• Asia pacific journal of information systems
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• v.17 no.2
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• pp.1-28
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• 2007

The success of new product development is a key factor for getting competitive advantages. Marketing research has been investigating marketing capability, manufacturing technical capability, cross-functional integration, market knowledge competence, market orientation, and competitive environment as the key success factors of new product development. Recently, the role of IT infrastructure in enhancing new product advantage is assumed in the literature. However, the empirical studies on the role of IT infrastructure are lacking. The purpose of this study is to empirically exam the impacts of IT infrastructure on new product competitive advantage. In this study, IT infrastructure is conceptualized as the flexibility of IT infrastructure. Based on previous research, a conceptual model is established by incorporating the direct impact of IT infrastructure flexibility and its indirect impact through the key success factors on new product development. To empirically test the research model, data are surveyed from a pair of IS department and Marketing department of 92 consumer goods manufacturers. By employing PLS technique, the measurement reliability and reliability of research variables are tested and the path analysis is conducted to do the hypothesis testing. The path analysis shows that IT infrastructure flexibility has no direct effect on new product advantage, However, the indirect effect of IT infrastructure is found, which is mediated by marketing capability, manufacturing technical capability, cross-functional integration, and market orientation respectively. Hence, The flexible IT infrastructure increases cross-functional integration (H1), market orientation (H3), marketing capability (H5), and manufacturing technical capability (H6). All success factors of new product development excepts for competitive environment have a positive association with new product competitive advantages (from H10 to H14). Finally, the path from IT infrastructure flexibility to cross-functional integration, to market orientation, to market knowledge capability, and to new product advantage is found as the strongest path. These results indicate that the flexible IT infrastructure enhances information sharing with multiple departments and collaboration within a distributed innovation environment. The collaboration among departments positively affects the level of customer and competitor intelligence. The ability to obtain knowledge about customers and competitors makes firms to adapt to a changing environment quickly and to respond to customers' demands adequately. The flexible IT infrastructure also enhances the capability of organization to more rapidly respond to the changes in product design resulting in faster product development and reduced costs. In addition to, it enhances marketing capability by the two-way communications with customers and the analyses of various kinds of customer data. In brief, the finding of this study suggests that the flexible IT infrastructure allows many firms to pursue sustained new product competitive advantages. This study advances research on IT infrastructure in two important aspects. First, by Integrating marketing research and IS research, this study develops a conceptual model on the role of IT infrastructure in enhancing new product advantage. Second, it empirically finds the indirect impacts of IT infrastructure on new product advantage, which confirms the potential for the IS field to contribute to new product development research. The limitations of this study are also discussed to provide research directions for future research.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.87-95
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• 2009

As information theoretic learning techniques, error entropy minimization criterion (MEE) and maximum cross correntropy criterion (MCC) have been studied in depth for supervised learning. MEE criterion leads to maximization of information potential and MCC criterion leads to maximization of cross correlation between output and input random processes. The weighted combination scheme of these two criteria, namely, minimization of Error Entropy with Fiducial points (MEEF) has been introduced and developed by many researchers. As an approach to unsupervised, blind channel equalization, we investigate the possibility of applying constant modulus error (CME) to MEE criterion and some problems of the method. Also we study on the application of CME to MEEF for blind equalization and find out that MEE-CME loses the information of the constant modulus. This leads MEE-CME and MEEF-CME not to converge or to converge slower than other algorithms dependent on the constant modulus.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.558-565
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• 2024

