Manufacturing firms face a paradigm shift from industrial systems driven by efficiency to post-industrial systems where success depends on a quick-response to customer demands for a variety of high-quality products. In essence, time is becoming a critical dimension for competition. New information technologies allow many firms to pursue time-based competitive strategies. The purpose of this research is to investigate the relationship among the types of information technology, behaviors of suppliers, the structures of new product development processes, and the competitiveness of the firms. The data for this study were collected from 96 Korean manufacturing firms that have implemented certain types of information technologies. Research results from LISREL analysis confirm that the competitiveness comes from product innovation capabilities and innovative product development process. But the linkage between the information technologies and the firms' competitiveness proves to be indirect. Suppliers, organizational culture related to IT, and some other factors also have indirect impact on the competitiveness. A summarized report of other findings is provided as well.

CRM is at the core of any customer-focused business strategy and includes the people, processes, and technology questions associated with marketing, sales, and service. In today's hyper-competitive world, organizations looking to implement successful CRM strategies need to focus on a common view of the customer using integrated information systems and contact center implementations that allow the customer to communicate via any desired communication channel. A CRM solution contains a number of sophisticated tools that enable to extract detailed information about customers. This information can be used to gain a better understanding of customers. From this we can determine trends, and so refine business toward customers' needs and target new products to particular customer groups. This paper presents an approach for forming the product-customer groups using neural networks for customer relationship management. The Carpenter-Grossberg's neural network, which has been used for manufacturing cell formation in group technology, is modified and applied for product-customer group formation. As a result of numerical experiments, it is also useful for more complex problems in which customers have different preferences for each product.

Recently, as information and communication technology is swiftly developed, consumers feel more convenient in making use of as well as access to the banking service. This change must affect consumer's benefit, however, there are rare previous studies and methods for measuring it. Thus, we utilize hedonic price technique to estimate consumer's benefit of electronic banking information. The results indicate that the price elasticity of consumer's communication service expenditure regarding the use of electronic banking information is about 0.057%. That is, users have willingness to pay 57 Won more than current communication fee for acquiring the additional electronic banking information.

In this study, we tried to find the factors that influenced appraisal and reward satisfaction in knowledge management, and to observe whether appraisal and reward satisfaction were related to employees' commitment to knowledge management. Analyzing valid 38 data in the organizational level, we found that only result validity and reward justness affected employee appraisal and reward satisfaction. Also, if was found that appraisal and reward satisfaction were related to employees' commitment to knowledge management. The implications of the findings and future research directions were discussed.

This study investigates the reliability and validity of research instruments used in Korean MIS research. Examination of reliability and validity is a necessary process for establishing proper arguments based on research results. We examined 172 MIS research articles published in four major Korean journals between 1990 and 1999. Among them, 79 papers which used multivariate research methods were analyzed in this study. The relationships between reliability measures and several research design characteristics were examined. We found that scale format and the number of items used to measure a construct were significantly correlated with reliability measure. About 27 percent of the articles we examined did not perform validity analysis. Based on the findings in our study, we proposed a checklist for presenting data validation analysis.

The prediction of stock price index is a very difficult problem because of the complexity of stock market data. It has been studied by a number of researchers since they strongly affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network(BPN). Finally, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

We propose utilizing a fuzzy cognitive map(FCM) to integrate tacit knowledge and explicit knowledge both of which are crucial to the success of knowledge management. Recently, explicit knowledge is getting more available as CRM and data mining approaches become popular as the advent of using database and the Internet technology. However, for the knowledge management to be successful, tacit knowledge should be seamlessly integrated with explicit knowledge seamlessly. The problem hindering such effort is how to find a vehicle facilitating transformation of explicit knowledge into tacit knowledge, and vice versa. FCM has been important method for representing tacit knowledge as a form of explict knowledge. In this respect, we suggest the detailed process about how to integrate explicit knowledge and tacit knowledge by using FCM. We gathered extensive set of data from the credit card company, and applied our proposed method. Results showed that our approach is robust and promising for the field of integrating two different kinds of knowledge.

Internet business is transforming the current structure and way of shopping behaviors. As a frontier area of internet business, internet shopping mall industry is influenced by this trend. In this shopping situation, shopping objects and information on the object are separated, which makes consumers to decide on the contents and marketing function offered by the shopping mall. This study proposes an integrated model including the influencing factors on customer royalty in Internet shopping environments. Eight hypotheses are proposed based on previous research in Internet marketing and information systems. The results are quite supporting the model and hypotheses. The contents structure, marketing activities, and customer satisfaction in the internet shopping environment influence shopping experience, next purchases and reference to other people. The proposed model and empirical results would contribute to setting up strategy of Internet shopping mall industry, and also to future research in information systems and Internet marketing.

This study identified CSFs(Critical Success Factors) for successful ERP system implementation in small and medium firms, and empirically tested relationship between CSFs and user performance. Survey questionnaires were distributed via email & fax to 142 firms that have implemented ERP systems. Out of 52 responded questionnaires, 46 data sets were available for statistical analysis with SPSSWin8.0. CEO's participation, vendor support & service, securing human resources, effective use of software, and hardware capacity were identified as CSFs from factor analysis. Among those factors, vendor support & service and effective use of software were related to user performance, and the relationship was shown to be statistically significant. Study results also showed that user performance of ERP system was significantly different among those surveyed firms when ERP system package products were used as a simple proxy measure of independent variable.

Though people frequently rely on intuition in managing activities, they rarely use it in developing effective decision-making support systems. In this report, we investigate the correlations between characteristics of cognition and emotion and judgmental time-series forecasting accuracy, and compare their strengths by using a self-supervised adaptive neural network. Through the experiments, we hope to help find a desirable atmosphere for decision-making. Our experiments showed that both cognition characteristics and emotion characteristics had correlations with the time-series forecasting accuracy, and that cognition characteristics had larger correlation than emotion characteristics. We also found that conceptual style had larger correlation than behavioral or analytical styles with the accuracy.