Foreign Policy Decision Making

The Effects of Stakes and Threat on Foreign Policy Decision-MakingAuthor(s): Allison Astorino-CourtoisSource: Political Psychology, Vol. 21, No. 3 (Sep., 2000), pp. 489-510Published by: International Society of Political PsychologyStable URL: http://www.jstor.org/stable/3791847 .Accessed: 24/08/2011 06:26

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Political Psychology, Vol. 21, No. 3, 2000

The Effects of Stakes and Threat on Foreign Policy Decision-Making Allison Astorino-Courtois Department of Political Science Texas A&M University

Decision research demonstrates that individuals adapt decision processing strategies according to the characteristics of the decision task. Unfortunately, the literature has neglected task factors specific to foreign policy decisions. This paper presents experimental analyses of the effects of the decisional stakes (i.e., salience of the values at issue) and threat (risk of loss on those issues) on decision-makers' information acquisition patterns and choice rules with respect to one offour hypotheticalforeign policy scenarios. Contrary to the notion that normative (rational) decision-making is more likely in less dramatic settings, the results indicate that elevated threat encourages rational decision processing, whereas heuristic processing was more prevalent in less threatening situations. Interestingly, the added presence of high stakes magnified both threat effects. These results, although preliminary, suggest that stakes-threat effects are not direct reflections of stress and/or complexity effects, but should be considered independently in foreign policy analyses.

KEY WORDS: foreign policy decision-making, process tracing, choice rule

Since the end of the Cold War, U.S. foreign policy decision-makers have grappled with an expanded array of decision problems. This has been the case especially in the areas of security policy and the use of U.S. military force abroad. Whereas in the past most decisions were associated with significant threats to key national security concerns, revision of the bipolar security calculus has increased the range of decision problems to include a greater number of issues of lower stakes and lesser threats. For example, policymakers in the Bush administration, within a short period, grappled with decision events that represented-and were perceived to represent-four distinct stakes-threat classifications. The initial intervention in Somalia in the final days of the Bush administration was seen as a low stakes-low threat decision where intervention was considered "relatively 'cheap and easy' and

489 0162-895X ? 2000 International Society of Political Psychology

Published by Blackwell Publishers, 350 Main Street, Malden, MA 02148, USA, and 108 Cowley Road, Oxford, OX4 IJF, UK.

worth it."1 By contrast, sending U.S. ground forces into Bosnia for many qualified as a low stakes-high threat decision task. Richard Haass (1994; see also Pa- payoanou, 1997) reported that the "importance of U.S. interests" in Bosnia was unclear, and while the nature of the fighting and logistical difficulty of a military operation in Bosnia suggested that U.S. casualties would be high in the event of an intervention. Finally, the administration's decision to send U.S. forces to the desert of Saudi Arabia under the banner of Operation Desert Shield was considered a relatively high stakes-low threat intervention, whereas the transfer of that operation to the war fighting of Desert Storm clearly involved higher risk and thus represented a high stakes-high threat decision (Haass, 1994; Powell, 1995).

Experimental research demonstrates that decision-makers use a range of decision strategies contingent on the characteristics of the decision task (Hansen & Helgeson, 1996; Payne, Bettman, & Johnson, 1988,1993; Payne, Johnson, Bettman, & Coupey, 1990). Although these studies have enhanced our understanding of the impact of environmental factors on decision processing, with a few exceptions they have generally failed to explore the processing effects of foreign policy-specific factors.2 Within the foreign policy analysis subfield, a substantial literature has explored decision-making in the context of high stakes-high threat (i.e., crisis) situations but has stopped short of comparing these to other types of decision settings. Methodologically, many of these studies (e.g., Allison, 1971; Brecher, 1980; Haney, 1994; Holsti, North, & Brody, 1968; Maoz, 1981; Smith, 1984) have tended to focus on the output of a decision process, rather than the processing strategies used in making the choice. This has produced a considerable body of work on the impact of various decision factors in the evolution of interational crises (e.g., the involvement of leaders' perceptions of threat, etc., in creating the international outcome), but the task factors that affect pre-choice behaviors remain largely unexplored.

As noted, two task factors that are of growing importance in post-Cold War decision-making are the stakes (i.e., salience of the values at issue) and the threat to critical assets and personnel that a decision problem represents. The central question guiding the present research is whether, and how, makers of foreign policy adapt their decision strategies to the stakes-threat characteristics of a decision task. The degree to which two key decision processes-information processing and choice strategy-are associated with different decision environments is examined. Specifically:

1. Do foreign policy decision-makers use different decision strategies according to the stakes-threat characteristic of the decision task? If so, which types of

I As reported by Richard Haass (1994, pp. 69-70), a key member of the NSC staff at the time. Ambassador Robert Oakley, in an April 1995 discussion group at Texas A&M University, has concurred.

2 Exceptions include Mintz et al. (1997) and the work of Tetlock, Suedfeld, and colleagues (e.g., Suedfeld & Tetlock, 1977,1992; Suedfeld, Tetlock, & Ramirez, 1977; Suedfeld, Wallace, & Thachuk, 1993). Related studies by Hybel (1993) and Khong (1992) provide case analyses of "analogizing" as a type of processing heuristic used by foreign policy decision-makers.

490 Astorino-Courtois

Stakes and Threat in Foreign Policy Decision-Making

tasks are associated with the more cognitively taxing information processing strategies?

