• Management & Information Systems Review
• /
• v.27
• /
• pp.131-147
• /
• 2008

The study examines common component existing in five Asian countries from 1991 to 2007. To do this, the daily stock market indices of Korea, Malaysia, Thailand, Indonesia, and the Philippines were used. Using a Vector Autoregressive Model this paper analyzes causal relations and dynamic interactions between five Asian stock markets. The findings in this study indicate that level of five Asian stock markets' stock return linkages are low. First, from the statistics for pair-wise Granger causality tests, I find Granger-causal relationship between Korea and Indonesia and between Malaysia and and Indonesia. Second, from the results of response function and the statistics of variance decomposition, I find that week shocks to Korean stock market return on Malaysia, Indonesia, Thailand, and the Philippines stock market returns. The results indicate increased Asian stock market linkages but the level is very low. This implies that the benefits of diversification within the five Asian stock markets are still existed.

• The Korean Journal of Applied Statistics
• /
• v.17 no.2
• /
• pp.239-252
• /
• 2004

It is known that the domestic and the U.S. stock prices tend to move together as those markets are closely interrelated. In this study, cointegration and causal relationships among the four stock price indexes of KOSPI, KOSDAQ, DOWJONES and NASDAQ are carefully investigated for the period of declining stock prices in the long run. When all indexes move in a similar fashion, cointegration does not exist and the causal linkages between the domestic and the U.S. stock prices appear relatively complex. On the other hand, when the domestic and the V.S. stock prices move in a different manner, cointegration exists and the causal relationships appear relatively simple. NASDAQ is apparently found to lead the domestic stock market in both periods, which is consistent with the actual market situation when the If industry is under recession.

• Environmental and Resource Economics Review
• /
• v.12 no.2
• /
• pp.327-346
• /
• 2003

Unlike previous studies on the causal relationship between energy consumption and economic growth, this paper analyses the dynamic causal relationship between these variables using the dynamic vector using Johansen's multiple cointegration procedure, dynamic vector error-correction model and impulse response function. The empirical results show that while the energy consumption to a shock in income responds positively, the income responds positively to the shocks in energy consumption in the first place and then the responses become negative. We also find that the impact of energy consumption shock on the income is short-lived and causes higher inflationary pressure.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.10
• /
• pp.97-104
• /
• 2022

The purpose of the existing work is to inspect the impact of knowledge management on organizational performance. Business experts now appreciate how important knowledge management is for organizational performance. Earlier studies have investigated the research model with causal linkages, however, only a few of them have considered sample-selecting bias problems when analyzing the model of knowledge management on organizational performance. The number of 312 executives related to knowledge management from 312 enterprises that have been approved with quality management systems offered suitable responses for analyses. The data was employed to investigate the effect of knowledge management on organizational performance, considering sample-selecting bias. The empirical outcomes indicate that sample-selecting bias exists in the causal impact of knowledge management on organizational performance. The empirical findings are helpful to scholars of knowledge management as well as business executives by giving an insight into the casual effect of knowledge management on organizational performance with the intervention of sample-selecting bias. The acceptance of knowledge management should be tailored to improve competitive advantages that will lead to better organizational performance.

• Journal of Korea Port Economic Association
• /
• v.24 no.1
• /
• pp.1-10
• /
• 2008

This paper analyses the dynamic causal relationship between vessel export and economic growth using annual data over the period from 1977 to 2006. Tests for ADF unit-roots, the dynamic vector using Johansen's multiple cointegration procedure, dynamic vector error correction model and impulse response function are presented. The findings of the Granger test suggest that vessel export Granger-causes economic growth in the short-run and economic growth Granger-causes exports in the short and long-run. The empirical results of impulse-response analysis show that the vessel export to a shock in real GDP responds positively and the real GDP responds positively to the shocks in vessel export. Also, the results indicate that the impact of vessel export shock on the real GDP is short-lived.

• The Journal of Society for e-Business Studies
• /
• v.7 no.1
• /
• pp.87-106
• /
• 2002

The behavioral and dynamic implications of an ERP implementation/installation are, to say the least, not well understood. Getting the switches set to enable the ERP software to go live is becoming straightforward. The really difficult part is understanding all of the dynamic interactions that accrue as a consequence. Dynamic causal and connectionist models are employed to facilitate an understanding of the dynamics and to enable control of the information-enhanced processes to take place. The connectionist model ran be analyzing (behind the scenes) the information accesses and transfers and coming If some conclusions about strong linkages that are getting established and what the behavioral implications of those new linkages and information accesses we. Ultimately, the connectionist model will come to an understanding of the dynamic, behavioral implications of the larger ERP implementation/installation per se. The underlying connectionist model will determine information transfers and workflow. Once a map of these two infrastructures is determined by the model, it becomes a relatively easy job for an analyst to suggest improvements in both. Connectionist models start with analog object structures and then use learning to produce mechanisms for managerial problem diagnoses. These mechanisms are neural models with multiple-layer structures that support continuous input/output. Based on earlier work performed and published by the author[10][11], a Connectionist ReasOning and LEarning System(CROLES) is developed that mimics the real-world reasoning infrastructure. Coupled with an explanation subsystem, this system can provide explanations as to why a particular reasoning structure behaved the way it did. Such a system operates in the backgmund, observing what is happening as every information access, every information response coming from each and every intelligent node (whether natural or artificial) operating within the ERP infrastructure is recorded and encoded. The CROLES is also able to transfer all workflows and map these onto the decision-making nodes of the organization.

