Impact of decision goal on escalation

Impact of decision goal on escalation

Niklas Karlsson *, �AAsgeir Juliusson, Gunne Grankvist,Tommy G€aarling

Department of Psychology, G€ooteborg University, Haraldsgatan 1, P.O. Box 500,

SE-40530 G€ooteberg, Sweden

Received 15 May 2001; received in revised form 10 January 2002; accepted 15 February 2002

Abstract

This research investigates the sunk-cost effect or escalation defined as the irrational ten-

dency to choose to continue to invest money, time, or effort following unsuccessful invest-

ments. Building on previous research demonstrating a loss-sensitivity principle in sequential

decision making, the hypothesis was proposed that a loss-minimization goal would lead to

stronger effects of sunk outcomes (prior gains and losses) than would a gain-maximizing goal.

The hypothesis was investigated in three experiments with undergraduates responding to in-

vestment decision scenarios. Although the tendency to continue investments was always larger

for gain-maximizing than for loss-minimizing goal instructions, the sunk-outcome effect was

stronger in the former case. However, when the decisions were personal and concerned lower

stakes rather than business investments involving large amounts of money, the expected stron-

ger effect of sunk outcomes was found for loss-minimizing goal instructions. Another finding

was that the expected value was never ignored, thus suggesting that future research should fo-

cus on the joint effects of the expected value and sunk outcomes.

� 2002 Elsevier Science B.V. All rights reserved.

PsycINFO classification: 2340

Keywords: Decision making; Escalation; Sunk cost

1. Introduction

The tendency to continue to invest money, time, or effort following unsuccess-

ful investments (termed sunk costs) is referred to as the sunk-cost effect (Arkes &

Acta Psychologica 111 (2002) 309–322

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*Corresponding author. Tel.: +46-31-773-1938; fax: +46-31-773-4628.

E-mail address: [email protected] (N. Karlsson).

0001-6918/02/$ - see front matter � 2002 Elsevier Science B.V. All rights reserved.PII: S0001-6918 (02 )00056-2

mail to: [email protected]

Blumer, 1985) or escalation (Staw, 1976, 1997). To take sunk costs into account in

making decisions is not rational (Dawes, 1988). It is always better to choose the al-

ternative expected to give the most beneficial future returns irrespective of whether

or not prior investments have been made in this alternative. Nevertheless, this type

of irrationality has been widely observed (Arkes & Ayton, 1999).Several explanations of why people escalate in response to sunk costs have been

proposed. Arkes and Blumer (1985) suggested that an important reason is that peo-

ple don’t want to appear wasteful to themselves and others. Hence, they argued that

escalation stems from an overgeneralization of a ‘‘don’t waste’’ decision rule (Arkes,

1996). Drawing on results showing that people who are responsible for an initial de-

cision escalate to a larger extent than those who are not responsible, another expla-

nation is that escalation reflects a need for self-justification (Brockner, 1992; Staw &

Ross, 1989). Still another explanation (Garland & Newport, 1991; Northcraft & Ne-ale, 1986; Schaubroeck & Davis, 1994) assumes that discontinuing or continuing in-

vestment is interpreted as a choice between a sure and an uncertain loss. As predicted

from prospect theory (Kahneman & Tversky, 1979), people would be risk seeking

(i.e., continue investments or escalate) when making such choices.

It has more recently been demonstrated that people sometimes discontinue invest-

ment too early, or de-escalate, in response to sunk costs (Heath, 1995; McCain,

1986). To account for that people both escalate and de-escalate in response to sunk

costs, Heath (1995) proposed a theory of mental budgeting. In this theory it isassumed that people set budgets so that they can track ongoing investments. Es-

calation occurs when investments are difficult to track or when the absence of esti-

mated returns makes it difficult to set a budget. According to the rate-of-return

hypothesis, de-escalation occurs when a budget can be set but total investments

(prior investments plus current investments) exceed estimated (total) returns. Al-

though Heath (1995) offers an account of when people escalate and when they de-

escalate, the proposed theory does not explain why people take sunk costs into

account in the first place.Other research has addressed the more general question of when and why people

