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Interacting effects of GDSS and leadership
Decision Support Systems 12 (1994) 199-211 North-Holland
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Interacting effects of GDSS and leadership L a i - H u a t Lim, K.S. R a m a n and Kwok-Kee Wei National University of Singapore, Kent Ridge, 0511 Singapore Effects of Group Decision Support Systems (GDSS) on decision making have been extensively studied in various contexts, involving important variables such as group task and group size. However, a factor of significant relevance to group meeting, leadership, has been little dealt with in GDSS research. This paper reports on an experimental investigation of the interacting effects of GDSS and elected leadership on influence attempts in a decision-room setting. Findings reveal that while the use of GDSS caused the influence distribution to be more equal among group m e m b e r s in the absence of leadership, the system did not withstand the overriding force of leadership when a group leader was present.
Keywords: G r o u p decision support systems; Electronic meeting system; Leadership; Influence
Lai-Huat Lim is a Senior Tutor in the D e p a r t m e n t of Information Systems and Computer Science, National University of Singapore. He is currently a doctoral candidate at the Faculty of Commerce and Business Administration, University of British Columbia. Mr. Lim received his Bachelor's degree in electrical engineering and his Master's degree in MIS, both from the National University of Singapore. His current research interests include group decision support systems, negotiation support systems and decision support systems.
Correspondence to: Lai-Huat Lira, Faculty of Commerce and Business Administration, University of British Columbia, #402-2053 Main Mall, Vancouver, B.C., C a n a d a V6T 1Z2. t Professor Gerry DeSanctis provided the S A M M software and offered valuable advice during the course of this research. Professor Ilze Zigurs m a d e helpful suggestions and clarifications on protocol analysis. A T & T International (Singapore) Inc. loaned a 3B2 500 computer for the experiment. T h e anonymous reviewers contributed valuable suggestions which substantially improved the quality of this paper.
1. Introduction
A Group Decision Support System (GDSS), also known as an Electronic Meeting System (EMS), is a combination of communication, computer, and decision technologies for supporting problem formulation and solution in group meetings [8]. The technology interacts with other factors (e.g., task features, group characteristics, contextual variables, etc) to produce an effect on meeting process and outcomes [3], Correspondingly, it is important to take into account these variables in studying the impact of GDSS use. GDSS use has been extensively investigated for its interaction with factors including group size (e.g., [6,32]), task difficulty (e.g., [11]), member proximity (e.g., [12,18]), and so on. However, an important aspect of organizational meetings that has been rarely dealt with in GDSS research is leadership. Among other things, a group leader
K.S. R a m a n is Senior Teaching Fellow and Coordinator of the Information Systems Program, D e p a r t m e n t of Information Systems and Computer Science, National University of Singapore. Before taking up this appointment, he was CIO of a large multinational conglomerate in the AsiaPacific region. His teaching and research interests include m a n a g e m e n t information systems, decision support systems, group decision support systems, and application of information technology in organizations. He is on the editorial boards of the journals MIS Quarterly and International Information Systems. He is a m e m b e r of Sigma Xi and is listed in Marquis W h o ' s W h o in the World. Kwok-Kee Wei is a Senior Lecturer in the D e p a r t m e n t of Information Systems and Computer Science, National University of Singapore. He received his B.Sc. degree in computer science from the Nanyang University, Singapore and a D.Phil from the University of York, England. His current research interests include group decision support systems, strategic information systems, and user-database interactions.
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has the ability to introduce structure into a meeting [31], and is also capable of causing an unequal distribution of influence in the group. Since one of the (expected or real) effects of GDSS use is to ensure greater equality in participation, it is both interesting and important to see how this technology variable might interact with the leadership factor if both were present in a group meeting. The current research aims to examine such interacting effect on influence attempts in a decisionroom setting. Section 2 reviews the relevant literature in both leadership and GDSS research. Section 3 defines influence attempts, explains the theoretical justification for deriving the hypotheses, and presents the hypotheses. Section 4 describes the research method. Section 5 reports the statistical results. Section 6 discusses the findings and their implications.
2. Review of relevant literature The purpose of this section is to provide a brief review of previous research relevant to the current study. We do not review GDSS or leadership research in general; readers are referred to the revised Stogdill's handbook of leadership [1] for a review of leadership research and Benbasat, DeSanctis, and Nault [2], Dennis, Nunamaker, and Vogel [5], and Pinsonneault and Kraemer [26] for GDSS research. 2.1. Leadership in small groups
Leadership has been viewed and defined in various ways [1]. In this paper, we view leadership as the exercise of influence [27,29]. Indeed, leaders have been found to affect, through their influence acts, the performance and satisfaction of their subordinates. Performance variables which have been investigated in this context include group drive and cohesion, which can both be influenced by leadership [29]. Greene and Schriescheim [13] specifically found task- and socialoriented leader behaviors to be causally antecedent to group drive, and suggested that both types of leader behavior are also important to group cohesiveness. Besides group performance, leadership can also affect subordinates' satisfaction. For exam-
pie, consultative leadership would yield more subordinate satisfaction if the leader felt that members were highly committed to the group and its goals [10]. Moreover, low leader influence could reduce the impact of leader behavior on both satisfaction and performance [25]. 2.2. Relevant G D S S research
Turoff and Hiltz [31] studied the effect of human leadership and computer feedback in a conferencing environment. They found either of the treatments to have a significant effect on the ability of a group in reaching consensus. Nevertheless, such effect disappeared when both factors were present. They inferred that decision support aids may undermine human leadership. George, Easton, Nunamaker, and Northcraft [14] studied the effect of GDSS use, assigned leadership, and anonymity. They found two interaction effects, one owing to the interaction between leadership and anonymity on members' satisfaction with process, and the other owing to the interaction between leadership and technology on participation. The latter, which is more relevant to the current study, states that when a manual group had an assigned leader, and when a GDSS group had no leader, members' participation rates were more equal; in other words, manual groups without a leader and GDSS groups with a leader were more likely to have unequal participation rates. As regards influence and domination, two other GDSS studies, conducted by Lewis [21] and Zigurs, Poole, and DeSanctis [35], have found computer-mediated communication to prevent any one individual from dominating the group process; however, these studies did not involve the leadership factor.
3. Construct definition, theory and hypotheses 3.1. Defining influence
Influence attempts are attempts or undertakings to move, affect, or determine a course of action. Following Zigurs et al. [35], this construct has been operationalized behaviorally in this study in terms of verbal and other acts of individual
L.-H. Lim et at / Decision Support Systems 12 (1994) 199-211
members. The m e a s u r e m e n t of these components will be dealt with in section 4. Multiple aspects of influence are studied using three dependent variables: (1) amount of influence behavior, which sums up the individual influence scores of the group, (2) influence inequality, which is a " r o o t - m e a n - s q u a r e " measure and reflects inversely the equality of influence distribution, and (3) dominance significance, which is the ratio of the most dominant m e m b e r ' s influence to the average influence score of the other members. These variables are mathematically defined in the following.
Amount of influence behavior This is defined as the sum of the individual influence scores. This m e a s u r e m e n t is useful as it will bear knowledge about what kind of treatment condition facilitates (or tempts) influence behavior. Denoting the individual influence score as T, for m e m b e r i, where i ranges from one to five for a five-member group, the amount of influence behavior of the group ( A ) is 5
A= ETi. i-1
Influence inequality This is defined for a group as the root-meansquare calculated from all m e m b e r s ' influence scores. This m e a s u r e m e n t is useful and important for understanding how GDSS technology and leadership variable interact to enhance or inhibit evenness of influence distribution among group members. Mathematically, influence inequality, I, is defined as
Dominance significance This is defined for a group as the ratio of the highest influence score (which, by definition, belongs to the most dominant m e m b e r ) to the average influence score of the other members. This variable provides another view for looking at how "democratic" is the group discussion. Unlike the previous variables which deal with influence at the group level, dominance significance captures the " n o r m a l i z e d " influence of an individual m e m b e r (specifically, the most dominant mem-
201
ber). Dominance significance, D, is mathematically defined as D = Tmax/ ~
E
T~ ,
i = 1 ,i ~ m a x
where Tm~x is the influence score of the most dominant member.
3.2. Theory and hypotheses In this section, we derive two sets of hypotheses, one pertaining to each independent variable. The hypotheses related to GDSS technology are developed based on a communication-process perspective. The hypotheses related to elected leadership are based on Hopkins' [17] proposition on rank-influence relationship.
A communication-process perspective of GDSS use DeSanctis and Gallupe [8] propose an information-exchange perspective on the use of GDSS. According to this view, the decision process is revealed in the production and reproduction of positions regarding group action, which are directed toward the convergence of members on a final choice. Supporting group decision making primarily involves changing, in a positive direction, the interpersonal exchange that occurs as a group proceeds with the problem solving process. In this sense, the goal of GDSS is to alter the communication process within groups. We propose that such alteration is achieved primarily through adding to the existing communication channels an electronic channel, characterized by two useful features: multi-accessibility and anonymous input procedure. (See also [22] for a detailed discussion of the electronic communication channel.) In contrast to the verbal channel which allows only one m e m b e r to "access" at any one time in order to be effective, the electronic channel of the GDSS grants multiple accesses at the same time. M e m b e r A need not wait for the "completion" of m e m b e r B before gaining access to the channel. This has significant implication with respect to power and influence in groups. Members who used to dominate the verbal channel prior to the implementation of GDSS cannot prevent others from using the electronic channel in a GDSS environment, and it becomes more difficult for
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them to remain in dominance. Other than reducing domination, multi-accessibility also reduces other process losses and increases process gains [24]. For example, as N u n a m a k e r et al. [24] pointed out, process loss due to "air time fragmentation" (i.e., the group must partition available speaking time among themselves) can be reduced because of the parallel communication that is made available by the multi-accessibility feature. The anonymity feature of the input procedure also has great impact on the group's influence process as this feature is able to detach ideas from their proponents. In the absence of the electronic channel, some group m e m b e r s may tend to shy away from using the existing communication channels including the verbal channel. This may be due to the presence of dominating individuals, the fear of contributing " w r o n g " ideas, and so on. However, if ideas and preferences are exchanged anonymously, individual m e m b e r s will not know who favors what, or where specific m e m b e r s stand on an issue. In other words, some critical political information that is often obtained in meetings will be lost when GDSS technology is introduced. This should greatly reduce the influence of members with high perceived power, and strongly discourage the e m e r g e n c e of new power. T h e r e f o r e , anonymity reduces process losses associated with conformance pressure and evaluation apprehension, and increases processes gains due to learning and more objective evaluation [24]. In sum, the use of GDSS leads to an enhanced communication environment. The amount of influence behavior should increase since meeting participants are now given more choices in the use of communication channels; m e m b e r s who previously feared to speak their ideas may now " e n t e r " their ideas through the terminals. Influence inequality will be lowered by directly benefitting from the two features of the electronic channel: The multi-accessibility feature makes the channel equally available to all meeting participants; the anonymity feature encourages more participation from the otherwise "shy" m e m b e r s by detaching ideas from their proponents. Similarly, dominance significance will reduce as the electronic channel cannot be easily dominated by any individual. Moreover, the important social and political cues which had previously helped
maintain or promote the p h e n o m e n o n of dominance may be lost when ideas and preferences are exchanged anonymously. Based on the above deliberation, we propose the following hypotheses regarding the effect of GDSS use: 2
HI: The total amount of influence behavior is greater in a group supported by GDSS than in a group without GDSS. H2: Influence inequality is lower in a group supported by GDSS than in a group without GDSS. H3: Dominance significance is lower in a group supported by GDSS than in a group without GDSS. The "rank-influence" perspective of leadership H o p k i n s [17] p r o p o s e s interrelationships among five status-related properties: rank, centrality, observability, conformity, and influence. O f particular interest to this study is his proposition relating rank to influence, which states that for any m e m b e r of a small group, the higher his rank, the greater is his influence. (The reasoning behind this simple relationship is that a higher rank is associated with greater centrality, which leads to greater observability, and consequently, greater influence.) Hopkins' rank-influence assertion suggests that a leader, if accepted to be one so as to justify his "rank", has greater influence than other group members. This proposition stems from the theory of authority, particularly from the argument of legitimacy. An example is the important statement by H o m a n s [16] that "the sentiments of the leaders of a group carry greater weight than those of the followers in establishing a social ranking" (p. 181). Since the elected leader is expected to have greater influence than other m e m b e r s as a result of his higher (legitimate) rank, he "naturally" becomes the dominant m e m b e r of the group. (The legitimacy of the leader's rank has especial
2 A counter argument exists for H1 and H2 which does not arise out of the information-exchangeview but is based on the novelty of technology. Specifically, for a novel technology such as GDSS, members may differ in their initial comfort and apprehensiveness, so that members who are faster acquainted with the technology may become more influential in the group's use of the GDSS. This argument was not tested in the current study.
