Meral Binbasioglu

Process-based reconstructive approach to model building

Abstract The role of derivational analogy approach in the model building domain is investigated. In particular, the paper focuses on enhancing decision support systems with model construction capabilities so that the prior modeling experience can be conveyed into new problem situations. The role of analogy in the model construction process is pointed out. This is followed by a discussion of the different approaches to analogical reasoning and the assessment of their suitability for model building decision support systems. The proposed approach, process analogies, is detailed as to required knowledge sources and representation schemes for problem and model description, and illustrated using examples. The reusable model pieces in the linear programming modeling domain are identified at various levels of abstraction and their impact on model base organization is pointed out. The alternative model base organization strategies are contrasted in terms of storage, search and reasoning tradeoffs.

Key features for model building decision support systems

Abstract We present a two-phased approach to automating the model building process in decision support systems (DSSs). The role of problem structuring in the model building process is stressed and is related to basic model building blocks (model types), which are in turn related to problem solving techniques developed in the artificial intelligence field. We propose the combined usage of classification and constructive problem solving methods. The classification method provides a high-level structure to the model building process since it facilitates the identification of the relevant model types. The constructive method then adapts and integrates the identified model types. Thus, the proposed approach a ultimately constructs a model corresponding to a given problem but in a deferred fashion. The advantages of this two-phased model building process are pointed out and related to the findings of cognitive studies. The proposed approach is illustrated using the programming (LP) modeling domain with examples from the production planning application domain.

Knowledge-based management support: an application to the IS change agent role problem

Abstract This paper explores how the change agent role problem can be detected and alleviated with the help of a knowledge-based support tool. The mismatch between MIS specialist change agent role style and IS environment is a complex problem to solve. The problem results when the MIS specialists role outlines responsibilities that cannot possibly manage the change and related uncertainty surrounding an IS initiative. MIS specialists are classified by change agent roles that reflect varying types of responsibility for social and technological change. Evaluation of IS environment constructs provide the MIS specialist with a formal way to compare the different IS change agent roles to moderate IS uncertainty, thereby increasing the likelihood of IS success. The relevant IS change agentry relationships are identified from a literature review. Results from a multiple case study were used to develop and validate a conceptual model of the IS change agentry application domain. Based on this model, a suitable knowledge representation scheme is developed that provides a high level structure to the IS change agent role application domain and also guides the reasoning process. The proposed approach supports the interpretation of domain relationships applicable when choosing among change agent roles. Therefore, it could be used by IS specialists proactively to facilitate the analysis of complex domain facts prior to committing resources to a change agent role. The approach is illustrated with case data. Managerial implications of the study are discussed.

A system for supporting organizations in knowledge-based document preparation

An overview of a knowledge-based document preparation system, REGENT (report generation tool), is presented. REGENT is a software environment which generates documents from reusable document pieces by planning, executing, and monitoring the document preparation process in an organizational setting. The organizational aspects of the document generation process are incorporated in the system architecture. The documents are constructed from stored document pieces using artificial intelligence methods. The report preparation process is detailed as to the knowledge representation structure and the problem solving strategy.<<ETX>>

Knowledge-based IS implementation support: an application to the IS change agent role problem

The threat of abandoned or extensively overhauled IS is a major concern for both MIS specialists and businesses. This concern may stem from the mismatch between MIS specialist change agent role and IS environment, and is a complex problem to solve. The problem results when the MIS specialists role outlines responsibilities that cannot possibly manage the state of uncertainty surrounding the IS initiative. This paper explores how the change agent role problem can be detected and alleviated with the help of a knowledge-based diagnostic support tool. A conceptual model of the IS change agentry application domain is developed to capture the interactions among IS implementation factors. This knowledge representation scheme guides the reasoning process. The proposed approach could be used by MIS specialists proactively to facilitate the analysis of complex domain facts prior to committing resources to a change agent role. The approach is illustrated with case data. Managerial implications of the study are discussed.