One of the fundamental roles of web object navigation is to support what the user wants precisely and efficiently from the enormous web database to the web browser. As long as the web search results are a set of individual lists, it is all right to display each and every web result for the web browser to display a web object one by one. However, in case the search results are a collection of multiple interrelated web objects, then there is a need to represent for a new mechanism for linked web objects at a time. We define a unit of web objects derived from a Steiner tree where the web objects include a set of specific keywords calculated by the weight from which the solutions are extracted. Even if a web object does not include all the keywords, then the related hypertext linked web objects are derived and displayed onto the mobile web browser with meta data in one shot. In this paper, it is applied for the mobile browser that the web contents can dynamically be displayed with Steiner trees until each renewal of the navigation request may be issued. In this paper, a new synchronized mobile browsing method is developed so that the navigating time can drastically be reduced and the web navigating efficiency can be dramatically enhanced without sacrificing memory consumption.

In this paper, we develop a new conceptual framework for finding new business opportunities in the cloud computing environment. We propose a service model framework for cloud computing business. In the service concept of the proposed business model, we categorize customer needs and service offering value, while we analyze customer behavior for developing revenue model. In addition, we analyze cloud computing market drivers for finding an evolution path of the proposed business model. Finally, we develop cloud computing business strategies for Korean IT service industry.

The mobile industry is the key foundation of digital convergence, and its constant growth is expected. Among mobile industries, new products leading the development of devices are the Emerging Device. This study is conducted to find out factors making differentiated by comparing the structural equation model(SEM) of the Tablet PC and the e-Book Reader. The main findings are as follows. First, the application of TAM to the Emerging Device shows that fitness of the model is generally high but the effect of Perceived Ease of Use has not been verified or found insignificant. Second, the acceptance model of the Tablet PC and the e-Book Reader has found that playfulness stimulates acceptance intentions. Third, the cost level of the Emerging Device acceptance model is not a factor stimulating consumers' acceptance intentions. Fourth, product attributes of the Tablet PC and the e-Book Reader to differentiate themselves from the other device are Functionality and Playfulness respectively.

The basic objective of broadcast scheduling is to get the smallest length TDMA frame, where many nodes are allowed to transmit simultaneously in a single time slot in a conflict-free manner. The secondary objective is to maximize the number of such transmissions for maximum use of the channel. An Artificial Bee Colony (ABC) with ranking strategy is proposed in this paper for the broadcast scheduling problem. Our proposed method is very efficient for generating initial and neighbor feasible solutions. We can get the best number of time slots and transmission utilization comparing to previous researches.

Time series analysis methods have been traditionally used in stock price prediction. However, most of the existing methods represent some methodological limitations in reflecting influence from external factors that affect the fluctuation of stock prices, such as oil prices, exchange rates, money interest rates, and the stock price indexes of other countries. To overcome the limitations, we propose a network based method incorporating the relations between the individual company stock prices and the external factors by using a graph-based semi-supervised learning algorithm. For verifying the significance of the proposed method, it was applied to the prediction problems of company stock prices listed in the KOSPI from January 2007 to August 2008.

Not only the preference data but also the similarity data can be used for developing effective marketing strategies. Hahn et al.[10] proposes a methodology of representing a brand(focal brand)'s competitors in a single map called the Preference-Similarity Map, according to their relative preference to and similarity with the focal brand. They also proposes a way to derive the relative preference and similarity values from the survey collecting the choice data from differing choice sets. This study identifies the limitations of the preference and similarity measures proposed by Hahn et al.[10] and shows how these measures can be revised. This study also proposes how to implement the revised measures and analyze brands' positioning strategies. Based on the results of the previous studies on the effect of inter brand similarity on brand evaluations, this study assumes that it is important to analyze how much a specific brand is preferred to its close competitors when evaluating the effectiveness of the brand's positioning in the market. This study applies the proposed measures to the data used in Hahn et al.[10] and also show how the proposed measures are related to the parameters of the choice model proposed by Batsell and Polking[1].

In B2B e-Commerce market, many companies used in B2B e-Commerce Guarantee Service. Guarantee service raised the stability of collect debts for seller, and made purchase fund for buyer. In 2001, The first year of implementation, B2B e-Commerce Guarantee Cost was just a 19 billion, but in 2008 was significantly increased a 3 trillion 982 billion. In previous studies, however, there was no research on performance management. This study focus on design of KPI weighting for measuring performance of B2B e-Commerce Guarantee Intermediary Service. Through analysis for 'B2B e-Commerce Guarantee Intermediary Service', the study selected KPI and made the KPI weighing. the process of designing a KPI weighting is 5 phase. This study suggests the standard of measuring performance and guidelines on the focus management of KPI in B2B e-Commerce Guarantee Service.