This paper presents the development of an optimization framework for road slope design. Recognizing the limitations of current manual stability analysis methods, which are time-consuming, are error-prone, and suffer from data mismatches, this study proposes a systematic approach to improve efficiency, reduce costs, and ensure the safety of infrastructure projects. The framework addresses the subjectivity inherent in engineers' decision-making process by formalizing decision variables, constraints, and objective functions to minimize costs while ensuring safety and environmental considerations. The necessity of this framework is embodied by the review of existing literature, which reveals a trend toward specialization within sub-disciplines of road design; however, a gap remains in addressing the complexities of road slope design through an integrated optimization approach. A genetic algorithm (GA) is employed as a fundamental optimization tool due to its well-established mechanisms of selection, crossover, and mutation, which are suitable for evolving road slope designs toward optimal solutions. An automated batch analysis process supports the GA, demonstrating the potential of the proposed framework. Although the framework focuses on the design optimization of single cross-section road slopes, the implications extend to broader applications in civil engineering practices. Future research directions include refining the GA, expanding the decision variables, and empirically validating the framework in real-world scenarios. Ultimately, this research lays the groundwork for more comprehensive optimization models that could consider multiple cross-sections and contribute to safer and more cost-effective road slope designs.

• Journal of the Korean Geotechnical Society
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• v.38 no.4
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• pp.59-70
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• 2022

There is a growing interest in evaluating earthquake damage and determining disaster prevention measures due to the magnitude 5.8 earthquake in Pohang, Korea. Since the liquefaction phenomena occurred extensively in the residential area as a result of the earthquake, there was a demand for research on liquefaction phenomenon evaluation and liquefaction disaster prediction. Liquefaction is defined as a phenomenon where the strength of the ground is completely lost due to a sudden increase in excess pore water pressure caused due to large dynamic stress, such as an earthquake, acting on loose sand particles in a short period of time. The liquefaction potential index, which can identify the occurrence of liquefaction and predict the risk of liquefaction in a targeted area, can be used to create a liquefaction hazard map. However, since liquefaction assessment using existing field testing is predicated on a single borehole liquefaction assessment, there has been a representative issue for the whole targeted area. Spatial interpolation and geographic information systems can help to solve this issue to some extent. Therefore, in order to solve the representative problem of geotechnical information, this research uses the kriging method, one of the geostatistical spatial interpolation techniques, and constructs a geotechnical information database for liquefaction and spatial interpolation. Additionally, the liquefaction hazard map was created for each return period using the constructed geotechnical information database. Cross validation was used to confirm the accuracy of this liquefaction hazard map.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.225-228
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• 2007

This paper presents a geostatistical methodology to model local uncertainty in spatial estimation of sediment grain size with high-resolution remote sensing imagery. Within a multi-Gaussian framework, the IKONOS imagery is used as local means both to estimate the grain size values and to model local uncertainty at unsample locations. A conditional cumulative distribution function (ccdf) at any locations is defined by mean and variance values which can be estimated by multi-Gaussian kriging with local means. Two ccdf statistics including condition variance and interquartile range are used here as measures of local uncertainty and are compared through a cross validation analysis. In addition to local uncertainty measures, the probabilities of not exceeding or exceeding any grain size value at any locations are retrieved and mapped from the local ccdf models. A case study of Baramarae beach, Korea is carried out to illustrate the potential of geostatistical uncertainty modeling.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.599-604
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• 2008

The dispersive phase velocity of a wave propagating through a system is an important parameter and carries valuable information in non-destructive tests related to multilayered systems such as a soil site. The dispersive phase velocity of a wave can be determined using the phase spectrum, which is easily evaluated through the cross power spectrum. However, the phase spectrum as determined using the cross power spectrum is sensitive to background noise which always exists in the field. This causes difficulties in the determination of the dispersive phase velocities. In this paper, a new method to evaluate the phase spectrum using the harmonic wavelet transform is proposed. The proposed method can successfully remove background noise effects. To evaluate the validity of the proposed method, numerical simulations of multi-layered systems were performed. Phase spectrums by the proposed method were found to be in good agreement with the actual phase spectrums under conditions characterized by heavy background noise. This shows the potential of the proposed method.

