Group Support Systems: The Effects of Mixing Support Systems on Information Pooling, Decision Time, and Decision Quality

Most group support systems (GSS) laboratory studies compare face-to-face groups with groups assigned to either a synchronous or asynchronous decision support system. Research findings have been inconclusive. A laboratory study that compared face-to-face groups with mixed support mode groups was conducted to determine the effectiveness of selectively using information technology to support the group process and explain some of the variability in research findings. Groups that shared information using a Web-based asynchronous system and discussed the shared information in a face-to-face meeting environment, assembled more information and made higher quality decisions in less time than groups that shared and discussed information in a face-to-face meeting environment

The Minnesota GDSS Research Project: Group Support Systems, Group Processes, and Outcomes

The Minnesota GDSS Research Project is a 20-year program of interdisciplinary research that has generated more than 80 articles, chapters, dissertations, and proceedings publications and has influenced other researchers who developed their own niches. Grounded in Adaptive Structuration Theory, which emerged and evolved as the research unfolded, the project studied the impact of technology characteristics (level of support, restrictiveness) and other support (training, heuristics, facilitation) on group processes and outcomes for a range of tasks (problem definition, decision making, planning). The project entailed a complex tapestry of a series of laboratory experiments and two major field studies. The basic theoretical framework, experimental strategy and design, field study design, and results are summarized, along with a discussion of the significance and implications of the project for contemporary theory and practice

A multidimensional framework for group decision support system research and design

Groups are a fundamental and essential part of organizational decision making. A group decision support system (GDSS) attempts to use computer and communications technology to help a group make better decisions. In this paper, previous GDSS research is extended to develop a better framework for future GDSS research and design. Six situational factors are identified; group size, member proximity, task type, group environment, and group development stage; so that a given group decision making situation can be accurately described. To standardize the features across different GDSS, six different levels of GDSS features are also identified. The paper then presents a multidimensional framework for conducting future GDSS research, and argues that future GDSS research needs to identify the appropriate GDSS features for the appropriate group decision situation. It is also suggested that researchers take a long-term, holistic approach while analyzing the results of using a GDSS

Social influence effects on remote group interactions

This paper discusses the results of an experiment exploring the effects of information technology intervention on decision making groups. Specifically, the study examines the effects communication modality {remote vs. face-to-face) and information load on the types of social influence used by group members and the amount of group polarization or choice shift exhibited by group members. The findings suggest that face-to-face groups use more informational influence than remote groups and that this difference increases as information load increases. Also, face-to-face groups experienced greater choice shift than remote groups at high information loads

Discrimination of Structure and Technology in a Group Support System: The Role of Process Complexity

It is not clear whether improvements found with group technology are due to the structure embedded in the technology or the added benefit of the technology in managing information complexity. Process complexity is proposed as the explanatory factor in previous coafiicting results. Task complexity is clarified and a Process Complexity Model is proposed and tested. The principal factors manipulated are task complexity (complex and less complex) and technology (present or absent). Ill-structured policy tasks are employed and, in addition to other outcome variables measured, task outcome quality is quantified by comparing the reported results of policy experts ir, these \u27asks. Since small group size (three to four) may be the reason that previous experiments have not shown significant differences, group size is controlled using larger groups of seven or more members

E-mail and Direct Participation in Decision Making: A Literature Review

This paper reviews the literature on the effects of the use of e-mail on direct participation in decision making (PDM) in organisations. After a brief review of the organisational literature on participation the paper distinguishes e-mail theories on direct participation in three different theoretical perspectives. Then the paper focuses the attention on the role of e-mail in affecting task type, vertical and horizontal communication and their consequences for PDM. Finally the paper presents indications and open questions for future research.email, e-mail, decision making, participation in decision making, literature review,

Model financijske mogućnosti nositelja osiguranja u kontekstu upravljanja rizikom osiguravajuće kuće

This paper analyses the manner of evaluation of insurance holder affordability conducted by an insurance company. A well done financial analysis and appropriate methodology applied enable our greater efficiency when making strategic decisions by selecting business partners, production programs, placing funds into investment programs with an aim of preserving and increasing company value, protecting interest of shareholders, insureds and other insurance creditors. Adequate macroeconomic methods are applied against a corresponding software application, the analysis and synthesis of which lead to conclusions verifying the set hypothesis that there is at least one model satisfying the required and sufficient condition to reduce the level of risk of an insurance company by determining the financial standing of an insured. On a sample of data corresponding results are obtained and commented on in the conclusion of this paper.U radu se analizira način ocjene financijske sposobnosti osiguranika od strane osiguravajuće kompanije. Kvalitetno urađena financijska analiza i pravilno odabrana metodologija omogućavaju nam veću učinkovitost pri donošenju strateških odluka, odabiranjem poslovnih partnera, proizvodnih programa, plasiranjem finansijskih sredstava u investicione programe u cilju očuvanja i uvećanja vrijednosti kompanije, zaštiti interesa akcionara, osiguranika i drudih poverilaca osiguranja. Primijenjene se adekvatne makroekonomske metode uz odgovarajuću softversku aplikaciju, čijom se analizom i sintezom došlo do zaključaka kojima je verifikovana postavljena hipoteza da postoji makar jedan model koji zadovoljava potreban i dovoljan uslov da se snizi razina rizika osigravajuće kompanije utvrđivanjem finansijske sposobnosti osiguranika. Na jednom uzorku podataka dobijeni su odgovarajući rezultati koji se komentarišu u zaključku ovog rad

Artificial Intelligence, Decision Making, and the Knowledge Creation Process

The continued evolution of artificial intelligence (AI) presents new opportunities for businesses to improve performance through better decision making. Prior literature has emphasized the relationship between AI and decision making as structures contributing to improved decision quality. This paper proposes that knowledge is a critical construct in the decision-making process and that it is the combined interactions of AI, decision making, and knowledge management within decision support systems and processes that contribute to improved decision quality. This paper outlines research trends that have occurred over the years and where the conversations regarding AI, decision making, and knowledge converge. Proposed in this paper is a research framework to classify AI capabilities in the knowledge creation process to further our understanding of these critical linkages

A REVIEW AND CRITIQUE OF DSS

Information Systems Working Papers Serie