L.-H. Lim et al. / Decision Support Systems 12 (1994) 199-211
significance in the setting of this study since the Singaporean culture accords high status and influence to a formal leader [15]. This point will be further elaborated in Section 6.) The effect is seen in terms of more unequal influence distribution and higher dominance significance in groups with elected leader. The impact of leadership on "total amount of influence behavior" (i.e., one of the three dependent variables defined earlier) cannot be predicted by the existing theory and is therefore not hypothesized. Correspondingly, we propose the following hypotheses regarding elected leadership: H2a: Influence inequality is higher in a group
with elected leader than in a group without elected leader. H3a: Dominance significance is higher in a group with elected leader than in a group without elected leader.
4. Research method 4.1. Research design and subjects
This study involved a laboratory experiment with a two-by-two (i.e., GDSS vs. Manual; Leadership vs. No leadership) factorial design. A total of eight groups per cell took part in the experiment, and each group consisted of five members. Owing to the high cost associated with the interaction analysis techniques chosen for this research, a subsample of five groups per cell was selected for the interaction analysis. Subjects consisted of first-year computer science undergraduates at the National University of Singapore. All participants had used computers before taking part in the experiment. The subjects were given course credit for their participation. More than one half of the subjects were males who had served two and a half years of national (military) service and had worked in teams before. Because subjects were randomly assigned to groups, most groups had no prior history of working together and are thus ad hoc groups. Correspondingly, when interpreting any findings of the current study, it ought to be taken into account the previous experimental evidence that members of established GDSS groups tend
2(13
to participate less equally than members of ad hoc GDSS groups [4]. 4.2. Research task
Many organizational meetings occur without prior or post knowledge of the "correct" outcome of a group meeting. For this reason, this study aimed to build on the available knowledge of GDSS impacts by examining the usefulness of the technology in situations where a group had to resolve competing personal preferences and maximize agreement on a solution to a problem. In such situations, achieving high decision quality would not be the primary goal of the group meeting. The preference allocation task used in this experiment was adapted from that developed and validated by Watson, DeSanctis, and Poole [33], with changes aimed at localizing the context. The task required subjects to allocate a given sum of money among six competing projects that had requested funds from a philanthropic foundation [33]. Conflict would arise because the members would have different preference structures, thus resulting in different allocation patterns. During the experiment, there was no time-limit specification for the task. On the average, each group took thirty minutes to complete its task. 4.3. The GDSS
The GDSS used in this research is the Software Aided Meeting Management (SAMM) system (version 1.3) developed at the University of Minnesota. A detailed description of the system can be found in Desanctis, Sambamurthy, and Watson [9]. Version 1.3 of SAMM provides seven features: problem definition, input of selection criteria, input of alternatives, ranking, rating, voting, and solution definition. Some of these features (e.g., ranking, rating, voting) serve similar purposes; groups made their own choice as regards which or how many of such "similar" features should be used. 4.4. Measurement of dependent ~,ariables
This study investigated three dependent variables: amount of influence behavior, influence inequality and dominance significance. These
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variables are realized through manipulations of the individual influence scores. Essentially, amount of influence behavior is the sum of these basic scores; influence inequality is conceptually equivalent to the standard deviation of the scores; and dominance significance is a ratio made out of the scores. This section looks at how the individual scores were obtained.
Verbal component Basically, each influence score consists of a verbal component and a nonverbal component. The verbal acts were analyzed using a scoring method [30], i.e., working from videotapes, the verbal acts (where "act" here refers to an instance of behavior) for each individual were coded under various categories of behavior. The interaction coding scheme used was that developed and validated by Putnam [27], and which had been intended for coding procedural messages (i..e., statements that guide the work of the group), including what the group is doing, where it is going, and what it should do. Procedural communication "occupies a substantial portion of group talk time, performs vital meta-message functions, and serves as indices of leadership emergence and decision making processes" [27] (p.332). Specifically, five types of verbal behavior are considered as constituting attempts to influence; these are behavior of initiation; goal-orientation; integration/summarization; implementation; and general processual direction. Zigurs [34] revised the scheme to study decision process under the influence of technological support and group size. Since the current research aimed to measure the effect of GDSS on influence behavior, it employed Putnam's coding scheme as revised by Zigurs. In justifying her choice of Putnam's scheme, Zigurs pointed out that since a GDSS is likely to have the most impact on how groups structure their work, capturing procedural messages is particularly important in such an analysis. Nonverbal component The nonverbal influence acts were measured by simple counting using computer log files or video tapes. There was no attempt to conduct an indepth analysis of nonverbal behavior such as eye gaze, hand gestures, facial expressions, and so on. The purpose of coding nonverbal procedural be-
havior was to capture influence attempts via the use of GDSS or its manual structure equivalent that would not have been captured by the verbal coding system. Consequently, the emphasis here is on a category called nonverbal procedural behavior [34], which consists of actions that reorient or change the group's visual attention through the use of supplementary visual aids. In the current context, nonverbal behavior can be either electronic, which occurs through the use of a large screen driven by GDSS, or manual, through the use of a flipehart. Depending on whether or not a group is provided with a GDSS, either the electronic nonverbal behavior or the manual nonverbal behavior may be defined. Uses of GDSS that suggest influence include changing the current display on the public screen, deleting an item from the system (which may be a problem definition, a selection criterion, or an alternative definition), and using the group communication feature. The number of times each individual member assumed any one of these categories of behavior was counted with an analysis of the computer log files. Corresponding behavior types were identified for manual groups by viewing videotapes. These behavior types consist of changing the currently displayed page of the flipchart, crossing out material on the flipchart, and writing comments on the flipchart.
4. 5. Experimental procedure Whereas all groups went through a warm-up task, only groups assigned to the leadership condition were asked to elect a leader after this task. The leader was instructed to focus the group's discussion, suggest specific ranking changes, promote consensus, and summarize the progress of meetings. These were the same responsibilities given to the group leaders in Turoff and Hiltz's [31] study. In the next major phase of the experiment, groups received different types of training depending on the (technological) treatment each was administered to. The computer-supported groups received training on how to use the GDSS. Essentially, they were led by the experimenter through the agenda provided by the SAMM software and given the opportunity to enter their inputs during each phase of the agenda. As for the manual groups, they were introduced to and
L.-H. Lim et al. / Decision Support Systems 12 (1994) 199-211 m a d e f a m i l i a r with an a g e n d a closely p a r a l l e l i n g t h e a g e n d a o f t h e S A M M system. I n t h e final p h a s e o f the e x p e r i m e n t , g r o u p s t a c k l e d t h e e x p e r i m e n t a l t a s k with o r w i t h o u t G D S S a n d / o r e l e c t e d l e a d e r s h i p . D u r i n g this p h a s e , m a n u a l g r o u p s w e r e a s k e d to follow t h e a g e n d a a f o r e m e n t i o n e d , a n d w e r e given aids including a flip chart, p e n c i l a n d p a p e r . T h e i d e a was to m a k e t h e s t r u c t u r e of t h e e x p e r i m e n t as e q u a l as p o s s i b l e b e t w e e n the two t r e a t m e n t conditions, so t h a t any o b s e r v e d d i f f e r e n c e m a y b e a t t r i b u t e d to t h e t y p e o f t e c h n o l o g i c a l s u p p o r t . F o r e a c h g r o u p r e g a r d l e s s o f its t r e a t m e n t , t h e e n t i r e m e e t i n g was v i d e o t a p e d .
4.6. Manipulation check T h e l e a d e r s h i p t r e a t m e n t was c h e c k e d in two ways. O b s e r v a t i o n o f t h e m e e t i n g s as well as viewing of t h e v i d e o t a p e s i n d i c a t e d t h a t t h e g r o u p l e a d e r s had, at d i f f e r e n t p o i n t s of t h e m e e t i n g , a t t e m p t e d to a d d r e s s e a c h of t h e f o u r responsibilities a s s i g n e d to them. M o r e i m p o r t a n t l y , it was f o u n d t h r o u g h c o d i n g that, for n i n e o u t o f t h e t e n e l e c t e d - l e a d e r groups, t h e h i g h e s t i n f l u e n c e score c a m e f r o m t h e l e a d e r . A s for t h e e x c e p t i o n , t h e g r o u p l e a d e r ' s score was very close to t h e h i g h e s t score. Since t h e p r o b a b i l i t y of achieving this situa t i o n by chance a l o n e is a l m o s t z e r o 3, we conclude that the leadership variable had been properly o p e r a t i o n a l i z e d .
