THE IMPACT OF COMPUTER-BASED SUPPORT ON THE PROCESS AND OUTCOMES OF GROUP DECISION MAKING

Interactive computer-based systems to support group decision making (group decision support systems or GDSS) have received increased attention from researchers and practitioners in recent years. Huber (1984) argues that as organizational environments become more turbulent and complex, decisions will be required to be made in less time and with greater information exchange within decision making groups. Thus, it is imperative that studies be undertaken to determine the types and characteristics of group decision tasks most appropriate for support by a GDSS and to determine the features of a GDSS that will support those tasks. A number of prominent researchers in the field of group decision making (Shaw, 1973, 1981; Hackman and Morris, 1975; Fisher, 1974) agree that the decision task itself is probably the most important factor in determining group decision making effectiveness. The characteristics of group decision tasks are many and varied, but according to Shaw (1973) the level of difficulty/complexity of the decision is a fundamental factor in influencing the performance of the group. Some decisions are characterized by information that is clear, concise, easily communicable, and where relationships between important factors in the decision are easily understood. In short, these decisions require relatively little effort to make and are therefore called easy decisions. Decision tasks where the information to be considered in making the decision is incomplete, difficult to understand, and where complex relationships exist within the information available are called complex or difficult decisions. The role of decision task difficulty in the effective use of GDSS is considered ih this study. This research is an initial experimental study, exploratory in nature, that aims to get a first-level understanding of the impact of a computer-based DSS on group decision making. The group decision support system that is used in this study has only those features that specifically support group decision making (alternatives generation and communication, preference ranking and voting support). The reason for this approach is to start a program of research with a simple system in order to determine the particular impact of these features on, not only the outcomes of group decision making (such as decision quality), but on the process of group decision making as well. A controlled 2 x 2 factorial experiment was used to compare the decisions made by groups which had GDSS support with those groups that had no GDSS support and those with a high difficulty task to those with a low difficulty task. Figure 1 shows the relationship among the main variables in the study. The experimental task was a marketing business case in which the company was experiencing declining profits. Each group was asked to find the problem which was causing the declining profits. Difficulty was manipulated by modifying the data in the case. The setting for this experiment was a decision room designed and set up to accommodate face-to-face group interaction. The GDSS treatment entailed the use of one computer terminal per group member so that the GDSS could be used to support group decision making. Each group member in the GDSS treatment also had the use of a pencil, paper, a hand calculator, and a blackboard. For the non GDSS treatment, the terminals were removed and the group used just pencils, paper, hand calculators, and a blackboard to assist in making the decision. The computer hardware consisted of a DEC VAX 11/780 timesharing system using the VMS operating system, and DEC VT-102 terminals. The terminals were connected to the VAX 11/780 using 2400 baud direct lines. The GDSS called Decision Aid for Groups (DECAID) was designed, coded, and tested to make sure that it worked in the experimental setting. The approach to design was to implement the features, and then to refine the system through testing to make those features work as efficiently as possible. The GDSS software performed the basic functions of recording and storing and displaying alternatives that were entered by group members, aggregating and displaying preference rankings that had been entered for those alternatives, and recording votes (either publicly or anonymously) for the various alternatives generated. The system was easy to use and menu driven. Eighty four senior undergraduate business administration students participated in the study. These subjects had taken at least one course each in management science/decision analysis techniques, marketing, management theory/organizational behavior, and all had exposure to case analysis techniques. All subjects had been given training in the use of the GDSS. Measures were taken of decision outcomes (decision quality, decision time, decision confidence, satisfaction with group process, and amount of GDSS usage), and decision process variables (number of issues considered, number of alternatives generated, and participation in the decision making). Decision quality was measured along two dimensions: (1) decision content - how close did the group\u27s decision come to that made by a panel of experts; and (2) decision reasoning -- how similar the group\u27s reasoning in arriving at their decision was to the reasoning of the experts. Decision time was defined as the length of time it took the group to reach a consensus decision. Decision confidence and satisfaction with the group process were measured by individual responses to a post- test questionnaire. The individual responses were then aggregated to give a group value. The amount of GDSS usage was measured by examining the computer logs that were kept during the GDSS sessions. Decision issues were defined as factors that were important in the analysis of the case. Decision alternatives were defined as those issues in the case that the group analyzed as being the possible major problems in the case and hence, possible solutions to the decision task. Participation was measured by counting the number of task related comments made by each individual group member. Issues, alternatives and participation were determined by analysis of the video and audio tapes that were made of the experimental sessions. The major findings of the study are: 1. Decision quality is enhanced when decision making is supported by a GDSS, particularly for high dificulty tasks. 2. Decision time is not affected by use of a GDSS. 3. Confidence in the group decision and satisfaction with the decision making process are reduced when a GDSS is used, irrespective of task difficulty. 4. The number of alternatives considered is increased when a GDSS is used to support group decision making. 5. Participation in the group decision making process is unaffected by GDSS support or by decision task difficulty. The paper concludes by suggesting directions for future research into GDSS. Work is needed to determine the effectiveness of additional features of a GDSS (such as other communication features, modeling features, etc.), to understand the impact of GDSS on the different phases of decision making, and to examine the effect of repeated use of a GDSS on the quality of group decision making

