Hayne, Stephen C.

Smith, C.A.P

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Association for Information SystemsAIS Electronic Library (AISeL)AMCIS 1996 Proceedings Americas Conference on Information Systems(AMCIS)8-16-1996Decision Making Under Time Pressure: AnInvestigation of Decision Speed and DecisionQuality of Computer Supported GroupsC.A.P SmithUniversity of MontanaStephen C. HayneArizona State University WestFollow this and additional works at: http://aisel.aisnet.org/amcis1996This material is brought to you by the Americas Conference on Information Systems (AMCIS) at AIS Electronic Library (AISeL). It has been acceptedfor inclusion in AMCIS 1996 Proceedings by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contactelibrary@aisnet.org.Recommended CitationSmith, C.A.P and Hayne, Stephen C., "Decision Making Under Time Pressure: An Investigation of Decision Speed and DecisionQuality of Computer Supported Groups" (1996). AMCIS 1996 Proceedings. 108.http://aisel.aisnet.org/amcis1996/108Decision Making Under Time Pressure: An Investigation of Decision Speed and Decision Quality of Computer Supported Groups C.A.P. Smith, University of Montana Stephen C. Hayne, Arizona State University West There is an emerging view that the pace of managerial decision making is increasing rapidly (El Sawy, 1991; El Sherif & Gray, 1991). As stated by Peter Keen, "Time-not technology-is the major strategic management issue" (Ruh, 1988). Further, Tapscott and Caston believe the old saying "better late than never" has turned into "better never than late" (1994). Rockhart and Hofman (1992) assert that, "Time has become a critical competitive differentiator: time to market for new products, manufacturing cycle for existing products, and timeliness of decision making, all previously important, are now critical." Ironically, McGrath (1990) points out that the study of a new technology called Group Support Systems (GSS) has seriously neglected matters of time.  This article reports the results from several empirical studies concerning the effects of time pressure on group decision making. The decision performance of groups using a GSS was compared to the decision performance of non-GSS groups. Several aspects of this study should make the results interesting to researchers and practitioners alike. First, the decision tasks involved complex business decisions; the results should be somewhat generalizable. Second, the subject groups were not formed in an ad hoc manner, rather the group members had considerable experience working with one another. Since a vast number of groups working together have a prior history, it is our intent to explore how these more "natural" groups respond to time pressure. Third, not only were all of the subjects highly experienced at the decision tasks, but the GSS supported groups had experience using the GSS to make task-related decisions. Finally, the groups had to communicate an extensive amount of information in order to make their collective decisions.  Group Support Systems and Time Pressure Most of the research to date on decision making under time pressure has focused on the related impacts on individual decision making. This body of research generally perceives time pressure to be related to the concept of information load. Information load is defined as the amount of information to be processed in a given period of time [Wright 1974]. In order to alleviate time pressure, an individual can implement a variety of macro-strategies to adjust the overall approach to the decision while leaving intact the core process by which information is combined [Miller 1960; Janis and Mann 1977; Connolly 1980; Hogarth 1981]. Alternatively, an individual might implement a shift in micro-strategy-i.e., an alteration of the specific information processing approach used to combine information [Jacob et al. 1986; Payne et al. 1988].  Macro-strategies related to overcoming information load focus on three types of adjustments. Time pressure may be reduced by eliminating segments of the available information, hence ignoring certain pieces of information in order to reduce time pressure-a process referred to as filtration. An alternative solution is to simply process the same information faster-i.e., acceleration. [Janis and Mann 1977]. A third method of dealing with information overload or time pressure would be for the decision maker to adapt to the situation by reframing the problem and perhaps even decomposing the larger problem into a sequence of smaller problems [Connolly 1980; Hogarth 1981].  Payne et al. [1988] classify micro-strategies into five types: weighted additive procedure (WADD), equal weight method (EQW), satisficing method (SAT), lexicographic (LEX), and elimination-by-aspects (EBA). While all five methods can be used for choice decisions (i.e., selection between two or more alternatives), only WADD and EQW use all available information. WADD uses a strategy of forming an overall score for each object by first multiplying the object's score on each attribute by an importance factor and then summing these products. The EQW method uses a simple additive method- essentially ignoring any relative importance of the factors.  