integrate prior (sunk) outcomes in facing a current decision (G€aarling, Karlsson,Romanus, & Selart, 1997; Laughhunn & Payne, 1984; Linville & Fischer, 1991; Tha-

ler & Johnson, 1990; Tversky & Kahneman, 1981). Several experiments with re-

peated gambles have supported a loss-sensitivity principle that accounts for how

people process prior gains or losses when making a decision (G€aarling & Romanus,1997; Romanus, Hassing, & G€aarling, 1996; Romanus, Karlsson, & G€aarling, 1997).According to this principle (G€aarling et al., 1997), people only take into account (in-tegrate) prior outcomes when evaluating potential future losses. A tendency to more

comprehensive processing of negative events such as losses (Larrick, 1993) may un-

derlie this asymmetry between future losses and gains. Taylor (1991) argued that

avoiding negative outcomes is more important for survival than attaining positive

outcomes. Also for this reason, losses may be processed more thoroughly.

Romanus et al. (1996) found that increasing attention to a potential loss made

participants more influenced by a prior outcome. Hence, prior outcomes may be ex-

pected to have a larger influence when people are motivated to minimize losses than

310 N. Karlsson et al. / Acta Psychologica 111 (2002) 309–322

when they are motivated to maximize gains. Generalizing this finding to escalation of

investment decisions, it is hypothesized that a loss-minimization goal would lead to

more escalation than a gain-maximization goal. That people fail to ignore prior in-

vestments may thus be due to the fact that they are more motivated to minimize

losses than to maximize gains. Hence, from the loss-sensitivity principle it is pre-dicted that people 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.

To offer a more comprehensive account of why escalation and de-escalation oc-

cur, it is necessary to address both the question of (i) when people take sunk costs

into account and (ii) when people escalate or de-escalate in response to sunk costs.

Combining the loss-sensitivity principle with the theory of mental budgeting gives

answers to both questions. The loss-sensitivity principle suggests that whether the de-

cision goal is to maximize gains or minimize losses would be crucial for whether aninvestment decision will be based on a mental budget excluding or including sunk

outcomes. As already explained, the mental budgeting theory predicts when inclu-

sion of sunk outcomes lead to escalation or de-escalation.

The primary aim of the present three experiments is to investigate the impact of

decision goal on decisions to continue or discontinue an investment. More specifi-

cally, the experiments examine whether sunk outcomes are processed differently de-

pending on whether the goal of the decision is to minimize losses or to maximize

gains. Experiments 1 and 2 investigate how the decision goal affects decisions to con-tinue or discontinue business investments, while Experiment 3 investigates how the

decision goal affects decisions to continue or discontinue personal investments.

2. Experiment 1

In line with Heath (1995), it is assumed that people who face the task of deciding

to continue an investment set a mental budget to track costs and benefits. Accordingto the rate-of-return hypothesis, a decisions to continue investments will be made

when the returns exceed the total (prior and current) investments, otherwise a deci-

sion to discontinue investments will be made. However, the loss-sensitivity principle

(G€aarling et al., 1997) predicts that prior investments will only have this effect whenthe goal is to minimize losses. In contrast, if the goal is to maximize gains it predicts

that prior investments are ignored so that the decision is based on an evaluation of

the future outcome (termed marginal decision making).

Experiment 1 and subsequent experiments used scenarios requiring participants tomake decisions to continue or discontinue a prior investment. Explicit information is

available about prior and current investments and prior and expected future returns.

Since the predictions are not confined to sunk costs, two levels of sunk costs were

crossed with two levels of positive sunk outcomes (i.e., prior returns exceeding prior

investments). Future returns were varied as a range implying that the current invest-

ment may be either successful or unsuccessful. The expected value defined as the

midpoint of the range minus current investment was either positive or negative.