Development of a decision support system through modelling of critical infrastructure interdependencies : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand

Critical Infrastructure (CI) networks provide functional services to support the wellbeing of a community. Although it is possible to obtain detailed information about individual CI and their components, the interdependencies between different CI networks are often implicit, hidden or not well understood by experts. In the event of a hazard, failures of one or more CI networks and their components can disrupt the functionality and consequently affect the supply of services. Understanding the extent of disruption and quantification of the resulting consequences is important to assist various stakeholders' decision-making processes to complete their tasks successfully. A comprehensive review of the literature shows that a Decision Support System (DSS) integrated with appropriate modelling and simulation techniques is a useful tool for CI network providers and relevant emergency management personnel to understand the network recovery process of a region following a hazard event. However, the majority of existing DSSs focus on risk assessment or stakeholders' involvement without addressing the overall CI interdependency modelling process. Furthermore, these DSSs are primarily developed for data visualization or CI representation but not specifically to help decision-makers by providing them with a variety of customizable decision options that are practically viable. To address these limitations, a Knowledge-centred Decision Support System (KCDSS) has been developed in this study with the following aims: 1) To develop a computer-based DSS using efficient CI network recovery modelling algorithms, 2) To create a knowledge-base of various recovery options relevant to specific CI damage scenarios so that the decision-makers can test and verify several ‘what-if’ scenarios using a variety of control variables, and 3) To bridge the gap between hazard and socio-economic modelling tools through a multidisciplinary and integrated natural hazard impact assessment. Driven by the design science research strategy, this study proposes an integrated impact assessment framework using an iterative design process as its first research outcome. This framework has been developed as a conceptual artefact using a topology network-based approach by adopting the shortest path tree method. The second research outcome, a computer-based KCDSS, provides a convenient and efficient platform for enhanced decision making through a knowledge-base consisting of real-life recovery strategies. These strategies have been identified from the respective decision-makers of the CI network providers through the Critical Decision Method (CDM), a Cognitive Task Analysis (CTA) method for requirement elicitation. The capabilities of the KCDSS are demonstrated through electricity, potable water, and road networks in the Wellington region of Aotearoa New Zealand. The network performance has been analysed independently and with interdependencies to generate outage of services spatially and temporally. The outcomes of this study provide a range of theoretical and practical contributions. Firstly, the topology network-based analysis of CI interdependencies will allow a group of users to build different models, make and test assumptions, and try out different damage scenarios for CI network components. Secondly, the step-by-step process of knowledge elicitation, knowledge representation and knowledge modelling of CI network recovery tasks will provide a guideline for improved interactions between researchers and decision-makers in this field. Thirdly, the KCDSS can be used to test the variations in outage and restoration time estimates of CI networks due to the potential uncertainty related to the damage modelling of CI network components. The outcomes of this study also have significant practical implications by utilizing the KCDSS as an interface to integrate and add additional capabilities to the hazard and socio-economic modelling tools. Finally, the variety of ‘what-if’ scenarios embedded in the KCDSS would allow the CI network providers to identify vulnerabilities in their networks and to examine various post-disaster recovery options for CI reinstatement projects

