Field Of Decision Support Systems Research Articles

Analysis of the Role of Global Information Management in Advanced Decision Support Systems (DSS) for Sustainable Development

Timely intelligent decision support systems (DSS) are increasingly important for the sustainable development of entrepreneurship. Global information management plays an important role in accurate DSS. Judgments can be made more quickly, accurately, and objectively thanks to the availability of large data and sophisticated artificial intelligence in the realm of quantitative smart decisions. In this context, this research analyzes the contribution of global information management for sustainable business development through DSS. This paper used the Scopus database to collect relevant research papers related to the research topic. This research helps researchers analyze the recent trend and development in the field of DSS in the context of global information management.

Decision making using document driven decision support systems

New innovations in the technologies have provided several opportunities to support the process of decision making by utilising decision support systems (DSS) which are one of the most important management systems in the modern environment of business. Document-driven DSS (DDDSS) is one of the most common types of DSS that assist decision-makers by facilitating the steps of extracting information and knowledge management. It searches for documents by keywords on a web page and utilises a collection of processing and recovery technologies for recovery and analysis. This paper aims to introduce a basic understanding of DDDSS and to help the researchers who interested in this field of DSS. It relies on the previous studies about document-driven DSS especially, and displayed the objectives and types of documents that it used. Then, it presented the features, and explained how it works. It mentioned also the benefits of DDDSS and showed the evolution and trend.

157: ASSESSING THE METHODOLOGICAL QUALITY OF DECISION SUPPORT SYSTEM (DSS) SYSTEMATIC REVIEWS BY AMSTAR CHECKLIST

Background and aims:It is all accepted that high-quality evidence is essential for clinical decision making. As Haynes “6S pyramid”, systems including decision support systems are at the top of this...

158: ASSESSING THE QUALITY OF SEARCH STRATEGIES IN DECISION SUPPORT SYSTEM (DSS) SYSTEMATIC REVIEWS

Background and aims:Search strategies play a major role in developing a systematic review. A comprehensive literature search dramatically reduces publication bias. The higher sensitive search leads to a more well-prepared...

A Critical Analysis of Decision Support Systems Research Revisited: The Rise of Design Science

In 2005 the Journal of Information Technology article ‘A critical analysis of decision support systems research’ analyzed 1020 decision support systems (DSS) articles from 1990 to 2003. Since 2003 business intelligence (BI) and business analytics have gained popularity in practice. In theory and research the period since 2003 has seen a change in the decision-making theory orthodoxy and the codification and acceptance of design science. To investigate the changes in the DSS field, a number of expectations were derived from previous literature analyses. These expectations were assessed using bibliometric content analysis. The article sample to 2010 now includes 1466 articles from 16 journals. The analysis of the expectations yields mixed results for the DSS field. On the negative side, there has been an overall decline in DSS publishing, the relevance of DSS research published in journals to IT professionals has declined, and the rigor of DSS research designs has not improved. On the positive side, there has been improvement in relevance to managers, grant funding of DSS research has increased, there has been a positive shift in judgment and decision-making foundations, BI publishing has increased, and group support systems publishing has reduced to a more balanced level. An important result from the analysis of the last 7 years of DSS research is the significant increase in DSS design-science research (DSR) to almost half of published articles. It is clear from the analysis that DSS is undergoing a transition from a field based on statistical hypothesis testing and conceptual studies to one where DSR is the most popular method.

Cloud computing and DSS: the case of spatial DSS

While academic researchers in the field of decision support systems (DSS) tend to emphasise the technology independent nature of the decision support concept, they also need to assess the role of new technology; cloud computing is one such new technology. This paper suggests that the specific nature of DSS means that cloud computing is of limited relevance in most sectors of DSS application. However, spatial DSS is a distinct area of DSS application where large volumes of generic data are needed from outside the organisation making the decision. Consequently, a number of issues arise in the provision of data for SDSS which are not typical of the DSS field. Spatial data infrastructure (SDI) projects provide large collections of spatial data and can make use of technologies such as cloud computing. This paper argues that cloud computing can contribute to spatial DSS applications which use these large data resources. Spatial DSS remains a form of DSS which continues to push the limits of technology and developments in this sector can inform our understanding of the progression of the DSS field.

A Medical Informatics Perspective on Decision Support

To summarize current excellent research in the field of decision-support systems. We provide a synopsis of the articles selected for the IMIA Yearbook 2009, from which we attempt to derive a synthetic overview of the activity and new trends in the field. Five papers from international peer reviewed journals have been selected for the section on decision support. While the state of the research in the field of decision-support systems is illustrated by a set of fairly heterogeneous studies, it is possible to identify trends. Thus, issues related to guidelines processing implementation occupies a central role in today's field with two alternative directions: 1. broad medical applications, which attempts to assist decision-makers to process large patient sets; 2. narrow clinical applications focused on in-depth real-time signal processing for a specific population or medical specialty. The best paper selection of articles on decision-supports shows examples of excellent research on methods concerning original development as well as quality assurance of reported studies. It is also observed that this year's selection point directly to more original research areas such as temporal signal processing, although more traditionally related areas, such as information retrieval and/or natural language processing, remain fairly active in the field. Altogether these papers support the idea that more elaborated computer tools, likely to combine together textual and highly structured data, including real-time data contents, are needed.

