Contingent Weighing of Past and Future Decision Outcomes

Transcription

1 No. 5:31,1 Contingent Weighing of Past and Future Decision Outcomes Ásgeir Juliusson, Niklas Karlsson, and Tommy Gärling Department of Psychology Göteborg University Juliusson, Á, Karlsson, N., and Gärling, T., Contingent Weighing of Past and Future Decision Outcomes. Göteborg Psychological Reports, 2001, 31, No. 5. This research investigated the weighing of past and future outcomes in investment decisions. Building on previous research demonstrating that both past and future outcomes determine choices to continue or discontinue investments, two experiments were conducted with the aim of investigating contingencies of how prior investments and returns are weighed relative to current investments and expected future returns. Experiment 1 tested the hypothesis that a gain-maximizing goal would make participants place less weight on sunk outcomes (prior returns minus prior investments) than would a lossminimizing goal do. Sunk outcomes influenced the decisions but only a main effect of decision goal was observed irrespectively of whether the investments were personal or business. In Experiment 2 the results showed a main effect of bonus although no evidence of an contingent effect for ignoring losses. The main findings of both experiments are that both the past and the future and both past losses and gains influence investment decisions. Key words: Decision making, sunk cost, escalation, contingent weighing Author Note: This research was financially supported by grant # from the Bank of Sweden Tercentenary Foundation. We thank Anders Biel for comments on an earlier draft.

2 No. 5:31,2 Prior irreversible investments in a project are referred to as sunk costs (Arkes & Blumer, 1985). To take sunk costs into account in making decisions is not rational (Dawes, 1988). It is always better to choose an alternative that is expected to give the most beneficial future returns irrespectively of whether or not prior investments have been made in this alternative. Nevertheless, this type of irrational behavior, referred to as the sunk-cost effect (Arkes & Ayton, 1999) or escalation (Staw, 1976, 1997), has been widely observed. Several explanations of the sunk-cost effect have been proposed. Arkes and Blumer (1985) argued that escalation stems from an overgeneralization of a don t waste decision rule (see also Arkes, 1996). That escalation reflects a need for self-justification is another explanation (Brockner, 1992; Staw & Ross, 1989) drawing on results showing that people who are responsible for an initial decision escalate to a greater extent than those who are not responsible. Still another explanation (Garland & Newport, 1991; Northcraft & Neale, 1986; Schaubroeck & Davis, 1994) assumes that discontinuing or continuing investment is interpreted as a choice between a sure and an uncertain loss. According to prospect theory (Kahneman & Tversky, 1979), people are risk seeking (i.e., continue investments or escalate) when making such choices. Sometimes people discontinue investment too early, or de-escalate, in response to sunk costs (Heath, 1995; Karlsson, Gärling, & Bonini, 2001; Karlsson, Juliusson, Grankvist, & Gärling, 2000; McCain, 1986). A don t waste rule, self-justification, and prospect theory all fail to explain this. Heath (1995) therefore proposed a theory of mental budgeting assuming that people set budgets so that they can track ongoing investments. Escalation occurs when investments are difficult to track or when the absence of estimated returns makes it difficult to set a budget. In contrast, de-escalation occurs when a budget can be set, but total investments (prior investments plus current investments) exceed estimated (total) returns. Heath (1995) thus accounted for when people escalate and when they de-escalate. It is tacitly assumed, however, that people always take sunk costs into account. The question why they do this therefore remains unanswered.