Table 1 summarizes the predicted investment decisions for gain-maximization and

N. Karlsson et al. / Acta Psychologica 111 (2002) 309–322 311

loss-minimization goals under the different combinations of sunk outcomes and ex-

pected outcomes. When the goal is gain maximization, participants are expected to

continue investments for positive expected values and discontinue investments for

negative expected values. When the goal is to minimize losses, participants are ex-

pected to continue investments (escalate) for a negative expected outcome in re-sponse to a positive sunk outcome, and to discontinue investments (de-escalate)

for a positive expected outcome following a negative sunk outcome.

In several studies of escalation (e.g., Brockner, 1992; Staw, 1976; Staw, Barsade,

& Koput, 1997; Teger, 1980), being responsible for the investment decision has ap-

peared to be a necessary condition for escalation to occur. Being responsible has fur-

thermore been shown to affect how people search and evaluate information

(Bazerman, Beekun, & Schoorman, 1982; Schoorman, 1988; Staw & Fox, 1977).

However, escalation is sometimes observed despite that it is unclear who was respon-sible for the prior decision (Conlon & Garland, 1993; Karlsson, G€aarling, & Bonini,2002).

It is hypothesized that responsibility evokes a loss-minimization decision goal be-

cause a decision maker responsible for a prior investment wants to avoid justifying

losses. Therefore, he or she will be more sensitive to both prior and future losses. It is

thus predicted that responsibility and inducing a loss-minimization goal will both in-

crease the tendency to take sunk outcomes into account. In four groups of partici-

pants, goal instructions were crossed with responsibility instructions. An effect ofexpected value was predicted in all groups. An effect of sunk outcome was predicted

in all groups except in the non-responsible gain-maximizing group.

2.1. Method

2.1.1. Participants

Forty-eight undergraduates at G€ooteborg University volunteered in return for theequivalent of $6 in payment. Their mean age was 25.2 years (ranging from 19 to 49years). None had studied economics or business administration for more than one

semester. An equal number of participants, half of them men and half of them

women, was 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 imagined that they were responsible for the prior in-

Table 1

Predicted decisions to continue or discontinue investments for gain-maximization and loss-minimization

goals under different combinations of sunk outcomes and expected outcomes

Sunk outcome Expected outcome Gain-maximization goal Loss-minimization goal

Negative Negative Discontinue Discontinue

Positive Negative Discontinue Continue

Negative Positive Continue Discontinue

Positive Positive Continue Continue


vestment decision, whereas in the other groups they imagined that another person

was responsible.

2.1.2. Procedure

Participants were seated in private booths facing a personal computer. They madeeight independent investment decisions for scenarios displayed on the computer

screen. The general instructions asked the participants to carefully read the scenarios

and answer questions related to them.

Participants were asked to play the role of a consultant who was hired in by a

company. The role of the consultant was to recommend continued or discontinued

investments in the business. The investment scenarios were similar to those used in

previous research (Conlon & Garland, 1993; Staw, 1976). They contained informa-

tion about prior investments, prior returns, current investments, and future expectedreturns (in the form of a range). All amounts were given in Swedish Crowns or SEK

(1 SEK is approximately equal to US $0.12). An alternative investment opportunity

yielding returns of 10% was also specified. An example is the following (words in

brackets were not presented to the participants):

The company has invested SEK 2.2 millions [prior investment] in developing

production facilities. So far the company has received SEK 7.7 millions in re-

turn [prior returns]. Your task is to recommend the company to make an ad-

ditional investment of SEK 2.5 millions [current investment] or not. The

expected returns if the project is completed may be as low as SEK 2.0 millions

or as high as SEK 5.0 millions [expected returns]. If the additional investment is

not made, the project will be discontinued and the expected returns foregone.

The company has an alternative investment opportunity [opportunity cost]with an expected 10% payoff.

After presenting each investment scenario, a summary was provided on the com-

puter screen of how much had been invested, how much had been gained, how muchadditional investment was needed, how much the additional investment would give

in returns, and what the returns would be of an alternative investment.

