JOURNAL OF APPLIED BEHAVIOR ANALYSIS

A SEQUENTIAL LEARNING ANALYSIS OF DECISIONS INORGANIZATIONS TO ESCALATE INVESTMENTS DESPITE

CONTINUING COSTS OR LOSSES

SONIA M. GOLTZUNIVERSITY OF NOTRE DAME

Reinforcement processes may underlie decisions frequently found in organizations to escalate in-vestments of time, money, and other resources in strategies (e.g., product development, capitalinvestment, plant expansion) that do not result in immediate reinforcers. Whereas cognitive biaseshave been proffered in previous explanations, the present analysis suggested that this persistence isa form of resistance to extinction arising from experiences with past investments that were variablyreinforced. This explanation was examined in two experiments by varying the pattern of returnsand losses subjects experienced for investment decisions prior to experiencing a series of losses.Consistent with the proposed explanation, two conditions resulted in higher levels of recommitmentduring continuous losses: (a) training using a variable schedule of partial reinforcement, and (b) notraining on the task. Results indicate that behavior analysis can be used to understand and controlsituations in organizations that are prone to escalation, such as investments in the research anddevelopment of new product lines and extensions of further loans to customers.DESCRIPTORS: behavior analysis, business problems, extinction, generalization, schedules of

reinforcement

These headlines share a theme: "Knowing theRight Time to Bail Out of a Mutual Fund" (Clem-ents, 1991); "Letting the Losses Run" (Wechsler,1989); "Entrepreneur Remains Undeterred byVenture's Failure" (Gupta, 1989); "How Wash-ington Got Stuck in the Mud of Nicaragua" (Wei-ner, 1988); and "RJR Nabisco Abandons 'Smoke-less' Cigarette" (Waldman, 1989). As evident inthe stories beneath these headlines, they refer tosituations involving long-term investments that havefailed or incurred costs. For example, "The failure

Parts of this article are based on the author's doctoraldissertation, performed under the supervision of HowardWeiss at Purdue University. Thanks also go to Bob Baron,Mike Bowen, John Capaldi, Alice Eagly, Mary Kay Steven-son-Busemeyer, Bob Vecchio, and several anonymous re-viewers for their helpful comments; James Northey, Jr., forcomputer expertise; and Rob Acker, Michelle Blakeslee, DiannLaughner, Tim Price, Mike Scaggs, Kendall Tilton, RobertWojcik, and Andy Wysong for help in data collection.

The first experiment was presented at the 96th annualconvention of the American Psychological Association, At-lanta, August 1988. The second experiment was presentedat the ORSA/TIMS Joint National Meeting, Denver, Oc-tober 1988.

Correspondence regarding this article should be addressedto Sonia Goltz, Department of Management, University ofNotre Dame, Notre Dame, Indiana 46556.

is one of the biggest and most expensive new-product flops in decades. The cigarette, which hadtaken nearly a decade to research and develop . . ."(Waldman, 1989); "Seragen has become a finan-cial black hole, swallowing up some $50 millionin university funds and threatening to soak up $100million more before the leukemia treatment beginsto pay off, if indeed it ever does" (Wechsler, 1989);"After years of bloody conflict in America's ownbackyard, billions of dollars of U.S. military aid,and a near constitutional crisis in Washington, it'sstill a foreign policy morass" (Weiner, 1988).

Although the topic of recommitment by indi-viduals in organizational settings to costly coursesof action is not generally found in the field ofbehavior analysis, it has intrigued researchers ineconomics, social psychology, and organizationalbehavior, generating a substantial body of literature(see Brockner & Rubin, 1985, and Staw & Ross,1987, for reviews). Three factors characterize thedilemma of interest: (a) an initial investment ofresources in a course of action by the decision-makerthat results in losses or costs; (b) some degree ofcontinuity over time of the decision dilemma; and(c) unknown consequences for withdrawal from thesituation and for persistence in the course of action

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SONIA M. GOLTZ

(Staw & Ross, 1987). Most studies indicate thatcontinued investing, rather than withdrawal, is theresponse that frequently occurs in this type of sit-uation (Brockner & Rubin, 1985; Staw & Ross,1987); thus, the behavior of concern has been de-fined as "a propensity to increase one's resourceallocation following an initial setback" (Conlon &Wolf, 1980, p. 172). This behavior has been var-iously termed escalation of commitment, entrap-ment, and sunk cost (each term being used pri-marily in a particular academic area; e.g., sunk costin economics and entrapment in social psychology).For purposes of the present investigation, the termthat is used most often in the organizational psy-chology literature-escalation of commitment-will be used here.Many proposed explanations of escalation have

