Context effects on group-based employee selection decisions

Organizational Behavior and Human Decision Processes 100 (2006) 47–59 www.elsevier.com/locate/obhdp

Context eVects on group-based employee selection decisions Jerel E. Slaughter ¤, Jessica Bagger, Andrew Li Department of Management and Policy, University of Arizona, Tucson, AZ 85721, USA Received 4 February 2004 Available online 28 February 2006

Abstract The decoy eVect occurs when preferences between two alternatives reverse as a result of the manipulation of a third alternative (i.e., a decoy) such that it is dominated by only one of the two original alternatives. Previous research has demonstrated this eVect in employee selection decisions, but only when decisions were made by individuals. The present investigation was designed to test the generalizability of the phenomenon to decisions made by groups, and to determine the inXuence of process and outcome accountability on the decoy eVect. Results showed that the overall decoy eVect held for both individual and group decisions. However, for both individuals and groups, the decoy eVect held only when decision makers knew they would have to justify their decision processes. © 2006 Published by Elsevier Inc. Keywords: Context eVects; Boundary conditions; Group decision making; Employee selection; Accountability

Introduction Several authors have recommended that greater attention be given to judgment and decision making (JDM) research when studying employee selection, especially employer choices among job Wnalists (e.g., Highhouse, 1997; Huber, Neale, & Northcraft, 1987; Slaughter, Sinar, & Highhouse, 1999). This is because, researchers have argued, it is possible that JDM phenomena observed in the laboratory in non-selection contexts may also be observed in the context of employee selection (Highhouse, 1997; Slaughter et al., 1999). For example, previous research has shown evidence of a conWrmation bias, in that judgments of interview performance can be inXuenced by information from candidates’ job applications (Dipboye, Fontenelle, & Garner, 1984). Choices among job candidates have been shown to be inXuenced by the order in which candidates are interviewed (Highhouse & Gallo, 1997) and experi*

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mentally-manipulated missing candidate information (Jagacinski, 1991). One intriguing phenomenon that has received considerable research attention in the area of job-Wnalist choice is known as the decoy eVect. The decoy eVect occurs when preferences between two alternatives reverse as a result of the manipulation of a third alternative (i.e., a decoy) such that it is dominated by only one of the two original alternatives (Huber, Payne, & Puto, 1982). Consider the simulated employee selection scenario presented by Highhouse (1996); see Table 1. In one condition, participants were presented with Candidates A, B, and C1 (the decoy candidate). Two-thirds of these participants chose Candidate A. In a second condition, participants were again presented with Candidate A and B, but they were presented with C2 instead of C1. This time, two-thirds of the participants chose candidate B. The decoy candidate was not chosen by any participants in either experimental condition. Therefore, a candidate that was never chosen strongly inXuenced decision makers’ relative preferences for the other two candidates. As Highhouse noted, the decoy eVect violates the choice behavior axiom known as

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Table 1 Candidate assessment scores from Highhouse (1996) Candidate

Work sample score

Promotability score

Candidate A Candidate B Candidate C1 Candidate C2

7 5 7 4

66 80 54 80

Note. Each participant was presented with three candidates: Candidate A, Candidate B, and either Candidate C1 or Candidate C2.

regularity, which contends that the addition of an option to a choice set cannot increase the probability that an existing option will be chosen (Luce, 1959). It should be noted that in each of the scenarios described above, the decoy candidate was completely dominated by one candidate but not the other, a situation that is commonly referred to as asymmetrical dominance. One alternative completely dominates another when the dominant alternative (a) performs at least as well as the dominated alternative on all dimensions and (b) performs better than the dominated alternative on at least one dimension (Highhouse, 1996). The candidate that dominates the decoy in each scenario is referred to as the target. The decoy eVect has been observed in many diVerent studies and a range of applied contexts, including choices among consumer products (e.g., Heath & Chatterjee, 1995), apartments (Simonson, 1989), gambles (Wedell, 1991), and job oVers (Wedell & Pettibone, 1996). However, the generalizability of the results of previous studies may be somewhat limited by the relatively narrow range of experimental conditions under which the eVect has been observed. One important gap in the current state of knowledge on the decoy eVect is that virtually nothing is known about whether the phenomenon holds in group decision making situations. This is potentially problematic for the generalizability of this phenomenon to personnel decision making. In typical personnel selection systems, evaluations of job candidates involve multiple judges (Arvey & Campion, 1982; Highhouse & Bottrill, 1995). The group-selection method is familiar to those working in academia, where search committees or entire departments may make selection or placement decisions (Larson, Foster-Fishman, & Keys, 1994; Wittenbaum, 1998). Selection by committee is also common for higher-level positions in large organizations. Top management team members are uncomfortable with the idea of entrusting a single person with the responsibility of making selection decisions for managerial and professional jobs (Sessa, Kaiser, Taylor, & Campbell, 1998; Sessa & Taylor, 2000). In fact, Sessa et al. (1998) found that only 26% of highlevel employee selection decisions are made by a single individual. Thus, the overall purposes of the present investigation were to determine whether the decoy phenomenon that has been found to inXuence individual decision making

also inXuences group decision making, and to determine whether there are features of the choice environment that diVerentially inXuence group and individual decision making vis-à-vis the decoy eVect. SpeciWcally, in addition to the study of the decoy eVect in group decision making, we also studied the eVects of process accountability and outcome accountability on group and individual decision making. Below, we discuss the theory and previous research that led to our hypotheses. Theory and hypotheses Generalizability of the decoy eVect to group decision making The Wrst issue addressed in the present investigation was whether the decoy eVect would generalize to situations in which decisions are made by group consensus, rather than by individuals. Indeed, research on consensus requirements in group decision making suggests that decision making groups will be likely to prefer the candidate targeted by the decoy. Classic theory on group discussion in problem-solving proposes a social interaction hypothesis. Interaction between group members provides an accuracy-enhancement function and facilitates individual thought and task involvement (Holloman & Hendrick, 1972; Taylor & Faust, 1952; Watson, 1928). For example, in a forecasting exercise, Holloman and Hendrick found that group consensus decisions were more accurate than other types of group decisions, including averaged group decisions, appointed-leader decisions, two-person committee decisions, and majority vote. The researchers concluded that this was the result of the higher quantity and quality of group interaction in consensus decisions. This suggests that, even if some group members initially prefer the non-targeted candidate, the process of group discussion and consensus reaching should increase the likelihood that decision makers will increase the search for reasons to choose one candidate over the other and choose the dominating option. Accordingly, we hypothesized that the decoy eVect would surface in both the individual and group decision making conditions. Hypothesis 1. The decoy eVect will be observed in individual and group decision making. Moderating inXuence of decision accountability Previous theory and research have identiWed two diVerent types of decision accountability: Outcome accountability and process accountability. It is important to make a distinction between these unique constructs, because they have been operationalized diVerently and have diVerent predicted eVects. Outcome accountability has been deWned as a condition in which evaluation is based on the quality of the outcome of the response (Siegel-Jacobs & Yates, 1996).