Table 2 shows how prior investments, prior returns, and current investments were

independently varied in the scenarios for fixed expected future returns. In half of the

scenarios prior investments were low (SEK 2.2 millions), in the other half high (SEK

5.5 millions). In half of the scenarios there were no prior returns, leading to two lev-

els of sunk costs (prior returns minus prior investments). In the other half of the sce-

narios sunk outcomes were positive at two levels due to prior returns of SEK 7.7millions. Current investments were varied so that in half of the scenarios they were

low (SEK 2.2 millions) leading to positive expected values (the midpoints of the

ranges of returns minus the current investments), in the other half they were high

(SEK 5.5 millions) so that the expected values were negative.

In each scenario the participants in the loss-minimizing groups were told that the

future financial situation for the company was insecure 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 concern for possible


losses. Participants in the responsibility groups were told that the prior investment

had been made on the basis of their recommendation, while in the no-responsibilitygroup participants were told that the prior investment had been made on the basis of

a recommendation by somebody else.

Participants made their recommendations by typing an A or B on the keyboard

corresponding to continue or discontinue investments. They also typed a number in-

dicating their confidence in the recommendation. The confidence scale ranged from 0

to 100, where 0 was defined as completely inconfident and 100 as completely confi-

dent. The scenarios were presented according to individually randomized orders. A

session lasted for about 15 min after which participants were debriefed and paid.

2.2. Results

The main dependent variable in this and the following experiments is the confi-

dence ratings. In scoring the ratings, a positive sign was assigned if the decision

was to continue, a negative sign if the decision was to discontinue. Hence, the ratings

range from �100 (completely confident in the decision not to continue) to 100 (com-pletely confident in the decision to continue). A 0 indicates complete inconfidenceabout which alternative to choose.

The mean signed confidence ratings are shown in Table 2. In Table 2 the percent-

ages of decisions to continue are reported for comparisons. The results are averaged

over the responsibility instructions since no effects of these were discernible. Overall

there appears to be effects of all three within-subject factors, although stronger effects

of prior returns and expected value than of prior investments. In addition, gain-max-

imizing participants seem to differ from participants who minimized losses. A 2

(gain-maximization vs. loss-minimization decision goal) by 2 (responsibility vs. noresponsibility instructions) by 2 (amount of prior investment) by 2 (no prior returns

vs. prior returns) by 2 (positive vs. negative expected value) mixed factorial analysis

of variance (ANOVA) with repeated measures on the last three factors performed on

the signed confidence ratings yielded significant main effects of prior investment,

Table 2

Mean signed confidence ratings and percentages of decisions to continue investments related to decision

goal (Experiment 1)

Prior

investment

Prior

return

Current

investment

Expected

return

Gain-maximization

goal

Loss-minimization

goal

M (%) M (%)

�5.5 0 �4.5 2.0–5.0 �45.46 20.8 �67.50 4.2

�2.2 0 �4.5 2.0–5.0 �53.13 8.3 �58.75 12.5

�5.5 7.7 �4.5 2.0–5.0 �3.21 50.0 �14.17 37.5

�2.2 7.7 �4.5 2.0–5.0 34.96 66.7 �21.25 37.5

�5.5 0 �2.5 2.0–5.0 �8.58 50.0 �10.21 45.8

�2.2 0 �2.5 2.0–5.0 9.33 58.3 �18.49 39.1

�5.5 7.7 �2.5 2.0–5.0 54.00 87.5 47.92 79.2

�2.2 7.7 �2.5 2.0–5.0 66.67 91.7 69.79 91.7


F ð1; 44Þ ¼ 4:96, p < 0:05, of prior returns, F ð1; 44Þ ¼ 42:18, p < 0:001, and ofthe expected value, F ð1; 44Þ ¼ 51:96, p < 0:001. Overall participants were morelikely to continue to invest when the prior investments was lower (M ¼ 3:64) thanwhen it was higher (M ¼ �5:90), less likely to continue to invest when there had beenno prior returns (M ¼ �31:60) than when there had been prior returns (M ¼ 29:34),and less likely to continue to invest when expected value was negative (M ¼ �28:56)than when the expected value was positive (M ¼ 26:30).Suggesting different effects of prior and expected outcomes on gain-maximizing

and loss-minimizing participants, the interaction between decision goal, prior in-

vestment, prior returns, and expected value reached significance, F ð1; 44Þ ¼ 9:10,p < 0:01. As Table 2 shows, gain-maximizing participants were in general morelikely to continue investments than were loss-minimizing participants. This is in par-

ticular true for a negative expected value when there were prior returns. In fact, onlyunder these conditions escalation is observed. On the other hand, when the expected

value was positive and there were no prior returns, de-escalation is demonstrated for

the loss-minimizing participants. The four-way interaction was furthermore modified

by the responsibility instructions, F ð1; 44Þ ¼ 5:69, p < 0:05. No interpretation canhowever be offered.

