• Asia pacific journal of information systems
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• v.26 no.1
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• pp.66-79
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• 2016

The availability of detailed data on customers' online behaviors and advances in big data analysis techniques enable us to predict consumer behaviors. In the past, researchers have built purchase prediction models by analyzing clickstream data; however, these clickstream-based prediction models have had several limitations. In this study, we propose a new method for purchase prediction that combines information theory with machine learning techniques. Clickstreams from 5,000 panel members and data on their purchases of electronics, fashion, and cosmetics products were analyzed. Clickstreams were summarized using the 'entropy' concept from information theory, while 'random forests' method was applied to build prediction models. The results show that prediction accuracy of this new method ranges from 0.56 to 0.83, which is a significant improvement over values for clickstream-based prediction models presented in the past. The results indicate further that consumers' information search behaviors differ significantly across product categories.

• The Journal of Fisheries Business Administration
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• v.51 no.1
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• pp.81-96
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• 2020

The purpose of this paper is to analyze factors affecting the net income of regional and industrial fisheries cooperatives in South Korea using panel data. This paper utilizes linear or GLS regression models such as pooled OLS model, fixed effects model, and random effects model to estimate affecting factors of the net income of regional and industrial fisheries cooperatives. After reviewing various tests, we eventually select random effects model. The results, based on panel data between 2013 and 2018 year and 64 fisheries cooperatives, indicate that capital and area dummy variables have positive effects and employment has negative effect on the net income of regional and industrial fisheries cooperatives as predicted. However, debt are opposite with our predictions. Specifically, it turns out that debt has positive effect on the net income of regional and industrial fisheries cooperatives although it has been increased. Additionally, this paper shows that the member of confreres does not show any significant effect on the net income of regional and industrial fisheries cooperatives in South Korea. This study is significant in that it analyzes the major factors influencing changes in the net income that have not been conducted recently for the fisheries cooperatives by region and industry.

• Asia-Pacific Journal of Business
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• v.11 no.2
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• pp.27-43
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• 2020

Purpose - This study explores the impact of the real estate industry on related industries for the perspective of Chinese steel companies. Design/methodology/approach - The impact of housing prices on the 41 listed steel companies' performance was analyzed by using the panel data model. We used two kinds of housing price indexes that are set in the panel data models to estimate the range of the real estate market, driving the performance growth of steel listed companies. Moreover, the net profit of steel companies is used as the dependent variable. To test the stability of the model, ROA used as a dependent variable for the robustness test. Also, to avoid the time trend of housing prices, this paper selects the growth rate of housing prices as the primary research variable. After Fisher-type testings, there is no unit root problem in both independent and dependent variables. Findings - The results indicated that the rise in the housing price has a positive influence on the steel company performance. When the housing price increases by 1%, the net profit of steel enterprises will increase by 5 to 20 million yuan. Research implications or Originality - In this paper, empirical data at the micro-level and panel model are used to quantify China's real estate industry's driving effect on the iron and steel industry, providing evidence from the microdata level. It helps us to understand further the status and role of China's real estate industry in the economic structure.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.399-408
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• 2015

This paper concentrated on the ultimate uniaxial compressive strength of stiffened panel with opening under lateral load and also studied the design-oriented formulae. For this purpose, three series of well executed experiments on longitudinal stiffened panel with rectangular opening subjected to the combined load have been selected as test models. The finite element analysis package, ABAQUS, is used for simulation with considering the large elasticplastic deflection behavior of stiffened panels. The feasibility of the numerical procedure is verified by a good agreement of experimental results and numerical results. More cases studies are executed employing nonlinear finite element method to analyze the influence of design variables on the ultimate strength of stiffened panel with opening under combined pressure. Based on data, two design formulae corresponding to different opening types are fitted, and accuracy of them is illustrated to demonstrate that they could be applied to basic design of practical engineering structure.