2. Is there an association between the stakes-threat property of a decision problem and the type of choice rule used?

Stakes and Threat as Decision Task Factors

During the last days of his administration, President George Bush outlined the principles involved in a decision to intervene militarily in any international crisis: "Using military force makes sense as a policy where the stakes warrant, where and when force can be effective,. .. where its application can be limited in scope and time, and where the potential benefits justify the potential costs and sacrifice."3 More formally, Bush was describing an evaluative guide including assessment of the perceived salience of the issues involved and the nation's ability to address them. In addition, he said, policymakers should anticipate a gain (or savings) in terms of critical assets associated with taking any action.

In foreign policy decision-making, the salience of and threat to national interests are critically important and interrelated task characteristics. They are also substantively distinct. Holsti et al. (1968) identified the salience of a particular issue to a decision-maker-the individual's degree of "involvement" in a decision situation-as a crucial variable in explaining his or her decisions. However, because these authors (like many others) limited their study to international crises, it is unclear to what degree the notion of decisional involvement is relevant in less critical settings. Indeed, as a result of the focus on crisis decision-making and the need to distinguish these settings from others, foreign policy decision analyses typically merge decision stakes and threat factors (see, e.g., Brecher & Wilkenfeld, 1982; Hermann, 1961). Following the conceptual lead of Holsti et al., isolating the stakes from the threat levels that characterize a particular decision event leaves the stakes associated with that event as a function of the salience of the interests, principles, or values at issue.4 The threat is then defined in terms of the anticipated loss of assets (e.g., human and material costs) associated with action or inaction in that instance. Thus, a high-threat decision problem might involve projections of a large number of casualties or a large monetary expense, regardless of the nature of the issues at stake. As for example the Bush administration's decisions to invade Iraq (where the stakes were perceived to be critical) or whether to send troops to Bosnia (where the stakes were generally perceived to be low).

3 Address to the U.S. Military Academy, West Point, New York, 5 January 1993, as excerpted in Haass (1994, p. 203).

4 The salience of an international event is not the same as the salience of information about it. The former is taken here to refer to the presence of critical national concerns, whereas the latter is typically defined in terms of "memorableness," or the accessibility and ease of recall from memory of certain bits of information (Posavac et al., 1997; Stasser, 1992).

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Are foreign policy decision-makers any more diligent in evaluating high stakes-high threat decision problems than they are in situations involving less important issues or lesser potential losses? Two difficulties arise for analysts interested in the task factors that affect foreign policy decision-making under various conditions. First, especially as compared to most foreign policy problems, decision tasks typically tested in experimental analyses involve relatively simple choices between equally simple or straightforward alternatives.5 Second, and relatedly, because the balance of this work has been conducted by analysts of human information processing, consumer choice, and psychology, the effect of the stakes-threat characteristic of a decision event-two of the most prevalent task- related considerations in the foreign policy setting-remain untested. Never- theless, the research on stress, complexity, and motivation effects on foreign policy decision-making can provide some direction.

The wide literature on decisional stress effects has shown that elevated stress levels can work to diminish decision performance (Maoz, 1990) by limiting information search (Brecher, 1980; Holsti, 1976, 1979), accelerating noncompensatory processing (Ben Zur & Breznitz, 1981), and reducing decision accuracy (Mandler, 1982). The stress associated with restricted time for a decision, in particular, has been found to evoke the use of simplifying and cognitively less demanding decision strategies (e.g., lexicographic decision-making, elimination by aspects), presumably because decision-makers are forced to evaluate only the most critical decision information (Lebow, 1985; Maoz, 1997; Payne et al., 1988).

Similarly, analyses of the effects of the complexity of a decision task generally indicate that more "difficult" decision problems encourage the use of simplifying decision heuristics. Studies as substantively diverse as those by Olshavsky (1979), Ostrom and Job (1986), Paquette and Kida (1988), Payne et al. (1990), Payne, Bettman, and Luce (1996), and Pelham and Neter (1995) have found that as choice problems become more complex, individuals tend to shift to effort-saving, noncompensatory, and dimension-based decision strategies.6 Jacoby (1975) and Stone and Kadous (1997) showed that decision accuracy is lost as well. On the other hand, research has also associated increased motivation with indicators of normative decision-making, including expanded information search and consideration of a greater number of decision alternatives (Posavac et al., 1997; Webster, 1993).

5 Keren (1996) commented on the bias associated with the (easier to study) gambling paradigm, where decision tasks are represented as "well-structured unambiguous tasks, like choosing between gambles" that fail to capture the complexity of real decision-making.

6 These studies measure the complexity of the decision task (i.e., its structural complexity) rather than the cognitive complexity with which a decision-maker approaches that problem. Cognitive complexity reflects the degree to which a decision-maker differentiates and integrates diverse bits of information in making a choice (Astorino-Courtois, 1995; Barner-Berry & Rosenwein, 1985; Suedfeld & Tetlock, 1977), whereas task complexity (Payne, 1976) refers to the characteristics of the decision problem itself (e.g., the number of dimensions and alternatives contained in the decision matrix, the severity of the value trade-offs, etc.).



