Influence of Computer-Based Meeting Support on Process and Outcomes for a Divisional Coordinating Group

This research examines the introduction of computer-based group decision support systems (GDSS) to members of a division level coordinating group. Participants performed authentic problem formulation tasks which varied naturally in degree of structuredness, in two non-GDSS meetings then were provided GDSS for four additional meetings. It was proposed that the introduction of the GDSS and task structuredness would influence (1) group process in terms of the amount of divergent and convergent thinking communicated during meetings and (2) perceived outcomes regarding quality, satisfaction, understanding, confidence, and commitment to group positions. Results suggest that GDSS use affected both the total amount and pattern of group communication but not perceived outcomes. Structuredness of the task affected perceived outcomes but neither amount nor patterns of communication. Additional qualitative data regarding perceived of costs and benefits in using GDSS provide richer explanation for study findings and suggest further lines of inquiry.     

Artificial Neural Systems as a Research Paradigm for the Study of Group Decision Support Systems

Artificial neural systems (ANSs) have received interest recently because of their ability to accurately forecast and classify data. Group decision support systems (GDSSs) also have received much interest for their support of group communication and decision making. This paper explores the potential of the ANS as a methodology for modeling the many complex, interrelated research variables involved in the field of GDSS. As an illustration, multilinear regression, an ANS with backpropagation, and an ANS with a genetic algorithm were developed to classify 133 subjects into verbal or GDSS groups based on their responses to a questionnaire. The ANSs with backpropagation and the genetic algorithm achieved higher classification accuracies (81.8 and 90.9%, respectively) than was achieved with multilinear regression (75.8%). Therefore, an ANS may more accurately model the many interrelationships occurring with GDSS group behavior.     

Cooperation support through the use of group decision systems

This article considers the development of the group decision support system (GDSS) field both from organizational and technological perspectives. The growing importance of teamwork, lateral coordination, and activities integration inside modern business organizations is emphasized. Technological and knowledge specialization, quick transformation of business environments, reduction of response time, and so on, are some of the reasons that can explain the renewed relevance of teamwork. Also, the development of information technology (IT) is analyzed in relation to the role it is assuming in supporting group activities. Research in the GDSS field is then introduced. A proposal concerning the identification of three different phases in GDSS studies is developed, ranging from decision rooms to distributed systems. Each phase shows distinctive research topics and application fields, together with different organizational goals. Results of these developments are the growth of potential application areas of GDSS tools. These theoretical considerations, together with empirical experiences coming from the study of a real manufacturing environment (an IBM plant where group cooperation plays a fundamental role for production efficiency), constitute the basis for a research GDSS prototype (GROUPS). Prototype features are designed to support executives in facing production‐planning problems through an improvement in communications and in knowledge representation.     

Executive GDSS: Behavioral considerations at individual,organizational, and environmental levels of analysis

This article emphasizes the importance of behavioral considerations at individual, organizational, and environmental levels of analysis when researching and evaluating the design, implementation, and use of group decision support systems (GDSS) within complex organizations. Discussion is based on interview and archival data collected on an executive level GDSS used within a corporate setting. Issues that are considered generalizable to organizational computing, coordination, and collaboration technologies concern (a) viewing organization participants as strategic, intuitive information processors, (b) understanding the importance of organizational power, politics, and situational constraints on decision making, and (c) appreciating the symbolic value of advanced information technologies to an organization's external environment.     

Evolution of group performance over time: A repeated measures study of GDSS effects

Many studies in the group decision support system (GDSS) literature have reported on the behavior and performance of ad hoc groups meeting for the first, and, in fact, the only time. Such one‐time studies of groups may not represent their longer term behavior and performance accurately. Adaptive Structuration Theory (AST) conceives of technology use as a social practice that emerges over time. AST suggests that meeting outcomes reflect the extent to which structures offered by the technology (such as GDSS tool sequences, meeting agenda, etc.) are faithfully appropriated by the group. Such faithful appropriation, however, takes time. This article explicitly recognizes the relevance of this appropriation process and reports on a lab study that examined the impact of computer support on group performance over time. In general, results showed that the performance of computer‐supported groups improved over time, whereas the performance of non‐computer‐supported groups stayed the same or declined. The number of alternatives generated by computer‐supported groups increased considerably as they became more proficient in incorporating the technology into group processes. However, the quality of decisions made by computer‐supported groups began to increase slightly, only during the last session. Both these findings suggest that AST is, in fact, a viable theory for studying group behavior and performance over time. Results from this study also point out the need for conducting more longitudinal studies of group processes in the future.     

