Data Mining - Concepts and Techniques.

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

The aim of this research essay is to examine the structural nature of theory in Information Systems. Despite the importance of theory, questions relating to its form and structure are neglected in comparison with questions relating to epistemology. The essay addresses issues of causality, explanation, prediction, and generalization that underlie an understanding of theory. A taxonomy is proposed that classifies information systems theories with respect to the manner in which four central goals are addressed: analysis, explanation, prediction, and prescription. Five interrelated types of theory are distinguished: (1) theory for analyzing, (2) theory for explaining, (3) theory for predicting, (4) theory for explaining and predicting, and (5) theory for design and action. Examples illustrate the nature of each theory type. The applicability of the taxonomy is demonstrated by classifying a sample of journal articles. The paper contributes by showing that multiple views of theory exist and by exposing the assumptions underlying different viewpoints. In addition, it is suggested that the type of theory under development can influence the choice of an epistemological approach. Support is given for the legitimacy and value of each theory type. The building of integrated bodies of theory that encompass all theory types is advocated.

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The nature of theory in information systems

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Handbook on Decision Support Systems 1

Conducting a safe and successful major event highly depends on the effective provision of medical emergency services that are often offered by different public and private agencies. Poor communication and coordination between these agencies and teams can result in delays in decision-making and duplication of efforts. Another related issue is that emergency decisions are usually made based on individual experience and domain knowledge of relevant managerial personnel. For sustainable knowledge management and more intelligent decision support it is beneficial to collect, consolidate, store and share these experiences in a form of a knowledge base or domain ontology. State-of-the-art surveys identify this gap that there is no common ontology describing the domain knowledge for planning and managing medical services in mass gatherings. Part of the reason is that the process of construction of such an ontology is not a trivial task. In this paper, we describe the process of developing and evaluating a Domain Ontology for Mass Gatherings (DO4MG) with a focus on medical emergency management. As part of the evaluation, we illustrate the application of DO4MG for implementing a case-based reasoning decision support for emergency medical management in mass gatherings. Such an implementation demonstrates the potential of using ontology for resolving terminology inconsistencies and their usefulness for supporting communication between medical emergency personnel in mass gatherings. We also illustrate how this ontology can be applied to different stages of medical emergency management as part of a system architecture. The lessons learnt from building DO4MG for this domain could be beneficial in general to the theory and practice of intelligent decision support and knowledge management in complex problem domains. Highlights? We describe how to improve medical emergency decision-making applying ontology. ? Systematic method for development and evaluation of such an ontology is described. ? Intelligent decision support system architecture incorporating ontology is proposed.

Development and evaluation of ontology for intelligent decision support in medical emergency management for mass gatherings

This paper is concerned with a type of information systems research that is comparatively poorly understood – the "systems development" (SD) or "engineering" approach. SD is seen as a natural intermediate step linking basic and applied research and as a form of action research. It is argued that we can learn from the view of SD research as action research and thus develop useful criteria for the conduct and evaluation of SD research. An illustration is given of the application of these criteria to an example of SD research in information systems. This illustration demonstrates the importance of recognizing the SD approach and relevant criteria for guiding and evaluating the validity and worth of such work.Presented at: 10th Australasian Conference on Information Systems; 1999 Dec 1-3; Wellington, New Zealand. p. 122-134.

Frada Burstein

Papers

Handbook on Decision Support Systems 1

Development and evaluation of ontology for intelligent decision support in medical emergency management for mass gatherings

The systems development or engineering approach to research in information systems: an action research perspective

Combining data mining and case-based reasoning for intelligent decision support for pathology ordering by general practitioners

Australian Journal of Information Systems