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Outcome accountability has been operationalized by having a reward dependent upon participants’ performance (Siegel-Jacobs & Yates, 1996) and by telling participants that particularly eVective or ineVective outcomes would be shared with other students and instructors as examples of good or bad decision making (Simonson & Staw, 1992). Process accountability, on the other hand, may be deWned as a condition in which evaluation is based on the quality of the decision making process used to produce the response. It is accompanied by the need to justify one’s decision strategies, including the method used to evaluate and compare alternatives. Process accountability is often operationalized by asking participants to write essays about the processes or strategies they used, or to consent to be interviewed about the process (e.g., Markman & Tetlock, 2000). When making decisions on the basis of two predictors, a selection decision must be based on some combination of two reasons: The relative importance of the two predictors, and relations among the candidates across dimensions. Because decision makers who are held accountable for their processes will have to justify their strategies, the introduction of accountability is predicted to lead participants to engage in a more thorough comparison process. The reason-based choice paradigm suggests that when decision makers are faced with a diYcult choice, they naturally attempt to come up with reasons for and against each option (ShaWr, Simonson, & Tversky, 1993). When decision makers are accountable for their decision processes, the search for reasons is further stimulated, and a dominating relationship is likely to be seen as a good reason for choosing one option over another.1 As Simonson (1989, p. 161) noted, justifying a choice to others based on attribute weights or a trade-oV analysis can be a risky strategy if the consumer is uncertain about the evaluators’ perceptions of these weights and trade-oVsƒ in the context of the attraction eVects, an asymmetric dominance relationship might loom large among the reasons for choice if consumers are concerned about others’ evaluations of their decisions. 1 Note that this does not mean that we necessarily favor the dominance heuristic explanation for the decoy eVect over other potential explanations, such as context-dependent weighting (Tversky, Sattath, & Slovic, 1988). Either of these explanations for the decoy eVect would lead the dominating alternative to appear to be more justiWable. The dominance heuristic explanation suggests that individuals use dominance as a simplifying choice strategy (Huber et al., 1982). A contextdependent weighting strategy suggests that the attribute on which both the target and the decoy perform well is over-weighted relative to the predictor on which the non-targeted candidate performs well. Either of these potential justiWcations for preferring the target (i.e., “this candidate is not weaker than this third candidate on either dimension,” or “this attribute is more important”) would be reasonable arguments in favor of the target.

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In other words, participants who are accountable for their decision processes will likely view relations among the candidates across dimensions as more important, at least in part because they cannot know with certainty which of two previous performance dimensions is actually more important (Simonson, 1989). Simonson found that introducing the perception that the participants would have to justify their decisions increased the likelihood of the decoy eVect. He also found that the target was perceived to be easier to justify and less likely to be criticized by others. It is expected that those individuals and groups who expect to be accountable for their decision processes will focus on accountability and search for justiWable reasons for choosing one candidate over another, leading them to be more likely to choose the dominating candidate. Therefore, we hypothesized: Hypothesis 2. Process accountability will signiWcantly increase the strength of the decoy eVect for individuals and for groups. Despite the fact that outcome accountability and process accountability are conditions that are common in organizational life, we were able to locate only one study that has crossed an outcome accountability manipulation with a process accountability manipulation (Brtek & Motowidlo, 2002). Brtek and Motowidlo manipulated process accountability and outcome accountability to determine their eVects on the validity of participants’ ratings of videotaped interviews (i.e., the correlations between participants’ ratings of the performance of actual interviewees and performance ratings received by interviewees from their actual supervisors). In this study, process accountability led to higher validity of interview ratings (relative to a no process accountability condition) and outcome accountability led to lower validity of interview ratings (relative to a no outcome accountability condition). The two types of accountability did not interact signiWcantly to aVect validity. Other studies have also shown detrimental eVects of outcome accountability on decision making performance (e.g. Doney & Armstrong, 1996; Markman & Tetlock, 2000; Siegel-Jacobs & Yates, 1996; Simonson & Staw, 1992). For example, Simonson and Staw (1992) found that outcome accountability led to greater escalation of commitment, and Siegel-Jacobs and Yates (1996) found that outcome accountability led to reduced calibration (the relation between conWdence and accuracy) and greater judgmental inconsistency. Siegel-Jacobs and Yates suggested that the detrimental eVects of outcome accountability were due to increased stress combined with a desire to increase performance without knowledge of how to do so. In the present investigation, we were interested in the potential eVects of crossing the manipulations of

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reported other races or did not report. Students signed up for participation on the internet and were rewarded for their participation with course credit and entry into a drawing for cash prizes. Of the participants, 24.8% reported having previously made hiring decisions and 48.3% reported having previous work experience in retail sales, which was the hypothetical job for which participants made selection decisions in this study. Eighty-Wve percent of the participants were juniors or seniors. The design for this study was a 3 (Decoy Condition: Target—High Customer Service, Target—High Sales Performance, No Decoy) £ 2 (Process Accountability: Present or Absent) £ 2 (Outcome Accountability: Present or Absent) £ 2 Decision Maker (Individual or Group) between-subjects design. The n for each condition is presented in Table 2. Individuals were randomly assigned to conditions before arriving to participate. The relative diYculty of Wlling time slots with 4 or more participants led to an oversampling of individuals relative to groups.

individual versus group decision making, process accountability, and outcome accountability on the choice of the candidate targeted by the decoy. Although we felt it was important to study the inXuence of outcome accountability on the decoy eVect, in our opinion there was not enough previous theory or research to permit us to write formal hypotheses or make formal predictions. For example, whereas Brtek and Motowidlo (2002) did not observe a process accountability £ outcome accountability interaction, being inXuenced by a dominating relationship of the target to the decoy is substantively diVerent from rating the performance of interviewees, so we could not necessarily make the same prediction. Similarly, whereas outcome accountability might increase participants’ stress by focusing decision makers on the correct answer without knowledge of how to determine what the answer is (Lerner & Tetlock, 1999; Siegel-Jacobs & Yates, 1996), this stress may be lessened or have a weaker inXuence when decision makers are also accountable for their decision processes, or when decisions are made in groups and accountability is shared by the group members. Thus, we explored the eVects of outcome accountability as a set of research questions: Does outcome accountability lead to a stronger or weaker decoy eVect? Does outcome accountability interact with process accountability to inXuence the decoy eVect? And Wnally, does outcome accountability interact with process accountability and group versus individual decision making to inXuence the decoy eVect?