Technology and Group Decision Process in Going-Concern Judgements

Accounting and auditing practices are continually being affected by advances in technology. This study empirically examined the effect of group decision processes and technological advances on group going-concern decision making. Groups with access to group decision support systems (GDSS) were compared to groups without access to GDSS for their going-concern judgments. The results show group discussion induced auditors to be more conservative and to consider factors which may have overlooked at the individual level, though neither structure significantly reduced the considerable variance in the individual going-concern judgments. Further, as compared to their counterparts in the face-to-face discussion groups, GDSS groups indicated much higher confidence in their group's final assessment of the client's going-concern status and a higher level of satisfaction and agreement with the group decision processes. The findings suggest that while group discussions did not significantly reduce auditors' considerable variance in going-concern judgments, future research should investigate which explicit models would improve the consensus on going-concern evaluations.     

An object-oriented architecture for group decision support systems

An object-oriented GDSS can produce a rich environment for easily accessing software tools or applications running under a Graphical User Interface and can provide communication among meeting participants. This requires definition of (1) objects to manage the meeting and participant sessions, (2) applications that can run under these sessions, and (3) data storage and data communications capability that handle both private and shared data. This article suggests that a GDSS system can operate under three layers of software: an application-layer, a GDSS environment, and an operating system environment. It defines the structure and behavior of the GDSS environment layer in terms of (1) objects and messages used to communicate among these objects and (2) a message passing protocol between the GDSS environment and the other two layers. These specifications result in an architecture that is sufficiently modular to enable addition of various GDSS software. This article also discusses a prototype implementation of the architecture that is developed in Smalltalk and runs under Microsoft's Windows 3.0.     

A Proposal of Toolkit for GDSS Facilitators

Most group decision meetings are perceived to be extremely unproductive in terms of efficiently utilizing the participants’ time and effectively achieving the group decision meeting objectives. Indeed, group decision meetings consume a great deal of time and effort in organizations. These problems occur frequently because effective guidelines or procedures are not used. To overcome these problems, many group decision support systems (GDSS) imbed some facilitation mechanisms and are currently being used with the help of a human facilitator who guides the group members through the decision process. We propose in this paper a toolkit for GDSS facilitators that we integrate in our proposed architecture for distributed GDSS. Based on a model of the decision making processes group facilitation tasks are automated, at least partially in order to increase the ability of inexperienced facilitator to monitor and control the group decision meeting process.     

Applying Multiattribute-Based Group Decision Making Techniques in Complex Equipment Selection Tasks

A practicing industrial engineer, even an experienced decision maker, needs help in the sense that there is a necessity to use more logical or analytical decision support tools, especially when dealing with control and instrumentation projects which are often worth millions of dollars. In this article we propose an algorithm which can support the process of group decision making relating to industrial automation, especially involving the selection of control and instrumentation equipment. The aim of this article is to look only at the algorithm's application and how it is applied. To this end, two test cases are used as examples: (1) selecting a local area network for installation in an academic environment; and (2) selecting an integrated control system for a real-world pulp and paper mill. Obtained results show that the algorithm leads to a satisfactory solution. A software form of the algorithm is being programmed for use as a decision support tool.     

Developing a Group Decision Support System for Advertising Media Evaluation: A Case in the Middle East

The importance of advertising media evaluation as a multifaceted problem is well known by both academics and practitioners. Although previous studies tried to optimize media evaluation, there still are some gaps and problems to address, particularly in areas of flexibility of models/frameworks, decision making quality, tension management, and agility of the evaluation process. Most of previous studies are based on inflexible models/frameworks that have limitations on number of criteria/alternatives they can consider and type of data they can process. A great volume of the work used arbitrary decision making; arbitrary decision making regarding criteria and media importance may reduce effectiveness of advertising campaigns. Furthermore, the academic literature offers little guidance on group decision aggregation, and tension management during decision making is neglected. Media evaluation is a time taking process and any acceleration will reduce pre-campaign costs. The main aim of this paper is to illustrate how a group decision support system (GDSS) can assist media planners to overcome mentioned problems more systematically. For this purpose, we developed a GDSS that is an integration of three well-known multi-criteria decision making techniques. With a real world case study, we illustrate the performance of the proposed GDSS. Results of our quantitative assessments indicate that the GDSS is flexible, allows decision makers to express their opinions, reduces tension among decision makers, and saves time.     

