• The Journal of Information Systems
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• v.27 no.3
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• pp.63-80
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• 2018

Purpose The purpose of this study is to build a machine learning-based customer classification model to promote customer expansion effect of the free sample promotion. Specifically, the proposed model classifies potential target customers who are expected to purchase the products included in the free sample promotion after receiving the free samples. Design/methodology/approach This study proposes to build a customer classification model for determining customers suitable for providing free samples by using various machine learning techniques such as logistic regression, multiple discriminant analysis, case-based reasoning, decision tree, artificial neural network, and support vector machine. To validate the usefulness of the proposed model, we apply it to a real-world free sample-based target marketing case of a Korean major cosmetic retail company. Findings Experimental results show that a machine learning-based customer classification model presents satisfactory accuracy ranging from 70% to 75%. In particular, support vector machine is found to be the most effective machine learning technique for free sample-based target marketing model. Our study sheds a light on customer relationship management strategies using free sample promotions.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.2
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• pp.92-99
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• 2014

The crop growing conditions make accurate predictions of yield ahead of harvest time difficult. Such predictions are needed by the government to estimate, ahead of time, the amount of crop required to be imported to meet the expected domestic shortfall. Corn and soybean especially are widely cultivated throughout the world and a staple food in many regions of the world. On the other hand, the CASA (Carnegie-Ames-Stanford Approach) model is a process-based model to estimate the land plant NPP (Net Primary Productivity) based on the plant growing mechanism. In this paper, therefore, a methodology for the estimation of corn/soybean yield ahead of harvest time is developed specifically for the growing conditions particular to Iowa and Illinois. The method is based on CASA model using MODIS data, and uses Net Primary Productivity (NPP) to predict corn/soybean yield. As a result, NPP at DOY 217 (in Illinois) and DOY 241 (in Iowa) tend to have high correlation with corn/soybean yields. The corn/soybean yields of Iowa in 2013 was estimated to be 11.24/3.55 ton/ha and Illinois was estimated to be 10.09/3.06 ton/ha. Errors were 6.06/17.58% and -10.64/-7.07%, respectively, compared with the yield forecast of the USDA. Crop yield distributions in 2013 were presented to show spatial variability in the state. This leads to the conclusion that NPP changes in the crop field were well reflected crop yield in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.971-989
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• 2015

With the development of cloud computing, more and more Web services are deployed on geo-distributed datacenters and are offered to cloud users all over the world. Through service composition technologies, these independent fine-grain services can be integrated to value-added coarse-grain services. During the composition, a number of Web services may provide the same function but differ in performance. In addition, the distribution of cloud datacenters presents a geographically dispersive manner, which elevates the impact of the network on the QoS of composite services. So it is important to select an optimal composition path in terms of QoS when many functionally equivalent services are available. To achieve this objective, we first present a graph model that takes both QoS of Web services and QoS of network into consideration. Then, a novel approach aiming at selecting the optimal composition path that fulfills the user's end-to-end QoS requirements is provided. We evaluate our approach through simulation and compare our method with existing solutions. Results show that our approach significantly outperforms existing solutions in terms of optimality and scalability.

• Journal of Contemporary Eastern Asia
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• v.17 no.1
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• pp.94-111
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• 2018

This study examines Korea's international development volunteer program as a citizen diplomacy initiative. Informed by a cultural perspective of transmission and relational models of public diplomacy, I examine the ways in which volunteer training incorporates cultural-learning into its program. The study finds that volunteer training is largely based on an instrumentalist approach to culture that places emphasis on learning the "explicit" side of culture, such as Korean traditional dance, art, and food as a strategy to promote the country's national image. In contrast, much less covered in the training program is a relational approach to culture-learning that is guided by a reflexive understanding of the "implicit" side of culture, or the values and beliefs that guide the worldviews and behavior of both volunteers and host constituents. Whereas the value of the volunteer program as a citizen diplomacy initiative is in its potential to build relationships based on two-way engagement, its conception of culture is mostly guided by that of the transmission model of public diplomacy. Based on the findings, this study calls for an integrated approach to culture-learning in volunteer training program to move the citizen diplomacy initiative forward.

