• Information Systems Review
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• v.9 no.2
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• pp.189-207
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• 2007

The importance of IT service management to improve the effectiveness and efficiency of IT outsourcing practices or performance has been emphasized in the fields. Accordingly, several methodologies of IT service management have been adopted in a fashion. This case based research tries to analyze the effects of ITIL-based IT service management practice in a company on IT outsourcing performance. The case analysis shows that ITIL-based service management influences systems quality, information quality, and service quality in direct manner. But it does not influence systems use and systems satisfaction in a meaningful way. This study would help IT service managers construct IT service environment which improves the performance of IT outsourcing service delivery and also researchers set up research proposition in a concise way in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.2
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• pp.75-96
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• 2011

Recently, Dennis et al.(2008) proposed media synchronicity theory. In this theory, for conveyance communication processes, use of media supporting lower synchronicity should result in better communication performance. But for convergence processes, use of media supporting higher synchronicity should result in better communication performance. This paper proved a part of the propositions of media synchronicity theory, because media synchronicity theory was proposed theoretically, not empirically. We used a data set generated from the survey. The respondents of survey were 163 students who had experienced the communication media in the classes that should summit result of team projects or team reports. According to the results of data analysis, higher use of communication media led to better learning performance. The familiarity of task moderated the effect of communication media on learning performance. And use of media supporting higher synchronicity led to better learning performance.

• International Commerce and Information Review
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• v.13 no.2
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• pp.3-26
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• 2011

The objective of this study is to improve export performance using e-Trade marketing systems. The use of e-Trade has been increasing but there is some controversy about the performance of e-Trade marketing for Small-to-Medium enterprises (SME). The research construct for determining the export performance is suggested and five factors are introduced in this paper such as: B2B relationship and cooperation, product complexity, online fitness, level of internationalization, and use of e-Trade marketing. Sample data were collected from the companies who are familiar with the e-Trade systems. The result shows that the use of e-Trade marketing mostly contributes to the increase of export performance. The regression and cluster analysis shows that both variables of e-Trade marketing and on-line fitness are significant to high export performance group. The implication for SMEs is that the use of e-Trade marketing methods could contribute to the increase of export performance and more analytical works need to be made for future study.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.499-509
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• 2018

Recently, hybrid transactional memory (HyTM) has gained much interest from researchers because it combines the advantages of hardware transactional memory (HTM) and software transactional memory (STM). To provide the concurrency control of transactions, the existing HyTM-based studies use a bloom filter. However, they fail to overcome the typical false positive errors of a bloom filter. Though the existing studies use a global lock, the efficiency of global lock-based memory allocation is significantly low in multi-core environment. In this paper, we propose an efficient hybrid transactional memory scheme using near-optimal retry computation and sophisticated memory management in order to efficiently process transactions in multi-core environment. First, we propose a near-optimal retry computation algorithm that provides an efficient HTM configuration using machine learning algorithms, according to the characteristic of a given workload. Second, we provide an efficient concurrency control for transactions in different environments by using a sophisticated bloom filter. Third, we propose a memory management scheme being optimized for the CPU cache line, in order to provide a fast transaction processing. Finally, it is shown from our performance evaluation that our HyTM scheme achieves up to 2.5 times better performance by using the Stanford transactional applications for multi-processing (STAMP) benchmarks than the state-of-the-art algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.41-60
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• 2004

A stream data is a data set that is accumulated to the data storage from a data source over time continuously. The size of this data set, in many cases. becomes increasingly large over time. To mine information from this massive data. it takes much resource such as storage, memory and time. These unique characteristics of the stream data make it difficult and expensive to use this large size data accumulated over time. Otherwise. if we use only recent or part of a whole data to mine information or pattern. there can be loss of information. which may be useful. To avoid this problem. we suggest a method that efficiently accumulates information. in the form of rule sets. over time. It takes much smaller storage compared to traditional mining methods. These accumulated rule sets are used as prediction models in the future. Based on theories of ensemble approaches. combination of many prediction models. in the form of systematically merged rule sets in this study. is better than one prediction model in performance. This study uses a customer data set that predicts buying power of customers based on their information. This study tests the performance of the suggested method with the data set alone with general prediction methods and compares performances of them.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.60-67
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• 2008

