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Journal articles on the topic 'Risky Framing'

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Author: Grafiati

Published: 14 March 2023

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1

Zhang, Ran, Luming Zhao, Lin Wu, Hongxu Chen, Gaoxing Zhou, Xiaoqing Zhang, Peng Fang, and Xufeng Liu. "The effects of optimism on self-framing and risky decision making." Social Behavior and Personality: an international journal 48, no. 10 (October 7, 2020): 1–9. http://dx.doi.org/10.2224/sbp.9409.

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The framing effect is a key topic that has been insufficiently studied in research on behavioral decision making. In our study we explored the effects of optimism on self-framing and risky decision making. Participants were 416 undergraduates who responded to the Life Orientation Test and a self-framing test based on the Asian disease problem. The results demonstrate that, compared with people low in optimism, highly optimistic individuals tended to use more positive words to describe problems, generate more positive frames, and choose more risky options. There was also a significant self-framing effect: Participants with a negative frame tended to be risk-seeking, whereas those with a positive frame tended to avoid risks. Additionally, selfframing suppressed the effect of optimism on risky decision making. We can conclude that optimism has significant effects on self-framing and risky decision making.

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2

Gosling, Corentin J., and Sylvain Moutier. "Is the framing effect a framing affect?" Quarterly Journal of Experimental Psychology 72, no. 6 (September 10, 2018): 1412–21. http://dx.doi.org/10.1177/1747021818796016.

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Over the past 30 years, researchers have shown that human choices are highly sensitive to the ways in which alternatives are presented. For example, when individuals face a choice between a sure and a risky option, their willingness to take risks varies depending on whether the alternatives are framed in terms of gain or loss. The current major hypothesis that explains such a framing effect predicts that compared with an equivalent risky option, sure gains are emotionally attractive and sure losses are emotionally aversive. Using a behavioural paradigm, the main objective of the current study was to experimentally observe the extent to which the emotional attraction to sure gains and aversion to sure losses are at the core of framing susceptibility. First, our results showed that, as the literature suggests, the emotional attraction to sure gains and aversion to sure losses underpin the framing effect. Second, our results showed that methodological factors moderated the role of these emotional mechanisms in the framing effect. Implications and directions for future studies are discussed.

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3

ZHANG, Wen-Hui. "Self-framing, Risk Perception and Risky Choice." Acta Psychologica Sinica 40, no. 6 (October 28, 2008): 633–41. http://dx.doi.org/10.3724/sp.j.1041.2008.00633.

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4

Wang, X. T. "Self-framing of risky choice." Journal of Behavioral Decision Making 17, no. 1 (December 16, 2003): 1–16. http://dx.doi.org/10.1002/bdm.454.

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5

Steiger, Alexander, and Anton Kühberger. "A Meta-Analytic Re-Appraisal of the Framing Effect." Zeitschrift für Psychologie 226, no. 1 (January 2018): 45–55. http://dx.doi.org/10.1027/2151-2604/a000321.

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Abstract. We reevaluated and reanalyzed the data of Kühberger’s (1998) meta-analysis on framing effects in risky decision making by using p-curve. This method uses the distribution of only significant p-values to correct the effect size, thus taking publication bias into account. We found a corrected overall effect size of d = 0.52, which is considerably higher than the effect reported by Kühberger (d = 0.31). Similarly to the original analysis, most moderators proved to be effective, indicating that there is not the risky-choice framing effect. Rather, the effect size varies with different manipulations of the framing task. Taken together, the p-curve analysis shows that there are reliable risky-choice framing effects, and that there is no evidence of intense p-hacking. Comparing the corrected estimate to the effect size reported in the Many Labs Replication Project (MLRP) on gain-loss framing (d = 0.60) shows that the two estimates are surprisingly similar in size. Finally, we conducted a new meta-analysis of risk framing experiments published in 2016 and again found a similar effect size (d = 0.56). Thus, although there is discussion on the adequate explanation for framing effects, there is no doubt about their existence: risky-choice framing effects are highly reliable and robust. No replicability crisis there.

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6

Rachev, Nikolay R., Hyemin Han, David Lacko, Rebekah Gelpí, Yuki Yamada, and Andreas Lieberoth. "Replicating the Disease framing problem during the 2020 COVID-19 pandemic: A study of stress, worry, trust, and choice under risk." PLOS ONE 16, no. 9 (September 10, 2021): e0257151. http://dx.doi.org/10.1371/journal.pone.0257151.

