Solving problems with an Aha! increases risk preference

References

• Alter, A. L., & Oppenheimer, D. M. (2006). Predicting short-term fluctuations by using processing fluency. Proceedings of the National Academy of Sciences of the United States of America, 103(24), 9369–9372. https://doi.org/10.1073/PNAS.0601071103/SUPPL_FILE/01071TABLE1.PDF
   PubMed Web of Science ®Google Scholar
• Becker, M., Kühn, S., & Sommer, T. (2021). Verbal insight revisited—Dissociable neurocognitive processes underlying solutions accompanied by an AHA! experience with and without prior restructuring. Journal of Cognitive Psychology, 33(6–7), 659–684. https://doi.org/10.1080/20445911.2020.1819297
   Web of Science ®Google Scholar
• Becker, M., Sommer, T., & Kühn, S. (2020). Verbal insight revisited: FMRI evidence for early processing in bilateral insulae for solutions with AHA! experience shortly after trial onset. Human Brain Mapping, 41(1), 30–45. https://doi.org/10.1002/hbm.24785
   PubMed Web of Science ®Google Scholar
• Binswanger, H. P. (1981). Attitudes toward risk: Theoretical implications of an experiment in rural India. The Economic Journal, 91(364), 867. https://doi.org/10.2307/2232497
   Web of Science ®Google Scholar
• Blais, A.-R., & Weber, E. U. (2006). A Domain-Specific Risk-Taking (DOSPERT) scale for adult populations. Judgment and Decision Making, 1(1), 33–47. http://ssrn.com/abstract=1301089Electroniccopyavailableat:http://ssrn.com/abstract=1301089 https://doi.org/10.1017/S1930297500000334
   Web of Science ®Google Scholar
• Bowden, E. M., & Jung-Beeman, M. (2003). Normative data for 144 compound remote associate problems. Behavior Research Methods, Instruments, & Computers, 35(4), 634–639. https://doi.org/10.3758/BF03195543
   PubMedGoogle Scholar
• Bowden, E., & M., Jung-Beeman, M. (2007). Methods for investigating the neural components of insight. Methods, 42(1), 87–99. https://doi.org/10.1016/j.ymeth.2006.11.007
   PubMed Web of Science ®Google Scholar
• Bowden, E., Jung-Beeman, M., Fleck, J., & Kounios, J. (2005). New approaches to demystifying insight. Trends in Cognitive Sciences, 9(7), 322–328. https://doi.org/10.1016/j.tics.2005.05.012
   PubMed Web of Science ®Google Scholar
• Bradley, M. M., & Lang, P. J. (2009). Emotion and motivation. In J. T. Cacioppo, L. G. Tassinary, & G. G. Berntson (Eds.), Handbook of psychophysiology (pp. 581–607). Cambridge University Press. https://doi.org/10.1017/CBO9780511546396.025
   Google Scholar
• Brooks, M. E., Kristensen, K., van Benthem, K. J., Magnusson, A., Berg, C. W., Nielsen, A., Skaug, H. J., Mächler, M., & Bolker, B. M. (2017). glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal, 9(2), 378–400. https://doi.org/10.32614/RJ-2017-066
   Google Scholar
• Brühlmann, F., Petralito, S., Aeschbach, L. F., & Opwis, K. (2020). The quality of data collected online: An investigation of careless responding in a crowdsourced sample. Methods in Psychology, 2, 100022. https://doi.org/10.1016/j.metip.2020.100022
   Google Scholar
• Bruner, D. M. (2009). Changing the probability versus changing the reward. Experimental Economics, 12(4), 367–385. https://doi.org/10.1007/s10683-009-9219-7
   Web of Science ®Google Scholar
• Brunyé, T. T., Gagnon, S. A., Paczynski, M., Shenhav, A., Mahoney, C. R., & Taylor, H. A. (2013). Happiness by association: Breadth of free association influences affective states. Cognition, 127(1), 93–98. https://doi.org/10.1016/J.COGNITION.2012.11.015
   PubMed Web of Science ®Google Scholar
• Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. Journal of Personality and Social Psychology, 67(2), 319–333. https://doi.org/10.1037/0022-3514.67.2.319