Although the existing literature is clearly instructive, it yields only restricted (and seemingly conflicting) suggestions about the likely effects of stress, complexity, and motivation on decision processing in the various stakes-threat contexts. Specifically, stress and complexity research can be used to anticipate stakes-threat effects if we are willing to accept two assumptions: that decision-makers are consistently cognitive misers, and (perhaps more questionably) that perceived task complexity and/or decision stress rise in parallel with stakes and threat. If these conditions obtain, we could then expect higher stakes and higher threat decision problems to elicit simplified, dimension-based, and noncompensatory decision-making. Motivation effects research seems to support the opposite proposition if we believe that makers of national policy are generally highly motivated decision-makers, at least in the political arena. That is, as decision stakes and threat rise, decision-makers would use less simplistic (i.e., more cognitively demanding) decision strategies.

Research Design and Methods

Without the benefit of invasive research techniques, there is currently no way to gauge with precision which decision strategy or strategies have been used in a given circumstance. It is possible, however, to identify a number of decision processes associated with normative and heuristic decision-making (Ursic & Helgeson, 1990). This paper reports the results of a test of stakes-threat effects on two important decision processes: the individual's information processing pattern and the choice rule used. For the sake of clarity, the test hypotheses have been phrased as suggested by the stress/complexity effects literature. That is, that decision strategies will most clearly represent cognitively taxing, normative (rational) theories of choice under low stakes-low threat conditions, whereas simplifying decision strategies will appear when stakes and threat are high. The hypotheses to be tested are:

Hypothesis 1. Decision-makers tend toward dimensional information processing under high stakes-high threat conditions, and toward alternative-based processing as stakes-threat diminish.

Hypothesis 2. Decision-makers use noncompensatory choice strategies in high stakes-high threat situations, and do more compensatory processing as stakes- threat decline.

Experiment Design, Sample, and Instruments

Decision process data were collected according to a between-groups factorial design in which 140 Texas A&M University undergraduates were randomly assigned to receive one of the four hypothetical foreign policy decision problems outlined below. Although university undergraduates are not generally known to be decision-making experts, research has shown that they can provide reliable empirical estimates of the variance between experimental groups (e.g.,

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Hansen & Helgeson, 1996; Payne et al., 1990, 1993; Stone & Kadous, 1997; van Schie & van der Pligt, 1995). In addition, neither domain experience nor expertise appear to affect processing patterns in unstructured decision tasks such as those studied here (Devine & Kozlowski, 1995). There is also no evidence that experimental subjects adapt choice strategies according to whether the consequences are known to be real or hypothetical (Wiseman & Levin, 1996).

The experimental manipulation (independent factor) in this study was the

foreign policy decision setting as distinguished by stakes and threat levels. Partici-

pants received decision scenarios representing one of the four experimental treatments: low stakes-low threat, low stakes-high threat, high stakes-low threat, or

high stakes-high threat choice problems. Each scenario described hypothetical international situations to which the United States was considering a response.7 These are summarized below.8 (The full text of the first scenario, together with the text of the corresponding decision matrix, appears in the Appendix.)

Low stakes-low threat (monsoon in Rongkur): A monsoon has caused

deadly flooding in the impoverished nation of Rongkur. Wealthy land-owners there are taking advantage of the devastation to mount a violent campaign to oust Rongkur' s socialist government. The fighting and flood damage have now halted critical relief efforts by international aid agencies. Unless these are restarted immediately, 1.5 million flood victims will die of starvation and water-borne disease.

Low stakes-high threat (warfare in Teursho): Intense fighting continues between Teurshonis and Elodowis on the island nation of Teursho. Nearby Elo- doteur has supplied heavy weapons to Elodowi fighters, who have dominated the bitter interethnic fighting. If the previously brokered U.N. cease fire is not enforced, more than one-quarter of Teursho's civilian population will die from injury, starvation, and disease.

High stakes-low threat (Zubani-Kabyli conflict): The oil-rich nation of Zubani, a former province of Kabylia, recently won its independence after years of bloody civil war. Zubani is now threatened by a Kabyli attack apparently intended to re-annex its "lost province." Kabyli troops are believed capable of

overrunning Zubani in as few as 5 days, but would not engage a defensive force they could not defeat.

7 In an independent sample pretest, respondents accurately assessed the intended stakes (83%) and threat (89%) for each setting manipulation. Experiment participants' posttest stakes and threat ratings (1 = lowest to 10 = highest, for both) also served as a reliability check on the manipulation. Mean scores by treatment group are as follows:

Treatment group Self-reported stakes Self-reported threat Low stakes-low threat 4.2 3.8 High stakes-low threat 6.2 4.5 Low stakes-high threat 5.1 5.1 High stakes-high threat 7.2 6.4

8 For the sake of congruity with analyses of decision-making in the actual cases, the scenarios were based on the critical elements of the Bush administration's Somalia, Desert Shield, Bosnia, and Desert Storm decisions.

Astorino-Courtois 494


High stakes-high threat (Assiami invasion of Pathan): Assiam, a nation listed by the State Department as a sponsor of international terrorism, has occupied the mountain region of neighboring Pathan. This is clearly an effort to exploit Pathan's rich uranium fields. Any uranium taken from Pathan would likely be used to expand Assiam's small arsenal of nuclear bombs, and as a source of income from the sale of uranium on the international black market.