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In the risky-choice framing effect, different wording of the same options leads to predictably different choices. In a large-scale survey conducted from March to May 2020 and including 88,181 participants from 47 countries, we investigated how stress, concerns, and trust moderated the effect in the Disease problem, a prominent framing problem highly evocative of the COVID-19 pandemic. As predicted by the appraisal-tendency framework, risk aversion and the framing effect in our study were larger than under typical circumstances. Furthermore, perceived stress and concerns over coronavirus were positively associated with the framing effect. Contrary to predictions, however, they were not related to risk aversion. Trust in the government’s efforts to handle the coronavirus was associated with neither risk aversion nor the framing effect. The proportion of risky choices and the framing effect varied substantially across nations. Additional exploratory analyses showed that the framing effect was unrelated to reported compliance with safety measures, suggesting, along with similar findings during the pandemic and beyond, that the effectiveness of framing manipulations in public messages might be limited. Theoretical and practical implications of these findings are discussed, along with directions for further investigations.

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7

Kühberger, Anton. "Risky choice framing by experience: A methodological note." Judgment and Decision Making 16, no. 5 (September 2021): 1314–23. http://dx.doi.org/10.1017/s1930297500008445.

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AbstractIn classic research on judgment and decision making under risk, risk is described by providing participants with the respective outcomes and probabilities in a summary format. Recent research has introduced a different paradigm – decisions-by-experience – where participants learn about risk by sampling from the outcomes, rather than by summary descriptions. This latter research reports a description-experience gap, indicating that some of the classic patterns of risk attitude reverse when people experience the risk. Recent research has attempted to investigate risky choice framing in the decisions-by-experience paradigm. I discuss how this research runs into problems in properly manipulating framing in decisions by experience. Drawing from framing research with animals, I argue that framing effects also exist in experience tasks. The classic Asian Disease task, however, awaits proper translation into an experience paradigm.

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8

Dertwinkel-Kalt, Markus, and Tobias Wenzel. "Focusing and framing of risky alternatives." Journal of Economic Behavior & Organization 159 (March 2019): 289–304. http://dx.doi.org/10.1016/j.jebo.2017.12.020.

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9

Guo, Lisa, Jennifer S. Trueblood, and Adele Diederich. "Thinking Fast Increases Framing Effects in Risky Decision Making." Psychological Science 28, no. 4 (February 1, 2017): 530–43. http://dx.doi.org/10.1177/0956797616689092.

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Every day, people face snap decisions when time is a limiting factor. In addition, the way a problem is presented can influence people’s choices, which creates what are known as framing effects. In this research, we explored how time pressure interacts with framing effects in risky decision making. Specifically, does time pressure strengthen or weaken framing effects? On one hand, research has suggested that framing effects evolve through the deliberation process, growing larger with time. On the other hand, dual-process theory attributes framing effects to an intuitive, emotional system that responds automatically to stimuli. In our experiments, participants made decisions about gambles framed in terms of either gains or losses, and time pressure was manipulated across blocks. Results showed increased framing effects under time pressure in both hypothetical and incentivized choices, which supports the dual-process hypothesis that these effects arise from a fast, intuitive system.

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10

Cheng, Pi-Yueh, and Wen-Bin Chiou. "Framing Effects in Group Investment Decision Making: Role of Group Polarization." Psychological Reports 102, no. 1 (February 2008): 283–92. http://dx.doi.org/10.2466/pr0.102.1.283-292.

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Prospect theory proposes that framing effects result in a preference for risk-averse choices in gain situations and risk-seeking choices in loss situations. However, in group polarization situations, groups show a pronounced tendency to shift toward more extreme positions than those they initially held. Whether framing effects in group decision making are more prominent as a result of the group-polarization effect was examined. Purposive sampling of 120 college students (57 men, 63 women; M age = 20.1 yr., SD = 0.9) allowed assessment of relative preference between cautious and risky choices in individual and group decisions. Findings indicated that both group polarization and framing effects occur in investment decisions. More importantly, group decisions in a gain situation appear to be more cautious, i.e., risk averse, than individual decisions, whereas group decisions in the loss situation appear to be more risky than individual decisions. Thus, group decision making may expand framing effects when it comes to investment choices through group polarization.

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11

Corbin, Jonathan, Todd McElroy, and Cassie Black. "Memory reflected in our decisions: Higher working memory capacity predicts greater bias in risky choice." Judgment and Decision Making 5, no. 2 (April 2010): 110–15. http://dx.doi.org/10.1017/s1930297500000966.

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AbstractThe current study looks at the role working memory plays in risky-choice framing. Eighty-six participants took the Automatic OSPAN, a measurement of working memory; this was followed by a risky-choice framing task. Participants with high working memory capacities demonstrated well pronounced framing effects, while those with low working memory capacities did not. This pattern suggests that, in a typical risky-choice decision task, elaborative encoding of task information by those with high working memory capacity may lead them to a more biased decision compared to those with low working memory.

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12

Wyszynski, Marc, and Adele Diederich. "Keep your budget together! Investigating determinants on risky decision-making about losses." PLOS ONE 17, no. 3 (March 21, 2022): e0265822. http://dx.doi.org/10.1371/journal.pone.0265822.