Separate ANOVAs yielded at p ¼ 0:05 significant main effects of prior returns andexpected value for loss-minimizing participants, whereas all three within-subject fac-

tors were significant for gain-maximizing participants. Only in the latter groups, theinteraction between prior investment, prior returns, and expected value was signifi-

cant.

2.3. Discussion

The results did not bear out the prediction that a sunk outcome would have an

effect only when the decision goal is to minimize losses. Unexpectedly, there was also

an effect of sunk outcome when participants maximized gains. No or only small dif-ferences due to the responsibility instructions were furthermore observed.

Although the decision goal did not have the expected effect, it was found to be

important for the investment decisions. Gain-maximizers and loss-minimizers ap-

peared to process sunk outcomes differently. For loss-minimizers the important fea-

ture of the sunk outcome was whether it was positive or negative, i.e., whether there

had been any prior returns or not. In contrast, for gain-maximizers the level of prior

investments and the interaction between prior investments, prior returns, and ex-

pected value also affected the investment decisions. Possibly, as expected from theloss-sensitivity principle (G€aarling et al., 1997), it was important for the loss-minimiz-ers whether or not a sunk outcome buffers possible future losses. On the other hand,

the unexpected effect of sunk outcome in the gain-maximizing group may be due to

the fact that prior investments and returns were used to forecast future gains. More

specifically, a higher return for a lower investment may signal more future profits in

the project and therefore lead to continued investments even when the expected value

is negative.


3. Experiment 2

If the gain-maximizing participants in Experiment 1 used information about prior

returns to forecast future returns, then deleting this information should reduce or

eliminate the effect of sunk outcome in these participants. This was tested in Exper-iment 2 by only presenting information about prior investments (sunk costs).

Since the responsibility instructions were involved in a higher-order interaction in

Experiment 1 and thus may have had some effect, these instructions were again var-

ied as a between-subject factor. The decision goal was varied as a within-subject fac-

tor to increase statistical power. The predictions were the same as in Experiment 1.

3.1. Method

3.1.1. Participants

Another 38 undergraduates at G€ooteborg University participated on a voluntarybasis. They received the equivalent of $6 in payment. None of them had studied eco-

nomics or business administration for more than one semester. Their mean age was

26.4 years (ranging from 19 to 46 years). An equal number of participants, half of

them men and half of them women, was randomly assigned to two groups who were

either given responsibility instructions or not.

3.1.2. Procedure

Individually serving participants made eight independent investment decisions de-

scribed in scenarios presented on the computer screen. The instructions were essen-

tially the same as in Experiment 1.

The scenarios were those used in Experiment 1 for which there were no prior re-

turns (see Table 2). As a consequence, large vs. small sunk cost (SEK 2.2 millions vs.

SEK 5.5 millions) was crossed with positive vs. negative expected value (current in-

vestment equal to SEK 2.5 millions vs. SEK 4.5 millions for the same expected re-turns).

Participants were presented with both gain-maximizing and loss-minimizing sce-

narios. Half of the participants were first presented the former, then the latter.

The order was reversed for the other half of the participants. The presentation order

was otherwise randomized. A session lasted for about 15 min after which partici-

pants were debriefed and paid.

