Classification of Decision Support Systems: Data-, Model-, Knowledge-, Document- and Communication-Driven Approaches

Abstract

Decision Support Systems (DSS) are computer-based systems designed to support individuals and organizations in making effective decisions by analyzing data, models, and relevant information. As organizations increasingly depend on large volumes of structured and unstructured data, decision-making has become more complex and requires systematic technological support. Decision Support Systems provide analytical capabilities that help users understand information, compare alternatives, evaluate possible outcomes, and select appropriate courses of action. DSS can be classified based on the type of support they provide, the nature of the information used, the interaction between users and the system, and the analytical techniques applied. Common classifications include data-driven, model-driven, knowledge-driven, document-driven, and communication-driven decision support systems. Each category focuses on different aspects of decision-making and is suitable for different organizational requirements. Data-driven systems primarily analyze large datasets, while model-driven systems use mathematical and analytical models to evaluate alternatives. Knowledge-driven systems provide recommendations using stored knowledge and rules, whereas document-driven systems support decisions through document retrieval and analysis. Communication-driven systems facilitate collaborative decision-making among multiple users. This paper presents an overview of decision support systems and explains their major classifications, characteristics, applications, advantages, limitations, and future scope. Understanding the classification of DSS helps organizations select suitable decision-support technologies according to their specific requirements. The study also highlights the role of modern technologies such as artificial intelligence, machine learning, cloud computing, and big data analytics in improving the capabilities of decision support systems.