• Journal of Global Scholars of Marketing Science
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• v.20 no.2
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• pp.123-134
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• 2010

Considering the benefits for both consumers and suppliers, firms are taking advantage of the Internet as a medium to communicate with and sell products to their consumers. This trend makes the online shopping environment a growing field for both researchers and practitioners. This paper contributes by testing a model of online consumer behavior with websites varying in levels of hedonism. Unlike past studies, we included all three types of emotions (arousal, pleasure, and dominance) and flow into the model. In this study, we assumed that website interfaces, such as background colors, music, and fonts impact the three types of emotions at the initial exposure to the site (Mazaheri, Richard, and Laroche, 2011). In turn, these emotions influence flow and consumers' perceptions of the site atmospherics-perception of site informativeness, effectiveness, and entertainment. This assumption is consistent with Zajonc (1980) who argued that affective reactions are independent of perceptual and cognitive operations and can influence responses. We, then, propose that the perceptions of site atmospherics along with flow, influence customers' attitudes toward the website and toward the product, site involvement, and purchase intentions. In addition, we studied the moderating impact of the level of hedonism of websites on all the relationship in the model. Thus, the path coefficients were compared between "high" and "low" hedonic websites. We used 39 real websites from 12 product categories (8 services and 4 physical goods) to test the model. Among them, 20 were perceived as high hedonic and 19 as low hedonic by the respondents. The result of EQS 6.1 support the overall model: $\chi^2$=1787 (df=504), CFI=.994; RMSEA=.031. All the hypotheses were significant. In addition, the results of multi-groups analyses reveal several non-invariant structural paths between high and low hedonic website groups. The findings supported the model regarding the influence of the three types of emotions on customers' perceptions of site atmospherics, flow, and other customer behavior variables. It was found that pleasure strongly influenced site attitudes and perceptions of site entertainment. Arousal positively impacted the other two types of emotions, perceptions of site informativeness, and site involvement. Additionally, the influence of arousal on flow was found to be highly significant. The results suggested a strong association between dominance and customers' perceptions of site effectiveness. Dominance was also found to be associated with site attitudes and flow. Moreover, the findings suggested that site involvement and attitudes toward the product are the most important antecedents of purchase intentions. Site informativeness and flow also significantly influenced purchase intentions. The results of multi-group analysis supported the moderating impacts of hedonism of the websites. Compared to low (high) hedonic sites, the impacts of utilitarian (hedonic) attributes on other variables were stronger in high (low) hedonic websites. Among the three types of emotions, dominance (controlling feelings) effects were stronger in high hedonic sites and pleasure effects were stronger in low hedonic sites. Moreover, the impact of site informativeness was stronger for high hedonic websites compared to their low-hedonic counterparts. On the other hand, the influence of effectiveness of information on perceptions of site informativeness and the impact of site involvement on product attitudes were stronger for low hedonic websites than for high hedonic ones.

• Journal of Animal Science and Technology
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• v.51 no.5
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• pp.345-352
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• 2009

This study utilized 332,625 records of linear type scores consisting for 15 primary traits, 22,175 final score and 84,612 pedigree information of 22,175 Holstein cows from 1993 to 2007 in Korea to estimate genetic parameters for 16 type traits. Genetic and error (co)variances between two traits selected from 16 traits were estimated using bi-trait pairwise analyses with DFREML package. The estimated heritabilities for stature (ST), strength (STR), body depth (BD), dairy form (DF), rump angle (RA), thurl width (TW), rear legs side view (RLSV), foot angle (FA), fore udder attachment (FUA), rear udder height (RUH), rear udder width (RUW), udder cleft (UC), udder depth (UD), front teat placement (FTP), front teat length (FTL) and final score (FS) were 0.31, 0.21, 0.25, 0.10, 0.29, 0.19, 0.09, 0.06, 0.12, 0.13, 0.12, 0.08, 0.26, 0.20, 0.28 and 0.15, respectively. ST had the highest positive genetic correlation with BD (0.90), while RLSV had the highest negative genetic correlation with FA (-0.56). RA had negative genetic correlation with most udder traits (-0.17~-0.02). Especially, RUW had the higher positive genetic correlation with STR (0.60), BD (0.62), and TW (0.49), however, UD had the higher negative genetic correlation with STR (-0.40) and BD (-0.40). FTL had negative genetic correlation with FUA, RUH, RUW, UC and UD. FS had positive genetic correlation with UC, UD and FTP (0.12, 0.18 and 0.20). However, additional research is needed on the use of these parameters in the genetic evaluation because estimated genetic and error variance-covariance matrices were not positive definite.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.391-400
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• 2015

