Many industries have deployed expert systems (ESs) to provide support for solving complicated and specialized problems since 1980. Because ESs are originally designed for generating feasible alternatives in an automated manner, users, especially decision makers, expect ESs to make decisions proactively and intelligently by automatically detecting users' contextual data. In other words, decision makers require decision support systems (DSSs) to be reinforced with proactive and intelligent ESs that can utilize contextual data. Meanwhile, ubiquitous technology-based applications currently only provide limited personalization services that use the user's context and preferences; in other words, these systems do not fully make use of sophisticated decision making capabilities. Hence, this paper describes how decision making and context-aware computing are jointly used to establish ubiquitous computing technology-based applications. To do so, we propose an amended DSS paradigm, Context-Knowledge-Dialogue-Data-Model (CKDDM). This model describes what may be considered for future DSSs when we regard ubiquitous computing technology as an inevitable effect that changes how decision making decisions are described. Under the CKDDM paradigm, a framework of ubiquitous decision support systems (ubiDSS) is addressed with the description of the subsystems within. To show the feasibility of ubiDSS, a prototype system, Context-Aware Multi Agent System-My Optimization (CAMA-myOpt) has been implemented as an illustrative example system.