speculated that it results from cognitive biases. Forexample, the "self-justification" explanation assertsthat people are trying to protect themselves from"psychological costs" associated with failure (Staw,1976; Staw & Fox, 1977; Staw & Ross, 1978;Teger, 1980). The "reactance" explanation statesthat individuals are responding to failure as if itwere a restriction in one's freedom to achieve desiredoutcomes (Staw & Ross, 1978); the "framing"explanation suggests that the decision situation trig-gers risk-seeking rather than risk-averse behavior(Arkes & Blumer, 1985; Northcraft & Neale,1986). The most well-tested of these explanations,self-justification, has received mixed support (e.g.,Davis & Bobko, 1986; Staw & Ross, 1978), andall three explanations can be criticized for treatingescalation as a decision error using a retrospectiveanalysis rather than viewing escalation as an adap-tive response to very uncertain circumstances (Bow-en, 1987).One basis for viewing escalation as an adaptive

response is the possibility that intermittent rein-forcement underlies some escalation effects (Staw& Ross, 1978). Although this possibility has beenacknowledged, an explanation based upon the in-dividual's reinforcement history has not been de-veloped or validated systematically (Staw & Ross,1987). The present analysis of escalation incor-porated the partial-reinforcement extinction effect

and other concepts from the nonhuman and humanlearning literatures in an effort to examine whetherescalation can be explained and predicted usingoperant principles.

A Learning-Based Analysis of a TypicalNew Investment Situation

Allocation responses made by individuals can beviewed as economic behaviors that, as Kagel andWinkler (1972) suggested, are analyzable usingexperimental and applied behavior-analytic meth-ods. One behavior analysis of escalation in humanallocation responses has been offered by Platt (1973),who posits the operation of immediate individualreinforcers (e.g., profits for military industrial com-plexes from selling arms) rather than long-termgroup reinforcers (e.g., lower national expenses andreduction in world terror because of disarmament)as being instrumental in influencing this type ofrecommitment behavior. However, as described be-low, several other principles found in the learningliterature can be used to analyze allocation situationsand behaviors.

In the typical new investment situation, and es-pecially in the prototypical escalation experiment(e.g., Staw, 1976), individuals (or groups of in-dividuals) have the opportunity to allocate money,time, or other resources in a course of action aboutwhich they have limited information and for whichno appropriate behaviors have been developed orprescribed. For example, at the time the ideas forsmokeless cigarettes and seragen were initially de-veloped, it is likely that their market niches andpotential costs and benefits were uncertain and spec-ulative at best. Therefore, it would have been justas appropriate to choose not to pursue these ideasany further (e.g., not invest in market and devel-opment research) as it was to choose to pursuethem. Subjects may, in this situation of limitedavailable information, generalize responses learnedin prior investment-related situations (Skinner,1965). With regard to the aforementioned situa-tions reported in the news, this analysis suggeststhat the responses being described were probablymuch the same as those developed previously tostimuli such as past "product ideas," past requests

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for military aid, and past advertisements of mutualfunds.

The question then arises as to what these learnedresponses are and how they were developed. State-ments such as "only one in ten such drugs ever

receives final FDA approval for commercial sale"(Wechsler, 1989), "where investment returns vary

widely" (Clements, 1991), and "he once hit thejackpot as an entrepreneur" (Gupta, 1989) implyexperiences of partial schedules of reinforcement forinvestments. It is possible that most individualshave experienced for most past investments a vari-able schedule of partial reinforcement (Ferster &Skinner, 1957) and that, because of this experience,nonreinforcement operates as a discriminative stim-

ulus for forthcoming positive outcomes, as pro-

posed in the sequential hypothesis of the partial-reinforcement extinction effect (Capaldi, 1966). Asa result, continued investing in the face of non-

reinforcement or failure could be a manifestationof the partial-reinforcement extinction effect (Am-sel, 1967). Evidence that persistence resulting froma history of partial reinforcement generalizes to new

situations (Eisenberger, Carlson, & Frank, 1979;Eisenberger, Heerdt, Hamdi, Zimet, & Bruck-meir, 1979) makes this analysis more credible.Some subjects' behavior may be based on rule

following rather than on direct generalization. Rulefollowing arises from the shared dass membershipof stimuli in the novel setting and elements of therule (Hayes, Thompson, & Hayes, 1989). The ruleapplied in these instances has been derived froman individual's actual history with investment-likesituations, which was variable in its pattern of re-

turns. Thus, the behavioral effect is similar to thatexpected with direct generalization (i.e., continuedinvesting in the face of nonreinforcement). Theadvice "to just buy and hold a mutual fund"(Clements, 1991) is an example of a rule that maybe founded upon a history of variable partial re-

inforcement for investing.

