• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.43-51
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• 2012

The OLS(ordinary least squares) method is widely used in hedonic housing models. One of the assumptions of the OLS is an independent and uniform distribution of the disturbance term. This assumption can be violated when the spatial autocorrelation exists, which in turn leads to undesirable estimate results. An alterative to this, spatial econometric models have been introduced in housing price studies. This paper describes the comparisons between OLS and spatial econometric models using housing transaction prices of Busan, Korea. Owing to the approaches reflecting spatial autocorrelation, the spatial econometric models showed some superiority to the traditional OLS in terms of log likelihood and sigma square(${\sigma}^2$). Among the spatial models, the SAR(Spatial Autoregressive Models) seemed more appropriate than the SAC(General Spatial Models) and the SEM(Spatial Errors Models) for Busan housing markets. We can make sure the spatial effects on housing prices, and the reconstruction plans have strong impacts on the transaction prices. Selecting a suitable spatial model will play an important role in the housing policy of the government.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.630-643
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• 2022

This study was conducted to derive the fresh weight and dry weight estimation formulas of Pinus densiflora and prepare a weight table using them. Aone-variable formula using only the diameter at breast height (DBH) and a two-variable formula using DBH and height were used to calculate the fresh and dry weight. Each equation was verified using statistics, such as fit index, standard error, and residuals. Theoptimal equation was evaluated for applicability by calculating the weight as a coefficient derived from a statistical verification. W = bD+cD² was selected for the one-variable equation, while W = aD^bH^c was selected for the two-variable equation. The fit index of the former was 0.87-0.92, while that of the latter was 0.94-0.98, both of which showed a good fit. A new weight table was prepared using the optimal estimation formula, and it was compared and analyzed with a previous weight table. Analysis results showed that Gangwon pine had higher values in the previous weight table, while pines in the central region had higher values in the newly created weight table.

• Korean small business review
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• v.41 no.2
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• pp.25-50
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• 2019

Although Korean government has implemented size-dependent policy, so called "the designation of SMEs-suitable industry", promoting SMEs growth, our understanding in the effectiveness of the policy is limited. We investigate the effect of the policy on SMEs performance in food product and beverages industry, which accounts for the majority in the SMEs-suitable industry. From the perspective of sales, profitability, and R&D intensity, which is regarded as indigenous effort for growth, we find the heterogeneity in the effectiveness of the policy across the sub-sectors in the industry. However, overall the policy does not significantly contribute to the growth of sales, profitability, and facilitation of R&D activity for indigenous innovative efforts of SMEs. Our study advances the theoretical discussion on the effect of the policy with the disaggregated level of analysis, i.e, sub-sector level. Our findings also contribute to the resolution of social and political conflicts between pros and cons of the policy. Our study suggests that policy makers should develop more sophisticated policy that incorporate the specific characteristics of individual sub-sectors. They also need to invest more resources in enhancing the effectiveness of the policy and accelerating SMEs innovative efforts.

• Information Systems Review
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• v.26 no.1
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• pp.193-218
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• 2024

This study identified factors related to the technological characteristics of conversational generative AI services and the user's task characteristics. Then, it analyzed the effects of task-technology fit on user satisfaction and continued use. The effects of trust, which represents the degree of users' belief in the information provided by generative AI, on task-technology fit, user satisfaction, and user continuance intention were also examined. A survey was conducted among users of various age groups, and 198 questionnaires were collected and analyzed using SmartPLS 4.0 to validate the proposed model. As a result of hypothesis testing, it was confirmed that language fluency and interactivity among technology characteristics and ambiguity among task characteristics significantly affect user satisfaction and intention to continue using via task-technology fit. However, creativity among skill characteristics and time flexibility among task characteristics did not significantly affect task-technology fit, and trust did not directly affect task-technology fit and intention to continue using, but only positively affected user satisfaction. The results of this study can provide meaningful implications for vendors who want to develop and provide conversational generative AI services or companies who want to adopt generative AI technology to improve business productivity.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.535-542
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• 2001