3 No. 5:31,3 Other research raises the more general question of when and why people integrate or segregate prior or sunk outcomes when facing a current decision (Gärling, Karlsson, Romanus, & Selart, 1997; Laughunn & Payne, 1984; Linville & Fischer, 1991; Thaler & Johnson, 1990). According to the loss-sensitivity principle (Gärling & Romanus, 1997; Romanus, Hassing, & Gärling, 1996), people are only integrating prior outcomes when they evaluate potential losses. A more comprehensive processing of negative events (Larrick, 1993; Taylor, 1991) is assumed to result in this asymmetry between future losses and gains. Hence, building on the loss-sensitivity principle, people may be expected to take sunk costs into account when they are motivated to minimize losses but not to the same extent when they are motivated to maximize gains. If the loss-sensitivity principle is combined with the theory of mental budgeting, a more comprehensive account is possible to offer of how, when, and why escalation and de-escalation occur. The loss-sensitivity principle suggests that whether the decision goal is to maximize gains or minimize losses is crucial for whether an investment decision will be based on a mental budget including or excluding sunk outcomes. As noted, the mental budgeting theory explains when inclusion of sunk outcomes lead to escalation or de-escalation. A major finding in the study by Karlsson et al. (2000) was that participants are influenced by both sunk outcomes and expected returns. Thus, exactly as Heath (1995) proposed, all available information is taken into account. However, in its simplest form Heath s rate-of-return hypothesis could not account for the results. In this article we report a test of an extension of this hypothesis. We start with formalizing the problem in the following equation where the strength of the choice of continuing investment (C) is related to prior investment (PI), prior returns (PR), current investment (CI), and expected returns (ER): C = b PR PR b PI PI + b ER ER b CI CI + a (1), where a is a constant and bs (>0) are weights. As specified in Table 1, different predictions can be made concerning these weights. The sunk-cost and sunk-outcome effects imply that no weight is placed on current

4 No. 5:31,4 investment and expected returns. In previous research this has frequently been induced by the experimental procedure since expected returns (and opportunity costs) have not been transparent (Staw, 1997). Furthermore, most studies have confined themselves to investigate the condition PR<PI, thus excluding a test of the sunk-outcome hypothesis. In fact results of research ignoring this boundary condition (Karlsson et al., 2001, 2000; Laughhunn & Payne, 1984; Thaler & Johnson, 1992) suggest that the sunkcost effect is a special case. The rate-of-return hypothesis (Heath, 1995) implies that if all information is transparent, equal weights are placed on the past and the future so that escalation occurs if the prior and future returns exceed prior and current investment, otherwise de-escalation occurs. Finally the marginal decision making hypothesis (Heath, 1995) implies that no weight is placed on the sunk outcomes. Table 1. Predictions of Weights of Prior and Future Outcomes in Escalation. Hypothesis Boundary condition Prediction Sunk-cost effect PR < PI b PR = b PI > 0; b ER = b CI = 0 Sunk outcome effect None b PR = b PI > 0; b ER = b CI = 0 Rate-of-return None b PR = b PI = b ER = b CI > 0 Marginal decision making None b PR = b PI = 0; b ER = b CI > 0 Note. PR denotes prior returns, PI prior investment, ER future returns, CI current investment. The bs are weights. We suggest that understanding escalation requires that a contingent weighing principle (Tversky, Sattah, & Slovic, 1988) is evoked, thus implying that additional factors must be brought in to predict whether escalation, de-escalation, or marginal decision making will occur. Thus, equation 1 and Table 1 only lay out a general framework that can be used to analyze the outcomes of experiments in which these additional factors are varied. In this paper we focus on two such factors, type of decision (whether investments are personal, made for a company, or consists of a decontextual

