Group Decision Support Systems

Given the difficulties with decision making in general, re­search has been conducted on group decision support systems (GDSS) to ease the added complexity of group decision mak­ing. GDSSs usually takes the form of computerized, net­worked systems that aid in idea generation and decision making. A brief summary of key findings follows, but a more detailed account can be found in Hollingshead and McGrath (1995). In general, groups using GDSS versus unaided groups demonstrate more equal participation and increased focus on the task but also interact less, take longer, and have lower over­all consensus and decreased satisfaction with the process and the decision (Hollingshead & McGrath, 1995; McLeod, 1992). GDSS provides a unique environment in which group members can interact anonymously. Jessup, Connolly, and Tansik (1990) showed that anonymous members using GDSS tended to be more critical, more probing, and more likely to generate comments or ideas than when individual contribu­tions were identified.

Which is better for group decision-making task perfor­mance: face-to-face interaction or GDSS? The answer

depends on the task. GDSSs are better for idea generation-Group members can simultaneously submit ideas, which reduces the problem of idea production being blocked while listening to others or waiting for a turn to speak. However face-to-face interactions appear to be superior for problem-solving and conflict-resolution situations. It is interesting to note that Hollingshead and McGrath (1995) suggested that some of the benefits of GDSSs may stem from the structured aspects of the decision-making process rather than from the GDSS itself. Note that Archer (1990) found no differences in decision quality between GDSS and face-to-face when the decision process phases of a complex business situation were organized and managed in a rational manner.

Much of the work in GDSS concerns the technology itself, and research on the behavioral impacts on group decision performance is still in the early stages. The limited research that has been conducted has largely used ad hoc teams. Work needs to be done on intact groups that have had experience working and making decisions together. In addition, there is evidence that simply structuring the decision-making task can improve performance. There may be other features that GDSSs can provide to improve decision making that cannot achieved in any other context.

Negotiation

Negotiation is the process in which people determine "what each side shall give and take or perform and receive in a transaction between them" (Thompson, 1990, p. 516). There is a vast literature in the field of negotiation, and our review here is cursory. For further information on the psychological aspects of the negotiation process, see Thompson (1990) and Bazerman, Curhan, Moore, and Valley (2000). We will focus on dyadic negotiations; however, there is also an extensive literature in multiparty negotiations and coalition formations that we do not discuss here (see Miller & Komorita, 1986; Murnighan, 1986, for reviews).

Early social psychological work in the 1960s and 1970s fo­cused primarily on individual differences or situational char­acteristics. The extensive literature on individual differences has shown little effect on negotiations (Thompson, 1990). The research on situational variables provided primarily descrip­tive accounts and did not use clear standards of rationality as a basis of evaluating performance (Bazerman et al., 2000). In economics, the game theoretic approach attempted to go beyond describing behavior and defined optimal behavior in negotiations. Unfortunately, this line of research suffers from two main disadvantages (Bazerman, 1998): It (a) requires that all possible strategies be defined with associated out­comes, which is either difficult or impossible to perform, and (b) makes the dubious assumption of rationality on the part of

the negotiator. More recently, researchers have examined the interaction between individual differences and contex­tual variables. For example, Kray, Thompson, and Galinsky (2001) examined how men and women adopt different bar­gaining strategies after stereotypes about effective negotiators are activated. When stereotypes are activated implicitly, men are more assertive than women and prevail in a distributive ne­gotiation. However, women are more assertive (and more suc­cessful negotiators) than men when stereotypes are activated explicitly.

The 1980s through 1990s used the behavioral decision re­search (BDR) as a framework. Raiffa (1982), in his decision analytic approach, shifted the attention away from prescrip­tions of optimal strategies to descriptions of actual negotiation behavior. Rather than propose optimal bargaining solutions based on objective facts of a negotiation, this type of research examines the perceptions of the situation, the other party, and

P the self. Thus, the new format was not to present a normative picture of negotiations but to describe behavior and, at times, demonstrate the systematic deviations from the rational nego­tiator. In the 1990s a social cognitive perspective was devel­oped, and the focus was on the negotiator as information processor (Thompson, Peterson, & Kray, 1995).