   Web of Science ®Google Scholar
• Charness, G., Gneezy, U., & Imas, A. (2013). Experimental methods: Eliciting risk preferences. Journal of Economic Behavior & Organization, 87, 43–51. https://doi.org/10.1016/j.jebo.2012.12.023
   Web of Science ®Google Scholar
• Chiles, T. H., & Mcmackin, J. (1996). Integrating variable risk preferences, trust, and transaction cost economics. The Academy of Management Review, 21(1), 73–99. https://doi.org/10.2307/258630
   Web of Science ®Google Scholar
• Cranford, E. A., & Moss, J. (2012). Is insight always the same? A protocol analysis of insight in compound remote associate problems. The Journal of Problem Solving, 4(2), 128. https://doi.org/10.7771/1932-6246.1129
   Google Scholar
• Danek, A. H., Fraps, T., von Müller, A., Grothe, B., & Öllinger, M. (2013). Aha! experiences leave a mark: Facilitated recall of insight solutions. Psychological Research, 77(5), 659–669. https://doi.org/10.1007/S00426-012-0454-8
   PubMed Web of Science ®Google Scholar
• Danek, A. H., Fraps, T., von Müller, A., Grothe, B., & Öllinger, M. (2014). It’s a kind of magic-what self-reports can reveal about the phenomenology of insight problem solving. Frontiers in Psychology, 5, 1408. https://doi.org/10.3389/FPSYG.2014.01408/ABSTRACT
   PubMed Web of Science ®Google Scholar
• Danek, A. H., & Wiley, J. (2016). What about false insights? Deconstructing the Aha! experience along its multiple dimensions for correct and incorrect solutions separately. Frontiers in Psychology, 7, 2077. https://doi.org/10.3389/fpsyg.2016.02077
   PubMedGoogle Scholar
• Danek, A. H., & Wiley, J. (2020). What causes the insight memory advantage? Cognition, 205, 104411. https://doi.org/10.1016/J.COGNITION.2020.104411
   PubMed Web of Science ®Google Scholar
• Danek, A. H., Wiley, J., & Öllinger, M. (2016). Solving classical insight problems without Aha! experience: 9 Dot, 8 coin, and matchstick arithmetic problems. Journal of Problem Solving, 9, 4. https://doi.org/10.7771/1932-6246.1183
   Web of Science ®Google Scholar
• Danek, A. H., Williams, J., & Wiley, J. (2020). Closing the gap: Connecting sudden representational change to the subjective Aha! experience in insightful problem solving. Psychological Research, 84(1), 111–119. https://doi.org/10.1007/S00426-018-0977-8
   PubMed Web of Science ®Google Scholar
• Demaree, H., Dedonno, M. A., Burns, K. J., & Everhart, D. E. (2008). You bet: How personality differences affect risk-taking preferences. Personality and Individual Differences, 44(7), 1484–1494. https://doi.org/10.1016/j.paid.2008.01.005
   Web of Science ®Google Scholar
• Drichoutis, A. C., & Lusk, J. L. (2016). What can multiple price lists really tell us about risk preferences? Journal of Risk and Uncertainty, 53(2–3), 89–106. https://doi.org/10.1007/s11166-016-9248-5
   Web of Science ®Google Scholar
• Falk, A., Becker, A., Dohmen, T., & Huffman, D. (2016). The preference survey module: A validated instrument for measuring risk, time, and social preferences. http://ftp.iza.org/dp9674.pdf
   Google Scholar
• Fama, E. F., & French, K. R. (2004). The capital asset pricing model: Theory and evidence. Journal of Economic Perspectives, 18(3), 25–46. https://doi.org/10.1257/0895330042162430
   Web of Science ®Google Scholar
• Frey, R., Pedroni, A., Mata, R., Rieskamp, J., & Hertwig, R. (2017). Risk preference shares the psychometric structure of major psychological traits. Science Advances, 3(10), e1701381. https://doi.org/10.1126/sciadv.1701381
   PubMed Web of Science ®Google Scholar