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The present study investigates the influence of framing, different amounts to lose, and probabilities of a risky and sure choice option, time limits, and need on risky decision-making. For a given block of trials, participants were equipped with a personal budget (number of points). On each trial within a block, a specific initial amount is possibly taken from the budget by the outcome of a gamble or the choice of a sure loss option. The goal was to avoid losing points from the budget for not falling below a predefined need threshold. Three different levels of induced need were included. Employing a psychophysical experimental approach, we furthermore tested a sequential component of human risk behavior towards a need threshold inspired by research on animal foraging behavior. Risk-sensitivity models and the Stone-Geary framework serve as generating hypotheses on need thresholds. We found that framing, need, and probabilities influenced risky choices. Time limits and initial amounts moderated the framing effect. No sequential component was observed.

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13

Zhang, Yin-ling, Li-jun Xiao, Yu Ma, and Dan-min Miao. "EFFECT OF FRAMING ON RISKY CHOICE: ONE CASE STUDY IN CHINA." Social Behavior and Personality: an international journal 36, no. 5 (January 1, 2008): 651–58. http://dx.doi.org/10.2224/sbp.2008.36.5.651.

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The effect of framing on Chinese undergraduates was explored using Tversky and Kahneman's (1981) well-known Asian Disease Problem. Participants were divided into three groups with different formats: positive, negative, and balanced format, respectively. There was a significant difference between the Chinese sample and Tversky and Kahneman's American sample under positive format, but no difference under the negative format. Chinese students were more prone to risky options. Results of the Chinese sample showed that the type of framing effect was unidirectional, characterized by predominant risk seeking under both framing conditions, with more risk seeking under the negative frame than the positive frame. The framing effect was evaluated using the balanced format condition as an objective measure of the existing risk preference. Results suggest that the military participants were influenced by both positive format and negative format, and in the Chinese civil sample the negative format had an important effect. These findings expand the literature on risk decision by demonstrating the framing effect and comparing results from Chinese and American participants.

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14

Marsh, B., and A. Kacelnik. "Framing effects and risky decisions in starlings." Proceedings of the National Academy of Sciences 99, no. 5 (February 26, 2002): 3352–55. http://dx.doi.org/10.1073/pnas.042491999.

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15

Wallin, Annika, Carita Paradis, and Konstantinos V. Katsikopoulos. "Evaluative polarity words in risky choice framing." Journal of Pragmatics 106 (December 2016): 20–38. http://dx.doi.org/10.1016/j.pragma.2016.09.005.

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16

De Jaegher, Kris. "Strategic framing to influence clients’ risky decisions." Theory and Decision 86, no. 3-4 (March 2, 2019): 437–62. http://dx.doi.org/10.1007/s11238-019-09691-x.

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17

Hausman, Bernice L. "Risky Business: Framing Childbirth in Hospital Settings." Journal of Medical Humanities 26, no. 1 (April 2005): 23–38. http://dx.doi.org/10.1007/s10912-005-1050-3.

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18

Druckman, James N., and Rose McDermott. "Emotion and the Framing of Risky Choice." Political Behavior 30, no. 3 (February 8, 2008): 297–321. http://dx.doi.org/10.1007/s11109-008-9056-y.

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19

Best, Ryan, and Alexandra M. Freund. "Age, Loss Minimization, and the Role of Probability for Decision-Making." Gerontology 64, no. 5 (2018): 475–84. http://dx.doi.org/10.1159/000487636.

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Background: Older adults are stereotypically considered to be risk averse compared to younger age groups, although meta-analyses on age and the influence of gain/loss framing on risky choices have not found empirical evidence for age differences in risk-taking. Objective: The current study extends the investigation of age differences in risk preference by including analyses on the effect of the probability of a risky option on choices in gain versus loss situations. Methods: Participants (n = 130 adults aged 19–80 years) chose between a certain option and a risky option of varying probability in gain- and loss-framed gambles with actual monetary outcomes. Results: Only younger adults displayed an overall framing effect. Younger and older adults responded differently to probability fluctuations depending on the framing condition. Older adults were more likely to choose the risky option as the likelihood of avoiding a larger loss increased and as the likelihood of a larger gain decreased. Younger adults responded with the opposite pattern: they were more likely to choose the risky option as the likelihood of a larger gain increased and as the likelihood of avoiding a (slightly) larger loss decreased. Conclusion: Results suggest that older adults are more willing to select a risky option when it increases the likelihood that larger losses be avoided, whereas younger adults are more willing to select a risky option when it allows for slightly larger gains. This finding supports expectations based on theoretical accounts of goal orientation shifting away from securing gains in younger adulthood towards maintenance and avoiding losses in older adulthood. Findings are also discussed in respect to the affective enhancement perspective and socioemotional selectivity theory.

