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

Decision-focussed resource modelling for design decision support

Resource management including resource allocation, levelling, configuration and monitoring has been recognised as critical to design decision making. It has received increasing research interests in recent years. Different definitions, models and systems have been developed and published in literature. One common issue with existing research is that the resource modelling has focussed on the information view of resources. A few acknowledged the importance of resource capability to design management, but none has addressed the evaluation analysis of resource fitness to effectively support design decisions. This paper proposes a decision-focused resource model framework that addresses the combination of resource evaluation with resource information from multiple perspectives. A resource management system constructed on the resource model framework can provide functions for design engineers to efficiently search and retrieve the best fit resources (based on the evaluation results) to meet decision requirements. Thus, the system has the potential to provide improved decision making performance compared with existing resource management systems

Decision Support System of Herb’s Production Schedulling Based On Good Traditional Medicine Manufacturing Practices (GTMMP) Standard

The purpose of this research is to develop a decision support system in the herbs production scheduling appropriates to Good Traditional Medicine Manufacturing Practices (GTMMP). Design of algorithm model for scheduling decision support system that complies with GTMMP standard was done using a network analysis technique, which combines the techniques Evaluation and Review Technique Program (PERT) and Critical Path Method (CPM). The structure of decision support systems consists of database management syatem and modelbase management system. The implementation of decision support systems is the consideration for companies that intend to certify GTMMP

DECISION MAKING SUPPORT THROUGH A KNOWLEDGE MANAGEMENT FRAMEWORK FOR COMPLEX IT SYSTEMS DEVELOPMENT PROJECTS IN THE KINGDOM OF SAUDI ARABIA

Recent research reveals a narrow, rational model of problem- solving and decision-making in complex IT systems development projects. This creates problems that are identified in the thesis. The aim of this study is to develop a novel decision-making framework to support the decision-making process of managers of complex IT systems development projects by focusing on knowledge management frameworks. The objectives for the research were determined through a critical review of the existing research on decision-making in IT projects, primarily to discover how project managers’ decision-making can be supported through project-specific knowledge management. A qualitative research approach was then designed to investigate the phenomenon in its context by conducting in-depth semi-structured interviews. This study used qualitative data, through expert participants’ observations and opinions on IT systems development, particularly by understanding project management issues. The expert participants expressed their experiences through in-depth interviews. The collected data was then analysed using the thematic analysis technique and the findings were used to develop the IT Systems Development Decision-Making Support Framework. The Framework was then validated through focus group interviews. The main contribution of this research is based on the application of knowledge creation and knowledge management theories to decision-making frameworks for IT systems projects through the IT Systems Development Decision-Making Support Framework. The Framework is expected to enable decision evaluation and project-specific knowledge generation and sharing in IT systems development projects. This is vital for the type of contextual knowledge required for project-specific knowledge creation and management. Since IT systems development projects tend to be unique and their development process is complex, it is contended that an effective novel approach for modelling the expert decision-making process and assessing the defined model through project-specific knowledge activities is essential. This approach should help to deal with high level of complexity that is normally found in IT systems development projects

Using reliability analysis to support decision making in phased mission systems

Due to the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support decision making by allowing comparison of the probability of success of different missions following reconfiguration. Binary Decision Diagrams (BDDs) offer fast, accurate reliability analysis that could contribute to real-time decision making. However, phased mission analysis using existing BDD models is too slow to contribute to the instant decisions needed in time-critical situations. This paper investigates two aspects of BDD models that affect analysis speed: variable ordering and quantification efficiency. Variable ordering affects BDD size, which directly affects analysis speed. Here, a new ordering scheme is proposed for use in the context of a decision making process. Variables are ordered before a mission and reordering is unnecessary no matter how the mission configuration changes. Three BDD models are proposed to address the efficiency and accuracy of existing models. The advantages of the developed ordering scheme and BDD models are demonstrated in the context of their application within a reliability analysis methodology used to support decision making in an Unmanned Aerial Vehicle

Analysing Questionnaires on IT Project Status - Complexity Reduction by the Application of Rough Concepts

Since its introduction half a century ago IT has become one of the most important infrastructure components of virtually any organisation. An important key area of qualitative research in information systems is interviewing decision makers. These interviews aim to disclose hidden structures within IT projects and usage to increase their efficiency and effectiveness. In this context, the definition and analysis of critical success factors for information technology projects are well established areas for qualitative research in information systems. The analysis of critical success factors is of special importance since the IT projects still suffer from high failures rates. Therefore it is an important research goal within information systems to better understand IT projects to improve their success rates. The interviews of critical success factors provide a good data basis to disclose hidden structures in this domain. Besides only quantitatively interpreting such interviews the analysis can be enriched by some qualitative methods to support quantitative analysis and may disclose formerly hidden structures within the data. Therefore the objective of the paper is to enrich the analysis of IT projects and evaluate rough sets based quantitative analysis techniques for symbolic data which are characteristic in the domain of critical success factors analysis