In order to investigate the distribution and species composition of fish in shallow wetlands that might be affected by environmental factors, we investigated the physicochemical parameters, macrophytes biomass, and fish assemblage in 24 shallow wetlands in South Korea from May to June, 2012. In this study, a total of 20 fish species were identified, and Cypinidae were found to be the most dominant species. Physicochemical parameters and macrophyte biomass were different in the survey sites, and macrophytes biomass, in particular, showed a positive relationship with fish abundance in stepwise multiple regression (df=1, F=32.00, P=0.001). According to the result of the cluster analysis between survey sites, the survey sites were divided into three groups in accordance with species composition of fish in relation to macrophytes biomass. In the wetlands of the first group, Lepomis macrochirus which belongs to Centrarchidae was found to be dominant and other fish assemblages were hardly seen. In the second group, unlike the first group, Carassius auratus that belongs to Cypinidae was found to be dominant. In the third group, Lepomis macrochirus was found to be as dominant as the first group but various other fish species appeared. Where there was abundance of the main food sources (i. e. zooplankton) of fish in the survey sites, there were more diverse macrophyte biomass. Consequently, it is proven that macrophytes strongly affect the species composition and abundance of fish, and high biomass of macrophytes support high assemblage of fish. Based on these results, we recommend establishing diverse aquatic macrophytes communities when restoring or creating wetlands to assure high diversity of fish species that use macrophytes as their habitat.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Korean Journal of Social Welfare
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• v.51
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• pp.29-61
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• 2002

This study was designed to find out the determinants of types of bullying behavior, and the effects of types of bullying behavior on the bullies. For this purpose, a hypothetical model which explains the relationships among 6 environmental factors, 5 types of bullying behavior, and 5 outcome variables for the bullies was developed. Using the data collected from 177 junior and high school students who have bullied the other students, the hypothetical model was tested. For data analysis, a path analysis was used, and the best-fitting model was found (df=78, GFI=0.953, CFI=1.00). As a result of analyzing the model, types of bullying behavior were found to be determined by the different environmental factors: Isolation was determined by 2 factors (feeling of isolation from friends, exposure to bullying), social bullying by 2 factors (lack of support from parents, exposure to bullying), verbal bullying by conflicts with parents, physical bullying by 3 factors (lack of support from parents, exposure to isolation and exposure to bullying), and instrumental bullying by lack of support from parents. On the other hand, the pleasure that the bullies feel after bullying behavior was increased by isolation, verbal bullying and physical bullying, while decreased by instrumental bullying. Guilt feeling was decreased by isolation and instrumental bullying, while increased by physical bullying. Isolation increased the tendency of blaming the victim. Isolation and instrumental bullying increased bullies' self-esteem, while social bullying decreased self-esteem. Verbal bullying increased the extent of bullying, while instrumental bullying decreased the extent of bullying. Based on the findings, the intervention strategies to change the bullies' attitudes toward victim, and to increase social support from the significant others as well as the effective ways to reorganize the school environment in order to reduce and prevent bullying behavior were suggested.

• Journal of vocational education research
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• v.37 no.2
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• pp.39-75
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• 2018

The purpose of this study is to verify the general characteristics in the previous studies and the magnitude of the correlation between the learner's satisfaction and the academic achievement in the education and training program. To do this, we searched relevant literature from 2000 to 2016, and conducted a systematic review of the literature on the final 31 studies through the selection criteria and quality evaluation. Among them, 27 meta-analysis of the literature was conducted. The finding of the study were as follows. First, a total of 31 studies were conducted from 2000 to 2016, and more than half of them(16) were conducted for the last 4 years(2009~2012). In terms of education and training students, there are 18 college students, 9 workers, and 4 elementary students in order of study. In terms of methods, 15 collective education, 14 distance education, 2 blended education. In terms of learner's participation, 22 the general participation, 9 the active participation. Second, as a result of the meta-analysis, the magnitude of the correlation between satisfaction and achievement was moderate(ZCOR=.297, 95%: CI .210~.383). Third, as a result of verifying the difference in the magnitude of the correlation effect between satisfaction and achievement according to the characteristics of the education and training program, there was no difference between the groups in the student object and education method, but there was a difference in the magnitude of the correlation effect depending on the participant type(Q=15.40, df=1, p<.0001). The active participation showed a correlation effect size larger(ZCOR=.588, 95%: CI .422~.754). The effect size of the general participation was lower than the median(ZCOR=.211, 95%: CI .12 ~.300).