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20

Elfahmi, Ryan, Endang Puji Astutik, and Kemas Vivi Andayani. "PENGARUH CONFIRMATION BIAS DAN RISKY CHOICE FRAMING TERHADAP KEPUTUSAN INVESTASI PETANI." SCIENTIFIC JOURNAL OF REFLECTION : Economic, Accounting, Management and Business 5, no. 4 (October 1, 2022): 1234–46. http://dx.doi.org/10.37481/sjr.v5i4.602.

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This study aims to determine the effect of Confirmation Bias and Risky Choice Framing on farmers' investment decisions. The questions in this study are whether Confirmation Bias affects farmers' investment decisions and whether Risky Choice Framing affects farmers' investment decisions. The analysis technique in this research includes correlation test, determination test and F test which is a model feasibility test, followed by multiple linear regression analysis and hypothesis testing (t). The sample method uses purposive sampling, with several criteria developed previously. Questionnaires were used to collect data from respondents. Respondents in this study were farmers in Blubur Limbangan District, Garut Regency. In total there are 356 respondents. Based on the results of hypothesis testing (t), Confirmation Bias affects farmers' investment decisions and Risky Choice Framing affects farmers' investment decisions.

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21

Slattery, Jeffrey P., and Daniel C. Ganster. "Determinants of Risk Taking in a Dynamic Uncertain Context." Journal of Management 28, no. 1 (February 2002): 89–106. http://dx.doi.org/10.1177/014920630202800106.

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We tested the effects of positive and negative framing on risky decision making in a simulated managerial judgement task. Until now the extensive research on framing effects has been characterized by static contexts, explicit probabilities, and hypothetical gambles. In contrast we simulated a more realistic decision making environment in which individuals chose more or less risky goals in a complex dynamic task that featured uncertain outcomes and meaningful consequences. Decision makers chose a series of performance goals under conditions of either potential losses or gains and also received feedback about their goal attainment. Our results failed to replicateProspect Theory predictions about initial gain vs.loss framing typically found in static decision making contexts. In addition, we tested competing hypotheses derived from Prospect Theory and Quasi-Hedonic Editing (QHE) Theory about the effects of performance outcome feedback on subsequent decisions. Consistent with QHE Theory, decision makers who had failed to reach their goals set lower, less risky goals in subsequent decisions. Our findings illustrate the need for further risk taking research in environments that more closely resemble managerial decision making.

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22

Reyna, Valerie F., and Susan C. Ellis. "Fuzzy-Trace Theory and Framing Effects in Children's Risky Decision Making." Psychological Science 5, no. 5 (September 1994): 275–79. http://dx.doi.org/10.1111/j.1467-9280.1994.tb00625.x.

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Traditional theories of cognitive development predict that children progress from intuitive to computational thinking, whereas fuzzy-trace theory makes the opposite prediction To evaluate these alternatives, framing problems were administered to preschoolers, second graders, and fifth graders Consistent with fuzzy-trace theory, results indicated (a) that younger children focused on quantitative differences between outcomes and did not exhibit framing effects (risk avoidance for gains, risk seeking for losses) and (b) that older children assimilated these quantitative differences and displayed framing effects

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23

Sasaki, Mika, and Hiroki Takikawa. "Investment attitude and framing effects on risky decisions." Proceedings of the Annual Convention of the Japanese Psychological Association 81 (September 20, 2017): 2B—013–2B—013. http://dx.doi.org/10.4992/pacjpa.81.0_2b-013.

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24

Costello, Thomas H., Sarah F. Smith, Shauna M. Bowes, Steven Riley, Gregory S. Berns, and Scott O. Lilienfeld. "Risky business: Psychopathy, framing effects, and financial outcomes." Journal of Research in Personality 78 (February 2019): 125–32. http://dx.doi.org/10.1016/j.jrp.2018.11.006.

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25

Wang, X. T., Fr�d�ric Simons, and Serge Br�dart. "Social cues and verbal framing in risky choice." Journal of Behavioral Decision Making 14, no. 1 (January 2001): 1–15. http://dx.doi.org/10.1002/1099-0771(200101)14:1<1::aid-bdm361>3.0.co;2-n.

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26

Wall, Daniel, Raymond D. Crookes, Eric J. Johnson, and Elke U. Weber. "Risky choice frames shift the structure and emotional valence of internal arguments: A query theory account of the unusual disease problem." Judgment and Decision Making 15, no. 5 (September 2020): 685–703. http://dx.doi.org/10.1017/s1930297500007877.

