Unfairness, Anger, and Spite: Emotional Rejections of Ultimatum Offers

ORGANIZATIONAL BEHAVIOR AND HUMAN DECISION PROCESSES

Vol. 68, No. 3, December, pp. 208–224, 1996 ARTICLE NO. 0100

Unfairness, Anger, and Spite: Emotional Rejections of Ultimatum Offers MADAN M. PILLUTLA Hong Kong University of Science and Technology AND

J. KEITH MURNIGHAN Northwestern University

This paper addresses an anomaly in experimental economics, the rejection of ultimatum offers, and uses a psychological explanation for this essentially economic event. The wounded pride/spite model predicts that informed, knowledgeable respondents may react to small ultimatum offers by perceiving them as unfair, feeling anger, and acting spitefully. Results of a large scale experiment support the model, showing that rejections were most frequent when respondents could evaluate the fairness of their offers and attribute responsibility to offerers. In addition, anger was a better explanation of the rejections than perceptions that the offers were unfair. The discussion addresses the rarely studied but frequently observed emotions that negotiations provoke. q 1996 Academic Press

Negotiations have often been described as mixed-motive interactions: Bargainers cooperate to increase the size of their potential joint outcome and to reach an agreement; they compete to boost their own individual outcomes (Rubin & Brown, 1975; Walton & McKersie, 1966). The competitive elements that surface in the endgame in negotiations often encourage one party to make a “take it or leave it” offer to the other. Agreement and the individual and joint benefits that agreement An earlier version of this paper was presented at the Academy of Management meetings in Dallas and the Economic Science Association meetings in Tucson, both in 1994. We appreciate the extremely helpful comments that Max Bazerman, Dan Brass, Charalambos Iacovou, Greg Oldham, Archana Vepa, and two anonymous reviewers provided on an earlier version of this paper, as well as Jim Schmidtke’s professional assistance with the data and the financial support of the Social Sciences and Humanities Research Council of Canada. Address correspondence and reprint requests to J. Keith Murnighan, Northwestern University, KGSM/OB/Leverone/360, 2001 N. Sheridan Road, Evanston, IL 60208. 0749-5978/96 $18.00 Copyright q 1996 by Academic Press All rights of reproduction in any form reserved.

provide may depend, then, on the acceptance of an ultimatum. The dynamics of ultimatum bargaining have recently been the subject of considerable attention in experimental economics (Kagel & Roth, 1995). One of the most consistent findings has been that, counter to theoretical predictions, positive ultimatum offers are sometimes rejected, leaving both parties with lower economic outcomes than they would have achieved if they had agreed. Economists have typically used explanations focusing on violations of fairness norms or fairness perceptions to explain these results. This paper reports an experiment that tests both a fairness and an emotional explanation for why ultimatum offers are rejected. In particular, we test a new model, Straub and Murnighan’s (1995) wounded pride/spite model, that presents a psychological explanation for these essentially economic events. The model suggests that fully informed respondents who perceive ultimatum offers as unfair may also feel anger and, if they do, they are likely to act spitefully and reject an economically valuable offer. From a broad perspective, our research documents how emotions can reduce the frequency of mutually beneficial, negotiated agreements. We focus on anger rather than other relevant emotions for two reasons. First, anger is a primary motive (Fischer, 1991) that may be the most disruptive of the emotions that influence negotiations, often being associated with negotiation failures. Second, Straub and Murnighan (1995), following Binmore, Shaked, and Sutton (1985), suggested that anger might be the underlying cause of the frequent, unpredicted rejections in experiments on ultimatums. They hypothesized that ultimatum respondents not only evaluate whether an offer is fair, but they may also take small offers personally, experiencing anger and wounded pride, which can

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lead them to reject ultimatum offers. The model proposes that perceptions of unfair treatment and feelings of wounded pride and anger provide the basis for spiteful rejections and inefficient disagreements. Wounded pride refers to a personal, inwardly focused feeling when another’s actions violate a person’s sense of self worth. When people are not given the dignity that they feel they deserve, they may question their image of themselves and/or feel hurt. This is wounded pride. Anger and spite are outwardly focused: Anger is an other-directed feeling that follows the perception of an unexpected, unavoidably negative outcome that someone else is responsible for (Ortony, Clore, & Collins, 1990). Spite is the behavioral reaction that accompanies anger and which is designed to hurt the offending other. Wounded pride may never be revealed; anger accompanies spiteful acts that punish someone for expressing disrespect. In spiteful actors’ thinking, their reaction is just retribution (Hogan & Emler, 1982); people believe that revenge has its own moral imperative (Bies & Tripp, 1996). The Straub–Murnighan model suggests, then, that the sequence for rejecting an offer is perceiving that the offer is unfair, feeling wounded pride and anger toward the offerer, and rejection of the offer in spite. By investigating the wounded pride/spite hypothesis, this study tests whether a psychological model can explain a consistent failure of economic theory, i.e., that positively valued ultimatum offers will be accepted. This study follows Siegel and Fouraker (1960); Roth, Malouf, and Murnighan (1981); and most recently Blount (1995) in using social psychological concepts to explain the effects of structural, economic variables, including payoffs, options, and various types of information on bargaining. It also explores the emotional bases for Bolton’s (1991) fairness model, which suggests that people are concerned with relative as well as absolute monetary payoffs. EMOTIONS

Although popular advice typically warns negotiators against becoming emotional (e.g., Connely, 1993) and anecdotes suggest that emotions can sidetrack otherwise efficient negotiations (e.g., Murnighan, 1991), literature on the effects of emotions in negotiations is remarkably sparse (Neale & Bazerman, 1991). Early research by Faucheux and Moscovisi (1968) suggested that evaluation pressures lead to high anxiety and increased competitiveness; Tedeschi, Burrill, and Gahagan (1969) also found that high anxiety increased competitiveness. Carnevale and Isen (1986) found that

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small manipulations of positive affect led to more efficient agreements. Most recently, Thompson, Valley, and Kramer (1995) showed how information about an opponent’s post-negotiation positive (negative) emotions led to negotiators’ feeling less (more) successful. Although emotions have not been directly studied in the context of ultimatums, at least two studies document emotional responses in distributive negotiations. Leventhal and Bergman’s (1969) study of severe inequity had two people perform two simple tasks in each other’s presence. After finishing, the experimenter told them that they had performed equally well and asked one of them to divide a joint payoff. After the division, the other person could redistribute up to 5 cents. Actual subjects divided $1.20 after the first task, almost always equally. Confederates divided $1.40 after the second task so that they received $1 or $1.35. They made this division matter-of-factly or, half of the time, they said “I’m dividing the money this way because I’m so much better than you. Here’s 5 cents (or 40 cents) if you really want to take it.” Although most people simply took the extra nickel, 30% of the participants who received 5 cents gave the nickel back. Leventhal and Bergman (1969) created perceptions of unfairness by suggesting that both people in the dyad performed equally well. Arguably, the small offer should be equally unfair whether accompanied by an insult or not. Thus, the different behavior in the two conditions suggests that the antecedents of equity restoring behavior are more than a simple calculation of unfairness; we suggest that the underlying reason is anger. More recently, Kravitz and Gunto (1992) presented respondents with small ultimatum offers, sometimes with a threatening statement that was similar to the insulting statement in Leventhal and Bergman (1969): “I know you’d like more, but that’s the way it goes. Take it or leave it!” Not surprisingly, this statement led to an increase in rejections. Neither of these studies, however, reported any measures of respondents’ anger. The current investigation was designed to test whether a less blatant, structural manipulation was still sufficient to generate anger and rejections. The role of emotions in potentially conflictual interactions is clearer in the procedural and interactional justice literature. Bies (1987) suggested that injustices, which violate social norms and cause personal harm, necessarily involve more than cognitive judgments; he focused on moral outrage as the motivational and emotional outcome of perceptions of injustice. In contrast, Folger (1993) focused on resentment, a feeling of persistent ill will toward a wrong, an insult, or an injury. Research results have consistently shown that anger and resentment are strongest when poor outcomes are inadequately explained (e.g., Brockner & Wiesenfeld,