• Korean Journal of Environment and Ecology
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• v.36 no.6
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• pp.566-574
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• 2022

Heavy metals are one of the dangerous pollutants that threaten urban biodiversity due to their accumulation over a long period without being decomposed in vivo. Accordingly, there is a need for biological monitoring to compare accumulation concentrations in living organisms according to the degree of heavy metal exposure to evaluate heavy metal contamination in the air in urban areas. This study aims to examine the possibility of using nesting materials as heavy metal monitoring samples and determine the effects of heavy metals on Paridae. We installed 54 artificial nest boxes in the research areas that included campus green spaces (14), urban forests (11), and urban parks (29) on a university campus in Cheonan City, Chungcheongnam Province. The birds' use rate of artificial nest boxes was 11/14 (78.57%) in campus green spaces, 8/11 (72.72%) in urban forests, and 6/29 (20.68%) in urban parks. Moss materials were collected from collected nests, and the heavy metal accumulation characteristics of each type of urban green space and the effects of heavy metals on the success of fledging of Paridae were compared through heavy metal analysis. The analysis showed that the average concentrations of zinc and lead were 228.08±209.62 ㎍/dry g and 17.67 ± 6.72 ㎍/dry g, respectively. There was no significant difference in zinc concentration for each type of urban green space (Kruskal-Wallis test, p-value=0.28), but lead concentration showed a significant difference (Kruskal-Wallis test, p<0.05^*). Of the 21 Paridae, nests analyzed for heavy metals, fledging of birds was observed in 11 nests (52.38%). Fledging of birds observed in each urban green space type was 7 campus green spaces (77.78%), 6 in urban forests (85.71%), and 1 in urban park (20%), mainly in urban forests and green spaces on campus. Heavy metal concentrations were compared to check the effect of heavy metal accumulation on the successful fledging of Paridae, but there was no statistically significant difference (Zn: W=44, p-value=0.74, Pb: t=0.64676, df =7.2422, p-value=0.54). This study is a basic study using the nesting materials of Paridae as heavy metal monitoring samples, and it is determined that it can be used as basic data for non-invasive biological monitoring.

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.222-238
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• 2024

Coniferous species in subalpine ecosystems are known to be highly sensitive to climate change. Therefore, it is becoming increasingly important to monitor community and population dynamics. This study monitored 37 plots within the distribution area of Abies koreana on Mt. Jirisan for a period of eight years. We analyzed the importance value, density of living stems, mortality rate, recruitment rate, basal area, DBH (diameter of breast height) class distribution, and tree health status. Our results showed changes in the importance value based on the tree stratum, with A. koreana decreasing by 3.6% and Tripterygium regelii increasing by 2.5% in the tree layer. Between 2015 and 2023, there were 149 dead trees/ha (17.99% mortality rate) and 12 living trees/ha (1.02% recruitment rate) of A. koreana. The decrease in basal area was attributed to a decrease in the number of living trees. Tree mortality occurred in all DBH classes, with a particularly high decline in the <10 cm class (65 trees/ha reduced). In terms of changes in tree health status, the population of alive standing (AS) type trees, initially consisting of 539 trees/ha, has been transformed into alive standing (AS), alive lean (AL), and death standing (DS), accounting for 69.7%, 0.5%, and 13.8%, respectively. Meanwhile, DS-type trees have transitioned into dead broken (DB) and dead fallen (DF) types. This phenomenon is believed to be caused by strong winds in the subalpine region that pull up the rootlets from the soil. Further research on this finding is recommended.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.279-286
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• 2020

The objective of this study was to assess the impact of El Niño on highland kimchi cabbage production for the period from 1991-2016 in South Korea. Years with less than 1.0 Oceanic Niño index (ONI) were classified into non El Niño years, while years with equal to or greater than 1.0 ONI were defined as El Niño years. The national average production (3,444 kg 10a-1) of high kimchi cabbage in El Niño years tended to be less than that in non El Niño years (3,722 kg 10a-1) with significant differences (p = 0.0042) in the production between these groups of years. The averaged production of highland kimchi cabbage of El Niño end years (3,289 kg 10a-1) was less than those of El Niño start years and non El Niño years by 310 and 433 kg 10a-1, respectively. Such difference was significant statistically (p=0.035). According to our analysis, the differences in kimchi cabbage productions resulted from low temperature, short sunshine duration, and precipitation increase during the cultivation period of highland kimchi cabbage. This study may help for further analysis on the impact of extreme weather conditions during El Niño years on crop production.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.4 no.1
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• pp.97-101
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• 1968

Effects of weather factors on leaf tobacco yield were studied from the yield data of flue-cured yellow tobacco variety Yellow pryer and weather recordes for 13 years from 1952 to 1964. The results are summarized as follows; 1. Leaf tobacco yield variation was large and larger coefficient of variance was calculated. 2. Yield of leaf tobacco was correlated largely to leaf number, with simple correlation coefficient r=0.736. Leaf number was correlated largely to sunshine hours during May with r=0.745, and multiple correlation coefficient R=0.837 between leaf number and multiple weather factors during May to June. 3. Leaf tobacco yield was largely affected by the sunshine hours (r=0.717) and temperature (r=0.329) in May and precipitation (r=0.421) in June. 4. From the study of partial regression of leaf tobacco yield on weather factors a formulation Y=441.664-31.255$X_1$+1.19$Y_2$-0.031$X_3$ was calculated for the estimation of leaf tobacco yield. Here R=0.8074 d.f.=7 was significant.