Among various types of creativity, team creativity has been always receiving attention from both practitioners and researchers because most of works are done in a team format in organizations. Therefore, it would be the best way for corporate performance to increase when team creativity is managed carefully to increase in a steadfast way. Though there are lots of ways to grow team creativity, this study explores the issue of increasing the team creativity by adopting CMC (computer-mediated communication) and exploration and exploitation, which were studied separately, but never analyzed together in the same research framework. Experiments to prove the validity of the research questions are based on ABM (Agent-Based Modeling) simulation. Netlogo language was adopted to build a prototype engine for the simulation engine. Experiment results revealed that in the short-term, both broad CMC mode with high exploration and exploitation, and local CMC mode with high exploration and exploitation result in higher team creativity than other types of combination. However, in the long run, broad CMC mode yields higher team creativity level than local CMC mode.

The automated teller machine (ATM) is developed as a system to provide customers with an easy deposit and withdrawal of their money without time restriction and be served for 24 hours. Today, ATM is come up to the level of an unmanned branch. The automatic financing system is developed as an essential one for dealing with the rationalization of management and the globalization of financing in order to improve the efficiency of financial management work and increase the customer service quality. With reducing the operational cost of financial organizations through the efficient maintenance operation of ATM and increasing the service quality through the maximization of its processing efficiency, this study is to draw the scheme to ensure the competitiveness among the finance companies. The importance of ATM is highly recognized as the utilization of ATM is increased and the processing function is extended, but ATM is quite vulnerable to the malfunction occurred during the nighttime after banking hours. The ATM maintenance is done through consignment to the specialized maintenance company. The efficient operation of ATM maintenance work is important to the satisfaction of customer using ATM in the nighttime.

In the Multi-Echelon maintenance environment, METRIC(Multi-Echelon Technique for Repairable Item Control) has been used in several different inventory level selection models, such as MOD-METRIC, Vari-METRIC, and Dyna- ETRIC. While this model's logic is easy to be implemented, a critical assumption of infinite maintenance capacity would deteriorate actual values, especially Expected Back Order(EBO)s for each item. To improve the accuracy of EBO, we develop two models using simulation and queueing theory that calculates EBO considering finite capacity. The result of our numerical example shows that the expected backorder from our model is much closer to the true value than the one from Vari-METRIC. The queueing model is preferable to the simulation model regarding the computational time.

There is no doubt Six Sigma is an excellent concept to improve quality of product or service. However, limitations to Six Sigma's implementation process have been discovered that are related to Six Sigma's foundation in statistical methods. The limitations of Six Sigma are overcome by the advantages of a strategic CoP (Community of Practice). Therefore, this research tries to build a strategic CoP for implementing Six Sigma. The method for building a strategic CoP is suggested, and then a case study of a real company is presented.

This study concerns with an applicability of the management science approach to the score adjustment among the College Scholastic Aptitude Test(CSAT) optional subjects. A linear programming model is developed to minimize the sum of score distortions between optional subjects. Based on the analysis of the 377,089 CSAT(2010) applicants' performances in social science test section, this study proposes a new approach for the score equating or linking method of the educational measurement theory. This study makes up for the weak points in the previous linear programming model. First, the model utilize the standard score which we can get. Second, the model includes a goal programming concept which minimizes the gap between the adjusting goal and the result of the adjustment. Third, the objective function of the linear programing is the weighted sum of the score distortion and the number of applicants. Fourth, the model is applied to the score adjustment problem for the whole 11 optional subjects of the social science test section. The suggested linear programming model is a generalization of the multi-tests linking problem. So, the approach is consistent with the measurement theory for the two tests and can be applied to the optional three or more tests which do not have a common anchor test or a common anchor group. The college admission decision with CSAT score can be improved by using the suggested linear programming model.

The theory of random utility maximization (RUM) defines the probability of an alternative being chosen as the probability of its utility being perceived as higher than those of all the other competing alternatives in the choice set (Marschak 1960). According to this theory, consumers perceive the utility of an alternative not as a constant but as a probability distribution. Over the last two decades, there have been an increasing number of studies on the effect of utility variance on choice probability. The common result of the previous studies is that as the utility variance increases, the effect of the mean value of the utility (the deterministic component of the utility) on choice probability is reduced. This study provides a theoretical investigation on the effect of utility variance on choice probability without any assumptions on the specific forms of probability distributions. This study suggests that without assumptions of the probability distribution functions, firms cannot apply the marketing strategy of maximizing choice probability (or market share), but can only adopt the strategy of maximizing the minimum or maximum value of the expected choice probability. This study applies the Chebyshef inequality and shows how the changes in utility variances affect the maximum of minimum of choice probabilities and provides managerial implications.