Page 1Current DSS research is rather fragmentary, and typically ayopic--it centers either on the decision situation which DSS s u~w r t , or on DSS tools or generators. In this paper we adopt a comprehensive view of DSS emphasizing their svstemic nature.This entails identifying the links among the five aspects that classically characterize a system: 1, the environment, i,e., decision situations and access patterns;2. the function (within this environment), i.e., types and levels of decision support;3. the functional components that ~k e it up, i.e., dialog, data, and model management; 4. the arrangement, i .e., the linkages among the components and the assignment of functions to modules; and 5. the resources consumed, i.e., hardware, software, human skills, and data,The systeaic view provides a concrete framework for the effective design of DSS, and serves as a basis for accumulating DSS research results. The premise of the systemic view of DSS is that understanding these systems requires the simultaneous consideration of the five system aspects, i.e., environment, role, components, arrangement of components, and resources required to support the system [Churchman 681, A seaningful DSS design must explicitly link all these aspects so that characteristics of the system's environment and role will be reflected in its components and their arrangement. Center for Digital EconomyThe m e DSS implies that the objects we are discussing are indeed Center for Digital Economy Research Stem School of Business IVorking Paper IS-84-8 1 systems, y e t t h i s perspective has been l o s t i n much of the DSS l i t e r a t u r e . The purpose of t h i s paper is to present a comprehensive view of DSS, using the systemic framework as an organizing concept. No new terminology is introduced. Rather, the paper attempts t o i n t e g r a t e the disparate perspectives found i n the DSS l i t e r a t u r e i n t o a consistent and coherent body of knowledge. This integrated view indeed reveals new insights.Section 2 defines the classical aspects of a system, Sections 3 through 7 apply these definitions t o DSS, explicating the meaning of each aspect i n t h e DSS context, Section 8 examines more closely t h e relationships among the systemic aspects of DSS, p a r t i c u l a r l y the ways r o l e and environment determine components, arrangement, and resources.Finally, section 9 considers the implications of a systemic view f o r DSS design, design research, and curricula. The Aspects of a SystemThe fundamental premise of systems theory (or the systems approach) is t h a t systems, regardless of t h e i r specific context, share a conunon set of aspects or elements [Churchman 681. The systems view, however , is an abstract model, as systems exist only i n the mind of the beholder, Well designed man-made systems are constructed t o resemble t h a t view, as it provides a methodical j u s t i f i c a t i o n f o r a set of corponents and t h e i r arrangesen t . order to answer wfiy an object is structured as it is, or how it ...
The research into time and data models has so far focused on the identification of extensions to the classical relational model that would provide it with "adequate" semantic capacity to deal with time.The temporally oriented data model (TODM) presented in this paper is a result of a different approach, namely, it directly operationalizes the pervasive three-dimensional metaphor for time. One of the main results is thus the development of the notion of the data cube: a three-dimensional and inherently temporal data construct where time, objects, and attributes are the primary dimensions of stored data. TODM's cube adds historical depth to the tabular notions of data and provides a framework for storing and retrieving data within their temporal context. The basic operations in the model allow the formation of new cubic views from existing ones, or viewing data as one moves up and down in time within cubes. This paper introduces TODM, a consistent set of temporally oriented data constructs, operations, and constraints, and then presents TOSQL, a corresponding end-user's SQL-like query syntax. The model is a restricted but consistent superset of the relational model, and the query syntax incorporates temporal notions in a manner that likewise avoids penalizing users who are interested solely in the current view of data (rather than in a temporal perspective). The naturalness of the spatial reference to time and the added semantic capacity of TODM come with a price-the definitions of the cubic constructs and basic operations are relatively cumbersome. As rudimentary as it is, TODM nonetheless provides a comprehensive basis for formulating an external data model for a temporally oriented database.
Software engineering tools used by designers are critical to most systems development methodologies, and successful methodologies are critical to improved productivity. However, the way in which designers use and relate to software engineering tools, whether computer assisted or not, has received little attention in the design literature. The purpose of this study is to gain insight into how people perceive the process of using design tools. The study is a qualitative analysis of interview information from participants in a field experiment. Four teams of student designers used various design tools during the development of interactive information systems typical of those that might be developed by sophisticated endusers. The research reported here is an exploratory study aimed at understanding how designers use one of these tools, the dialogue charts. The broad range of purposes included the uses predicted by the reference literature on design. However, the end-user designers also used the tool opportunistically -they found a broader range of tool usage than the literature on design tools predicted. For example, they consistently used the tool as a communications vehicle among different phases of design and development. The results show that the relationships these 'end-user designers' developed with the target tool are expressed in highly emotional language. These attitudes are tightly coupled with the purposes for which the designers use the tool. The methodology uses a field experiment as a treatment and a semistructured interview with a hidden agenda for gathering data. h e data analysis techniques draw on the concepts of discovering grounded theory as described by Glaser and Straws. They further draw on the concepts of qualitative content analysis synthesized by Krippendodf and the qualitative data analysis methods described by Miles and Huberman.
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