• Galentino, A., Bonini, N., & Savadori, L. (2017). Positive arousal increases individuals’ preferences for risk. Frontiers in Psychology, 8, 2142. https://doi.org/10.3389/FPSYG.2017.02142/BIBTEX
   PubMed Web of Science ®Google Scholar
• Gick, M. L., & Lockhart, R. S. (1995). Cognitive and affective components of insight. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 197–228). The MIT Press. https://psycnet.apa.org/record/1994-98855-006
   Google Scholar
• Hedne, M. R., Norman, E., & Metcalfe, J. (2016). Intuitive feelings of warmth and confidence in insight and noninsight problem solving of magic tricks. Frontiers in Psychology, 7, 1314. https://doi.org/10.3389/FPSYG.2016.01314/BIBTEX
   PubMed Web of Science ®Google Scholar
• Herman, A. M., Critchley, H. D., & Duka, T. (2018). Risk-taking and impulsivity: The role of mood states and interoception. Frontiers in Psychology, 9, 1625. https://doi.org/10.3389/fpsyg.2018.01625
   PubMed Web of Science ®Google Scholar
• Hillson, D., & Murray-Webster, R. (2017). Understanding and managing risk attitude: Second edition (pp. 1–183). Routledge. https://doi.org/10.4324/9781315235448/UNDERSTANDING-MANAGING-RISK-ATTITUDE-DAVID-HILLSON-RUTH-MURRAY-WEBSTER
   Google Scholar
• Holt, C. A., & Laury, S. K. (2002). Risk aversion and incentive effects. American Economic Review, 92(5), 1644–1655. https://doi.org/10.1257/000282802762024700
   Web of Science ®Google Scholar
• Jiang, Y., Cho, A., & Adaval, R. (2009). The unique consequences of feeling lucky: Implications for consumer behavior. Journal of Consumer Psychology, 19(2), 171–184. https://doi.org/10.1016/j.jcps.2009.02.010
   Web of Science ®Google Scholar
• Josef, A. K., Richter, D., Samanez-Larkin, G. R., Wagner, G. G., Hertwig, R., & Mata, R. (2016). Stability and change in risk-taking propensity across the adult life span. Journal of Personality and Social Psychology, 111(3), 430–450. https://doi.org/10.1037/pspp0000090
   PubMed Web of Science ®Google Scholar
• Juergensen, J., Weaver, J. S., May, C. N., & Demaree, H. A. (2018). More than money: Experienced positive affect reduces risk-taking behavior on a real-world gambling task. Frontiers in Psychology, 9, 2116. https://doi.org/10.3389/fpsyg.2018.02116
   PubMed Web of Science ®Google Scholar
• Jung-Beeman, M., Bowden, E. M., Haberman, J., Frymiare, J. L., Arambel-Liu, S., Greenblatt, R., Reber, P. J., & Kounios, J. (2004). Neural activity when people solve verbal problems with insight. PLoS Biology, 2(4), E97. https://doi.org/10.1371/journal.pbio.0020097
   PubMed Web of Science ®Google Scholar
• Kaplan, C. A., & Simon, H. A. (1990). In search of insight. Cognitive Psychology, 22(3), 374–419. https://doi.org/10.1016/0010-0285(90)90008-R
   Web of Science ®Google Scholar
• Keith, M. G., Tay, L., & Harms, P. D. (2017). Systems perspective of Amazon Mechanical Turk for organizational research: Review and recommendations. Frontiers in Psychology, 8, 1359. https://doi.org/10.3389/fpsyg.2017.01359
   PubMed Web of Science ®Google Scholar
• Kizilirmak, J. M., Galvao Gomes da Silva, J., Imamoglu, F., & Richardson-Klavehn, A. (2016). Generation and the subjective feeling of “aha!” are independently related to learning from insight. Psychological Research, 80(6), 1059–1074. https://doi.org/10.1007/S00426-015-0697-2
   PubMed Web of Science ®Google Scholar
• Kizilirmak, J. M., Thuerich, H., Folta-Schoofs, K., Schott, B. H., & Richardson-Klavehn, A. (2016). Neural correlates of learning from induced insight: A case for reward-based episodic encoding. Frontiers in Psychology, 7, 1693. https://doi.org/10.3389/FPSYG.2016.01693/BIBTEX
   PubMed Web of Science ®Google Scholar
