Many organizations have been attempting to build a conceptual framework for managing technology, with varying degrees of success. Most begin by consulting leading technology authorities, borrowing elements of their thinking, and adapting these elements to their organizational and personal situations. This dissertation extends this process by using the formal research methodology of multiple perspectives (technical, organizational, personal, and cross-cuing) to build a case-based model of the technology integration process. The research and the model construction benefits from a solid foundation established through a review of technology management and knowledge systems literature. The significant aspects of the research are tied to its objectives which can be divided into academic and industrial classifications: Academic Objectives: 1. Use multiple perspectives in real-time (for input to decisions as events unfold) 2. Focus on a multiple perspectives view of technology integration into an organization Industrial Objectives: 1. Improve project effectiveness by increasing understanding of the technology integration process 2. Establish a model for the integration of a new technology into an organization The development of the case-based model was the primary objective, with the other objectives providing the methodology and subject-matter content to support model development. These four objectives are of interest to three parties: scholars who are interested in the theoretical and methodological aspects of technology integration and inquiring systems, technology developers in general who can benefit from improved means to integrate technology and analyze success/failure, and technology developers in information systems organizations who can obtain specific insight as well as utilize the general industrial results. From the multiple perspectives investigation, thirteen conclusions were reached about the process of integrating knowledge systems into an information systems organization. These conclusions are specific to the case study, but may have general applicability. The multiple perspectives methodology is then presented as the foundation for a technology integration model, on which the technology usage phases of awareness, motivation, and functioning capability can be completed. The model is described and then illustrated with two knowledge systems development project cases. With regards to the research objectives, it is concluded that: 1. The use of multiple perspectives in real-time are difficult and requires practice 2. Because technology integration is dependent upon technical, organization, and personal factors, the use of multiple perspectives are appropriate and useful. Eight of 13 conclusions were dependent upon the cross-cuing process 3. Multiple perspective analysis improved the understanding of the technology integration process. This understanding was sometimes helpful and sometimes harmful to the effectiveness of the integration process 4. The proposed technology integration model, using the awareness, motivation, and functioning capability phases, was developed and exercised. This model proved useful in limited application Finally, a method for organizing and navigating the perspectives, cross-cuing, and conclusions is presented and used.

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science. Johannesburg 1990. / No abstract provided.

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This dissertation introduces a novel validation method for knowledge-based systems (KBS). Validation is an essential phase in the development lifecycle of knowledge-based systems. Validation ensures that the system is valid, reliable and that it reflects the knowledge of the expert and meets the specifications. Although many validation methods have been introduced for knowledge-based systems, there is still a need for an incremental validation method based on a lifecycle model. Lifecycle models provide a general framework for the developer and a mapping technique from the system into the validation process. They support reusability, modularity and offer guidelines for knowledge engineers to achieve high quality systems. CommonKADS is a set of models that helps to represent and analyze knowledge-based systems. It offers a de facto standard for building knowledge-based systems. Additionally, CommonKADS is a knowledge representation-independent model. It has powerful models that can represent many domains. Defining an incremental validation method based on a conceptual lifecycle model (such as CommonKADS) has a number of advantages such as reducing time and effort, ease of implementation when having a template to follow, well-structured design, and better tracking of errors when they occur. Moreover, the validation method introduced in this dissertation is based on case testing and selecting an appropriate set of test cases to validate the system. The validation method defined makes use of results of prior test cases in an incremental validation procedure. This facilitates defining a minimal set of test cases that provides complete and effective system coverage. CommonKADS doesn’t define validation, verification or testing in any of its models. This research seeks to establish a direct relation between validation and lifecycle models, and introduces a validation method for KBS embedded into CommonKADS

Application of artificial intelligence (Al) has been a topic of interest among researchers for the past decade or more. Years of research in the commercial application of Al, availability of hardware support for Al application and affordability of software and hardware has generated a lot of interest in this field and brought this technology within the reach of micro-computer based users. The commercial impact of AI is due to expert systems (ESs). ES technology is a collection of methods and techniques for constructing human-machine systems with specialized problem solving expertise. This project explores the application of ESs in landscape architecture by developing a prototype ES and testing implications of its use with designers while working on a hypothetical problem in a studio environment. The development process helps identify the typical difficulties of such an application, to uncover technical problems, and to identify areas needing further research. The project aims at building an ES that provides very limited preliminary data and design guidelines to initialize the design process and keeps track of the most fundamental issues necessary for planning, thus acting as an expert and assistant simultaneously. The idea is to explore the possibility of applying ESs to facilitate the design process so that designers may concentrate on other important aspects of design which include intuitive judgement about qualitative aspects. / Master of Landscape Architecture

This study proposes an Architectural Expert System (AES) to act as a design partner for architectural designers. Architectural designers are faced with a very complex task of searching a solution space, which is a labyrinth of several domains ranging from social to cultural, and from aesthetic to scientific. With the number of domains come a number of experts of that domain. After progressing through tedious analytical procedures involving the physical principles in architecture, and applying the knowledge of experience, the experts are able to convert the raw data into useful design guidelines. Research in the field of artificial intelligence has developed techniques which can capture such expertise in a computer program, which then emulates the expert. This technology is know as Expert System (ES). This study has used this technology to develop a system to aid architectural design. An AES model is derived from literature review. As the nature of a system based on this model is complex and would require custom built software, an alternative is developed based on the derived model. Based on this alternative, a prototype is developed for energy audit and energy conservation by capturing the expertise of an energy conscious design expert. This prototype module is one component of the sub-system of AES and provides an example for further modules. Various areas such as design, architecture, artificial intelligence and expert systems technology, and energy conscious design and energy conservation converge, and become parts of this study. / Master of Science

This research report investigates the use of an expert system to aid project engineers at the Naval Training Systems Center in making decisions concerning the requirements of the computer systems used in simulators. For a prototype system domain, the author chose an expert system that would generate a software development cost estimate. This system questions the user about the features and options required on the training system. The expert system then analyzes the information to generate a “lines of code” estimate. A selected model will combine various factors to generate s value answer for the user. The capabilities and features of current expert system development tools are reviewed as to what features would best address this problem domain. EXSYS, a rule-based expert system shell that runs on both Zenith and IBM PCs, was selected to develop the prototype because of its capability to meet the requirements of the software cost estimation domain. The COCOMO estimation model was selected to generate the user answers. The technique of using a rule-based system in combination with other management decision tools, such as spreadsheets, holds a potential of being an excellent approach for providing a tool for storing and utilizing estimation data and heuristics.

An expert system approach to help OR naive users formulate and solve goal programs is proposed. The approach is demonstrated for single product blending problems using VP-Expert as the developmental tool. Results of a study using undergraduate and graduate business students to test the expert system effectiveness are provided. An expert system determines the problem type using a taxonomy based upon problem context. Each problem type possesses distinct characteristics. Characteristics of twenty-four different problem types are discussed. Formulation of constraints using problem characteristics is demonstrated. The expert system uses constraint information to assist users in goal selection. Goal structures are constructed using a pairwise comparison technique. Solution values, recommendations based upon sensitivity analysis, and trade-offs between conflicting goals are provided to the user. A feedback loop permitting model changes and reiteration of solution and recommendation steps is provided. / Ph. D.