determinants of risky dm behaviors

8/3/2019 Determinants of Risky DM Behaviors

1/21

Determinants of Risky Decision-Making Behavior: A Test of the Mediating Role of RiskPerceptions and Propensity

Author(s): Sim B Sitkin and Laurie R. WeingartSource: The Academy of Management Journal, Vol. 38, No. 6 (Dec., 1995), pp. 1573-1592Published by: Academy of ManagementStable URL: http://www.jstor.org/stable/256844 .

Accessed: 24/09/2011 02:10

Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at .http://www.jstor.org/page/info/about/policies/terms.jsp

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of

content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms

of scholarship. For more information about JSTOR, please contact [email protected].

Academy of Managementis collaborating with JSTOR to digitize, preserve and extend access to The Academy

of Management Journal.

http://www.jstor.org
http://www.jstor.org/action/showPublisher?publisherCode=aomhttp://www.jstor.org/stable/256844?origin=JSTOR-pdfhttp://www.jstor.org/page/info/about/policies/terms.jsphttp://www.jstor.org/page/info/about/policies/terms.jsphttp://www.jstor.org/stable/256844?origin=JSTOR-pdfhttp://www.jstor.org/action/showPublisher?publisherCode=aom


2/21

? Academy of Management Journal1995, Vol. 38, No. 6, 1573-1592.

DETERMINANTS OF RISKY DECISION-MAKINGBEHAVIOR: A TEST OF THE MEDIATING ROLEOF RISK PERCEPTIONS AND PROPENSITYSIM B SITKINDuke UniversityLAURIE R. WEINGART

Carnegie Mellon UniversityThe reported research examined the usefulness of placing risk propen-sity and risk perception in a more central role in models of risky de-cision making than has been done previously. Specifically, this arti-cle reports on two studies that examined a model in which riskpropensity and risk perception mediate the effects of problem fram-ing and outcome history on risky decision-making behavior. Impli-cations of the pattern of results for future research are discussed.

Most scholars who have studied decision-making behavior in riskyorganizational situations have focused on the direct effects of one or twodeterminants of this behavior. However, such an approach does not ade-quately reflect the complex sets of influences on risk behavior in organ-izations. In addition, it has led to contradictions in the literature and po-tentially inaccurate conclusions about the causes of decision-making be-havior (Sitkin & Pablo, 1992). For example, Kahneman and Tversky's"prospect theory" (1979) conclusion that negatively framed situationslead to greaterrisk taking contradicts the results of research by March andShapira (1987) and Osborn and Jackson (1988).In an attemptto build upon these direct effects approaches, Sitkin andPablo (1992) proposed a mediated model of the determinants of risky de-cision making, theorizing that the effects of a number of previously ex-amined variables on risk taking were not direct but were instead mediat-ed by risk propensity and risk perception. Their model extended the di-rect effects approaches and posited a direct causal effect between thevariables studied and risk taking. In addition, where direct effects ap-proaches have predicted specific choices under conditions of risk, Sitkinand Pablo focused on the process of making risky decisions. This articlereports two studies that provide initial tests of key portions of the Sitkin-Pablo approach.

We would like to thank Robyn Dawes, George Huber, Amy Pablo, Gerald Salancik, DavidSchkade, Michael Hitt, and three anonymous reviewers for their helpful comments on ear-lier versions of this article.1573


3/21

Academy of Management JournalCLARIFYING KEY CONSTRUCTS AND DISTINCTIONS

Sitkin and Pablo (1992) reviewed a number of potentially relevant in-dividual, organizational, and problem characteristics that have been iden-tified as predictors of risky individual decision making. Perhaps the mostsignificant focus of their analysis was the previously distinct effects of out-come history and problem framing, which they argued had been over-looked-and sometimes unintentionally confounded-in prior work.Specifically, Sitkin and Pablo suggested that previous contradictory find-ings could be explained by disentangling outcome history from problemframing. Following their theoretical emphasis, we focus on these two fre-quently studied predictors of risky decision making. This choice wasguided by our desire to stress variables whose effects were predicted bySitkin and Pablo to be mediated by risk propensity and risk perceptions,so as to provide an initial test of their core propositions.Although it focuses on only a subset of the broader model, Figure 1reflects the core ideas underlying the mediated model of the determinantsof risky decision making and captures its most critical variables. First, itrepresents antecedent characteristics as affecting decision making only in-directly, through their effect on risk propensity and risk perceptions; thisis the mediated aspect of the model. In addition, the paths shown in Fig-ure 1 are numerically keyed to the hypothesized bivariate relationships be-tween the variables of the model (discussed later in the article).Before addressing the rationale for each relationship posited in themodel we should define several key constructs, since these distinctionsunderlie several of our arguments. Variables identified in the Sitkin andPablo (1992) model addressed here include their dependent variable, de-cision risk, their proposed mediating variables (risk perception and riskpropensity), and two key exogenous predictor variables that they identi-

FIGURE 1Mediated Model of the Determinants of Risky Decision-Making Behaviora+ RiskOutcome History H1 Propensitysk

~H4^ RiskyH3 - > Decision-Makingv _ Behavior

+ Risk H5Problem Framing H2 Perceptionska The numbers shown on the paths of the model are keyed to some of the hypothesesdiscussed herein. Several hypotheses are not shown here because they represent the mediationhypotheses rather than a specific hypothesized relationship. Specifically, Hypotheses 6 and 7posit that the effects of outcome history on risky decision making and risk perception aremediated by risk propensity, and Hypotheses 8 and 9 posit that the effects of problem framingand risk propensity are mediated by risk perception.