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AbstractWe examine a Query Theory account of risky choice framing effects — when risky choices are framed as a gain, people are generally risky averse but, when an equivalent choice is framed as a loss, people are risk seeking. Consistent with Query Theory, frames affected the structure of participants’ arguments: gain frame participants listed arguments favoring the certain option earlier and more often than loss frame participants. These argumentative shifts mediated framing effects; manipulating participants initial arguments attenuated them. While emotions, as measured by PANAS, were related to frames but not related to choices, an exploratory text analysis of the affective valence of arguments was related to both. Compared to loss-frame participants, gain-frame participants expressed more positive sentiment towards the certain option than the risky option. This relative-sentiment index predicted choices by itself but not when included with structure of arguments. Further, manipulated initial arguments did not significantly affect participant’s relative sentiment. Prior to changing choices, risky choice frames alter both the structure and emotional valence of participants’ internal arguments.

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27

Hornig, Susanna. "Framing Risk: Audience and Reader Factors." Journalism Quarterly 69, no. 3 (September 1992): 679–90. http://dx.doi.org/10.1177/107769909206900316.

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News stories of recent years often involve science and technology, either directly or indirectly — from the Chernobyl incident in the former Soviet Union to progress in understanding AIDS. This experimental study asks: how do lay readers respond to the risk implicit in such stories? The four factors that emerged from analysis can be described as the proposition that science and technology are expensive and risky (rationalist factor), the idea that science and technology can have negative effects (effects factor), concerns associated with control and dependency (control factor), and fear that science and technology can be misused (utilization factor).

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Gvozdenović, Vasilije, and Kaja Damnjanović. "INFLUENCE OF THE PROBABILTY LEVEL ON THE FRAMING EFFECT IN REFERENCE POINT OF LOSS." Primenjena psihologija 9, no. 1 (April 7, 2016): 83. http://dx.doi.org/10.19090/pp.2016.1.83-100.

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Framing effect, which refers to preference reversal due to different descriptions of the same outcome, is examined through risky choice tasks, in which experimental reference point is typically positioned in win-area (situation of lottery). The aim of the conducted study was to examine a framing effect pattern as a function of the level of risk in risky options when experimental reference point is positioned in loss-area (paying a bill). Results show general loss aversion in monetary domain, which is in an accordance with previous studies. Frame influences decisions in the situations when possibility of total loss (level of risk) is perceived as relatively low. Interpretation of these results leads to the conclusion that the probability and reference point determine framing effect. In win-area, frame influences decisions on the highest levels of probability, and, vice-versa, in loss-area, frame influences decisions on the lowest levels of probability. Results confirm notion that risk-aversion is dependent upon a decision-maker’s perception of spending (an investment or a loss). Although observed risk-seeking decisions in negative frame and different decision patterns in loss and win areas can be explained by the model of cumulative prospect-theory, influence of different experimental reference point can not.

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White, Claire M., Michaela Gummerum, and Yaniv Hanoch. "Framing of online risk: Young adults’ and adolescents’ representations of risky gambles." Decision 5, no. 2 (April 2018): 119–28. http://dx.doi.org/10.1037/dec0000066.

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Cheng, Pi-Yueh, and Wen-Bin Chiou. "Rejection or Selection: Influence of Framing in Investment Decisions." Psychological Reports 106, no. 1 (February 2010): 247–54. http://dx.doi.org/10.2466/pr0.106.1.247-254.

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According to prospect theory, reflection effects result in preferences for risk-averse choices in gain situations and risk-seeking choices in loss situations. However, relevant literature in regard to decision making has suggested that positive information receives more weight in a selection task, whereas negative information receives more weight in a rejection task. The present study examined whether the nature of a decision task (selection vs rejection) would moderate the reflection effects. Undergraduates (47 men, 49 women; M age = 20.5 yr., SD = 1.1), selected according to specific screening criteria, participated in an experimental study. Typical reflection effects were observed in both selection and rejection task conditions. More importantly, negative information (i.e., the information about probable loss in risky choice of gain situations and the information about certain loss in cautious choice of loss situations) provided in the context of a rejection task received more weight and resulted in more frequent endorsements of the cautious choice in gain situations and of the risky choice in loss situations. Hence, the findings suggest that a decision context characterized by rejection may expand the reflection effects and thereby provide important information about situations in which investment decisions occur in a context characterized by rejection.

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Macchi, Laura, and Edoardo Zulato. "Numbers do not add up! The pragmatic approach to the framing of medical treatments." Judgment and Decision Making 16, no. 3 (May 2021): 596–613. http://dx.doi.org/10.1017/s1930297500007750.