A system dynamics model as a decision aid in evaluating and communicating complex market entry strategies

Developing a market entry strategy is a critical activity for any firm but all the more so for those firms that wish to successfully compete in today's challenging global economy. Unfortunately, developing a market entry strategy is an ill-structured and complex activity for which structured approaches have proven inadequate. In less structured situations, data driven and model based decision-support systems (DSS) have been shown to be of significant help to decision-makers faced with such tasks. Getting managers to use such systems, however, is a major challenge that has been the subject of considerable research in the field of DSS. As far back as the 1970's scholars identified reasons why managers are reluctant to use such systems. Among the most often cited reasons why managers are reluctant to use these systems are: they do not understand the model inherent in the DSS; they do not know when to use them; they are unable to extend the use of the DSS; or they are unable to explain the model or its output to others. This paper describes the process of building a system dynamics model that can be employed by marketing managers to help them test the effectiveness of different market entry strategies, and equally important to help them to explain the system's logic and output. The model was built in a bottom-up fashion with the help of a team of marketing managers. In this way the team that helped build the model not only felt a sense of ownership concerning the model, but were also be able to better explain and defend their proposed strategy.

Eight key issues for the decision support systems discipline

This paper integrates a number of strands of a long-term project that is critically analysing the academic field of decision support systems (DSS). The project is based on the content analysis of 1093 DSS articles published in 14 major journals from 1990 to 2004. An examination of the findings of each part of the project yields eight key issues that the DSS field should address for it to continue to play an important part in information systems scholarship. These eight issues are: the relevance of DSS research, DSS research methods and paradigms, the judgement and decision-making theoretical foundations of DSS research, the role of the IT artifact in DSS research, the funding of DSS research, inertia and conservatism of DSS research agendas, DSS exposure in general “A” journals, and discipline coherence. The discussion of each issue is based on the data derived from the article content analysis. A number of suggestions are made for the improvement of DSS research. These relate to case study research, design science, professional relevance, industry funding, theoretical foundations, data warehousing, and business intelligence. The suggestions should help DSS researchers construct high quality research agendas that are relevant and rigorous.

Abstracting Data With A Decision Support System Based on Data Warehouses for the Evaluation of Ship Form Alternatives

A new aided decision support system (DSS) based on data warehouses is discussed. It is composed of data warehouses, on-line analysis processing, and data mining, which is new in the field of DSS. The essential principle, the setting up of the model, the development environment, the main system interface, and a sketch of the theory framework of the new DSS architecture are also described. The decision support system was applied to data abstraction for evaluating ship form scenarios. Tests have shown it to be practical and dependable in complex systems, such as in the demonstration of ship forms.

The enabling role of decision support systems in organizational learning

Organizations routinely process information, make decisions, and implement them. Recent advances in computer and communications technologies have changed the way in which organizations perform these functions. Decision support systems (DSSs) are a major category of tools that an organization utilizes to support and enhance its decision-making activities. Traditionally, organizations are considered to have a predefined and static set of goals. However, in order to stay competitive and survive in today's dynamic environment, organizations must be able to quickly respond and adapt to changes in their business settings. Such changes could be due to technological advances, growing and changing customer demands, competitive forces, changes in the labor force, environmental and political concerns, societal impacts, security concerns, and others. In recent years, the field of DSS has become more sophisticated to encompass such paradigms as expert systems (ESs), intelligent DSSs, active DSSs, and adaptive DSSs. Artificial intelligence (AI)-based techniques are being embedded in many DSS applications, thus enhancing the support capabilities of the DSS. Such paradigms have application potential in both individual and organizational learning contexts. However, the degree to which current DSSs can support organizational learning has yet to be investigated in depth. This paper examines the learning strategies employed by organizations and DSSs and provides a framework to demonstrate how a DSS can enhance organizational learning.

DSS research and practice in perspective

The aim of this paper is to assess the state-of-the-art in the Decision Support Systems (DSS) field from both a research and a practice perspective. Three main dimensions of DSS research and practice are addressed: 1) supporting human decision-making processes, 2) integrating DSS into the organizational context, and 3) identifying new application domains. The related analysis and discussion provides a better understanding of past developments in the DSS field and insights into future evolution patterns.

Decision Support Systems (DSS) development using a model of user inquiry types: Methodological proposals and a case study

A study of the DSS implementation area reveals an increased emphasis on methodologies for DSS development. As the DSS field matures, a larger number of methodological options are becoming available to the DSS developer. Existing methodologies have adopted various methods for performing the important task of DSS requirements analysis and specification. In envisaging a hierarchy of requirements analysis methods, a method for improved requirements analysis is proposed to remedy observed deficiencies within it. This method is based on a view of generic types of inquiries or solicitations made by the DSS user during decision-making. This formalism constitutes the basis of a proposed DSS development methodology that offers several benefits to DSS development. The intended benefits include a sharper and more focused requirements analysis to improve the DSS development process. This paper describes the model and methodology, alongside details of a real-world example of their use in developing a Marketing Decision Support System (MKDSS) for the support of marketing decision-making.

Decision Support Systems (DSS): A survey

Interest in aiding and supporting decision-making through the use of computers has been stimulated by technological developments in areas such as personal computers, computer networks, large data bases, colour graphics and computer-based models. These uses are known as Decision Support Systems (DSS) and imply computer systems designed to extend managers' capabilities, and at the same time to integrate these uses into existing managerial activities and needs. During the past few years there have been rapid international developments in the DSS field. In South Africa this trend is also noticeable, although on a smaller scale. The object of this article is to give a survey of Decision Support Systems by defining the concept and by showing how it relates to other fields, and to present a framework of the typical functions and components of such a system. Some practical applications are discussed for illustrative purposes.