1574 December


4/21

Sitkin and Weingartfled as characterizing the person and the situation: outcome history andproblem framing. Each of these five constructs is defined below.Decision risk is a construct used to characterize the alternatives con-fronting a decision maker; it can, for example, describe how undesirablethe likely effects of an alternative are and the likelihood of their occur-rence. Risk can also be used to characterize an overall decision-how riskyit is compared to other alternatives. Following Sitkin and Pablo, we de-fined decision risk as "the extent to which there is uncertainty aboutwhether potentially significant and/or disappointing outcomes of decisionswill be realized" (1992: 10). To the extent that a decision involves high un-certainty or extreme outcomes, either in terms of the choice among alter-natives or for individual alternatives in aggregate, the decision is charac-terized as risky.Included in the model are two direct determinants of decision risk-risk perception and risk propensity-that also serve as mediators of an-tecedent characteristics of the decision maker and the problem situation.Risk perception is defined as an individual's assessment of how risky a sit-uation is in terms of probabilistic estimates of the degree of situational un-certainty, how controllable that uncertainty is, and confidence in those es-timates (Baird & Thomas, 1985; Bettman, 1973).Risk propensity is defined as an individual's current tendency to takeor avoid risks. It is conceptualized as an individual trait that can changeover time and thus is an emergent property of the decision maker. This de-finition of risk propensity, which follows Sitkin and Pablo (1992), is re-lated to but departs in a critical way from previous conceptualizations ofpropensity as a stable dispositional attribute (e.g., Fischhoff, Lichtenstein,Slovic, Derby, & Keeney, 1981; Rowe, 1977). It is interesting to note thateven critics of the predictive value of the risk propensity construct (e.g.,MacCrimmon &Wehrung, 1990; Schoemaker, 1990) have employed the tra-ditional conception of risk propensity as a stable individual attribute.We are contrasting the traditional conception of risk propensity as "astable and constant" dispositional attribute (Wolman, 1989: 103) with ourconceptualization of it as a changeable trait that is "persistent" (Suther-land, 1989: 452) or "enduring" (Goldenson, 1984: 757) but can be "learnedor inherited" (Corsini & Osaki, 1984: 542-543). Hair color or facial fea-tures-frequently cited as examples of traits (e.g., Goldenson, 1984)-il-lustrate the concept of persistence and change in that hair color respondsto exposure to the sun and facial features can be altered through cosmet-ic surgery. Similarly, a trait-based definition of risk propensity conceptu-alizes the construct as a cumulative tendency to take or avoid risks thatis simultaneously persistent and can change over time as a result of ex-perience. By focusing on the important role of past experience, this con-ceptualization can account for the capacity for people to adapt withoutdenying that as individuals gain more experience, they may be less sus-ceptible to contextual influence and more likely to exhibit cross-situationalconsistency. Thus, our approach to risk propensity as "stable but change-

1995 1575


5/21

Academy of Management Journalable" both builds upon and modifies the traditional "stable and constant"view.

Although the tendency to take risks (i.e., risk propensity) is almost cer-tainly related causally to making riskier decisions, as we will hypothesizeand test below, the two constructs are not synonymous because a numberof factors can impede the realization of a decision maker's tendencies inany particular instance. Even an individual who consistently leans towardseeking risks could in a specific case, such as a business investment, failto act on this tendency, because of inadequate funding, a missed ap-pointment, an unexpected illness, a natural disaster, or other obstruction.We also examined two exogenous variables posited in Sitkin andPablo's (1992) model. Problem framing refers to whether a situation is pre-sented to a decision maker as an opportunity or a threat (e.g., Jackson &Dutton, 1988) or in terms of gains or losses (Kahneman & Tversky, 1979).That is, the situation can be portrayed in a generally positive or negativelight. Outcome history, a person-situation interaction characteristic, is de-fined as the degree to which the decision maker believes that previous risk-related decisions have resulted in successful or unsuccessful outcomes. Forour purpose, this variable reflects an individual's overall mental repre-sentation of how well he or she has fared in the past in similar situations(see Sitkin [1992] and Weick [1984] for reviews).

A MEDIATED-EFFECTS MODEL OF THE DETERMINANTS OFRISK BEHAVIORDeterminants of Risk Propensity

Outcome history. Although outcome history is posited here to affectdecision making, the role of outcome history has been notably absent inmany theories of risky decision-making behavior. Nearly all studies havefocused on either individual risk orientation (MacCrimmon & Wehrung,1986a, 1986b, 1990) or decision maker computation of risk (Dyer & Sarin,1982; Tversky & Kahneman, 1986) while essentially ignoring the poten-tially important role of previous decisions made and their outcomes.This ahistorical viewpoint is challenged by recent research findingsshowing that prior success in taking risks can increase the propensity totake risks. For example, the work of March and Shapira (1987), Osborn andJackson (1988), and Thaler and Johnson (1990) found that decision mak-ers will persist in taking risks if prior risk-related actions were success-ful.Hypothesis 1: The more successful the outcomes of a de-cision maker's risk-related decisions have been, the high-er his or her risk propensity.

Determinants of Risk PerceptionProblem framing. An important influence on a decision maker's riskperceptions is whether a problem is framed in positive or negative terms.

1576 December


6/21

Sitkin and WeingartIn an influential study of individual risk behavior under conditions of var-ied problem frames, Kahneman and Tversky (1979) formulated prospecttheory, noting that positively framed situations led to the making of risk-averse decisions, whereas negatively framed situations led to risk seeking.A number of succeeding studies (e.g., Neale, Bazerman, Northcraft, &Alperson, 1986; Singh, 1986; Tversky & Kahneman, 1986, 1992) havefound the influence of problem framing on decision making to be robust.However, none of these studies has directly examined the causalmechanisms underlying the observed behavioral effects posited in prospecttheory. If perceptions and other omitted mechanisms are left unexam-ined, it remains unclear how problem framing comes to affect decisions.Following Sitkin and Pablo (1992), we hypothesized that framing direct-ly affects how risky a situation is perceived to be, which in turn leads tothe behavioral outcomes they observed. This hypothesis implies that pos-itive frames, which emphasize situational threats to existing resources, maymake the risks inherent in a situation more salient (inducing risk-aversebehavior), whereas an emphasis on the upside potential for increasing lim-ited holdings or recouping losses may decrease the salience of risks by in-creasing the salience of opportunities (inducing risk-seeking behavior).Such an explanation is consistent with the nonlinearity that lies at theheart of prospect theory and its empirical support, but it extends prospecttheory by suggesting the cognitive mechanism through which observablebehavioral responses occur.

