Challenging Group Support Systems Research: The Case for Strategic Decision Making

Strategic decision making (SDM) often occurs in groups that can benefit from the use of group support systems (GSS). However, no comprehensive review of this logical intersection has been made. We explore this intersection by viewing GSS research through the lens of SDM. First, SDM is broadly characterized and a model of GSS-mediated SDM is produced. Second, we review empirical GSS research linking these findings to the characteristics of SDM. We conclude that GSS research has not produced sufficient knowledge about group history, heterogeneity, member experience, task type, time pressure, technology or tool effects, and decision consensus for a favorable evaluation of SDM in GSS groups. SDM in GSS groups challenges researchers to study the effects of group processes such as those just mentioned in a context that involves ongoing and established groups, political activity, and a multiplicity of tasks.     

Critical Situations for Decision Making: A Support Based on a Modelling Tool

This paper proposes to give a toll to help decision makers in critical situations. The principle of our research is based on a modelling approach for Cooperative Knowledge Based Systems. This approach is based on a Task/Method paradigm that we describe. We then propose to take into account collateral effects of tasks in order to support decision makers in a critical context. The proposed tool can then generate a degraded solution for which, collateral effects of previous tasks have been taken as new goals to reach. This study is possible thanks to the definition of several kinds of models: a Good Functioning Model and a Degraded Tasks Library.     

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.     

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.     

Coordination Structures and System Restrictiveness in Distributed Group Support Systems

Most GSS research has studied the impact of restricting group interaction to GSS-prescribed coordination structures with face-to-face groups, while Distributed GSS (DGSS) has been largely ignored. Due to the nature of mediated communication in asynchronous interaction, it is relatively difficult to coordinate distributed groups, and a special coordination structure must be arranged to overcome these difficulties. This study examines the effect of system restrictiveness of coordination structures in an asynchronous environment. A 2 × 2 factorial experiment was designed with two independent variables – sequential vs. parallel coordination mode, and with vs. without a leader – to construct coordination structures with varying degrees of restrictiveness. The study finds that less restrictive coordination structures are more appropriate to support asynchronously interacting distributed groups. Objective decision quality is equal for both parallel and sequential coordination mode, but is significantly better with a group leader. Groups with parallel coordination mode have a stronger belief that the decisions they made are of higher quality than those of groups with sequential coordination mode. In groups with a leader, communication effectiveness is better. Satisfaction with a decision process is higher in parallel coordination groups and in groups with a leader. There is also a significant interaction effect. Satisfaction with the decision process is higher in sequential coordination groups with a leader than sequential coordination groups without a leader.     

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.     

A framework for thinking about Group Decision Support Systems (GDSS)

Strategic problem solving in organizations is a social process that disturbs established social relationships. Maintaining a negotiated social order is crucial to political feasibility and to emotional commitment from the participants in relation to a solution package. However, Group Decision Support Systems that attend overly to managing social order risk group think through bounded vision. This may be avoided if emotional commitment is also encouraged through participants experiencing the problem situation from multiple perspectives and in relation to alternative solution strategies. Commitment depends upon both means/ends rationality and procedural rationality. This acknowledges the balance in providing support to a group with respect to the negotiation of social order, with the more traditional group decision support for socially negotiating order out of the problem situation. This article argues that effective Group Decision Support Systems must attend to both aspects of creating order. OR modelling methods and the support that can be provided by modern micro-computers offer a new way forward—models can be toys that a group can play with together, enabling them to create knowledge as well as use it.     

Ethical Decision Making: A Comparison of Computer- Supported and Face-to-face Group

This study compares computer-supported groups, i.e., groups using group support systems (GSS), and face-to-face groups using ethical decision-making tasks. A laboratory experiment was conducted using five-person groups of information systems professionals. Face-to-face (FTF) and GSS groups were compared in terms of their decision outcomes and group members' reactions. The results revealed that computer-supported and face-to-face groups showed no significant difference in terms of the decision outcomes of choice shift and decision polarity. However, FTF groups reached their decisions more quickly and they were more successful in attaining group consensus than GSS groups. Subjects evaluated face-to-face communication more favorably than GSS interaction on most post-group measures related to perceived group processes and satisfaction. Despite these outcomes, some possibilities for using GSS technology in an ethical decision making context are examined.     

