Role of affect in decision making

CHAPTER

Role of affect in decision making

3

Debarati Bandyopadhyay, V.S. Chandrasekhar Pammi1, Narayanan Srinivasan Centre of Behavioural and Cognitive Sciences, University of Allahabad, Allahabad, India 1 Corresponding author. Tel.: þ91-91981-58299, Fax: þ91-532-2460738, e-mail address: [email protected]

Abstract Emotion plays a major role in influencing our everyday cognitive and behavioral functions, including decision making. We introduce different ways in which emotions are characterized in terms of the way they influence or elicited by decision making. This chapter discusses different theories that have been proposed to explain the role of emotions in judgment and decision making. We also discuss incidental emotional influences, both long-duration influences like mood and short-duration influences by emotional context present prior to or during decision making. We present and discuss results from a study with emotional pictures presented prior to decision making and how that influences both decision processes and postdecision experience as a function of uncertainty. We conclude with a summary of the work on emotions and decision making in the context of decision-making theories and our work on incidental emotions.

Keywords emotion, affect, incidental emotions, decision making, IAPS, regret, rejoice

1 INTRODUCTION Decision making often occurs in the face of uncertainty about whether one’s choices will lead to benefit or harm. A decision can be regarded as an outcome of the mental processes (cognitive processes) leading to the selection of a course of action among several alternatives. Traditional accounts in economics had a normative flavor which prescribed what the decisions should be, based on optimization of the payoffs. Recently, with the concepts of psychology, descriptive theories of decision making (Kahneman and Tversky, 1979) have evolved that describe the kinds of judgments and decisions people actually make in practice. The cognitive and affective factors Progress in Brain Research, Volume 202, ISSN 0079-6123, http://dx.doi.org/10.1016/B978-0-444-62604-2.00003-4 © 2013 Elsevier B.V. All rights reserved.

37

38

CHAPTER 3 Role of affect in decision making

limit the rational behavior approach taken by normative theories (Miyapuram and Pammi, in press; Pammi and Miyapuram, 2012). The normative theories of decision making attempt to explain how people should behave when they are confronted with risky choices. The behavioral models based on theories like the expected utility theory (EUT) emphasize the rationality of decisions (Bernoulli, 1763/1958). The EUT attaches a subjective value or utility to each of the prospects and people believed to choose choices that maximize their (expected) utility. According to this theory, when a person prefers A prospect over B, then the utility of A should be higher than that of B. Often the criticism of EUT has been motivated by experiments, where it had been noticed that a decision maker’s decisions systematically violated the rationality axioms. Von-Neumann and Morgenstern (1944) proposed the expected utility theorem describing under what conditions (called as “axioms”) preferences can be (numerically) represented using a mathematical function. This allows for a cardinal representation of preferences, that is, allowing quantification of how much an option is preferred over another one. Consistency with the axioms viz., completeness, transitivity, and continuity is the definition of rational behavior. An implicit assumption in expected utility theorem was independent of lotteries. The independence axiom has been challenged by well-known paradoxes (Allais, 1953; Ellsberg, 1961). The descriptive theories with the help of empirical experiments attempt to explain how people make decisions in real-life situations. Examples of such theories include prospect theory and regret theory (Bell, 1982; Kahneman and Tversky, 1979; Loomes and Sugden, 1982). One critical factor that influences decision making is affect. In the area of emotion and decision making, regret theory is one of the successful descriptive models of human choice behavior (Bell, 1982, 1983; Fishburn, 1982; Loomes and Sugden, 1982, 1987) which explains the violations of classical EUT and incorporates emotional components related to decision-making process into the expected utility framework. The central idea behind the theory is that, when making decisions individuals take into account not only the consequences that might be obtained as a result of the action chosen but also how each consequence compares with what they would have experienced under the same state of the world, had they chosen differently. Therefore, the consequence and expected utility of alternative outcome that could have obtained are dependent on one another. However, people maximize utility in a sense that they aspire to avoid regret or disappointment. A decision maker under such influences might opt for what appears to be a suboptimal choice to avoid future regrettable situations. There are two key points within regret theory: first, regret is commonly experienced and, second, people try to anticipate and avoid the experience of future regret. Formally, the function c (regret function, Bell, 1982) represents the comparison between the value (v) of choice (x) and the value of a rejected alternative (y): c[v(x)v(y)]. In regret theory, the function c enters into the utility function (U): U(x;y) ¼ v(x) þ c[v(x)v(y)]. The modified or overall utility of an action (e.g., choice of x and simultaneous rejection of y) can be computed as the sum of the choiceless utility of the chosen act (x) and of the anticipated regret–rejoice

2 Affect in decision making

term c(). Regret theory argues that expected utilities are modified by the anticipated regret or rejoice and hence the anticipated emotions affect decision making. In the following section, we will discuss the role of affect (of different kinds) influence decision making followed by a discussion of theoretical models that explain attempt to explain such influences.