Many of the findings in this field have taken the heuristics and biases results (e.g., framing and overconfidence) and found them in a negotiation context. A great deal of evidence indicates that the framing of a negotiation has strong implica­tions for negotiations. For example, in a labor-management salary negotiation (Bazerman, 1984), a raise from $10 to $ll/hr can been seen by labor as a gain of $1 or as a loss of $1 if the union demanded $12/hr. Likewise, management can view $ 11/hr as a loss of $ 1, compared to the previous salary, or as a gain of $1, compared to the union's demands. The

I greater impact of losses over equal magnitude gains (i.e., "loss aversion") results in a reluctance to trade concessions (Ross & Stillinger, 1991), creating a barrier to conflict reso­lution, Neale and Bazerman (1985) showed that negotiators with positive frames were more likely to make conces­sions and were more successful than those with negative frames (however, negatively framed negotiators earned on average more per transaction when an agreement was bached). Real estate agents have been shown to anchor on 'he list price of a house and insufficiently adjust when assess­es the value of a home (Northcraft & Neale, 1987); conflict tt&nagement experts fall prey to the availability bias and do ⁿ°t search sufficiently for necessary information (Pinkley, ^nffith, & Northcraft, 1995); and student negotiators were ^Dverconfident in believing that their offer will be accepted in ^fiial arbitration (Bazerman & Neale, 1982).

m addition, new biases have been found that are unique to "* negotiation context. One well-known bias, the fixed-pie

Conclusion 511

assumption, occurs because the negotiators assume that they must distribute a fixed pie (Bazerman, Magliozzi, & Neale, 1985) instead of searching for integrated solutions that in­crease joint payoffs. This belief in the mythical fixed pie can also lead to the incompatibility bias (Thompson & Hastie, 1990; Thompson & Hrebec, 1996), in which negotiators falsely assume that their interests are incompatible with those of their opponents. Bazerman (1998) gave an example of a labor-management negotiation in which both sides value in­creased training programs: Management would gain work­force flexibility, labor would gain job security. However, because of the incompatibility bias, they settle for a less-than-optimal arrangement because they do not realize that they have common interests and negotiate as if a compromise must be reached. In addition, the fixed-pie assumption can lead to devaluing any concession made by the opponent (Ross & Stillinger, 1991): If management is offering more job train­ing, it must not be too costly or must be benefiting them in some way.

Recent research augments the BDR perspective and adds an emphasis on social psychological variables, such as the im­portance of relationships, egocentrism, and emotions. Ethics, the mode of communication, and cross-cultural issues have also received more attention recently.

CONCLUSION

As this selective survey of JDM connections to industrial and organizational (I/O) psychology has, we hope, made clear, we see the linkage between the two fields as having accom­plished significant work, but as having a potential for much more. As Highhouse (2001) pointed out, there are many top­ics in I/O psychology that seem to fall naturally into the JDM domain: personnel selection and placement, job choice, per­formance assessment, feedback provision and acceptance, compensation, resource planning, strategic forecasting, and others. The two disciplines have, however, remained largely isolated, despite the clear potential for collaboration. Our hope is that the present chapter may contribute something to stimulate this linkage.

It may help a little if we clarify what we see as the current state of development of JDM. The mere name of the disci­pline makes an implicit claim: that there is sufficient com­monality across different decision situations for a general theory of decisions to make some sense. We would assess the evidence to date on this point as mixed. Weather forecasters do have something to say to heart surgeons, and hog judges have something to say to HR practitioners; but it would be absurd to claim that we have a successful general theory of judgment and decision that embraces all four territories as

512 Judgment and Decision Making

mere applications. Any general claims require extensive local tinkering before they bring much insight to specific practical applications.

