• Journal of the Korean Society for Railway
• /
• v.9 no.5 s.36
• /
• pp.555-560
• /
• 2006

This study finds out and suggests success factors for the application of RIMS project through the case study of Seoul Metro and literature survey. The successful application of RIMS needs expert knowledge and concept of BOM, standardization of maintenance planning, check lists of heavy maintenance inspection, organization structure of rolling stock maintenance offices, material management system of warehousing and the process of parts repairing between offices, connection of material ordering system, problem solving of circular spare parts administration among inspection, maintenance, and material organizational units, systemic serial number management of parts with RFID, daily closing diary connected with work process chart, and sufficient period of RIMS's test run. RIMS contributes to real time management of rolling stock maintenance, transparency of management, reliability of train operation, customer satisfaction, and management innovation.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2030-2032
• /
• 2001

In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock, or other economic markets. Most previous experiments used multilayer perceptrons(MLP) for stock market forecasting. The Kospi 200 Index is modeled using different neural networks and fuzzy system predictions. In this paper, a multilayer perceptron architecture, a dynamic polynomial neural network(DPNN) and a fuzzy system are used to predict the Kospi 200 index. The results of prediction is compared with the root mean squared error(RMSE) and the scatter plot. Results show that both networks can be trained to predict the index. And the fuzzy system is performing slightly better than DPNN and MLP.

• Proceedings of the Technology Innovation Conference
• /
• 2003.02a
• /
• pp.27-40
• /
• 2003

Though it has been recognized that the accumulation of technological knowledge has been the core competency to reinforce the competitiveness of individual firms and to raise the innovation capability of social and economic systems, only single or fragmentary variables, such as R&D expenditure, R&D stock, the number of researchers and the number of R&D employee have been adopted to measure the amount of technological knowledge. In this research, we use nine conventional technological knowledge measures under the conceptual structure of input-output framework to technological knowledge. Applying correlation and factor analysis, we examine the relationships among the nine proxy measures quantitatively and suggest the new approach for the calculation of technological knowledge index as a aggregated measure.

• Proceedings of the Technology Innovation Conference
• /
• 1999.12a
• /
• pp.197-215
• /
• 1999

With the advent of knowledge-based economy and information society, information and telecommunications(IT) industry is reckoned as the crucial sector for the creation and diffusion of technological knowledge. In this study, we analyze the process of 'industrialization of IT'and 'informatization of industries' based on the technology linkage structure, or technological knowledge network. The former is defined as the process whereby IT industry absorbs technological knowledge from other industries to grow as an independent industrial sector. The latter is defined as the process whereby other industries adopt IT technology to enhance productivity and upgrade industrial structure, We employ the R&D stock as a proxy for technological knowledge of respective industries and measure the flow of technological knowledge between industries in terms of I/O relationship. By applying the network analysis, we examine the changing pattern of technology linkage structure of the Korean industry throughout the years from 1983 to 1997. Some policy implications are presented based on the findings from the analysis.

• Journal of Convergence for Information Technology
• /
• v.11 no.1
• /
• pp.28-33
• /
• 2021

Since the stock price is a measure of the future value of the company, when analyzing the stock price, the company's growth potential, such as sales and profits, is considered and invested in stocks. In order to set the criteria for selecting stocks, institutional investors look at current industry trends and macroeconomic indicators, first select relevant fields that can grow, then select related companies, analyze them, set a target price, then buy, and sell when the target price is reached. Stock trading is carried out in the same way. However, general individual investors do not have any knowledge of investment, and invest in items recommended by experts or acquaintances without analysis of financial statements or growth potential of the company, which is lower in terms of return than institutional investors and foreign investors. Therefore, in this study, we propose a research method to select undervalued stocks by analyzing ROE, an indicator that considers the growth potential of a company, such as sales and profits, and predict the stock price flow of the selected stock through deep learning algorithms. This study is conducted to help with investment.

• Journal of Information Science Theory and Practice
• /
• v.3 no.3
• /
• pp.17-44
• /
• 2015

Due to the oil business, settlements in the Gulf Region developed into prosperous cities. But in the near future, oil is off. The plans of the Gulf Cooperation Council (GCC) states bank on diversified and knowledge-intensive economies. Are those development plans realistic? What is the state of the art of knowledge institutions in the GCC countries? Applying the theoretical frameworks of Knowledge City and Science Indicators research, we empirically and theoretically studied the emerging Gulf cities Kuwait City (Kuwait), Manama (Bahrain), Doha (Qatar), Abu Dhabi, Dubai, Sharjah (all UAE), and Muscat (Oman). Our methodological framework includes grounded theory, ethnographic field study, ServQual-like quantitative questionnaires and semi-standardized qualitative interviews conducted on-site with informed people, informetrics, and, finally, the use of official statistics. In particular, we describe and analyze the cities' knowledge infrastructures, their academics, and expenditure on R&D as input indicators; and publications as well as graduates as output indicators. A further crucial aspect of a knowledge society is the transition of graduates into knowledge-intensive public services and private companies.