• Korean System Dynamics Review
• /
• v.4 no.1
• /
• pp.69-91
• /
• 2003

Using qualitative methods hinged on urban dynamics models, the paper addresses major issues concerned with new administrative capital construction. It tries to summarize the existing debates on new administrative capital construction and reinterpret diverse interacting factors in terms of reinforcing or balancing feedback structure. The paper suggests that understanding up on the dynamic mechanism imbedded in circular causal loop diagrams is the key to set up appropriate proposals and action plans for the new administrative capital, as they would reveal complicated linkages between the Capital Region and the rest, in addition to the urban dynamic of new administrative capital. In the same context, the paper can confirm similar features reflected in the relocation of capital functions at Canberra, Australia and Berlin, Germany. It has paid special attention to the fact that both Australian and German governments altogether stress the positive feedback loops as they have overcome unprecedented political confrontation among rival cities: Basically, they have encouraged gives-and-takes among major stake-holders. These research findings indicate that the future of new administrative capital construction depends on consensus buildings that can accommodate socio-economic and territorial changes between pros and cons. Although further researches and validations are needed, the system approach presented in this paper could assist Korean decision-makers in developing robust and responsive policy initiatives under uncertainties.

• Journal of Korea Port Economic Association
• /
• v.27 no.3
• /
• pp.13-39
• /
• 2011

Many previous studies on the subject of supply chain have consistently claimed that they need collaboration among the partners of supply chains in order to enhance supply chain performance. The purpose of research is to examine the causal linkages among relational characteristics, collaboration, performance in the logistics firm and this research focuses on two types collaboration(operational collaboration and strategic collaboration) as the mediation variable between relational characteristics and supply chain performance. To test the above research questions, we collected data from logistics firm(N=164). The proposed structural model was tested using the PLS(Partial Least Square) statistical program. The research results are as follows. Trust, and information sharing have positive influences on operational collaboration, and operational collaboration have also positive influences on supply chain performance. Duration and information sharing have positive influences on strategic collaboration. However, strategic collaboration has non-positive influences on supply chain performance. The effect of relational characteristics on supply chain performance is mediated by operational collaboration.

• International Journal of Computer Science & Network Security
• /
• v.24 no.5
• /
• pp.11-20
• /
• 2024

While artificial neural networks are adept at identifying patterns, they can struggle to distinguish between actual correlations and false associations between extracted facial features and criminal behavior within the training data. These associations may not indicate causal connections. Socioeconomic factors, ethnicity, or even chance occurrences in the data can influence both facial features and criminal activity. Consequently, the artificial neural network might identify linked features without understanding the underlying cause. This raises concerns about incorrect linkages and potential misclassification of individuals based on features unrelated to criminal tendencies. To address this challenge, we propose a novel region-based training approach for artificial neural networks focused on criminal propensity detection. Instead of solely relying on overall facial recognition, the network would systematically analyze each facial feature in isolation. This fine-grained approach would enable the network to identify which specific features hold the strongest correlations with criminal activity within the training data. By focusing on these key features, the network can be optimized for more accurate and reliable criminal propensity prediction. This study examines the effectiveness of various algorithms for criminal propensity classification. We evaluate YOLO versions YOLOv5 and YOLOv8 alongside VGG-16. Our findings indicate that YOLO achieved the highest accuracy 0.93 in classifying criminal and non-criminal facial features. While these results are promising, we acknowledge the need for further research on bias and misclassification in criminal justice applications

• The Journal of Society for e-Business Studies
• /
• v.17 no.1
• /
• pp.111-136
• /
• 2012

The global recession has made it more difficult for companies to invest in IT, and they are increasingly aware of the environmental costs of so doing. In these circumstances, cloud computing has emerged as a new paradigm in the business IT sector. Governments, institutes and companies around the world, as well as specifically in Korea since 2009, have turned to this model of providing IT resources. This study is concerned to identify those characteristics of cloud computing that affect its introduction on a company's part; it offers a theoretical framework describing cloud services and seeks to establish causal linkages between antecedent factors and a company's introduction and application of this form of IT provision. The features of cloud computing in particular contexts that the study selected for analysis were its scalability, speed, security, potential compatibility with existing services, efficiency, economic feasibility, dependency and credibility. The study thus related these to whether or not cloud computing was adopted, verifying adjustment effects for cloud services. On the basis of a survey of enterprise IT decision-makers, it emerged through a statistical analysis of correlations that cloud computing's efficiency, economic feasibility and credibility had an effect on its introduction. This study's results should be of use to vendors and potential purchasers of cloud computing services. It is one of the first pieces of research on cloud computing from the customer perspective, based on the perceived characteristics of cloud services as they are seen and valued by users.