A behavior analysis for allocation situations, suchas the one offered above, can generate testable pre-

dictions. One area in which predictions can be de-rived and tested concerns allocation responses dur-ing a period of continuous losses following training

on a task using differing schedules ofreinforcement.For example, one expects that a variable scheduleof returns presented during training on an invest-ment task will result in higher allocations duringlater continuous losses than a fixed schedule ofreturns presented during training (either in termsof continuous returns or a regular pattern of returnsand losses). This prediction was the focus of in-vestigation in the first experiment.

Another area of potential investigation basedupon the present analysis concerns individuals' gen-eralization of reinforcement histories or applicationof rules to investment situations associated with noclear history or prescribed rules. For example, ifone assumes that individuals do not generalize anyhistory of reinforcement to a novel investment sit-uation, one might expect that subjects exposed im-mediately to a series of losses with no previoustraining on an investment task will persist only fora brief duration; in other words, they will behavemore like subjects trained with a fixed or continuousschedule of reinforcement than like subjects trainedwith a variable schedule. On the other hand, as-suming that responses arise from rules or behaviorslearned in previous situations associated with a vari-able schedule of reinforcement (as proposed in thepresent analysis) suggests a different set of expec-tations. One would predict that subjects experi-encing no training with a task will respond moresimilarly to subjects trained on a variable reinforce-ment schedule than to subjects who have experi-enced a fixed schedule of returns (continuous re-turns or a regular pattern of returns and losses).The second experiment, in addition to examiningthe replicability of results of the first experiment,examined this prediction.

EXPERIMENT 1

METHOD

SubjectsOne hundred sixty-four students enrolled in an

introductory psychology course at Purdue Univer-sity chose to participate in this study for partialcourse credit.

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Table 1Monetary Feedback Per Trial During Acquisition for

Experiment 1 (in Terms of Dollar Amount Gained or Lostfor Every $100 Invested)

Con- Con- Con-tinuous Partial Partial tinuous tinuous

Trial small fixed variable large short

1 +10 -10 -10 +30 +302 +10 +30 +30 +30 +303 +10 -10 +30 +30 +304 +10 +30 -10 +30 +305 +10 -10 -10 +30 +306 +10 +30 -10 +30 +307 +10 -10 +30 +30 +308 +10 +30 -10 +30 +309 +10 -10 +30 +30 -1010 +10 +30 +30 +30 -1011 +10 -10 -10 +30 -1012 +10 +30 -10 +30 -1013 +10 -10 +30 +30 -1014 +10 +30 -10 +30 -1015 +10 -10 +30 +30 -1016 +10 +30 +30 +30 -10

Task

The task induded the aforementioned factorsthat characterize a situation with potential for es-

calation (Staw & Ross, 1987). Each subject per-

formed a dynamic investment decision task on a

computer. To influence students to earn as muchas possible with their responses, subjects were toldthey were being "entrusted" with a predeterminedamount of "money" to "manage" ($10,000 per

decision period) and would be asked to explain thehandling ofthe money at the end ofthe experiment.Similar to tasks used in past investigations of es-

calation (e.g., Staw & Fox, 1977), the subject couldallocate any portion of the money (from $0. to

$10,000, in increments of $100) to a given alter-native (in this case a "stock," which could resultin gains or losses) and reserve any portion of it foranother use (in this case a "money market fund"that did not earn or lose money).

After each trial, the subject received informationfrom the computer concerning the dollar gain or

loss per $100 invested in the stock (e.g., "Invest-ment in the stock during this period resulted in a

gain of $30 per $100 invested"). The particulardollar amount reported to the subject dependedupon the condition to which he or she was assigned

(see Table 1). The task took place during one 20-min experimental session and continued for 32trials (16 acquisition trials and 16 extinction trials).After the last trial, the subject was informed of thetotal dollar amount he or she had gained or lostduring the experiment. (Subjects were not told atthe beginning of the experiment how many trialswould occur or how long the session would last.)

ProcedureEach subject was assigned randomly to one of

the five conditions defined below. Experimentersincluded the author and seven trained undergrad-uate students. After each subject read an instructionsheet that explained the task, the experimentershowed him or her a demonstration trial on thecomputer that required the subject to respond withan investment amount. During the demonstration,the experimenter reiterated that investments in thestock could result in losses or gains, and that al-locations made to the money market fund wouldnot result in any gains or losses. The experimenterthen answered any remaining questions and left theroom.

After performing the task, each subject com-pleted a questionnaire that posed general questionsconcerning thoughts and strategies during the ex-periment and assessed speculations as to the ex-perimental hypotheses. Finally, the subject was de-briefed and thanked.

Dependent MeasureThe dollar amounts subjects chose as additional

allocations to the stock alternative were examinedfor escalation during the period ofcontinuous losses,in which all subjects received a loss of $10 per$100 invested in the stock regardless of condition.Dollar amount invested during this phase, whichcould range from $0 to $10,000 per trial, servedas the dependent variable.