Procedure Participants were presented with a hypothetical employee selection scenario. Participants were told that they were in charge of selecting the best salesperson candidate from a group of 2 (in the No Decoy condition) or 3 (in the Decoy conditions) candidates for a retail organization called RugMart. RugMart was described as a local San Diego, California retailer of rugs for home use. The initial sales training program was described as occurring on the job and in the downtown store, and as one that included sales techniques and customer service training. Participants were told that initial internal promotions occur by transfers from the downtown location to one of the four suburban stores, and that their task was to replace a top associate from the Del Mar, California store with 1 of the 2 or 3 candidates presented to them. As opposed to the typical matrix presentation format of attribute information, we attempted to make the decision more complex and realistic by presenting candidate sales quantity and service quality in separate folders

Method Participants and design Participants were 605 undergraduate business and psychology students (51% female, mean age D 21.6) at a large university in the southwestern United States. Of the participants, 63% were White, 13% were Hispanic, 10% were Asian-American, 5% were Middle Eastern, 3% were African-American, and the remaining 6% Table 2 Number of participants by experimental condition Process accountability

No process accountability

Outcome acct.

No outcome acct.

Outcome acct.

No outcome acct.

Individual decisions No decoy Target—high sales Target—high customer service

10 15 15

10 16 15

9 15 15

11 15 15

Group decisions No decoy Target—high sales Target—high customer service

32 (8 groups) 40 (10 groups) 40 (10 groups)

36 (9 groups) 40 (10 groups) 40 (10 groups)

32 (8 groups) 40 (10 groups) 36 (9 groups)

32 (8 groups) 40 (10 groups) 40 (10 groups)

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Table 3 Summary of candidate qualiWcations Candidate

Sales

Customer service

Level

Total sales 4th quarter 2003 ($)

Percentage of store total (%)

Supervisor rating (1–9)

Level

Average rating (1–5)

Example customer comment

J. Smith

High

30,595

15.3

9

Average

3.67

M. Johnson

Average

22,645

11.3

6

High

4.67

A. O’Briena A. O’Brienb

High Low

30,350 16,210

15.2 8.1

9 2

Low High

1.67 4.67

“It was what I expected. Nothing more, nothing less.” “Excellent service. Nice, polite, friendly. I would come back.” “Bad service.” “Wonderful service.”

for each candidate, each with a simulated sales report from the 4th quarter of 2003 and handwritten copies of customer comment cards from the same period. Order of presentation of the candidates was counterbalanced. Participants were asked to keep the information in the folders, but were provided space to take notes on the information they read. Participants read the information from the folders, and either made their individual decision or discussed the candidate qualiWcations in groups and made the group decisions. After answering some supplementary questions, participants were debriefed and dismissed.

Service candidate.2 O’Briena, the High Sales—Low Customer Service candidate, was the decoy candidate that targeted Smith (High Sales—Average Customer Service). When O’Briena was included in the choice set, Smith was targeted because O’Briena was asymmetrically dominated—dominated by Smith but not by Johnson. O’Brienb, the Low Sales—High Customer Service candidate, was the decoy candidate that targeted Johnson (Average Sales—High Customer Service). When O’Brienb was included in the choice set, Johnson was targeted because O’Brienb was asymmetrically dominated—dominated by Johnson but not by Smith.

Manipulations

Outcome accountability Participants were randomly assigned to an Outcome Accountability (OA) or a No Outcome Accountability (No OA) condition. In both conditions, participants were told that the information they would use to make the decision was based on an actual promotion decision situation in a real organization. They were told that, in reality, all (or both) of the candidates were actually promoted, but over the next several years, one of the candidates far outperformed the other(s) and won the organization’s equivalent of an “employee of the year” award. Instructions included the statement, “One purpose of this study is to assess whether undergraduate business students can predict future performance on the basis of past performance.” Individuals in the OA condition, however, were also told that those that chose the correct candidate would be entered into a drawing for a $100 prize. Groups were told that groups that gave the correct answer would be entered into the drawing as a group, and each member of the winning group would receive $100. Those in the No OA conditions were simply told

As noted above, the 4 independent variables were completely crossed in a 2 £ 3 £ 2 £ 2 design, resulting in 24 experimental conditions. Individual versus group decision making Individual decisions were made alone. Each individual read the provided information and completed the questionnaire in a separate room. Group decisions were made in 4-person groups. Participants were placed in groups at the outset of the experiment. Participants were asked to make a group decision, while other questionnaire items were completed individually following the group decision. Four-person groups were utilized to maximize the potential for disagreement, and to minimize the potential for a lone dissenter simply agreeing with the majority decision. Group discussions were audiotaped. The gender makeup of the groups varied and was normally distributed. Of the 111 decision making groups, 10 had 0 females, 27 had 1 female, 39 had 2 females, 25 had 3 females, and 10 groups had 4 females. Decoy The decoy manipulation consisted of three conditions. Candidate qualiWcations are summarized in Table 3. Inspection of Table 3 reveals that Smith was presented as the High Sales—Average Customer Service candidate and Johnson was the Average Sales—High Customer

2 We had previously tested the materials for these two candidates in a pilot study with 21 upper-level undergraduate students (38% female; mean age D 21.8 years) as participants. Participants were asked to indicate their Wnal choice and the overall performance of the candidates. A t test showed no diVerence between the two candidates on overall performance, t (20) D 0.77, p D .45. Not unexpectedly, participants showed a slight preference for service quality over sales quantity; 12 participants (57%) chose the candidate with stronger customer service; 9 participants (43%) chose the candidate with stronger sales.

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that they (or their group, in the group condition) would be entered into a drawing for a $100 prize for themselves (or for each member of their group). This is consistent with how the prizes were actually determined: One individual was randomly selected to receive a $100 cash prize, and one 4-person group was randomly selected for each member to receive a $100 cash prize. Process accountability We randomly assigned participants to either a Process Accountability (PA) condition or a No Process Accountability (No PA) condition. In the PA condition, the instructions included the following paragraph (taken from the group decision making condition): Once your group has completed this decision making task, each of you will be asked to write a short essay explaining the decision strategies that you (as a group) used to come up with a decision. Once you have completed this essay, it will be read and evaluated by a graduate student. We will ask you to give your contact information on the essay; a portion of the study participants will be contacted in a short while to come back for an interview regarding the essay. This interview will be audiotaped so you will need to sign a separate consent form authorizing audiotaping of this conversation. A second purpose of this study is to assess the strategies undergraduate business students use when making promotion decisions. In the PA condition, participants were also asked to write a short (300–450 word) essay “explaining the strategies that you (as a group) used to come up with a decision.” Participants were asked to provide email contact information, and were told that a portion of study participants would be contacted to return for an interview. Participants would be asked to sign a separate consent form for this interview. In the no PA conditions, participants did not receive any of the instructions pertaining to essays, evaluation of essays, or additional interviews.