For both choice and judgment tasks, WADD is usually considered the optimal decision strategy. However, WADD and EQW strategies require more information processing and can be problematic under time pressure. Nevertheless, under heavy time pressure individuals often attempt to use an acceleration macro-strategy rather than shift micro-strategies.  McGrath (1991) formulated the Time-Interaction-Performance theory (TIP). Central to this theory is the concept of entrainment. Entrainment refers to a phenomenon in which members of working groups become somewhat synchronized, or temporally coupled, to one another and to the rhythms of the task that they are performing.  TIP theory suggests that the effects of time pressure on the performance of groups will depend on the typical pace of work and the type of task with which the group is entrained. Groups can be entrained to rapid or slow progress. Similarly, groups can be entrained to quantitative or qualitative tasks. A quantitative task refers to one in which the work to be done is not particularly difficult, but there is a large quantity of that work to be accomplished. A qualitative task is one which is more cognitively difficult than normal.  McGrath reasons that if a work group is presented with a situation in which the required task or work pace is different than those to which they are accustomed, then the work patterns of the group are disrupted. TIP theory predicts a variety of different outcomes for disrupted groups, depending on the nature of the change in pace and/or task. This study investigated the situation in which the pace of work must increase, while the difficulty level of the task also increases, thus simulating a typical crisis. For groups entrained with tasks of normal difficulty, TIP theory predicts that:  Groups with projects involving a time crisis will follow whatever strategy they happen to begin with, and will focus only on direct execution of the production function, with no evaluating, stock-taking, and strategy change, and no interpersonal communication. They do low quality work and may be self-destructive. (McGrath, Kelly, Futoran, Harrison, VanderStoep & Gruenfeld, 1989).  Most recently, Hwang (1994) proposed a model of decision making when under time pressure. We have expanded this model to include predictions from TIP and results from recent empirical studies. To summarize the model, time pressure results in the selection of a suboptimal strategy (macro or micro), which in turn causes a decrease in performance. Increasing time pressure is likely to increase task difficulty (as opposed to task complexity). On the other hand, the more difficult a task becomes, the more an individual or group may commit to the goal of solving the task. In a meta-analysis of goal commitment, Wofford, Goodwin and Premack (1992) found that task difficulty was positively related to goal commitment. Apparently, the challenge of a difficult task raises an individual's determination to reach the goal.  Finally, the role of an information system is to counteract the negative impact of time pressure on decision strategy selection and performance. For example, Hwang (1994) found that presentation formats of information systems (graphics vs. tables) have a positive impact on performance when under time pressure.  During the last few years, several GSS have been implemented and studied in action. Johansen (1988) has provided a method for categorizing them using the dimensions of space and time. GSS software such as: GroupSystems, SAMM, NICK and MeetingWare (Dennis, George, Jessup, Nunamaker & Vogel, 1988; Watson, DeSanctis & Poole, 1988; Ellis, Gibbs, S. J. & Rein, G. L., 1991; Lewis & Whitely, 1992) are characterized by work conducted at the same time and in the same place. The Electronic Discussion System (Pendergast, 1989) and Object Lens (Lai & Malone, 1988) allow work at the same time and any place. A few systems are attempting to support work at any time and any place: Coordinator and VisionQuest (Flores, Graves, Hartfield & Winograd, 1988; Wagner, 1991). It is believed that a GSS optimized for crisis management should operate in at least the "same time/any place" mode because the time pressure associated with crises creates a need for "same time" decision making, and the decision makers may be dispersed geographically.  