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in press; Folger, Rosenfield, & Robinson, 1983). Shapiro (1991) has also shown that people are more punitive, a behavioral reaction like spite, when they have been selfishly deceived by a potential partner. Emotions also play a central role in Tripp, Sondak, and Bies’s (1995) model of the role of fairness in negotiations. They suggest that self-interest includes emotional satisfaction that people want to maximize, in addition to material rewards. Thus, people may reject small, unfair offers rather than experiencing the emotional distress associated with accepting them. Tripp et al. also argue that, while it has been established that people care about fairness in negotiations, it is important to determine how fairness matters. Garrett and Libby (1973) have shown that the ability to attribute intentionality to the distributor of inequitably small outcomes increases unfairness perceptions. Lamm (1986) also suggests that the intensity of negative emotions triggered by injustice depends, among other things, on attributions of causality: The more an injustice can be attributed to another person, particularly someone who had control and can be seen as intentional, the more likely are negative emotions, especially anger. The current study establishes exactly these conditions, suggesting that emotional reactions will be frequent. Tripp et al. (1995) suggest that people look for more than material rewards in their negotiations. They also value symbolic rewards (e.g., status) and emotional satisfaction. Thus, formal models which are only based on the maximization of material rewards will not be adequate. Only a thorough investigation of the instrumental, affective, and symbolic aspects of exchange and exchange relationships will provide answers about how fairness concerns affect behavior. While there has been progress in identifying the effects of concern for symbolic rewards (e.g., Lind & Tyler, 1988), not much has been done to investigate the systematic effects of emotions. The current study focuses more directly on anger than previous bargaining or justice research and investigates how spontaneous rather than strategic anger can interfere with achieving mutually beneficial outcomes. If people who receive small ultimatum offers view them as unexpected and unavoidable and a negative situation that someone else is responsible for, then the setting perfectly describes the contextual antecedents of anger (e.g., Smith & Ellsworth, 1985; Frijda, Kuipers, & Ter Schure, 1989). This allows us to test whether a psychological model can explain a consistent failure of economic theory, i.e., that people will accept positively valued monetary ultimatums.

ULTIMATUMS

Given the ubiquity of conflict, and the frequent use of negotiations to resolve disputes, ultimatums are common organizational and social events (even if ultimatums are not always recognized as ultimatums, e.g., most retail prices). Empirical research in ultimatum bargaining began with Guth, Schmittberger, and Schwarze (1982). Their simple experimental procedure has been duplicated in most subsequent studies. One of a pair of people is randomly chosen to be the offerer. He or she controls an amount of money (e.g., $10) and must offer some portion (say, $3) to the respondent, who can either accept or reject the offer. Both players know the amount being divided and the negotiation rules. An acceptance means the respondent receives the offered amount ($3) and the offerer receives the rest ($7). A rejection means that both people receive nothing. The interaction can also be modified to include outside options (e.g., Kahn & Murnighan, 1993), where respondents who reject an offer receive a fixed payoff, designated in advance as their outside option. Game theory’s models of subgame perfect equilibria (Selten, 1965) use techniques of backward induction to analyze what would happen if two rational actors played an ultimatum game. Since the game ends with the respondents’ accept or reject decision, the analysis starts from there and works backwards to the beginning. Because something is better than nothing, respondents should accept almost any offer. In turn, offerers should make extremely small offers—and these should be accepted. This prediction reflects the fact that the offerer has tremendous control: Once an offer has been made, it cannot be changed, and the respondent can only accept or reject it. Most previous research has not given respondents an outside option; they received nothing if they rejected an offer. (Offerers also received nothing.) Like Kahn and Murnighan (1993), this study provided respondents with outside options, insuring that they would receive some gain, even if they rejected an ultimatum offer. Subgame perfect equilibrium models then predict that offerers who know the value of respondents’ outside options should boost their offers to just exceed the option, making acceptance of their offer slightly more rewarding than rejection. Experiments on ultimatum games without outside options have consistently and repeatedly violated these predictions: Offers are not small, with averages exceeding 40% of the amount being divided, and 15 to 20% of all offers are rejected (Ochs & Roth, 1989). Recent research probing the reasons for these findings have shown that offerers rarely act out of true concerns for fairness (e.g., Harrison & McCabe, 1992; Pillutla &

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Murnighan, 1995; Prasnikar & Roth, 1992; Straub & Murnighan, 1995). Instead, they seem to be consistently strategic, making large offers to avoid rejections and to appear fair rather than to be truly fair. Fairness concerns, however, continue to be used as explanations for respondents’ ultimatum offer rejections. THE WOUNDED PRIDE/SPITE MODEL

Straub and Murnighan (1995) found no evidence for two early explanations for ultimatum rejections, that low offers may have negative utility and that people may require some minimum payoff (Ochs and Roth, 1989): various measures of utilities had no significant relation to ultimatum responses and most respondents said that they would accept offers as small as a penny when they did not know how much was being divided; they clearly did not have a set minimum. Respondents seemed, however, to reject offers not only because they thought that the offers were unfair but also because the offers made them angry. The wounded pride hypothesis, which we have expanded here into the wounded pride/ spite model, suggests that perceptions that an offer is unfair can also lead to anger and wounded pride and, ultimately, to a greater likelihood that an offer will be rejected. Perceptions of unfairness are a necessary foundation for the possibility of a dual emotional reaction—anger and wounded pride—which then increases the chances of spiteful rejections. The model conceptualizes people’s reactions to ultimatum offers as theorists have traditionally conceptualized attitude formation, in the sense that they consist of cognitive, emotional, and behavioral elements. (See Eagly & Chaiken, 1993, for a contemporary discussion of attitude models.) Although the model assumes that perceptions of unfairness necessarily precede anger, wounded pride and anger may not always follow perceptions of unfairness. People may be fatalistic, thinking that unfairness simply happens in life and that it provides no basis for anger or personal reactions; other variables may also mitigate the connection between unfairness and emotion (e.g., external attributions, Lewicki & Bunker, 1996; social accounts, Bies, 1987). The model also does not assume that all angry respondents will act with spite: like early attitude models, behaviors may not necessarily follow cognitions and emotions (Fishbein, 1967). Respondents may perceive an outcome to be unfair; they may get angry and hurt; but if the outcome is large enough, they may find it difficult to reject (cf., Dawes, 1980). Economics may outweigh emotion’s effects on behavior. At the same time, the presence of strong emotions should boost the likelihood of spiteful action. In an early test of the model, Pillutla and Murnighan

(1995) predicted that small offers that were accompanied by claims that these small offers were fair (especially when respondents could see that the offers were unfair) would be rejected more than offers that were not accompanied by such claims. In fact, they found that offerers’ claims had no effect on rejection rates: respondents did not seem to take exception to obviously inaccurate claims of fairness. Because the manipulation was fairly weak and the study included no measures of respondents’ emotions, the current study was designed to test the model more directly and completely. THE CURRENT STUDY