5 No. 5:31,5 gamble) and decision goal. In Experiment 1 we compare personal to business investment decisions as well as a loss-minimizing goal to a gainmaximizing goal. In Experiment 2 personal investment decisions are compared to gambling decisions. We also enhance the comparison between a loss-minimizing goal and gain-maximizing goal by offering a bonus. Experiment 1 In conjunction with the theory of mental budgeting (Heath, 1995) the loss-sensitivity principle (Gärling & Romanus, 1997; Romanus et al., 1996) offers a more comprehensive account of how, when, and why escalation and de-escalation occur. It is predicted from the loss-sensitivity principle that a loss-minimizing decision goal leads to that choices to continue or discontinue investments are based on a mental budget including sunk outcomes. Whether escalation or de-escalation occurs may then be predicted from the rate-of-return hypothesis (Table 1). In contrast, if the decision goal is to maximize gains, sunk outcomes are expected to have no or at least a weaker effect. Thus, in this case the marginal decision making hypothesis would predict the choices. However, two previous experiments (Karlsson et al., 2000; Experiments 1 and 2) failed to demonstrate the expected stronger effect of sunk outcomes when participants are instructed that their goal is to minimize losses instead of maximizing gains. An outcome in line with the prediction was however obtained when the decision concerned personal stakes (Experiment 3) that were lower than in the business scenarios employed in the other experiments. Yet, stake in itself seems not to be important since varying it had no effect. The explanation offered was that loss minimization was felt to be more important in the personal domain. In Experiment 1 we employ a fractional factorial design (Kirk, 1995) that allows estimation of the weights participants place on prior returns (PR), prior investments (PI), expected returns (ER), and current investments (CI) when choosing between continuing or discontinuing investments. We hypothesize that participants who are instructed to minimize losses will place more weight on the sunk outcome (prior returns minus prior

6 No. 5:31,6 investments) than would participants with a gain-maximizing goal. In line with previous results, this may however only occur when participants are asked to make personal financial decision and not when they are asked to make business decisions. Method Participants and Design. Forty eight undergraduates at Göteborg University volunteered in return for the equivalent of $6 in payment. Their mean age was 25.5 years (ranging from 19 to 47 years). Two of them had studied economics or business administration for more than one semester. Participants were randomly assigned to four groups. In two groups the participants were instructed to make the decision with the goal of maximizing gains, in the other two groups with the goal of minimizing losses. In one of the former and in one of the latter groups, the participants were instructed to imagine that they made decisions to invest their own money in a project. In the remaining two groups participants were instructed to imagine that they were a company manager whose task was to make an investment decision for the company. Procedure. Participants were seated in private boots facing a personal computer. They made nine independent investment decisions described in scenarios displayed on the computer screen. The general instructions asked the participants to carefully read the descriptions of the scenarios and answer questions related to them. The investment scenarios were similar to those used in Karlsson et al. (2000) which in turn were modeled after Staw s (1976) pioneering study. In the scenarios information was given about prior investments (PI), prior returns (PR), current investments (CI), and expected returns (ER). In the fractional factorial design (see Table 2) each factor had three equally spaced levels that were combined so that the main effects were orthogonal. The

7 No. 5:31,7 number of scenarios was kept to nine by confounding the interaction effects with the main effects 1. In the business investment scenarios participants imagined that they were a company manager whose task was to continue or discontinue a prior investment of the company s money he or she was responsible for. The levels of each factor were 4, 8, and 16 million Swedish Crowns (SEK) (1 SEK is about US$ 0.12). In the personal investment scenarios participants imagined that they were facing the task of deciding to continue to invest their own money in a project that they had already invested in. The levels of each factor were 4,000, 8,000, and 16,000 SEK. An alternative investment opportunity yielding returns of 10% was always specified. In each scenario the participants in the loss-minimizing groups were told that the future financial situation was not secure so that minimizing losses was an important goal, while participants in the gain-maximizing groups were told that the future financial situation was secure so that there was no reason to be concerned about possible losses. Participants typed their choices in the keyboard corresponding to continue or discontinue investments. They also typed a number indicating their confidence in their decision. The scale ranged from 0 to 10, where 0 was defined as completely inconfident and 10 as completely confident. The scenarios were presented in individually randomised orders. A session lasted about 15 minutes after which participants were debriefed and paid. Results and Discussion The main dependent variable in this and the following experiment is the confidence ratings that were given a positive sign if the choice was to continue, a negative sign if the choice was to discontinue. Hence, the ratings range from -10 (completely confident in the choice not to continue) to 10 (completely confident in the choice to continue). A 0 indicates completely uncertain about whether to continue or discontinue. 1 In the study by Karlsson et al. (2000, interaction effects were in geneal not significant.