2 AFFECT IN DECISION MAKING Affect influences many cognitive processes (Gazzaniga et al., 2002). Research has demonstrated that positive affect improves the problem-solving skills (Isen and Means, 1983) and enhances memory processes related to the performance of perceptual–motor skills (Isen, 1970; Isen and Levin, 1972; Isen and Simmonds, 1978). Research in the past several decades has demonstrated the influence of emotion on decision making. Moreover, understanding the mechanisms underlying the interaction between emotion and decision making has become an essential part of building descriptively valid theories of decision making in real-world situations. Here, we discuss some of the ways in which emotion interacts with decision-making process based on the nature of emotional processes. Broadly, there are two types of affective influences: those of relevant emotions and those of irrelevant emotions. Relevant emotions are the ones which originate from the decision-making task at hand. It has its source in the consequences of the decision itself and is felt during the time of making decision (also called predicted emotions) or when the consequences are experienced (i.e., after the outcome is given) (see also Loewenstein and Lerner, 2003). These emotions might be reflected through changes in the nature or depth of processing (Tiedens and Linton, 2001) or visceral influences on behavior (Loewenstein, 1996). Examples of these emotions include regret, disappointment, etc. Irrelevant emotions are the ones which come from any source other than the decision-making task at hand. These are called incidental emotions (Loewenstein and Lerner, 2003). The sources for these emotions are usually present in the environmental stimuli (e.g., good smell, beautiful sights and scenes, good music, etc.), or it may also include a person’s mood or temperamental disposition. Emotions are critical for decision making (Bechara et al., 1997; Damasio, 1994; Luce et al., 1997). Recent neuroscientific studies show that individual with major emotional deficits lack the somatic markers and thus might have difficulty making good decisions (Bechara et al., 1997). The somatic marker hypothesis states that emotion-based biasing signals arising from the body are integrated in higher order brain regions, in particular, the ventromedial prefrontal cortex, to regulate decision making in complex situations. It explains how emotions are biologically indispensable to decisions. However, some well-reasoned studies dispute the evidence for somatic markers (Maia and McClelland, 2004). They find that conscious knowledge, rather than nonconscious somatic markers, guide advantageous behavior in the Iowa Gambling task.

39

40

CHAPTER 3 Role of affect in decision making

Emotions also affect the type of decision strategies used to make choices (Luce et al., 1997). Compensatory strategies require making difficult trade-offs and integrating information across all the attributes. Here, a good value on one attribute can compensate for a poor value on another. Noncompensatory strategies, in contrast, are those for which a good value on one attribute cannot make up for a poor value on another. They only require rank ordering alternatives on a single attribute and thus avoid difficult trade-offs between attributes. Luce et al. (1997) found that when faced with emotionally difficult decisions, individuals tend to switch from a compensatory to noncompensatory strategies to avoid making difficult negative emotional trade-offs. In a recent review by Pfister and Bohm (2008), a fourfold classification of emotions with respect to their functions in decision making has been proposed. One function is to provide information about pleasure and pain for preference construction (which is a modification of the previous approaches), a second function is to enable rapid choices under time pressure (supported by the somatic marker hypothesis), a third function is to focus attention on relevant aspects of a decision problem, and a fourth function is to generate commitment concerning morally and socially significant decisions.

3 THEORETICAL FRAMEWORKS Multiple theoretical approaches have been proposed to explain how emotion interacts with decision-making process. One of the first approaches was Schwarz and Clore’s (1983) affect-as-information framework which states that affective states such as positive or negative mood provide information about evaluative judgments, for example, about one’s life satisfaction. This is particularly prominent when the mood state cannot be attributed to an unrelated causal event. In contrast to the affect-as-information framework that focuses mainly on incidental affect, decision affect theory advanced by Mellers et al. (1997) and Mellers (2000) is based on anticipated or predicted emotions, that is, feelings of pleasure or displeasure that originate directly from the choice consequences under consideration. Decision affect theory, a modification of the disappointment and regret theories (Bell, 1982, 1985; Loomes and Sugden, 1982, 1986), assumes that decision makers compute a weighted sum of anticipated emotions which they believe to obtain from possible outcomes of a decision option and then choose the option they believe to yield the greatest amount of potential pleasure. Consider the emotional reaction to an outcome A of a risky choice with two possible outcomes, A and B. Decision affect theory predicts that the feeling associated with outcome a is expressed as Ra ¼ a½ua þ gðua  ub Þðl  sa Þ ¼ b; where a and b are linear coefficients in a judgment function relating an emotional feeling to a response, ua and ub are the utilities of the obtained and unobtained outcomes, respectively, and sa is the subjective probability of outcome a. The g