We designed this study to generate feelings of unfairness, emotions, and increased rejections so that we could adequately test the wounded pride/spite model. All participants received a set of anonymous ultimatum offers. If they had complete information, they knew that offerers were dividing $20, a relatively large amount given that the offers were either $1 or $2. Complete information allowed respondents to make fairness evaluations; partial information, where they did not know how much was being divided, did not. (Complete information is analogous, on a much smaller scale, to labor negotiators knowing management’s profits before they begin collective bargaining.) Respondents also had outside options of $0, $1, or $2, payoffs that they would receive if they rejected their offer. These options meant that respondents would receive a payoff that was equal to or greater than (by $1 or $2) the payoff offerers would receive (zero) following a rejection. Another condition, common knowledge, let respondents know that offerers knew their outside options before they had made their offer; respondents without common knowledge knew that offerers did not know about their outside options. Although respondents had no real information or knowledge about how offerers actually formulated their offers, they could use the value of the offer they received to speculate about its creation (Croson, 1993). In Bies and Tripp (1996), many victims of an injustice gave the perpetrators the benefit of the doubt and searched for plausible external explanations or attributions for their harm. Thus, in the current study, when people knew that the other person had no knowledge of their outside options, they might not attribute intentionality to them. In contrast, knowing that offerers knew their outside options prior to making their offers allowed respondents to think that offerers were simply reducing their offers to increase their own outcomes. Respondents receiving small offers could attribute greedy intentions to knowledgeable offerers much more easily than they could to offerers who

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did not know their outside options. This analysis is similar to the logic of Kahneman, Knetsch, and Thaler’s (1986) respondents, who felt that using personal information to take economic advantage of someone was extremely unfair (e.g., a landlord who knew that a tenant would find it hard to move and therefore increased the rent excessively). Each of the independent variables in the current study has strong roots in experimental economics (Kagel & Roth, 1995), which does not accommodate attributional characterizations. A simple economic analysis suggests that people will accept $1 rather than nothing and prefer $2 to $1; similarly, respondents should not accept offers that are less than the value of their outside option. The third variable, information, was first investigated by Siegel and Fouraker (1960; Fouraker & Siegel, 1963) in a classic series of experiments showing that increasing information about a counterpart’s profits increased the efficiency and the equality of negotiated agreements. More recently, the study of asymmetric information in game theory has grown dramatically (Milgrom & Roberts, 1987; Kennan & Wilson, 1993), formalizing the notion that information is powerful and can contribute to high outcomes. Straub and Murnighan (1995) also investigated complete and partial information ultimatums: They found that offerers made and respondents accepted smaller offers in partial information compared to complete information conditions. Pillutla and Murnighan (1995) and Croson (1993) reported similar results. Finally, Roth and Murnighan (1982; 1983) manipulated the presence of common knowledge in a followup to Siegel and Fouraker (1960), showing that information that is not common knowledge encourages ineffective bluffing. Information (or its absence) is common knowledge if what each person knows is known by all and if, in addition, everyone knows that everyone knows, and everyone knows that everyone knows that everyone knows, and so on. When knowledge is not common, who knows what is not commonly known: bargainers may not know what their counterparts know. In ultimatum bargaining, offerers who know respondents’ options might alter their strategies: if they are game theoretic players, they should offer just more than respondents’ options. For respondents who are interested only in financial outcomes, knowing how much offerers knew should be unimportant: acceptances or rejections should be based only on the size of their offers. Thus, classical economic models of game theoretic strategies predict that common knowledge will have no effect. This set of economic/structural variables provides an opportunity to test a series of economic hypotheses and psychological hypotheses based on models of fairness

and justice or on a model of emotions, the wounded pride/spite model. Emotions are rarely included in rational, economic models (see Frank, 1988, for an exception). The wounded pride/spite model suggests that, in this context, the important effects of economic variables are cognitive and emotional, and these psychological reactions are the strongest determinants of the ultimate outcomes in ultimatum bargaining. HYPOTHESES

Classical economic models tend to focus on monetary, measurable outcomes, making their hypotheses in this context straightforward: Rational models suggest that responses to ultimatum offers will only be affected by the size of offers and outside options. (Traditional game theoretic models do not include any predictions for information or knowledge in this context.) If respondents are simple profit maximizers, they should reject any offer that is less than their outside option and accept any offer that is greater than their outside option. When offers equal outside options, they have no basis for choice, suggesting that they will accept half of these offers. (Non-economic models of altruism might posit that more than half will be accepted.) For this study, then, the rational model generates four hypotheses: Hypothesis 1a. People will accept more $2 than $1 offers. Hypothesis 1b. People will accept offers that exceed their outside option. Hypothesis 1c. People will reject offers that are less than their outside option. Hypothesis 1d. People will accept half of their offers when offers equal outside options.

The notion that people will accept more money rather than less seems obvious. However, Straub and Murnighan (1995) and Murnighan and Saxon (in press) found that, using the same format that they used for ultimatum offers, people rejected offers (up to $5) that had no strings attached, that is, no other person was involved and the instructions emphasized that they were simply being offered money. In essence, people indicated that small amounts of money were not worth much to them and weren’t worth bothering with (cf., Harrison, 1989), suggesting that the universality of accepting more rather than less money may not be so obvious and that investigations of the basic tests of self interest, as we conduct in this experiment, can be revealing. Equity theory (Adams, 1963) and other justice models (Bies, 1987; Folger, 1987) suggest that people make comparisons with referent others to determine whether they

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are being treated fairly. Bolton’s (1991) recent economic model also posits that people’s utility functions include concerns for relative gains. Both models suggest that if accepting an offer results in respondents’ outcomes being low relative to offerers’, respondents are likely to perceive that their offer is unfair; equity theory also suggests that people might strive to restore equity or justice to the situation. For this study, then, fairness models suggest that responses to ultimatums will only be affected by the size of their offers and their outside options and information about the amount being divided. Fairness and justice models focus on the imbalance between outcomes and expectations; they present clear predictions about people’s cognitive and behavioral reactions to injustice. (We pursue possible emotional reactions shortly.) They predict: Hypothesis 2a. Complete information about the amount being divided will increase the likelihood that respondents will perceive small offers as unfair. Hypothesis 2b. Complete information about the amount being divided will increase the likelihood that respondents will reject small offers.

Although previous research has not typically measured whether offers were perceived as fair (since experimental economics research rarely utilizes post-experimental questionnaires), studies have repeatedly found that complete information increases rejections (Croson, 1993; Kagel, Moser, & Chan, 1994; Straub & Murnighan, 1995). The wounded pride/spite model suggests that these rejections depend not only on unfairness perceptions but also on emotional reactions. The current study allows for a test that separates these two effects, that is, to determine whether unfairness perceptions are sufficient to cause rejections or whether emotions are also necessary. Prior research (Folger et al., 1983) supports both the idea and the method, by showing that justifications reduce self reported anger but do not affect self reported unfairness. The current study also includes respondents’ behavioral reactions, and relates them to their fairness judgments, their emotional reactions, or both. The wounded pride/spite model makes the same predictions about complete information that the fairness models do, that it will lead to unfairness perceptions and rejections. Anger may also surface and may result in rejections. But the wounded pride/spite model makes only a qualified prediction—anger may result in rejections—and makes no prediction about the independent addition of common knowledge to partial information, when respondents do not know how much is being divided. Only when common knowledge is added to complete information does it predict an effect on both perceptions of fairness and feelings of anger and wounded

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pride: The emotional model suggests that ultimatums responses will be affected by the size of offers, outside options, information, and knowledge that the offerer knew the value of respondents’ outside options. As noted, the model suggests that complete information will increase unfairness perceptions and rejections and that it may also lead to increased anger. Rather than restating Hypotheses 2a and 2b, we only add hypotheses about emotions, the first being: Hypothesis 3a. Complete information about the amount being divided may increase the likelihood that respondents will react to small offers with wounded pride and anger.