DesignA repeated measures analysis of variance (ANO-

VA) was applied, in which the independent variablewas the reinforcement schedule presented duringacquisition and the dependent variable was theamount invested during extinction. The following

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2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Acquisition TrialsFigure 1. Average amounts invested during acquisition in Experiment 1. Fixed: partial returns-fixed schedule; variable:

partial returns-variable schedule; Cont.-Large: continuous returns-large magnitude; Cont.-Small: continuous returns-smallmagnitude; Cont.-Short: continuous returns-short training.

five reinforcement schedules were used: (a) contin-uous returns-small magnitude; (b) partial returns-fixed schedule; (c) partial returns-variable schedule;(d) continuous returns-large magnitude; and (e)continuous returns-short training. This design re-sulted in a 5 (Groups) by 12 (Trials) ANOVA.The monetary feedback per trial for each conditionduring acquisition is displayed in Table 1.

The partial returns-fixed schedule (n = 33), thepartial returns-variable schedule (n = 32), and thecontinuous returns-large magnitude (n = 32) con-ditions were established to examine directly theexpectation that a variable schedule of returns pre-sented during training would result in higher al-locations during a later period of continuous lossesthan either a fixed partial schedule or a continuousschedule. The remaining conditions controlled forplausible alternative explanations such as magni-tude, duration, and return rate. For example, bothpartial groups had the same rate (50%) and amount($2,400) of return as the continuous return-shorttraining group. In addition, variables that previ-ously have been found to affect escalation were kept

constant. (For instance, all subjects were informedthat outcomes were contingent on amounts investedand that they would be asked to explain theirhandling of the money at the end ofthe experiment.Also, the framing of the decision situation was thesame for all conditions in that all subjects werepresented with identical instructions both orally andon the computer.)

REsuLTsManipulation CheckTo determine whether the contingencies differ-

entially affected investing during training on thetask, the dollar amounts invested during Trials 2through 17 (i.e., acquisition) were examined. Arepeated measures ANOVA indicated the existenceof a significant main effect of condition, F(3, 129)= 25.7, p < .001. A significant interaction effectof trial by condition was also found, F(45, 1935)= 13.6, p < .001. A visual examination of thedata (see Figure 1) revealed that subjects respondedin patterns characteristic of schedule-controlled be-havior. Variably reinforced subjects invested con-

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SONIA M. GOLTZ

1 2 3 4 5 6 7 8 9 10 11 12

Extinction TrialsFigure 2. Average amounts invested during extinction in Experiment 1. Abbreviations as in Figure 1.

servatively at a steady rate throughout acquisition;continuously reinforced subjects increased their in-vestments substantially during acquisition; andsubjects receiving a fixed schedule of returns ex-

hibited alternating patterns of large and small in-vestments.

Recommitment over Time

To be consistent with the perspective that es-

calation is a dilemma that occurs over time (Staw& Ross, 1987), the first 12 trials after the changein contingencies (i.e., from acquisition to extinction)

were analyzed. (Analyses were limited to 12 trialsto enable the use of paired comparisons, as ex-

plained later.)For the continuous returns-small magnitude,

partial returns-variable schedule, and continuousreturns-large magnitude conditions, contingenciesshifted with a loss following subjects' responses on

the 17th trial of the experiment. Therefore, re-

sponses beginning with Trial 18 and continuingthrough Trial 29 were analyzed for escalation. Sim-ilarly, because subjects in the partial returns-fixedschedule condition were introduced to the changein contingencies following the loss on Trial 18,Trials 19 through 30 were examined for escalationeffects. Because subjects in the continuous returns-

short training condition encountered the initial lossafter their responses on Trial 9, their performanceson Trials 10 through 21 were assessed.An examination of Figure 2 suggests that mean

dollar amounts invested during the first 12 trialsofextinction decreased almost immediately and quitesubstantially for all conditions except the partialreturns-variable schedule condition, in which themeans decreased at a much slower rate. A repeatedmeasures ANOVA confirmed the existence of an

Extinction Trial by Condition interaction, F(44,1738) = 4.5,p < .001. Because of this interaction,post hoc paired comparisons were conducted on the

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A Cont-Shorto Cont-Small

* Cont-Largeo Fixed

* Variable

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data using four blocked sets of three trials each inorder to identify behavior patterns. (Trials occurringat the end of the experiment that did not form aset of three for a blocked trial were omitted so thatequivalent numbers of equally blocked trials couldbe used for each condition i.e., three trials in thefirst three conditions mentioned above, two trialsin the fourth, and 11 trials in the fifth.) Thesecomparisons indicated that the amount invested bysubjects in the partial returns-variable schedulecondition was significantly higher than each of theother conditions during all blocked periods exceptfor the first and fourth periods, during which itwas not significantly higher than the partial returns-fixed schedule condition. Paired comparisons alsorevealed that the partial returns-fixed schedule con-dition differed significantly on amount invested fromthe continuous returns-short training conditionduring the first blocked period (p < .05 for allsignificant comparisons). No other pairwise differ-ences were significant.