4 Incidental emotions and decision making

function is called the disappointment function and reflects the comparison between what occurred and what might have occurred under a different state of the world. The function is weighted by (1  sa), the probability that something else would occur. With complete feedback, emotional experiences are described by another form of the theory. In a choice between two gambles, with outcomes a and b (for Gamble 1), and outcomes c and d (for Gamble 2), suppose the decision maker selects Gamble 1, receives outcome a, and then learns that Gamble 2’s outcome was c. The emotional response to a, when Gamble 2’s outcome was c, is RaðcÞ ¼ JR ½ua þ d ðua  ub Þð1  sa Þ þ r ðua  uc Þð1  sa sc Þ: The affect heuristic, proposed by Slovic et al. (2002), is a related approach to describe the importance of affect in guiding judgments and decisions. The affect heuristic—a quick and simplified process of evaluating a risky option by relying on one’s immediate feelings of liking or disliking—refers to affect elicited by the options under consideration, but the affective reaction might as well be caused by unknown influences from unrelated events or memories. The affect heuristic has much in common with the model of “risk as feelings” proposed by Loewenstein et al. (2001). According to the “risk as feeling” approach, to the extent that emotion responses to and cognitive evaluations of risky choice options are dissociated, risk preference is mostly determined by the former. Emotional reactions guide choices not only at their first occurrence, but also through conditioning and memory at a later point in time (e.g., somatic markers). The feeling-is-for-doing approach, proposed by Zeelenberg and Pieters (2006), conceptualizes emotions as motivational processes. This approach goes beyond categorizing emotions in a bivalent way and categorizes them as having multiple dimensions. It highlights that emotions commit decision makers to certain courses of action by bringing forward an associated goal that may overrule other goals. Because different emotions are associated with different goals (Nelissen et al., 2007), it follows that different emotions have their idiosyncratic impact on decision making.

4 INCIDENTAL EMOTIONS AND DECISION MAKING Incidental influences are the influences from immediate emotions that arise from factors unrelated to the decision at hand. Such factors could include individual’s immediate environment or chronic dispositional affect. Influences from incidental emotions are difficult to justify because such emotions, by definition, arise from factors that are incidental to—that is, normatively irrelevant to—the decision. Nevertheless, numerous studies have revealed remarkable effects of incidental emotions on the process related to decision making. It has been argued that people tend to be more optimistic when they are in good moods than when they are in bad moods (Forgas, 2003). Recent studies, however, have begun to reveal more nuanced effects of specific emotions. For example, fearful individuals make relatively pessimistic

41

42

CHAPTER 3 Role of affect in decision making

and risk-averse choices, whereas, angry individuals make relatively optimistic and risk-seeking choices. Moreover, choices of angry individuals more closely resemble those of happy individuals than those of fearful individuals. Also, it has been shown that appraisal patterns of each specific emotion carry over to a new situation and drive such emotion-specific effects (Lerner and Keltner, 2001). Incidental emotions also affect other kinds of decisions, such as valuation of objects and decisions regarding prosocial behavior. For example, sadness from past situations increased buying prices and decreased selling prices of an object. Disgust, on the other hand, decreased both buying and selling prices (Lerner et al., 2004). Incidental happiness induced by finding a dime in a phone booth or receiving free cookies increases people’s willingness to help others (Isen and Levin, 1972). Similarly, incidental gratitude increased people’s willingness to engage in costly helping behavior (Bartlett and DeSteno, 2006). Considering that these effects all held even when real outcomes were at stake, these studies demonstrated reliable and nonnegligible effects of incidental emotions. Fleeting feelings from one’s past can systematically alter decisions in the present. Sadness increases the amount of money that decision makers give up to acquire a commodity (Cryder et al., 2008). Isen et al. (1988) studied the influence of positive affect on individuals’ perceived value (utility) functions. Their results indicated that persons in whom positive affect had been induced showed a more negative subjective utility for losses than did controls. These results suggested that losses seem worse to people who are feeling happy than to those in a control condition. Emotions also change the rate of temporal discounting in choices between long-term large rewards over short-term smaller rewards. Gray (1999) found that participants who were shown aversive images (producing a feeling of being threatened) had higher discount rates. Stress focused individuals’ attention on immediate returns makes them appear more impulsive and makes them to choose a more immediate reward than a long-term reward. None of the major approaches that explain the role of emotion in decision making have clearly given a theoretical model which can predict how incidental affect can influence choice behavior. Moreover, there is also a gap in the literature about the interaction between the different kinds of emotional influences in all the phases of decision process. It is still not clear, how incidental affect influences the experienced utility (the utility for the outcome of a choice) of a decision maker. Decision affect theory is till now the only theoretical framework which has modeled experienced utility (disappointment and regret) of the decision process. Given very little is known in terms of how incidental emotions (emotional context irrelevant to the decision process) affect decision making, we performed a set of experiments to study the influence of incidental emotion on regret and rejoice behavior. The experiments attempted to investigate the role of incidental emotional information on decision making and post-choice decision experience involving regret or rejoice. Incidental emotions can occur during decision making and also during periods before decision making. In one of our studies, we investigated how emotional (happy, neutral, and sad) faces presented during decision-making task influence