Knowing that offerers did not know their outside options allowed respondents to forgive offerers for making small offers: They could not be blamed for intentionally offering no more than respondents’ outside option since they did not know its value. Respondents with no information about the amount being divided also could not blame them, even if they knew that offerers knew their outside options. Intentionality attributions are only possible when offerers knew the value of the respondent’s outside option and respondents had complete information: respondents then know that offerers offered them only as much as their outside option and they are likely to attribute this to offerers’ unfair intentions (Kelley, 1967). The ability to make such attributions should increase respondents’ emotional reactions (Lamm, 1986), in this case, anger, wounded pride, and rejections: Hypothesis 3b. Having complete information and knowing that offerers knew their outside options prior to formulating their offers (common knowledge) will lead respondents to reject more offers than they reject in all of the other conditions.

Folger et al.’s (1983) results support this prediction: Justifications (which may activate the same attributions as not common knowledge in this study) did not change the perception of small outcomes as unfair but did reduce angry emotions. Supporting Hypothesis 3b would support the fairness/justice models and would extend their effects to post-decision behaviors. More importantly, this is a critical prediction of the wounded pride/spite model: an increase in rejections in this condition reflects true spite. The converse of this logic also implies that even small offers may be accepted if they do not generate anger. The wounded pride/spite model suggests, paradoxically, that additional information can make respondents worse off: knowing more about how much is being divided and what offerers knew can lead to more disagreements and stronger negative emotions than knowing less. In their study of “the curse of knowledge,” Camerer, Loewenstein, and Weber (1989) have shown how ignoring private information is both difficult and

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an antecedent of unnecessary economic losses. Support of Hypothesis 3b would extend their findings by demonstrating how additional information leads respondents to change from economically efficient to economically inefficient strategies. If the economic hypotheses are supported, information and knowledge should have their strongest effects when offers are identical to respondents’ outside options because respondents’ economic concerns then become immaterial, that is, acceptance or rejection gives them the same outcome. Respondents can then exercise fate control (Thibaut & Kelley, 1959) over offerers, determining whether they receive a positive or a zero outcome. The wounded pride/spite model suggests that a particular set of circumstances—knowing the amount being divided and how much the offerer knew prior to making the offer—will be pivotal in these attributionally influenced decisions. METHOD

Sample Participants were 118 undergraduate students in introductory management classes at the University of British Columbia. None had any previous background with the task. The study was run as a classroom exercise with a long explanation/lecture following the task. Design and Procedure Table 1 displays the complete factorial design. Information (partial and complete), offer size ($1 and $2), and outside options ($0, $1 and $2) were experienced by all participants; they were within-subject factors. Participants were either in the common or in the not common knowledge condition, a between-subject factor. Partial information respondents were not told how

much had been divided; in complete information they were told that offerers were dividing $20 (except for control offers). In common knowledge, they were told that offerers knew their outside options before formulating offers; in not common knowledge, respondents were told that offerers did not know about their outside options before making offers. We included two control offers for each respondent to provide a baseline for how they would react to small, 50–50 offers when they knew how much was being divided. Straub and Murnighan (1995) defined 50–50 offers in this context as “perfectly fair” as they satisfy most, if not all criteria for fairness (Allison & Messick, 1992). The control condition reduced the amount being divided to $2 for offers of $1 and $4 for offers of $2. Both were complete information offers with the values of respondents’ outside options being equal to the size of their offers. Control offers were presented in both common and not common knowledge conditions. Rejections suggest that respondents are using some basis other than fairness to make their accept/reject decisions since these offers could not be considered unfair (even though they were small). We expected that most would be accepted. Although offers ostensibly came from anonymous others, each providing one, all offers were actually predetermined. Respondents received fourteen offers, of $1 and $2 when their outside options were $0, $1, and $2, with and without knowing how much was being divided, plus two control condition offers. Partial information offers preceded complete information offers which preceded control offers; offers were randomly ordered within each of the information conditions and between the two control condition offers. Respondents received either common knowledge or not common knowledge offers; they never received both.

TABLE 1 The Experimental Design Partial information

Complete information Knowledge

Amount divided

Outside options

The offer

NotCommon

Common

NotCommon

Common

$20

$0

$1 $2 $1 $2 $1 $2 $1 $2

A A A A A A — —

A8 A8 A8 A8 A8 A8 — —

B B B B B B C C

B8 B8 B8 B8 B8 B8 C8 C8

$1 $2 $2 $4

$1 $2

Note. Conditions marked by a dash were not part of the overall design. Respondents received A offers (randomly ordered) followed by B offers followed by C offers or A8 offers followed by B8 offers followed by C8 offers.

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Following each offer, respondents were asked two open-ended questions, “How did you react when you received your offer?”and “How do you feel?” We made a judgment call and decided not to use more intrusive methods, e.g., asking respondents to rate the fairness of (or their anger toward) each offer. While questions like these would have provided more fine-grained data, we were concerned that they might unduly influence subsequent choices since research suggests that normative rules affect how emotions are expressed (Fischer, 1991; Lazarus, 1975). The downside of our method is that our open-ended questions may have led to underreporting of respondents’ anger and unfairness reactions, even though studies suggest that people often express anger when they feel it (Fischer, 1991). The experiment also did not include a measure of wounded pride, for much the same reasons: We feared that questions about an individual’s pride would be so invasive that they would prompt their own unique reactions. Thus, the presence of wounded pride in this study, and in other distributions of small outcomes, remains an unsupported inference and a part of the model that warrants future investigation. Two independent raters coded responses for perceptions of unfairness and anger on 7- and 6-point scales, respectively. They were given no special training and were told to use everyday definitions of anger and fairness to evaluate people’s responses. The fairness scale ranged from 21 for reports of fairness to 0 (no mention), to 1 (slight unfairness) to 5 (increasingly strong expressions of unfairness). The anger scale ranged from 0 (no mention) to 1 (slight anger) to 5 (more and more anger). Examples of participants’ statements and the unfairness ratings they received include: “Bad: $2 is better that $1, but I feel that they were unfair to me”(5)1; “Unfair and Unhappy” (4); “The offer is still not fair but $2 is higher than 0” (3); “Not very equally divided” (2); and “His offer was too small” (1). Examples of participants’ statements and their anger ratings include: “I’m angry that they take me for a fool: They are greedy and deserve nothing” (5); “S/he is being too greedy: he/ she should share the wealth” (4); “Feel like punishing: divider should get nothing if I get nothing” (3); “Better than nothing though the other person is being cheap” (2); and “I’d rather he not get any money. At least I still get $1” (1). Interrater reliabilities were high for both measures: r 5 .91 for unfairness ratings and r 5 .83 for anger ratings; we combined the two raters’ ratings prior to the analyses. Respondents could accept all, none, or some of the 1

All of the statements rated as 5 for unfairness also received ratings for anger. There were no statements that combined a 5 rating for unfairness and a 0 rating for anger.

offers. They were told that a lottery would randomly select one of their responses to determine their actual payoffs. The instructions emphasized that they should react to each offer as if it were the only offer they would receive since their reactions to offers not selected to determine their payoffs would not influence their payoffs. If they had rejected the selected offer, they would receive their outside option and the offerer would receive nothing. If they had accepted the selected offer, they would be paid the amount offered and we would return to the offerer and pay him/her the remainder. (Since there were no offerers, this statement was included only to make the story consistent.) At the end of the experiment, the lotteries were conducted, payoffs were determined, each respondents was paid in cash, and everyone was thoroughly debriefed. RESULTS