USING A GDSS TO FACILITATE GROUP CONSENSUS: SOME INTENDED AND UNIMTENDED CONSEQUENCES

RATIONALE AND PURPOSE OF THE STUDY The empirical research examining group decision support systems suggests that many of the hopes for GDSS can be realized. For example, Lewis (1982) and, more recently, Gallupe (1985) both found that groups supported by a GDSS made higher quality decisions than groups without GDSS support. Applegate (1986) and Steeb and Johnston (1981) have demonstrated the viability of GDSS in live planning situations. Positive effects of a GDSS on groups have also been reported by Gray et al. (1981), Turoff and Hiltz (1982), and Siegel et al. (1986). Computer support has been shown to foster a democratic approach to the decision process, with more equality of participation among members (Siegel et at. 1986), to improve satisfaction with the decision process (Applegate 1986), and to result in a greater shift away from initial individual preferences (Siegel et al. 1986). These intended effects of the technology have been demonstrated for a limited number of task types. To date, positive effects of GDSS have been observed for idea generation (Applegate 1986; Lewis 1982), problem finding (Gallupe 1985), intellective choice (i.e., selection of a correct answer among a given set of alternatives) (Hiltz and Turoff 1982), and planning tasks (Applegate 1986; Steeb and Johnston 1981). In two of these studies, group members were dispersed and interacted with one another via a communication network (Hiltz and Turoff 1982; Siegel et al. 1986), while in the other studies group members met in a face-to-face (i.e., conference room) setting. In all cases, each member had direct interaction with the GDSS, and in most of the studies the performance of the group was compared to an objective measure of decision quality. Of course, many organizational meetings occur without prior or post knowledge of the correct outcome of a group meeting. For this reason, the current study aimed to build on the available knowledge of GDSS impacts by examining the usefulness of the technology in situations where a group must resolve competing personal preferences and maximize agreement on a solution to a problem. In such situations, achieving high decision quality is not the primary goal of the group meeting. The theory of GDSS would argue that the technology should be as useful in achieving consensus as in identifying correct solutions. In either situation, the GDSS should foster more even participation in the decision and a more systematic, or structured, group decision process (DeSanctis and Gallupe 1987; Huber 1984a). For the most part GDSS research is being conducted in laboratory settings where the organizational context and other factors can be controlled so that the impact of the technology on group outcomes can be carefully assessed. The current study aimed to build on the available GDSS research by systematically comparing groups supported with a GDSS with groups that had either no support whatsoever ( baseline groups) or a paper-and-pencil ( manual ) support system, that contained the same decision structure as the GDSS (cf. Lewis 1982). The purpose of having two control groups was to determine whether increments or decrements in outcomes were due to the GDSS or simply due to imposing a problem-solving structure on the group. Three major hypotheses were investigated: HYPOTHESES Hl. The degree of post-meeting consensus will vary as a function of the type of support given to the group. Hla. Post-meeting consensus will be higher in the GDSS groups than in the manual support or baseline groups, controlling for initial level of conflict. Hlb. Post-meeting consensus will be higher in manual support groups than in the baseline groups, controlling for initial level of conflict. H2. The equality of influence will vary as a function of the type of support given to the group. H2a. Influence will be more even in the GDSS groups than in the manual support groups. H2b. Influence will be more even in the manual support groups than in the baseline groups. H3. Attitudes toward the group process will be different in the GDSS groups than in the manual system and baseline groups. METHOD Forty-four three-person and 38 four-person groups participated in the study. Group size in this study was similar to that in previous research (Lewis 1982; Gallupe 1985; Siegel et al. 1986). The groups were made up of undergraduate and graduate students enrolled in introductory MIS classes. Many of the students were employed full-time in business settings, and most were working at least parttime. On average, the participants were 24 years of age with slightly more than two-and-a-half years of work experience in a business or related setting. All of the groups were live groups in that they were actively working together as teams on class assignments. In this way, the initial socialization that occurs early in group formation could be avoided during the data collection. THE GDSS The GDSS, called Computer Assisted Meeting (CAM), was designed, coded, and tested by a research team at the University of Minnesota. The system is described in DeSanctis and Dickson (1987) and is being used for several related studies of group DSS (Poole and DeSanctis 1987; Watson 1987; Zigurs 1987). Basically, the system incorporates a rational problem-solving agenda (Dewey 1910). The software is similar to that used by Lewis (1982) and Gallupe (1985) in that it performs the basic functions of recording, storing, and displaying problem definitions, criteria for evaluating solutions, alternative solutions, and a final group decision. Group members can enter relative weights for solution criteria, and the system will