4 Incidental emotions and decision making

the processes involved in decision making as well as the postdecision emotional experiences (Bandyopadhyay et al., submitted). The faces were not relevant to the decision-making task. They were manipulated as incidental emotional context. We utilized the modified regret paradigm (Chandrasekhar et al., 2008) that consisted of a gambling task in which the participants were asked to choose among three faces (of same emotion) behind which there were points hidden (þ100 and 100). After they made their choice, they were shown the points for all three faces. Participants’ target was to win as many points as they could by choosing a face. After that, they had to rate their pleasantness feeling on a visual analog scale (VAS) of 15 (very unpleasant) to þ15 (very pleasant). Our dependent measures were decision time and pleasantness rating of post-choice satisfaction. We also manipulated uncertainty by varying probability (high probability and low uncertainty: 2/3 chance of winning and low probability and high uncertainty: 1/3 chance of winning) and indicated this probability in every trial using a cue. In terms of postdecision experience, our results indicate that happy faces decrease regret for losses and increase rejoice for gains when compared to the neutral and sad faces. The results show that happy faces significantly affected emotional experience both after winning and losing. During the decision-making phase when the amount of uncertainty was high, subjects took significantly more time to choose with sad faces compared to neutral faces. However, when uncertainty was low, they were significantly faster in the presence of happy as well as sad faces compared to neutral faces. The results indicate that, even if the emotional information is irrelevant, they affect uncertain choice and the experience evoked by the outcome. The emotional context of a decision-making task, that is, emotional information present in the environment while making a decision, modulates our cognition and postdecision emotions. In addition, the effects of emotions on choice time and postdecision experience were different indicating that the mechanisms underlying these effects are different. The influence of incidental affect on postdecision experience was not sensitive to uncertainty whereas the influence of incidental affect on choice time changed with uncertainty. The study discussed so far used emotional faces and presented them during the decision making trial. The context before a decision making scenario can also influence the processes associated with decision making as well as the postdecision experience. To investigate the effect of incidental emotional context before decision making scenario takes place, we presented emotional pictures (pleasant, neutral, and unpleasant) that were irrelevant to the task as prior context, given that emotional scenes are known to induce affect in participants seeing those scenes. Emotional scenes are considered more realistic and canonical as stimuli for priming emotions compared to emotional faces. Prior studies using emotional scenes have found links between specific emotional content and attentional processes (Olivers and Nieuwenhuis, 2006). They used positive, neutral, and negative pictures in between trials in which participants performed an attentional blink task. In the attentional blink task, participants have to identify two targets separated by variable duration and presented among other

43

44

CHAPTER 3 Role of affect in decision making

stimuli in a rapid serial visual presentation. In general, performance for the second target is worse especially at shorter time intervals between the first and the second targets. They found better second target identification with positive pictures indicating attentional processes are affected by the task-irrelevant emotional content between trials. We used a similar manipulation in this study by presenting emotional pictures before the decision-making task at the beginning of a trial. We hypothesized that irrelevant information would affect both the experience of outcome and decision time. Previous studies using the regret paradigm eliciting different levels of regret or rejoice (Chandrasekhar et al., 2008) found that people experienced more regret when they received a shock under low probability conditions and more rejoice when they avoided a shock under high probability conditions. Emotional experience is stronger when the outcomes are unexpected, called surprise effect (Mellers et al., 1997; Mellers et al., in press). Hence, we predicted that people experience more regret due to losing under low uncertainty (high probability of winning) condition compared to high uncertainty (low probability of winning) condition. Similarly, we predicted that people experience more rejoice due to winning under high uncertainty (low probability of winning) compared to low uncertainty (high probability of winning). In relation to emotional content, we hypothesized that pleasant and unpleasant pictures would affect postdecision regret and rejoice. Pleasant pictures might elicit a positive emotion resulting in increased rejoice or decreased regret and unpleasant pictures might elicit a negative emotion resulting in decreased rejoice and increased regret. Similar to our earlier study with emotional faces, we expected that choice time would depend both on the probability and the emotional content of the scenes.

5 METHOD Data were collected on 26 participants (mean age ¼ 22.19 years). All the participants received payment for their participation in the experiment. In addition, they were instructed that they could also gain more on the basis of their performance. At the beginning of each experimental trial, participants were shown an emotional scene for 500 ms from the International Picture Affective System (IAPS) database. The pictures were pleasant (7.47), unpleasant (2.88), or neutral (5.31). The scenes (total of 36) were selected based on ratings from an Indian population (Lohani et al., submitted for publication) in such a way that the arousal values were equal for the pleasant and unpleasant scenes. The decision task and the dependent measures were the same as in our earlier study with emotional faces described previously. The IAPS scenes were presented as emotional context primes (prior to the choice stimuli) for the decision-making task and post-choice experience and were uninformative (not predictive) of the probability or the consequence of decision making. The decision-making task consisted of a display containing three identical doors with an indicator of how many doors have þ100 points hidden behind (prior probability—high: 2/3rd and low: 1/3rd probability of winning). The participant’s task was to select one of the doors with a mouse

6 Results

500 ms

500 ms

Until response

3000 ms

+100 -100 +100

Until response

Very unpleasant

Very pleasant

Next trial

FIGURE 1 An example experimental trial (the emotion here is neutral in nature).

click. Immediately, the points (win: þ100; lose: 100) hidden behind doors were revealed and then the participants were instructed to their experience of outcome (positive values for pleasantness and negative values for unpleasantness) on a VAS ranging from 15 (very unpleasant) to þ15 (very pleasant). A blank screen with a fixation cross appeared in between the trials and the order of presentation of trials was random (Fig. 1). The total number of trials across the uncertain conditions of all the emotion types was kept same.