Results We Wrst tested for an overall decoy eVect in both the individual decision making conditions and the group decision making conditions. In the Wrst analysis, we tested for the decoy eVect in individual decision making, including in our analysis the control group. We found the eVect to be signiWcant, 2 (2, N D 161) D 12.50, p < .01, 2 D .08. Choice percentages are presented in Table 4. Inspection of Table 4 reveals that, when no decoy candidate is presented, the high service-quality candidate, Johnson, is overwhelmingly preferred (85%). This is contrast to the pilot study, in which individuals showed only a slight preference for the candidate strong on customer service. The presence of the decoy used to target the high

Table 4 Separate decoy eVects within each condition of decision making context Decision making context

Target

Percentage choosing high quality candidate (%)

No decoy High quality High quantity

85 (N D 40) 83 (N D 60) 59 (N D 61)

No decoy High quality High quantity

82 (N D 32) 90 (N D 40) 49 (N D 39)

Individual decisions

Group consensus decisions

Note. For individual decisions 2 (2, n D 161) D 12.50, p < .01, 2 D .08. For group consensus decisions, 2 (2, n D 110) D 18.50, p < .01, 2 D .17.

service-quality candidate does not aVect the choice percentage of this candidate (83%). However, the presence of the decoy candidate used to target the high salesquantity candidate reduces the percentage of individuals choosing the high quality candidate by 26%, to 59%. An analysis of a portion of the data that included only the conditions in which there was a decoy candidate showed a signiWcant preference shift across the conditions, 2 (1, N D 121) D 8.70, p < .01, 2 D .07. Next, we turned to the group-level decisions. An analysis of the decoy eVect when the control group was included showed an overall decoy eVect, 2 (2, N D 111) D 18.50, p < .01, 2 D .17. Therefore, Hypothesis 1 was supported. Choice percentages are presented in Table 4. As with the individual decisions, the overwhelming majority of the groups presented with only 2 candidates chose Johnson, the high service-quality candidate (82%). The addition of the decoy used to target the high service-quality candidate only marginally increased the percentage of groups choosing this candidate (90%). However, the addition of the decoy candidate used to target the high sales candidate, Smith, reduced the percentage of groups choosing the high service-quality candidate to 49%. An analysis of a portion of the data that included only the conditions in which there was a decoy candidate showed a signiWcant preference shift across the conditions, 2 (1, N D 78) D 15.41, p < .01, 2 D .20. Next, we turned our attention to Hypothesis 2, which predicted that PA would signiWcantly increase the strength of the decoy eVect. Because of the undersampling of the control condition, which was of less interest than the other groups for considering the eVects of accountability, in this set of analyses we only included the participants who were presented with a decoy candidate. For the sake of parsimony, we also recoded the choice data to reXect whether the individual or group had chosen the targeted candidate (1 D target chosen; 0 D otherwise). Next, we conducted a 2 (PA: present versus absent) £ 2 (choice of target versus choice of non-target) chi-square analysis, and observed that the eVect did

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not reach the conventional level of signiWcance at p < .05, but was marginally signiWcant at p < .10, 2 (1, N D 197) D 3.24, p D .07, 2 D .02. In addition, the results were in the predicted direction; the targeted candidate was chosen 71% of the time when decision makers were accountable for their decision processes, and 58% of the time when they were not accountable. Thus, Hypothesis 2 received modest support. To explore these eVects further, we compared the eVects across experimental conditions. First, we analyzed individual decisions; choice percentages are presented in Table 5. When individuals were held accountable for neither their decision process nor their decision outcome, the decoy eVect was not signiWcant, 2 (1, N D 30) D 1.29, p D .26, nor was it signiWcant when individuals were held accountable for their outcomes but not their decision processes, 2 (1, N D 30) D .60, p D .44. When individual were held accountable for their decision processes but not their outcomes, the decoy eVect was signiWcant, 2 (1, N D 31) D 4.21, p < .05, 2 D .14. Table 5 shows that when the high quality candidate was targeted, 93% of individual participants chose the high quality candidate, whereas only 63% of individuals chose this candidate when the high quantity candidate was targeted. Similarly, when individuals were held accountable for their decision processes and decision outcomes, the decoy eVect was again signiWcant, 2 (1, N D 30) D 4.66, p < .05, 2 D .16. When the high quality candidate was targeted, 93% of individual participants chose the high quality candidate, whereas only 60% of individuals chose this candidate when the high quantity candidate was targeted. Thus, for individual decision makers, the decoy eVect was observed only when decision makers were made accountable for their processes.

Analyses of the decoy eVect in groups by the diVerent accountability conditions showed that the decoy eVect was not present in the no accountability condition, 2 (1, N D 19) D 1.02, p D .31, or the OA-only condition, 2 (1, N D 20) D 1.98, p D .16. When only PA was introduced, however, the eVect was signiWcant, 2 (1, N D 17) D 4.55, p < .05, 2 D .24. Inspection of Table 6 reveals that, in this accountability condition, 90% of the groups chose the high service quality candidate when this candidate was targeted, whereas only 44% of the groups chose this same candidate when the high sales quantity candidate was targeted. Similarly, the last set of cells in Table 6 shows that under conditions of PA and OA, they decoy eVect was strong and signiWcant, 2 (1, N D 20) D 10.77, p < .01, 2 D .54. Table 6 shows that, in this condition, 100% of the groups chose the high service candidate when this candidate was targeted, whereas only 30% of the groups chose this candidate when the high sales candidate was targeted. Thus, for group decision making, as for individual decision making, the decoy eVect only surfaced when decision makers were accountable for their decision process. The support for Hypothesis 1, therefore, must be qualiWed by our Wndings concerning Hypothesis 2. Our Wrst research question concerned whether OA inXuenced the decoy eVect. To examine this, we conducted a 2 (OA) £ 2 (choice of target) chi-square analysis. This value was not signiWcant, 2 (1, N D 197) D .16, p D .69, suggesting that OA did not have direct inXuence on whether participants chose the candidate targeted by the decoy. Our second research question was whether OA interacted with PA to inXuence the decoy eVect. To examine this, we conducted a hierarchical moderated logistic

Table 5 Choice percentages by decoy and accountability conditions, individual decision making

Table 6 Choice percentages by decoy and accountability conditions, group decision making

Accountability condition

Accountability condition

Target

Percentage choosing high quality candidate (%)

No process, no outcome

Target

Percentage choosing high quality candidate (%)

No process, no outcome High quality 73 (N D 15) High quantity 53 (N D 15)

Outcome, no process

High quality High quantity

89 (n D 9) 70 (n D 10)

High quality High quantity

80 (n D 10) 50 (n D 10)

High quality High quantity

90 (n D 10) 44 (n D 9)

High quality High quantity

100 (n D 10) 30 (n D 10)

Outcome, no process High quality 73 (N D 15) High quantity 60 (N D 15)

Process, no outcome

Process, no outcome High quality 93 (N D 15) High quantity 63 (N D 16)

Process and outcome

Process and outcome High quality 93 (N D 15) High quantity 60 (N D 15)

Note. For no process, no outcome, 2 (1, N D 30) D 1.29, p D .26. For outcome, no process, 2 (1, N D 30) D .60, p D .44. For process, no outcome, 2 (1, N D 31) D 4.21, p < .05, 2 D .14. For process and outcome, 2 (1, N D 30) D 4.66, p < .05, 2 D .16.