In 11 ofthe 12 trials, the partial returns-variableschedule condition was found to contain the largestpercentage of subjects investing some money in thestock alternative (i.e., $100 or more). This wassignificant according to a Friedman two-way anal-ysis of variance by ranks, X2(4) = 31.3, p < .001.(Descriptive statistics for subjects who invested ineach of the extinction trials can be obtained fromthe author.)

Immediate RecommitmentDespite the suggestion that escalation is a dilem-

ma that occurs over time (Staw & Ross, 1987),much of past empirical research on escalation hasdiscussed escalation primarily by focusing on re-sponses occurring immediately prior to and im-mediately subsequent to one failure experience.Consequently, a repeated measures ANOVA wasalso conducted on responses immediately precedingthe first trial of extinction and responses immedi-ately following the first trial of extinction in orderto assess escalation. Thus, this analysis indudeddata from the first trial of the 12 extinction trialsexamined in preceding analyses as well as responsesgenerated on the trial immediately prior to the

Po.

09

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8000F

6000[

4000[

2000FA COUW.arto CuL.a* C414leo Fud* ~

Before AftrExtinction Trials

Figure 3. Average amounts invested before and after thechange in contingencies in Experiment 1. Abbreviations asin Figure 1.

change in contingencies. Specifically, Trials 18 and19 were analyzed for the partial returns-fixedschedule condition, Trials 9 and 10 were analyzedfor the continuous returns-short training condition,and Trials 17 and 18 were analyzed for each ofthe remaining three conditions.As seen in Figure 3, the partial returns-variable

schedule group was the only group that escalated,rather than decreased, investments over the courseof these two trials. Results of a repeated measuresANOVA confirmed a significant Trial by Conditioninteraction, F(4, 159) = 7.2, p < .001. Becauseof this interaction, post hoc paired comparisonswere performed to examine certain behavior pat-terns. Significant differences in amount investedoccurred between the partial returns-variableschedule condition and each of the other conditionsduring the trial before the initiation of extinctionbut not during the trial after the initiation of ex-tinction (p < .05 for all significant comparisons).Also, a paired comparison of responses before andafter the initial extinction trial within the partialreturns-variable schedule condition revealed thatthe increase in means was nonsignificant.

Allocations made on these two trials were alsoexamined in terms of between-group differences inpercentages of subjects increasing allocations, de-

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SONIA M. GOLTZ

creasing allocations, and investing the same amount.A larger percentage of subjects in the partial re-turns-variable schedule condition increased theirinvestments (3 7.5%), compared with 9.1% for thefixed schedule, 9.9% for the continuous returns-large magnitude condition, 13.9% for the contin-uous returns-small magnitude condition, and12.9% for the continuous returns-short trainingcondition. The relative numbers of individuals in-creasing investments, decreasing investments, andmaking equal investments across these trials werefound to be significantly different across conditionsin a chi-square test of independence, X2(8) = 26.4,p < .001. The moderate average change by subjectswho increased investments in the partial returns-variable schedule condition (M = $3,577, n =13), along with the high individual variability inamounts of increase (SD = $3,545), may explainwhy the amount invested did not increase signifi-cantly overall, although the percentage of subjectsincreasing investments was greater in this groupthan in other groups.

EXPERIMENT 2

METHOD

SubjectsParticipants in this study were 102 students en-

rolled in a principles of management class at theUniversity of Notre Dame who chose to completethe experimental task for extra credit.

DesignThe task, procedures, and dependent measures

were the same as in Experiment 1, except the fol-lowing four reinforcement schedules were used (a)partial returns-fixed schedule (n = 25), (b) partialreturns-variable schedule (n = 25), (c) continuousreturns-large magnitude (n = 28), and (d) notraining (n = 24). The first three conditions wereidentical to conditions in Experiment 1. In the no-training condition, subjects were not provided witha history of either continuous or partial returns forthis task. Instead, on each trial throughout theexperiment, these subjects received a loss of $10

per $100 invested (i.e., extinction began imme-diately). All four conditions were included to testthe prediction that subjects who have not beentrained on a task before experiencing a series oflosses will, like subjects who have been trained onthe task using a variable schedule of partial rein-forcement, allocate more during extinction thansubjects who have experienced a fixed schedule ofreturns (continuous returns or a fixed schedule ofpartial returns).