Experimental Procedure and Dependent Measures

Process tracing is a research technique that allows observation of various indicators of an individual's choice strategy. Most studies of information processing use some form of information display board (IDB) in an experimental design (Nakajima & Hotta, 1989). IDBs present subjects with an alternative (rows) by dimension (columns) matrix of decision information and "trace" subjects' moves through the decision set. In experiments where computerized IDBs are used, collection of the decision process data is invisible to the subject. The Decision Board, a Macintosh-based IDB platform, was used in the present study to trace

subjects' information processing patterns and final choice.9 Participants began the experiment with a practice exercise to familiarize

themselves with the Decision Board. After reading the assigned decision scenario (i.e., treatments 1 to 4), they returned to the Decision Board to view information regarding the consequences of four choice alternatives (specific to each scenario) on four value dimensions: the economy, foreign relations, national security, and domestic opinion. Information displayed in the 4 x 4 matrix was hidden from view until a participant moved to "open" the cell by clicking it with the computer mouse. As in Mintz, Geva, Redd, and Carnes (1997), cell information consisted of a short assessment of the impact of an alternative on a given dimension, as well as a numeric evaluation. For example, an information cell from the high stakes-high threat scenario at the "U.S. air strikes" choice alternative on the "international affairs" dimension contained this text: "Some nations will criticize unilateral action as reflecting U.S. disregard for the views of the rest of the world. Also, a successful strike could cause 25,000 Assiami casualties-a figure certain to incite international condemnation and limit our ability to influence reactions to future world crises. On a scale of 1 = worst to 10 = best, this option is a 4."

Information cells could be accessed only once, and only one cell could be opened at a time. 1 Participants were instructed to access only as much information as needed to make their final choice, which they indicated by clicking on the desired

9The Decision Board platform was developed by Mintz and Geva (1997) and applied in Mintz et al. (1997) and Mintz (1999).

10 This constraint is a result of the problems of interpreting search data collected in a multi-access setting. To limit the possible effect of this constraint on the decision strategy used, we allowed the participants to take brief notes if desired.

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Astorino-Courtois

alternative. At the end, each participant completed a brief posttest questionnaire. An experiment session lasted about 30 to 35 minutes.

The two dependent measures are indicators of important decision opera- tions: information processing pattern and choice rule. As shown in Table I, the values of each factor fall along a continuum from the expectations of cognitively demanding, normative decision models at one end, to use of simplifying strategies at the other.

Processing pattern. Participants' information processing strategies were evaluated according to their pre-choice moves through the decision matrix as recorded by the Decision Board process-tracer. Alternative-based decision-making implies that an individual considers all (dimensional) information on a given alternative before reviewing information on the next alternative (Mintz et al., 1997; Payne, 1976). Dimension-based processing, on the other hand, is indicated by nonsequential comparison of alternatives on a single dimension at a time. The cognitive processing demands of the former are greater than those required to compare alternatives along a single dimension. 1

A processing strategy (PS) index was developed to measure the degree to which participants' acquisition of decision information followed a primarily dimensional or an alternative-based processing pattern. The index is a revised version of one proposed by Billings and Scherer (1988) that measures an individual's information processing by subtracting the number of alternative-based (i.e., dimension-to-dimension) moves through the decision matrix from the number of dimension-based moves, and dividing by the total number of these moves.12 Because dimension-to-alternative and alternative-to-dimension moves are not figured into the Billings-Scherer measure, it can fail to distinguish between genuine alternative-based processing and a pattern of indiscriminate moves through the matrix with, for example, only a single alternative-to-alternative comparison.

The PS index was amended to account for the full path of a decision-maker's information acquisition (i.e., it includes non-dimensional and non-alternative- based shifts) so as to minimize the indeterminacy in the original measure. The PS measure is a conceptually similar but more sensitive indicator of the cognitive effort a decision-maker has expended in gaining decision information. The PS index was calculated as

PS = (a - d)(a + d + s) (1)

where a is the number of consecutive moves within the same decision dimension, d is the number of consecutive moves on the same decision alternative, and s is the number of dimension-to-alternative or alternative-to-dimension shifts. Values of

1 See Payne et al. (1988, 1993) for more complete discussions of the cognitive demands associated with various decision strategies.

12The Billings-Scherer index = (a - d)l(a + d), where a = total alternative-to-alternative moves and d = total dimension-to-dimension moves.

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Table I. Summary of Processing Characteristics by Decision Strategies

Cognitively demanding Effort-saving (heuristic) (normative) strategies strategies

Pattern Alternative-based < < < < > > > > Dimension-based Pattern Rule Compensatory < < < < > > > > Noncompensatory Rule

this index range from -1 (completely dimension-based processing) to 1 (completely alternative-based processing). The following illustrates how the PS scores were calculated.

Dimension A Dimension B Dimension C Dimension D Alternative 1 8 9 Alternative 2 1 7 5 Alternative 3 2 4 Alternative 4 3 6

In this example, the decision-maker began his search of the 4 x 4 decision matrix by accessing information on the implications of Alternative 2 for Di- mension A (labeled "1" for the first information cell accessed). He next took two dimension-based moves (i.e., examined the impact of Alternatives 2 and 3 on that Dimension), then shifted five times and ended with one alternative- based comparison (between Dimensions C and D on Alternative 1). Following Equation 1, then, PS = (2 - 1)/(2 + 1 + 5) = .125, indicating only a slight amount of alternative-based processing.