aggregate and display average group weightings. In addition, the system will cumulate and display ratings, rankings, and votes associated with one or more alternative solutions to a problem. These features have been identified as appropriate for supporting the communication needs of groups (Huber 1984b; DeSanctis and Gallupe 1987; Joyner and Tunstall 1970). Experimental Task and Procedure The research task required subjects to allocate a given sum of money among six competing projects that have requested funds from a philanthropic foundation. Conflict arises because the team members have varying preference structures that result in different allocation patterns. The projects that subjects can fund are based upon the personality components scheme described by Spranger (1928), who asserts that there are six basic interests or motives in personality: theoretical, economic, aesthetic, social, political, and religious. The six projects that can be funded correspond to Spranger\u27s six personality traits. Correlation analysis based on the 300 experimental subjects was used to check that the amount allocated to a project by an individual was highly correlated with that person\u27s values as measured by the Study of Values instrument (Allport et al. 1970). The strengths of the task are twofold. First, it produces conflict in a group. Second, the source of the conflict is identifiable; it is based upon different preference structures arising from varying personality traits. The task and its validation are further described in Watson (1987). The experimental procedure was as follows: 1. Subjects listened to a standard introductory script read by the administrator of the experiment, and then read a background statement. 2. Subjects completed a consent form, a background questionnaire, and the Study of Values instrument. 3. Subjects individually allocated funds to the six projects requesting support from the philanthropic trust (these measures were used to calculate pre-meeting consensus). Subjects also allocated funds to five other sets of six projects each in order to give them practice and to help stabilize their reasoning processes. 4. Groups allocated funds to the six projects requesting support from the philanthropic trust. 5. Subjects completed a post-meeting questionnaire for measuring an individual\u27s perception of the group\u27s decision-making process, and individually allocated funds to the six projects requesting support from the philanthropic trust (these were used to calculate post-meeting consensus). 6. The administrator conducted a debriefing of the subjects. During section step 4 of the experiment, the group decision-making phase, teams were given one of the three treatments discussed previously. In the case of the manual groups, subjects were provided with a eleven-page handout outlining the same agenda that was on the GDSS. Each page of the handout explained an agenda item, giving details on how to accomplish the item parallel to those in the submenus of the GDSS. Manual groups were given a flip chart to display ideas publicly. Every effort was made to ensure that manual groups had the same structural aids as the GDSS groups, the only difference being that the manual groups operated without computer support. GDSS groups were provided with a 20-minute training session on use of the system, manual groups were also trained in how to use the meeting structure. Baseline groups were given no structure, flip chart, or training. They were told to operate with their own resources. FINDINGS This investigation identified some intended and unintended effects of using a decision support system for groups. Overall, the results on consensus and equality of influence for the GDSS and manual conditions tended to be similar, showing different patterns than the results for the baseline condition. As intended, the presence of a suggested structure for the group meeting improved the degree of post-meeting consensus. Also, in contrast to the baseline and manual system group meetings, users of the GDSS reported more input into the group\u27s solution and were less likely to perceive that there was a leader in the group. The relationship between pre-meeting and post-meeting consensus was similar in GDSS and manual groups, but post-meeting consensus was not significantly higher in the GDSS groups than in the baseline or manual groups. Although the structure provided in the GDSS and manual conditions reduced the variance across groups on their equality of influence, use of the GDSS did not result in more equal influence of group members on the final solution. The most surprising unintended effect was that GDSS users, compared to the other experimental groups, perceived the issues discussed in the group meeting to be more trivial and the group\u27s problem solving process to be less understandable. Other observations of the study were that use of the GDSS tended to reduce face-to-face interpersonal communication in the group; use of the GDSS presented a challenge to the groups, thus making their meeting task more difficult than groups without the GDSS; and groups using the GDSS appeared to become very procedure-oriented, rather than issue-oriented, in their discussions. In the future, GDSS research should press further to sort out what Kiesler calls intended technological effects (faster processing, fewer errors, more equal participation), unintended social effects (heightened conflict), and transient effects (effects that will diminish with group experience with the system) of the technology on groups. ACKNOWLEDGEMENT This project was funded by NCR Corporation, the MIS Research Center, and the Graduate School of the University of Minnesota

