THE NATURE OF DSS LITERATURE PRESENTED IN MAJOR IS CONFERENCE PROCEEDINGS (1980-1985)

This paper reports and analyzes the nature, content, and trends exhibited by DSS papers presented at the four major annual or biennial IS/DSS conferences during 1980-1985. (Three of the conferences held their first meeting during this period.) It then compares the findings from this analysis with those obtained with a different database, namely all DSS articles published in 22 professional journals during this same period. Inferences are drawn concerning (1) the perceived roles and benefits of conferences versus those of journals and (2) the apparent state and direction of the DSS field

Deep space network energy program

If the Deep Space Network is to exist in a cost effective and reliable manner in the next decade, the problems presented by international energy cost increases and energy availability must be addressed. The Deep Space Network Energy Program was established to implement solutions compatible with the ongoing development of the total network

Decision support systems for large dam planning and operation in Africa

Decision support systems/ Dams/ Planning/ Operations/ Social impact/ Environmental effects

Aspects of automation of selective cleaning

Cleaning (pre-commercial thinning) is a silvicultural operation, primarily used to improve growing conditions of remaining trees in young stands (ca. 3 - 5 m of height). Cleaning costs are considered high in Sweden and the work is laborious. Selective cleaning with autonomous artificial agents (robots) may rationalise the work, but requires new knowledge. This thesis aims to analyse key issues regarding automation of cleaning; suggesting general solutions and focusing on automatic selection of main-stems. The essential requests put on cleaning robots are to render acceptable results and to be cost competitive. They must be safe and be able to operate independently and unattended for several hours in a dynamic and non-deterministic environment. Machine vision, radar, and laser scanners are promising techniques for obstacle avoidance, tree identification, and tool control. Horizontal laser scannings were made, demonstrating the possibility to find stems and make estimations regarding their height and diameter. Knowledge regarding stem selections was retrieved through qualitative interviews with persons performing cleaning. They consider similar attributes of trees, and these findings and current cleaning manuals were used in combination with a field inventory in the development of a decision support system (DSS). The DSS selects stems by the attributes species, position, diameter, and damage. It was used to run computer-based simulations in a variety of young forests. A general follow-up showed that the DSS produced acceptable results. The DSS was further evaluated by comparing its selections with those made by experienced cleaners, and by a test in which laymen performed cleanings following the system. The DSS seems to be useful and flexible, since it can be adjusted in accordance with the cleaners’ results. The laymen’s results implied that the DSS is robust and that it could be used as a training tool. Using the DSS in automatic, or semi-automatic, cleaning operations should be possible if and when selected attributes can be automatically perceived. A suitable base-machine and thorough research, regarding e.g. safety, obstacle avoidance, and target identification, is needed to develop competitive robots. However, using the DSS as a training-tool for inexperienced cleaners could be an interesting option as of today

A critical analysis of decision support systems research

This paper critically analyses the nature and state of decision support systems (DSS) research. To provide contest for the analysis, a history of DSS is presented which focuses on the evolution of a number of sub-groupings of research and practice: personal DSS, group support systems, negotiation support systems, intelligent DSS, knowledge management-based DSS, executive information systems/business intelligence and data warehousing. To understand the state of DSS research an empirical investigation of published DSS research is presented. This investigation is based on the detailed analysis of 1,020 DSS articles published in 14 major journals from 1990 to 2003. The analysis fund that DSS publication has been falling steadily since its peak in 1994 and the current publication rate is at early 1990s levels. Other findings include that personal DSS and group support systems dominate research activity and data warehousing is the least published type of DSS. The journal DSS is the Major publishing outlet, US 'Other" journals dominate DSS publishing and there is very low exposure of DSS in European journals. Around two-thirds of DSS research is empirical, a much higher proportion than general IS research. DSS empirical research is overwhelming positivism, and is more dominated by positivism than IS research in general. Design science is a major DSS research category. The decision support focus of the sample shows a well-balanced mix of development, technology, process, and outcome studies. almost half of DSS papers did not use judgement and decision-making reference research in the design and analysis of their projects and most cited reference works are relatively old. A major omission in DSS scholarship is the poor identification of the clients and users of the various DSS applications that are the focus of investigation. The analysis of the professional or practical contribution of DSS research shows a field that is facing a crisis of relevance. Using the history and empirical study as a foundation, a number of strategies for improving DSS research are suggested

METHODOLOGIES FOR DSS ANALYSIS AND DESIGN: A CONTINGENCY APPROACH TO THEIR APPLICATION

The analysts and design of systems for decision support typically has taken a single methodology approach, ignoring the fact that DSSs vary in their scope, complexity and purpose. This paper examines three primary approaches to DSS analysis and design in order to begin formalizing a consistent framework for the selection of a DSS development methodology. The contingency framework emphasizes the conditions under which the various methodologies are appropriate and likely to be effective, and provides guidelines for matching decision situations with development approaches

An Inductive Approach to Documenting the Core and Evolution of the IS Field

This article inductively examines the question of the IS field\u27s core. We argue that as a socially constructed field, the core aspects of IS can be identified from the work conducted and published by members of IS community. The abstracts (including titles) of 1,197 IS studies in three premier IS journals for the past 26 years were examined to identify the core of the field and explore its evolving nature with help of a neural network software as the analysis tool. The field, contextual, transitory, and evolving core of IS are identified through the analysis of 267,034 words in the knowledge base constructed. The results show both stability and evolution of the core of IS field. The three journals examined show sufficient commonality on core of the field, with slightly different preferences for research topics and methods. Given the diverse nature of the IS field, we believe that such a retrospective and descriptive study can document evidence of the core and facilitate a better understanding of the evolution of the field

A Critical Review of Decision Support Systems Foundational Articles

Abstract Decision Support Systems (DSS) is a mature field of study with an extensive conceptual and empirical literature. This research study provides a starting point for learning and reviewing the foundation literature of the field. Decision support and analytics researchers can benefit from revisiting the methodologies, identifying under-explored ideas, and hopefully identifying visionary concepts from thought leaders who established the DSS research stream. This article reports a systematic examination of the DSS foundational literature published in MIS Quarterly during its first fifteen years of publication -- 1977-1991. In addition to examining the relevance of these articles to current and future research, the findings of the study provide a reference point of DSS research categories. Articles were categorized in terms of theory, methods, concepts and perspectives about computerized decision support that enrich research and encourage future exploration

KEY FEATURES FOR PROBLEM FRAMNG DECISION SUPPORT

This paper addresses the concern for improving DSS design and implementation in the areas of problem framing and problem formulation. It relates key principles of DSS development that are based on a cognitive information processing framework with the tasks that are part of a problem formulation process. Furthermore, the paper shows how the components of a DSS can be related to elements of the combined information processing and problem formulation process frameworks

Model Management Systems: Proposed Model Representations and Future Designs

The availability of microcomputers, modeling langauges and general purpose spreadsheets has resulted in an increase in the use of models for decision making within organizatons. Decision makers with microcomputers on their desks and spreadsheet and modeling software can create models rapidly. Problems with model redundancy, consistency, integrity and security have prompted an increased interest in the design of model management systems (MMS). Several model management designs have been discussed in the literature. Different model representation techniques have been proposed. These include formal logic, semantic inheritance networks, frames, and relational representations. The approaches to model management are evaluated in respect to their model manipulation and model storage functions. A framework for the design of MMS is proposed based on the system design objectives and the system domain complexity. Advantages and disadvantages of each model representation method are identified. Application domains for the classifications are proposed which focus on the strengths and weaknesses of the model representation for supporting model storage and model manipulation functions. An example of the design of a MMS using the classification is presented