Skin color is a very important information for an automatic face recognition. In this paper, we proposed a skin region extraction method using color information and skin color model. We use the adaptive lighting compensation technique for improved performance of skin region extraction. Also, using an preprocessing filter, normally large areas of easily distinct non skin pixels, are eliminated from further processing. And we use the modified ST color space, where undesired effects are reduced and the skin color distribution fits better than others color space. Experimental results show that the proposed method has better performance than the conventional methods, and reduces processing time by $35{\sim}40%$ on average.

• Management & Information Systems Review
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• v.33 no.1
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• pp.237-261
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• 2014

This study is to investigate the impact of information technology implementation on supply chain risk and performance. It focuses on how information technology adoption affects supply risk as well as performance. It collected one hundred fifty nine responses from supply executives and supply and purchasing managers of U.S manufacturing firms by applying a survey methodology. The research results provide empirical evidence that the use of information technology in the supply chain mitigates supply risk and improves performance. More importantly, information technology adoption involves three aspects: inbound and outbound communications, internal communications and administration and finally, mitigation of supply risks and improved performance via order taking and procurement. This research emphasizes the importance of IT implementation in supply risk management. It also points out how information technology adoption facilitates the impact of information technology in risk mitigation in the supply chain and in performance. Thus, supply and purchasing managers need to consider IT implementation and adoption when establishing their risk mitigating strategies within the supply chains.

• The Journal of Information Technology
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• v.7 no.2
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• pp.7-17
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• 2004

An academic performance can advance the expectations that lead to academic success. The purpose of this study was to research the relationship of the variables; past performance, the ability to use information technology, outcome expectations, grade goal of studies, and study performance in an information technology course. Participants completed a background questionnaire, the Information Technology Proficiency Exam, the scale of the ability using computer, and the Technology Outcome scale. Based on path model results, the findings suggest that students' academic performance is related to past performance. Consistent with theory, the findings suggest that the studies performance is influenced by ability using information technology via the establishment of the grade goal of studies. In the present study, the past performance variable failed to predict an academic studies performance when impacted by outcome expectations.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.17-22
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• 2021

With the application of the Data 3 method, the scope of the use of pseudonym information has expanded. In the case of pseudonym information, a specific individual can be identified by linking and combining with various data, and personal information may be leaked due to incorrect use of the pseudonym information. In this paper, we propose the scope of use of data is subdivided and a differentiated pseudonym information processing method according to the scope. For the study, the formula was modified by using zero-knowledge proof among the pseudonym information processing methods, and when the proposed formula was applied, it was confirmed that the performance improved by an average of 10% in terms of verification time compared to the case of applying the formula of the existing zero-knowledge proof.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.770-802
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• 2022

With the development of deep learning techniques, text mining is producing breakthrough performance improvements, promising future applications, and practical use cases across many fields. Likewise, even though several attempts have been made in the field of financial information, few cases apply the current technological trends. Recently, companies and government agencies have attempted to conduct research and apply text mining in the field of financial information. First, in this study, we investigate various works using text mining to show what studies have been conducted in the financial sector. Second, to broaden the view of financial application, we provide a description of several text mining techniques that can be used in the field of financial information and summarize various paradigms in which these technologies can be applied. Third, we also provide practical cases for applying the latest text mining techniques in the field of financial information to provide more tangible guidance for those who will use text mining techniques in finance. Lastly, we propose potential future research topics in the field of financial information and present the research methods and utilization plans. This study can motivate researchers studying financial issues to use text mining techniques to gain new insights and improve their work from the rich information hidden in text data.