Hypothesis 2: Positively framed situations will be per-ceived as involving higher risk than negatively framedsituations.Risk propensity. Risk propensity influences the relative salience ofsituational threat or opportunity and thus leads to biased risk perceptions(Brockhaus, 1980; Vlek &Stallen, 1980). Specifically, risk-averse decisionmakers (i.e., individuals with a propensity to avoid risks) are hypothesizedto attend to and weight potentially negative outcomes more heavily thanpositive outcomes (Schneider & Lopes, 1986), thus overestimating theprobability of loss relative to the probability of gain. Conversely, risk-seek-ing decision makers are hypothesized to attend to and weight positive op-portunities more heavily (March &Shapira, 1987), thus overestimating theprobability of gain relative to the probability of loss.

Hypothesis 3: The higher a decision maker's risk propen-sity, the lower the level of perceived situational risk.Determinants of Risky Decision-Making Behavior

Risk propensity. The straightforward intuitive basis for positing thatan individual's "willingness to take risks" (MacCrimmon & Wehrung,1990) affects whether he or she will actually make riskier decisions makesextensive explanation unnecessary. Although the Sitkin-Pablo model hasnot been tested previously, its core (see Figure 1) concerns the notion that

1995 1577


7/21

Academy of Management Journalan individual's propensity to take or avoid risks affects decision making,an idea that is grounded in a number of previous studies (e.g., Kogan &Wallach, 1964; MacCrimmon & Wehrung, 1986a, 1990). For example,Brockhaus (1980) hypothesized that the overall orientation of an individ-ual toward risk (risk propensity) would predispose some individuals tomake riskier decisions than other individuals. Thus,

Hypothesis 4: The higher a decision maker's risk propen-sity, the riskier will be his or her decision-making be-havior.Risk perception. Although we have acknowledged that prospect the-ory does not explicitly consider risk perceptions, Sitkin and Pablo (1992)

suggested that the findings of prospect theory research are consistent witha negative relationship between perceived risk and making risky decisions.That is, risk avoidance is greater when threats to assets are salient (highrisk is perceived) than it is when an individual perceives little risk becausethere is nothing to lose. It also seemed reasonable to posit that higher lev-els of perceived situational risk would be negatively related to makingrisky decisions since people tend to associate risk with negative outcomesmore strongly than with outcome variability (e.g., Levitt & March, 1988).Given this perceptual asymmetry, we hypothesized that actions taken un-der conditions of higher perceived situational risk would also be per-ceived to have a lower expected value.Hypothesis 5: The degree to which individuals makerisky decisions will be negatively associated with theirlevel of perceived risk.The Role of Risk Perception and Risk Propensity

As stated earlier, most previous research has overlooked a critical the-oretical issue raised by the Sitkin-Pablo model-the causal mechanismsby which a variety of exogenous variables come to affect decision-makingbehavior. As shown in Figure 1, they argued that the direct impact of an-tecedent variables on risky decision making actually takes place only viathe mediating function of risk propensity and risk perception.No theories prior to Sitkin and Pablo (1992) and no empirical workhas focused explicitly on the indirect effects of outcome history on riskydecision making. Nonetheless, Sitkin and Pablo drew on the earlier workof March and Shapira (1987), Osborn and Jackson (1988), and Thaler andJohnson (1990) to argue that successful or unsuccessful outcome historiesaffect how decision makers perceived risky situations and acted upon themby influencing what kinds of information decision makers attended to andalso by influencing how much those decision makers leaned a priori to-ward or away from taking risks. Historical success or failure does not, theysuggested, direct attention toward specific risk elements of a situation. In-stead, their analysis was grounded in the familiar notion that decision mak-ers would be prone to persist in pursuing what worked in the past and to

December578


8/21

Sitkin and Weingartabandon what did not. This intuitive argument, they noted, is that outcomehistory affects a decision maker's propensity to take risks, and that it is thetendency to take or avoid risks that in turn directs attention to high- or low-risk aspects of a situation (i.e., risk perception) and leads to pursuing oravoiding risky behaviors.

Hypothesis 6: The effect of outcome history on risky de-cision-making behavior will be fully mediated by riskpropensity.Hypothesis 7: The effect of outcome history on risk per-ception will be fully mediated by risk propensity.

We hypothesized that risk propensity and problem framing affectrisky decision making by influencing what is perceived. Risk propensityis linked to risk perception in several ways; these include limiting whatinformation is attended to and limiting an individual's ability to notice andrespond to risky attributes that influence how risky situations will be eval-uated. This approach is consistent with previous work that has defined riskperception in terms of situational labeling (Jackson &Dutton, 1988; Staw,Sandelands, &Dutton, 1981) and estimates of the extent and controllabilityof risks (Baird & Thomas, 1985; Vlek & Stallen, 1980). Thus, risk propen-sity is not only posited to affect decision making directly, but is alsoposited to have an indirect effect on risky decision making through its ef-fect on risk perceptions (cf. Sitkin & Pablo, 1992).

Hypothesis 8: The effect of risk propensity on risky de-cision-making behavior will be partially mediated byrisk perception.Similarly, the effect of problem framing on risky decision making ismediated by risk perception because framing affects the strength and clar-ity of an individual's positive or negative perceptions of aspects of a sit-uation. Thus, building on the previously discussed logic of Hypotheses 2

and 5, we posit that:Hypothesis 9: The effect of problem framing on risky de-cision-making behavior will be fully mediated by riskperception.The overall goal of the empirical research reported in this article wasto provide a preliminary test of several key aspects of the mediated mod-el. We describe the results of two studies, each of which tested selected

portions of the model.1 Study 1 manipulated outcome history to examine1 We attempted during pretesting to include these separate aspects of the model in a sin-gle experimental design. Although their reactions to each manipulated variable were distinct,when both were used simultaneously we found that subjects confused the two manipula-tions. Therefore, we ran two experiments that presented subjects with only one manipula-tion at a time.