REsuLnSManipulation CheckTo determine whether the contingencies differ-

entially affected investing during acquisition, thedollar amounts invested during Trials 2 through17 were examined as in Experiment 1. Results weresimilar to those in Experiment 1, in that subjectsresponded in patterns characteristic of schedule-induced behavior. A repeated measures ANOVAindicated a significant main effect of Condition,F(2, 75) = 34.4, p < .001. A significant inter-action of Trial by Condition was also found, F(30,1125) = 8.7,p < .001.

Recommitment over TimeAs in the first experiment, the first 12 trials after

the change in contingencies (i.e., from acquisitionto extinction) were analyzed. The specific trials usedwere the same as in Experiment 1 for the threeconditions found in both experiments. For the no-training condition, Trials 2 through 13 were usedin the analysis because the first experience of theseries of losses occurred during the first trial.

Mean responses by condition for these 12 trialsare presented in Figure 4. A repeated measuresANOVA indicated the existence of an ExtinctionTrial by Condition interaction, F(33, 1078) = 3.2,p < .001. Because of this interaction, post hocpaired comparisons were conducted on the datausing four blocked sets of three trials each to explorebehavior patterns. These comparisons indicated thatthe amount invested in the partial returns-variableschedule condition was significantly higher than inthe no-training condition during the first blockedperiod and was significantly higher than in the

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1 2 3 4 5 6 7 8 9 10 11 12Extnction Trials

Figure 4. Average amounts invested during extinction in Experiment 2. Abbreviations as in Figure 1.

partial returns-fixed schedule and continuous re-

turns conditions during the second and fourthblocked trials (p < .05 for all significant compar-

isons). No other pairwise differences were signifi-cant.

When the percentage of subjects actually in-vesting $100 or more was calculated for each con-

dition in these 12 trials, the partial returns-variableschedule and no-training conditions contained sim-ilar percentages. When compared with the contin-uous returns and partial returns-fixed schedule con-

ditions, the no-training condition had more subjectsinvesting in 10 of the 12 extinction trials. A Fried-man two-way ANOVA by ranks showed this to

be significant, X2(2) = 18.5,p < .001. The partial

returns-variable schedule condition had more sub-jects investing than did the continuous returns andpartial returns-fixed schedule conditions for all 12trials; this was significant in the Friedman test,

X2(2) = 2 1.2, p < .001. (Descriptive statistics for

subjects who invested in each of the extinction trialsare available from the author.)

Immediate RecommitmentAs in Experiment 1, a repeated measures ANO-

VA was conducted on responses immediately pre-

ceding the first trial of extinction and responses

immediately following the first trial of extinction.The trials used in this analysis were the same as

those used in Experiment 1 for the conditions foundin both experiments. Trials 1 and 2 were used inthe analysis for the no-training condition.

As can be seen in Figure 5, the average invest-ment decreased substantially from the first trial ofextinction to the second trial of extinction for thecontinuous returns and partial returns-fixed sched-ule conditions but not for the no-training and par-

tial returns-variable schedule conditions. A signif-icant Extinction Trial by Condition interaction was

found in a repeated measures ANOVA, F(3, 98)

"0

0n

To

4-j

A No Training* Cont-Largeo Fixed

* Variable

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SONIA M. GOLTZ

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I? 8000

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1F

Before

Extinction TrialsFigure 5. Average amounts invested before and after the

change in contingencies in Experiment 2. Abbreviations as

in Figure 1.

= 6.7, p < .001. Post hoc paired comparisonsperformed on each of these trials to identify be-havior patterns indicated significant differences ininvestment amount between the partial returns-

variable schedule condition and the continuous re-

turns and partial returns-fixed schedule conditionsas well as between the no-training condition andthe continuous returns and partial returns-fixedschedule conditions on the trial before the initiationof extinction (p < .05 for all significant compar-

isons). Also, paired comparisons of responses beforeand after the initial extinction trial revealed thatthe increase in investment amount within the partialreturns-variable schedule condition was nonsignif-icant, as was the decrease within the no-trainingcondition.

As in the previous experiment, allocations were

also examined by studying between-group differ-ences in percentages of subjects increasing invest-

ments, decreasing investments, and investing thesame amounts across these two trials. Larger per-

centages of subjects in the partial returns-variableschedule condition and the no-training conditionincreased their investments (44% and 33.33%, re-

spectively), compared with 16% in the partial re-

turns-fixed schedule condition and 7.14% in the

continuous returns-large magnitude condition. Therelative numbers of individuals escalating, decreas-ing, and staying constant were found to be signif-icantly different across conditions in a chi-squaretest of independence, x2(6) = 13.59, p < .05.The moderate average change by subjects in thepartial returns-variable schedule condition who in-creased investments (M = $3,064, n = 11), alongwith the high variability in individual amounts ofincrease (SD = $2,768) in this group, may explainwhy the amount invested did not increase signifi-cantly overall, although the percentage that in-creased allocations was greater in this group thanin other groups. The small average change by sub-jects who increased investments in the no-trainingcondition (M = $875, n = 9, SD = $540) com-pared with the higher average change by subjectsin this group who decreased investments (M =

$980, n = 10, SD = $578) may explain why theamount invested did not increase significantly over-all, although the percentage who escalated was sub-stantially greater in this group than in the partialreturns-fixed schedule condition and the continu-ous returns-large magnitude condition.