We first present an overview of the acceptances and rejections and highlight some of the changes in rejection frequencies that relate to the hypotheses. Then we present a series of analyses to identify when and where these changes were statistically significant. We present the results on anger and unfairness reactions in the same way. Table 2 displays the frequencies and percentages of offers rejected. The marginal totals for the columns in the table indicate that, overall, partial information rejections just exceeded 25% and were not affected by the presence or absence of common knowledge. With the addition of complete information, rejections increased markedly. With the addition of both complete information and common knowledge, rejections increased again to almost 50% of the offers. This is in direct contrast to the control condition offers, where adding common knowledge to complete information reduced the percentage of rejections, from 26.1 to 12.0%. The fact that rejections were considerably more frequent in the comparable experimental conditions (where offers equaled outside options) suggests that the rejections in the experimental conditions were due in large part to fairness concerns. It also indicates that our attempts to boost rejections succeeded. The rows’ marginal totals, shown in Column 5, are also telling. Row 5 shows that several offers of $1 were accepted when respondents’ outside options were $2. These choices were clearly not economic; they may have been altruistic, since acceptance meant that the offerers obtained $19 (or an uncertain amount in the partial information conditions) rather than $0. The rejections in rows 1, 2, and 4 were also not in respondents’ economic interests since these offers exceeded the respondents’ outside options. Combined, they yielded 116 rejections (16.4%), including 10.7% in

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TABLE 2 Frequencies and Percentages of Offer Rejections (Acceptances Are in Parentheses) Partial information

Complete information

Knowledge Amount divided

Outside options

The offer

$20

$0

$1

row 1

$2

row 2

$1

row 3

$2

row 4

$1

row 5

$2

row 6

$1

$2

$2

$1

$1

row 7

$4

$2

$2

row 8

Totals in experimental conditions (excluding rows 5, 7, and 8)

NotComm Column 1

Common Column 2

NotComm Column 3

Common Column 4

Totals Column 5

7(64) 9.9% 4(67) 5.6% 37(34) 52.1% 10(61) 14.1% 66(5) 93.0% 34(37) 47.9%

5(42) 10.6% 0(47) 0% 26(21) 55.3% 4(43) 8.5% 44(3) 93.6% 25(22) 53.2%

92(263) 25.9%

60(175) 25.1%

12(59) 16.9% 8(63) 11.2% 50(21) 70.4% 19(52) 26.8% 66(5) 93.0% 47(24) 66.2% 18(53) 25.4% 19(52) 26.8% 136(219) 38.4%

18(29) 38.3% 11(36) 23.4% 34(13) 72.3% 18(29) 38.3% 43(4) 91.5% 34(13) 72.3% 6(40) 13.1% 5(41) 10.9% 115(120) 48.9%

42(194) 17.8% 23(213) 9.7% 147(89) 62.3% 51(185) 21.6% 219(17) 92.8% 140(96) 59.3% 24(93) 20.5% 24(93) 20.5% 403(777) 34.2%

partial information and 30.0% in the complete information conditions. These frequencies are directly comparable to those reported in Ochs and Roth’s (1989) review. The first two columns of rows 3 and 6 indicate that respondents rejected 51.7% of the offers that equaled their outside options in the partial information conditions, just more than the 50% predicted by Hypothesis 1d. Rejections were considerably more frequent, however, in the complete information conditions. In almost every condition, participants rejected more complete than partial information offers and more common than not common knowledge offers, especially with complete information. The most frequent rejections, other than those that were economically disadvantageous (row 5), were those where offers equaled outside options: When respondents had complete information and common knowledge, they rejected a remarkable 72.3% of these offers. Also noteworthy are the rejections of offers that were larger than respondents’ outside options; these were most frequent (numbering exactly one in three) when respondents had both complete information and common knowledge. None of these rejections are predicted by the rational model. Hypothesis Tests A logistic regression analysis comparing the frequencies of the common and not common knowledge rejections in the control conditions led to a significant effect (b 5 2.48, SE 5 .187, p , .02): Having common knowledge led to fewer rejections than not having common

knowledge. Unlike the other conditions, participants who had more information about what offerers knew in the control condition were more likely to accept their offers, all of which equalized their outcomes. Table 3 reports the results of a logistic regression analysis that included the control condition data and comparable experimental data (complete information TABLE 3 Logistic Regression Models of the Acceptance of Offers in Complete Information Conditions When Offers 5 Outside Options Independent variables 1. Payoff difference between offerers and respondents 2. Outside option

Models 1 1.09** (.107)

x2 df

1.10** (.108) 0.07 (.214) 20.13 (.109)

3. Knowledge 4. Outside option 3 payoff differences 5. Knowledge 3 payoff differences 6. Constant

2

0.26* (.202) 121.9 1

0.18 (.339) 122.88 3

Note. Numbers in parentheses are standard errors. *p , .05; **p , .01.

3 1.28** (.348) 0.06 (.217) 20.19 (.119) 20.06 (.217) 20.29** (.119) 0.24 (.348) 129.12 5

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responses when offers equaled respondents’ outside options). Since respondents could calculate offerers’ outcomes here, we included payoff differences in the analysis, dummy coding control data as 0 (indicating that offerers and respondents received equal payoffs following an acceptance) and experimental data as 1 [indicating that offerers received more ($18 vs $2 or $19 vs $1) following an acceptance]. Model 1, which included only the difference in payoffs, was significant. Model 2 added outside options and knowledge: the only significant effect was payoff differences. The model did not fit the data better than Model 1 [x(2)2 5 1.59, ns]. Model 3 added the difference by outside option and the knowledge by difference interactions; the knowledge by difference interaction was significant.2 This model provided a marginally significant improvement over Model 1 (X(4)2 5 7.83; p , .10). Parsimony suggests that Model 1 provides the best fit for the data and suggests that the difference in offerers’ and respondents’ payoffs is a critical determinant of acceptances. In essence, people accepted offers that gave both offerer and respondent the same amount (the control condition) more than offers that favored the offerer over the respondent (the experimental data). This violates classical economic predictions but is consistent with Bolton’s (1991) argument for the importance of relative payoffs. Also, by rejecting offers that gave offerers more, respondents in the experimental conditions achieved greater outcomes (their outside option) than offerers (who received zero). We analyzed the experimental conditions’ acceptances and rejections using maximum likelihood logistic regression procedures, testing three models suggested by our hypotheses (see Table 4). The main effects model, Model 1, led to significant effects for offer size, outside options, knowledge, and information. The beta weights were positive for offer size and negative for outside options, indicating that acceptances increased with offer size but decreased with increasing outside options, supporting Hypothesis 1a (respondents accepted $2 offers more than $1 offers). The data also show that people accepted more partial than complete information offers, supporting Hypothesis 2b. Model 2 included the interaction between offer size and outside options and improved on Model 1 [X2(1) 5 12.35, p , .01]. All the main effects and the interaction were significant. An inspection of the rejections (see Table 2) reveals that some people rejected offers that were larger than their outside options; some accepted 2 This unexplainable interaction was not significant when the 13 respondents who indicated some confusion with the task were dropped from this analysis. They were included in all of the other analyses; removing them led to no other noticeable differences.