• Knoblich, G., Ohlsson, S., Haider, H., & Rhenius, D. (1999). Constraint relaxation and chunk Decomposition in insight problem solving. Journal of Experimental Psychology: Learning Memory and Cognition, 25(6), 1534–1555. https://doi.org/10.1037/0278-7393.25.6.1534
   Web of Science ®Google Scholar
• Knutson, B., & Greer, S. M. (2008). Anticipatory affect: Neural correlates and consequences for choice. Philosophical Transactions of the Royal Society B: Biological Sciences, 363(1511), 3771–3786. https://doi.org/10.1098/rstb.2008.0155
   PubMed Web of Science ®Google Scholar
• Knutson, B., Katovich, K., & Suri, G. (2014). Inferring affect from fMRI data. Trends in Cognitive Sciences, 18(8), 422–428. https://doi.org/10.1016/J.TICS.2014.04.006
   PubMed Web of Science ®Google Scholar
• Kounios, J., & Beeman, M. (2014). The cognitive neuroscience of insight. Annual Review of Psychology, 65(1), 71–93. _ https://doi.org/10.1146/annurev-psych-010213-115154
   PubMed Web of Science ®Google Scholar
• Kounios, J., Frymiare, J. L., Bowden, E. M., Fleck, J. I., Subramaniam, K., Parrish, T. B., & Jung-Beeman, M. (2006). The prepared mind neural activity prior to problem presentation predicts subsequent solution by sudden insight. Psychological Science, 17(10), 882–890. https://doi.org/10.1111/j.1467-9280.2006.01798.x
   PubMed Web of Science ®Google Scholar
• Kuhnen, C., Knutson, B., Kuhnen, C., & Knutson, B. (2011). The influence of affect on beliefs, preferences, and financial decisions. Journal of Financial and Quantitative Analysis, 46(3), 605–626. https://econpapers.repec.org/RePEc:cup:jfinqa:v:46:y:2011:i:03:p:605-626_00 https://doi.org/10.1017/S0022109011000123
   Web of Science ®Google Scholar
• Laukkonen, R. E., Kaveladze, B. T., Protzko, J., Tangen, J. M., von Hippel, W., & Schooler, J. W. (2022). Irrelevant insights make worldviews ring true. Scientific Reports, 12(1), 2075. 1 https://doi.org/10.1038/s41598-022-05923-3
   PubMed Web of Science ®Google Scholar
• Laukkonen, R. E., Kaveladze, B. T., Tangen, J. M., & Schooler, J. W. (2020). The dark side of Eureka: Artificially induced Aha moments make facts feel true. Cognition, 196, 104122. https://doi.org/10.1016/j.cognition.2019.104122
   PubMed Web of Science ®Google Scholar
• Laukkonen, R. E., & Tangen, J. M. (2018). How to detect insight moments in problem solving experiments. Frontiers in Psychology, 9, 282. https://doi.org/10.3389/fpsyg.2018.00282
   PubMed Web of Science ®Google Scholar
• Laukkonen, R. E., Webb, M., Salvi, C., Tangen, J. M., Slagter, H. A., & Schooler, J. W. (2023). On selecting ideas: Cognitive and neurocomputational mechanisms of insight. https://psyarxiv.com/ez3tn/
   Google Scholar
• Loewenstein, G. F., Hsee, C. K., Weber, E. U., & Welch, N. (2001). Risk as feelings. Psychological Bulletin, 127(2), 267–286. https://doi.org/10.1037/0033-2909.127.2.267
   PubMed Web of Science ®Google Scholar
• Ludvig, E. A., Madan, C. R., & Spetch, M. L. (2015). Priming memories of past wins induces risk seeking. Journal of Experimental Psychology. General, 144(1), 24–29. https://doi.org/10.1037/xge0000046
   PubMed Web of Science ®Google Scholar
• Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
   Web of Science ®Google Scholar
• Mata, R., Frey, R., Richter, D., Schupp, J., & Hertwig, R. (2018). Risk preference: A view from psychology. Journal of Economic Perspectives, 32(2), 155–172. https://doi.org/10.1257/jep.32.2.155
   PubMed Web of Science ®Google Scholar
• Mayer, R. E. (1995). The search for insight: Grappling with Gestalt psychology’s unanswered questions. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 3–32). The MIT Press.