Choice rule. The second dependent measure taps the compensatory versus noncompensatory nature of the decision rule an individual has used in making his or her final choice. A choice process is noncompensatory if, in a multidimensional problem, a low score on one decision dimension (e.g., national security) cannot be offset by a high score on another dimension (e.g., economic stability). Decision alternatives associated with the low value are eliminated from further consideration despite their additive value (i.e., value across all decision dimensions). For example, an elected official might consider her popularity rating a critical aspect of all policy decisions. Because no value on a "noncritical" dimension will offset a low popularity score, alternatives associated with popularity ratings below her thresh- old value-even if the overall maximizing choice-are rejected. Noncompensatory processing is identified as a simplifying heuristic (see Mintz & Geva, 1997; Payne et al., 1990). By comparison, more cognitively demanding compensatory choice allows interdimensional trade-offs, so that a high value on one dimension can compensate for an unsatisfactory value on another. Once compensatory trade-offs are made, an additive rule is typically applied and the maximizing alternative is chosen. Normative decision models (e.g., rational, weighted additive value, expected utility) generally assume compensatory decision-making.

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How can we identify the extent to which a compensatory or noncompensatory choice strategy has been used? Payne et al. (1988) suggested the conceptual link between the consistency-selectivity with which an individual accesses decision information and the choice rule used. The authors argued that a comprehensive and systematic search of decision information is required to support more complex, compensatory decision-making. An individual using a simplifying noncompensatory rule, however, can be much more selective in accessing information, for example, only as relevant to a "critical" dimension. Consequently, consistent search (i.e., uniform types and amounts of information accessed) can be taken as an indicator of a compensatory choice strategy, and highly selective (i.e., uneven) search can be construed as reflecting the use of a noncompensatory rule.

Consistency-selectivity (CS) indices were developed to measure the variance in the amounts of information searched across decision alternatives (CSalt) and decision dimensions (CSdim). In this study, CS scores range from 0, indicating complete consistency in information searched, to 16, representing the maximum selectivity in the 4 x 4 decision matrices. Search consistency-selectivity on decision alternatives (CSalt) was calculated as

I _n n

CSalt = - Vy

Z

ayn - azn (2) n=l n=l

where n is the number of alternatives in the choice set, and a represents the number of (information) cells of the decision matrix accessed on each alternative y, z, and so on. CSdim scores were calculated as

CSdim = --Xu / waum awm (3)

where m is the number of dimensions in the choice set, and a is the number of cells accessed on each dimension u, w, and so on. The following example illustrates calculation of the CS measures.

Dimension A Dimension B Dimension C Dimension D Number Considered Alternative 1 8 9 2 Alternative 2 1 7 5 3 Alternative 3 2 4 2 Alternative 4 3 6 2

CSalt= (2 - 3)+(2 - 2)+(2 - 2)+(3- 2) + (3 - 2) + (2 - 2)1

= -1+0+0+1-1+01

=3

Reading across the row for alternative 1, we see that the decision-maker accessed two information cells on that alternative (i.e., on Dimensions C and D). Three information cells were searched on Alternative 2, two cells on Alternative 3, and



two cells on Alternative 4. Summing the absolute differences in the numbers of cells accessed on each alternative according to Equation 2 yields CSalt = 3, indicating a fairly consistent search and the use of a compensatory strategy. Figuring Equation 3 in the same manner shows an equally consistent search on dimensions (CSdim = 3).

Controls on time stress and complexity effects. Both subjective and objective measures of task complexity were made. The four manipulations of decision setting were designed with equal time constraints, information load, and numbers of dimensions and alternatives so as to minimize the effects of time-related stress and decision complexity on decision processing.

Participants' own evaluations of the complexity of their decision task were assessed by way of a post-experiment questionnaire asking them to rate its difficulty on a scale from 1 (very easy/straightforward) to 10 (very complex). The PS index was not significantly correlated with perceived task complexity (r = -.07, p = .43).

An objective task complexity measure was figured for each of the four decision scenarios according to the severity of the value trade-offs contained in its decision matrix. Trade-off complexity (TC) scores were computed as

n m-1 m

12 X (r - rq)2 TC= i=1 =lq=j+l (4)

nm2(n2 -1)

where n is the number of decision alternatives (four in this case), m is the number of value dimensions (four again), and rji is the rank given to alternative i on dimension j.13 TC scores range from 0 to 1. Scores nearing 0 indicate choice problems that require minimal value trade-offs in order to reveal a single optimizing alternative.'4 Scores nearing 1 reflect highly complex decisions that involve multiple alternatives ranked as near opposites on all dimensions.

The complexity scores calculated for the four decision scenarios were all near the middle of the range (low stakes-low threat TC = .34; low stakes-high threat TC = .44; high stakes-low threat TC = .50; high stakes-high threat TC = .54), and each was unrelated to the PS measure. That is, there was no immediate indication that participants systematically adapted their decision processes to accord with either the perceived or the structural complexity of their decision problem.

13 See Maoz (1990) for a discussion of this measure, and Maoz and Astorino (1992) and Astorino-Cour- tois and Trusty (2000) for applications.

14Problems that involve only a single dimension or alternative obviously score low on trade-off complexity as well.