8 No. 5:31,8 The results are given in Table 2 for each project and between-groups condition. In this table the percentages of choices to continue are reported for comparisons (more than 50% represents continued investment, less than 50% discontinued investment, and 50% indifference). As may be seen, overall participants in the gain-maximizing group continued to invest to a larger extent than did participants in the loss-minimizing group (M = 0.5 vs. -3.9). That this effect was reliable was substantiated by a 2 (gainmaximizing vs. loss-minimizing decision goal) by 2 (business investment vs. personal investment decision) by 9 (project) mixed factorial analysis of variance (ANOVA) yielding a main effect of decision goal, F(1, 48) = 5.94, p<.05. There was no significant difference between personal and business investments (M = -1.5 vs. -1.9), F(1, 48) = 3.75, p =.07. Neither did the between-groups factors interact with each other or with the within-group factor whereas the main effect of the latter was significant, F(5.08, 198.7) = 47.51, p< In all tests involving within-group factors, the Greenhouse-Geisser correction is applied to the dfs.

9 No. 5:31,9 Table 2. Mean Confidence Ratings and Percentages of Choices to Continue Investments for Levels of Prior Investment (PI), Prior Returns (PR), Current Investment (CI), and Future Returns (ER) Related to Type of Investment Decision and Decision Goal (Experiment 1) Personal investment Business investment Loss-minimization Gain-maximization Loss-minimization Gain-maximization PI PR CI ER M SD % M SD % M SD % M SD Low Low Low Low Low Medium Medium High Low High High Medium Medium Low Medium Medium Medium Medium High Low Medium High Low High High Low High High High Medium Low Medium High High Medium Low Note. The low, medium, and high factor levels were 4,000, 8,000, and 16,000 Swedish Crowns in the personal investment decisions, 4, 8, and 16 million Swedish Crowns in the business investment decisions.

10 No. 5:31,10 To further illuminate the main effect of the within-group factor, one-way repeated-measures ANOVAs were conducted with three levels (low, medium, and high) separately for prior investment, prior returns, current investment, and expected returns, respectively. Overall there were significant main effects of prior investment (M = 1.8 vs. 0.3 vs. 2.2, F(1.87, 88) = 21.50, p<.001), prior returns (M = 2.1 vs. 1.4 vs. 0.7, F(1.78, 88) = 14.90, p<.001), current investments (M = 3.3 vs. 0.4 vs. 3.0, F(1.60, 88) = 44.40, p<.001), and future returns (M = 4.8 vs. 1.4 vs. 0.7, F(1.90, 88) = , p<.001). Since the changes were not always linear although monotonically increasing or decreasing, the following ω 2 (Kirk, 1995) were computed as an estimate of the weights: for prior investment.46, for prior returns.36, for current investment.60, and for expected returns.83. Thus, although all components had a significant effect, the effect was stronger for current investment and expected returns. Despite that no significant interaction effects involving the betweengroups factor were obtained in the overall analyses, the repeated-measures ANOVAs were performed separately for each group to test the main effect of the factors. In each case ω 2 was computed. As can be seen in Table 3, no clear pattern is discernible except that current investment and expected returns tend to have stronger effects in all groups. Table 3. F and ω 2 Corresponding to Main Effects of Prior Investment, Prior Return, Current Investment, and Expected Returns Related to Type of Investment Decision and Decision Goal (Experiment 1). Personal investment Business investment Loss-minimization Gain-maximization Loss-minimization Gain-maximization F ω 2 F ω 2 F ω 2 F ω 2 Prior investment 3.51* ** * *.30 Prior return 12.20** * * Current investment 16.75** ** ** **.38 Expected return 38.65** ** ** **.67 Note. Greenhouse-Geisser corrections have been applied. *p<.05 **p<.01