   Google Scholar
• McDougal, Y. B. (1995). Decision making under risk: Risk preference, monetary goals and information search. Personality and Individual Differences, 18(6), 771–782. https://doi.org/10.1016/0191-8869(94)00207-9
   Web of Science ®Google Scholar
• Nygren, T. E., Isen, A. M., Taylor, P. J., & Dulin, J. (1996). The influence of positive affect on the decision rule in risk situations: Focus on outcome (and especially avoidance of loss) rather than probability. Organizational Behavior and Human Decision Processes, 66(1), 59–72. http://faculty.virginia.edu/familyandtenure/_notes/assets/isen.pdf https://doi.org/10.1006/obhd.1996.0038
   Web of Science ®Google Scholar
• Oh, Y., Chesebrough, C., Erickson, B., Zhang, F., & Kounios, J. (2020). An insight-related neural reward signal. NeuroImage, 214, 116757. https://doi.org/10.1016/j.neuroimage.2020.116757
   PubMed Web of Science ®Google Scholar
• Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the Barratt Impulsiveness Scale. Journal of Clinical Psychology, 51(6), 768–774. https://doi.org/10.1002/1097-4679(199511)51:6<768::AID-JCLP2270510607>3.0.CO;2-1
   PubMed Web of Science ®Google Scholar
• Phelps, E. A. (2006). Emotion and cognition: Insights from studies of the human amygdala. Annual Review of Psychology, 57(1), 27–53. https://doi.org/10.1146/annurev.psych.56.091103.070234
   PubMed Web of Science ®Google Scholar
• Powell, M., & Ansic, D. (1997). Gender differences in risk behaviour in financial decision-making: An experimental analysis. Journal of Economic Psychology, 18(6), 605–628. https://doi.org/10.1016/S0167-4870(97)00026-3
   Web of Science ®Google Scholar
• Pratt, J. W. (1978). Risk aversion in the small and in the large. In P. Diamond & M. Rothschild (Eds.), Uncertainty in economics (pp. 59–79). Academic Press. https://doi.org/10.1016/B978-0-12-214850-7.50010-3
   Google Scholar
• Salvi, C. (2023). Markers of insight. In The Routledge international handbook of creative cognition (1st ed., pp. 475–490). Routledge. https://doi.org/10.4324/9781003009351-30
   Google Scholar
• Salvi, C., Beeman, M., Bikson, M., McKinley, R., & Grafman, J. (2020). TDCS to the right anterior temporal lobe facilitates insight problem-solving. Scientific Reports, 10(1), 946. https://doi.org/10.1038/s41598-020-57724-1
   PubMed Web of Science ®Google Scholar
• Salvi, C., & Bowden, E. (2020). The relation between state and trait risk taking and problem-solving. Psychological Research, 84(5), 1235–1248. https://doi.org/10.1007/s00426-019-01152-y
   PubMed Web of Science ®Google Scholar
• Salvi, C., Bricolo, E., Franconeri, S. L., Kounios, J., & Beeman, M. (2015). Sudden insight is associated with shutting out visual inputs. Psychonomic Bulletin & Review, 22(6), 1814–1819. https://doi.org/10.3758/s13423-015-0845-0
   PubMed Web of Science ®Google Scholar
• Salvi, C., Bricolo, E., Kounios, J., Bowden, E., & Beeman, M. (2016). Insight solutions are correct more often than analytic solutions. Thinking & Reasoning, 22(4), 443–460. https://doi.org/10.1080/13546783.2016.1141798
   PubMed Web of Science ®Google Scholar
• Salvi, C., Simoncini, C., Grafman, J., & Beeman, M. (2020). Oculometric signature of switch into awareness? Pupil size predicts sudden insight whereas microsaccades predict problem-solving via analysis. NeuroImage, 217, 116933. https://doi.org/10.1016/j.neuroimage.2020.116933
   PubMed Web of Science ®Google Scholar
• Samanez-Larkin, G. R., & Knutson, B. (2015). Decision making in the ageing brain: Changes in affective and motivational circuits. Nature Reviews. Neuroscience, 16(5), 278–289. https://doi.org/10.1038/nrn3917
   PubMed Web of Science ®Google Scholar
• Sanders, K. E. G., Osburn, S., Paller, K. A., & Beeman, M. (2019). Targeted memory reactivation during sleep improves next-day problem solving. Psychological Science, 30(11), 1616–1624. https://doi.org/10.1177/0956797619873344
   PubMed Web of Science ®Google Scholar
• Santarnecchi, E., Sprugnoli, G., Bricolo, E., Costantini, G., Liew, S. L., Musaeus, C. S., Salvi, C., Pascual-Leone, A., Rossi, A., & Rossi, S. (2019). Gamma tACS over the temporal lobe increases the occurrence of Eureka! Moments. Scientific Reports, 9(1), 5778. https://doi.org/10.1038/s41598-019-42192-z
   PubMedGoogle Scholar
• Shen, W., Yuan, Y., Liu, C., & Luo, J. (2016). In search of the “Aha!” experience: Elucidating the emotionality of insight problem-solving. British Journal of Psychology, 107(2), 281–298. https://doi.org/10.1111/BJOP.12142