Contrasting Single User and Networked Group Decision Support Systems for Strategy Making

The use of computers to support group work – as a Group Decision Support System (GDSS) – on strategy making has grown over the last decade. Some GDSS's have a facilitator managing the computer with the group viewing a public screen displaying the debate, problem definition, and agreements of the group as it negotiates strategies. Others involve members of the group in the direct input of data that forms part of the problem definition – data that is then used by the group employing electronic voting and other organizing devices. This paper discusses a real case relating to an organization seeking to reach important agreements about its strategy. The case involved the top management team and over 50 senior managers. The organization used a facilitator driven GDSS for some of this work, and a networked system for other parts. Some of the meetings were video taped, some were observed through one-way mirrors, and all of the participants were interviewed about their reactions to the different systems. This paper reports on some of the significant contrasts between the two approaches.     

Multiple Criteria Decision Making Models in Group Decision Support

Use of multiple criteria decision making (MCDM) models to aid the group decision process was tested. Two multiple criteria group decision support systems (MCGDSS) were studied, one using the AHP/Tchebycheff method of Iz and the other using Kersten's NEGO system. These systems were compared with a commercial GDSS, VisionQuest. VisionQuest does not include multiple criteria tools. To make the study comparable, VisionQuest was augmented with an ad hoc linear programming model that could generate solutions with specified characteristics requested by the using group. The three systems were compared on the dimensions of solution quality and decision support effectiveness.One of the hypotheses was that MCDM models would force participants to examine criteria, preferences, and aspirations more thoroughly, thus leading to decisions of better quality. Subjects using the MCGDSSs were expected to have higher mean quality and effectiveness values. However, the quality and effectiveness values of the VisionQuest/ad hoc system were found to be better on the dimension of effectiveness. Explanations for this result are included in the paper.Another hypothesis was that the AHP/Tchebycheff method of Iz, a value-oriented system, would yield more effective group support than the goal-oriented NEGO system. However, the NEGO system was found to yield solutions with better quality measures than the solutions obtained with the AHP/Tchebycheff system.Observation of the groups using the MCDM systems indicate that both the AHP/Tchebycheff and NEGO methods can be revised to enhance their effectiveness. The primary difficulty encountered with the AHP/Tchebycheff method was in the large number of pairwise comparisons required by AHP. The NEGO method can be enhanced by including specification of desired attainment levels in the first stage of the method. Both MCDM techniques have potential to benefit group decision support by giving using groups a means to design better solutions.     

Distributed group support systems: Social dynamics and design dilemmas

A “distributed group support system”; includes decision support tools and structures embedded within a computer‐mediated communication system rather than installed in a “decision room.”; It should support groups who are distributed in space but not time ("synchronous”; groups), as well as “asynchronous”; groups whose members participate at different times. Pilot studies conducted in preparation for a series of controlled experiments are reviewed in order to identify some of the problems of implementing such a system. Many of the means used by groups meeting in the same place at the same time to coordinate their activities are missing. Embedding decision support tools within a different communications medium and environment changes the way they “work.”; Speculations are presented about software tools and structuring or facilitation procedures that might replace the “missing”; coordination channels.     

The Effects of Integrating Cognitive Feedback and Multi-attribute Utility-Based Multicriteria Decision-Making Methods in GDSS

