• Asia-Pacific Journal of Business
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• v.15 no.3
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• pp.81-100
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• 2024

Purpose - This study investigates the direct effects of national governance quality on international logistics activities. The results provide practical insights for different stakeholders such as policymakers and offer detailed recommendations for improving national governance quality in projects aimed to enhance cross-border logistics operations. Design/methodology/approach - To test the hypotheses, a multivariate linear regression model using the ordinary least squares estimator is applied to 166 countries covering six periods: 2007, 2010, 2012, 2014, 2016, and 2018. Findings - All national governance indicators have a significant positive influence on the performance of cross-border logistics operations. At the dimensional level, government effectiveness, legal systems, anti-corruption efforts and regulatory quality have a greater impact than democracy and a stable political environment on all dimensions of logistics performance. Research implications or Originality - This study sheds light on how the quality of governance directly affects trading logistics. It advises governments to enhance governance quality and nurture a supportive institutional environment to improve transnational logistics proficiency. It also provides a better understanding of the institutional backgrounds of international logistics companies in target countries before their performance plans.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.321-328
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• 2009

In regression analysis, the ordinary least squares estimates of regression coefficients become poor, when the correlations among predictor variables are high. This phenomenon, which is called multicollinearity, causes serious problems in actual data analysis. To overcome this multicollinearity, many methods have been proposed. Ridge regression, shrinkage estimators and methods based on principal component analysis (PCA) such as principal component regression (PCR) and latent root regression (LRR). In the last decade, many statisticians discussed sensitivity analysis (SA) in ordinary multiple regression and same topic in PCR, LRR and logistic principal component regression (LPCR). In those methods PCA plays important role. Many statisticians discussed SA in PCA and related multivariate methods. We introduce the method of PCR and LRR. We also introduce the methods of SA in PCR and LRR, and discuss the properties of SA in PCR and LRR.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.815-826
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• 2012

The underestimating trend using existing ordinary regression (OR) based trend analysis has been a well-known problem. The existing OR method based on least squares approximate the conditional mean of the response variable given certain values of the time t, and the usual assumption of the OR method is normality, that is the distribution of data are not dissimilar form a normal distribution. In this regard, this study proposed a quantile regression that aims at estimating either the conditional median or other quantiles of the response variable. This study assess trend in annual daily maximum rainfall series over 64 weather stations through both in OR and QR approach. The QR method indicates that 47 stations out of 67 weather stations are a strong upward trend at 5% significance level while OR method identifies a significant trend only at 13 stations. This is mainly because the OR method is estimating the condition mean of the response variable. Unlike the OR method, the QR method allows us flexibly to detect the trends since the OR is designed to estimate conditional quantiles of the response variable. The proposed QR method can be effectively applied to estimate hydrologic trend for either non-normal data or skewed data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.51-66
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• 2022

SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

• The Journal of Fisheries Business Administration
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• v.40 no.1
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• pp.27-49
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• 2009

Recently, the Korea's economy concerns the second money crisis because of the rapid increase of the exchange rate. The Korea's economy which is very dependent on the foreign trade is more sensitive to the change of exchange rates. There are many literatures which analyze the effects of variations of the exchange rates on the secondary and tertiary industries such as the manufacturing industry and IT(Information Technology). But there have been no studies which try to figure out the effects of variations of exchange rate on the primary industries, especially, fisheries' industry. Therefore this paper tries to analyze the effect of price competition structure and the change of exchange rate on foreign fisheries exporting prices in Korea's fisheries import market. This study utilizes OLS(Ordinary Least Squares Analysis) for the analysis in the market of frozen yellow corvina, hairtail, angler fish which are major fisheries importable in Korea. The results show that the exporting country which has the highest market share is more sensitive to the change of the exchange rates itself than that of the other exporting countries' price when it starts to set up its exporting price. And the exporting countries which have low market share are more sensitive to the change of price which country has the highest market share than that of price whose countries have low market share and those of their exchange rate. Also we can find out that the countries which have similar market share try to set up price-setting strategy in the opposite direction. In other words, one country tries to bid up its price, other countries response to rival country by lowering their prices. In the consideration of the fact that most exporting countries aren't affected by Korea's fisheries' prices, the exporting countries in Korea's fisheries import market are more sensitive to the prices of other exporting countries than that of Korea's. This result indicates that the price leader-follower model could be applicable to the Korea's fisheries import market.