Note. For no process, no outcome, 2 (1, N D 19) D 1.02, p D .31. For outcome, no process, 2 (1, N D 20) D 1.98, p D .16. For process, no outcome, 2 (1, N D 19) D 4.21, p < .05, 2 D .24. For process and outcome, 2 (1, N D 20) D 10.77, p < .01, 2 D .54.

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regression analysis, regressing choice of target on the OA and PA main eVects in the Wrst step, and on the OA £ PA interaction term in the second step. The interaction term was not signiWcant, 2 (1, N D 197) D 0.29, p D .59, suggesting that the inXuence of OA on the decoy eVect is not dependent upon whether decision makers were also accountable for their decision processes. Our third and Wnal research question concerned whether OA interacted with PA and type of decision maker (individual versus group) to inXuence the decoy eVect. To examine this possibility, we conducted a 3stage hierarchical logistic regression analysis in which OA, PA, and decision making party (DMP) were entered on the Wrst step, the three 2-way interaction terms were entered on the second step, and the 3-way interaction term (OA £ PA £ DMP) was entered on the third step. This analysis showed only a signiWcant weight for the PA main eVect, consistent with analyses for Hypothesis 2. Thus, it did not appear that OA exerted much of an eVect in the present investigation. Process evidence from audiotaped discussions To further investigate these Wndings, we analyzed the audiotaped discussions of the groups that had been assigned to one of the two conditions in which there was a decoy option. Of these 79 groups, 12 of the audiotapes were not audible, leaving a total of 67 tapes to analyze. After listening to several of the audiotapes initially, it was clear that the groups were using multiple strategies to determine the preferred candidate. To provide some guidance in analyzing the group discussions about the candidates, we elected to code the discussions as including or not including conversations that were relevant to one of the four theoretical explanations for the decoy eVect (Highhouse, 1996): Loss aversion, range-frequency eVects, use of the dominance heuristic, and context-dependent weighting. The loss aversion explanation (Tversky & Kahneman, 1991) suggests that the decoy candidate is used as a reference point, and that the decision maker evaluates the target and non-targeted candidate based on how diVer they from the decoy in expected loss. For example, when the decoy candidate has high sales and low customer service, the candidate with high sales and average customer service (i.e., the target) is preferred because this candidate represents no loss on sales and a small gain on customer service. The candidate with average sales and strong customer service is less attractive because, while a large gain in customer service is achieved, it comes at the price of a loss on sales. A quotation exemplifying a lossaversion strategy was: “Johnson is in the dead middle; Smith on the other hand ƒ he is obviously good at something, his customers buy ƒ but are they happy with it? They could be buying once and not be coming back again.”

Another explanation of the decoy eVect, the use of a dominance heuristic, suggests that the target is chosen because this option dominates the decoy (Huber et al., 1982; Wedell, 1991). That is, selection of the target simpliWes the choice process by requiring the decision maker to make fewer trade-oVs (Wedell, 1991). The following discussion among group members illustrates the use of a dominance heuristic: “Johnson’s customer service record compared to O’Brien is basically the same; then you look at Johnson’s sales record compared to O’Brien, he got a higher performance rating.” Another explanation is based on range-frequency theory (e.g. Parducci, 1974). According to this explanation, the decoy increases preferences for the target by increasing range on the dimension on which the target is deWcient and by increasing the frequency of scores higher than the non-targeted candidate on the other dimension (Huber et al., 1982). A quotation from the group discussion that was marked as evidence for this explanation was: “The other two (Johnson and O’Brien) are nice guys and this Smith guy is a jerk.” Finally, the context-dependent weighting explanation for the decoy eVect (Tversky et al., 1988) is that the dimension on which the target and decoy excel is given more weight in the Wnal decision. The idea behind this explanation is that the choice context inXuences decision makers to construct their preferences for one dimension at the time of choice (Payne, Bettman, & Johnson, 1993). Evidence for the use of a context-dependent weighting strategy was evident in this example quotation from a group discussion: “The whole purpose of owning a store is to make a proWt; if I was a manager I would promote a person who on paper is making a lot more, assuming they are both decent guys.” The second and third authors analyzed the audiotaped group discussions to determine whether groups mentioned utterances related to one of the four explanations described above. It was found that 6 of the groups did not mention anything related to these explanations—in each of these groups, each of the group members agreed on the preferred candidate after reviewing the materials, and there was no group discussion. In the remaining 61 groups, 24 groups discussed reasons related to loss aversion, 18 discussed reasons related to range and frequency, 15 discussed the dominance relationship, and 47 discussed the relative importance of the two dimensions. On average, the number of decision strategies use by each group was 1.55 (SD D 0.91). Of the 61 groups that showed evidence of some kind of strategy, 29 used 1 strategy, 23 used 2 strategies, 7 used 3 strategies, and 2 used 4 strategies.

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Next, we determined whether the PA manipulation was related to particular kinds of strategy use. For each strategy, we again conducted 2 (PA) £ 2 (strategy use) chi-square analyses. We found that for loss aversion, 2 (1, N D 61) D .89, p D .34; for the use of a dominance heuristic, 2 (1, N D 61) D 15.52, p < .01, 2 D .25; for recognizing range and frequency, 2 (1, N D 61) D 5.42, p < .05, 2 D .09; and for attribute weighting, 2 (1, N D 61) D .46, p D .50. We found that, relative to those groups not accountable for their processes, process-accountable groups were signiWcantly less likely to mention the dominance relationship or to mention reasons related to range and frequency (no PA D 97%; PA D 53%). This suggests that process-accountable groups seemed to use simpler strategies than groups not accountable for their processes. Indeed, we found that process-accountable groups (M D 1.15, SD D 0.75), on average, used fewer diVerent types of strategies than non-process-accountable groups (M D 1.84, SD D 1.05); t D 3.18, p < .01. We also tested the relation between choice of the target candidate and strategy use. Chi-square analyses showed that evidence of loss aversion, dominance heuristic, and recognition of range and frequency were not signiWcantly associated with choice of the target candidate, 2 (1, N D 61) D .88, p D .35, 2 (1, N D 61) D 1.21, p D .27, and 2 (1, N D 61) D .34, p D .56, respectively. However, groups choosing the target were more likely to mention relative importance of the attribute weights, 2 (1, N D 61) D 7.52, p < .01, 2 D .12. Eighty-Wve percent of the groups that chose the target mentioned the relative importance of weights, while only 50% of groups that chose the non-target mentioned relative importance.