5.1. A m o u n t of influence behavior T a b l e 1 s u m m a r i z e s the m e a n s a n d s t a n d a r d deviations of amount of influence behavior. Table 2 p r e s e n t s t h e A N O V A table, which shows significant effects for b o t h d e c i s i o n aid a n d l e a d e r s h i p factors. S e p a r a t e t-tests w e r e c a r r i e d out for t h e i n d e p e n d e n t v a r i a b l e s a n d b o t h t u r n e d o u t to b e significant. Thus, t h e h y p o t h e s i s r e l a t e d to decision aid (i.e., H I ) was c o n f i r m e d . T h e m a i n effect of e l e c t e d l e a d e r s h i p was not h y p o t h e s i z e d .
5.2. Influence inequality M e a n s a n d s t a n d a r d d e v i a t i o n s of i n f l u e n c e i n e q u a l i t y a r e shown in T a b l e 3, T h e m e a n scores
Table 1 Amount of influence behavior: Mean score Istandard deviation, cell size). Leader No leader Total
GDSS
Manual
Total
193.60 (18.81,5) 269.20 (24.26,5) 231.40 (44.79,10)
127.20 (20.33,5) 185.80 (23.59,5) 156.50 (37.21,10)
160.40 (39.56,10) 227.50 (49.40,10) 193.95 (55.52,20)
Table 2 Amount of influence behavior: analysis of variance. Source of variation
5. Results T h e A N O V A m o d e l was u s e d to d e t e c t significant effects. S t e p s have b e e n t a k e n in t h e analysis to e n s u r e t h e satisfying of t h e t h r e e a s s u m p t i o n s underlying the ANOVA model, namely, homog e n e i t y of v a r i a n c e , i n d e p e n d e n t s a m p l e s , a n d n o r m a l i t y o f e r r o r t e r m s [23]. F o r e a c h o f t h e o b s e r v e d significant effects arising o u t o f t h e analysis o f v a r i a n c e , a s u b s e q u e n t o n e - s i d e d t-test was c o n d u c t e d to c o n f i r m o r d i s c o n f i r m t h e rel a t e d h y p o t h e s i s . A 5 % level o f significance was u s e d in all F - t e s t s a n d t-tests. 3 The probability of getting the highest influence score for the leader in nine out of ten groups assuming that influence was randomly distributed among all group members can be calculated as follows: P = 0 . 2 9 * 0.81 + 0 . 2 1 ° = 0.0000(1051.
205
df
Decision aid Leadership Decision aid X leadership Error Total
SS
F
1 1 1
28050 22510 361
58.67 * * 47.06 * * 0.76
16 19
7650 58573
** p < 0.01.
Table 3 Influence inequality: Mean score (standard deviation, cell size). Leader No leader Total
GDSS
Manual
Total
62.70 (21.24,5) 27.04 (9.89,5) 44.87 (24.43,10)
55.95 (9.69.5) 58.89 (12.40,5) 57.42 (10.60,10)
59.32 (15.96,10) 42.96 (19.84,10) 51.14 (19.43,20)
L.-H. Lim et al. / Decision Support Systems 12 (1994) 199-211
206 Influence Inequality
Table 5 Influence inequality: Analysis of simple effects of leadership factor.
70__
Source of variation
Leader
60__
Leadership @ GDSS Leadership @ Manual Error
50__ Leader
4 0
df
SS
F
1
3179
15.97 * *
1
22
16
3186
0.11 -
** p < 0.01.
30__ 2O
I
I
Manual
GDSS Fig. 1. M e a n scores of influence inequality.
Table 6 Influence inequality: Analysis of simple effects of decision-aid factor. Source of variation
Table 4 Influence inequality: analysis of variance. Source of variation Decision aid Leadership Decision aid X leadership Error Total
df
SS
F
1 1 1
788 1338 1863
3.96 6.72 * 9.35 * *
16 19
3186 7174
-
df
Decision aid @ Leader Decision aid @ No Leader Error
SS
1
114
l
2536
16
3186
F 0.57 12.74" * -
* * p < 0.01.
5.3. Dominance significance
* p < 0.05. ** p < 0.01.
are also shown graphically in Figure 1, which indicates an interaction effect between the independent variables. The output of the A N O V A procedure is presented in Table 4. It can be seen that the leadership factor had a significant main effect on influence inequality. A follow-up t-test confirmed the hypothesis related to this main e f f e c t (i.e., H2a). In addition, there was a significant interaction effect of the independent variables. An exploratory analysis was necessary. The method of analysis of simple effects [19] was used to analyze the observed interaction. The simple effects of each factor are recorded in Tables 5 and 6. The analysis of the leadership factor (Table 5) shows significant effect under the GDSS condition. On the other hand, in the analysis of the decision-aid factor (Table 6), the treatment effect was significant for no-elected-leader groups. For each of these significant F-tests, the follow-up t-test confirmed the significant difference.
To satisfy the assumptions of the statistical model, dominance significance was transformed Table 7 (Inverse) dominance significance: M e a n score (standard deviation, cell size).
Leader No leader Total
GDSS
Manual
Total
0.36 (0.20,5) 0.71 (0.05,5) 0.53 (0.23,10)
0.18 (0.09,5) 0.31 (0.10,5) 0.24 (0.11,10)
0.27 (0.18,10) 0.51 (0.22,10) 0.39 (0.23,20)
Table 8 (Inverse) dominance significance: analysis of variance. Source of variation Decision aid Leadership Decision aid X leadership Error Total ** p < 0.01.
df
SS
F
1 1 1
2.88 2.55 0.07
13.25" * 11.71" * 0.32
16 19
3.48 8.98
-
L.-H. Lim et al. / Decision Support Systems 12 (1994)
using an inverse function. Means and standard deviations of (inverse) dominance significance are shown in Table 7. Table 8 presents results of the analysis of variance. T h e r e were significant main effects for both decision aid and leadership factors. Subsequent t-tests confirmed both of the related hypotheses (i.e., H3 and H3a).
6. Discussion
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leadership that they simply submitted to it by minimizing their own influence attempts. Apparently, when the issue of power and authority has been m a d e certain in a group (for example, through election), group m e m b e r s are likely to submit to the leader rather than try to overtake h i m / h e r . Therefore, they exhibit much less influence behavior. As a result, the total amount of influence associated with elected-leader groups was observed to be less in comparison to no-elected-leader groups.
6.1. Findings on amount of influence behavior 6.2. Findings on influence inequality The hypothesis related to technological support was supported by the statistical findings, i.e., GDSS did bring about a greater total amount of influence behavior. The electronic communication channel had served as an alternative for m e m b e r s who did not want to use the verbal channel for one reason or another. With the new channel, there was a lower risk of exposure due to the anonymity feature, so that m e m b e r s who used it need not be afraid of being criticized for wrong or lousy ideas. This finding supports the information-exchange perspective offered by DeSanctis and Gallupe [8] which was used to derive the related hypothesis. A favourable view on the use of GDSS is implied here. In the context of a preference-allocation task where there is no correct answer to be anticipated and thus no expertise required, it is only healthy and fair that everybody has h i s / h e r favoured communication channel for attempts to influence others. It should be cautioned that the finding could be partly due to the early stages of development of the experimental groups, as it has been suggested that during the early stages of group development, group m e m b e r s tend to define and defend their positions, and try to obtain a basis of influence over the decision process [20]. The generalizability of this finding to groups in their advance stages of development may thus be limited [5]. Although the relationship between leadership and amount of influence behavior was not hypothesized, findings suggest that groups without elected leader generate more influence behaviors than groups with elected leader. It seems that the elected leaders were exercising influence at the expense of the other members, and the non-leader m e m b e r s were so much " h a u n t e d " by the elected
The hypothesis related to the decision technology was not supported, but that related to elected leadership was. It was found that influence behaviors were more evenly distributed in groups without elected leader. However, an interaction effect was observed in addition to the main effect of elected leadership. Further analysis showed that a GDSS had no effect on elected-leader groups, but caused a more e~en influence distribution than manual support did in groups without elected leader. By omitting the insignificant effects, Figure 1 can be simplified into Figure 2. Referring to Figure 2, starting from the manual-support condition: for a group with an elected leader, the effect of GDSS was horizontal, i.e., there was no improvement; for a no-electedleader group, there was a downward effect, causing the influence distribution to become more even than before. An interesting p h e n o m e n o n is revealed by these observations: GDSS does discourage the emergence of new power in the case
Influence Inelaality (Manual, NoLeader) (GI~SS, L ~
a
~
.~Ma-nual, Leader)
(GDSS, NoLeader) Fig. 2. Interactingeffectson influenceinequality.
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where there is no established leadership, but does not stop the already established formal leadership from exercising influence. What follows from this conclusion are two positive implications derived from two different situations. In an organizational meeting involving a group of " p e e r s " with no rank differentials solving a preference-allocation task, a more even influence distribution is achievable with the aid of GDSS, and that is desirable for the group. It must be qualified that this is a desirable situation because the task type is a preference allocation task. A preference allocation task, being one which has no correct answer, requires no single member to be more influential than the other group members to arrive at a " b e t t e r " or the " b e s t " solution. Instead, the solution is shaped by each member's preference. Therefore, it is only fair that each member has a share in influencing the others. Without the use of GDSS technology, dominant members may compete to become the informal leader even in the early stages of meeting, a phenomenon which may not be desirable. On the other hand, an egalitarian pattern of influence distribution may not be suitable for groups with formal leaders. In real life organizations, leaders are usually the ones who decide whether or not to implement new technologies. If GDSS technology were found to improve influence distribution in group discussions at the expense of the leader's influence, it might not be easily adopted. As the finding has indicated that GDSS does not give rise to a more even distribution of influence in the presence of a leader, it implies that leaders may show less resistance to its adoption. 6.3. Findings on dominance significance The hypothesis related to decision technology was supported; this means that GDSS groups reported lower dominance significance than manual groups. Since dominance significance measured the most dominant member's influence score over the average score of the other members, the finding has provided us with insight into GDSS's ability to reduce individual dominance. The "multi-accessibility" feature of the electronic communication channel made it almost impossible for a dominant individual to prevail through the use of this channel, since at any one
time, more than one member could gain access to the channel. Also, the anonymity feature of the electronic communication channel had caused some social cues associated with the usual political dynamics of the group to be lost. These effects together made it much more difficult for the otherwise dominant individuals to remain in dominance in a GDSS environment. Thus, GDSS intervention had the effect of reducing the dominant individual's influence through its multiaccessibility and anonymity features. The absence of significant interaction effect appears to suggest that GDSS had reduced the dominance of an individual regardless of whether h e / s h e was a formal leader, a derivation which contradicts the conclusions arrived at in the case of the influence inequality measure (where leadership was found to have an overriding effect over the use of GDSS). A follow-up exploratory analysis revealed that the significant main effect of decision support had largely been due to the no-elected-leader groups. When the scores of the elected-leader groups alone were tested, no significant difference was found in the dominance significance between GDSS and manual treatments. It thus confirmed our earlier conclusion that GDSS discourages the emergence of new power in the group but does not stop the already-established leadership from exercising influence. The hypothesis related to elected leadership was supported, since groups with elected leader reported higher dominance significance than groups without elected leader. It was found that in all cases but one, the most dominant member in an elected-leader group was actually the elected leader himself/herself. Even in the exceptional case, the leader was almost the most dominant member. We make an attempt here to link this finding with the issue of formal versus informal leadership. An elected leader, being formally elected by the group members in a unanimous manner, is by definition a formal leader. From the perspective of the exercise of influence, the most dominant member in a group without elected leader can be regarded as the informal leader of the group. Given this interpretation and the findings we obtained, it can be concluded that formal leadership commands a higher dominance over group members than informal leadership does. In other words, the findings appear to suggest that
L.-H. Lim et aL / Decision Support Systems 12 (1994) 199-211 Table 9 Comparison of findings Study
Findings
Zigurs et al. [35] a
GDSS caused more equal distribution of influence. A leader in manual groups and no leader in GDSS groups led to the most equal participation. GDSS groups with no leader led to the most equal distribution of influence
George et al. [14]
Current study
a Experimental groups contained no formal leaders.
formal leadership is "better" accepted than informal leadership by group members.