TABLE 4 Logistic Regression Models of the Acceptance of Offers in the Different Experimental Conditions Independent variables 1. Offer size 2. Outside option 3. Information 4. Knowledge 5. Offer size 3 outside option 6. Information 3 knowledge 7. Constant x2 df

Models 1 1.72*** (.147) 21.78*** (.099) 0.44*** (.069) 0.14** (.069)

20.44** (.213) 601.58 4

2 0.96*** (.252) 22.81*** (.325) 0.45*** (.069) 0.14** (.069) 0.69*** (.197)

0.61 (.371) 613.93 5

3 0.97*** (.253) 22.82*** (.325) 0.48*** (.071) 0.13* (.069) 0.69*** (.198) 20.14** (.069) 0.60 (.372) 617.90 6

***p , .01; **p , .05; *p , .10.

offers that were less than their outside options. Clearly, Hypotheses 1b and 1c were not completely supported. But the fact that Model 2 was a reasonable fit to the data suggests that, overall, the economic model’s predictions received general support. Model 3 tested Hypothesis 3b by adding the knowledge by information interaction. All of the effects were significant. Further analysis revealed that the knowledge effect was significant in the complete information condition (b 5 0.173; p , .05) but not in the partial information condition (b 5 2.005; ns), suggesting that the likelihood of rejections depended on both complete information and common knowledge. This is strong support for Hypothesis 3b and its underlying rationale. Anger and Unfairness Perceptions Anger and unfairness ratings were significantly correlated (r 5 0.55, p , .01), but 35.1% of those reporting perceptions of unfairness did not report anger, allowing us to separate the effects of unfairness from those of anger. Most participants who reported anger also reported perceptions of unfairness (see Table 5), particularly when information was complete. Thus, when we discuss the separate effects of anger and unfairness, we are actually contrasting the effects of unfairness alone with the effects of unfairness accompanied by anger. Few respondents were angry or felt that their offers were unfair when they had no information about the amount being divided and knew that offerers did not know their outside options (the partial information-not

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TABLE 5 The Percentage of Respondents Reporting Anger and Unfairnessa Partial Information Not common Outside Option Offer Outcome Unfair $0

$1 $2

$1

$1 $2

$2

$1 $2

Totals

Reject Accept Reject Accept Reject Accept Reject Accept Reject Accept Reject Accept Reject Accept Overall

0.0 1.7 50.0 0.0 0.0 0.0 0.0 3.5 1.6 0.0 13.3 0.0 4.3 1.2 2.3

Complete Information Common

Not common

Common

Unfair/ Angry

n

Unfair

Unfair/ Angry

n

Unfair

Unfair/ Angry

n

Unfair

Unfair/ Angry

n

20.0 6.9 50.0 3.2 15.6 3.1 0.0 0.0 4.8 0.0 6.7 0.0 8.6 2.8 4.9

(5) (58) (2) (62) (32) (32) (8) (57) (62) (4) (30) (35) (139) (248) (387)

40.0 15.4 0.0 6.4 16.7 0.0 20.0 4.7 11.9 0.0 21.7 13.6 17.3 8.1 11.6

20.0 7.7 0.0 4.3 16.7 5.0 0.0 2.3 14.3 0.0 13.0 4.5 13.5 4.6 7.9

(5) (39) (0) (47) (24) (20) (10) (43) (42) (2) (23) (22) (104) (173) (277)

33.3 15.1 0.0 9.1 14.6 0.0 7.1 4.7 5.2 50.0 14.6 0.0 11.3 8.4 9.7

44.4 16.9 60.0 12.7 36.6 5.6 42.9 6.9 34.5 0.0 41.5 10.0 38.7 11.5 24.2

(9) (53) (5) (55) (41) (18) (14) (43) (58) (2) (41) (20) (168) (191) (359)

16.7 8.3 0.0 15.6 9.7 0.0 6.3 3.8 12.2 33.3 12.5 0.0 10.7 8.5 9.8

77.7 20.8 81.8 18.8 54.8 25.0 75.0 23.1 41.5 0.0 68.8 15.4 61.1 19.8 43.9

(18) (24) (11) (32) (31) (8) (16) (26) (41) (3) (32) (13) (149) (106) (255)

a

Few people reported anger alone (without unfairness); for presentation purposes, we combined the anger only with the Unfair/Angry ratings. Because these were responses to open-ended questions, some data are missing.

common knowledge conditions; see Table 5). This is not unexpected: Having no information about how much money is being divided and no information about what offerers knew makes payoff comparisons impossible and attributions uncertain. Any judgments of fairness or feelings of anger in these conditions are uninformed and arbitrary. The last row of Table 5 shows that unfairness perceptions alone increased with the addition of common knowledge and/or complete information. In contrast, the frequency of angry reactions increased when common knowledge was added to partial information, they increased even more with complete information, and they increased the most when respondents had both complete information and common knowledge. This pattern is almost identical to the pattern of rejections. Although anger and unfairness accompanied rejections more than acceptances, 22.9% of the complete information acceptances were also accompanied by unfairness and/or anger. Clearly, some people who accepted offers still felt they were unfair and were angry about them. [For complete information acceptances, 25 of 297 (8.4%) felt they were unfair; 43 of 297 (14.5%) reported both unfairness and anger.] While people accepted complete information offers that exceeded their outside options more than offers that equaled their options (61.6 versus 28.9%), doing $1 or $2 better than their outside options led them to report more unfairness

perceptions and/or anger (25.3 versus 11.9%) than informed acceptors whose offers equaled their outside options: Paradoxically, these small economic advantages led to more acceptances but also more anger and unfairness perceptions. The data also present a striking portrayal of the emotions associated with rejections. Common knowledge led to more angry rejections than not common knowledge in each of the complete information conditions, as predicted. More notably, in both common and not common knowledge conditions, respondents who rejected offers that exceeded their outside options expressed anger most often (77.7% of the time in common knowledge and 46.4% in not common), more than they did when offers equaled their outside options (61.9% in common knowledge; 39.0% in not common), and least often when the offers were less than their outside options (41.5% in common knowledge; 34.5% in not common). In other words, when respondents had complete information and common knowledge and received offers that exceeded their outside options, they accepted more offers but also reported more anger when they rejected offers. When people could reject offers with no loss to themselves, they reported less anger than they did when they rejected offers that were economically valuable. A multivariate analysis of variance on the anger and unfairness ratings revealed many significant effects

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ANGRY ULTIMATUM REJECTIONS

TABLE 6

TABLE 7

Anova Summary Table for Reported Feelings of Anger and Unfairness

Logit Analysis of Four Models of the Effects of Feeling Anger and/or Perceiving Unfairness on Acceptance Probabilities

Source Knowledge Outside option Offer size Information Outside options 3 offer size Knowledge 3 information Knowledge 3 outside options 3 information Knowledge 3 offer size 3 information Outside options 3 offer size 3 information

df 1,84 2,168 1,84 1,84 2,168

Unfairness F 5 12.34*** 5.42** 4.53** 50.85*** 6.00**

Anger F 5 11.94*** 5.34** 5.78** 49.17*** .63

1,84

0.96

10.31**

2,168

1.02

2.45*

2,168

5.34**

3.03*

2,168

1.55

3.39**

***p , .001; **p , .05; *p , .1.

(see Table 6). Knowledge or information increased feelings of anger and perceptions of unfairness, supporting Hypotheses 2a and 3a, which predicted increases in unfairness perceptions and anger with complete information. Most notably, the interaction between knowledge and information was significant for anger but not for unfairness: Anger increased little when common knowledge was added to partial information (unfairness ratings showed a larger increase); anger did increase when complete information was added to not common knowledge; it increased most when respondents had both common knowledge and complete information. This pattern duplicates the pattern observed for rejections and provides additional, strong support for Hypothesis 3b. To test the relative predictive ability of unfairness and anger, we used a logistic regression analysis with accept/reject choices as the dependent variable and anger and unfairness ratings as independent variables. To do this, we collapsed both the anger and the unfairness scales: For each scale, when anger or unfairness was reported, we coded it as 1; when either was not reported, we coded it as zero. (The results of this analysis should be interpreted with caution because anger and unfairness are self reports, not experimental manipulations. Significant effects suggest covariation of the two variables; no causality can be inferred.) Table 7 shows that the best fitting model, Model 1, includes anger, unfairness, and their interaction. Model 3, using only anger, is a better fit than Model

Models a

Predictor variables 1. Anger 2. Unfairness

3. Anger 3 Unfairness 4. Constant x2 df

1 0.51** (.100) 0.10 (.100) 0.41** (.100) 20.34** (.100) 121.54 3

2 0.41** (.089) 0.25** (.086)

20.34** (.063) 103.38 2

3

4

0.59** (.063) 0.53** (.059)

20.02 (.063) 94.89 1

0.04 (.059) 82.80 1

a Anger and unfairness were categorical variables. The reported contrasts are deviation contrasts. These are not experimental manipulations and are therefore not strictly predictor variables. Note. Numbers in parentheses are standard errors. *p , .05; **p , .01.