• Korean Journal of Construction Engineering and Management
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• v.13 no.1
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• pp.160-169
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• 2012

Domestic construction industry, which has recently had difficulty in market saturation and slowing growth, is trying to resolve this situation by incorporation with IT technology. However, there was less choice and has simply used IT technology as required in construction field. In other word, IT technology has applied to not all processes but some parts. Therefore, in this paper, we find out suitable and promising IT technology to each step of construction process, analyzing IT convergence technology related to whole process comprehensively in order to suggest fundamental directions for effective construction IT convergence in the field.

• Knowledge Management Research
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• v.20 no.1
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• pp.133-153
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• 2019

Due to the uncertainty of dynamic business environment, modern organizations have been giving attention to dynamic capabilities beyond traditional notion of core competence. Among them, absorptive capacity and boundary-spanning activity are considered the most important. The former refers to activities regarding acquisition, assimilation, transformation and exploitation of internal and external knowledge. The latter is composed of boundary-loosening and boundary-tightening activities to detect internal or external information and then to preserve, protect, or acquire resources. Thus, both have achieved wide recognition as a potential source of change and innovation. This study investigated the cross-level relation between boundary-spanning leadership at team level and absorptive capacity at individual level. We also explored self-efficacy and extra-role behavior that can affect employees' absorptive capacity. To test multi-level analysis, the survey data were collected from 862 members in 137 teams of different firms. Results revealed that boundary-spanning leadership had the positive cross-level impact on absorptive capacity in the team context. Moreover, absorptive capacity was positively associated with self-efficacy and extra-role behavior at individual level. Based on these findings, we provided theoretical and practical implications to address rapidly changing environments and discussed limitations of this paper for further research.

• Journal of The Geomorphological Association of Korea
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• v.24 no.3
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• pp.105-118
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• 2017

The debris slope landforms which are existent in Korean mountains is generally on the steep slopes and mostly covered by vegetation, it is difficult to investigate the landform. Therefore a scientific method is required to come up with an effective field investigation plan. For this purpose, the use of Remote Sensing and GIS technologies for a spatial analysis is essential. This study has extracted the potential area of debrisslope landform formation using Fuzzy set and Bayesian Predictive Discriminate Model as mathematical data integration methods. The first step was to obtain information about debris locations and their related factors. This information was verified through field investigation and then used to build a database. In the second step, the map that zoning the study area based on the degree of debris formation possibility was generated using two modeling methods, and then cross validation technique was applied. In order to quantitatively analyze the accuracy of two modeling methods, the calculated potential rate of debrisformation within the study area was evaluated by plotting SRC(Success Rate Curve) and calculating AUC(Area Under the Curve). As a result, the prediction accuracy of Fuzzy set model wes 83.1% and Bayesian Predictive Discriminate Model wes 84.9%. It showed that two models are accurate and reliable and can contribute to efficient field investigation and debris landform management.

• Journal of The Geomorphological Association of Korea
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• v.24 no.1
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• pp.77-91
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• 2017

Many debris landforms in the mountains of Korea have formed in the periglacial environment during the last glacial stage when the generation of sediments was active. Because these landforms are generally located on steep slopes and mostly covered by vegetation, however, it is difficult to observe and access them through field investigation. A scientific method is required to reduce the survey range before performing field investigation and to save time and cost. For this purpose, the use of remote sensing and GIS technologies is essential. This study has extracted the potential area of debris landform formation using a fuzzy set model as a mathematical data integration method. The first step was to obtain information about the location of debris landforms and their related factors. This information was verified through field observation and then used to build a database. In the second step, we conducted the fuzzy set modeling to generate a map, which classified the study area based on the possibility of debris formation. We then applied a cross-validation technique in order to evaluate the map. For a quantitative analysis, the calculated potential rate of debris formation was evaluated by plotting SRC(Success Rate Curve) and calculating AUC(Area Under the Curve). The prediction accuracy of the model was found to be 83.1%. We posit that the model is accurate and reliable enough to contribute to efficient field investigation and debris landform management.