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AbstractThe risky choice framing effect disclosed that presenting data in a loss scenario lead decision-makers towards risky choices. Conversely, a gain scenario prevents them from taking a risk. Framing effect robustness has been widely confirmed by psychological literature. However, the framing of medical treatments, based on McNeil et al. (1982) paradigm, raised both methodological doubts and contrasting evidence. Our research aimed to investigate the presence and the nature of the framing effect in the McNeil et al. (1982) paradigm. In particular, we thought that the obtained switch of preferences across frames was due to a misleading formulation of the data given in a negative cumulative frequency format. We conducted three studies: (1) we replicated McNeil et al.’s (1982) original study (N=150) with medicine (n=50), statistics (n=50) and lay (n=50) students; (2) we tested (N=180) our hypothesis by comparing a cumulative frequency format with an alternative version, namely a linear progression one; (3) we compared (N=430) the effect of different formats (cumulative frequency, linear progression and interval frequency) on choices. Our results showed that, while the framing effect is present when employing a cumulative frequency format, it disappears when using a linear progression one. Moreover, our results show that decision-makers better understand information when given in a linear progression and an interval frequency format. In the current paper, we argue that the way in which a problem is formulated plays a relevant role in the representation of the decisional task and the decision-making.

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Diederich, Adele, Marc Wyszynski, and Ilana Ritov. "Moderators of framing effects in variations of the Asian Disease problem: Time constraint, need, and disease type." Judgment and Decision Making 13, no. 6 (November 2018): 529–46. http://dx.doi.org/10.1017/s1930297500006574.

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AbstractThis study examined framing effects in decisions concerning public health. Tversky and Kahneman’s famous Asian Disease Problem served as experimental paradigm. Subjects chose between a sure and a risky option either presented as gains (saving lives) or as losses (dying). The amount of risk varied in terms of different probabilities. The number of affected people was either small (low need) or large (high need). Additionally, the decisions were linked to three different types of diseases (unusual infection, AIDS, leukemia). We also implemented two different time constraints during which the subjects had to give a response. Finally, we tested a within-subject design. The data analysis assuming a linear mixed effects model revealed significant effects of framing, probabilities, and need. Furthermore, the type of disease and time constraints were moderating the framing effect. Across the different diseases, framing effects were amplified when decision time was short.

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Chien, Yu-Chin, Cindy Lin, and Joanna Worthley. "Effect of Framing on Adolescents' Decision Making." Perceptual and Motor Skills 83, no. 3 (December 1996): 811–19. http://dx.doi.org/10.2466/pms.1996.83.3.811.

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92 young adolescents were tested using Tversky and Kahneman's (1981) decision problems for framing effects. A notable number of young adolescents tested were not influenced by the context of the decision problems, thus they selected the same response option for positively and negatively framed problems. Parallel information was not available in Tversky and Kahneman's study for adults because they used a between-subjects design. However, for present adolescents who selected different response options for different framing problems, the response pattern exhibited by them resembled the general pattern exhibited by the adults tested in Tversky and Kahneman's study—negative frames led them to accept risk to avoid certain loss; positive frames prevented them from risking what they were certain to gain. Boys and girls were similar in their susceptibility to framing effects as were honors students in mathematics as compared to nonhonors students. Although the positive vs negative framing only influenced some of the young adolescents tested in this study, because the influence was consistent, researchers and educators interested in adolescents' decisions involving risky choices might use framing principles to design and assess cognitive interventions for high-risk behaviors among young adolescents.

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34

Zhou, Lei, Nan Liu, Ya-Qiong Liao, and Ai-Mei Li. "Risky choice framing with various problem descriptions: A replication and extension study." Judgment and Decision Making 16, no. 2 (March 2021): 394–421. http://dx.doi.org/10.1017/s1930297500008615.

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AbstractIn “Risky choice framing: Task versions and a comparison of prospect theory and fuzzy-trace theory”, Kühberger and Tanner (2010) examined the impacts of removing stated zero/non-zero complements of risky options on the gain/loss framing effect. They also tested two rival theoretical explanations for this effect: prospect theory and fuzzy-trace theory. The present study aimed to examine the reliability and robustness of the evidence provided by Kühberger and Tanner by precise replication in Study 1. The original findings were reported for conditions in which the probability of the risky option was fixed, and the expected value of the two alternatives was approximately equivalent. The present study also aimed to examine the generality of their findings under additional conditions in which large, medium and small probabilities of the risky option were assigned, and the expected value of the certain or risky options differed. The main findings of Kühberger and Tanner (2010) were successfully replicated and confirmed under the original and additional conditions. The implications of these findings are discussed.

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Gonzalez, Cleotilde, and Katja Mehlhorn. "Framing From Experience: Cognitive Processes and Predictions of Risky Choice." Cognitive Science 40, no. 5 (August 27, 2015): 1163–91. http://dx.doi.org/10.1111/cogs.12268.

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Herranz-Zarzoso, Noemí, Gerardo Sabater-Grande, and Ainhoa Jaramillo-Gutiérrez. "Framing and repetition effects on risky choices: A behavioural approach." Journal of Behavioral and Experimental Economics 84 (February 2020): 101504. http://dx.doi.org/10.1016/j.socec.2019.101504.