4, using unfairness alone. These findings continue to support the logic of Hypothesis 3b. DISCUSSION

All of the hypotheses received general support: People tended to accept $2 offers more than $1 offers and offers that exceeded their outside options; they tended to reject offers that were less than their outside options; they perceived more offers as unfair when they knew how much was being divided; complete information increased the frequency of their reported anger; and combining common knowledge and complete information prompted considerable anger and many rejections. While the data support the predictions of the rational models, the predictions can be augmented by considering the effects of fairness perceptions and emotions. The economic models did predict behavior very well in the partial information conditions; when people had more knowledge or information, however, their concern for comparable outcomes surfaced, and this concern was exacerbated when they could attribute intentionality to offerers. The presence of either common knowledge or complete information boosted reports of unfairness, suggesting that it may take very little for people to perceive small offers as unfair. In contrast, anger increased markedly across conditions, particularly when respondents had both common knowledge and complete information. Although anger did not predict all of the rejections (and its absence did not predict all of the acceptances), the similarity of the anger and rejection results emphasizes anger’s importance in people’s decisions.

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The model that best fits the data included significant effects for each of the independent variables as well as the knowledge by information and the offer size by outside option interactions. Analysis also indicated that common knowledge had an impact on respondents only when they also had complete information. This could happen only if respondents attributed unfairness to offerers (due to their information) and then reacted with anger when their knowledge about the offerers’ information increased. The fairness model can explain the effect for information, but it cannot explain the knowledge effect: People reacted most strongly when they also knew that offerers knew their outside option. These results are similar to those prompted by Kravitz and Gunto’s (1992) power statement (“I know you’d like more, but that’s the way it goes. Take it or leave it!”) but they are more subtle, as they are based on structural rather than interpersonal variables. The fact that common knowledge increased acceptances in the control conditions also strengthens the conclusion that offers must be perceived as unfair before people make strong attributions, get angry, and deny both themselves and offerers objective benefits. Unfairness perceptions alone were not so potent. The increase in rejections that accompanied the addition of anger to unfairness (Column 4 in Table 2) can be directly attributed to spite. Unfairness alone led to rejections; anger led to many more. Since this study did not manipulate anger, these conclusions are correlational rather than causal. Anger seems to be a strong determinant of rejections and inefficient outcomes, however, since anger at small offers seems to be a more plausible cause of rejections than anger at small outside options (which would have boosted rejections in all of the conditions). In conjunction with the results on offerers (e.g., Pillutla & Murnighan, 1995), the picture of ultimatum bargaining now looks like this: Ultimatum offerers tend to be strategic, looking for ways to increase their own outcomes. Respondents expect fairness: When they perceive that an offer is unfair, many react angrily and spitefully reject beneficial offers. The asymmetry of the two parties’ outlooks, with offerers defining ultimatums strategically and respondents defining them morally (Murnighan & Pillutla, 1995), is particularly striking. Recent research by Guth and Van Damme (1994), however, suggests that respondents’ angry and unfair reactions are self-centered: When their respondents received offers with reasonable outcomes and knew that another recipient, whose outcome depended on their decision, received a small, unfair offer, they tended to accept the offers. They were essentially unaffected by the others’ outcomes: whether they accepted or rejected an offer depended on their own outcome rather than

others’. This suggests that respondents are not seeking broadly based fairness, but only fairness for themselves. CONCLUSIONS

Almost 30 years ago, Walton and McKersie (1966) used rational analysis to outline when negotiators might be expected to reach agreement and when they should disagree. Negotiations that could provide profitable outcomes (i.e., a positive bargaining range) were those that should yield an agreement; disagreements were warranted only when joint profit was not possible (a negative bargaining range). The current study included one condition where agreements were not expected, when offers were less than respondents’ outside options. Respondents rejected a great majority of these offers; they also accepted most of the offers that exceeded their outside options. The strict economics of offers, which boosted respondents’ outcomes by $1 or $2, was enough to determine whether most respondents accepted or rejected offers, supporting Walton and McKersie’s basic logic and the predictions of the rational model. A substantial minority of the respondents, however, rejected economically advantageous offers. By predicting that people will be concerned about their relative payoffs as well as their absolute payoffs, the fairness models (e.g., Adams, 1965; Bolton, 1991) provided a more complete explanation of these findings. While rational models do well in predicting most of the outcomes of this experiment, the fact that they pay little or no attention to the negotiation process limits their predictive power. The fairness models not only posit that interpersonal comparisons will influence people’s decisions, they also suggest that emotional reactions like resentment and moral outrage can also contribute to subsequent behavior (Bies, 1987; Folger, 1987). Our approach focused on anger, which seems to be a more basic (and possibly pervasive) emotion. Anger is usually one element in resentment and moral outrage; it also provides a basis for a direct behavioral consequence—spite. In some sense, the wounded pride/spite model is more comprehensive than the fairness models: It makes all of the fairness model’s predictions and more and, through anger, provides a deeper explanation for why some small offers are accepted and others are not. The current results supported its predictions and its underlying logic, in a fairly subtle situation that included no verbal abuse (as in previous research). Future research might consider whether the model can be applied more broadly than just within the context of ultimatum bargaining. Overall, the results supported all three sets of predictions: all of the motivational bases that are inherent in

ANGRY ULTIMATUM REJECTIONS

the models probably contributed to respondents’ choices. They may all contribute to interpersonal choices in other contexts as well. The real issue in predicting people’s reactions to outcome distributions, then, is determining which motivation dominates when. Few people will refuse huge sums of money, even if the offerer makes them angry or if they feel the offer is unfair. (Although the saying that anger is blind suggests that sufficient provocation may overcome even very attractive economic outcomes.) Fairness concerns also continue to be a standard yardstick that people use to evaluate outcome distributions, in Socrates’ early dialogues (described in Plato’s Republic) as well as in current employment equity debates. And most people both experience and depend on emotions to function efficiently (Damasio, 1995). The current study contrasted these motivations since, in some conditions, offers were larger than respondents’ alternatives (i.e., they were economically good) but they were procedurally unfair and/or apparently manipulative. Although respondents in the common knowledge-complete information conditions reported more anger than anyone else in the study, most still accepted these offers. This suggests that procedural injustice may not be able to change immediate, economic behaviors by itself; instead, it may leave a powerful residue of bad feelings, stress, and resentment which may find a later outlet. The findings also suggest that distributive justice and economic issues may have more immediate behavioral impact and that procedural injustice might have its greatest behavioral effects in combination with distributive injustice. This is exactly the conclusion, drawn independently and more systematically, by Brockner and Wiesenfeld (in press). The rejection of economically advantageous offers prompted frequent reports of anger. This suggests that a compensating mechanism may work between anger and money: Each might overcome the other, depending on their strengths and a person’s inclinations. The idea that money can overcome negative feelings is not new: Dawes (1980) noted that people often defect in social dilemmas if their payoffs are high enough, even though they might otherwise cooperate. Previous research (Pillutla and Murnighan, 1995) has also shown that respondents tended to accept relatively large offers (approximately $4 when $10 was being divided) even when an independent third party had labeled them unfair. While money can overcome anger, unfair ratings, and tendencies to cooperate, this study also documents a widely accepted but (apparently) previously undocumented lay observation, that anger can overcome money and interfere with the efficient fulfillment of the profit motive. A few respondents expressed anger even when they accepted offers (though they were fewer in number than

