The objective of this paper is to develop a new priority setting algorithm that considers the cross-impact of the future technology alternatives and that satisfies the final goal of the technology management through multi-hierarchy evaluation criteria. By combining the Analytic Hierarchy Process (AHP) model, which is a well-known priority setting model, and Cross Impact Analysis (CIA) model, which is a technological forecasting method that considers cross-impact among R&D Items, we developed an Integrated Cross-Impact Hierarchical (CIH) model, which sets the priority by considering technological forecasting and technology dependency simultaneously. A step-by-step numerical example of the model developed here is presented as backup of its practicality.

This paper examines the effect of the producer-supplier quality contract parameters and the magnitude of the quality related variables on the quality of the final products. Our analysis focuses on the parties' equilibrium behavior In a quality game environment where the supplier should choose among the two production technologies, one requiring high cost but producing high quality Parts and the other requiring low cost but producing low quality parts and where the producer should decide whether to do the inspection of the parts. The game framework is employed to depict the potential conflicts existing between the Producer and the supplier because the Producer can not observe the supplier's choice and each party wants the other to bear the cost of producing high quality products. In our model, we specifically consider the competitive situation where the producer competes with a firm producing the same product. We employ the market share attraction model to Incorporate the competitive situation and completely characterize the equilibrium by using the Nash equilibrium concept for the game solution. Our results show that the equilibrium depends on the contract terms and the magnitude of the quality related variables. Compared to the non-competitive situation, the probability of producer's Inspection and the probability of supplier's choosing the high quality technology increases in a competitive situation. This is true even when the competitor's quality is lower than the producer's lowest. As a result, the quality of the final product increases In a competitive situation. And as the failure cost borne by the supplier increases, the probability of choosing the high quality technology Increases and the probability of inspection decreases. The net effect of this results in the decrease of the final product quality.

A fully connected Artificial Neural Network (ANN) contains many connections. Compared to the pruned ANN with fewer connections, the fully connected ANN takes longer time to produce solutions end may not provide appropriate solutions to new unseen date. Therefore, by reducing the sloe of ANN, we can overcome the overfitting problem and increase the computing speed. In this research, we reduced the size of ANN by destroying the connections. In other words, we investigated the performance change of the reduced ANN by systematically destroying the connections. Then we found the acceptable level of connection-destruction on which the resulting ANN Performs as well as the original fully connected ANN. In the previous researches on the sloe reduction of ANN, the reduced ANN had to be retrained every time some connections were eliminated. Therefore, It tool lolly time to obtain the reduced ANN. In this research, however, we provide the acceptable level of connection-destruction according to the size of the fully connected ANN. Therefore, by applying the acceptable level of connection-destruction to the fully connected ANN without any retraining, the reduced ANN can be obtained efficiently.

The launch of a new business is crucial to the future growth and profitability of a company. A new business project typically requires a large amount of resources while it has a high possibility of failure. The evaluation of new business opportunities is therefore quite a critical decision-making to companies. This evaluation includes screening of a large number of criteria at a time which often makes desision-making very complicated. Management should evaluate the business alternatives in a sound and consistent manner that is hard to achieve because the new business evaluation is a typical semi/unstructured decision-making problem. The difficulty in such an evaluation will increase if it is required for management to consider both quantitative and qualitative criteria simultaneously. Under these circumstances, this study has proposed a decision-making framework that utilizes analytical hierarchy process(AHP). This study has identified a set of criteria essential to the new business evaluation and suggested a systematic framework for it. Both qualitative and quantitative evaluations are incorporated into the single framework in this study.

The development of Information technologies huts contributed on-line training as one of important education methods. On-line training In firms, which is similar to e-learning or virtual education, provides trainees with more education opportunities in diverse ways. It has developed a range of innovative services with an one-stop solution of education within the electronic sector. Also under the on-line training environment, trainees can undertake customized training packages at anytime and any places. Moreover, information technology allows both the trainers and other trainees to be decoupled in any of the elements of time, place, and space. Two research questions are investigated : what are the determinants affecting the on-line training effectiveness and how those variables effect the two aspects of training effectiveness: learning performance and transfer performance. Based on the previous literature conducted on the traditional training environment, the determinants of training effectiveness are derived. light hypotheses are developed based on literature reviews and tested by questionnaires survey data. The collected data have been analyzed by LISREL. It is found that the relationship between individual, organizational and on-line sloe design variables and training effectiveness (learning and transfer) are significant. The contribution and limitations of this research are also discussed tilth future studies.

The tilde use of Information Technology (IT), especially the rapid diffusion of the internet, brings us a new paradigm, called "Electronic Commerce," or "Digital Economy." The paradigm is regarded as a business strategy essential to organizations′competitive advantages. Because few studies have been shown in the area of e-strategies, especially in the combined strategies of clicks and mortars, a study of this area is required. The main questions of this study are empirically to validate the usefulness and applicability of a decision roadmap and to analyze the situation of Korean firms in the view of the decision roadmap. Major results of this study are as follows : First, there is an evidence that the roadmap can be applied to Korean firms regardless of their industry and size. Second, the usefulness of the roadmap is proved because companies following the directions of the roadmap show high degree of satisfaction with online sales. Third, Korean companies in general do not achieve an Ideal Integration (or separation), especially In terms of management and operation. In conclusion, this study provides an e-business strategy Planner some guidelines about how to achieve right mix of on-line and off-line business.

The ever-glowing demands for more responsiveness and more flexibility in manufacturing generate greater expectation for the AGV system. So far. a significant amount of research has been carried out to fulfill those requirements. However, the dynamic characteristics of manufacturing systems make it hard to solve the problem analytically. In this paper, the AGV system is analyzed in the production environments which adopt a cycle time to produce materials. The use of the cycle time could eliminate much of uncertainty Inherent In the manufacturing process so that it is possible to build the deterministic model for the AGV systems, which eventually Produce better results on the important issues such as AGV dispatching, determination of the number of AGVs, and empty vehicle travel time.