• Proceedings of the KOR-KST Conference
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• 1998.09a
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• pp.160-167
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• 1998

Recent world-wide interest in activity-based travel behavior modeling has generated an entirely new perspective on how the profession views the travel demand process. This paper seeks to further promote the case of activity-based travel behavior models by providing some empirical evidence of relationship between travel time and activity duration decision for worker with transportation panel data. The travel time from home to work and from work to home, without activity involvement, is estimated by the Ordinary Least Squares (OLS) method. And, the travel time to and from the selected activity and the activity duration are modeled simultaneously by the Three Stage Least Squares (3SLS) method due to the endogenous relationship between travel time and activity duration. Two kinds of models, OLS and 3SLS, include selectivity bias corrections in a discrete/continuous framework, because of the inter-relationship between the choice of activity type/travel mode (discrete) and the travel time/activity duration (continuous). Estimation is undertaken using a sample of over 1300 household two-day trip diaries collected from the same travelers in the Seattle area in 1989. The behavioral consequences of these models provide interesting and provocative findings that should be of value to transportation policy formulation and analysis.

• Korea Real Estate Review
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• v.27 no.1
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• pp.33-44
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• 2017

The continuously rising housing prices in major Chinese cities have raised question about whether inflation is the main reason to drive up housing price to skyrocket in recent years. Based on the provincial panel dataset of China from 2006-2014, this paper investigates the impact of inflation on Chinese housing markets within the frameworks of both static and dynamic panel data models. Our empirical results show evidence that inflation has indeed been a main force of accumulating housing bubbles in these housing markets, especially in eastern region of China. We also find an interesting phenomenon in which Chinese housing bubble is, to a certain extent, affected by market self-adjustment mechanism.

• Journal of Korea Water Resources Association
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• v.44 no.1
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• pp.1-8
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• 2011

This paper addresses the correlation between the flood damage cost and recovery cost. National data (15 regions) for 20 years, panel data, has been analyzed for this test. Model specification of panel data analysis depends on the characteristics of data set and "fixed" or "random" effects model can be used. The results are represented in both models. As we expected all independent variables show positive relationship with recovery cost, except for the number of death and suffers. The damage of public facilities, such as rivers and road are the major factors on the damage and recovery cost, which means that flood damage can not be decreased without decreasing damages of public facilities from floods. Especially, the recovery cost is always higher than the damage cost and investment for flood control. Unlikely, government investment for flood control is the highest and recovery cost is the always lower than da mage cost andinvestment in Japan. Which means that proper investment can reduce economic damage cost of flood and recovery cost.

• Korean Journal of Legislative Studies
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• v.23 no.2
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• pp.147-177
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• 2017

Although a number of empirical studies found that political ideology plays a significant role in Korean elections, they entirely rely on cross-sectional data analysis. In contrast to previous research, this study investigates the effects of ideology in the 2012 Korean presidential election through standard panel data analysis. Specifically, using "EAI Panel Study, 2012", the effects of ideology on both candidate evaluation and vote choice were examined via fixed effects, random effects, and pooled regression analysis. And the results from applying the two most popular models of ideological voting, the proximity model and the directional change model were also compared. The results show that candidate evaluations and vote choice during the election (April, 2012- December, 2012) were significantly influenced by the ideological difference between voters and candidates, independent from partisanship and other standard socio-demographic factors. And this ideological voting during the election seems better captured by the directional change model than by the proximity model.

• Journal of the Semiconductor & Display Technology
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• v.11 no.1
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• pp.67-71
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• 2012

The optical properties of PDP, such as the transmittance and reflectance, were analyzed with 3D optical code. Three different ITO-less structures in the front panel are examined. In the assembled panel study, the test 1 structure shows 16.6% and 10.2% higher reflectance than the structures of tests 2 and 3, respectively. In order to check the validation of the simulation result, three 7.5-inch test panels having the same geometry and property are fabricated as simulation models. The calculated reflective properties are compared to the measured data from real panels. The relative difference extracted from the simulation and measurement methods is less than 4.9% and are well matched.

• Economic Analysis
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• v.17 no.1
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• pp.103-130
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• 2011

This paper intends to provide applied economists which study the effects of research and development with valuable information on econometric model selection. It includes extensive discussion on econometric models which have been applied for the study on the relationship between research and development and productivity. In particular, it compares various stochastic production frontier models which have been developed recently. The discussion decomposes them into models with scaling property and the ones with nonscaling property as well as models with monotonic and nonmonotonic relationships between research and development and productivity. Finally, this paper applies the models to two different panel data sets (firm level data and country level data) and compare estimation results from competing econometric models.