221

those who expressed anger when they rejected offers). Since this occurred most often when offers were larger than outside options, it suggests that participants were angry at themselves for allowing their economic rationality to override their concerns for fairness.3 Viewed this way, self-directed anger is a result of the act (i.e., to accept or reject) and a person who can forecast her feelings may try to avoid this unpleasant state by acting to reduce anticipated negative emotion. Tripp et al.’s model, which views emotional satisfaction (distress) as a utility (disutility) to be maximized (minimized) would support such an inference. We have no way of verifying this, however, in this study; future research might distinguish between the effects of self- and other-directed anger. Although spite led many respondents to choose less profitable outcomes rather than accept and give offerers much larger outcomes, spiteful behaviors occurred a minority of the time and the economic costs that respondents imposed upon themselves by their spiteful acts were fairly small (only $1 or $2). The subtlety of the situation may have contributed to this effect. Future research might investigate whether more potent attributional antecedents, like personal insults and outrageous demands, might lead people to give up even more money to spite a counterpart [although such research may run afoul (appropriately) of ethical constraints]. Field research might also investigate how much anger might possibly cost when larger economic sums are involved. Examples of anger blocking profitable collaborations within or between organizations are numerous. Property purchase negotiations often break off when sellers take offense at a buyer’s low opening offer, even when a mutually beneficial agreement is possible. Strikes impose losses on both management and labor when both can usually gain from agreement. Similar economic inefficiencies can occur when emotions get so heated that people cannot bear to interact with each other. Anger not only results when people receive small ultimatums: it can also stimulate ultimatums. The inability of people to predict the effects of their own actions on others (e.g., Ginzel, 1994) may well instigate an angry interaction spiral, similar to that associated with conflict spirals (Lawler, 1986). Future research might also pursue these dynamics, which precede the process we have investigated here. Although the possibility of inefficiencies due to anger are not surprising, it is surprising that they have not been documented so clearly before. Anger provides a compelling short term explanation for ending negotiations or limiting interaction, in ultimatum bargaining

3

We thank an anonymous reviewer for this observation.

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and in many other social and organizational interactions, even though cooler, rational thought, even by the parties involved, may make them wonder at their willingness (at least in the short term) to suffer unnecessary losses. Bazerman (1993) argued that the study of fairness is complicated by the fact that fairness judgments are often inconsistent: they may be based on normatively irrelevant concerns (e.g., whether individuals like the person they are comparing themselves to); they may depend on the way a problem is framed (e.g., whether they face a gain or a loss; Kahneman & Tversky, 1982); and they are sometimes intransitive (Bazerman, Loewenstein, & White, 1992). This makes it difficult to determine fairness judgments’ effects on subsequent behaviors. In her study of ultimatum bargaining, Blount (1995) found that comparative outcome judgments (fairness concerns in our terminology) have a different impact on subsequent behavior depending on whether a human or a non-human agent causes the outcome and whether the human is self-interested. Taken together with our results, which show that fairness concerns affect subsequent behavior in some situations and not in others, this suggests that fairness judgments and their subsequent effects may both be inconsistent. The wounded pride/spite model suggests that emotional reactions provide the critical link that determines when fairness perceptions tend to affect immediately subsequent behavior. Although all of these observations imply that emotions should be held in check during negotiations, Damasio’s (1995) recent medical research suggests that moving to the opposite extreme of removing all emotions is far worse. He studied people who had suffered prefrontal brain damage: they performed well on cognitive tests but felt no emotion, which left them paralyzed by the number of available choices when they faced a decision. According to Damasio, the limits of human memory make emotions and feelings a necessary component of decision making. In any decision scenario, before the application of cost/benefit analyses and before a person can reason toward a solution, something important can happen: if people experience an association between a bad outcome and a current response option, however fleetingly, they experience an unpleasant gut feeling. These feelings help eliminate options, making decisions tractable. Damasio concludes that feelings and emotions give people the opportunity to use logic in their own best interests and that a reduction in the ability to experience emotions may be an important source of non-rational behavior. The current results also suggest that a necessary condition for feeling anger (and possibly any emotion) in negotiations is the presence of relevant information:

without information, there can be no anger. This idea prompts a somewhat paradoxical solution to the problem of inefficient agreements, that is, to interfere with the emergence of emotions by restricting people’s information. The old saying “ignorance is bliss” may not only be based on the consideration that knowledge can bring unhappiness; knowledge may also provoke emotions that interfere with future outcomes, making less knowledge more profitable (and possibly blissful). This suggests that people who have less information may be happier with their outcomes. This does not fit, however, the conclusions of early research on pay secrecy (Lawler, 1963) which suggested that people without information suspected that others’ salaries were higher than they actually were. The different approaches of the two lines of research suggest that the effects of the presence or absence of information may depend on the context and the kind of information, opening a wide array of research topics for consideration. In competitive, negotiation-oriented contexts, where ultimatums appear or which ultimatums evoke, the current data suggest that the cooperative strategy of sharing all information may have serious negative consequences for all concerned. It would be interesting to see how far this maxim might extend. Offers that exceeded outside options in this experiment led to one of two basic reactions: many acceptances or, less frequently, angry rejections. Offers that equaled outside options led to fewer acceptances and less frequent reports of anger; offers that were exceeded by outside options were rarely accepted. This pattern suggests that people may need to be angry to act in a way that reduces their outcomes. When they can punish others without suffering losses themselves, they may do so without getting angry. But if punishing unfair behavior requires that they lose something themselves, they may decline to do so (as observed in coalition bargaining by Murnighan & Szwajkowski, 1979) or respond with considerable anger. Although we designed this experiment to maximize rejections and anger, we created many conditions where people could punish others without suffering losses themselves. True spite may require such personal losses. Although this study displayed much higher rejection rates than previous ultimatum research, the presence of outside options may have made this possible. Thus, the wounded pride/spite hypothesis might be tempered in conditions where people can enforce a disagreement without hurting themselves. We would revise the model to suggest that, for people to punish others at a cost to themselves, they have to be angry; unfairness alone, unaccompanied by anger, will lead to rejections only if a person will not suffer their own loss.

ANGRY ULTIMATUM REJECTIONS

This study illuminates the important interplay between emotions and action in competitive negotiations. Having information and the ability to make sharp attributions about the actions of the powerful players (offerers) led those with less power (respondents) to exert their control (to reject offers), especially if they had attractive alternatives. [Like the postulates of Lawler’s (1986) model of conflict spirals, parties whose power bases varied had an increased likelihood of conflict.] Some respondents reacted with true spite, hurting the powerful offerer more than themselves by not going along with an inequitable payoff proposal. And although perceptions of unfairness were necessary, they did not provide a complete explanation for the rejections of small outcomes. Instead, strong reactions seemed to also require anger. Given the frequency of outcome distributions in both social and organizational negotiations, many of which seem arbitrary and involve parties with asymmetric power bases, further investigation of the emotional, cognitive, and behavioral dynamics of ultimatums and other outcome distributions may help model a diverse array of conflict resolution processes.

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