1995 1579


9/21

Academy of Management Journalthe hypothesized mediating role of risk propensity and risk perception.Study 2 manipulated problem framing to examine the hypothesized me-diating role of risk perception. STUDY 1Methods

Subjects. Thirty-eight master's of business administration students ina required organizational behavior class participated in the study. The sub-jects' average age was 28.3 years (ranging from 23 to 46), and their workexperience averaged 6.2 years (ranging from 0 to 25 years). Sixty-six per-cent of the subjects were men.Procedures and stimulus materials. The study was a class exercise.A packet containing the stimulus materials and questionnaire was dis-tributed. Subjects were asked to read through the stimulus materials andto individually fill out an attached questionnaire.A modified version of a widely used decision-making case, Carter Rac-ing (Brittain &Sitkin, 1989), was used.2 Carter Racing places decision mak-ers in a situation of risky choice. The case masks the facts of the Nation-al Aeronautics and Space Administration's (NASA) decision to launch thespace shuttle Challenger in the guise of a decision about whether a racecar team should compete in the last race of the season. The decision in-volves risk in a number of domains, including business risk, personal fi-nancial risk, and physical risk. In the study, we focused on the impact ofthe decision about whether to race on the financial viability of the racecar team as an organization-that is, business risk.This particular stimulus was chosen because it avoids a major prob-lem frequently associated with experimental stimulus materials in that ithas been found to be highly realistic and quickly engaging. Since the caseas originally written fosters highly skewed choice patterns, modificationsto the original case were made (concerning information about the racing

team's history of success and failure and the amount of money at stake)that would lead to a more balanced distribution of decisions. The basiccase information was changed so that the expected value of racing wasequal to the expected value of not racing when ambient air temperaturewas not incorporated into the calculations.3Variables

Outcome history. Outcome history was manipulated after subjects hadread the case and before they read the first question of the questionnaire.2 The complete text of the revised case is available from the authors.3 Air temperature was not included in developing equality across the options (i.e.,race/not race) in our revision because it was not incorporated by the Challenger decisionmakers or by students using the case in the past (Brittain & Sitkin, 1989).

December580


10/21

Sitkin and WeingartIndividuals in the unsuccessful outcome history condition read the fol-lowing:

As Pat Carter,you have had a moderate amount of training forand experience with this type of decision. Your previous de-cisions have been largely unsuccessful and you have alwayshad a naggingworry that your poor "trackrecord" could even-tually have more serious consequences. You feel uncertain be-cause of the lack of success of those decisions you have madein the past.Subjects in the successful outcome history condition read:As Pat Carter,you have had a moderate amount of training forand experience with this type of decision. Your previous de-cisions have been largely successful and you have always de-rived a sense of self-assurance from your successful "trackrecord"in making such decisions. You feel confident becauseof the success of those decisions you have made in the past.A three-item outcome history manipulation check ("Extent to whichproblems have resulted from Pat's decisions like this in the past," "Degreeto which Pat has analyzed decisions like this correctly in the past," and"Degree to which successful outcomes have resulted from Pat's decisionslike this in the past") was found to be reliable (a = .71). The manipula-tion check was found to be significant across conditions (F136 = 14.68, p

< .001) and in the predicted direction (success condition, x = 4.68, s.d.=0.91; failure condition, x = 3.44, s.d. = 1.08).Decision-making behavior. Immediately following the manipulation,subjects were asked to indicate whether they would race (definitely notrace, 0%; definitely race, 100%). Next, a dichotomous forced-choice item(race vs. not race) was presented. The scaled format item is an indirectmeasure of decision making that gathers data on a subject's intentions,whereas the forced-choice item measures decision-making behavior di-rectly. Because the scaled format allowed for more response variance thandid the dichotomous choice format and the two items were highly corre-lated (r37 = .72, p < .001), we used the scaled format item as the indica-tor of decision-making behavior (see the Appendix for the text of this andsubsequently described items).Risk perception. A four-item scale was adapted from MacCrimmonand Wehrung (1985, 1986a, 1986b) and Wehrung, Lee, Tse, and Vertinsky(1989) to measure the amount of perceived risk associated with the deci-sion to be made (oa= .75).Risk propensity. An original five-item scale for business risk propen-sity was employed (o = .86).Results

Direct effects. The direct effects posited in Hypotheses 1, 3, 4, and 5were examined through correlation and regression analyses. First, asshown in Table 1, outcome history significantly influences risk propensi-

1995 1581


11/21

Academy of Management JournalTABLE 1

Study 1 Descriptive Statistics and t-Test ResultsOutcome History Conditiona

Failure SuccessVariable Mean s.d. Mean s.d. t dfRisky decision making 58.33 34.00 77.50 22.68 -2.06* 36Risk propensity 3.73 1.23 4.51 1.00 -2.15* 36Risk perception 3.64 1.28 2.80 0.87 2.38* 36

a Failure, n = 18; success, n = 20.* p< .05

ty (t36= -2.15, p < .05). Thus, subjects who were informed that Pat Carter(whose role they adopted as decision maker) had successfully made sim-ilar decisions in the past reported higher levels of risk propensity for Pat,supporting Hypothesis 1. Second, risk propensity was found to be nega-tively related to risk perception, supporting Hypothesis 3 (r = -.54, p


12/21

Sitkin and Weingart

tionship was no longer significant (3 = .17, n.s.), and risk propensity wassignificantly related to decision making (P = .46, p < .01). In addition, thechange in beta associated with outcome history was significant (A3 = .16,t35 = 2.23, p < .05). Thus, Hypothesis 6 was supported.Second, Hypothesis 7, suggesting that risk propensity mediated the re-lationship between risk outcome history and risk perception, was also test-ed using stepwise regression. The direct effects of outcome history ex-plained a significant portion of the variance in risk perception (R2 = .14,p < .05), and the change in R2 when propensity was added to the equa-tion was significant (AR2= .19, p < .01). Results of step 1 showed that out-come history was negatively related to risk perception (P = -.37, p < .05).When risk propensity was added to the equation in step 2, the effect of out-come history was no longer significant (p = -.21, n.s.), and the riskpropensity effect was significant (P = -.46, p < .01). In addition, thechange in beta associated with outcome history was significant (AP = .16,t3 = -2.15, p < .05). Thus, Hypothesis 7 was supported.Finally, Hypothesis 8 was tested to determine if risk perception par-tially mediated the effects of risk propensity on risky decision making. Thedirect effect of propensity explained a significant portion of the variancein risk behavior (R2 = .27, p < .001), and the change in R2 when risk per-ception was added to the equation was significant (AR2 = .35, p < .001).Results from step 1 showed that risk propensity was positively related todecision making (p = .52, p < .001). When risk perception was added tothe equation, the relationship was no longer significant (p = .15, n.s.), andrisk perception was significantly related to decision making (3 = -.70, p< .001). The change in beta associated with risk propensity was signifi-cant (Ap = .47, t3 = 3.69, p < .01). Because the mediation effect was full,rather than partial, Hypothesis 8 was not supported.Summary. Taken together, the results of study 1 demonstrate that theeffects of outcome history cascade from outcome history to risk propen-sity to risk perception and finally from risk perception to risky decision-making behavior. These results provide support for the role of outcome his-tory in the mediated model of risky decision making while clarifying ourunderstanding of the path through which these effects occur.