6 RESULTS There were two dependent measures in the experiment: decision time and pleasantness rating. Decision time data was log transformed and was analyzed in a 3 (emotion)  2 (probability) repeated measures ANOVA. Similar analyses were done separately for the pleasantness experience in the regret and rejoice conditions (participants indicated regret when they lost and rejoice when they won in a given trial). Emotional Ratings: For the regret rating (result of losing), the main effect of emotion was significant, F(1, 25) ¼ 3.234,p ¼ 0.048. Planned comparison results revealed that the participants experienced significantly more regret in the presence of unpleasant context compared to pleasant context, t(29) ¼ 2.619,p < 0.05. The difference between unpleasant and neutral contexts was close to significance, t(29) ¼ 1.927,

45

CHAPTER 3 Role of affect in decision making

p ¼ 0.064. The main effect of probability was significant, F(1, 25) ¼ 31.814,p  0.000, with less regret experienced in the high uncertainty compared to low uncertainty condition. This is in line with the findings on surprise effects from decision affect theory (Mellers et al., 1997). With rejoice rating, the main effect of emotion was significant, F(1, 25) ¼ 4.526,p ¼ 0.016. Participants significantly experienced more rejoicing in the presence of pleasant context compared to unpleasant scenes, t(29)¼ 2.745,p ¼ 0.01. The difference between pleasant and neutral contexts was close to significance, t(29) ¼ 1.613,p ¼ 0.117. The difference between neutral and unpleasant contexts was significant, t(29) ¼ 2.869,p ¼ 0.008. The main effect of probability was significant, F(1, 25) ¼ 9.411,p ¼ 0.005, with more rejoice experienced in the high uncertainty compared to low uncertainty condition (Figs. 2 and 3). This is again consistent with the surprise effect based on decision affect theory (Mellers et al., 1997). Decision Times: Results from decision time revealed the main effects of emotion and probability were not significant. The interaction effect of emotion and probability was significant, F(1, 25) ¼ 5.698,p ¼ 0.006. Planned comparisons showed that participants took significantly longer time to decide in the pleasant compared to the neutral condition when the uncertainty was high, t(29) ¼ 3.539,p < 0.05. Similar effect was obtained with unpleasant context, t(29) ¼ 2.421,p ¼ 0.023. There was no significant difference between decision times for pleasant and unpleasant contexts under high uncertainty. In the low uncertainty, there was a trend of faster decision times with the pleasant context compared to the unpleasant, t(29) ¼ 1.777,p ¼ 0.088 and neutral, t(29) ¼ 1.681,p ¼ 0.105 contexts. With the pleasant context, participants were significantly faster in the low compared to high uncertainty condition, t(29) ¼ 2.637, p < 0.05 (Fig. 4). Thus, we conclude that under high uncertainty, emotional context (irrespective of valence) makes people slower to choose when compared to neutral context, and under low uncertainty, people chose faster in a pleasant context. This shows that pleasant emotion has a different impact on decision time depending on the probability or uncertainty. Emotion -5.00

Pleasantness rating (VAS)

46

Pleasant

Unpleasant

Neutral

-6.00 -7.00 -8.00 -9.00

*

-10.00

FIGURE 2 Emotion rating in the regret condition as a function of emotional context.

7 Discussion

Pleasantness rating (VAS)

10.00

*

9.00

*

8.00

7.00

6.00

5.00

Pleasant

Unpleasant

Neutral

Emotion

FIGURE 3 Emotion rating in the rejoice condition as a function of emotional context. 2500.00

High uncertainty Low uncertainty

Choice time (ms)

* 2000.00

1500.00

1000.00

Pleasant

Unpleasant

Neutral

Emotion

FIGURE 4 Decision/choice time with respect to emotion for each prior probability of winning.

7 DISCUSSION The results from the study show that people’s post-choice satisfaction is not only affected by the anticipated emotions (Mellers, 2000; Mellers et al., 1997) but also by the emotions which are irrelevant to the decision-making task. However, the effect of incidental emotions on regret and rejoice was different. With respect to regret, only exposure to unpleasant scenes before decision making increased regret. Pleasant scenes did not differ from neutral scenes with respect to the regret ratings. With