In our view the best contributions that JDM can currently make to I/O issues is as a fertile source of interesting hy­potheses and as a provider of frameworks and instruments. For example, we would not read the literature on overconfi-dence in lab problems as supporting strong predictions that managers will be overconfident in predicting hiring needs. It does, we think, make such a hypothesis worth exploring. It also suggests how the relevant research could be conducted. In return, such research would inform JDM of the boundary conditions on its findings: When, for example, does overcon-fidence generalize, when is it bounded, what mechanisms are successful in minimizing it? It is this two-way enrichment of one another's disciplines that we see as the potential for an enhanced collaboration between JDM and I/O. Our fond hope is that this chapter may do something to facilitate the interchange.

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Funke, J. (1995). Experimental research on complex problem solving. In P. Frensch & J. Funke (Eds.), Complex problem solv­ing: The European perspective (pp. 243-268). Hillsdale, NJ: Erlbaum.

Garland, H. (1990). Throwing good money after bad: The effect of sunk costs on the decision to escalate commitment to an ongoing project. Journal of Applied Psychology, 75, 728-731.

Getty, D. J., Pickett, R. M., D'Orsi, C. J., & Swets, J. A. (1988). Enhanced interpretation of diagnostic images. Investigative Radiology, 23, 240-252.

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Goldstein, W. M., & Hogarth, R. M. (Eds.). (1997). Research on judgment and decision making: Currents, connections, and con­troversies. New York: Cambridge University Press.

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Greenberg, J. (1988). Equity and workplace status: A field experi­ment. Journal of Applied Psychology, 73, 606-613.

Guion, R. M. (1975). Recruiting, selection, and job placement. In M. D. Dunnette (Ed.), Handbook of industrial and organiza­tional psychology (pp. 777-828). Chicago: Rand-McNally.

Guzzo, R. A., & Waters, J. A. (1982). The expression of affect and the performance of decision-making groups. Journal of Applied Psychology, 67, 67-74.

Hammond, K. R. (1955). Probabilistic functioning and the clinical method. Psychological Review, 62, 255-262.

Hammond, K. R.. & Adelman, L. (1976). Science, values and

human judgment. Science, 194, 389-396. Hershman, R. L., & Levine, J. R. (1970). Deviations from optimal

information purchase strategies in human decision making.

Organizational Behavior and Human Performance, 5, 313-329.

Hesse, F. W. (1982). Effects of semantic context on problem solv­ing, Zeitschrift fur Experimented und Angewandte Psychologic 29, 62-91.

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 psychol
(Vol. 1, pp. 314-332). Beverly Hills, CA: Sage. ' °®

Hitt, M. A., & Barr, S. H. (1989). Managerial selection decision models: Examination of cue processing. Journal of Applied

Psychology, 74, 53-61.

Hogarth, R. M. (1987). Judgement and choice: The psychology _nf decision (2nd ed.). London: Wiley.

Hollingshead, A. B., & McGrath, J. E. (1995). Computer-assisted groups: A critical review of the empirical research. In R. aGuzzo & E. Salas (Eds.), Team effectiveness and decision making in organizations (pp. 46-78). San Francisco: Jossey-Bass,

Jackson, S. E., May, K. E„ & Whitney, K. (1995). Understanding the dynamics of diversity in decision-making teams. In R. A. Guzzo & E. Salas (Eds.), Team effectiveness and decision making in organizations (pp. 204-261). San Francisco: Jossey-Bass.

Jam's, I. L. (1972). Victims of groupthink. Boston: Houghton-Mifflin.

Jessup, L. M., Connolly, T, & Tansik, D. A. (1990). Toward a the­ory of automated group work: The deindividuating effects of anonymity. Small Group Research, 21, 333-348.

Josephs, R. A., Larrick, R. P., Steele, C. M._t & Nisbett, R. E. (1992).

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