Data mining in medical records for the enhancement of strategic decisions: a case study

The impact and popularity of competition concept has been increasing in the last decades and this concept has escalated the importance of giving right decision for organizations. Decision makers have encountered the fact of using proper scientific methods instead of using intuitive and emotional choices in decision making process. In this context, many decision support models and relevant systems are still being developed in order to assist the strategic management mechanisms. There is also a critical need for automated approaches for effective and efficient utilization of massive amount of data to support corporate and individuals in strategic planning and decision-making. Data mining techniques have been used to uncover hidden patterns and relations, to summarize the data in novel ways that are both understandable and useful to the executives and also to predict future trends and behaviors in business. There has been a large body of research and practice focusing on different data mining techniques and methodologies. In this study, a large volume of record set extracted from an outpatient clinic’s medical database is used to apply data mining techniques. In the first phase of the study, the raw data in the record set are collected, preprocessed, cleaned up and eventually transformed into a suitable format for data mining. In the second phase, some of the association rule algorithms are applied to the data set in order to uncover rules for quantifying the relationship between some of the attributes in the medical records. The results are observed and comparative analysis of the observed results among different association algorithms is made. The results showed us that some critical and reasonable relations exist in the outpatient clinic operations of the hospital which could aid the hospital management to change and improve their managerial strategies regarding the quality of services given to outpatients.Decision Making, Medical Records, Data Mining, Association Rules, Outpatient Clinic.

A domain analysis model for eIRB systems: addressing the weak link in clinical research informatics

pre-printInstitutional Review Boards (IRBs) are a critical component of clinical research and can become a significant bottleneck due to the dramatic increase, in both volume and complexity of clinical research. Despite the interest in developing clinical research informatics (CRI) systems and supporting data standards to increase clinical research efficiency and interoperability, informatics research in the IRB domain has not attracted much attention in the scientific community. The lack of standardized and structured application forms across different IRBs causes inefficient and inconsistent proposal reviews and cumbersome workflows. These issues are even more prominent in multi-institutional clinical research that is rapidly becoming the norm. This paper proposes and evaluates a domain analysis model for electronic IRB (eIRB) systems, paving the way for streamlined clinical research workflow via integration with other CRI systems and improved IRB application throughput via computer-assisted decision support

Novel Decision Support Systems: Design and Assessment

This dissertation consists of three essays that propose designs and theoretically-based evaluations of two novel decision support systems (DSS): a web-based spatial DSS (SDSS), a dialectic DSS (DDSS), and a comparative analysis of subjective and objective measures of system success in terms of decision process and outcome. In the first essay, a web-based SDSS that utilizes the latest advances in web-based geographic information systems (GIS) is designed and developed to support decision makers for making spatial decisions. Task-technology, goal setting, and self-efficacy theories are synthesized to develop a conceptual model to explore the perceptual factors impacting the perceived performance of web-based SDSS. Building on the first essay’s theoretical model, a conceptual model for the second essay is developed for evaluating the efficacy of the proposed web-based DDSS that embeds a dialectic technique for unstructured problems, in order to elicit the underlying assumptions in the decision process. The third essay uses the research data from the prior essays to examine whether there is a discrepancy between subjective measures and objective measures of information-system success factors in the context of SDSS and DDSS. Together, these three essays extend the field by adding spatial and critical-thinking dimensions to the existing DSS and may provide a deeper understanding of perceptual and objective success measures for such systems

SYSTEMS ANALYSIS OF ARMY MATERIEL REPORTING FOR THE MIDDLE TIER OF ACQUISITION PATHWAY

The Acquisition Modernization Integration (AMI) team within the ASA(ALT) office is critical in the Army decision-making process. The AMI creates reports that include actionable knowledge rendered to Army strategic leaders. These reports include vital data on critical Army programs integrated into the modernization efforts. Part of this necessary data are the First Unit Issued (FUI) and the First Unit Equipped (FUE) dates. These reported dates directly affect Army units’ training, deployment, and logistics support timelines as they become part of the data-driven analytics on reports provided to decision-makers. Because of the initiatives to improve efficiency in the acquisition process, realignment, and creation of new organizations, the AMI needs a system that facilitates accurate and consistent FUI and FUE dates reporting. This research used several systems engineering (SE) concepts and methods such as stakeholders’ analysis, functional analysis, mapping of functions to systems’ parameters, modeling-based systems engineering, and analysis of alternatives. The application of these SE tools resulted in identifying a system/process that will accurately and consistently facilitate FUI and FUE date reporting to meet the AMI’s needs. This system/process provides a reporting capability for current and future acquisition programs and could be implemented across the DOD and all other government agencies and departments.Major, United States ArmyCaptain, United States ArmyCaptain, United States ArmyCaptain, United States ArmyCaptain, United States ArmyApproved for public release. Distribution is unlimited