Discussion The Wrst goal of the present investigation was to determine whether the decoy phenomenon generalizes to decisions made in groups. On the basis of theory and research on consensus requirements in group decision making (e.g. Holloman & Hendrick, 1972), Hypothesis 1 predicted that the decoy eVect would be observed in groups. Hypothesis 1 was supported. It is worth noting that, although not hypothesized, the decoy manipulation actually appears to be stronger on group decision making than on individual decision making. The manipulation of the decoy candidate accounted for twice as much variance in decision making among groups as it did among individuals (2 D .17 for groups; 2 D .08 for individuals). Turning our attention only to the conditions of PA, in which the decoy eVect was signiWcant, the eVects are much larger for groups than for individuals (2 D .38 for groups; 2 D .15 for individuals). It is possible that the additional accountability to one’s group members led to this stronger decoy eVect in groups. For example, when individuals who were placed in groups read the

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materials, they may have been trying to determine which candidate would be the most justiWable in the eyes of the other group members before stating their preferred candidate to the group. However, this explanation is post hoc, and needs greater theoretical elaboration and empirical replication before it can be accepted. A Wnergrained analysis of the individual judgments and decisions that take place before group members begin discussion would be a worthwhile avenue for future research. The second goal of this research was to understand the inXuence of process accountability on the decoy eVect in groups. Hypothesis 2, which received modest support, predicted that the decoy eVect would be stronger when participants were told that they would have to explain their decision processes in an essay and that they may be interviewed about their essays at a later date. Thus, initially, it might seem as though individuals and groups use more complex and analytic decision strategies when they are made accountable for their decision processes (McAllister, Mitchell, & Beach, 1979), leading them to recognize the dominating relationship and identify the target as the preferred candidate (Simonson, 1989). The audiotaped process evidence from the group discussions, however, tells a diVerent story. Our analysis of the tapes suggested that those made accountable for their decision processes may have been more likely to choose the target candidate primarily because they quickly identiWed the dimension on which the target and the decoy were superior as being more important, supporting a context-dependent weighting explanation for the decoy eVect (Huber et al., 1982; Tversky et al., 1988). In fact, groups accountable for their processes seemed to use fewer decision strategies overall, and were less likely to mention a dominating relationship or to discuss reasons related to range and frequency than groups who were not process-accountable. These results are unique, and somewhat interesting, because previous theory and research have suggested that PA leads individuals to think in more complex ways, which would suggest that participants in processaccountable groups would use more complex strategies. Our analyses obviously suggested otherwise. As one reviewer noted, the relatively stronger decoy eVect in the process-accountable condition was likely due to decision makers’ focus on accountability and the need to justify, which appears to have led group members to translate the dominance relationship to a shift in importance weights rather quickly. Therefore, as another reviewer noted, the shift in weight may be more of a justiWcation than a cause of the decoy eVect. In rather serendipitous fashion, then, the present investigation may have shown that while accountability often leads to using a larger number of strategies and integratively complex thinking (Lerner & Tetlock, 1999), a focus on accountability

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could also cause decision makers to narrow their overall strategy by eliminating reasons for one candidate or the other that seem to be less justiWable. What the group discussions could not speak to, however, were the cognitive strategies used by individuals when they were processing the information prior to discussion. It is quite possible that many individuals in the process-accountable groups considered the dominating relationship, or used the decoy as a reference point, or recognized the frequency of data points above the nontargeted candidate, to determine that the target was the preferred option, but they did not verbalize this during the group discussion. To examine this possibility, we next re-read the essays written by those in the process-accountable groups. Although we did not Wnd many essays that reXected the strategies described above, we did notice a rather interesting trend. Virtually all essays written by individuals (or individuals in groups) that chose the targeted candidate contained information indicating that the dimension on which the target and the decoy were superior was more important, consistent with the context-dependent weighting explanation. This was expected. Interestingly, however, we found that many essays also indicated that the dimension on which the target was average (i.e., sales when the high-service quality candidate was targeted; service when the high-sales candidate was targeted) was the performance dimension that was easier to improve in the future. This was often used as the secondary justiWcation for the decision. Below are some example quotations from essays using improvability as justiWcation: “Ultimately, we chose Smith on the basis that customer service skills would be easier taught than salesperson skills (Johnson).” (High sales candidate targeted.) “We decided to go with Johnson because it is easier to improve on your sales skills than personality.” (High service candidate targeted.) “Since it is very diYcult to teach someone how to be a good salesman, high sales and above average customer service is very beneWcial.” (High sales candidate targeted.) “We all agreed that customer service was very important and a skill that would be harder to develop or learn.” (High service candidate targeted.) Turning back to Table 3, it appears that when either the high sales or high quality candidate was the worst performer on a particular dimension (e.g., Johnson has the lowest performance on sales when O’Briena was presented), this dimension is seen as being more diYcult to improve than a dimension on which the candidate’s scores lie in the middle (e.g., Smith’s average customer service is the middle of the three scores when O’Briena was presented). This explanation is somewhat similar to the range-frequency explanation (i.e., “Smith’s service is

not so bad, when compared to O’Brien’s”), but the potential for improvement appears to be a qualitatively diVerent justiWcation. Those accountable for their decision processes appear to have pushed themselves to generate additional reasons why the targeted candidate was preferred, and in many cases, they settled on “improvability” as a reason. These results suggest the value of studying the decoy eVect in an employee selection context, as potential for improvability would not likely factor into justiWcation for choices of consumer products or gambles. A third goal of this study was to explore the eVects outcome accountability on the decoy eVect in both individual and group decision making. We found that outcome accountability did not have a statistically signiWcant eVect, nor did it signiWcantly interact with any of the other independent variables. These Wndings are in contrast with several studies discussed earlier that showed a detrimental eVect of outcome accountability (e.g. Brtek & Motowidlo, 2002). It is possible that while outcome accountability does inXuence some types of decision making performance (e.g. Siegel-Jacobs & Yates, 1996; Simonson & Staw, 1992), telling participants that rewards are contingent upon choosing the best overall candidate does not inXuence this particular kind of context eVect. We believe that it is worth noting that the strongest decoy eVect (2 D .54) did occur in groups that were accountable for both their processes and outcomes (see Table 6). However, given that the diVerences in eVect sizes across conditions were not statistically signiWcant, it would not be appropriate to speculate on this further. Nevertheless, because outcome accountability and process accountability are commonly present in organizational decision making situations, we believe it would be worthwhile to continue to study potential OA £ PA interactions in other contexts. A supplementary goal of the present investigation was to gain some understanding of increased complexity of the experimental stimuli as a potential boundary condition on the decoy eVect. That is, whereas most previous research on the decoy eVect has presented numerical attributes in a matrix format, in the present investigation we used separate folders for each candidate, in which customer comment cards and performance appraisal documents included both quantitative and qualitative information. In the current study, the decoy eVect was not signiWcant in the absence of accountability for the decision process. This was likely because decision makers were inXuenced more by participants’ perceptions about the relative importance of the dimensions, and less by the context that is changed as a result of the manipulation of the decoy. Our results are similar to those of Ratneshwar, Shocker, and Stewart (1987), who found that the decoy eVect was much weaker, but still signiWcant, under conditions of meaningful elaboration of

