A Review On Evaluation And Benefits Of Decision Support Systems <s> Communications-driven DSS <s> I. Introduction to Decision Support Systems. Chapter 1. Introduction. Chapter 2. Decision Making. II. DSS Components. Chapter 3. The Data Component. Chapter 4. The Model Component. Chapter 4S. Intelligence and Decision Support Systems. Chapter 5. The User Interface. III. Issues of Design. Chapter 6. International Decision Support Systems. Chapter 7. Designing a Decision Support System. Chapter 8. Object Oriented Technologies and Decision Support Systems Design. Chapter 9. Implementation Strategy. IV. Extension of Decision Support Systems. Chapter 10. Executive Systems and Dashboards. Chapter 11. Group Decision Support Systems. <s> BIB001 </s> A Review On Evaluation And Benefits Of Decision Support Systems <s> Communications-driven DSS <s> 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. <s> BIB002
Communications-driven DSS are systems where the driving technology is a facilitation of interpersonal communications. Systems in this category are sometimes called Group Decision Support Systems (GDSS), Group Support Systems (GSS), or Groupware. These systems can benefit group decision-making by inhibiting negative group behaviors while promoting the positive aspects. Since negative aspects are more pronounced the larger the group, these systems provided the most benefit to large groups. Groupware (messaging, conferencing, group document handling, work flow, utilities/development tools, frameworks, services, and vertical market applications) facilitates movement of documents and messages to enhance the quality of communication among group members. Adding the DSS components (database management, model, and user interface) and, often a facilitator, the GDSS is able to provide process support in addition to decision-making support. Group memory aspects of the system allow retrospective analysis and interpretation of the process by group members. Other benefits afforded by GDSS include greater flexibility in the definition of meetings and anonymity of participation by group members as needed BIB001 . A classic and widely-cited DSS in this category is described in  . In the context of a field study, the authors collect data about the process related to outcome effectiveness (quality of outcome and quality of session process), efficiency (costs and benefits relative to performing the same function manually), and user satisfaction (utilization rates and self-reported levels of satisfaction). With respect to effectiveness, they find that participation is more evenly distributed than would normally occur in a manual setting. Interviews with managers indicate they believe that the system provides outcome effectiveness as well. Regarding efficiency, man-hours are significantly reduced relative to manual settings. User satisfaction is strongly supported by utilization rates of the system, and this is confirmed by participants' self-reported levels of satisfaction. More recently, Miller (2008) studies how the presence or absence of a facilitator affects the benefits of a GSS. Examining process facilitation from an Adaptive Structuration Theory perspective, the author compares highand low-levels of facilitator restrictiveness. The data indicate significantly different amounts and types of appropriation moves between the two levels of facilitator control. Additionally, the author examines the impact individual facilitators might have on the process. He finds substantial differences in both the quantity and the type of appropriation moves, and the proportion of moves involving the facilitator differ across facilitators as well. Barkhi & Kao (2010) use data envelopment analysis (DEA) to propose an economic efficiency measure for GDSS performance evaluation. The measure considers both decision inputs and outputs simultaneously, making it potentially more useful than traditional single-factor measures. Implementing a 2 by 2 by 2 factorial design through variation of three context variables (communication mode, group leadership mode, and incentive structure) in an experimental setting, the authors demonstrate that DEA can measure each GDSS user's performance and then determine how different contextual variables affect decision efficiency. Their results suggest that incentive structure and communication mode have a significant impact on DEA decision efficiency in the GDSS setting. They discuss possible extensions of their work including analyzing performance at the group level using redefined group inputs and outputs, and incorporating DEA methodology into development of next-generation GDSS. Barkhi & Kao (2011) extend their earlier work to examine the impact of psychological climate on GDSS users' decision-making performance. Their work specifically analyzes psychological safety, the freedom GDSS users believe they have to express themselves without negative impact, and psychological meaningfulness, which is the reciprocity felt by GDSS users in terms of returns from their input to the decision-making team. In lab settings where communication mode, incentive structure, and leadership mode were varied, they find that psychological safety does positively influence both GDSS users' task performance and work attitude. However, with respect to psychological meaningfulness, they find that it enhanced GDSS users' satisfaction with their participation but it is not significantly related to overall decision process efficiency. Facilitating GDSS users in a distributed computing framework differs from the facilitation process in faceto-face settings. Computer-mediated communication must be used, which often results in a lower level of bonding among group participants. This lower bonding may subsequently cause participants to have lower interest and energy levels during meetings. BIB002 propose a set of tools that can be incorporated in the decisionmaking process to provide embedded facilitation to complement the facilitator's intervention effort. Dialogue Manager, Group Memory, Session Planning, and Group Toolkit modules comprise the distributed GDSS architecture. The Group Toolkit module consists of four categories: idea generation, idea organization, idea evaluation tools, and solution choice. The authors examine a three-phase group facilitation process (pre-meeting, during meeting, and post-meeting) in a case study at a plant that specializes in liquefying gas, providing a detailed discussion of the process activities as they can be enabled by the proposed GDSS toolkit.