3.2. Results and discussion

Table 3 displays the results averaged across order and responsibility instructions

which did not yield any significant effects. As may be seen, both the signed confi-

dence ratings and the percentages of decisions to continue indicate that participants

were more likely to continue investments when the expected value was positive than

when it was negative. A 2 (responsibility vs. no responsibility instructions) by 2

(gain-maximization vs. loss-minimization decision goal) by 2 (high vs. low sunk cost)

by 2 (positive vs. negative expected value) mixed factorial ANOVA with repeated


measures on the last three factors performed on the signed confidence ratings yielded

a significant main effect of expected value, F ð1; 38Þ ¼ 145:04, p < 0:001. For a largesunk cost participants were less likely to continue than for a small sunk cost, al-

though the effect did not reach significance, F ð1; 38Þ ¼ 2:82, p ¼ 0:10. Substantiatedby a significant interaction between sunk cost and expected value, F ð1; 38Þ ¼ 4; 54;p < 0:05, this effect was stronger for a positive than for a negative expected value.Consistent with the decision goal, with loss-minimizing instructions participants

were overall less likely to continue investment than with gain-maximizing instruc-

tions, F ð1; 38Þ ¼ 6:25, p < 0:05. The two-way interaction between the decision goaland sunk cost was marginally significant, F ð1; 38Þ ¼ 4:09, p ¼ 0:05, indicating, con-trary to the hypothesis, that the sunk cost effect was stronger when participants max-

imized gains than when they minimized losses.

Separate ANOVAs for the two decision goals only yielded a significant effect ofsunk costs at p ¼ 0:05 when participants maximized gains. Furthermore, only thenthe effect of the expected value and the interaction between expected value and sunk

cost were significant. In contrast, when loss was minimized, only the effect of the ex-

pected value was significant.

It should be noted that the effect of sunk cost was opposed to the one usually re-

ported (e.g., Arkes & Blumer, 1985; Staw, 1976), i.e., when participants faced a lar-

ger sunk cost they were more likely to discontinue investment than when they faced a

smaller sunk cost. It is therefore still possible that the sunk cost was used to forecastfuture returns.

4. Experiment 3

In Experiment 2, contrary to the predictions it was found that when participants

maximized gains they were more affected by sunk costs than when they minimized

losses. It is still possible that this result was due to the fact that when maximizinggains participants used information about sunk costs to forecast future returns.

Whether such was the case in Experiment 3 was tested by asking participants to state

how large they expected the future returns would be for each scenario.

Most studies on escalation have been conducted with undergraduates making

fictitious investment decisions involving large amounts of money. Since the main

objective of the present research is to investigate the impact of the decision goals

Table 3

Mean signed confidence ratings and percentages of decisions to continue investments related to sunk cost,

expected value, and decision goal (Experiment 2)

Sunk cost Expected value Gain-maximization goal Loss-minimization goal

M (%) M (%)

High Negative �42.38 20.0 �69.28 5.0

Low Negative �37.50 30.0 �67.72 8.0

High Positive 19.13 65.0 13.63 63.0

Low Positive 55.25 83.0 23.63 70.0


of minimizing losses or maximizing gains, it is important that participants can imag-

ine how it would feel if their decisions result in future losses or gains. In debriefing

participants in Experiment 2, some expressed that they had difficulties in imagining

the large amounts of money entailed by the scenarios. This might have affected their

involvement in the task, and their thoughts about costs and benefits may have beendifferent if these had been easier to relate to their own economy. In Experiment 3 the

investment scenarios were therefore brought closer to the economic realities of the

participants who were asked to imagine that the decisions concerned their own pri-

vate economy and the money amounts were much lower. As in the preceding exper-

iments, the hypothesis was that when the decision goal is loss-minimization, sunk

costs are taken into account to a greater extent than when the decision goal is

gain-maximization.

Besides making the investment scenarios personal and lowering the amounts, Ex-periment 3 also investigated whether participants process sunk costs differently de-

pending on the level of money amounts involved. Romanus et al. (1996) found that

prior outcomes had a greater impact if the choices involved higher stakes than if

the stakes were lower. They suggested that higher stakes make people more sensitive

to losses. In line with this, it is predicted that sunk costs are taken into account to

a greater extent when the decisions involve higher amounts than when they involve

lower amounts. Sunk costs are thus predicted to have the least impact for low level

of amounts and for the gain-maximizing group. The decision goal was varied betweensubjects in order to reduce the number of scenarios presented to each participant.