Cognitive conflicts arise within groups because the members of a group view a problem from different perspectives, even when they have similar interests in achieving a goal. Disagreement within a group may occur due to: (a) differing judgment policies among the members, (b) inconsistency by any member in using a judgment policy, (c) group process losses that prevent group members from understanding each other better, or (d) limited processing capability which may prevent group members from processing all information effectively. Disagreement is especially likely when policies, processes, or information are conflicting in nature.A level 2 GDSS to aid judging in cognitive conflict tasks is presented that combines cognitive feedback and Multi-attribute utility (MAU) theory based multicriteria decision-making techniques with the communication structure and activity-structuring capabilities of a level 1 GDSS. Though cognitive feedback and MAU methods have been used separately to help groups resolve cognitive conflicts, never before have the two decision aids been used together in a computer-based collaborative system.The contributory effects of the components of this GDSS design were empirically tested in a laboratory setting. Three treatments: an unaided face-to-face meeting, a level 1 GDSS supported meeting, and a level 2 GDSS supported meeting were compared in a repeated measures experimental design.Results largely supported the proposed research hypotheses. Some specific findings include: (1) the level 2 GDSS reduced disagreement between group members and improved consistency of judgments better than the other meeting environments did; (2) there was no significant difference in the reduction of disagreement between the level 1 GDSS and face-to-face meetings; and (3) while there was no difference in improvement of consistency of individual judgments between the face-to-face and level 1 GDSS supported meetings, group judgments made in face-to-face meetings were more consistent.     

New Approaches to Business Process Redesign: A Case Study of Collaborative Group Technology and Service Mapping

Whether it is called reengineering, quality function deployment, quality circles, continuous improvement or total quality management, business process redesign (BPR) is occurring in many organizations. In the broadest sense, BPR includes nearly any kind of systematic effort by companies to realign their business processes so that they are more competitive. Successful business process redesign can lead to dramatic improvements in productivity and quality. But BPR typically requires vast amounts of time and money to implement, since extensive employee input is necessary during the redesign process. Group Decision Support Software (GDSS) provides a viable alternative to the traditional BPR approach. GDSS is defined as computer-based information systems used to support intelligent, collaborative work.This technology allows multiple users to meet and discuss topics simultaneously via a computer network, thus increasing employee commitment while decreasing time and cost.This paper describes a business process redesign project that was conducted for a division within a large government agency fall of 1993. The BPR was done using a type of Group Decision Support Software called Group Systems V. A services marketing tool called service mapping was also used to identify customer needs and interfaces. Data were collected throughout the project to measure employee attitudes about the redesign process and the GroupSystems technology. Time to complete tasks was also recorded. The results of the study showed that the business process redesign was accomplished more effectively in a shorter period of time than with traditional BPR methods previously used. Participants also indicated that the service mapping tool provided a perspective that is missing from many BPR approaches: an understanding of the service from the customer's perspective.     

GDSS research: An overview and historical analysis

Group Decision Support Systems (GDSS) is a relatively new area of Information Systems research, but some patterns have begun to emerge in the focus of this research and in the approaches to conducting it. This article represents a substantial review of a large body of GDSS literature and an analysis of that literature according to a specific classification scheme. The dimensions of the classification scheme include the age of the research publication, the general research approach, the philosophy underlying the data collection, the type of GDSS support, whether the research is longitudinal, and the primary focus of the research, as well as a few demographic variables such as author and source. The results of the literature analysis lead to recommendations to GDSS researchers by the authors of a need for greater use of the available research approaches and other data analysis philosophies, a greater emphasis on field work, more longitudinal research, and some changes in the focus of the research.     

供应链柔性决策机制的建立

在对供应链的决策机制的研究过程中,大部分都是源于传统的决策理论方法。在传统的决策理论研究领域一般分为两个阵营,一个是基于理性决策研究,另一个是基于行为规则的决策理论研究。对于前者大部研究者在假设决策者是理性的前提下给予了研究,在这个领域里往往会运用博弈论的知识对决策行为给予剖析。但是由于市场环境的复杂多变,使得理性决策有时在一定的条件下存在着极大的局限性。尤其是特定的供应链网络系统内,在面对多个决策主体在空间与时间上的非同步性时,如何对决策者之间的关系进行协调以及时地应对外界环境的变化,从而使供应链整体效益最优,是研究的主要目的。基于规则决策的观点,用群决策支持系统原理(GDSS)为供应链网络设立一种更为柔性化的决策机制。     

A Formal Basis for Negotiation Support System Research

A high-level theoretical model of negotiation activity is introduced as a foundation for guiding future research and development in the area of negotiation support literature. A formal model at this level is presently absent from the negotiation support systems. The model is formally expressed in terms of definitions and postulates that describe eight important negotiation parameters. Relationships between the model and research in game theory, social behavior science, and decision support systems fields are examined.