A Cost-Benefit Analysis of Face-to-Face and Virtual Communication: Overcoming the Challenges

Virtual communication has become the norm for many organizations (Baltes, Dickson, Sherman, Bauer, & LaGanke, 2002; Bergiel, Bergiel, & Balsmeier, 2008; Hertel, Geister, & Konradt, 2005). As technology has evolved, time and distance barriers have dissolved, allowing for access to experts worldwide. The reality of business today demands the use of virtual communication for at least some work, and many professionals will sit on a virtual team at some point (Dewar, 2006). Although virtual communication offers many advantages, it is not without challenges. This article examines the costs and benefits associated with virtual and face-to-face communication, and identifies strategies to overcome virtual communication\u27s challenges

Maximising the impact of careers services on career management skills: a review of the literature

The review identified an international body of work on the development and implementation of competency frameworks in reaction to CMS, including the ‘Blueprint’ frameworks, which are a series of inter-related national approaches to career management skills (originating in the USA and taken up subsequently, and with different emphases, by Canada, Australia, England and Scotland). There is, as yet, little empirical evidence to support the overall efficacy of CMS frameworks, but they have the advantage of setting out what needs to be learned (usually as a clear and identifiable list of skills, attributes and attitudes) and, often, how this learning is intended to happen. The international literature emphasised the iterative nature and mixture of formal and informal learning and life experiences that people needed to develop CMS. It suggested that, though there was no single intervention or group of interventions that appeared most effective in increasing CMS, there were five underpinning components of career guidance interventions that substantially increased effectiveness, particularly when combined. These included the use of narrative/writing approaches; the importance of providing a ‘safe’ environment; the quality of the adviser-client relationship; the need for flexibility in approach; the provision of specialist information and support; and clarity on the purpose and aims of action planning. The review also identified a possible emergent hierarchy around the efficacy of different modes of delivery of career guidance interventions on CMS development. Interventions involving practitioner contact and structured groups appeared more effective than self-directed interventions or unstructured groups. Computer-based interventions were found to work better when practitioner input was provided during the intervention or when they were followed up by a structured workshop session to discuss and review the results.Skills Funding Agenc

The Effects of a Flexible Benefits Expert System on Employee Decisions and Satisfaction

Anecdotal reports and recent reviews assert that expert systems are potentially useful decision aids in human resource management. This study examines the effects of an expert system designed to aid employees when they make their choices in a flexible bellcfit program. A four group quasi-field experimental design is used to examine the relative effects of the expert system compared to a conventional spreadsheet decision aid. Eighty employees at an NCR-AT&T facility were randomly selected and assigned to the groups. Employees using the expert system expressed greater benefits satisfaction compared to those using the spreadsheet aid. The spreadsheet did not have any effect on employees\u27 decisions. When the benefit choices recommended by the expert system differed from the employees\u27 current choices, employees are more likely to change their choices. Consequently, the expert system is likely to affect employees\u27 decisions. Implications are discussed and future research needs are suggested

Maximising the impact of careers services on career management skills: a review of the literature

The review identified an international body of work on the development and implementation of competency frameworks in reaction to CMS, including the ‘Blueprint’ frameworks, which are a series of inter-related national approaches to career management skills (originating in the USA and taken up subsequently, and with different emphases, by Canada, Australia, England and Scotland). There is, as yet, little empirical evidence to support the overall efficacy of CMS frameworks, but they have the advantage of setting out what needs to be learned (usually as a clear and identifiable list of skills, attributes and attitudes) and, often, how this learning is intended to happen. The international literature emphasised the iterative nature and mixture of formal and informal learning and life experiences that people needed to develop CMS. It suggested that, though there was no single intervention or group of interventions that appeared most effective in increasing CMS, there were five underpinning components of career guidance interventions that substantially increased effectiveness, particularly when combined. These included the use of narrative/writing approaches; the importance of providing a ‘safe’ environment; the quality of the adviser-client relationship; the need for flexibility in approach; the provision of specialist information and support; and clarity on the purpose and aims of action planning. The review also identified a possible emergent hierarchy around the efficacy of different modes of delivery of career guidance interventions on CMS development. Interventions involving practitioner contact and structured groups appeared more effective than self-directed interventions or unstructured groups. Computer-based interventions were found to work better when practitioner input was provided during the intervention or when they were followed up by a structured workshop session to discuss and review the results.Skills Funding Agenc

Do Interventions Designed to Support Shared Decision-Making Reduce Health Inequalities? : A Systematic Review and Meta-Analysis

Copyright: © 2014 Durand et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: Increasing patient engagement in healthcare has become a health policy priority. However, there has been concern that promoting supported shared decision-making could increase health inequalities. Objective: To evaluate the impact of SDM interventions on disadvantaged groups and health inequalities. Design: Systematic review and meta-analysis of randomised controlled trials and observational studies.Peer reviewe