4.1. Method

4.1.1. Participants

Another 28 undergraduates at the G€ooteborg University participated on a volun-tary basis. They received the equivalent of $6 in payment. None of them had studied

economics or business administration for more than one semester. Their mean agewas 25.2 years (range 19–42 years). An equal number, half of them men and half

of them women, was randomly assigned to two groups. Participants in one group re-

ceived instructions to maximize gains, in the other group to minimize losses.

4.1.2. Procedure

The procedure was the same as in Experiments 1 and 2 except that the scenarios

were altered. Participants were instructed to imagine that they had started a project

based on their own business idea. They were further told that all investments in theproject were made with their own money. They decided whether they wanted to con-

tinue or discontinue investments. In each scenario participants with the loss-minimi-

zation goal were asked to imagine that their future financial situation was insecure so

that minimizing losses was an important goal. Participants with the gain-maximiza-

tion goal were asked to imagine that their future financial situation was secure so

that there was no reason to be concerned about possible losses.

The scenarios were presented at a low and high level of amounts. For the low level,

low and high sunk costs (SEK 2000 vs. SEK 10000) were crossed with positive and


negative expected values (i.e., with expected returns ranging from SEK 3000 to SEK

9000, and with a current investment equal to SEK 4000 vs. SEK 8000). Likewise, for

the high level, low and high sunk costs (SEK 16 000 vs. SEK 80 000) were crossed with

positive and negative expected value (i.e., with expected returns ranging from SEK

30 000 to SEK 60 000, and with a current investment equal to SEK 32 000 vs. SEK58 000).

Participants responded to each scenario by indicating whether they would con-

tinue investments or not and how confident they were in the decision. In addition,

they were asked to estimate how much they expected in returns by typing a number

within the given range.

A session lasted for about 15 min after which participants were debriefed and

paid.

4.2. Results and discussion

Table 4 displays the mean signed confidence ratings, percentages of decisions to

continue, and estimates of expected returns. The numbers in Table 4 are averaged

across the level of amounts since this factor did not significantly affect the results.

Two participants were discarded because they stated expected returns that were out-

side the defined ranges.

As may be seen, participants in both groups were more willing to continue invest-ment for a positive than for a negative expected value. A 2 (gain-maximization vs.

loss-minimization decision goal) by 2 (low vs. high level of amounts) by 2 (positive

vs. negative expected value) by 2 (low vs. high sunk costs) mixed factorial ANOVA

with repeated measures on the last three factors performed on the signed confidence

ratings yielded a significant main effect of expected value, F ð1; 24Þ ¼ 60:32, p <0:001. Substantiated by a significant interaction between expected value and sunkcost, F ð1; 24Þ ¼ 8:09, p < 0:01, the effect of sunk cost was larger for a negative thanfor a positive expected value. There was also a significant main effect of decisiongoal, F ð1; 24Þ ¼ 8:10, p < 0:01. The gain-maximizing participants continued to in-vest to a greater extent than did the loss-minimizing participants.

In separate ANOVAs at p ¼ 0:05 only the expected value affected gain-maximiz-ing participants’ decisions to continue. For loss-minimizing participants, there was a

Table 4

Mean signed confidence ratings, percentages of choices to continue investments, and mean estimated fu-

ture returns (in 1000 SEK) related to sunk cost, expected value, and decision goal (Experiment 3)

Sunk

costs

Expected

value

Gain-maximization goal Loss-minimization goal

Investment decision Estimated

future re-

turns (M)

Investment decision Estimated

future re-

turns (M)M (%) M (%)

High Negative �16.6 45.8 24.4 �40.0 25.0 26.0

Low Negative �35.6 20.8 24.8 �80.5 3.6 24.2

High Positive 57.5 91.7 27.8 18.0 64.3 24.5

Low Positive 54.7 91.7 26.0 30.7 75.0 27.2


significant effect of expected value and a significant interaction between expected va-

lue and sunk costs. When the expected value was positive, the loss-minimizing par-

ticipants continued to invest to a larger extent when the sunk cost was low than when

it was high. When the expected value was negative, they continued to invest to a lar-

ger extent when the sunk cost was high than when it was low. These results differedfrom the results of the two previous experiments in which the gain-maximizing par-

ticipants were affected by the interaction between sunk costs and expected value and

the loss-minimizing participants were affected only by expected value.

