1982 - Processes and Tools for Decision Support

Schloss Laxenburg, Austria, 19-21 July

Proceedings edited by H.G. Sol.

Title Pages
Sol, H. G.
Ćećez-Kecmanović, D.

Our research is devoted to the analysis of information in decision-making processes. For this purpose we develop descriptive models of decision-making with various types of uncertainties. Then we can examine the influence of information on decision-makers' behavior in different situations. Decision support systems with various focuses of information are observed within two experiments and the resulting impact of information on the decision-makers' performance are measured.

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Lee, R. M.
Keywords:Decision Support Systems Knowledge Representation Knowledge-Based Systems Applied Epistemology Denotational Semantics

Knowledge-based decision support applications differ from those typical of artificial intelligence expert systems in their open-ended, evolutionary character and need to coordinate with other systems resources, such as organizational databases and quantitative analysis routines. While knowledge representation machinery is becoming available, the corresponding formalization of managerial/administrative knowledge needed for DSS application is still lacking. This entails problems of an epistemological nature, identifying the foundational concepts of business. An abstract framework based on formal languages and denotational semantics is proposed, and ontological issues are identified.

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Coelho, H.

Recent research in decision support systems shows a growing interest in knowledge representation and knowledge-based systems. Yet, implementations of DSS continue to be dominated by quantitative, algorithmic perspectives of such languages as APL, BASIC, FORTRAN, etc. This paper presents an alternative approach. It uses the language Prolog.

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Young, L. F.

Interactive computer-based Decision Support Systems are supposed to enable managers to more closely follow their own behavioral process and apply judgement and creativity in decision-making. However, an examination of actual applications of DSS indicates that they are largely mathematical-model based, and quantitatively analytical in their approach. This kind of process had been called "left-brained" because it is associated with what are thought to be functions of the left hemisphere of the human brain. More qualitative approaches toward creativity in dealing with “open” decision problems have been applied in some human group processes such as brainstorming and synectics. These “Right-brained” approaches have been examined in order to formulate a starting point for functionally specifying a set of computer modules for a new kind of DSS. This new type of system, called “Right-brained DSS”, is described in this work. A total DSS, utilizing an interface between Right and left-brained approaches, is also described. Selected modules are currently being experimentally developed by the author.

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Bonczek, R. H., Holsapple, C. W. and Whinston, A. B.

The DSS literature is plagued with muddled descriptions of implementations. Without a framework for comparison, discussion would be futile. This paper presents a theoretical framework for analyzing a DSS. A multilevel approach is employed to reflect the objectives and constraints of the many different DSS users. A design mechanism, based on data base management, is motivated by this framework.

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Bosman, A.

There is a lot of discussion about the status and the future of decision support systems (DSS). In this discussion two points relevant for the development of DSS do not get the attention they deserve. The first one is the fact that in various sciences studying the topic of decision processes in organizations a hard core for research is missing. It is questionable whether DSS, even in the form of a theory, can deliver such a hard core. The second point is that too much emphasis is placed on the possibilities to generate action alternatives. This can result in a situation where it is difficult to find a solution for the co-ordination problem with the usually applied instruments. Therefore the two aspects of decision making in organizations, namely the generation of action alternatives and finding a solution of the co-ordination problem, should be regarded simultaneously.

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Methlie, L. B.

The general problem dealt with in this paper is how the infrastructure set up by an organization, on the one hand, will give several economic benefits and, on the other hand will impose constraints on individuals, and thus affect socio-political behavior. Both kinds of variables are assumed to influence overall effectiveness of specific DSSs. A proposition set forward and analyzed in the paper, is that the more complex the infrastructure is, the less discretion will the decision-maker exercise in the job. Rational-economic thinking may support sharing of a range of resources in the organization. However, socio-political issues may counteract these expected economic benefits. The ultimate interest is how potential dysfunctional consequences of socio-political aspects impact on effectiveness and efficiency of task performance.

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Fox, M. S.