• The Journal of Asian Finance, Economics and Business
• /
• v.6 no.3
• /
• pp.141-149
• /
• 2019

The paper proposes a knowledge innovation performance model by the dynamic data envelopment analysis with slacks-based measure approach for evaluating the effectiveness of 30 regional knowledge innovation activities in China from 2010 to 2016. In recent years, China has paid more attention to knowledge innovation activities, as central and local governments have pushed on with their innovation projects by lots of investment whatever the difficulties may be. Decision-maker is usually interested in judge its knowledge innovation performance relative to target benchmark by exploring whether one provincial administration region performs better among others and/or if the growth of economy will be benefited greatly by the knowledge innovation activities. To acquire the managerial insight about this issue from a comprehensively designed performance evaluation model, knowledge innovation activity is conceptualized as an intertemporal production process. Invention patent and regional gross product are imposed on desirable outputs, highlighting the need for knowledge economy. The empirical result shows that knowledge innovation has a positive effect on economic development. At the same time, decision-maker should be interest in the economic effect of patents' type and quality. The government should then encourage new technical applications with greater commercial value from a market-oriented perspective, in order to benefit the most from the innovation process in the short-run.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.7
• /
• pp.135-144
• /
• 2022

The relationship between applying knowledge management and accepting environmentally managed accounting is more complicated than previous studies suggested. Knowledge management is both an antecedent and a consequence of implementing environmentally managed accounting in the workplace. Nonetheless, none of the prior studies have systematically investigated this relationship. The current article attempted to scrutinize the reciprocated multifaceted tie between environmental managerial accounting and knowledge management by utilizing the methods of directed graph searches as well as directed acyclic graphs. The research data was gathered from 342 publicly-listed corporations in Vietnam's key stock markets. The empirical findings disclose that implementing knowledge management can lead to adopting environmental managerial accounting in business, which is, in turn, an antecedent of accepting knowledge management. More importantly, the current research found that the adoption of knowledge management is the first factor to affect the research model. Nonetheless, the usage of knowledge management in business can, in turn, have a positive effect back to the implementing extent of environmental managerial accounting. The findings are beneficial to scientists and particularly to executives by shedding new insight into this reciprocated bond, which can lead executives to make sound decisions regarding knowledge management and environmental managerial accounting for businesses to acquire competitive advantages.

• Journal of Korea Trade
• /
• v.27 no.1
• /
• pp.139-158
• /
• 2023

Purpose - The study of co-movements between stock markets is a crucial area of finance and has recently received much interest in a variety of studies, especially in international finance. Stock market co-movements are a major phenomenon in financial markets, but they are not necessarily independent of the real market. Several studies support the idea that bilateral trade linkages significantly impact stock market correlations. Motivated by this perspective, this study investigates whether real market integration due to trade agreements brings about financial market integration in terms of stock market co-movement. Design/methodology - Over the 10 free trade agreements (FTAs) signed by the United States, using a dynamic conditional correlations (DCC) multivariate GARCH (MGRACH) model, we empirically measure the degree of integration by finding DCCs between the US market and the partner country's market. We then track how these correlations evolve over time and compare the results before and after trade agreements. Findings - According to the empirical results, there are positive return spillover effects from the US market to eight counterpart equity markets, except Jordan, Morocco, and Singapore. Especially Mexico, Canada, and Chile have large return spillover effects at the 1% significance level. All partner countries of FTAs generally have positive correlations with the US over the entire period, but the size and variance are somewhat different by country. Meanwhile, not all countries that signed trade agreements with the United States showed the same pattern of stock market co-movement after the agreement. Korea, Mexico, Chile, Colombia, Peru, and Singapore show increasing DCC patterns after trade agreements with the US. However, Canada, Australia, Bahrain, Jordan, and Morocco do not show different patterns before and after trade agreements in DCCs. These countries generally have the characteristic of relatively lower or higher co-movements in stock markets with the US before the signing of the FTAs. Originality/value - To our knowledge, few studies have directly examined the linkages between trade agreements and stock markets. Our approach is novel as it considers the problem of conditional heteroscedasticity and visualizes the change of correlations with time variations. Moreover, analyzing several trade agreements based on the United States enables the results of cross-country pairs to be compared. Hence, this study provides information on the degree of stock market integration with countries with which the United States has trade agreements, while simultaneously allowing us to track whether there have been changes in stock market integration patterns before and after trade agreements.

• Journal of Technology Innovation
• /
• v.11 no.1
• /
• pp.125-145
• /
• 2003

In the knowledge-based economy, the accumulation of technological knowledge is undoubtedly the core competency to reinforce the competitiveness of individual firms and to raise the innovation capability of social and economic systems. Thus far, however, only single or fragmentary indicators, such as R&D expenditure, R&D stock, the number of researchers and the number of R&D employees have been adopted to measure the amount of technological knowledge. In this research, we suggest an approach for aggregating and structuring respective indicators. Applying correlation and factor analysis, we examine the relationship among nine conventional proxy measures for technological knowledge and present a new approach for gauging an aggregated measure.