The results of Experiment 3 cannot be explained by differences in the estimates of

future returns. When controlling for these in an analysis of covariance (ANCOVA),

the significant ANOVA effects remained. Furthermore, refuting that sunk cost af-

fects estimates of expected returns, no significant effects were observed on the ratings

of expected returns.

5. General discussion

The present research showed clearly that people take sunk outcomes, that is, prior

gains and losses, into account in investment decisions although such outcomes

should be ignored. Furthermore, in line with recent research (Heath, 1995), it was

found that people may both continue (escalate) and discontinue (de-escalate) in re-sponse to sunk costs. A consistent finding was nevertheless that expected value had

the strongest effect. In order to understand escalation, it may therefore be insufficient

to only consider the reasons for why people are affected by sunk costs. An approach

that needs to be pursued is to investigate the more general phenomenon of how and

why people weigh information about prior and future gains and losses (G€aarlinget al., 1997). Heath’s (1995) rate-of-return hypothesis is one such attempt that cannot

however account for the present results. This hypothesis wrongly predicted that par-

ticipants would invariably discontinue investments in Experiment 2 and 3.In all three experiments, the instructions to maximize gains made participants

more confident in continuing investment compared to loss-minimization in-

structions. As a consequence, more participants continued investment for a negative

expected value when the goal was to maximize gain, and more participants discon-

tinued investments for a positive expected value when the goal was to minimize

losses. Hence, the decision goal appears to have an effect on how likely people will

be to escalate as well as to de-escalate. The main objective was, however, not to in-

vestigate this overall effect of decision goal but its interaction with sunk outcomes.Unexpectedly, in Experiments 1 and 2, the manipulation of sunk cost had a greater

impact on the investment decisions when the goal was to maximize gain than when it

was to minimize losses. A reason for this may be that gain-maximizing participants

used information about prior returns and sunk costs to forecast future returns. In

line with this, in Experiment 3 when participants estimated future returns, the results

were in line with the prediction in that sunk cost had a greater impact on the invest-

ment decisions made by loss-minimizing participants than by gain-maximizing par-

ticipants. By asking participants to estimate their expected returns themselves, they


were perhaps less likely to use the sunk cost information to forecast future returns.

Also possibly accounting for the difference in results was that the decisions con-

cerned participants’ private economy rather than the economy of a company. For

this reason, the losses may have been more salient.

Nevertheless, it cannot unequivocally be concluded from the present series of ex-periments that people take sunk costs into account to a greater extent when making

decisions that are motivated by loss minimization. What may be concluded, how-

ever, is that the goal of the decision has an impact on how sunk costs influence

investment decisions. The results furthermore did not support the fact that respon-

sibility instructions induce loss minimization since no or only weak effects of respon-

sibility were observed. The failure to find whether responsibility instructions

are necessary for obtaining a sunk cost effect is not an isolated finding (Conlon &

Garland, 1993; Karlsson et al., 2002).Escalation has been referred to as ‘‘the human tendency to judge options accord-

ing to the size of previous investments rather than the size of expected returns’’ (Ay-

ton & Arkes, 1998, p. 40). The main conclusion to be drawn from the present

research is however that expected returns are a more important determinant of the

choices than are sunk costs. A reason for this may be that in the present experiments

both expected returns and opportunity costs were explicit (although not specified

with certainty). Still, specifying the expected returns did not eliminate the effect of

sunk costs as rational decision making dictates it should. Thus, both the past andthe future have an influence. Furthermore, 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 of which

escalation appears to be a special case.

Acknowledgements

We would like to thank Anders Biel and an anonymous reviewer for comments.

The research was financially supported by grant # #98-0131 from the Bank of Swe-

den Tercentenary Foundation.

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Impact of decision goal on escalation