This paper describes the Intelligent Management System (IMS) project, which is part of the Factory of the Future project in the Robotics Institute of Carnegie-Mellon University. IMS is a long term project concerned with applying artificial intelligence techniques in aiding professionals and managers in their day to day tasks. This report discusses both the long term goals of IMS, and current research. It describes research in the modeling of organizations, constraint-based job-shop scheduling, organization simulation, user interfaces, and system architecture. Examples of working systems are provided.

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Brookes, C. H. P.

The hardware and software environment which is increasing the sophistication of mechanised office and text processing systems can also play a role in the design of decision support systems. It is clear that managers make considerable use of so-called ‘soft information’ in their work, and this is almost always encoded in textual or natural language form. The manner in which text processing technology might be used to increase effectiveness is examined. The design basis for a message system which can fulfill a DSS role by reporting text data is described.

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Maes, R., Vanthienen, J. and Verhelst, M.

The PROcedural DEcision MOdeling (PRODEMO) system was developed to enhance the application of decision tables as a general management technique. This shift of focus with relation to the usefulness of decision tables is briefly indicated in the paper, after which the proper PRODEMO system is presented. Then attention is given to practical experiences with the PRODEMO system in multiple organizations. To this end, three typical case studies are reviewed and empirical results obtained from many other cases are reported on.

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Dickson, G. W.

The equivalent of today’s black dial telephone in the early 1990’s will be a management support facility. These devices will cost, relative to managerial wage rates, roughly four times what today’s telephone costs. The important issue concerns the functions these devices will perform. This paper defines the functionality of the MSF based upon managerial and professional task requirements plus a forecast of the MSF's technical attributes.

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Klein, M. R. and Manteau, A.

This paper: - introduces the concept of a Decision Support Center (DSC) and of a Decision Support System Generator (DSSG) - gives an example of the implementation of a DSS using OPTRANS - points out some important concepts of OPTRANS and give some examples of some of the language constructs available in OPTRANS to use these concepts - describes our experience with the system

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Bergquist, J. W. and McLean, E. R.

The Integrated Data Analysis and Management System (IDAMS) is an APL-based system designed to support business and scientific end users. Although there are a number of references to the use of APL as a DSS tool, IDAMS is one of the first examples of an APL-based DSS generator. It was developed at the IBM Scientific Center in Heidelberg, Germany, and is now undergoing testing and further development in the United States in a joint project between the IBM Scientific Center in Los Angeles and the University of California, Los Angeles (UCLA). This paper describes the design objectives and structure of IDAMS and illustrates its use with a sample terminal session.

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Humphreys, P. and Larichev, O. I.

Issues determining the success of applications of Decision Support Systems in ill-structured situations are examined through four case studies of R & D decision making. These concern (1) introduction of a new product where the R & D decision is taken at the company board level; (2) the determination of the product mix for a medium-sized manufacturing enterprise where more than one level of decision making is involved; (3) R & D decision making at the branch level within a three-level planning hierarchy; (4) the use of DSS in “top-level” decision making involving selection between proposals covering a wide range of R & D activities. In each case the context of each round in the decision making process is identified, together with the roles, motivation and responsibilities of the participants, and the level in the organizational process at which the DSS is implemented; factors which are shown to vitally influence the nature and success of the DSS usage. Pitfalls for DSS designers are uncovered through analysis and comparison of the cases, and ways of avoiding them are proposed.

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Bohanec, M., Bratko, I. and Rajkovič, V.

A new decision support system, developed as an expert system, is presented. The method is formally described and discussed. Its distinguishing feature is its human orientation which is mainly reflected in the system’s ability to explain utility calculation. A corresponding computer implementation is presented together with a practical application in decision making.

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Takkenberg, C. A. T.

CAP (Computer Aided Planning) is a DSS for the planning of production levels. The major tools are linear programming and model experimentation. This paper presents a case history and evaluates CAP as a DSS. The major recommendation is to start the development of DSS with the construction of a descriptive model.

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