   PubMed Web of Science ®Google Scholar
• Sprugnoli, G., Rossi, S., Emmendorfer, A., Rossi, A., Liew, S. L., Tatti, E., di Lorenzo, G., Pascual-Leone, A., & Santarnecchi, E. (2017). Neural correlates of Eureka moment. Intelligence, 62(March), 99–118. https://doi.org/10.1016/j.intell.2017.03.004
   Google Scholar
• Strickland, J. C., & Stoops, W. W. (2019). The use of crowdsourcing in addiction science research: Amazon Mechanical Turk. Experimental and Clinical Psychopharmacology, 27(1), 1–18. https://doi.org/10.1037/pha0000235
   PubMed Web of Science ®Google Scholar
• Subramaniam, K., Kounios, J., Parrish, T. B., & Jung-Beeman, M. (2009). A brain mechanism for facilitation of insight by positive affect. Journal of Cognitive Neuroscience, 21(3), 415–432. https://doi.org/10.1162/jocn.2009.21057
   PubMed Web of Science ®Google Scholar
• Tik, M., Sladky, R., Luft, C. D. B., Willinger, D., Hoffmann, A., Banissy, M. J., Bhattacharya, J., & Windischberger, C. (2018). Ultra-high-field fMRI insights on insight: Neural correlates of the Aha!-moment. Human Brain Mapping, 39(8), 3241–3252. https://doi.org/10.1002/hbm.24073
   PubMed Web of Science ®Google Scholar
• Tompkins, M. K., Bjälkebring, P., & Peters, E. (2018). Emotional aspects of risk perceptions. In Psychological perspectives on risk and risk analysis: Theory, models, and applications (pp. 109–130). Springer International Publishing. https://doi.org/10.1007/978-3-319-92478-6_5
   Google Scholar
• Topolinski, S., Likowski, K. U., Weyers, P., & Strack, F. (2009). The face of fluency: Semantic coherence automatically elicits a specific pattern of facial muscle reactions. Cognition & Emotion, 23(2), 260–271. https://doi.org/10.1080/02699930801994112
   Web of Science ®Google Scholar
• Topolinski, S., & Reber, R. (2010). Gaining insight into the “Aha” experience. Current Directions in Psychological Science, 19(6), 402–405. https://doi.org/10.1177/0963721410388803
   Web of Science ®Google Scholar
• Tulver, K., Kaup, K. K., Laukkonen, R., & Aru, J. (2023). Restructuring insight: An integrative review of insight in problem-solving, meditation, psychotherapy, delusions and psychedelics. Consciousness and Cognition, 110, 103494. https://doi.org/10.1016/J.CONCOG.2023.103494
   PubMed Web of Science ®Google Scholar
• Tversky, A., & Fox, C. R. (1995). Weighing risk and uncertainty. Psychonological Review, 102(2), 269–283. https://psycnet.apa.org/buy/1995-24035-001
   Web of Science ®Google Scholar
• Vieider, F. M., Lefebvre, M., Bouchouicha, R., Chmura, T., Hakimov, R., Krawczyk, M., & Martinsson, P. (2015). Common components of risk and uncertainty attitudes across contexts and domains: Evidence from 30 countries. Journal of the European Economic Association, 13(3), 421–452. https://doi.org/10.1111/jeea.12102
   Web of Science ®Google Scholar
• Watson, D., Wiese, D., Vaidya, J., & Tellegen, A. (1999). The two general activation systems of affect: Structural evolutionary considerations, and psychobiological evidence. Journal of Personality and Social Psychology, 76(5), 820–838. https://doi.org/10.1037/0022-3514.76.5.820
   Web of Science ®Google Scholar
• Webb, M. E., Little, D. R., & Cropper, S. J. (2016). Insight is not in the problem: Investigating insight in problem solving across task types. Frontiers in Psychology, 7, 1424. https://doi.org/10.3389/fpsyg.2016.01424
   PubMed Web of Science ®Google Scholar
• Webb, M. E., Little, D. R., & Cropper, S. J. (2018). Once more with feeling: Normative data for the aha experience in insight and noninsight problems. Behavior Research Methods, 50(5), 2035–2056. https://doi.org/10.3758/s13428-017-0972-9
   PubMed Web of Science ®Google Scholar
• Weber, E. U., & Hsee, C. K. (1999). Models and mosaics: Investigating cross-cultural differences in risk perception and risk preference. Psychonomic Bulletin & Review, 6, 611–617.
   Google Scholar
• Wu, C. C., Sacchet, M. D., & Knutson, B. (2012). Toward an affective neuroscience account of financial risk taking. Frontiers in Neuroscience, 6, 159. https://doi.org/10.3389/FNINS.2012.00159/PDF
   PubMed Web of Science ®Google Scholar
• Zhao, D., Gu, R., Tang, P., Yang, Q., & Luo, Y. J. (2016). Incidental emotions influence risk preference and outcome evaluation. Psychophysiology, 53(10), 1542–1551. https://doi.org/10.1111/psyp.12694
   PubMed Web of Science ®Google Scholar