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

A new model for the development of information systems

The most commonly used systems specification and design techniques in commercial computing are described and compared; Information Engineering as proposed by James Martin, A Framework for Information Definition-Muitiview proposed by Wood-Harper et al, Real-world Modeling as described by Jackson, Structured Analysis and Design as In Demarco, Yourdon and Constantine and Output-Oriented Structured Requirement Definition proposed by Orr. In addition, system prototyping is discussed, including the role of prototyping in large software development projects and as a tool for the design of human-computer interfaces. Other areas described and discussed include decision support systems (DSS) and knowledge based management support systems. The context is in the design and development approaches for DSS, prototyping for DSS, expert system for DSS and the integration of DSS and information system. The design and development of human-computer interface is also discussed in relation to user Interface complexity and adaptive interfaces. Further, the important issue of user involvement and support within the development process Is discussed. Thus, weaknesses of current approaches to the system development process are identified and a new model for the development of information system is proposed. In proposing the model, data and functional analysis structured method and methodology for decision support systems (DSS) development is presented including guidelines for the development of knowledge based DSS. The new proposed model is put to test in the design, development and implementation of large integrated commercial systems including DSS. Results and discussion on the use of the model is reported with special consideration to the users' and developers' view of the model. Finally the objectives of this research program are examined in relation to what has been achieved during this program of research. The prospect of using the model for the development of information systems are concluded with references to current and future goals

Design science research for decision support systems development: recent publication trends in the premier IS journals

This paper presents a contemporary literature review of design science research (DSR) studies in the domain of decision support systems (DSS) development. The latest studies in the DSS design domain claim that DSR methodologies are the most popular design approach, but many details are still yet to be revealed for supporting this claim. In particular, it is important to thoroughly investigate the trends in either the form or deeper insights in use of DSR in this field. The aim of this study is to analyse the existing DSS design science studies to reveal insights into the use of DSR, so that we can outline research agenda for a special issue, based on findings of analysis. We selected articles (from 2005 to 2014) that were published in seven selected premier IS journals (ranked as A* in the ABDC journal ranking). The selected 57 sample articles are representative of DSS design studies that used DSR in theorising, designing, implementing, and evaluating DSS solutions. We discuss the theoretical positions of DSR for DSS development through six categories: DSS artefacts, DSR methods, DSR views, user involvement, DSS design innovations and problem domains. The findings indicate that new studies are needed to fill the knowledge gap in DSS design science, for more solid theoretical basis in near future

Identifying Appropriate MIS/DSS Support: A Cost Analysis Approach

This paper describes a microeconomic theory-based tool, called cost analysis, which can be used in MIS research to develop guidance for systems analysts and information resource managers. An example of this guidance is a matrix of decision making contexts versus appropriate MIS/DSS support. Systems analysts can use this matrix to help identify appropriate MIS/DSS design alternatives. Information resource managers can use this matrix to help plan for the proper evolution of MIS/DSS support

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

Selected Issues of Design and Implementation od Decision Support Systems

The paper presents selected issues related to design and implementation of model based Decision Support Systems (DSS). For over ten years the SDS Program has been involved in cooperation with various projects at IIASA and in collaborating research institutes. This cooperation has resulted in the development of many DSS, which in turn stimulated research on the theory and methodology of decision analysis. An overview of selected DDS developed within the cooperation with IIASA is presented. Different concepts of DSS are briefly discussed and one specific type of DSS, namely model based, aspiration-led DSS is characterized. Finally, selected problems of designing and implementation of a DSS are discussed in more detail. A short description of software packages developed within the cooperation with the MDA Project is provided. The paper also gives a short summary of recent activities of the Methodology of Decision Analysis Project and of the DSS software available from the MDA Project

STR-996: OPTIMIZATION FOR BRIDGE TYPE SELECTION USING ARTIFICIAL NEURAL NETWORKS

Many Researchers have attempted to establish a methodology for the selection of bridge type in a systematic manner. Knowledge based systems (KBS) and other Expert Systems (ES) have been used for this purpose but they have some limitations and restrictions. This paper proposes a methodology to implement a Decision Support System (DSS) in an artificial intelligent environment that aims to suggest a bridge type with its main components at the conceptual design phase, based on the characteristics and performance of existing and similar bridges in order to predict the performance of proposed ones that have been analyzed by decision makers with limited subjectivity. The proposed methodology is divided into three main divisions: 1) this division includes a database that will be structured to store appropriated information besides including models like Point Scale and Quality Function Deployment (QFD) systems that will serve for linguistic conversion to numbers needed for the DSS engine. This division contains as well all the mandatory criteria that have influence on the performance of proposed bridges. 2) this division is the core of the “DSS Engine” where it receives the information from the database that will be implemented in an Artificial Neural Network (ANN) module for training, testing and then predicting the performance of a new case bridge. Afterwards a decision will be made to implement the ANN’s results into a Bridge Information Modeling (BrIM) environment to visualize the suggested design and to predict the potential problems. 3) In this division, a final decision will be made based on the results of the second division. In the proposed DSS, most of the factors are considered as criteria in the database; criteria that have influence on the decision are automatically considered during the analysis process and are introduced in the DSS Engine. The flexibility of the proposed methodology and particularly the database and the method of analysis will make the DSS very helpful in the area of bridge design and management. This will provide bridge engineers with an efficient tool that will minimize the subjectivity in their decisions. A case project will be considered to test the workability and capability of the proposed methodology

DESIDS: An Integrated Decision Support System for the Planning, Analysis, Management and Rehabilitation of Pressurised Irrigation Distribution Systems

Pressurized irrigation distribution systems (PIDSs) play a vital role in irrigation intensification, especially in the Mediterranean region. The design, operation and management of these systems can be complex, as they involve several intertwined processes which need to be considered simultaneously. For this reason, numerous decision support systems (DSSs) have been developed and are available to deal with these processes, but as independent components. To this end, a comprehensive DSS called DESIDS has been developed and tested. This DSS has been developed to bear in mind the needs of irrigation district managers for an integrated tool that can assist them in taking strategic decisions for managing and developing reliable, adequate and sustainable water distribution plans which provide the best services to farmers. Hence, four modules were integrated in DESIDS: (i) irrigation demand and scheduling module; (ii) hydraulic analysis module; (iii) operation and management module; and (iv) design and rehabilitation module. DESIDS was tested on different case studies, proving itself a valuable tool for irrigation district managers, as it provides a wide range of decision options for the proper operation and management of PIDSs. The developed DSS can be used as a platform for future integrations and expansions, and to include other processes needed for better decision-making support