An Intelligent Distributed System for Strategic Decision Making

The decision-making process in strategic planning is often too complex to be handled by conventional methods. Strategic planning problems (building new plans, new product planning, etc.) belong to the class of problems called ill-structured by H. Simon. They involve a decomposition of the main problem into a set of subproblems, a reasoning process at the subproblem level, and then a coordinated and aggregated process to build a global solution. Because partial solutions are generated without having a complete view of the global objective, this type of decision-making process very often generates incoherent and contradictory hypotheses and actions. Therefore, the main problem is to find a way to achieve coherence and coordination among decisions made locally by different agents, at different levels.Recent advances in Artificial Intelligence, particularly in the field of multi-agent theory, offer great promises in modeling strategic planning processes. In this article we present a general framework called 'A Coherent Plan of Coordinated Actions (CPCA)' for building intelligent distributed strategic decision making systems which integrates advances in both distributed decision making and Distributed Artificial Intelligence. We then describe a multi-blackboard system, ARISTOTE, which is aimed at helping corporate managers address the feasibility and coherence of a plan of actions.     

基于Web的环境决策支持系统

本文基于浏览器/服务器模式开发了基于Web的环境决策支持系统(WEDSS),该系统由前台客户端、中间层及后台数据库等三层构成,其所有操作逻辑和事务逻辑由各层服务器完成。客户端只完成展示逻辑的功能,可大大提高系统的安全性、稳定性、可维护性和可扩展性,降低网络负载,提高与用户的交互能力,客户终端只要安装Web浏览器就能同时使用和参与环境系统的分析。该系统为城市规划者和政府管理人员更好地进行环境决策,解决当今人类居住、商务及工业发展三者之间的需求关系提供了一个有效途径,但由于环境问题和潜在解决方案流程在WEDSS系统中量化表述的难度,环境决策支持系统在推广方面还存在一定困难。     

农产品物流安全应急决策支持系统研究

针对农产品物流安全的特点,围绕运输车辆、农产品腐烂等突发事故,集成Internet GIS、无线数据传输、无线通讯等信息化技术,构建了分布式应急决策支持系统（DDSS）。最后基于GPS／GIS／GSM（3G）技术,以车辆调度为例阐述了典型功能区的远程数据采集与决策管理实现。     

Decision Support Systems in Marketing

The practical application of decision support systems in marketing is still in its infancy, even though academic research has been recommending the use of such systems for years. This is largely due to the lack of a single, generally applicable decision support system. The specific requirements and problems of management are too dissimilar to make the development of one universal decision support system feasible. However, improved PC performance, enhanced market survey methods such as conjoint measurement, and further developed programming tools permit the varying requirements to be fairly flexibly met. The following article describes state-of-the-art know-how regarding the practical utilization of such systems, and addresses the preconditions for employing them. We have included many examples gathered from our own experience with numerous applications.     

Towards a Design Science of Ethical Decision Support

Ethical decision making involves complex emotional, cognitive, social, and philosophical challenges. Even if someone wants to be ethical, he or she may not have clearly articulated what that means, or know how to go about making a decision consistent with his or her values. Information technology may be able to help. A decision support system could offer individuals and groups some guidance, assisting them in making a decision that reflects their underlying values. The first step towards a design science of ethical decision support is to develop a theoretical base on which first-generation systems can be built. This paper brings together work in cognitive, social and moral psychology, information systems, and philosophy relevant to ethical decision making. Attributes of a system that would support ethical decision making are described.     

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.     