• Journal of Korean Society for Quality Management
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• v.38 no.4
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• pp.521-530
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• 2010

Global regulatory pressures relating climate change and environmental responsibility are asking companies to find out the best way for sustaining their continuous business growths. It could be known that inadequate management for environmental issues are bad for business, negatively affecting brand image, causing unnecessary losses and costs for environmental preservation. For this reason, environmentally conscious green business growth has been recognized as an essential requirement for a company to stay in business. Many companies are looking for green business opportunities of improving their environmental and financial results, and struggling with how green fits into their business. In this paper, the Green Six Sigma, an environmentally conscious Six Sigma methodology, is presented as a way to find solutions for green growths. The Six Sigma is known as a disciplined, data-driven approach and methodology for achieving world-class performance in any process from manufacturing to transactional. In chronological order, the Six Sigma has been evolved from Motorola's quality-oriented methodology to GE's cost-oriented lean approach, and is being evolved and developed as an environment-oriented green growth approach. There is no doubt that the Green Six Sigma, as an engine of green growth, is a power tool for achieving competitive business performance and reducing the impact on the environment.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.555-564
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• 2016

Space perception is generally treated as a problem relevant to the ability to recognize objects. Alternatively, the data from shape perception studies contributes to discussions about the geometry of visual space. This geometry is generally acknowledged not to be Euclidian, but instead, elliptical, hyperbolic or affine, which is to say, something that admits the distortions found in so many shape perception studies. The purpose of this review article is to understand perceived shape and the geometry of visual space in the context of visually guided action. Thus, two prominent approaches that explain the relation between perception and action were compared. It is important to understand the fundamental information of how human perceive visual space and perform visually guided action for the convergence on embodied cognition, and further on artificial intelligence researches.

• Asia pacific journal of information systems
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• v.29 no.3
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• pp.503-523
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• 2019

Many cities in the world have increased initiative to realize smart tourism. There are unexplored challenges for the people which lead and manage smart tourism projects and realize its value in tourism (we call them as 'Smart tourism initiatives'), such as orchestrating of tourism complexity, developing and sharing tourism strategy, sustaining tourism projects and innovation. Concerning these challenges, we aim to design a holistic capability maturity model for sustainable and smart tourism governance enabling sustainable tourism innovations via tackling the challenges above. We adopted Dynamic capability theory as a theoretical lens and introduced Design science research methodology in order to develop a new capability maturity governance model as a design artifact. As a result of the study, we could synthesize findings from iterations of the design research cycle based on the IT Capability Maturity Model. Our result proposes a potential capability maturity model supporting effective communication and strategic alignment for the initiatives with illuminating future paths with evaluation methods on tourism capabilities for the initiatives. Throughout this study, we contribute to the body of knowledge as well as practice by proposing a new tourism capability governance model.

• Spatial Information Research
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• v.21 no.6
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• pp.11-21
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• 2013

This study aims to establish a strategic NSDI (National Spatial Data Infrastructure) model for developing countries based on good practices in the Republic of Korea. The Republic of Korea is a unique country in the world, which has become a developed country from a recipient of international aid since the Korean War in 1950. The rapid economic growth can be mostly attributed to the IT technologies and the Republic of Korea's NSDI efforts as a good practice could provide useful lessons for developing countries. This study consists of theoretical reviews, interviews of Korean NSDI experts, analysis for lessons learned, a summary of the lessons in terms of Six NSDI components and finally a strategic NSDI model for developing countries. The NSDI model is structured by (1) implementation strategies suggested for geospatial data, capacity building, geospatial platform, and cost-effective management with partnership, (2) a roadmap of important NSDI tasks and activities, and finally, (3) a harmonized approach for successful NSDI implementation.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.175-190
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• 2007

Stock market volatility largely depends on firms' value and growth opportunities. However, with the globalization of world economy, the effect of the synchronization in major countries is gaining its importance. Also, domestically, the business cycle and cash market of the country are additional factors needed to be considered. The main purpose of this research is to attest the application and usefulness of System Dynamics as a general stock market forecasting tool. Throughout this research, System Dynamics suggests a conceptual model for forecasting a KOSPI(Korea Composite Stock Price Index), taking the factors of the composite stock price indexes in traditional researches. In conclusion of this research, System Dynamics was proved to bean appropriate model for forecasting the volatility and direction of a stock market as a whole. With its timely adaptability, System Dynamic overcomes the limit of traditional statistic models.

• Journal of Contemporary Eastern Asia
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• v.12 no.2
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• pp.61-87
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• 2013

This study applies grounded theory to develop an emic substantive theory of regional integration in Greater East Asia. The role of norms and policies is explored through discursive content analysis of a wide theoretical sample of official elite policy statements dealing with regionalism and related policy areas. A resulting model of regional integration titled "Harmony through Holistic Engagement" is then discussed in relation to the etic consensus on the phenomenon. The study concludes that the etic consensus on the nature of regional integration in Greater East Asia greatly differs from the results of an emic approach and thus reflects a normative consensus rather than a descriptive reality.