47

48

CHAPTER 3 Role of affect in decision making

respect to rejoice, both pleasant and unpleasant scenes affected rejoicing with pleasant scenes increasing rejoice and unpleasant scenes reducing rejoice. In comparison with the study with emotional faces presented during the trial, this experiment also found a significant effect of incidental emotion induced by the IAPS picture on post choice satisfaction. These results are somewhat different from the results we obtained with emotional faces presented during decision making (Bandyopadhyay et al., submitted). The incidental emotion effect during the decision-making phase was primarily driven by the happy face, but the effect with emotional scenes preceding the decisionmaking phase was predominantly driven by unpleasant scenes. Pleasant scenes only showed a trend of increasing rejoice but did not influence regret. The experiments differed in terms of when the incidental emotion information was obtained (prior to choice stimuli or during the presentation of choice stimuli). In addition, they are also differed in terms of the nature of emotional stimuli. The previous experiment employed emotional faces (happy and sad) where as current experiment used pleasant and unpleasant scenes that consisted of multiple emotions (fear, anger, disgust, sadness all being part of the unpleasant scenes). Further studies with similar emotional stimuli presented during as well as prior to decision-making phase would enable us to fully understand the influence of incidental affect on post-choice experience. In terms of decision time, both experiments showed a significant interaction between emotional context and probability. With high uncertainty, both pleasant and unpleasant emotional scenes presented before the stimuli for making choice slowed choice time. With faces presented along with choice stimuli, choice time was slow only with sad faces. Negative emotional stimuli both prior and during decision making possibly attract attention slowing decision-making processes. Given that happy faces are recognized easily even under conditions of less attention, they does not seem to affect choice time (Bandyopadhyay et al., submitted). With low uncertainty, unpleasant emotional scenes prior to presentation of choice stimuli slowed choice times whereas both sad and happy faces during the decision-making phases speeded up choice times. The results indicate that emotional context before and during decision-making processes affect choice time differently and this needs to be taken into account by theories of affect and decision making.

8 CONCLUDING REMARKS Till now most theories of emotion and decision making have focused on how emotions arising from the experience of outcomes of decision influence choice behavior. Regret and disappointment theories (Bell, 1982, 1985; Loomes and Sugden, 1982, 1986, 1987) and decision affect theory (Mellers et al., 1997) specifically deal with anticipated and experienced emotions of decision making. According to regret theory, choice is modeled as the minimizing of a regret function, which is the difference between the outcome yielded by a given choice and the best outcome that could have been achieved in that state of nature (Bell, 1982, 1985; Loomes and Sugden, 1982,

8 Concluding remarks

1986, 1987). The decision affect theory depicts that people make choices based on maximization of their emotional experience rather than utility (Mellers et al., 1997). Emotional responses to an outcome not only depend on its utility but also on the probabilities and unobtained outcome. Another approach by Damasio (1994) argues that anticipatory emotions serve as beneficial heuristic for making decision when time and cognitive resource to make a decision is limited. All these theories do emphasize the importance of emotions in making decisions. A slightly different view of emotions and decision making emerges from twosystem theories of decision making (Kahneman, 2003, 2011). Kahneman (2003, 2011) have classified affective valence and mood as determinants of accessibility in the intuitive system. The intuitive system or the System 1 according to the two-system view (Kahneman and Frederick, 2002) is emotionally charged, fast, and effortless. Another approach that utilizes the two-system approach is by Fo¨rster and colleagues (Fo¨rster and Dannenberg, 2010; Fo¨rster and Denzler, 2012; Fo¨rster and Higgins, 2005). They argue that global processing is related to promotion focus or approach strategies and local processing is related to prevention focus or vigilant strategies. Their study has implications for the effects of emotion on cognitive processes including decision making given that studies have linked happy emotions to global processing and sad emotions to local processing (Srinivasan and Gupta, 2011; Srinivasan and Hanif, 2010). Happy or sad emotions may affect decision making via changes in attention or regulatory focus. Most studies on the effect of incidental emotions on decision making have focused on the effects of mood (Forgas, 1995; Fo¨rster and Higgins, 2005; Schwarz and Clore, 1983). One’s positive or negative mood can influence one’s judgment (Scwarz and Clore, 1988; Forgas, 1995). Zajonc (1980, 2000) has argued that affect is often a dominant force in determining people’s responses to social situations. Forgas (1995) has proposed an affect infusion model to account for the effect of mood on judgment and decision making. A main assertion of the model is that the effects of mood tend to be aggravated in complex situations that demand substantial cognitive processing. In other words, as situations become more complicated and unpredictable, mood becomes more influential in driving evaluations and responses. The AFM also predicts that even in a lesser complex situation, with heuristic processing (similar to affect-as-information; Schwarz and Clore, 1983), the effect of mood will be quite pronounced. Given that positive emotion is related to heuristic, faster and global processing and negative emotion to substantive, slower and local processing (Fo¨rster and Higgins, 2005), their influence on task of judgment will also be different. In addition to mood, incidental emotional information from stimuli present in the environment can and does influence decision making. We have shown with studies on incidental emotions that people’s decision processes are influenced differently by positive and negative emotions even if the emotions were irrelevant to the task at hand. With emotional context present before decision making, decision time was mostly affected by pleasant emotional context with differences dependent on probability of winning. They were also slower in the unpleasant context for both

49

50

CHAPTER 3 Role of affect in decision making

conditions of uncertainty. Participants experienced more regret in the presence of unpleasant context and more rejoice in the context of pleasant emotion. Our results are in line with the prevailing theories of emotions and decision making with pleasant and unpleasant emotions having different kinds of effect of different phases of decision making. In the context of two-system theories, one possibility is that incidental emotions influence decision-making process via System 1. Another possibility is that these differences due to emotions are linked to differences in processing strategies induced by these emotions either before or during decision making. We need further studies to understand the mechanisms underlying the interaction of incidental emotion with integral emotions in decision making. It may be worthwhile to understand how a longer exposure to emotional scenes as primes (in contrast to just as primes) can affect the decision time and post choice satisfaction of people. These concepts can also be extended to study how the theoretical models of emotion and decision making can be modified in the light of findings from studies on incidental emotions.