Combining GDSS and Gaming for Decision Support

Both gaming and group (decision) support systems (GDSS) are frequently used to support decision-making and policymaking in multi-actor settings. Despite the fact that there are a number of ways in which gaming and GDSS can be used in a complementary manner, there are only sporadic examples of their combined use. No systematic overview or framework exists in which GDSS are related to the functions of gaming or vice versa. In this article, we examine, why, how and for what purpose GDSS can be used to enrich and improve gaming simulation for decision support, and vice versa. In addition to a review of examples found in the literature, four games are discussed where we combined gaming and GDSS for complex decision making in a multi actor context: incodelta, a game about transportation corridors; infrastratego, a game about a liberalizing electricity market; containers a drift, a game about the planning of a container terminal, and; dubes, a game about sustainable urban renewal. Based on the literature and these four experiences, a classification is presented of (at least) four ways in which GDSS and gaming can be used in a complementary or even mutually corrective, manner: the use of GDSS for game design, for game evaluation, for game operation and the use of gaming for research, testing and training of GDSS.     

Monte Carlo Simulation Techniques in a Decision Support System for Group Decision Making

This paper describes a group decision support system based on an additive multi-attribute utility model for identifying a consensus strategy in group decision-making problems where several decision-makers or groups of decision-makers elicit their own preferences separately. On the one hand, the system provides procedures to quantify the DMs or group of DMs preferences separately. This involves assessing the DMs or group of DMs component utilities that represent their preferences regarding the respective possible attribute values and objective weights that represent the relative importance of the criteria. On the other hand, we propose Monte Carlo simulation techniques for identifying a consensus strategy. An iterative process will be carried out, where, after the simulations have been performed, the imprecise component utilities and weights corresponding to the different DMs or groups of DMs are tightened to output more meaningful information in the next simulations to achieve a consensus strategy. Finally, an application to the evaluation of remedial strategies for restoring contaminated aquatic ecosystems illustrates the usefulness and flexibility of this decision support tool.     

A conceptual framework of anonymity in Group Support Systems

As the development and use of automated systems for collaborative work grows, the need for a better understanding of these systems becomes more important. Our focus is on one type of system, a Group Support System (GSS) and, in particular, on one important aspect of a GSS—anonymity. A conceptual framework for the study of anonymity in a GSS is presented, which describes the general classes of variables and their relationships. These variables include the factors that influence anonymity in a GSS, types of anonymity, and the effects of anonymity on a message sender, receiver, group process, and outcome. Each of these variables is discussed with working propositions presented for important group process and outcome measures. The objectives of this article are to highlight the importance and complexity of anonymity, to act as a guide for empirical investigations of anonymity, and to influence future GSS development and use.     

Reinforcing Ethical Decision Making Through Organizational Structure

In this paper I examine how the constituent elements of a firm's organizational structure affect the ethical behavior of workers. The formal features of organizations I examine are the compensation practices, performance and evaluation systems, and decision-making assignments. I argue that the formal organizational structure, which is distinguished from corporate culture, is necessary, though not sufficient, in solving ethical problems within firms. At best the formal structure should not undermine the ethical actions of workers. When combined with a strong culture, however, the organizational structure may be sufficient in promoting ethical conduct. While helpful, ethics training and corporate codes are neither necessary nor sufficient in promoting ethical behavior within firms.     

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.     

基于分布式数据挖掘的连锁商业企业经营决策分析

分布式经营系统是大型连锁商业企业发展的基础,采用分布式数据挖掘辅助连锁商业企业决策是一种理想选择。连锁商业企业经营决策可以通过基于分布式数据挖掘的全局控制站点决策模式和分站点决策模式,各站点的独立和全局的综合来实行;基于分布式数据挖掘的决策机制与集中式数据挖掘的决策机制相比有划分粒度小、分析与综合性强、面向顾客的灵活度高等特点;并实现了一个客户细分的决策过程。