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Mahoney, Kevin T., Walter Buboltz, Irwin P. Levin, Dennis Doverspike, and Daniel J. Svyantek. "Individual differences in a within-subjects risky-choice framing study." Personality and Individual Differences 51, no. 3 (August 2011): 248–57. http://dx.doi.org/10.1016/j.paid.2010.03.035.

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Kühberger, Anton. "The Influence of Framing on Risky Decisions: A Meta-analysis." Organizational Behavior and Human Decision Processes 75, no. 1 (July 1998): 23–55. http://dx.doi.org/10.1006/obhd.1998.2781.

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Garelik, Steven, and X. T. Xiao-Tian Wang. "Multiple Framing: Verbal, Facial, and Vocal Cues in Risky Choice." Journal of Behavioral Decision Making 30, no. 2 (February 9, 2016): 322–31. http://dx.doi.org/10.1002/bdm.1942.

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Okder, Hidetaka. "The illusion of the framing effect in risky decision making." Journal of Behavioral Decision Making 25, no. 1 (October 7, 2010): 63–73. http://dx.doi.org/10.1002/bdm.715.

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Schulte-Mecklenbeck, Michael, and Anton Kühberger. "Out of sight – out of mind? Information acquisition patterns in risky choice framing." Polish Psychological Bulletin 45, no. 1 (March 1, 2014): 21–28. http://dx.doi.org/10.2478/ppb-2014-0004.

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Abstract We investigate whether risky choice framing, i.e., the preference of a sure over an equivalent risky option when choosing among gains, and the reverse when choosing among losses, depends on redundancy and density of information available in a task. Redundancy, the saliency of missing information, and density, the description of options in one or multiple chunks, was manipulated in a matrix setup presented in MouselabWeb. On the choice level we found a framing effect only in setups with non-redundant information. On the process level outcomes attracted more acquisitions than probabilities, irrespective of redundancy. A dissociation between acquisition behavior and choice calls for a critical discussion of the limits of process-tracing measures for understanding and predicting choices in decision making tasks

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SCHILIRO, Daniele. "Economics and Psychology. The Framing of Decisions." Journal of Mathematical Economics and Finance 2, no. 2 (April 2, 2017): 77. http://dx.doi.org/10.14505//jmef.v2.2(3).05.

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In the Theory of Rational Decision Making the psychological aspects are set aside. This contribution seeks to point out the relevance of psychology into eco- nomic decisions. The essay treats the “framing of decisions”, which is a pillar of Kahneman’s behavioral theory. Framing must be considered a special case of the more general phenomenon of dependency from the representation. The best-known risky choice-framing problem, i.e. the “Asian Disease Problem”, is shown where an essen- tial aspect of rationality: invariance, is violated. In addition, the contribution ex- plains Kahneman and Tversky’s Prospect Theory and illustrates their value function. Finally, it discusses the reversals of preference in framing and framing of contingen- cies. The framing manipulation is viewed as a public tool for influencing the decision maker’s private framing of the problem in terms of gains or losses, which determines the decision maker’s evaluation of the options. In conclusion, the psychology of choice is relevant both for the descriptive question of how decisions are made and for the nor- mative question of how decisions ought to be made.

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Diwakar, Pranathi. "A Recipe for Disaster: Framing Risk and Vulnerability in Slum Relocation Policies in Chennai, India." City & Community 18, no. 4 (December 2019): 1314–37. http://dx.doi.org/10.1111/cico.12457.

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This article investigates how governments use dramatic natural events such as disasters to justify potentially unpopular policy interventions. I use the case of the southern Indian city of Chennai to explore how different arms of the government have historically engaged with the question of slum tenure from the 1960s until the present moment. Using archival methods, I analyze policy documents to excavate how slums have been framed within the context of political and policy imperatives. I show that slums are framed as risky to themselves and the broader urban public, and are portrayed as dangerous, messy, or illegal. I analyze the role of the disaster moment in catalyzing slum relocation policies, and I argue that this moment allowed the government a new modality to frame slums as not just risky but also at risk, or vulnerable to disasters in their original locations. I make the case that the anti–poor policy of slum relocation has been justified as pro–poor by framing slums as not just risky, but also at risk. The framing of slums as at risk in Chennai has been necessary within the extant political matrix, which has historically courted slums for electoral success. The analysis of shifting slum policies offers new insight into how urban policy and politics of disaster vulnerability frame and interact with the urban poor in cities of the Global South.

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Lahtinen, Sonja, and Elina Närvänen. "Co-creating sustainable corporate brands: a consumer framing approach." Corporate Communications: An International Journal 25, no. 3 (June 3, 2020): 447–61. http://dx.doi.org/10.1108/ccij-11-2019-0121.