Acknowledgment We would like to acknowledge grant support (SR/CSI/28/2009) from Department of Science and Technology (DST), Government of India.

References Allais, M., 1953. Le Comportement de l’Homme Rationnel devant le Risque: Criticue des Postulats et Axiomes de l’Ecole Americaine. Econometrica 21, 503–546. Bandyopadhyay, D., Srinivasan, N., Pammi, V.S.C., submitted for publication still under review. Dissociable effects of task irrelevant emotional information on decision making under uncertainty. Bartlett, M.Y., DeSteno, D., 2006. Gratitude and prosocial behavior: helping when it costs you. Psychol. Sci. 17, 319–325. Bechara, A., Damasio, H., Tranel, D., Damasio, A.R., 1997. Deciding advantageously before knowing the advantageous strategy. Science 275, 1293–1295. Bell, D.E., 1982. Regret in decision making under uncertainty. Oper. Res. 30, 961–981. Bell, D.E., 1983. Risk premiums for decision regret. Manage. Sci. 29, 1156–1166. Bell, D.E., 1985. Disappointment in decision making under uncertainty. Oper. Res. 33, 1–27. Bernoulli, D., 1763/1958. Exposition of a new theory on the measurement of risk. Econometrica 22, 23–36. Chandrasekhar, P.V.S., Capra, C.M., Moore, S., Noussair, C., Berns, G.S., 2008. Neurobiological regret and rejoice functions for aversive outcomes. Neuroimage 39, 1472–1484. Cryder, C.E., Lerner, J.S., Gross, J.J., Dahl, R.E., Ronald, E., 2008. Misery is not miserly: sad and self-focused individuals spend more. Psychol. Sci. 19 (6), 525–530.

References

Damasio, A.R., 1994. Descartes’ Error: Emotion, Reason and the Human Brain. Grosset/Putnam, New York. Ellsberg, D., 1961. Risk ambiguity, and the Savage axioms. Q. J. Econ. 75, 643–669. Fishburn, P.C., 1982. Nontransitive measurable utility. J. Math. Psychol. 26, 31–67. Forgas, J.P., 1995. Mood and judgment: the affect infusion model (AIM). Psychol. bull. 117 (1), 39. Forgas, J.P., 2003. Affective influences on attitudes and judgments. In: Davidson, R.J., Scherer, K.R., Goldsmith, H. (Eds.), Handbook of Affective Sciences. Oxford University Press, pp. 596–618. Fo¨rster, J., Dannenberg, L., 2010. GLOMOsys: a systems account of global versus local processing. Psychol. Inq. 21, 175–197. Fo¨rster, J., Denzler, M., 2012. Sense creative! The impact of global and local vision, hearing, touching, tasting, and smelling on creative and analytic thought. Soc. Psychol. Pers. Sci. 3, 108–117. Fo¨rster, J., Higgins, E.T., 2005. How global versus local perception fits regulatory focus. Psychol. Sci. 16, 631–636. Gazzaniga, M.S., Ivry, R.B., Mangun, G.R., Phelps, E.A., 2002. Emotion. In: Gazzaniga, M.S., Ivry, R.B., Mangun, G.R. (Eds.), Cognitive Neuroscience: The Biology of the Mind. W.W. Norton & Company, New York, pp. 537–576. Gray, J.R., 1999. A bias toward short-term thinking in threat-related negative emotional states. Pers. Soc. Psychol. Bull. 25 (1), 65–75. Isen, A.M., 1970. Success, failure, attention and reactions to others: the warm glow of success. J. Pers. Soc. Psychol. 15, 294–301. Isen, A.M., Levin, P.F., 1972. The effect of feeling good on helping: cookies and kindness. J. Pers. Soc. Psychol. 15 (4), 294–301. Isen, A.M., Means, B., 1983. The influence of positive affect on decision-making strategy. Soc. Cogn. 2 (1), 18–31. Isen, A.M., Simmonds, S.F., 1978. The effect of feeling good on a helping task that is incompatible with good mood. Soc. Psychol. 41, 345–349. Isen, A.M., Nygren, T.E., Ashby, F.G., 1988. Influence of positive affect on the subjective utility of gains and losses: it is just not worth the risk. J. Pers. Soc. Psychol. 55 (5), 710–717. Kahneman, D., 2003. A perspective on judgment and choice: mapping bounded rationality. Am. Psychol. 58 (9), 697–720. Kahneman, D., 2011. Thinking, Fast and Slow. Farrar, Straus and Giroux, New York. Kahneman, D., Frederick, S., 2002. Representativeness revisited: attribute substitution in intuitive judgment. In: Gilovich, T., Griffin, D., Kahneman, D. (Eds.), Heuristics and Biases. Cambridge University Press, New York, pp. 49–81. Kahneman, D., Tversky, A., 1979. Prospect theory: an analysis of decision under risk. Econometrica 47, 263–291. Lerner, J.S., Keltner, D., 2001. Fear, anger, and risk. J. Pers. Soc. Psychol. 81, 146–159. Lerner, J.S., Small, D.A., Loewenstein, G., 2004. Heart strings and purse strings: effects of emotions on economic transactions. Psychol. Sci. 15, 337–341. Loewenstein, G., 1996. Out of control: visceral influences on behavior. Organ. Behav. Hum. Decis. Process. 65 (3), 272–292. Loewenstein, G., Lerner, J., 2003. The role of affect in decision making. In: Dawson, R.J., Scherer, K.R., Goldsmith, H.H. (Eds.), Handbook of Affective Science. Oxford University Press, Oxford, pp. 619–642.