STUDY 2Study 2 was designed to test the portion of the model relating to theframing effect-focusing on the relationships between problem framing,risk perception, and risky decision making. Two direct-effect hypothesesand one mediating hypothesis were tested: Hypothesis 2, positing a posi-tive relationship between problem framing and risk perception, Hypoth-esis 5, positing a negative relationship between risk perception and riskydecision making, and Hypothesis 9, addressing the expectation of the me-diating role of risk perception in the relationship between framing andrisky decision making.

1995 1583


13/21

Academy of Management JournalMethods

Subjects. Sixty-three students in an undergraduate introductoryorganizational behavior class participated in the study. Subjects were onaverage 20.1 years old (range = 18-26 years) and averaged 4.2 years ofwork experience (range = 0-9 years). Seventy-one percent of the subjectswere men.Procedures and stimulus materials. The general procedure for study2 was similar to that described for study 1. Subjects received a packet con-taining the Carter Racing scenario, the manipulation of problem framing,and a series of questions designed to assess their decisions, their percep-tions of the risk in the situation, and a problem-framing manipulationcheck.Variables

Problem framing. All subjects were given an identical description ofthe decision-making situation. This three-page description included in-formation about both potential gains and losses. Problem framing was ma-nipulated after they had read the case and before they read the first ques-tion of the questionnaire. A randomly assigned half of the subjects read aframing paragraph that selectively drew upon information from the caseto highlight the potential for losses, and the other half read a framing para-graph that highlighted the potential for gains. Subjects in the negativelyframed condition (domain of losses) read:As Pat Carter,you face a tough decision, because it involvestrade-offs. If you race, you have a 29% chance of blowing anengine and losing all of your support for next year, includingthe $500,000 oil and $300,000 tire sponsorships. If you do notrace, you will lose the $300,000 tire sponsorship you had se-cured for next year.

Participants in the positively-framed condition (domain of gains)read:As Pat Carter,you face a tough decision, because it involvestrade-offs. If you race, you have a 42% chance of finishing inthe top 5 and winning the $300,000 tire sponsorship plus theprice money. If you do not race, you will be able to secure the$500,000 oil sponsorship for the next season.A three-item framing manipulation check was employed (a = .70) thatassessed the degree to which subjects focused on the opportunities (ratherthan the threats) inherent in the situation. Items included the following:"Future opportunities were key, even though they were uncertain," "Thiswas the biggest opportunity we ever had," and "We just had to go for it-you can't win by sitting in the pits." Subjects responded on a seven-pointscale ranging from strongly disagree to strongly agree.Risk perception and risky decision-making behavior. The measuresof perception of risk in the situation and risky decision making were thesame as used in study 1.

1584 December


14/21

Sitkin and WeingartTABLE 2

Study 2 Descriptive Statistics and t-Test ResultsProblem-Framing Conditiona

Negative PositiveVariable Mean s.d. Mean s.d. t dfRisky decision making 72.58 20.10 51.56 27.10 3.44*** 61Risk perception 3.27 0.69 3.58 0.84 -2.99** 61

a Negative framing, n = 31; positive framing, n = 32.**p < .01*** p < .001

ResultsManipulation check. The framing manipulation was found to be ef-fective (F1,62 = 5.33, p < .05), with subjects in the positively framed con-dition reporting a significantly higher concern for opportunity (x = 5.10,s.d. = 1.01) than those in the negatively framed condition (x = 4.33, s.d.=1.56).Hypothesis tests. Results supported Hypotheses 2 and 5 and partial-ly supported Hypothesis 9. First, as shown in Table 2, problem framing andrisk perception were significantly related, as predicted in Hypothesis 2 (t61

=-2.99, p < .01). Second, risk perception and risky decision making werenegatively correlated (r62 = -.59, p < .001), supporting Hypothesis 5. Fi-nally, results of a regression analysis showed that the direct effects of fram-ing explained a significant portion of the variance in decision making (R2.16, p < .001), and the change in R2 when risk perception was added tothe equation was significant (AR2= .22, p < .001). In a test of Hypothesis9, regression results showed that the effect of framing on risky behaviorwas significant (p = -.40, p < .001) when examined in isolation. Whenrisk perception was added to the equation in step 2, risk perception wassignificantly related to risky decision making (P = -.51, p < .001), andthe strength of the effect of framing was reduced (t61 = -2.98, p < .01) butremained significant (P = -.22, p < .05). These findings show that riskperception partially mediated the relationship between problem framingand risky decision-making behavior. Therefore, Hypothesis 9, positingfull mediation, was not supported.Summary. The results of study 2 suggest that problem framing hasboth a direct and an indirect effect on risky decision-making behavior. Ingeneral, these results lend support for the mediated model of risky deci-sion making and clarify our understanding of the causal path throughwhich these influences occur.

