What Are the Characteristics of Decision Support Systems?

Decision Support System is a computer-based information system used to support business or organizational decision-making activities. DSS serves organizational management, operations, and planning management (usually middle and senior management) and helps people make decisions about issues that can change quickly and that are not easy to predict. Decision support systems can be fully computerized, human-driven, or a combination of both.

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The concept of decision support comes from the late 1950s and early 1960s

The decision-making process is generally divided into 4 steps:

(1) Finding problems and forming decision-making goals, including establishing decision-making models, drawing up plans, and determining effectiveness measures, which are the starting points of decision-making activities;

(2) Quantitatively describe the possibility of various outcomes produced by each scheme with probability;

(3) Decision makers make quantitative evaluations of various outcomes, and generally use the utility value to quantify. Utility value is a quantitative estimate of the value of various outcomes by relevant decision makers based on factors such as personal talents, experience, style, and environmental conditions;

(4) Comprehensive analysis of all aspects of information to determine the final choice of the program, and sometimes sensitivity analysis of the program, to study the impact of the optimal solution when the original data changes, to determine the parameter range that has a greater impact on the program.

Decisions are often impossible to complete all at once, but rather an iterative process. Decision-making can be accomplished with the help of a computer decision-support system, that is, using computers to assist in the determination of goals, formulation of plans, analysis and evaluation, and simulation verification. In this process, human-computer interaction can be used, and decision makers provide parameters for various schemes and select schemes.

The basic structure of the decision support system is mainly composed of four parts, namely the data part, the model part, the inference part and the human-computer interaction part:

The data part is a database system;

The model part includes the model library (MB) and its management system (MBMS);

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Like other systems, decision support systems require a structured approach. This framework includes people, technology and development methods.

Theoretically, DSS can be established in any knowledge field. The main practical applications are as follows:

(1) Clinical decision support system for medical diagnosis. The development of the clinical decision support system (CDSS) has four stages: the original version is independent and does not support integration; the second generation supports integration with other medical systems; the third is based on standards and the fourth is based on a service model of.

(2) DSS is widely used in business and management. The software allows faster decisions, identifies negative trends, and better allocates business resources. All the information of the organization is summarized in the form of charts and graphs, which helps management to make strategic decisions. For example, one application of DSS is the management and development of complex counter-terrorism systems.

(3) Application in agricultural production and sustainable development marketing. For example, funding backed by development through the United States Agency for International Development in the 1980s and 1990s has allowed rapid assessments of several agricultural production systems around the world to facilitate farm- and policy-level decisions. Precision agriculture aims to customize decisions for specific parts of the farm. However, the successful adoption of DSS in agriculture has many limitations.

(4) Application in forest management, in which long-term planning issues require specific requirements. All aspects of forest management, from log shipping, felling scheduling to sustainability and ecosystem protection, have been addressed by modern DSS. In this regard, consider one or more management objectives related to the provision of traded or non-traded goods and services, and are often affected by resource constraints and decision-making issues.

(5) Applied to railway supervision. One specific example involves the Canadian National Railways system, which uses a decision support system to regularly test railway equipment. Problems with any railway (wear or defective tracks) can cause trains to derail hundreds of times a year. With DSS, the Canadian National Rail System has managed to reduce the incidence of derailment.

(5) Application in snowmelt flood warning. The DSS system assists monitoring and analysis to provide early warning of possible disasters from snowmelt floods. ^[4]