11 No. 5:31,11 Experiment 2 The results of Experiment 1 apparently failed to demonstrate any weighing contingent on type of decision and decision goal. The observed main effects seem to rule out the possibility that the participants were not affected by the instructions. Still, the instructions may need to be enhanced. To this end monetary incentives were introduced in Experiment 2. Furthermore, to further enhance the effect of monetary incentives relative to the effect of the investment scenario information, decontextual two-stage gambles were used in one condition. In another condition the same monetary incentives as in the gambles were introduced in the personal investment scenarios. It is possible that people are generally loss sensitive (Thaler & Johnson, 1992; Tversky & Kahneman, 1981), so that they for that reason invariably take prior outcomes into account to at least some extent. If this holds true, one needs to devise a test where there is no loss. This was done in Experiment 2 in that in one condition monetary bonuses that participants were promised were only based on expected returns, thus ignoring current investments. In another condition the bonuses were based on expected returns minus current investments. It was expected that sunk costs would be ignored to a larger extent in the former than in the latter condition. Method Participants and Design. Another 48 undergraduates at Göteborg University volunteered in return for the equivalent of $6 in payment. They were between 17 and 48 years old with a mean of Four had studied economics or business administration for more than one semester. An equal number of participants were randomly assigned to four groups. Two groups received bonuses based on expected returns (gain conditions), another two based on expected returns minus current investments (gain-loss conditions). In each case one of the groups received the personal investment scenarios, the other group the decontextual two-stage gambles.

12 No. 5:31,12 Procedure. In the personal investment scenarios, prior investments, prior returns, and current investments were the same as in Experiment 1. However, expected returns were stated as a probability (.20,.40, or.80) to obtain SEK 20,000. In the gambles the monetary amounts were 0.4% of those in the personal investment scenarios. Participants were instructed that they had staked an amount in one gamble and won or lost another amount, and that they were facing a second chance to gamble. They could then either choose to gamble and pay the stake ( continue investment ) or choose not to gamble ( discontinue investment ). The procedure was exactly the same as in Experiment 1 except that the instructions also thoroughly described the bonus. In the gamble conditions, particpants were first told that they would receive SEK 30, the highest amount they could loose. Then, in the gambles they were informed that one gamble would be randomly determined and played. In the gain condition participants were told that they would receive the gain or nothing (and nothing if they choose not to gamble), in the gain-loss condition that they would receive the gain minus the stake or loose the stake if they choose to gamble (otherwise nothing). In the personal investment scenarios the instructions similarly explained that the outcome would be determined for a randomly chosen scenario. In the gain condition participants would receive 0.25% (the sum divided by 400) of the returns or nothing, whereas in the gain-loss condition they would receive 0.25% of the returns minus 0.25% of the current investment or lose the latter sum. To check that participants understood the bonus instruction, they were asked to calculate the bonus for one practice example that was repeated until a correct answer was given. All participants managed to do this after repeating the practice example once. Results and Discussion The results are given in Table 4 for each project and between-groups condition. As may be seen, overall participants in the gain conditions discontinued to invest to a smaller extent than did participants in the gain-loss conditions (M = -0.2 vs. 0.7). Furthermore, this difference appeared to be

13 No. 5:31,13 Table 4. Mean Confidence Ratings and Percentages of Choices to Continue Investments for Levels of Prior Investment (PI), Prior Returns (PR), Current Investment (CI), and Expected Returns (ER) Related to Gamble vs Personal Investment and Type of Bonus (Experiment 2) Gamble Personal investment Gain-Loss Gain Gain-Loss Gain PI PR CI ER M SD % M SD % M SD % M SD % Low Low Low Low Low Medium Medium High Low High High Medium Medium Low Medium Medium Medium Medium High Low Medium High Low High High Low High High High Medium Low Medium High High Medium Low Note. The low, medium, and high factor levels were for PI, PR, and CI SEK 4,000, 8,000, and 16,000 in the personal investment scenario, SEK 16, 32, and 64 in the gambles. The levels of ER corresponded to the probability.2,.4, and.8 of returns of SEK 20,000 (SEK 32).