DISCUSSION AND CONCLUSIONThe two studies reported here allowed us to test key portions of theSitkin-Pablo model. As the results summarized in Figure 2 show, all but

1995 1585


15/21

Academy of Management JournalFIGURE 2Revised Model of the Determinants of Risky Decision-Making BehaviorBased on Combined Results of Studies 1 and 2a

+ RiskOutcome History Propensity(Si) PropensityRisky- (S) Decision-MakingBehavior

I u 1..* + ^r Risk (S1,S2)Problem Framing (2) Perception(S2) Perception(S2)

aOnly significant relationships are shown, with the sign of the relationship indicatedalong each path. Studies from which each result was derived are indicated in parentheses (S1for study 1 and S2 for study 2). The strength of the results is indicated by the number of plusor minus signs shown; "+" or "-" indicates significance of p < .05 or greater, whereas "++"or "--" indicates significance of p < .01 or greater.

one of the causal steps hypothesized in the model received support. Ourresults provide support for the inclusion of risk perception and riskpropensity as mediators of effects on risky decision-making behavior. Inboth studies reported here, risk propensity and risk perception were foundto significantly reduce the relationships between the antecedent variablesand risky decision making. In study 1, the relationship between outcomehistory and decision making was mediated by risk propensity and risk per-ception. In study 2, risk perception was found to substantially mediate therelationship between problem framing and decision making, although theresults also indicated that a direct effect of problem framing on risky de-cision-making behavior remained. Finally, risk propensity effects on riskydecision making were found to be mediated by perceptions of risk instudy 1. Thus, our results provide preliminary support for the mediatingapproach and challenge the direct effects model underlying most previousresearch on risk behavior.Limitations and Future Research

We view the results reported here to be but an initial test of key ele-ments in a much broader model. Two limitations of the studies reportedhere highlight opportunities for future research.Omitted variables. In the future, scholars should begin to examine theeffects of other variables that are of potential relevance to risk behavior.For example, as we noted at the beginning of the article, we have only ex-amined a subset of the variables posited by Sitkin and Pablo (1992) as af-fecting risk behavior, and future studies should begin to examine the oth-er variables they identified, such as an organization's cultural orientation

1586 December


16/21

Sitkin and Weingarttoward risk, role models provided by organizational leaders, reward sys-tems, and individuals' risk preferences.In addition, a number of other variables could be fruitfully integrat-ed into future research using the general approach taken here. For exam-ple, although demographic variables did not affect our results, researchershave identified important risk-related differences based on gender (Arch,1993) and age (e.g., Hambrick & Mason, 1984; MacCrimmon & Wehrung,1990). In addition, experience has been found to influence risk behaviorand learning from risk taking (cf. Levitt &March, 1988; Osborn &Jackson,1988). In terms of future treatments of experience, researchers could drawupon work on self-efficacy (Bandura, 1977) or learned helplessness (Selig-man, 1975) to theorize about how people's past successes and failures in-fluence their propensity to take risks.Experience of study sample. The range of experiential history acrossthe potentially relevant risk domains raised by the stimulus material waslimited in our samples. Although the study design and its use of experi-mentally manipulated variables did not rely upon the personal decision-making experience of subjects, nonetheless their limited personal experi-ence is a potential limitation to be acknowledged and should be addressedin future work, which could use more experienced decision makers as sub-jects.Theoretical Extensions and Implications

Importance of risk propensity. Sitkin and Pablo (1992) argued that theperceived value of risk propensity as a construct has waned because of itspoor conceptualization and measurement. The results of our empiricalstudies support their contention that rumors of the demise of risk propen-sity were premature.The finding that risk propensity was negatively associated with riskperception in study 1-that the more a subject was inclined to take risks,the less risky he or she perceived the Carter Racing scenario to be-is con-sistent with March and Shapira's (1987) finding that risk-seeking decisionmakers tend to attend more to the opportunities inherent in a situation thanto the threats. This finding provides additional support for the potentialvalue of retaining the risk propensity construct in theories and empiricalresearch. Thus, it appears that Sitkin and Pablo's (1992) conception of riskpropensity as a current tendency based on cumulative historical outcomesrather than a fixed dispositional characteristic (e.g., Kogan & Wallach,1964) has merit and should be subjected to further theoretical and em-pirical scrutiny.Reexamining framing effects. The finding in study 2 that problemframing is partially mediated by risk perceptions is potentially importantin that it extends previous research on framing effects. Whereas a directeffects model was implied in the original formulation and supportingstudies of prospect theory (Kahneman & Tversky, 1979), our results pro-vide partial support for Sitkin and Pablo's (1992) reformulation. This sup-

1995 1587


17/21

Academy of Management Journal

port suggests that future work should reexamine prospect theory studiesby independently varying framing and perceptions.Traditionally, framing effects have been tested in very controlled set-tings using simple scenarios, with the manipulation of gains and lossesmade very salient to decision makers. These research designs have resultedin much stronger framing effects than emerged from study 2. It is possi-ble that the complexity of the task materials dampened the salience of themanipulation. Decision makers read a lengthy scenario and a subtle ma-nipulation and then responded to a large set of items designed to assessmultiple constructs. The large amount of information to which the deci-sion makers had to attend may have weakened the framing effect. Thus,our findings in study 2 might help to identify a potential boundary con-

dition for framing effects while supporting the broad finding in the liter-ature that they are robust.Theoretical importance of considering decision maker experience.Future research could examine the role of experience more directlythrough longitudinal designs that track changes in propensity under con-ditions in which experienced outcome histories are systematically variedthrough sampling rather than through experimental manipulation of con-ditions. For example, future research could study populations of decisionmakers whose experiential base is more varied, such as acquisition spe-cialists, mediators, venture capitalists, or-using our stimulus-race carteam members.It is important to highlight that such an extension is not merelymethodological. It is also theoretically important in that it raises the ques-tion of whether different models apply to experienced decision makers andto inexperienced ones. For example, it is possible that risk propensity isless likely to mediate outcome history when decision makers do not havesufficient personal experience to have developed stable outcome historiesor propensities with respect to a specific decision being made.Studies are often criticized, especially in the organizational literature,for studying inexperienced student decision makers, but we think this crit-icism can be misplaced if made indiscriminately. Every decision maker hashad to start somewhere; thus, research on first-time decision makers is in-deed valid so long as the researchers are clear about the population towhich they can generalize. In addition, if the findings of other scholars arecorrect in suggesting that experience (among other attributes) may not gen-eralize from one domain to another, even experienced decision makers mayfrequently encounter decision situations in which they are novices. Thus,our findings may well be far more generalizable than a narrow view of de-cision maker experience might suggest. To determine whether our resultsapply to all decision makers or only to those who are relatively low in do-main-specific experience will require additional empirical study. Notwith-standing the limitations of this study, our findings do provide a startingpoint from which to propose a reformulation of the Sitkin-Pablo model ofthe determinants of risky decision-making behavior.