6.4. Comparison with preuious studies This section compares the findings of this study with those of two previous GDSS studies, George et al. [14] and Zigurs et al. [35]. George et al. examined the effect of GDSS, leadership, and anonymity on participation (among other dependent variables); Zigurs et al. studied the effect of GDSS on influence using constructs similar to those employed in the current study, although the experimental groups used in Zigurs et al.'s study had no formal leaders. Table 9 summarizes the findings of the three studies on comparable dependent variables. A common finding shared by these studies is that GDSS-supported groups with no (formal) leader had the most equal participation or influence. Therefore, it is important that organizational groups employing the technology take into account the proper "mix" of the group structure, with special regard to formal leadership. This implies that for organizational meetings intending to see influence being distributed in an egalitarian pattern by using GDSS, steps must also be taken to ensure that the relationships between participants are of a " p e e r " nature so as to avoid any obvious status differentials. Besides the above similarity in the studies' findings, a noticeable difference also exists. George et al. found that manual groups with a leader had comparable equality in participation as GDSS groups with no leader, whereas the current study found the two conditions to be
20q
significantly different. The fact that leadership had dissimilar impacts within the non-GDSS groups between the studies may be accountable using a cultural explanation as follows. Hofstede [15] found the Singaporean culture to differ from the American culture in two important aspects: individualism and power distance 4. The Singaporean culture is characterized by low individualism and high power distance, whereas the American culture exhibits almost opposite characteristics. The implication of low individualism is that an individual in this culture will tend to see himself/herself as part of "we" and strive for group interest. The interpretation of high power distance is that both supervisors and subordinates in the related culture expect power differences to be translated into visible status differentials. Consequently, in the traditional (i.e., non-GDSS) meeting environment, higher status and influence is accorded to the leader in the Singaporean culture than in the American culture. This explanation is consistent with the difference observed between George et al. and the current study as regards the difference in participation within the manual groups with a leader. The importance of culture in GDSS research is thus evident. Two points follow from this observation. Firstly, the generalizability of the findings here is restricted by the cultural factor. Secondly, and perhaps more importantly, future research should pay more attention to issues related to cross-cultural differences in GDSS design and use [7]. A major reason contributing to the increasing importance of the cultural factor is the globalization of work force [28].
6.5. Limitations o f study In addition to those limitations pointed out elsewhere in the paper, the findings of this study
4 "Individualism" stands for a preference for a loosely knit social framework in society in which individuals are supposed to take care of themselves and their immediate families only, as opposed to "collectivism",which stands for a preference for a tightly knit social framework in which individuals can expect their relatives, clans, and other ingroups to look after them, in exchange for unquestioning loyalty. "Power Distance" is the extent to which society accepts the fact that power in institutions and organizations is distributed unequally.
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a r e also subject to t h e following two limitations. Firstly, H o p k i n s ' [17] t h e o r y has n o t b e e n very m u c h t e s t e d since its c o n c e p t i o n . Obviously, t h e derived propositions regarding leadership would have b e e n o t h e r w i s e stronger. Secondly, typical use o f S A M M involves b o t h t h e e l e c t r o n i c a n d v e r b a l c o m m u n i c a t i o n s . This is in c o n t r a s t to s o m e o t h e r G D S S s (e.g., G r o u p S y s t e m s ) w h e r e e l e c t r o n i c c o m m u n i c a t i o n typically a l m o s t rep l a c e s v e r b a l c o m m u n i c a t i o n . It is p o s s i b l e t h a t a g r o u p l e a d e r w o u l d find it m o r e effective to exerCise his i n f l u e n c e with b o t h v e r b a l a n d e l e c t r o n i c c h a n n e l s t h a n with t h e e l e c t r o n i c c h a n n e l alone. Thus, g e n e r a l i z i n g t h e results h e r e to a setting involving s o m e o t h e r G D S S s s h o u l d b e d o n e only a f t e r this s u b t l e d i f f e r e n c e has b e e n t a k e n into account.
7. Conclusion GDSS-supported groups, aided with the a n o n y m i t y f e a t u r e to d e t a c h p r o p o s e d i d e a s f r o m t h e i r p r o p o n e n t s , r e p o r t e d l a r g e r a m o u n t s o f inf l u e n c e b e h a v i o r t h a n m a n u a l l y - s u p p o r t e d groups. T h e r e was n e v e r t h e l e s s lack o f e v i d e n c e to support the assertion that GDSS promotes equality o f i n f l u e n c e in all groups. I n s t e a d , an i n t e r a c t i o n effect was o b s e r v e d . G D S S was f o u n d to b e useful in s u p p r e s s i n g t h e e m e r g e n c e o f n e w p o w e r f r o m t h o s e w h o s o u g h t it. A s a result, t h e influe n c e d i s t r i b u t i o n was m o r e even in n o - e l e c t e d l e a d e r g r o u p s given t h e G D S S t r e a t m e n t t h a n in n o - e l e c t e d - l e a d e r g r o u p s given t h e m a n u a l t r e a t ment. Nevertheless, GDSS could not stop the e l e c t e d l e a d e r f r o m exercising influence, i.e., e l e c t e d l e a d e r s h i p a p p e a r e d to have an o v e r r i d ing effect over G D S S use. C o n s e q u e n t l y , no diff e r e n c e was r e p o r t e d b e t w e e n G D S S a n d m a n u a l t r e a t m e n t s for t h e e l e c t e d - l e a d e r groups. Also, it h a d b e e n i n d i c a t e d statistically t h a t G D S S red u c e d i n d i v i d u a l d o m i n a n c e in groups. In fact, t h e r e s u l t h e r e was similar in p a t t e r n to t h a t o n i n f l u e n c e d i s t r i b u t i o n such t h a t l e a d e r s h i p still h a d a n o v e r r i d i n g force over t h e use o f G D S S ( a l b e i t to a lesser e x t e n t in t e r m s o f d o m i n a n c e significance so t h a t it was insufficient to c a u s e a significant i n t e r a c t i o n effect). W e t h e r e f o r e conclude that GDSS promotes more democratic g r o u p discussion in t h e a b s e n c e o f an e l e c t e d leader.
References [1] Bass, B.M., Stogdill's Handbook of Leadership, New York, NY: Free Press, 1981. [2] Benbasat, I., DeSanctis, G. and Nault, B.R., Empirical Research in Managerial Support Systems: A Review and Assessment, Recent Developments in Decision Support Systems, C, Holsapple and A. Whinston (eds.), SpringerVerlach, 1992. [3] Benbasat, I. and Lim, L.H., The Effects of Group, Task, Context, and Technology Variables on the Usefulness of Group Support Systems: A Meta-analysis of experimental Studies, Small Group Research 24, No. 4 (1993) 430-462. [4] Dennis, A.R., Easton, A.C., and Easton, G.K., Ad hoc Versus Established Groups in an Electronic Meeting System Environment, Proceedings of the 23rd Annual Hawaii International Conference on System Sciences, J.F. Nunamaker, Jr. (ed.), 1990, III: 23-29. [5] Dennis, A.R., Nunamaker, J.F. and Vogel, D.R., A Comparison of Laboratory and Field Research in the Study of Electronic Meeting System, Journal of Management Information Systems 7, No. 3 (1991) 107-135. [6] Dennis, A.R., Valacich, J.S. and Nunamaker, J.F., An Experimental Investigation of the Effects of Group Size in an Electronic Meeting Environment, IEEE Transactions on Systems, Man, and Cybernetics 20, No. 5 (1990) 1049-1057. [7] DeSanctis, G., Shifting foundations in group support system research. In L.M. Jessup and J.S. Valacich (eds.), Group support systems: New perspectives, NY: Macmillan Publishing Company, 1993, 97-111. [8] DeSanctis, G. and Gallupe, R.B., A Foundation for the Study of Group Decision Support Systems, Management Science 33, No. 5 (1987) 589-609. [9] DeSanctis, G., Sambamurthy, V. and Watson, R.T., Computer Supported Meetings: Building a Research Environment, Large Scale System 13, (1987) 43-59. [10] Farrow, D.L., Valenzi, E.R. and Bass, B.M., A Comparison of Leadership and Situational Characteristics within Profit and Non-Profit Organizations, Proceedings of the Academy of Management, 1980. [11] Gallupe, R,B., DeSanctis, G. and Dickson, G.W., Computer-Based Support for Problem Finding: An Experimental Investigation, MIS Quarterly 12, No. 2 (1988) 277-296. [12] Gallupe, R.B. and McKeen, J.D., Enhancing ComputerMediated Communication: An Experimental Investigation into the Use of a Group Decision Support System for Face-to-Face versus Remote Meetings, Information & Management 18, (1990) 1-13. [13] Greene, C.N. and Schriesheim, C., Causal Paths among Dimensions of Leadership, Group Drive and Cohesiveness: A Longitudinal Field Investigation, Proceedings of the Academy of Management, 1977. [14] George, J.F., Easton, G.K., Nunamaker, J.F. and Northcraft, G.B., A Study of Collaborative Group Work with and without Computer Based Support, Information Systems Research 1, No. 4 (December 1990) 394-415. [15] Hofstede, G., Culture's Consequences: International Differences in Work-Related Values, Beverly Hills: Sage Publications, 1980.