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PurposeThe purpose of this research is to explore how consumers co-create sustainable corporate brands (SCBs) by framing brands with a newly adopted sustainability orientation.Design/methodology/approachThe qualitative data were generated from four focus groups consisting of altogether 25 Finnish millennial consumers. The data were analysed using thematic analysis, and the resulting themes were classified as different framings.FindingsThe findings indicate three ways of framing SCBs: as signs of corporate hypocrite, as threats that increase societal fragmentation and as signs of corporate enlightenment. These framings are based on two components: the perceived attributes and activities of the corporate brand.Practical implicationsThe role of corporate brands is expanding from the business sphere towards actively influencing society. Yet, sustainability activities can be risky if consumers, as primary stakeholders, deem them unacceptable, unethical or untrustworthy. This research supports brand managers to succeed in co-creating SCBs as contributors to societal and environmental well-being, at a time when multiple stakeholders consider this a worthwhile endeavour.Originality/valueThe theoretical contribution is twofold: firstly, the paper extends the sustainable corporate branding literature by demonstrating how SCBs are co-created through an interactive framing process between the corporation and primary stakeholders, and, secondly, it contributes to the constitutive approach to corporate social responsibility communication (CSRC) research by showing how millennial consumers frame corporate brands that communicate corporations' newly adopted sustainability orientation.

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Widayanti, Ipuk. "Framing Information and its Impact on Saving Decision in Conventional and Sharia Banks: Experimental Study of Students of the Faculty of Islamic Economics and Business in Yogyakarta." Global Review of Islamic Economics and Business 3, no. 1 (December 31, 2016): 018. http://dx.doi.org/10.14421/grieb.2015.031-02.

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Islamic and Conventional Banks in delivering information of margin in saving product have different ways. Islamic bank uses “nisbah” while conventional bank uses interest. Both have different words and disclosure but in the nominal calculation of nisbah and interest is same, because Islamic bank uses Profit Equilization Reserve which the function is as allowance, and to simply it, Islamic banking informs that to consumer as Equivalent Rate. By using Attribute Framing and Risky Choice Framing this research aims to test the information frame of nisbah and interest and it influences on saving decision making. Quasi Experiment Model is used with 49 students of Islamic Economic Studies as subject of experimental group and 20 students of other studies except Islamic Economic as subject of control group. Experimental design of this research is between subject 2X2 by using 2 cases and Random Assignment technique. Two Way ANOVA is used as analitical tool. The result of this research is when information of margin is framed in gain domain/positive frame and loss domain/positive frame subject decision in saving is less risky while when information of margin is framed in gain domain/negative frame and loss domain/negative frame subject decision in saving is risk seeking. The largest framing effect is on the certain/probability (gain domain/positive frame) and the smallest effect is on uncertain/presentation (loss domain/negative frame).

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Keane, Nick, and Maren Eline Kleiven. "Risky Intelligence." International Journal of Police Science & Management 11, no. 3 (September 2009): 324–33. http://dx.doi.org/10.1350/ijps.2009.11.3.134.

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The article concerns the use by police services of the abstract idea of intelligence-led policing, often embodied as it is in the United Kingdom in the National Intelligence Model. We will argue that while this is a central framing idea in policing, it contains omissions which lead to faulty decision-making. The article charts the rise of intelligence-led policing in the United Kingdom and argues that circumstances have led to the concept of intelligence becoming equated to ‘information which leads to a detection’; however, that this construction leads to the exclusion of intelligence which then impacts upon the business of the police service. One outcome of this is that the members of the community that the police service is charged with protecting and serving pay the price of this decision-making. The central argument of our article is that an overconcentration on the detection of offences has skewed the way the map has been drawn up and how it is currently being used. Our main contention is not that the concept of intelligence-led policing should be abandoned, but that it should be revisited and revised to take greater notice of the changes in the landscape it is designed to cover. The territory is changing but the map is not being amended; it is time for some major revisions.

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Gonzalez, Cleotilde, Jason Dana, Hideya Koshino, and Marcel Just. "The framing effect and risky decisions: Examining cognitive functions with fMRI." Journal of Economic Psychology 26, no. 1 (February 2005): 1–20. http://dx.doi.org/10.1016/j.joep.2004.08.004.

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van Buiten, Marc, and Gideon Keren. "Speaker–listener incompatibility: Joint and separate processing in risky choice framing." Organizational Behavior and Human Decision Processes 108, no. 1 (January 2009): 106–15. http://dx.doi.org/10.1016/j.obhdp.2008.03.002.

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Shin, Kiwon, and Taeyun Jung. "Effects of goal framing and conformity pressure on risky behavior intention." Journal of Multi-Cultural Contents Studies 29 (December 31, 2018): 91–117. http://dx.doi.org/10.15400/mccs.2018.12.29.91.

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Pense, Christine M., and Stephen H. Cutcliffe. "Risky Talk: Framing the Analysis of the Social Implications of Nanotechnology." Bulletin of Science, Technology & Society 27, no. 5 (October 2007): 349–66. http://dx.doi.org/10.1177/0270467607306592.

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