1588 December


18/21

Sitkin and Weingart

Implications for Practicing ManagersThe findings reported in this article have several implications for prac-

ticing managers that can be extended in future work as well. The findingthat the mediator variables are strong predictors of risky decision-makingbehavior, if supported in future studies under different contexts, providesan opportunity to more efficiently predict individual risk behavior. Specif-ically, if two mediator variables continue to show strong predictive pow-er, the large number of antecedent variables used in today's studies couldbe supplanted by a much more parsimonious approach.4Risk perception. The studies reported here provide clear support forthe importance of risk perception as a crucial influence on individual risk-taking behavior, an influence that mediates the effects of at least severalother influences on risk behavior. This work implies that managers whowish to either increase or decrease the risks taken by subordinates or oth-ers can most effectively target their efforts toward problem framing or oth-er determinants of risk perception. The applications for such a finding arequite broad. For example, Pablo, Sitkin, and Jemison (in press) recentlyexamined how risk perception could affect the ways that managers ap-proach the inherent risks involved in acquiring and integrating anotherfirm. Other applications include the willingness to openly disclose sen-sitive information, such as information about safety (Douglas &Wildavsky,1982; Osborn & Jackson, 1988; Tamuz & Sitkin, 1992), and the willingnessto pursue high-risk corporate innovations (Van de Ven & Polley, 1992).Risk propensity. An area to be explored further in the future concernsour operational definition of risk propensity as involving a cumulative ten-dency to take or avoid risks. This finding and perspective have two po-tential implications for practice. First it suggests that risk taking can bemore easily influenced early in a decision maker's "domain career"-when he or she has had little experience in that domain-as risk propen-sity will become more stable and difficult to influence as time passes. Thisimplication fits quite nicely with the more general point made by social-ization theorists (e.g., Van Maanen &Schein, 1979) about the relative mal-leability of inexperienced and experienced employees. Second, it suggeststhat even once an individual's risk orientation is fixed, individual orgroup decision makers can be purposively selected on the basis of theiroutcome histories and risk propensity to influence the likelihood thatmore or less risky decisions will be made.Domain specificity. Although these studies did not directly addressthe question of domain specificity, a natural extension of this work wouldbe to focus on the conditions under which past experiences in taking risksin one domain are generalized and thus affect perceptions and propensi-ties to undertake risks in another domain. Of even more practical value tomanagers is the implication that issue definition (e.g., Dutton & Jackson,

4 We would like to thank George Huber for pointing out this implication of our results.

1995 1589


19/21

Academy of Management Journal

1987) may prove to be an effective way to influence what domain a deci-sion is seen as relating to and thus may provide the opportunity for sig-nificant points of influence on a decision maker's risk propensity, per-ceptions, and behavior.Conclusion

This article presented the results of a first test of the Sitkin and Pablomodel of the determinants of risk behavior and provided support for theportions of the model tested, in particular for the general notion that a me-diated model of risk behavior is more powerful than one in which the di-rect effects of a large number of individual antecedent variables are ex-amined individually. Not only did the studies reported here provide gen-eral support for a mediated model in which risk perception and riskpropensity are key mediators, but they also clarified some of the likelycausal relationships involved. Thus, this article provides a conceptual andempirical springboard for future work on other potentially important de-terminants of risky decision-making behavior.

REFERENCESArch, E. 1993. Risk taking: A motivational basis for sex differences. Psychological Reports,73: 3-11.Bandura, A. 1977. Self-efficacy: Toward a unifying theory of behavioral change. Psycholog-ical Bulletin, 84: 191-215.Baird, I. S., & Thomas, H. 1985. Toward a contingency model of strategic risk taking. Acad-emy of Management Review, 10: 230-243.Baron, R. M., & Kenney, D. A. 1986. The moderator-mediator variable distinction in socialpsychological research: Conceptual, strategic, and statistical considerations. Journal ofPersonality and Social Psychology, 51: 1173-1182.Bettman, J. R. 1973. Perceived risk and its components: A model and empirical test. Jour-nal of Market Research, 10: 184-190.Brittain, J., &Sitkin, S. B. 1989. Facts, figures, and organizational decisions: Carter racing andquantitative analysis in the organizational behavior classroom. Organizational Behav-ior Teaching Review, 14(1): 62-81.Brockhaus, R. H. 1980. Risk-taking propensity of entrepreneurs. Academy of ManagementJournal, 23: 509-520.Corsini, R. J., &Osaki, B. D. (Eds.). 1984. Encyclopedia of psychology, vol. 3. New York: Wi-ley.Douglas, M., &Wildavsky, A. 1982. Risk and culture. Berkeley: University of California Press.Dutton, J E., & Jackson, S. E. 1987. Categorizing strategic issues: Links to organizational ac-tion. Academy of Management Review, 11: 76-90.Dyer, J. S., & Sarin, R. K. 1982. Relative risk aversion. Management Science, 28: 875-886.Fischhoff, B., Lichtenstein, S., Slovic, P., Derby, S. L., &Keeney, R. L. 1981. Acceptable risk.Cambridge, England: Cambridge University Press.Goldenson, R. M. (Ed.). 1984. Longman dictionary of psychology and psychiatry. NewYork: Longman.Hambrick, D. C., & Mason, P. 1984. Upper echelons: The organization as a reflection of itstop managers. Academy of Management Review, 9: 193-206.Jackson, S. E., &Dutton, J. E. 1988. Discerning threats and opportunities. Administrative Sci-ence Quarterly, 33: 370-387.Kahneman, D., & Tversky, A. 1979. Prospect theory: An analysis of decision under risk.Econometrica, 47: 263-291.