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Analysis and Results

Test 1: Stakes-Threat Effect on Information Processing Strategy

Is the processing pattern decision-makers use contingent on the stakes-threat character of the decision task? A one-way between-groups analysis of variance (ANOVA)15 was conducted to identify the effect of the stakes-threat manipulation (i.e., low stakes-low threat, low stakes-high threat, high stakes-low threat, high stakes-high threat) on the order in which individuals reviewed decision information. The dependent factor was the PS index.

The ANOVA shows a nearly significant main effect of the stakes-threat task manipulation on information processing [F(3, 115) = 2.35, p = .07]. Was the effect consistent with hypothesis I?

Figure 1 shows mean PS scores (ranging from -1 = pure dimension-based to 1 = pure alternative-based processing) for the four treatment groups. Interestingly, participants in the high stakes-high threat treatment group engaged in the highest degree of alternative-based processing (PSgl = .43). In fact, a closer look reveals that, contrary to the hypothesized effect and regardless of the stakes involved, both high-threat treatments prompted relatively more alternative-based processing than did either low-threat treatment. An ANOVA of (combined) high- and low-threat treatment groups shows this relationship to be quite strong [F(1, 115) = 5.07, p = .03; PShigh threatkl = .38, PSlow threat,l = . 13], which suggests that the threat posed by the decision problem was a significant factor in the use of more demanding, alternative-based processing strategies. In other words, it provides evidence of processing diligence in high-threat foreign policy settings, and a tendency to use simplifying heuristics in evaluating less threatening problems. The impact of the stakes on the use of alternative-based versus dimension-based decision strategies is less clear.

Although an ANOVA failed to show a strong effect [F(1, 115) = .348, p = .557; high stakes ,t = .22, low stakes ,t = .29] of decisional stakes on participants' choice of processing strategy, there may be some interaction between the stakes and threat factors. As shown in Figure 1, the low- and high-threat decision tasks can be distinguished by the presence of high stakes. On one end of the scale, high stakes appear to intensify the heuristic (dimensional) processing already associated with the low threat level, presumably reducing the cognitive effort allotted to that problem (i.e., creating a literal "no-brainer"). The same effect appears on the other end of the scale. The presence of highly salient national interests in a setting that is also highly threatening serves to increase the extent of cognitively taxing,

15 Between-groups ANOVA refers to the partitioning of total variability in the data into the differences between treatment means on two or more groups plus the residual effect (i.e., differences of observations within treatments from the overall treatment mean). In assessing stakes-threat effects, the "treatment" is having received one version of the four different decision scenarios.



V I0.43 C)

a)

0.34

.CD

c

_ - 0.25 .0

CD

E

-0.5 high stakes- low stakes- low stakes- high stakes- low threat low threat high threat high threat

Decision Type

Figure 1. Alternative-based versus dimensional processing by treatment.

alternative-based processing. The results of this first test show a significant move to alternative-based decision strategies associated with elevated threat. Further

testing is warranted, however, before conclusions can be made about stakes-threat interaction effects.

Test 2: Stakes-Threat Effect on Decision Rule

The second test explored whether the stakes-threat characteristics of the

foreign policy decision problem altered the choice rule decision-makers used

(hypothesis 2). The dependent factor was the relative consistency-selectivity of information search. Tests were conducted separately for search consistency on alternatives (CSait) and on dimensions (CSdim).

The ANOVA shows the level of threat (high vs. low) to have a weak effect [F(1, 115) = 2.8, p = .09; low threat g = 3.89, high threat ,t = 2.76] on the choice rule participants used in making a decision.16 As shown in Figure 2, the higher threat condition encouraged more consistent access of information for all alternatives considered. Again, contrary to the simplifying effect suggested by previous adaptive decision studies, individuals engaged in more cognitively demanding

6 Because the F statistic used here is a two-tailed test, the limit of statistical significance, as is general convention, is taken to be p < .09.

501

2:a 4 3.89 3.9

3 111 1112.76 2.73

low threat high threat low stakes high stakes

Decision Type

Figure 2. Mean search consistency by combined treatments.

decision processing, in this case compensatory choice, under the high-threat condition. An ANOVA of the stakes treatment (high vs. low) also showed a weak manipulation effect [F(1, 115) = 3.26, p = .07; low stakes gt = 2.73, high stakes L = 3.9]. In contrast to the threat effect, however, higher stakes encouraged more selective search on alternatives, indicating the use of an effort-saving, noncompensatory strategy.

Although the threat and stakes factors affected participants' evaluations of response alternatives, neither treatment significantly affected evaluation of which decision dimensions (e.g., public opinion, economic impact) should be satisfied [F(l, 115) = 1.72, p= .19 for threat; F(1, 115) = 1.32, p = .25 for stakes]. Why did the participants adapt their choice rules when comparing alternatives, but not when seeking information on dimensions? One explanation may be that the willingness (or ability) to trade values on multiple decision dimensions is more clearly a function of an individual's belief system than is the process of weighing possible response options. Simply put, the fact that people have different core values is more important in dimensional evaluation than in deciding between alternatives. More- over, making trade-offs between dimensions requires the decision-maker to priori- tize disparate interests and varied standards of utility. Evaluating alternatives, on the other hand, may be a more straightforward judgment on the appropriateness of a specific action in a specific circumstance, and is not as sensitive to the differences in individual preferences.



