: heuristics in investment decision making. TEJAS Thiagarajar College Journal, 35-44.

Vives, M.-L., Aparici, M., & Costa, A. (2018). The limits of the foreign language effect on decision-making: The case of the outcome bias and the representativeness heuristic. PLOS ONE, 1-14. https://doi.org/10.1371/journal.pone.0203528 DOI: https://doi.org/10.1371/journal.pone.0203528

Wan, W. (2018). Prospect theory and investment decision behavior: a review. 2018 International Conference on Education Technology and Social Sciences (ETSOCS 2018) (pp. 114-118). Francis Academic Press, UK.

Winter, E. (2014). Feeling Smart: Why Our Emotions Are More Rational Than We Think. Jerusalem: PublicAffairs Publishing.

Winter, E. (2015). Financial decisions and emotions: why do we like others to decide for us on our finances? Psychology Today.

Wong, A., Holmes, S., & Schaper, M. T. (2018). How do small business owners actually make their financial decisions? Understanding SME financial behaviour using a case-based approach. Small Enterprise Research, 25(1), 36-51. https://doi.org/10.1080/13215906.2018.1428909 DOI: https://doi.org/10.1080/13215906.2018.1428909

Xie, W., & Zhang, W. (2016). Negative emotion boosts quality of visual working memory representation. Emotion, 16(5), 760. https://doi.org/10.1037/emo0000159 DOI: https://doi.org/10.1037/emo0000159

Yang, J. (2017). An empirical study of Meta-Cognition in English writing course. Proceedings of the Sixth Northeast Asia International Symposium on Language, Literature and Translation. Datong, China. Pg.640-43

Downloads

Published

2022-04-05

How to Cite

Ismail, N. ., Nik Muhammad, N. M. ., Wan Husin, W. Z. ., & Ab Halim, A. I. . (2022). The Mediating Effect of Representativeness Heuristic on Neurofinance and SME’s Financial Decision Making. International Journal of Criminology and Sociology, 9, 2157–2167. https://doi.org/10.6000/1929-4409.2020.09.255

Issue

Section

Articles

Most read articles by the same author(s)