• Spatial Information Research
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• v.20 no.4
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• pp.1-16
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• 2012

There is no doubt that the urban heat island (UHI) is a mounting problem in built-up environments, due to energy retention by the surface materials of dense buildings, leading to increased temperatures, air pollution, and energy consumption. To investigate the UHI, three-dimensional (3-D) information is necessary to analyze complex sites, including dense building clusters. In this research, 3-D building geometry information is combined with two-dimensional (2-D) urban surface information to examine the relationship between urban characteristics and temperature. In addition, this research introduces spatial regression models to account for the spatial spillover effects of urban temperatures, and includes the following steps: (a) estimating urban temperatures, (b) developing a 3-D city model, (c) generating urban parameters, and (d) conducting statistical analyses using both Ordinary Least-Squares (OLS) and Spatial Regression Models. The results demonstrate that 3-D urban characteristics greatly affect temperatures and that neighborhood effects are critical in explaining temperature variations. Finally, the implications of the results are discussed, providing guidelines for policies to reduce the UHI.

• Journal of Distribution Science
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• v.16 no.12
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• pp.47-56
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• 2018

Purpose - The potential use of cryptocurrencies in a retail environment proposes a rapid shift from the traditional financial system. Nakamoto(2008) defines Bitcoin as an open source alt-coin based on the blockchain technology. Luther(2016) insists that the new technology will be widely adopted for the digital payment processes. However, the use of Bitcoin is in the real world is still sparse. Despite the growing attention and purported benefits, it is doubtful whether the Bitcoin will be eagerly accepted by ordinary consumers in the mainstream market. To answer this question, this paper develops a causal model that has a dual path to explain the motivation to adopt Bitcoin. According to Glaser, Zimmermann, Haferkorn, Weber, and Siering(2014), Bitcoin is both an asset and a currency at the same time. In summary, the attitude towards Bitcoin may vary depending on whether the fin-tech product is viewed as an asset or as a currency. Based on the arguments, we propose that asset attitude and currency attitude will give influence to consumers' intention to adopt Bitcoin. Research design, data, and methodology - Quantitative data collection is conducted from a Bitcoin SIG(special interest group) working in an internet community. As a result, 192 respondents who know Bitcoin completed the survey. To analyze the causal relations in the research model, PLS-SEM(partial least squares structural equation modeling) method is used. Also, reliability and validity of measures are tested by performing Cronbach's alpha test, Fornell-Larcker test and confirmatory factor test. Results - Our test results show that every hypothesis is supported except the influence of perceived ease of use. In addition, we find that the relationships between constructs are different between the high innovative group and low innovative group. Conclusions - We provide evidence that asset attitude and currency attitude are key antecedents of Bitcoin adoption.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.199-207
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• 2017

The business environment changing very fast with technology advance and convergence makes the role of R&D become more and more important to firms' success. By analyzing the 683 firm-level data of small and medium venture firms with the ordinary least squares regression, this study sheds new light on the following four points. First, small and medium venture firms' exterior R&D collaboration network heterogeneity positively impacts their import substitution from technology development. Second, the existence of the corporate R&D center moderates the positive impact of small and venture firms' exterior R&D collaboration network heterogeneity on their import substitution from technology development. Third, small and venture firms' exterior R&D information network heterogeneity positively impacts their import substitution from technology development. Fourth, The existence of the corporate R&D center moderates the positive influence of small and venture firms' exterior R&D information network heterogeneity on their import substitution from technology development.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.743-755
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• 2016

The objectives of this research is to examine: 1) how the rates of adolescents' BMI change over time in terms of the state level; and 2) development difference in the state level of BMI in terms of children's obesogenic behaviors from 1999 to 2011. Data were drawn from the 1999-2011 Youth Risk Behavior Survey in the United States (N=260, 293, grades 9-12, and 27 states). Ordinary least squares regression and hierarchical linear modeling were utilized to capture a longitudinal time effect of school-aged adolescents' obesity rates across the states, controlling for demographics and nutrition- and physical activity-related behaviors. The state's level of children's BMI percentile was significantly associated with longitudinal time. Longitudinal time effect across the states appears to play an important factor associated with children's decrease of BMI percentile. Therefore the states' implementation of physical activity and nutritional policies seems to be effective for preventing and reducing childhood obesity during last decade. More attention should focus on enforcing the policy and overcoming current barriers in order to minimize children's obesogenic factor.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.223-235
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• 2011

Although ordinary least squares (OLS) regression analysis can be used to examine the spatial relationships between environmental equity and urban quality of life, this global method may mask the local variations in the relationships between them. These geographical variations can not be captured without using local methods. In this context, this paper explores the spatially varying relationships between environmental equity and urban quality of life across the Atlanta metropolitan area by geographically weighted regression (GWR), a local method. Environmental equity and urban quality of life were quantified with an integrated approach of GIS and remote sensing. Results show that generally, there is a negatively significant relationship between them over the Atlanta metropolitan area. The results also suggest that the relationships between environmental equity and urban quality of life vary significantly over space and the GWR (local) model is a significant improvement on the OLS (global) model for the Atlanta metropolitan area.