GSS have been shown to affect group interaction in beneficial ways. For example, the possibility for GSS groups to work in parallel may result in a reduction of production blocking (Dennis, 1991; Dennis, Nunamaker & Vogel, 1992; Gallupe, Dennis, Cooper, Valacich, Bastianutti & Nunamaker, 1992). GSS can influence the structure of group interaction through enforced procedures embedded in the software; enforced structuring of group interaction appears to yield positive results when there is a good task-structure fit (Dennis, George, Jessup, Nunamaker & Vogel, 1988; Easton, George, J.F., Nunamaker & Pendergast, 1990; Gallupe, DeSanctis & Dickson, 1988; Nunamaker, Dennis, A., Valacich, J., Vogel, D. & George, J., 1991). Some GSS are designed to allow facilitation, which has been shown to improve some meeting outcomes (Grohowski, McGoff & Vogel, 1990).  Experiments We report the results from 3 separate sets of experiments (Arnold, Hayne, Smith and Sutton, 1996; Smith, Hayne and Connole, 1992; Smith, Hayne, 1996) where college students engaged in business decision-making experiments while experiencing time pressure. All groups were randomly assigned to use Group Support Systems or to interact face-to-face. All experiments had four independent decision making periods (not including at least one practice period). In experiment Three, two periods were chosen at random to become the time pressure sessions and periods were randomly assigned to control for learning effects.  In experiments One and Two, 14 general business student groups of 5 students each produced a set of 26 decisions which formed the input to a business simulation exercise. In experiment Three, 18 accounting (audit) student groups of 4 or 5 students each determined the materiality judgment for firms. All experimental decisions lead to a quantitative measure from which a precise variation in decision quality can be determined. All experiments used monetary incentive payoff functions directly related to the groups' decision quality and decision speed. Subjects were informed of these functions and told that money would be paid to their group in cash at the end of the experiment. Reward money was displayed ($1500) to encourage them to believe they would indeed be paid. If groups earned negative net income during an experiment period, they received $0 payment. As mentioned above, periods were independent observations so losses would not roll over into the next period and thereby induce portfolio or end game effects.  Discussion of Results No order effects for either business case or time pressure condition were observed. In all experiments, making decisions using the GSS took significantly longer. We attribute this difference in speed to two factors: the greater media richness of face-to-face communication, and the more structured decision process used by the GSS groups. Although the GSS supported groups had the potential advantage of parallel communication, they did not use this advantage (a relatively serial process was followed as deduced from the transcripts), and the low-bandwidth keyboard interface served to produce slower decisions. For small groups using similar decision processes, the high bandwidth of face-to-face communication would seem to allow faster decision making. All else being equal, one might expect that this difference in speed could be reduced or possibly reversed for large groups, due to the proportionally greater potential for parallel communication in the GSS groups as group size increases.  TABLE 1: ANOVA Analysis (Decision Quality) for Experiment One Variable F p Time Pressure 1.314 .21 GSS Support 2.183 .05 TABLE 2: ANOVA Analysis (Decision Quality) for Experiment Two Variable F p Time Pressure 28.07 .000 GSS Support 10.39 .001 Interaction TPxGSS 6.04 .013 TABLE 3: ANOVA Analysis (Decision Quality) for Experiment Three Variable F p Time Pressure .384 .538 GSS Support 10.47 .002 Interaction TPxGSS 1.76 .19 From Tables 1, 2 and 3, the presence of time pressure during the crisis simulation had a variable effect. Checking the means (not reported here due to space) shows that a decrease in decision quality for both the supported and non-supported groups was found, as suggested by TIP theory. Yet during the simulation, while highly motivated by large dollar incentives, the GSS supported groups made decisions of greater quality than the non-GSS groups, when under time pressure, in two out of the three experiments. In the third experiment, while not significant, the GSS groups made better decisions under time pressure than when not. The negative effects of time pressure seem to have been mitigated somewhat by the use of the GSS. We argue that the superiority of the GSS groups under time pressure is primarily related to their greater consistency, which came as result of their more structured decision process.  References available upon request from first author.   

Decision Making Under Time Pressure: An Investigation of Decision 
Speed and Decision Quality of Computer Supported Groups

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Decision Making Under Time Pressure: An Investigation of Decision Speed and Decision Quality of Computer Supported Groups

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