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[16] Homans, G.C., The Human Group, New York: Harcourt Brace, 1950. [17] Hopkins, T.K., The Exercise of Influence, Totowa, NJ: The Bedminster Press, 1964. [18] Jessup, L.M. and Tansik, D.A., Decision Making in an Automated Environment: The Effects of Anonymity and Proximity with a Group Decision Support System, Decision Sciences 22, (1991) 266-279. [19] Keppel, G., Design and Analysis: A Researcher's Handbook (2nd ed.), Englewood Cliffs, New Jersey: PrenticeHall, 1982. [20] Kraemer, K,L. and Pinsonneault, A., The Implication of Group Support Technologies: An Evaluation of the Empirical Research, Proceedings of the Twenty-second Hawaii International Conference on System Sciences, 1989. [21] Lewis, L.F., A Decision Support System for Face-to-Face Groups, Journal of Information Science 13, (1987) 211219. [22] Lira, F.J., and Benbasat, I., A Communication Based Framework for Group Interfaces in Computer-supported Collaboration, Proceedings of the 24th Annual Hawaii International Conference on System Sciences, Vol. 3 (1991). [23] Neter, J., Wasserman, W. and Kutner, M.H., Applied Linear Statistical Models: Regression, Analysis of Variance and Experimental Design (2nd ed.), Homewood, IL: Irwin, 1985. [24] Nunamaker, J.F., Denn:is, A.R., Valacich, J.S., Vogel, D.R., and George, J.F., Electronic Meeting Systems to Support Group Work, Communications of the ACM 34, No. 7 (1991) 40-61. [25] O'Reilly, C.A. III and Roberts, K.H., Supervisor Influence and Subordinate Mobility Aspirations as Moderators of Consideration Ratings and Structure, Journal of Applied Psychology 63, (1978) 96-102. [26] Pinsonneault, A. and Kraemer, K.L., The Impact of
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Technological Support on Groups: An Assessment of the Empirical Research, Decision Support Syslems 5, (1989) 197-216. [27] Putnam, L.L., Procedural Messages and Small Group Work Climates: A Lag Sequential AnaLysis, Communication Yearbook 5, M. Burgoon (ed.), New Brunswick, NJ: Transaction Books, 1981, 331-350. [28] Rao, S., Information Systems and the GIobalization ot' the Work Force. Proceedings of the Canadian InIbrmation Processing Society Congress 91, Victoria, BC, 1991. 119-128. [29] Schriesheim, C.A., Mowday, R.T. and Stogdill, R.M.. Crucial Dimensions of Leader-Group Dimensions. Cross-Currents in Leadership, J.G. Hunt and L.L. Larson (eds.), Carbondale: Southern Illinois University Press, 1979. [30] Todd, P. and Benbasat, I., Process Tracing Methods in Decision Support Systems Research: Exploring the Black Box, MIS Quarterly 11, No. 4 (December 1987) 493-51Z [31] Turoff, M. and Hiltz, S.R., Computer Support for Group versus Individual Decisions, IEEE Transactions on Communications COM-30, No. 1 (1982) 82-90. [32] Watson, R.T., A Study of Group Decision Support System Use in Three- and Four-Person Groups for a Preference Allocation Decision, Ph.D. dissertation, University of Minnesota, 1987. [33] Watson, R.T., DeSanctis, G. and Poole, M.S., Using a GDSS to Facilitate Group Consensus: Some Intended and Unintended Consequences, M1S Quarterly 12, No. 3 (1988) 462-478. [34] Zigurs, I., The Effect of Computer Support on Influence Attempts and Patterns in Small Group Decision-Making, Ph.D. dissertation, University of Minnesota, 1987. [35] Zigurs, I., Poole, M.S. and DeSanctis, G., A Study of Influences in Computer-Mediated Communication, MIS Quarterly 12, No. 4 (1988) 625-644.
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Interacting effects of GDSS and leadership L a i - H u a t Lim, K.S. R a m a n and Kwok-Kee Wei National University of Singapore, Kent Ridge, 0511 Singapore Effects of Group Decision Support Systems (GDSS) on decision making have been extensively studied in various contexts, involving important variables such as group task and group size. However, a factor of significant relevance to group meeting, leadership, has been little dealt with in GDSS research. This paper reports on an experimental investigation of the interacting effects of GDSS and elected leadership on influence attempts in a decision-room setting. Findings reveal that while the use of GDSS caused the influence distribution to be more equal among group m e m b e r s in the absence of leadership, the system did not withstand the overriding force of leadership when a group leader was present.
Keywords: G r o u p decision support systems; Electronic meeting system; Leadership; Influence
Lai-Huat Lim is a Senior Tutor in the D e p a r t m e n t of Information Systems and Computer Science, National University of Singapore. He is currently a doctoral candidate at the Faculty of Commerce and Business Administration, University of British Columbia. Mr. Lim received his Bachelor's degree in electrical engineering and his Master's degree in MIS, both from the National University of Singapore. His current research interests include group decision support systems, negotiation support systems and decision support systems.
Correspondence to: Lai-Huat Lira, Faculty of Commerce and Business Administration, University of British Columbia, #402-2053 Main Mall, Vancouver, B.C., C a n a d a V6T 1Z2. t Professor Gerry DeSanctis provided the S A M M software and offered valuable advice during the course of this research. Professor Ilze Zigurs m a d e helpful suggestions and clarifications on protocol analysis. A T & T International (Singapore) Inc. loaned a 3B2 500 computer for the experiment. T h e anonymous reviewers contributed valuable suggestions which substantially improved the quality of this paper.
1. Introduction
A Group Decision Support System (GDSS), also known as an Electronic Meeting System (EMS), is a combination of communication, computer, and decision technologies for supporting problem formulation and solution in group meetings [8]. The technology interacts with other factors (e.g., task features, group characteristics, contextual variables, etc) to produce an effect on meeting process and outcomes [3], Correspondingly, it is important to take into account these variables in studying the impact of GDSS use. GDSS use has been extensively investigated for its interaction with factors including group size (e.g., [6,32]), task difficulty (e.g., [11]), member proximity (e.g., [12,18]), and so on. However, an important aspect of organizational meetings that has been rarely dealt with in GDSS research is leadership. Among other things, a group leader
K.S. R a m a n is Senior Teaching Fellow and Coordinator of the Information Systems Program, D e p a r t m e n t of Information Systems and Computer Science, National University of Singapore. Before taking up this appointment, he was CIO of a large multinational conglomerate in the AsiaPacific region. His teaching and research interests include m a n a g e m e n t information systems, decision support systems, group decision support systems, and application of information technology in organizations. He is on the editorial boards of the journals MIS Quarterly and International Information Systems. He is a m e m b e r of Sigma Xi and is listed in Marquis W h o ' s W h o in the World. Kwok-Kee Wei is a Senior Lecturer in the D e p a r t m e n t of Information Systems and Computer Science, National University of Singapore. He received his B.Sc. degree in computer science from the Nanyang University, Singapore and a D.Phil from the University of York, England. His current research interests include group decision support systems, strategic information systems, and user-database interactions.
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has the ability to introduce structure into a meeting [31], and is also capable of causing an unequal distribution of influence in the group. Since one of the (expected or real) effects of GDSS use is to ensure greater equality in participation, it is both interesting and important to see how this technology variable might interact with the leadership factor if both were present in a group meeting. The current research aims to examine such interacting effect on influence attempts in a decisionroom setting. Section 2 reviews the relevant literature in both leadership and GDSS research. Section 3 defines influence attempts, explains the theoretical justification for deriving the hypotheses, and presents the hypotheses. Section 4 describes the research method. Section 5 reports the statistical results. Section 6 discusses the findings and their implications.
2. Review of relevant literature The purpose of this section is to provide a brief review of previous research relevant to the current study. We do not review GDSS or leadership research in general; readers are referred to the revised Stogdill's handbook of leadership [1] for a review of leadership research and Benbasat, DeSanctis, and Nault [2], Dennis, Nunamaker, and Vogel [5], and Pinsonneault and Kraemer [26] for GDSS research. 2.1. Leadership in small groups
Leadership has been viewed and defined in various ways [1]. In this paper, we view leadership as the exercise of influence [27,29]. Indeed, leaders have been found to affect, through their influence acts, the performance and satisfaction of their subordinates. Performance variables which have been investigated in this context include group drive and cohesion, which can both be influenced by leadership [29]. Greene and Schriescheim [13] specifically found task- and socialoriented leader behaviors to be causally antecedent to group drive, and suggested that both types of leader behavior are also important to group cohesiveness. Besides group performance, leadership can also affect subordinates' satisfaction. For exam-
pie, consultative leadership would yield more subordinate satisfaction if the leader felt that members were highly committed to the group and its goals [10]. Moreover, low leader influence could reduce the impact of leader behavior on both satisfaction and performance [25]. 2.2. Relevant G D S S research
Turoff and Hiltz [31] studied the effect of human leadership and computer feedback in a conferencing environment. They found either of the treatments to have a significant effect on the ability of a group in reaching consensus. Nevertheless, such effect disappeared when both factors were present. They inferred that decision support aids may undermine human leadership. George, Easton, Nunamaker, and Northcraft [14] studied the effect of GDSS use, assigned leadership, and anonymity. They found two interaction effects, one owing to the interaction between leadership and anonymity on members' satisfaction with process, and the other owing to the interaction between leadership and technology on participation. The latter, which is more relevant to the current study, states that when a manual group had an assigned leader, and when a GDSS group had no leader, members' participation rates were more equal; in other words, manual groups without a leader and GDSS groups with a leader were more likely to have unequal participation rates. As regards influence and domination, two other GDSS studies, conducted by Lewis [21] and Zigurs, Poole, and DeSanctis [35], have found computer-mediated communication to prevent any one individual from dominating the group process; however, these studies did not involve the leadership factor.
3. Construct definition, theory and hypotheses 3.1. Defining influence
Influence attempts are attempts or undertakings to move, affect, or determine a course of action. Following Zigurs et al. [35], this construct has been operationalized behaviorally in this study in terms of verbal and other acts of individual
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members. The m e a s u r e m e n t of these components will be dealt with in section 4. Multiple aspects of influence are studied using three dependent variables: (1) amount of influence behavior, which sums up the individual influence scores of the group, (2) influence inequality, which is a " r o o t - m e a n - s q u a r e " measure and reflects inversely the equality of influence distribution, and (3) dominance significance, which is the ratio of the most dominant m e m b e r ' s influence to the average influence score of the other members. These variables are mathematically defined in the following.