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consumer products. Perhaps one reason for the diVerences across the two studies—that is, that the eVect is weakened in Ratneshwar et al. (1987) and is eliminated in the present investigation—is that simulated Wles with job candidate information may be more meaningful to decision makers than elaborated textual information about consumer products such as televisions, orange juice, and beer. When information is more meaningful, biases that favor one dimension as being more important may be more likely to inXuence decision making. It is also important to point out that only the candidate that was high on sales performance was helped by the presence of the decoy candidate. In part, this Wnding in the present investigation was due to the fact that when no decoy candidate was present, individuals and groups overwhelmingly preferred the candidate that was high on customer service. This was likely because nearly half of the participants had previous work experience in retail organizations. The fact that such a strong preference shift occurred toward the high sales candidate when this candidate was targeted indicates the strength of the decoy phenomenon.

Limitations and conclusion Although the Wndings we observed serve to increase our conWdence that the phenomenon is generalizable to applied settings, there are some limitations that must be noted. First, it appears that groups that were presented with decoy candidates had minimal disagreement, and came to consensus by majority. Therefore, we believe it would be very interesting in future research to use a confederate in groups. As one reviewer suggested, groups could be randomly assigned to a situation in which the confederate argued for either the targeted candidate or the non-targeted candidate (i.e., the competitor). This would further help to determine whether group members will explicitly argue for the targeted candidates with reasons related to the dominating relationship. As far as we are aware, this was only the second study to cross manipulations of process accountability and outcome accountability conditions, as most previous research has left them as separate experimental conditions (Doney & Armstrong, 1996; Markman & Tetlock, 2000; Siegel-Jacobs & Yates, 1996; Simonson & Staw, 1992). The manipulation of accountability in the present investigation serves to enhance generalizability of our Wndings to employee selection decisions in organizations, as those making selection decisions can expect to be accountable for the outcome and the process. That is, they will personally have to work with the individual who is hired, or if not, they will likely have to justify their choice to others who will have to work with the new hire. In addition, it is interesting to note that it is only when process accountability is imposed that the

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decoy eVect becomes signiWcant. Although increases in accountability are often implemented to solve problems in organizations (Frink & Klimoski, 1998) and in other areas (Hammond, 1991; Sato, 1989), in the case of the decoy eVect, they may cause more problems than they solve. It is worth considering how often a phenomenon such as the decoy eVect is likely to be observed in employee selection settings, given that the setting in the present investigation is somewhat contrived. That is, in the current study, decision makers did not actually have to work with the individuals they chose, and therefore did not face the same consequences for making a poor decision as would someone in the workplace. However, eVorts were made to create conditions that were similar to real-world personnel decision making (complex stimulus materials concerning sales performance and customer service ratings, and increased decision maker accountability for the decision process and decision outcome). As the conditions arguably became more similar to the conditions in which actual personnel selection decisions are made, (i.e., when decisions were made in groups and were subject to process accountability), the decoy eVect became stronger. It should also be noted that previous research has also suggested that the decoy eVect is more than merely lazy decision making (e.g. Slaughter et al., 1999). In an intriguing study, Pan, O’Curry, and Pitts (1995) showed evidence for a decoy eVect in the 1992 presidential elections. Pan et al. asked respondents to rate George Bush, Bill Clinton, and Ross Perot on national defense and health care on 7-point scale, and asked them to choose one candidate. When Perot was perceived to be asymmetrically dominated by Bush, respondents chose Bush 56% of the time. When Perot was perceived to be asymmetrically dominated by Clinton, Clinton was chosen 79% of the time. The fact that participants in this study were not instructed on how alternatives were to be perceived provides strong evidence for the potential for decoy eVects in real-world decision making. Taken together, it seems reasonable to suggest that when people perceive dominating relations among alternatives in employee selection settings, it is very much possible for a decoy eVect to occur. To avoid the decoy candidate inXuencing the decision, it will be important for organizations to specify with precision the weights given to various predictors in the selection process. However, it is important to note that Highhouse (1996) observed the decoy eVect even when respondents were asked to choose the more important predictor prior to viewing candidate information. Thus, to avoid the decoy eVect, not only must decision makers provide explicit weights for the assessments to be used in making choices among job Wnalists, but they must also use the preassigned weights when making a Wnal decision. In addition to studying boundary conditions on the decoy eVect and other decision making phenomena, we strongly believe it is also important that we begin to

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study the eVects of decision making training on the proliferation of errors. Whereas the goal of JDM research on these phenomena may be to describe anomalous decision making behavior, industrial-organizational (I-O) psychologists should be just as concerned about changing it (e.g. Highhouse, 2001). For example, I-O psychologists have long been aware of the potential judgment errors involved in performance appraisal and have experimented with various methods of reducing such errors, most notably frame-of-reference training (e.g. Gully, Payne, Koles, & Whiteman, 2002; Schleicher, Day, Mayes, & Riggio, 2002). Other researchers have experimented with ways to reduce sunk cost eVects and escalation of commitment (Bornstein & Chapman, 1995; Heath, 1995; Simonson & Staw, 1992). Given that a decoy candidate can aVect which candidate is chosen for a vacancy, making organizational decision makers aware of the phenomenon and helping them to avoid it becomes all the more important.

Acknowledgments We are grateful to Jim DiefendorV for helpful comments on an earlier version of this article. We also thank Christina West for her assistance with data collection.