The objective of this study is to develop a spatial analysis modeling technique to evaluate the functional suitability of forest lands for land slide prevention. The functional suitability is classified into 3 categories of high, medium and low according to the potential of land slide on forest lands. The potential of land slide hazards is estimated using the measurements of 7 major site factors : slope, bed rock, soil depth, shape of slope, forest type and D.B.H. class of trees. The analytic hierarchical process is applied to determining the relative weight of site factors in estimating the potential of land slides. The spatial analysis modeling starts building base layers for the 7 major site factors by $25m{\times}25m$ grid analysis or TIN analysis, reclassifies them and produces new layers containing standardized attribute values, needed in estimating land slide potential. To these attributes, applied is the weight for the corresponding site factor to build the suitability classification map by map algebra analysis. Then, finally, cell-grouping operations convert the suitability classification map to the land unit function map. The whole procedures of the spatial analysis modeling are presented in this paper.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.480-488
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• 2018

The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.857-866
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• 2009

In this study, basic data is consisted annual maximum rainfall at 56 stations that has the rainfall records more than 30years in Korea. The 14 probability distributions which has been widely used in hydrologic frequency analysis are applied to the basic data. The method of moments, method of maximum likelihood and probability weighted moments method are used to estimate the parameters. And 4-tests (chi-square test, Kolmogorov-Smirnov test, Cramer von Mises test, probability plot correlation coefficient (PPCC) test) are used to determine the goodness of fit of probability distributions. This study emphasizes the necessity for considering the variability of the estimate of T-year event in hydrologic frequency analysis and proposes a framework for evaluating probability distribution models. The variability (or estimation error) of T-year event is used as a criterion for model evaluation as well as three goodness of fit criteria (SLSC, MLL, and AIC) in the framework. The Jackknife method plays a important role in estimating the variability. For the annual maxima of rainfall at 56 stations, the Gumble distribution is regarded as the best one among probability distribution models with two or three parameters.

• Journal of Embryo Transfer
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• v.18 no.3
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• pp.215-225
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• 2003

This study was carried out to investigate the change of blood compositions by age in Hanwoo, and a total of 866 of Hanwoo, which consisted with 638 of steer and 228 of bulls, were used to measure serum concentrations. A multiple regression equation was estimated with collection age and blood composition as independent and dependent variables, respectively. Complicated regression equations for blood compositions in steer and bulls were IGF-I(cubic), calcium (linear), and IP(linear). Linear and cubic equations were fitted to testosterone in steer and creatinine in bulls, respectively. A cubic equation in steer and linear equation in bulls were fitted to HDLC. Equations of quadratic in steer and cubic in bulls were fitted to concentration of triglyceride, globulin, and A/G ratio. BUN was fitted by equations of cubic in steer and quadratic in bulls. TP and albumin were fitted by equations of quadratic in steer and linear in bulls. A cubic regression equation did not explain the change of cortisol by age in steer and bulls. A cubic regression equation did explain the change of glucose by age in steer, but not in bulls. Higher R-square values (R-SQUARE>0.1) were estimated to IGF-1, albumin, creatinine, Inorganic phosphorous(IP) and HDLC in steer, and testosterone, IGF-I, TP, albumin, glucose, creatinine, IP, and HDLC in bulls for the fitted regression equations of blood compositions. Therefore, IGF-I, albumin, creatinine, IP, and HDLC were regarded as comparatively large variation by age in steer and bulls.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.121-128
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• 2005

Forest fire is expanded to large-scale forest fire based on topographic characteristics, particularly slope. This report addresses the currently available methods of calculation slope angle from a digital elevation model and develops a new method that circumvents a number of the shortcomings associated with other algorithms. The results of the comparison of five different slope angle calculation algorithms show that maximum uphill slope angle calculation is the proper method for the purpose of predicting forest fire hazard.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.94-102
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• 2016

The purpose of this study was to investigate the effect of corporate association of sports equipment companies on brand trust, and brand loyalty. The subjects were college student and 400 data were collected and 385 of them were chosen as for final data analysis. Data analysis were conducted using frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis and structural equation modeling with SPSS 22.0 and AMOS 22.0. Based on the above study method and procedures, the results of the study are summarized as follows: First, corporate ability association and corporate social responsibility association had a positive effect on brand trust. Second, brand trust had a positive effect on brand loyalty.