This paper proposes a new referential model for data retrieval as an alternative to exact matching. While exact matching is an effective data retrieval model, it is based on fairly strict assumptions and limits our capabilities in data retrieval. This study redefines data retrieval to include non-binary data retrieval in addition to binary data retrieval, proposes Double Anchor Preference Model (DAPM), and analyzes its logical charateristics. DAPM supports non-binary data retrieval. Further, it produces the same result as exact matching for the conventional binary data retrieval. These findings show that, at the logical level, the proposed DAPM retains all the desirable features for data retrieval.

This paper provides a framework for evaluating business information systems. The framework identifies three evaluation domains: IS business value, IS expenses, and IS functionality. Discussions of each category encompass what to be measured, how to measure, and how to judge the measured value. Then, the framework classifies three categories of individual information systems based on IS life cycle: industry-common, industry-similar, and firm-specific. This categorization is used to match the role of an individual system with the focus of evaluation efforts. The framework can contribute to the systematic design of evaluation programs for business information systems.

This paper proposes a synergism of neural networks (NN) and knowledge-based decision support system (KBDSS) to effectively design an intelligent strategic planning system. Since conventional KBDSS becomes inoperative partially or totally when problem deviates slightly from the expected problem-domain, a new DSS concept is needed for designing an effective strategic planning system, where strategic planning environment is usually turbulent and consistently changing. In line with this idea, this paper developes a NN-based DSS, named ConDSS, incorporating the generalization property of NN into its knowledge base. The proposed ConDSS was extensively operated in an experimentally designed environment with three models: BCG matrix, Growth/Gain matrix, and GE matrix. The results proved very promising when encountered with unforeseen situations in comparisons with conventional KBDSS.

Material Requirement Planning(MRP) has been the most widely implemented large scale production management system in the manufacturing industry. Computerization of MRP systems involves, in general, Bill Of Material(BOM) explosion algolithms which usually takes heavy computation time. In order to improve the effectiveness of the MRP systems, we propose to build a logical BOM database in advance, which reflects the Join operations for the BOM explosion. It reduces the response time for the BOM indented explosion. It reduces the MRP processing time. It also increased main memory utilization.

We presents a source module implementation system using building blocks as one of the software reusing approach. Based on module text retrieval system, system is composed of library management program and new module making program for module management. We build a software module by virtue of the reuser's customization and by applying a practical module to this model and then proved that program development through reusing approach is better than that of writing out a source code directly.

In spite of the importance that MIS researchers place in Expert Systems, there is no agreement as to whether Schools of Business should include this topic in their curriculum. To answer this question, this study presents a survey of the use and impacts of Expert Systems in Organizations. The study also assesses the impact of training on users ' perceptions and use of Expert Systems. The survey indicates that Expert Systems are being used in several areas of industry and that Business schools would serve their student body better by exposing thenm to these tools. The study also reviews the alternatizes used by IBM MoIS Grant Schools for incorporating Expert Systems in their curriculum. A discussion of the cases where each alternative would be more appropriate is included.