References Arvey, R. D., & Campion, J. E. (1982). The employment interview: A summary and review of recent research. Personnel Psychology, 35, 281–322. Bornstein, B. H., & Chapman, G. B. (1995). Learning lessons from sunk costs. Journal of Experimental Psychology: Applied, 1, 251–269. Brtek, M. D., & Motowidlo, S. J. (2002). EVects of procedure and outcome accountability on interview validity. Journal of Applied Psychology, 87, 185–191. Dipboye, R. L., Fontenelle, G. A., & Garner, K. (1984). EVects of previewing the application on interview process and outcome. Journal of Applied Psychology, 69, 118–128. Doney, P. M., & Armstrong, G. M. (1996). EVects of accountability on symbolic information search and information analysis by organizational buyers. Journal of the Academy of Marketing Science, 24, 57–65. Frink, D. D., & Klimoski, R. J. (1998). Toward a theory of accountability in organizations and human resource management. In G. R. Ferris (Ed.), Research in personnel and human resources management (Vol. 16, pp. 1–51). Greenwich, CT: JAI Press. Gully, S. M., Payne, S. C., Koles, K. L., & Whiteman, J. K. (2002). The impact of error training and individual diVerences on training outcomes: An attribute-treatment interaction perspective. Journal of Applied Psychology, 87, 143–155. Hammond, A. L. (1991). Calculating national accountability for climate change. Environment, 33, 11. Heath, C. (1995). Escalation and de-escalation of commitment in response to sunk costs: The role of budgeting and mental accounting. Organizational Behavior and Human Decision Processes, 62, 38–54. Heath, T. B., & Chatterjee, S. (1995). Asymmetric decoy eVects on lower-quality versus higher-quality brands: Meta-analytic and experimental evidence. Journal of Consumer Research, 22, 268–284.

Highhouse, S. (1996). Context-dependent selection: EVects of decoy and phantom job candidates. Organizational Behavior and Human Decision Processes, 65, 68–76. Highhouse, S. (1997). Understanding and improving job-Wnalist choice: The relevance of behavioral decision research. Human Resource Management Review, 7, 449–470. Highhouse, S. (2001). Judgment and decision making research: Relevance to industrial and organizational psychology. In N. Anderson, D. S. Ones, H. K. Sinangil, & C. Viswesvaran (Eds.), Handbook of industrial, work, and organizational psychology (pp. 253–286). Thousand Oaks, CA: Sage. Highhouse, S., & Bottrill, K. V. (1995). The inXuence of social (mis)information on memory for behavior in an employment interview. Organizational Behavior and Human Decision Processes, 62, 220–229. Highhouse, S., & Gallo, A. (1997). Order eVects in personnel decision making. Human Performance, 10, 31–46. Holloman, C. R., & Hendrick, H. W. (1972). Adequacy of group decisions as a function of the decision-making process. Academy of Management Journal, 15, 175–184. Huber, V. L., Neale, M. A., & Northcraft, G. B. (1987). Decision bias and personnel selection strategies. Organizational Behavior and Human Decision Processes, 40, 136–147. Huber, J., Payne, J. W., & Puto, C. (1982). Adding asymmetrically dominated alternatives: Violations of regularity and the similarity hypotheses. Journal of Consumer Research, 9, 90–98. Jagacinski, C. M. (1991). Personnel decision making: The impact of missing information. Journal of Applied Psychology, 76, 19–30. Larson, J. R., Foster-Fishman, P. G., & Keys, C. B. (1994). Discussion of shared and unshared information in decision-making groups. Journal of Personality and Social Psychology, 67, 446–461. Lerner, J. S., & Tetlock, P. E. (1999). Accounting for the eVects of accountability. Psychological Bulletin, 125, 255–275. Luce, R. D. (1959). Individual choice behavior. New York: Wiley. Markman, K. D., & Tetlock, P. E. (2000). Accountability and close-call counterfactuals: The loser who nearly won and the winner who nearly lost. Personality and Social Psychology Bulletin, 26, 1213–1224. McAllister, D. W., Mitchell, T. R., & Beach, L. R. (1979). The contingency model for the selection of decision strategies: An empirical test of the eVects of signiWcance, accountability, and reversibility. Organizational Behavior and Human Performance, 24, 228–244. Pan, Y., O’Curry, S., & Pitts, P. (1995). The attraction eVect and political choice in two elections. Journal of Consumer Psychology, 4, 85–101. Parducci, A. (1974). Contextual eVects: A range-frequency analysis. In E. C. Carterette & M. P. Friedman (Eds.), Handbook of perception. New York: Academic Press. Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993). The adaptive decision maker. New York: Cambridge University Press. Ratneshwar, S., Shocker, A. D., & Stewart, D. W. (1987). Toward understanding the attraction eVect: The implications of product stimulus meaningfulness and familiarity. Journal of Consumer Research, 13, 520–533. Sato, T. (1989). Accountability and the debt crisis. Futures, 21, 593–607. Schleicher, D. J., Day, D. V., Mayes, B. T., & Riggio, R. E. (2002). A new frame for frame-of-reference training: Enhancing the construct validity of assessment centers. Journal of Applied Psychology, 87, 735–746. Sessa, V. I., Kaiser, R., Taylor, J. K., & Campbell, R. J. (1998). Executive selection: A research report on what works and what doesn’t. Greensboro, NC: Center for Creative Leadership. Sessa, V. I., & Taylor, J. J. (2000). Choosing leaders: More cooks make a better broth. Consulting Psychology Journal: Research and Practice, 52, 218–225. ShaWr, E., Simonson, I., & Tversky, A. (1993). Reason-based choice. Cognition, 49, 11–36.

J.E. Slaughter et al. / Organizational Behavior and Human Decision Processes 100 (2006) 47–59 Siegel-Jacobs, K., & Yates, J. F. (1996). EVects of procedural and outcome accountability on judgment quality. Organizational Behavior and Human Decision Processes, 65, 1–17. Simonson, I. (1989). Choice based on reasons: The case of attraction and compromise eVects. Journal of Consumer Research, 16, 158–174. Simonson, I., & Staw, B. M. (1992). Deescalation strategies: A comparison of techniques for reducing commitment to losing courses of action. Journal of Applied Psychology, 77, 419–426. Slaughter, J. E., Sinar, E. F., & Highhouse, S. (1999). Decoy eVects and attribute-level inferences. Journal of Applied Psychology, 84, 823–828. Taylor, D. W., & Faust, W. L. (1952). Twenty questions: EYciency in problem-solving as a function of size of group. Journal of Experimental Psychology, 44, 360–368.

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Tversky, A., & Kahneman, D. (1991). Loss aversion in riskless choice: A reference-dependent model. Quarterly Journal of Economics, 1039–1061. Tversky, A., Sattath, S., & Slovic, P. (1988). Contingent weighting in judgment and choice. Psychological Review, 95, 371–384. Watson, G. B. (1928). Do groups think more eYciently than individuals? Journal of Abnormal and Social Psychology, 23, 328–336. Wedell, D. H. (1991). Distinguishing among models of contextuallyinduced preference reversals. Journal of Experimental Psychology: Learning, Memory, and Cognition,, 17, 767–778. Wedell, D. H., & Pettibone, J. C. (1996). Using judgments to understand decoy eVects in choice. Organizational Behavior and Human Decision Processes, 67, 326–344. Wittenbaum, G. M. (1998). Information sampling in decision-making groups: The impact of members’ task-relevant status. Small Group Research, 29, 57–84.