Amount of influence behavior This is defined as the sum of the individual influence scores. This m e a s u r e m e n t is useful as it will bear knowledge about what kind of treatment condition facilitates (or tempts) influence behavior. Denoting the individual influence score as T, for m e m b e r i, where i ranges from one to five for a five-member group, the amount of influence behavior of the group ( A ) is 5
A= ETi. i-1
Influence inequality This is defined for a group as the root-meansquare calculated from all m e m b e r s ' influence scores. This m e a s u r e m e n t is useful and important for understanding how GDSS technology and leadership variable interact to enhance or inhibit evenness of influence distribution among group members. Mathematically, influence inequality, I, is defined as
Dominance significance This is defined for a group as the ratio of the highest influence score (which, by definition, belongs to the most dominant m e m b e r ) to the average influence score of the other members. This variable provides another view for looking at how "democratic" is the group discussion. Unlike the previous variables which deal with influence at the group level, dominance significance captures the " n o r m a l i z e d " influence of an individual m e m b e r (specifically, the most dominant mem-
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ber). Dominance significance, D, is mathematically defined as D = Tmax/ ~
E
T~ ,
i = 1 ,i ~ m a x
where Tm~x is the influence score of the most dominant member.
3.2. Theory and hypotheses In this section, we derive two sets of hypotheses, one pertaining to each independent variable. The hypotheses related to GDSS technology are developed based on a communication-process perspective. The hypotheses related to elected leadership are based on Hopkins' [17] proposition on rank-influence relationship.
A communication-process perspective of GDSS use DeSanctis and Gallupe [8] propose an information-exchange perspective on the use of GDSS. According to this view, the decision process is revealed in the production and reproduction of positions regarding group action, which are directed toward the convergence of members on a final choice. Supporting group decision making primarily involves changing, in a positive direction, the interpersonal exchange that occurs as a group proceeds with the problem solving process. In this sense, the goal of GDSS is to alter the communication process within groups. We propose that such alteration is achieved primarily through adding to the existing communication channels an electronic channel, characterized by two useful features: multi-accessibility and anonymous input procedure. (See also [22] for a detailed discussion of the electronic communication channel.) In contrast to the verbal channel which allows only one m e m b e r to "access" at any one time in order to be effective, the electronic channel of the GDSS grants multiple accesses at the same time. M e m b e r A need not wait for the "completion" of m e m b e r B before gaining access to the channel. This has significant implication with respect to power and influence in groups. Members who used to dominate the verbal channel prior to the implementation of GDSS cannot prevent others from using the electronic channel in a GDSS environment, and it becomes more difficult for
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them to remain in dominance. Other than reducing domination, multi-accessibility also reduces other process losses and increases process gains [24]. For example, as N u n a m a k e r et al. [24] pointed out, process loss due to "air time fragmentation" (i.e., the group must partition available speaking time among themselves) can be reduced because of the parallel communication that is made available by the multi-accessibility feature. The anonymity feature of the input procedure also has great impact on the group's influence process as this feature is able to detach ideas from their proponents. In the absence of the electronic channel, some group m e m b e r s may tend to shy away from using the existing communication channels including the verbal channel. This may be due to the presence of dominating individuals, the fear of contributing " w r o n g " ideas, and so on. However, if ideas and preferences are exchanged anonymously, individual m e m b e r s will not know who favors what, or where specific m e m b e r s stand on an issue. In other words, some critical political information that is often obtained in meetings will be lost when GDSS technology is introduced. This should greatly reduce the influence of members with high perceived power, and strongly discourage the e m e r g e n c e of new power. T h e r e f o r e , anonymity reduces process losses associated with conformance pressure and evaluation apprehension, and increases processes gains due to learning and more objective evaluation [24]. In sum, the use of GDSS leads to an enhanced communication environment. The amount of influence behavior should increase since meeting participants are now given more choices in the use of communication channels; m e m b e r s who previously feared to speak their ideas may now " e n t e r " their ideas through the terminals. Influence inequality will be lowered by directly benefitting from the two features of the electronic channel: The multi-accessibility feature makes the channel equally available to all meeting participants; the anonymity feature encourages more participation from the otherwise "shy" m e m b e r s by detaching ideas from their proponents. Similarly, dominance significance will reduce as the electronic channel cannot be easily dominated by any individual. Moreover, the important social and political cues which had previously helped
maintain or promote the p h e n o m e n o n of dominance may be lost when ideas and preferences are exchanged anonymously. Based on the above deliberation, we propose the following hypotheses regarding the effect of GDSS use: 2
HI: The total amount of influence behavior is greater in a group supported by GDSS than in a group without GDSS. H2: Influence inequality is lower in a group supported by GDSS than in a group without GDSS. H3: Dominance significance is lower in a group supported by GDSS than in a group without GDSS. The "rank-influence" perspective of leadership H o p k i n s [17] p r o p o s e s interrelationships among five status-related properties: rank, centrality, observability, conformity, and influence. O f particular interest to this study is his proposition relating rank to influence, which states that for any m e m b e r of a small group, the higher his rank, the greater is his influence. (The reasoning behind this simple relationship is that a higher rank is associated with greater centrality, which leads to greater observability, and consequently, greater influence.) Hopkins' rank-influence assertion suggests that a leader, if accepted to be one so as to justify his "rank", has greater influence than other group members. This proposition stems from the theory of authority, particularly from the argument of legitimacy. An example is the important statement by H o m a n s [16] that "the sentiments of the leaders of a group carry greater weight than those of the followers in establishing a social ranking" (p. 181). Since the elected leader is expected to have greater influence than other m e m b e r s as a result of his higher (legitimate) rank, he "naturally" becomes the dominant m e m b e r of the group. (The legitimacy of the leader's rank has especial
2 A counter argument exists for H1 and H2 which does not arise out of the information-exchangeview but is based on the novelty of technology. Specifically, for a novel technology such as GDSS, members may differ in their initial comfort and apprehensiveness, so that members who are faster acquainted with the technology may become more influential in the group's use of the GDSS. This argument was not tested in the current study.
L.-H. Lim et al. / Decision Support Systems 12 (1994) 199-211
significance in the setting of this study since the Singaporean culture accords high status and influence to a formal leader [15]. This point will be further elaborated in Section 6.) The effect is seen in terms of more unequal influence distribution and higher dominance significance in groups with elected leader. The impact of leadership on "total amount of influence behavior" (i.e., one of the three dependent variables defined earlier) cannot be predicted by the existing theory and is therefore not hypothesized. Correspondingly, we propose the following hypotheses regarding elected leadership: H2a: Influence inequality is higher in a group
with elected leader than in a group without elected leader. H3a: Dominance significance is higher in a group with elected leader than in a group without elected leader.
4. Research method 4.1. Research design and subjects
This study involved a laboratory experiment with a two-by-two (i.e., GDSS vs. Manual; Leadership vs. No leadership) factorial design. A total of eight groups per cell took part in the experiment, and each group consisted of five members. Owing to the high cost associated with the interaction analysis techniques chosen for this research, a subsample of five groups per cell was selected for the interaction analysis. Subjects consisted of first-year computer science undergraduates at the National University of Singapore. All participants had used computers before taking part in the experiment. The subjects were given course credit for their participation. More than one half of the subjects were males who had served two and a half years of national (military) service and had worked in teams before. Because subjects were randomly assigned to groups, most groups had no prior history of working together and are thus ad hoc groups. Correspondingly, when interpreting any findings of the current study, it ought to be taken into account the previous experimental evidence that members of established GDSS groups tend
2(13
to participate less equally than members of ad hoc GDSS groups [4]. 4.2. Research task
Many organizational meetings occur without prior or post knowledge of the "correct" outcome of a group meeting. For this reason, this study aimed to build on the available knowledge of GDSS impacts by examining the usefulness of the technology in situations where a group had to resolve competing personal preferences and maximize agreement on a solution to a problem. In such situations, achieving high decision quality would not be the primary goal of the group meeting. The preference allocation task used in this experiment was adapted from that developed and validated by Watson, DeSanctis, and Poole [33], with changes aimed at localizing the context. The task required subjects to allocate a given sum of money among six competing projects that had requested funds from a philanthropic foundation [33]. Conflict would arise because the members would have different preference structures, thus resulting in different allocation patterns. During the experiment, there was no time-limit specification for the task. On the average, each group took thirty minutes to complete its task. 4.3. The GDSS
The GDSS used in this research is the Software Aided Meeting Management (SAMM) system (version 1.3) developed at the University of Minnesota. A detailed description of the system can be found in Desanctis, Sambamurthy, and Watson [9]. Version 1.3 of SAMM provides seven features: problem definition, input of selection criteria, input of alternatives, ranking, rating, voting, and solution definition. Some of these features (e.g., ranking, rating, voting) serve similar purposes; groups made their own choice as regards which or how many of such "similar" features should be used. 4.4. Measurement of dependent ~,ariables
This study investigated three dependent variables: amount of influence behavior, influence inequality and dominance significance. These
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variables are realized through manipulations of the individual influence scores. Essentially, amount of influence behavior is the sum of these basic scores; influence inequality is conceptually equivalent to the standard deviation of the scores; and dominance significance is a ratio made out of the scores. This section looks at how the individual scores were obtained.
Verbal component Basically, each influence score consists of a verbal component and a nonverbal component. The verbal acts were analyzed using a scoring method [30], i.e., working from videotapes, the verbal acts (where "act" here refers to an instance of behavior) for each individual were coded under various categories of behavior. The interaction coding scheme used was that developed and validated by Putnam [27], and which had been intended for coding procedural messages (i..e., statements that guide the work of the group), including what the group is doing, where it is going, and what it should do. Procedural communication "occupies a substantial portion of group talk time, performs vital meta-message functions, and serves as indices of leadership emergence and decision making processes" [27] (p.332). Specifically, five types of verbal behavior are considered as constituting attempts to influence; these are behavior of initiation; goal-orientation; integration/summarization; implementation; and general processual direction. Zigurs [34] revised the scheme to study decision process under the influence of technological support and group size. Since the current research aimed to measure the effect of GDSS on influence behavior, it employed Putnam's coding scheme as revised by Zigurs. In justifying her choice of Putnam's scheme, Zigurs pointed out that since a GDSS is likely to have the most impact on how groups structure their work, capturing procedural messages is particularly important in such an analysis. Nonverbal component The nonverbal influence acts were measured by simple counting using computer log files or video tapes. There was no attempt to conduct an indepth analysis of nonverbal behavior such as eye gaze, hand gestures, facial expressions, and so on. The purpose of coding nonverbal procedural be-
havior was to capture influence attempts via the use of GDSS or its manual structure equivalent that would not have been captured by the verbal coding system. Consequently, the emphasis here is on a category called nonverbal procedural behavior [34], which consists of actions that reorient or change the group's visual attention through the use of supplementary visual aids. In the current context, nonverbal behavior can be either electronic, which occurs through the use of a large screen driven by GDSS, or manual, through the use of a flipehart. Depending on whether or not a group is provided with a GDSS, either the electronic nonverbal behavior or the manual nonverbal behavior may be defined. Uses of GDSS that suggest influence include changing the current display on the public screen, deleting an item from the system (which may be a problem definition, a selection criterion, or an alternative definition), and using the group communication feature. The number of times each individual member assumed any one of these categories of behavior was counted with an analysis of the computer log files. Corresponding behavior types were identified for manual groups by viewing videotapes. These behavior types consist of changing the currently displayed page of the flipchart, crossing out material on the flipchart, and writing comments on the flipchart.