51

52

CHAPTER 3 Role of affect in decision making

Loewenstein, G., Weber, E.U., Hsee, C.K., Welch, N., 2001. Risk as feelings. Psychol. Bull. 127 (2), 267–286. Lohani, M., Gupta, R., Srinivasan, N., submitted for publication. Still under review. Crosscultural validation of the international affective picture system on an Indian sample. Loomes, G., Sugden, R., 1982. Regret theory: an alternative theory of rational choice under uncertainty. Econ. J. 92, 805–824. Loomes, G., Sugden, R., 1986. Disappointment and dynamic consistency in choice under uncertainty. Rev. Econ. Stud. 53, 271–282. Loomes, G., Sugden, R., 1987. Some implications of a more general form of regret theory. J. Econ. Theory 41, 270–287. Luce, M.F., Bettman, J.R., Payne, J.W., 1997. Choice processing in emotionally difficult decisions. J. Exp. Psychol. Learn. Mem. Cogn. 23 (2), 384–405. Maia, T.V., McClelland, J.L., 2004. A reexamination of the evidence for the somatic marker hypothesis: what participants really know in the Iowa Gambling Task? Proc. Natl. Acad. Sci. 101 (45), 16075–16080. Mellers, B.A., 2000. Choice and the relative pleasure of consequences. Psychol. Bull. 126 (6), 910–924. Mellers, B.A., Schwartz, A., Ho, K., Ritov, I., 1997. Decision affect theory: emotional reactions to the outcomes of risky options. Psychol. Sci. 8, 423–429. Mellers, B., Fincher, K., Drummond, C., Bigony, M., 2013. Surprise: a belief or an emotion? Prog. Brain Res. 202, 1–20. Miyapuram, K.P., Pammi, V.S.C., 2013. Understanding decision neuroscience—a multidisciplinary perspective and neural substrates. Prog. Brain Res. 202, 239–266. Nelissen, R.M.A., Dijker, A.J., De Vries, N.K., 2007. Emotions and goals: assessing relations between values and emotions. Cogn. Emot. 21, 902–911. Olivers, C.N., Nieuwenhuis, S., 2006. The beneficial effects of additional task load, positive affect, and instruction on the attentional blink. J. Exp. Psychol. Hum. Percept. Perform. 32 (2), 364–379. Pammi, V.S.C., Miyapuram, K.P., 2012. Neuroeconomics of individual decision making at multiple levels: a review. In: Tandon, P.N., Tripathi, R.C., Srinivasan, N. (Eds.), Expanding Horizons of the Mind Science(s). Nova Publications, New York, pp. 159–185. Pfister, H.-R., Bohm, G., 2008. The multiplicity of emotions: a framework of emotional functions in decision making. Judgm. Decis. Mak. 3 (1), 5–17. Schwarz, N., Clore, G.L., 1983. Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. J. Pers. Soc. Psychol. 45 (3), 513. Slovic, P., Finucane, M., Peters, E., MacGregor, D.G., 2002. The affect heuristic. In: Gilovich, T., Griffin, D., Kahneman, D. (Eds.), Heuristics and Biases: The Psychology of Intuitive Judgment. Cambridge University Press, New York, pp. 397–420. Srinivasan, N., Gupta, R., 2011. Global-local processing affects recognition of distractor emotional faces. Q. J. Exp. Psychol. 64, 425–433. Srinivasan, N., Hanif, A., 2010. Global-happy and local-sad: perceptual processing affects emotion identification. Cogn. Emot. 24, 1062–1069. Tiedens, L.Z., Linton, S., 2001. Judgment under emotional certainty and uncertainty: the effects of specific emotions on information processing. J. Pers. Soc. Psychol. 81, 973–988. Von-Neumann, J., Morgenstern, O., 1944. Theory of Games and Economic Behavior. Princeton University Press, Princeton.

References

Zajonc, R.B., 1980. Feeling and thinking: preferences need no inferences. Am. Psychol. 35, 151–175. Zajonc, R.B., 2000. Feeling and thinking: closing the debate over the independence of affect. In: Forgas, J.P. (Ed.), Feeling and Thinking: The Role of Affect in Social Cognition. Cambridge University Press, New York, pp. 31–58. Zeelenberg, M., Pieters, R., 2006. Feeling is for doing: a pragmatic approach to the study of emotions in economic behavior. In: DeCremer, D., Zeelenberg, M., Murnighan, J.K. (Eds.), Social Psychology and Economics. Erlbaum, Mahwah, NJ, pp. 117–137.

53