DISCUSSION

The present investigation contributes to the lit-erature on escalation of commitment by demon-strating the utility of a learning-based analysis, aperspective in which escalation is viewed as an adap-tive response rather than as a dysfunctional behav-ior. The present analysis suggests that recommit-ment responses in the face of failure are based onthe larger context of a series of investment-likeexperiences rather than on the outcome of any oneinvestment experience. It may be that these re-sponses arise from a number of learning effects,including sequential learning and the partial-rein-forcement extinction effect. Varying the patterns ofoutcomes received during training on the task intwo separate experiments supported this explana-tion. Experiences with a variable schedule of returnsresulted in a greater degree of recommitment duringcontinuous losses than experiences with continuousor fixed returns. Furthermore, the lack of significant

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differences in responding among the continuouslyreinforced subjects in Experiment 1 (i.e., smallmagnitude, large magnitude, and short training)suggests that return rate, magnitude, and lengthof reinforcement history are factors that are not as

significant in producing escalation as is the se-

quential nature of the reinforcement history.The present analysis also suggests that, given no

direct experience with an investment situation, in-

dividuals generalize responses or rules learned dur-ing previous similar situations. Assuming that most

allocation situations are associated with a variableschedule of reinforcement, one would expect to see

persistence during a series of losses for investing.Results of the second experiment lend some support

to this explanation. Subjects not trained on the taskbefore experiencing continuous losses responded to

extinction more like those who had been trainedwith a variable schedule of returns than like thosewho had been trained with either continuous re-

turns or with a fixed schedule of returns.

Although subjects receiving no training with theinvestment task invested persistently, these subjectsdid not respond as similarly to subjects in the partialreturns-variable schedule condition as was expect-

ed. One possible explanation is that the no-trainingsubjects might have been generalizing a pattern thathad a smaller rate of return than did subjects inthe partial returns-variable schedule condition, whohad experienced a one-to-one ratio of returns to

losses for investment in the stock. Another expla-nation is that subjects' behavior is governed by a

rule that generates responses different from thoseexpected from direct generalization. Future inves-tigations might explore (a) what rates of returns

are encountered in different decision-making situ-ations (e.g., investing in research and development,buying stocks, etc.), (b) how and when these rates

are converted to rules, and (c) how direct gener-

alization and rule following differentially affect in-vestment decisions.

Results of the present investigation also indicatedthat escalation occurs over time. Many past esca-

lation investigations have reported between-groupdifferences on a second allocation decision only andhave not examined the significance of within-group

changes (e.g., Staw, 1976; Staw & Ross, 1978).However, the present investigation found more ev-idence of differences in recommitment behaviorsbetween groups when allocations made both im-mediately before and immediately after the firstexperience of a series of losses were compared thanwhen only allocations occurring after the initialexperience of extinction were examined. The dif-ference in results might be attributable to a differ-ence in methods. Previous studies on escalation(which usually consist of only two trials) have ar-tificially imposed the amount invested on the initialtrial (e.g., $10 million in Staw, 1976; $48 millionin Staw & Ross, 1978) for subjects in allconditions,only allowing them to choose in which of twoalternatives to invest the money. Only during thesecond trial are subjects given a dollar range fromwhich to choose (e.g., from $0 to $20 million inStaw, 1976; from $0 to $70 million in Staw &Ross, 1978).

The question of the meaningfulness of previousfindings of escalation is raised by results in thepresent investigation. Unlike previous studies, sub-jects in the present experiments were free to investany amount within the same range on every trial.Under these conditions, a between-trial examina-tion of the condition that escalated (partial returns-variable schedule) revealed a nonsignificant in-crease. However, interesting differences in patternsof investing did appear. A significantly larger per-centage of subjects escalated in this condition thanin other conditions, and the small increase acrosstrials in the variable condition became meaningfulin light of the large decreases in each of the con-tinuous conditions and in the fixed condition.

