China
Africa
Explore chapters and articles related to this topic
Introduction to Machine Learning and Probabilistic Graphical Models for Decision Support Systems
Published in Kim Phuc Tran, Machine Learning and Probabilistic Graphical Models for Decision Support Systems, 2023
Industry 4.0 can provide automatic solutions to different sectors such as manufacturing, healthcare, automation, supply chain management. However, there are many challenges in Industry 4.0 such as shorter product life cycles, the need for resources to design, manufacture, and quality control that decision-making processes in companies are becoming extremely complex and require more and more knowledge 3. In this context, decision-making based on the data gathered from the process of data-driven decision-making is essential. Data-driven decision-making is a technology that brings a lot of benefits to the decision-making process of enterprises. As an essential tool, Decision Support System (DSS) is designed to assist companies to support the decision-making process and making more effective decisions. A DSS is an information system that analyses data from organizations and presents it so that managers can make decisions more easily4.
CEL
Published in Noura Metawa, Mohamed Elhoseny, Aboul Ella Hassanien, M. Kabir Hassan, Expert Systems in Finance, 2019
Andino Maseleno, K. Shankar, Miftachul Huda, Marini Othman, Prayugo Khoir, Muhammad Muslihudin
The decision support system (DSS) is a system to support decision makers in solving semi-structured problems. DSS aims as a tool for decision makers to expand their abilities, but not to replace their judgments [21]–[24]. Man and Watson propose that a DSS is an interactive system that helps decision makers through the use of semi-structured and unstructured data and decision models [25]–[28]. It proposes that the types of decisions are grouped into two kinds. The first is the programmed decision, this decision is related to a known issue, and the decision making is routine and scheduled [29]–[33]. The moment the decision is not programmed, the decision is new because it deals with new problems [34]–[37].
Advanced Topics
Published in Günther Ruhe, Product Release Planning, 2010
A decision support system (DSS) is a computer-based solution used to support complex decision making and problem solving. Research in this area typically focuses on how information technology can improve the efficiency, effectiveness and transparency of the decision-making process. By analyzing the last decade of existence of these systems, within and beyond the domain of software engineering, hesitation of decision makers to trust the computer-based solutions has been analyzed. This tendency was evaluated and confirmed for ReleasePlannerTM, the decision support tool for product release planning, as well.
DSS research: a bibliometric analysis by gender
Published in Journal of Decision Systems, 2022
The Decision Support System (DSS) field came into existence more than four decades ago (Power et al., 2019) examining the role of technologies like databases, mathematical models, and visual interfaces to support and enhance managerial decision-making. Decision support systems (DSS) are computer technology solutions designed to support complex decision-making and problem-solving for individual decision-makers and workgroups or teams (Shim et al., 2002). Since its inception, DSS has attracted attention from a wide range of domains including healthcare and engineering where it has been adopted and used. Continuous improvements in technology and the availability of data have created new opportunities for DSS. Existing research has used bibliographic approaches to examine the range of disciplines encompassing DSS (Eom, 2011) and the main areas of DSS application (P. B. Keenan, 2021; Eom, 2011; Eom & Lee, 1990; P.B. Keenan, 2016).
Cognitive bias, decision styles, and risk attitudes in decision making and DSS
Published in Journal of Decision Systems, 2019
Gloria Phillips-Wren, Daniel J. Power, Manuel Mora
Analytics and decision aids such as decision support systems (DSS) are intended to improve the quality of decisions by, for example, using communications technologies, acquiring and processing data, assisting in analyzing data and documents, using quantitative models to identify and solve problems, completing decision process tasks, and guiding decision making. Traditionally, technologically-oriented decision tools have supported only part of an organizational or individual decision process due to the complexity and uncertainty inherent in semi-structured and unstructured decision tasks. The user is expected to interact with the system in some way to provide input or data, make choices about processing, interpret results, or come to a decision. In short, the system should help the decision maker think rationally. In general, these aids are underpinned by statistical, mathematical, and computer science research on problem identification and solution along with studies of human – computer interaction (for a brief history of DSS, see Shim et al., 2002). Advances in fields such as artificial intelligence, data acquisition and storage, cloud computing, virtualization, and network speed has led to the more recent fields of business intelligence, analytics, and big data.
Requirements from vehicle routing software: perspectives from literature, developers and the freight industry
Published in Transport Reviews, 2018
Nicolas Rincon-Garcia, Ben J. Waterson, Tom J. Cherrett
“Decision Support Systems (DSS) are computer technologies that can be used to support complex decision-making and problem solving” (Shim et al., 2002, p. 111). Since the 1970s, major technological breakthroughs have offered innovative solutions for vehicle planners and more recently, individual drivers. In this section, a review of CVRS capabilities and the respective technological components that support them are presented.