Discussion

Individuals generally adapted their decision strategies to the stakes-threat property of the decision tasks in terms of both the processing patterns and choice rules used. Overall, and contrary to the propositions of a good deal of stress effects research, participants followed more cognitively demanding (i.e., alternative- based) information processing patterns under high-threat conditions. Simplifying (dimension-based) processing was more commonly used in the low-threat settings. Interestingly, in both the high- and low-threat settings, the addition of elevated stakes had no significant independent effect, but rather appeared to intensify the processing effect of the threat level.

The threat characteristic of the decision problem also influenced choice rules. Again, contrary to the large body of literature associating crises with heuristic- based decision-making, the high-threat manipulation encouraged more effortful (compensatory) choice. On the other hand, the level of stakes involved in the decision task had the reverse effect on the choice rule. That is, the presence of high stakes promoted the use of a simplifying, noncompensatory choice rule. Although this study represents an initial exploration of the effects of the stakes and threat properties on decision-making, the results nonetheless indicate that these should not be taken as simple reflections of stress and complexity effects. On the contrary, these foreign policy domain-specific decision factors appear to be independent of-and, in general, produce effects opposed to-those associated with stress and complexity.

Haass (1997) has observed that "the world in the wake of the Cold War ... promises to be terribly complex, more so than what came before" (p. 1). Moreover, for powers like the United States, it promises to be freer from threats of cataclysmic proportions, at the same time that it is "more dangerous (with the emergence of more numerous if lesser threats)." The results of this analysis have implications both for post-Cold War foreign policy decision-making and for our theoretical understanding of rational and quasi-rational decision-making. In the foreign policy setting, improved understanding of how various characteristics of a given decision situation might affect decision-making can help sensitize leaders to the "biases, pitfalls and fallacies that characterize decision-making processes" (Maoz, 1990, p. 179). For example, when evaluating a "lesser" international threat, decision- makers should be aware of the tendency to simplify decision processes in these settings rather than search for optimal alternatives.

On a theoretical level, this paper has extended research by decision theorists primarily working outside political science. Although those studies provide a solid basis for inquiry, what we can learn about the impact of the unique elements of foreign policy decision problems (or, indeed, decision-making in other political arenas) will greatly enhance our understanding of the connections among domestic and international decision settings, decision strategies, and political outcomes.

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ACKNOWLEDGMENTS

I am grateful to Uri Geva, Nehemia Geva, Brittani Trusty, Guy Whitten, Alex Mintz, the Decision Lab of the Program in Foreign Policy Decision-making at Texas A&M, and anonymous reviewers for their invaluable suggestions and assistance. Correspondence concerning this article should be sent to Allison Astorino- Courtois, Department of Political Science, Texas A&M University, College Sta- tion, TX 77843-4348. E-mail: [email protected]

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APPENDIX

Decision Scenario and Decision Matrix for Low Stakes-Low Threat Treatment

Presidential Briefing on Monsoon Devastation and Crisis in Rongkur

Situation: A devastating monsoon has ravaged the lowlands of Rongkur. After 2 years of severe drought, the monsoon rains have caused mud slides and deadly flooding. International relief workers estimate that 250,000 Rongkuris have died in the flooding so far, and unless aid missions begin immediately, as many as 1.5 million more will soon die of starvation and water-borne diseases. The National Security Council (NSC) considers this crisis to be both low stakes in terms of the importance to vital U.S. interests and policy, and low threat in terms of the potential risk/costs to U.S. resources and personnel.

Background: Rongkur's economy is built on subsistence farming. During the drought wealthy landowners bought up land from peasant farmers desperate for quick money in order to survive. The landowners then charged enormous rent to the former owners to live on and farm the land. When the socialist government of Rongkur attempted to reform this practice, the landowners hired and armed their



own "gangs" to resist implementation. Two months ago, gang-Army clashes broke out when Rongkur's Prime Minister was assassinated by one of the landowner

gangs. Army Chief General Harani is now serving as acting Prime Minister. Currently: The landowners are taking advantage of the monsoon to mount an

offensive against the Rongkuri government. The capital city has been the site of continuous gun battles. In addition, there are unconfirmed reports that General Harani-who has not appeared in a number of days-has been kidnapped by the landowner gangs. Without his leadership the Rongkuri Army is quickly becoming disorganized and ineffective.

The fighting, together with the flood damage, make the situation in Rongkur both difficult and dangerous for international relief workers: along with the indiscriminate shootings, and demands of extortion payments to the gangs, many of Rongkur's roads and bridges have been destroyed. Distribution of critical relief supplies to the countryside is now nearly impossible. Helicopter airlifts are the only way to reach those areas. In addition, fighting around Rongkur's only airport has

prevented delivery of food and medical aid. Aid/rescue workers are running critically low on supplies needed for the million Rongkuris left homeless by the flood.

Public Opinion: CNN has been broadcasting special reports on the situation in Rongkur, including a now well-known report from a temporary shelter filled with thousands of poor children orphaned by the floods and fighting. Having in many cases seen their parents swept away by the floods, the children now face starvation and death from preventable diseases simply because relief supplies are bogged down by the fighting in the capital. The latest polls indicate growing

Yarbu River

Rongkur st\. Dester River

Rongkur Citl

Monsoon devastation area

Rongkuri Sea

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sentiment among the American public that something must be done to relieve the suffering in Rongkur.

At the U.N.: Our U.N. Ambassador reports that the U.N. Security Council would welcome a U.S. initiative to aid Rongkur. He feels that since Rongkur is a resource-poor and poverty-stricken country without any major allies, U.S. action would encourage other nations to get involved as well.