14 No. 5:31,14 slightly attenuated for the gambles (M = 0.3 vs. 0.3) as compared to the personal investment scenarios (M = -0.6 vs. 1.1). A 2 (loss vs. gain-loss condition) by 2 (gamble vs. personal investment) by 9 (project) mixed factorial ANOVA only yielded significant main effects of bonus, F (1,48) = 7.44, p <.01, and project, F (6.02, ) = 40.73, p <.001 Separate one-way repeated - measure ANOVAs showed that overall there were significant effects of the level of prior investment (M = 1.7 vs. 1.1 vs. 0.5, F (1.99, 93.53) = 10.82, p <.001, ω 2 =.18), prior returns (M = vs. 1.1 vs. 1.7, F (1.97, 92.59) = 11.08, p <.001, ω 2 =.19), current investment (M = 3.2 vs. 0.7 vs. 1.6, F (1.76, 82.72) = 35.28, p<.001, ω 2 =.42), and expected returns (M = -3.2 vs. 1.0 vs. 4.4, F (1.65, 77.55) = 87.20, p <.001, ω 2 =.87). The results of ANOVAs performed separately for each group are given in Table 5. As may be seen, both overall and for the different groups, the results did not differ importantly from Experiment 1. Weights are placed on all components, although current investment and expected returns are weighed more heavily than the others. Despite an overall effect of bonus, parallelling the effect of decision goal in Experiment 1, contingent weighing does not seem to account for this effect. Table 5. F and ω 2 Corresponding to Main Effects of Prior Investment, Prior Return, Current Investment, and Expected Returns Related to Gamble vs. Personal Investment and Type of Bonus (Experiment 2). Gamble Personal investment Gain-loss Gain Gain-loss Gain F ω 2 F ω 2 F ω 2 F ω 2 Prior investment * * **.40 Prior return * **.38 Current investment 17.42** * ** **.42 Expected returns 29.43** ** ** **.71 Note. Greenhouse-Geisser corrections have been applied. *p<.05 **p<.01

15 No. 5:31,15 General Discussion The present research yielded clear support for that people take both the past and the future into account when making decisions. In fact this tendency appeared to be very strong and was not affected neither by goal instructions, monetary incentives, or scenario information. Thus, there is little basis at present for concluding that weighing is contingent. In line with Heath (1995) the results showed that participants both escalated and de-escalated. The same holds true if one in Tables 2 and 4 only considers the three projects with a sunk cost. Thus, escalation is apparently not invariably observed. Of course, the reason is that participants place weights on expected value. In fact, this was found in Karlsson et al. (2000) as well as in Karlsson et al. (2001) where escalation was only observed when expected values for two alternatives were equal. It may be concluded that the rate-of-return hypothesis (Heath, 1995) provides the best account of the present results. However, an explanation is also needed of why the past has less influence than the future. In fact, it may reflect that all participants place weight on the future, whereas only some are irrational and take the past into account. A future study may enquiry into how people understand sunk costs, possibly depending on their training. The instructions to maximize the gains of the decision made participants more confident in continuing investment compared to lossminimization instructions. The same was found when a bonus was based on gains disregarding losses. In Equation 1 differences in the constant a account for these effects whereas the weights b did not change. Thus, the effect of instructions to maximize gains vs. minimizing losses and bonus appear to be to make participants less cautious. Perhaps they first make a tentative decision about what to do on the basis of the available information, then become more confident in that decision given that a loss is not serious. Of course, in Experiment 2 it would have been rational to always continue investment (or gamble), since the bonus would be the same irrespectively of the current investment (or stake). Yet, the available information appeared to have such a compelling effect that a majority of participants were unable to ignore it.

16 No. 5:31,16 The present research makes two main contributions. First, it establishes that when expected returns in the future are transparent, they will influence investment decisions. However, despite this influence, sunk costs are not ignored. Thus, both the past and the future have an influence. Second, not only prior losses (sunk costs) but also gains influence subsequent investment decisions. In addition to the sunk-cost effect (Arkes & Blumer, 1985), there is thus also evidence for the house-money effect (Thaler & Johnson, 1990) implying that a prior gain makes people more willing to invest. The future challenge is to understand these more general phenomena.

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