1590 December


20/21

Sitkin and WeingartKogan, N., &Wallach, M. A. 1964. Risk taking: A study in cognition and personality. NewYork: Holt, Rinehart & Winston.Levitt, B., & March, J. G. 1988. Organizational learning. In W. R. Scott &J. Blake (Eds.), An-

nual review of sociology, 14: 319-340. Palo Alto, CA: Annual Reviews.MacCrimmon, K. R., & Wehrung, D. A. 1985. A portfolio of risk measures. Theory and De-cision, 19: 1-29.MacCrimmon, K. R., &Wehrung, D. A. 1986a. Taking risks: The management of uncertainty.New York: Free Press.MacCrimmon, K. R., &Wehrung, D. A. 1986b. Assessing risk propensity. In L. Daboni, A. Mon-tesano, & M. Lines (Eds.), Recent developments in the foundations of utility and risktheory: 291-309. Dordrecht: D. Reidel Press.MacCrimmon, K. R., &Wehrung, D. A. 1990. Characteristics of risk taking executives. Man-agement Science, 36: 422-435.March, J. G., & Shapira, Z. 1987. Managerial perspectives on risk and risk-taking. Manage-

ment Science, 33: 1404-1418.Neale, M. A., Bazerman, M. H., Northcraft, G. B., &Alperson, C. 1986. "Choice shift" effectsin group decisions: A decision bias perspective. International Journal of Small GroupResearch, March: 33-42.Osborn, R. N., & Jackson, D. H. 1988. Leaders, riverboat gamblers, or purposeful unintend-ed consequences in the management of complex dangerous technologies. Academy ofManagement Journal, 31: 924-947.Pablo, A. L., Sitkin, S. B., &Jemison, D. B. In press. The role of risk in acquisition decisionmaking processess. Journal of Management.Rowe, W. D. 1977. An anatomy of risk. New York: Wiley.Schneider, S. L., & Lopes, L. L. 1986. Reflection in preferences under risk: Who and when

may suggest why. Journal of Experimental Psychology: Human Perception and Per-formance, 12: 535-548.Schoemaker, P. 1990. Are risk attitudes related across domains and response modes? Man-agement Science, 36: 1451-1463.Seligman, M. E. P. 1975. Helplessness. San Francisco: Freeman.Singh, J. 1986. Performance, slack, and risk taking in organizational decision making. Acad-emy of Management Journal, 29: 562-585.Sitkin, S. B. 1992. Learning from failure: The strategy of small losses. In B. M. Staw & L. L.Cummings (Eds.), Research in organizational behavior, vol. 14: 231-266. Greenwich,CT:JAI Press.Sitkin, S. B., &Pablo, A. L. 1992. Reconceptualizing the determinants of risk behavior. Acad-

emy of Management Review, 17: 9-39.Staw, B. M., Sandelands, L. E., & Dutton, J. E. 1981. Threat-rigidity effects in organizationalbehavior: A multi-level analysis. Administrative Science Quarterly, 26: 501-524.Sutherland, S. (Ed.). 1989. International dictionary of psychology. New York: Continuum.Tamuz, M., & Sitkin, S. B. 1992. The invisible muzzle: Organizational and legal con-straints on the disclosure of information about health and safety hazards. Working pa-per, University of Texas School of Public Health, Houston.Thaler, R. H., &Johnson, E. J. 1990. Gambling with the house money and trying to break even:The effects of prior outcomes on risky choice. Management Science, 36: 643-660.Tversky, A., & Kahneman, D. 1986. Rational choice and the framing of decisions. In R. M.Hogarth & M. W. Reder (Eds.), Rational choice: The contrast between economics and

psychology: 67-94. Chicago: University of Chicago Press.Tversky, A., &Kahneman, D. 1992. Advances in prospect theory: Cumulative representationof uncertainty. Journal of Risk and Uncertainty, 5: 297-323.Van de Ven, A. H., &Polley, D. 1992. Learning while innovating. Organization Science, 3(1):92-116.Van Maanen, J., & Schein, E. H. 1979. Toward a theory of organization socialization. In B.

1995 1591


21/21

Academy of Management JournalStaw & L. Cummings (Eds.), Research in organizational behavior, vol. 1: 209-259.Greenwich, CT:JAI Press.

Vlek, C., & Stallen, P. J. 1980. Rational and personal aspects of risk. Acta Psychologica, 45:273-300.Wehrung, D. A., Lee, K., Tse, D. K., &Vertinsky, I. B. 1989. Adjusting risky situations: A the-oretical framework and empirical test. Journal of Risk and Uncertainty, 2: 189-212.Weick, K. E. 1984. Small wins: Redefining the scale of social problems. American Psychol-ogist, 39: 40-49.Wolman, B. B. (Ed.). 1989. Dictionary of behavioral science. San Diego: Academic Press.

APPENDIXScale Items and ReliabilitiesRisky Decision-Making Behavior

Subjects in studies 1 and 2 were asked: "If you were Pat Carter, what is the probabilitythat you would decide to race/not race (where 0% = definitely not race and 100% = defi-nitely race)?" Choices were provided in increments of 10 percent.Risk Perception

This four-item scale (a = .75) was used in studies 1 and 2. The first three items reflect-ed responses to the following question:"How would you characterize the decision faced by Pat Carter?" (1) 1 = significant op-portunity to 7 = significant threat; (2) 1 = potential for loss to 7 = potential for gain (reverse-scored); (3) 1 = positive situation to 7 = negative situation.The fourth item was a response to the following question:"What is the likelihood of the Carter Racing Team succeeding at the Pocono race?" (4)1 = very unlikely to 7 = very likely (reverse-scored).Risk Propensity

This five-item scale (a = .86) was used in study 1 and captured responses to the followingquestion:"As Pat Carter you face a decision that affects your organization's financial future. Giv-en this circumstance, how would you rate your tendency to. . . (1) choose more or less riskyalternatives based on the assessment of others on whom you must rely, (2) choose more orless risky alternatives which rely upon analyses high in technical complexity, (3) choose moreor less risky alternatives which could have a major impact on the strategic direction of yourorganization, (4) initiate a strategic corporate action which has the potential to backfire, (5)support a decision when I was aware that relevant analyses were done while missing sev-eral pieces of information."

Sim B Sitkin is an associate professor of management at the Fuqua School of Busi-ness, Duke University. He received he Ph.D. degree in organizational behavior fromthe Graduate School of Business, Stanford University. His research examines theprocesses by which organizations and their members become more or less capableof change and innovation. More specifically, his work focuses on the effect of for-mal and informal organizational control systems on risk taking, accountability, trust,learning, and innovation.

Laurie R. Weingart is an associate professor of industrial administration in theGraduate School of Industrial Administration at Carnegie Mellon University. She re-ceived her Ph.D. degree in organization behavior from Northwestern University. Herresearch interests include individual and group decision-making processes, primar-ily focusing on negotiation tactical behavior.

December592

determinants of risky dm behaviors

Documents