4. 5. Experimental procedure Whereas all groups went through a warm-up task, only groups assigned to the leadership condition were asked to elect a leader after this task. The leader was instructed to focus the group's discussion, suggest specific ranking changes, promote consensus, and summarize the progress of meetings. These were the same responsibilities given to the group leaders in Turoff and Hiltz's [31] study. In the next major phase of the experiment, groups received different types of training depending on the (technological) treatment each was administered to. The computer-supported groups received training on how to use the GDSS. Essentially, they were led by the experimenter through the agenda provided by the SAMM software and given the opportunity to enter their inputs during each phase of the agenda. As for the manual groups, they were introduced to and
L.-H. Lim et al. / Decision Support Systems 12 (1994) 199-211 m a d e f a m i l i a r with an a g e n d a closely p a r a l l e l i n g t h e a g e n d a o f t h e S A M M system. I n t h e final p h a s e o f the e x p e r i m e n t , g r o u p s t a c k l e d t h e e x p e r i m e n t a l t a s k with o r w i t h o u t G D S S a n d / o r e l e c t e d l e a d e r s h i p . D u r i n g this p h a s e , m a n u a l g r o u p s w e r e a s k e d to follow t h e a g e n d a a f o r e m e n t i o n e d , a n d w e r e given aids including a flip chart, p e n c i l a n d p a p e r . T h e i d e a was to m a k e t h e s t r u c t u r e of t h e e x p e r i m e n t as e q u a l as p o s s i b l e b e t w e e n the two t r e a t m e n t conditions, so t h a t any o b s e r v e d d i f f e r e n c e m a y b e a t t r i b u t e d to t h e t y p e o f t e c h n o l o g i c a l s u p p o r t . F o r e a c h g r o u p r e g a r d l e s s o f its t r e a t m e n t , t h e e n t i r e m e e t i n g was v i d e o t a p e d .
4.6. Manipulation check T h e l e a d e r s h i p t r e a t m e n t was c h e c k e d in two ways. O b s e r v a t i o n o f t h e m e e t i n g s as well as viewing of t h e v i d e o t a p e s i n d i c a t e d t h a t t h e g r o u p l e a d e r s had, at d i f f e r e n t p o i n t s of t h e m e e t i n g , a t t e m p t e d to a d d r e s s e a c h of t h e f o u r responsibilities a s s i g n e d to them. M o r e i m p o r t a n t l y , it was f o u n d t h r o u g h c o d i n g that, for n i n e o u t o f t h e t e n e l e c t e d - l e a d e r groups, t h e h i g h e s t i n f l u e n c e score c a m e f r o m t h e l e a d e r . A s for t h e e x c e p t i o n , t h e g r o u p l e a d e r ' s score was very close to t h e h i g h e s t score. Since t h e p r o b a b i l i t y of achieving this situa t i o n by chance a l o n e is a l m o s t z e r o 3, we conclude that the leadership variable had been properly o p e r a t i o n a l i z e d .
5.1. A m o u n t of influence behavior T a b l e 1 s u m m a r i z e s the m e a n s a n d s t a n d a r d deviations of amount of influence behavior. Table 2 p r e s e n t s t h e A N O V A table, which shows significant effects for b o t h d e c i s i o n aid a n d l e a d e r s h i p factors. S e p a r a t e t-tests w e r e c a r r i e d out for t h e i n d e p e n d e n t v a r i a b l e s a n d b o t h t u r n e d o u t to b e significant. Thus, t h e h y p o t h e s i s r e l a t e d to decision aid (i.e., H I ) was c o n f i r m e d . T h e m a i n effect of e l e c t e d l e a d e r s h i p was not h y p o t h e s i z e d .
5.2. Influence inequality M e a n s a n d s t a n d a r d d e v i a t i o n s of i n f l u e n c e i n e q u a l i t y a r e shown in T a b l e 3, T h e m e a n scores
Table 1 Amount of influence behavior: Mean score Istandard deviation, cell size). Leader No leader Total
GDSS
Manual
Total
193.60 (18.81,5) 269.20 (24.26,5) 231.40 (44.79,10)
127.20 (20.33,5) 185.80 (23.59,5) 156.50 (37.21,10)
160.40 (39.56,10) 227.50 (49.40,10) 193.95 (55.52,20)
Table 2 Amount of influence behavior: analysis of variance. Source of variation
5. Results T h e A N O V A m o d e l was u s e d to d e t e c t significant effects. S t e p s have b e e n t a k e n in t h e analysis to e n s u r e t h e satisfying of t h e t h r e e a s s u m p t i o n s underlying the ANOVA model, namely, homog e n e i t y of v a r i a n c e , i n d e p e n d e n t s a m p l e s , a n d n o r m a l i t y o f e r r o r t e r m s [23]. F o r e a c h o f t h e o b s e r v e d significant effects arising o u t o f t h e analysis o f v a r i a n c e , a s u b s e q u e n t o n e - s i d e d t-test was c o n d u c t e d to c o n f i r m o r d i s c o n f i r m t h e rel a t e d h y p o t h e s i s . A 5 % level o f significance was u s e d in all F - t e s t s a n d t-tests. 3 The probability of getting the highest influence score for the leader in nine out of ten groups assuming that influence was randomly distributed among all group members can be calculated as follows: P = 0 . 2 9 * 0.81 + 0 . 2 1 ° = 0.0000(1051.
205
df
Decision aid Leadership Decision aid X leadership Error Total
SS
F
1 1 1
28050 22510 361
58.67 * * 47.06 * * 0.76
16 19
7650 58573
** p < 0.01.
Table 3 Influence inequality: Mean score (standard deviation, cell size). Leader No leader Total
GDSS
Manual
Total
62.70 (21.24,5) 27.04 (9.89,5) 44.87 (24.43,10)
55.95 (9.69.5) 58.89 (12.40,5) 57.42 (10.60,10)
59.32 (15.96,10) 42.96 (19.84,10) 51.14 (19.43,20)
L.-H. Lim et al. / Decision Support Systems 12 (1994) 199-211
206 Influence Inequality
Table 5 Influence inequality: Analysis of simple effects of leadership factor.
70__
Source of variation
Leader
60__
Leadership @ GDSS Leadership @ Manual Error
50__ Leader
4 0
df
SS
F
1
3179
15.97 * *
1
22
16
3186
0.11 -
** p < 0.01.
30__ 2O
I
I
Manual
GDSS Fig. 1. M e a n scores of influence inequality.
Table 6 Influence inequality: Analysis of simple effects of decision-aid factor. Source of variation
Table 4 Influence inequality: analysis of variance. Source of variation Decision aid Leadership Decision aid X leadership Error Total
df
SS
F
1 1 1
788 1338 1863
3.96 6.72 * 9.35 * *
16 19
3186 7174
-
df
Decision aid @ Leader Decision aid @ No Leader Error
SS
1
114
l
2536
16
3186
F 0.57 12.74" * -
* * p < 0.01.
5.3. Dominance significance
* p < 0.05. ** p < 0.01.
are also shown graphically in Figure 1, which indicates an interaction effect between the independent variables. The output of the A N O V A procedure is presented in Table 4. It can be seen that the leadership factor had a significant main effect on influence inequality. A follow-up t-test confirmed the hypothesis related to this main e f f e c t (i.e., H2a). In addition, there was a significant interaction effect of the independent variables. An exploratory analysis was necessary. The method of analysis of simple effects [19] was used to analyze the observed interaction. The simple effects of each factor are recorded in Tables 5 and 6. The analysis of the leadership factor (Table 5) shows significant effect under the GDSS condition. On the other hand, in the analysis of the decision-aid factor (Table 6), the treatment effect was significant for no-elected-leader groups. For each of these significant F-tests, the follow-up t-test confirmed the significant difference.
To satisfy the assumptions of the statistical model, dominance significance was transformed Table 7 (Inverse) dominance significance: M e a n score (standard deviation, cell size).
Leader No leader Total
GDSS
Manual
Total
0.36 (0.20,5) 0.71 (0.05,5) 0.53 (0.23,10)
0.18 (0.09,5) 0.31 (0.10,5) 0.24 (0.11,10)
0.27 (0.18,10) 0.51 (0.22,10) 0.39 (0.23,20)
Table 8 (Inverse) dominance significance: analysis of variance. Source of variation Decision aid Leadership Decision aid X leadership Error Total ** p < 0.01.
df
SS
F
1 1 1
2.88 2.55 0.07
13.25" * 11.71" * 0.32
16 19
3.48 8.98
-
L.-H. Lim et al. / Decision Support Systems 12 (1994)
using an inverse function. Means and standard deviations of (inverse) dominance significance are shown in Table 7. Table 8 presents results of the analysis of variance. T h e r e were significant main effects for both decision aid and leadership factors. Subsequent t-tests confirmed both of the related hypotheses (i.e., H3 and H3a).
6. Discussion
199-211
207
leadership that they simply submitted to it by minimizing their own influence attempts. Apparently, when the issue of power and authority has been m a d e certain in a group (for example, through election), group m e m b e r s are likely to submit to the leader rather than try to overtake h i m / h e r . Therefore, they exhibit much less influence behavior. As a result, the total amount of influence associated with elected-leader groups was observed to be less in comparison to no-elected-leader groups.
6.1. Findings on amount of influence behavior 6.2. Findings on influence inequality The hypothesis related to technological support was supported by the statistical findings, i.e., GDSS did bring about a greater total amount of influence behavior. The electronic communication channel had served as an alternative for m e m b e r s who did not want to use the verbal channel for one reason or another. With the new channel, there was a lower risk of exposure due to the anonymity feature, so that m e m b e r s who used it need not be afraid of being criticized for wrong or lousy ideas. This finding supports the information-exchange perspective offered by DeSanctis and Gallupe [8] which was used to derive the related hypothesis. A favourable view on the use of GDSS is implied here. In the context of a preference-allocation task where there is no correct answer to be anticipated and thus no expertise required, it is only healthy and fair that everybody has h i s / h e r favoured communication channel for attempts to influence others. It should be cautioned that the finding could be partly due to the early stages of development of the experimental groups, as it has been suggested that during the early stages of group development, group m e m b e r s tend to define and defend their positions, and try to obtain a basis of influence over the decision process [20]. The generalizability of this finding to groups in their advance stages of development may thus be limited [5]. Although the relationship between leadership and amount of influence behavior was not hypothesized, findings suggest that groups without elected leader generate more influence behaviors than groups with elected leader. It seems that the elected leaders were exercising influence at the expense of the other members, and the non-leader m e m b e r s were so much " h a u n t e d " by the elected
The hypothesis related to the decision technology was not supported, but that related to elected leadership was. It was found that influence behaviors were more evenly distributed in groups without elected leader. However, an interaction effect was observed in addition to the main effect of elected leadership. Further analysis showed that a GDSS had no effect on elected-leader groups, but caused a more e~en influence distribution than manual support did in groups without elected leader. By omitting the insignificant effects, Figure 1 can be simplified into Figure 2. Referring to Figure 2, starting from the manual-support condition: for a group with an elected leader, the effect of GDSS was horizontal, i.e., there was no improvement; for a no-electedleader group, there was a downward effect, causing the influence distribution to become more even than before. An interesting p h e n o m e n o n is revealed by these observations: GDSS does discourage the emergence of new power in the case
Influence Inelaality (Manual, NoLeader) (GI~SS, L ~
a
~
.~Ma-nual, Leader)
(GDSS, NoLeader) Fig. 2. Interactingeffectson influenceinequality.