According to the Joint Chiefs of Staff, the landowner gangs represent only a minor threat to any U.S. personnel sent to Rongkur. Again, your advisors in the National Security Council consider this crisis to be both low stakes in terms of the

importance to vital U.S. interests and policy, and low threat in terms of the potential risk/costs to U.S. resources and personnel.

After analyzing the situation, the NSC staff has submitted four alternatives for possible U.S. response:

RESPONSE ALTERNATIVES

Offer $5,500,000 in U.S. emergency assistance to Rongkur (MONEY)

* U.S. (unilateral) military force sufficient to rebuild roads and assure aid worker safety (U.S. ACTION)

* Lead U.N. military (coalition) force authorized only to rebuild roadways and assure the safety of aid workers (U.N./AID)

* Lead larger U.N. military force authorized to deliver aid and restore political order and stability in Rongkur (U.N./POLITICAL)

In making your final choice among these alternatives, you may want to consider any, or all, of these areas of concern:

CONCERNS

* Cost in $ and economic impact (ECON)

? Impact on U.S. national security (NAT'L SECURITY)

* Impact on relations with other nations (INT'L RELATIONS)

* Domestic opinion (PUBLIC OPINION)

To continue, please return to the computer screen and click on "NEXTPAGE"...

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Decision Matrix Cell Contents

MONEY U.S. ACTION

This option will While U.S. not affect the U.S. humanitarian

economy; the action will not $5.5 million is affect U.S. available through business or trade, the international it will cost $6 to

emergency relief 8 million in fund. On a scale unbudgeted of 1 = worst to expenses. 10 = best, this Moreover, option is a 9. intervention

now could set a precedent for costly U.S. intervention in future world humanitarian/

political crises. On a scale of 1 = worst to 10 = best, this

option is a 3.

U.N./AID

This option will involve moderate

operational costs as non-

participating Security Council members should

provide some financial

compensation for participants. On a scale of 1 = worst to 10 = best, this

option is a 6.

U.N./POLITICAL

Stabilizing Rongkur's political situation will likely entail moderate-

high costs for the U.S. that could last for a year or more. These costs will increase if U.N. forces come under attack from landowner gangs and additional

troops/weapons are needed. On a scale of 1 = worst to 10 = best, this

option is a 3.

NAT'L This option will SECURITY not affect either

U.S. or world

security. On a scale of 1 = worst to 10 = best, this

option is a 10.

Sending a humanitarian force to Rongkur will in no way diminish our

ability to defend U.S. security interests around the globe. U.S. lives will be at moderate risk

only if landowner

gangs believe the U.S. action poses a threat to their

political power. On a scale of 1 = worst to 10 = best, this

option is an 8.

Although in If all Rongkuri command of the landowners U.N. force, U.S. perceive U.N.

generals in political objectives Rongkur may be as enhancing their unable to control power/influence, the bearing (e.g., U.N. forces should

prejudices, be at low risk.

aggressive tactics) However, if U.N. of foreign military stabilization efforts units. Some are seen by even U.S./U.N. one landowner as casualties should threatening, be expected if U.S./U.N. forces landowners see will come under the U.N. force attack with as politically potentially heavy threatening. On a casualties. On a scale of 1 = worst scale of 1 = worst to 10 = best, this to 10 = best, this option is a 7. option is a 5.

ECON

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MONEY U.S. ACTION U.N./AID U.N./POLITICAL

INT'L As financial RELATIONS assistance will

not resolve the aid distribution crisis in Rongkur, the U.S. should

expect criticism-

especially by poorer nations- for indifference to the lives of non-Western people. This could affect our influence in affairs beyond Europe and Japan. On a scale of 1 = worst to 10 = best, this

option is a 6.

This option will This option enhance our influence abroad

by demonstrating U.S. concern with human rights and welfare, regardless of

political ideology, economic ties, etc. On a scale of 1 = worst to 10 = best, this option is a 10.

should enhance U.S. international

prestige by demonstrating our willingness to work with other nations in defense of human welfare-

regardless of political differences. On a scale of 1 = worst to 10 = best, this

option is a 10.

This option may enhance our influence among nations with similar views on human and

political rights to ours. However, our relations will be harmed with some Third World nations who

perceive it as

patronizing and

arrogant imposition of Western

political practices on the rest of the world. On a scale of 1 = worst to 10 = best, this option is a 6.

While this option This option will involves no loss be popular as long of U.S. lives, as U.S. casualties

public and media are low, the

perception that operation is the administration successful and is indifferent to its U.S. troops are concerns over returned home

Rongkuri suffering within 5 months. could significantly If not, your re- decrease your election chances

popularity ratings. could be harmed. On a scale of On a scale of l = worst to 1 = worst to 10 = best, this 10 = best, this option is a 2. option is a 6.

As long as there are no U.S. casualties, Americans will

support this option as reflecting U.S. moral leadership and compassion- without the expense of unilateral action. On a scale of 1 = worst to 10 = best, this

option is an 8.

Americans will

support intervention as

long as U.S. casualties are low. If casualties increase, public support will turn and possibly mark this as a major foreign policy blunder. On a scale of 1 = worst to 10 = best, this

option is a 5.

PUBLIC OPINION

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Foreign Policy Decision Making

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