These results also contained interesting differ-ences in individual responding. For example, inExperiment 1, subjects in the partial returns-vari-able schedule condition were almost evenly dividedamong responses of increasing, decreasing, and stay-ing constant. In addition, in both investigations,several individuals in the continuous reinforcementconditions escalated. Some individual differences inpersistence may be developed through differingschedules of reinforcement experienced in child-hood (Amsel, 1979). Another possibility is that

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with longer or more variable training schedules,individual differences during extinction will de-crease. This latter explanation is especially likely ifindividuals are acting according to sets of rules theybring to the experimental situation, given that re-sults of some investigations indicate that rule con-trol may override schedule effects even when thelatter are strong (Baron, Kaufman, & Stauber, 1969;Harzem, Lowe, & Bagshaw, 1978).

The proposed analysis should be viewed as anelementary model that can be expanded. First, therole of other factors found to affect escalation, suchas competition and framing (e.g., Northcraft &Neale, 1986; Teger, 1980), should be addressedbefore concluding that behavior analysis can pro-vide a complete picture of resource allocation re-sponses. In addition, there are a number of areasof behavioral research not considered in the presentanalysis that may be useful in understanding re-commitment responses. For example, an expandedmodel might consider the behavior analysis of fram-ing effects (e.g., Rachlin, Castrogiovanni, & Cross,1987; Rachlin, Logue, Gibbon, & Frankel, 1986),in which discounting of delayed rewards is thoughtto account for some escalation responses, and thesimilar explanation that short-term individual con-sequences rather than long-term group conse-quences control responses in escalation situations(Platt, 1973). An expanded model could also in-vestigate the possibility that responsibility effectsthought to arise from self-justification (Staw, 1976)might result from providing outcomes highly con-tingent on behavior versus outcomes not contingenton behavior. Another area of possible expansioninvolves the investigation of discrimination andgeneralization gradients with regard to investmentstimuli. For example, in a new investment situation,some past investment-type stimuli and not othersmay be found to be similar enough that responsesdeveloped to them will be generalized.

Although the current analyses advance our un-derstanding of these phenomena, they do not ex-amine directly whether behavior analysis can beeffective in tempering escalation in actual situationswhen it is undesirable and increasing escalationwhen it is desirable. To sustain the dual efforts in

applied behavior analysis of both investigation andimprovement, as suggested by Dietz (1978), thisissue should be addressed by future research. Thepresent results suggest that employees (e.g., bankloan officers) could be trained with continuous re-inforcement contingencies to decrease recommit-ment in decision-making dilemmas such as an-swering requests for the extension of credits to clientsdelinquent on past loans. For decision-making po-sitions in which payoffs for investments are usuallydelayed and in which escalation is desirable (e.g.,a director of research and development), decision-makers could be trained using variable reinforce-ment. These implications contrast with strategiespreviously offered in the escalation literature (e.g.,Staw & Ross, 1987), such as reducing organiza-tional penalties for failure (i.e., decreasing the mag-nitude of aversive consequences for failure) andreducing the ambiguity of negative feedback (i.e.,increasing the discriminability of these stimuli). Infuture research, behavior analysis could be used tocompare directly the effectiveness of these variousstrategies.

The present analysis offers most of the aspectsof an applied behavior analysis (i.e., applied, be-havioral, analytic, technological, conceptual, effec-tive: Baer, Wolf, & Risley, 1968, 1988) but doesnot explore conditions controlling the generalizationof effects, thus leaving doubts as to the externalvalidity of the findings. A current analysis of thegeneralizability of laboratory findings in the fieldof organizational behavior suggests that experi-ments are important in identifying essential featuresof behavioral phenomena (Locke, 1986). The pres-ent investigation has identified some essential fea-tures that may control escalation. It remains forfuture investigations to examine whether these fea-tures are essential enough to control allocation be-haviors in the field (e.g., with "real" money, length-ened investment periods, and actual investors) andwhen the allocation behavior differs from an in-vestment of money.

Consideration of type of allocation behavior of-fers a number of interesting avenues for the ap-plication of behavior analysis. The escalation lit-erature typically refers to product development and

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other financial investments, such as Lockheed's costlyTri-StarJet program, British Columbia's $300 mil-lion loss in Expo '86, and the nonperforming loansto Latin America of large banks (Staw & Ross,1987). However, there are a number of situationsin which the allocation response does not involvean investment of money. For example, supervisorsevaluate more highly the performance ofemployeesthey originally hired than employees hired by others(Bazerman, Beekum, & Schoorman, 1982). Otherescalation situations that do not necessarily involvemoney include waiting after being placed on holdfor a telephone call and continuing to work in anonrewarding job (Staw & Ross, 1987). These andother situations in organizations prone to escalationrepresent a setting that could benefit from the un-derstanding attained and performance improve-ments made possible by the application of behavioranalysis.

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Received June 4, 1990Initial editorial decision October 23, 1990Revision received January 17, 1992Final acceptance May 11, 1992Action Editors, E. Scott Geller and John Parrish