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where there is no established leadership, but does not stop the already established formal leadership from exercising influence. What follows from this conclusion are two positive implications derived from two different situations. In an organizational meeting involving a group of " p e e r s " with no rank differentials solving a preference-allocation task, a more even influence distribution is achievable with the aid of GDSS, and that is desirable for the group. It must be qualified that this is a desirable situation because the task type is a preference allocation task. A preference allocation task, being one which has no correct answer, requires no single member to be more influential than the other group members to arrive at a " b e t t e r " or the " b e s t " solution. Instead, the solution is shaped by each member's preference. Therefore, it is only fair that each member has a share in influencing the others. Without the use of GDSS technology, dominant members may compete to become the informal leader even in the early stages of meeting, a phenomenon which may not be desirable. On the other hand, an egalitarian pattern of influence distribution may not be suitable for groups with formal leaders. In real life organizations, leaders are usually the ones who decide whether or not to implement new technologies. If GDSS technology were found to improve influence distribution in group discussions at the expense of the leader's influence, it might not be easily adopted. As the finding has indicated that GDSS does not give rise to a more even distribution of influence in the presence of a leader, it implies that leaders may show less resistance to its adoption. 6.3. Findings on dominance significance The hypothesis related to decision technology was supported; this means that GDSS groups reported lower dominance significance than manual groups. Since dominance significance measured the most dominant member's influence score over the average score of the other members, the finding has provided us with insight into GDSS's ability to reduce individual dominance. The "multi-accessibility" feature of the electronic communication channel made it almost impossible for a dominant individual to prevail through the use of this channel, since at any one
time, more than one member could gain access to the channel. Also, the anonymity feature of the electronic communication channel had caused some social cues associated with the usual political dynamics of the group to be lost. These effects together made it much more difficult for the otherwise dominant individuals to remain in dominance in a GDSS environment. Thus, GDSS intervention had the effect of reducing the dominant individual's influence through its multiaccessibility and anonymity features. The absence of significant interaction effect appears to suggest that GDSS had reduced the dominance of an individual regardless of whether h e / s h e was a formal leader, a derivation which contradicts the conclusions arrived at in the case of the influence inequality measure (where leadership was found to have an overriding effect over the use of GDSS). A follow-up exploratory analysis revealed that the significant main effect of decision support had largely been due to the no-elected-leader groups. When the scores of the elected-leader groups alone were tested, no significant difference was found in the dominance significance between GDSS and manual treatments. It thus confirmed our earlier conclusion that GDSS discourages the emergence of new power in the group but does not stop the already-established leadership from exercising influence. The hypothesis related to elected leadership was supported, since groups with elected leader reported higher dominance significance than groups without elected leader. It was found that in all cases but one, the most dominant member in an elected-leader group was actually the elected leader himself/herself. Even in the exceptional case, the leader was almost the most dominant member. We make an attempt here to link this finding with the issue of formal versus informal leadership. An elected leader, being formally elected by the group members in a unanimous manner, is by definition a formal leader. From the perspective of the exercise of influence, the most dominant member in a group without elected leader can be regarded as the informal leader of the group. Given this interpretation and the findings we obtained, it can be concluded that formal leadership commands a higher dominance over group members than informal leadership does. In other words, the findings appear to suggest that
L.-H. Lim et aL / Decision Support Systems 12 (1994) 199-211 Table 9 Comparison of findings Study
Findings
Zigurs et al. [35] a
GDSS caused more equal distribution of influence. A leader in manual groups and no leader in GDSS groups led to the most equal participation. GDSS groups with no leader led to the most equal distribution of influence
George et al. [14]
Current study
a Experimental groups contained no formal leaders.
formal leadership is "better" accepted than informal leadership by group members.
6.4. Comparison with preuious studies This section compares the findings of this study with those of two previous GDSS studies, George et al. [14] and Zigurs et al. [35]. George et al. examined the effect of GDSS, leadership, and anonymity on participation (among other dependent variables); Zigurs et al. studied the effect of GDSS on influence using constructs similar to those employed in the current study, although the experimental groups used in Zigurs et al.'s study had no formal leaders. Table 9 summarizes the findings of the three studies on comparable dependent variables. A common finding shared by these studies is that GDSS-supported groups with no (formal) leader had the most equal participation or influence. Therefore, it is important that organizational groups employing the technology take into account the proper "mix" of the group structure, with special regard to formal leadership. This implies that for organizational meetings intending to see influence being distributed in an egalitarian pattern by using GDSS, steps must also be taken to ensure that the relationships between participants are of a " p e e r " nature so as to avoid any obvious status differentials. Besides the above similarity in the studies' findings, a noticeable difference also exists. George et al. found that manual groups with a leader had comparable equality in participation as GDSS groups with no leader, whereas the current study found the two conditions to be
20q
significantly different. The fact that leadership had dissimilar impacts within the non-GDSS groups between the studies may be accountable using a cultural explanation as follows. Hofstede [15] found the Singaporean culture to differ from the American culture in two important aspects: individualism and power distance 4. The Singaporean culture is characterized by low individualism and high power distance, whereas the American culture exhibits almost opposite characteristics. The implication of low individualism is that an individual in this culture will tend to see himself/herself as part of "we" and strive for group interest. The interpretation of high power distance is that both supervisors and subordinates in the related culture expect power differences to be translated into visible status differentials. Consequently, in the traditional (i.e., non-GDSS) meeting environment, higher status and influence is accorded to the leader in the Singaporean culture than in the American culture. This explanation is consistent with the difference observed between George et al. and the current study as regards the difference in participation within the manual groups with a leader. The importance of culture in GDSS research is thus evident. Two points follow from this observation. Firstly, the generalizability of the findings here is restricted by the cultural factor. Secondly, and perhaps more importantly, future research should pay more attention to issues related to cross-cultural differences in GDSS design and use [7]. A major reason contributing to the increasing importance of the cultural factor is the globalization of work force [28].
6.5. Limitations o f study In addition to those limitations pointed out elsewhere in the paper, the findings of this study
4 "Individualism" stands for a preference for a loosely knit social framework in society in which individuals are supposed to take care of themselves and their immediate families only, as opposed to "collectivism",which stands for a preference for a tightly knit social framework in which individuals can expect their relatives, clans, and other ingroups to look after them, in exchange for unquestioning loyalty. "Power Distance" is the extent to which society accepts the fact that power in institutions and organizations is distributed unequally.
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a r e also subject to t h e following two limitations. Firstly, H o p k i n s ' [17] t h e o r y has n o t b e e n very m u c h t e s t e d since its c o n c e p t i o n . Obviously, t h e derived propositions regarding leadership would have b e e n o t h e r w i s e stronger. Secondly, typical use o f S A M M involves b o t h t h e e l e c t r o n i c a n d v e r b a l c o m m u n i c a t i o n s . This is in c o n t r a s t to s o m e o t h e r G D S S s (e.g., G r o u p S y s t e m s ) w h e r e e l e c t r o n i c c o m m u n i c a t i o n typically a l m o s t rep l a c e s v e r b a l c o m m u n i c a t i o n . It is p o s s i b l e t h a t a g r o u p l e a d e r w o u l d find it m o r e effective to exerCise his i n f l u e n c e with b o t h v e r b a l a n d e l e c t r o n i c c h a n n e l s t h a n with t h e e l e c t r o n i c c h a n n e l alone. Thus, g e n e r a l i z i n g t h e results h e r e to a setting involving s o m e o t h e r G D S S s s h o u l d b e d o n e only a f t e r this s u b t l e d i f f e r e n c e has b e e n t a k e n into account.
7. Conclusion GDSS-supported groups, aided with the a n o n y m i t y f e a t u r e to d e t a c h p r o p o s e d i d e a s f r o m t h e i r p r o p o n e n t s , r e p o r t e d l a r g e r a m o u n t s o f inf l u e n c e b e h a v i o r t h a n m a n u a l l y - s u p p o r t e d groups. T h e r e was n e v e r t h e l e s s lack o f e v i d e n c e to support the assertion that GDSS promotes equality o f i n f l u e n c e in all groups. I n s t e a d , an i n t e r a c t i o n effect was o b s e r v e d . G D S S was f o u n d to b e useful in s u p p r e s s i n g t h e e m e r g e n c e o f n e w p o w e r f r o m t h o s e w h o s o u g h t it. A s a result, t h e influe n c e d i s t r i b u t i o n was m o r e even in n o - e l e c t e d l e a d e r g r o u p s given t h e G D S S t r e a t m e n t t h a n in n o - e l e c t e d - l e a d e r g r o u p s given t h e m a n u a l t r e a t ment. Nevertheless, GDSS could not stop the e l e c t e d l e a d e r f r o m exercising influence, i.e., e l e c t e d l e a d e r s h i p a p p e a r e d to have an o v e r r i d ing effect over G D S S use. C o n s e q u e n t l y , no diff e r e n c e was r e p o r t e d b e t w e e n G D S S a n d m a n u a l t r e a t m e n t s for t h e e l e c t e d - l e a d e r groups. Also, it h a d b e e n i n d i c a t e d statistically t h a t G D S S red u c e d i n d i v i d u a l d o m i n a n c e in groups. In fact, t h e r e s u l t h e r e was similar in p a t t e r n to t h a t o n i n f l u e n c e d i s t r i b u t i o n such t h a t l e a d e r s h i p still h a d a n o v e r r i d i n g force over t h e use o f G D S S ( a l b e i t to a lesser e x t e n t in t e r m s o f d o m i n a n c e significance so t h a t it was insufficient to c a u s e a significant i n t e r a c t i o n effect). W e t h e r e f o r e conclude that GDSS promotes more democratic g r o u p discussion in t h e a b s e n c e o f an e l e c t e d leader.
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