• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.195-209
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• 2021

According to the 2019-2020 social media usage survey conducted by the Seoul e-commerce center, 5 out of 10 consumers have experienced shopping through social media. The cost of traditional advertising media has been reduced and advertising spending on social media has risen by 74%, indicating that social media is becoming a more important marketing element. While the number of users of social media has increased and corporate marketing activities have increased accordingly, research has been conducted in various aspects of marketing such as user motivation for social media, satisfaction, and purchase intention. There was no subdivided study on the differences in the social media usage frequency of consumers in actual purchasing behavior. This study attempted to identify differences in consumer characteristics by cluster in the agrifood purchase situation by grouping them by type according to the frequency of use of social media for consumers who purchase agri-food online. Product involvement, product need, and online purchase channel Consumer characteristics such as demographic distribution, perceived risk, and eating and lifestyle in each cluster were checked for the three agrifood purchase situations including choice, and types for each cluster were presented. To this end, questionnaire data on the frequency of social media use and online agrifood purchase behavior were collected from 245 consumers, and the validity of the measurement variables was secured through factor analysis and reliability analysis. As a result of cluster analysis according to the frequency of social media use, it was divided into three clusters. The first cluster was a group that mainly used open social media, and the second cluster was a group that used both open and closed social media and online shopping malls; The third cluster was a group with low online media usage overall, and the characteristics of each cluster appeared. Through regression analysis, the effect on product involvement, product need, and purchase channel selection when purchasing agri-food online through each of the three clusters was confirmed through regression analysis. As a result of the regression analysis, the characteristic of cluster 1 in the situation of purchasing agri-food online is a male in his 30s living in a rural area who has no reluctance to purchase agri-food on social media or online shopping malls. The characteristics of cluster 2 are mainly consumers who are interested in purchasing health food, and the consumer characteristics are represented. In the case of cluster 3, when purchasing products online, they purchase after considering quality and price a lot, and the consumer characteristics are represented as people who are more confident in purchasing offline than online. Through this study, it is judged that by identifying the differences in consumer characteristics that appear in the agri-food purchase situation according to the frequency of social media use, it can be helpful in strategic judgments in marketing practice on social media customer targeting and customer segmentation.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• Journal of Industrial Convergence
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• v.1 no.1
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• pp.41-70
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• 2003

Many researches on brand equity have been focused in definition about it, factors of it, and the process of formation. Most of them have been used by voluntary production category, as is durable goods or nondurable goods. But this study, using the model is developed by Foote, Cone & Be1ding(FCB) Company, classified four fields, high-low involvement, rationality(rational or sensitive) involvement. The selected goods is a sensitive high involvement(casual wear). This study investigate the effects of brand equity and search the influences of brand equity formation according to factors of marketing mix. To this goals, this study kept a literature survey and a demonstrative research. In literature survey, there are several definitions of brand and brand equity. The research model is derived from selected factors of marketing mix and former study. This study used the regression analysis to verify effects from brand equity through the selected marketing mix. The research data is collected from the capital area. The focus of this study is effects of brand equity according to marketing mix. The followings are results and suggestions of this study. First, in the price factors, the affirmative effects are revealed the perceived quality and the brand awareness in a rational high involvement goods, the perceived quality and the brand associations in a sensitive high involvement goods, all factors of brand equity in a rational low involvement goods, and the perceived quality in a sensitive low involvement goods. As summary, the important characteristics is the price factors to consumers, and consumers recognize that a high price means a high quality. Second, in the store image factors, the affirmative effects are revealed all brand equity factors in a rational high involvement and a sensitive high-low involvement. A good store image incites more interest, contact, and visit from potential consumer. And such store offers more consumer satisfaction, simulates more active and positive conversation to consumers. Third, in advertising spending factors, the affirmative effects are revealed the brand awareness and associations in a rational high involvement and a sensitive high involvement, all brand equity factors in a rational low involvement and a sensitive low involvement. An advertisement increases not only a brand awareness but also strong brand associations. Forth, in price promotion factors, the affirmative effects are revealed the brand associations in a rational high involvement, the negative effects are revealed all brand equity in sensitive high involvement. According the result about the effects of brand royalty through the brand equity factors, a perceived quality and brand associations have positive effects to brand royalty in all factors. Consumers choice a deep perceived quality than other competitive brand. So, brand equity will increase according to a qualitative grade of a perceived brand by consumers. Brand associations represent a quality and a degree of involvement. In conclusion, brand associations and equity have a positive relation each other. According to the analysis results about a brand royalty of selected marketing mix factors, the affirmative effects are revealed the store image and price promotion factors in a rational high involvement, the price and store image in a sensitive high involvement, and the price and advertising spending in a rational low involvement. The results about the affect of selected marketing mix factors according to brand equity, are the perceived quality in a high involvement, and all brand equity factors in a low involvement. The affirmative effects about a store image are revealed all equity factors in high-low involvement. In advertising spending factors, the affirmative effects are revealed the brand awareness and associations in a high involvement goods, and the perceived quality and the brand awareness in a low involvement goods. In price promotion factors, the affirmative effects are revealed the brand awareness in a low involvement goods, and the negative effects are revealed the brand awareness in a high involvement goods. According to a degree of involvement, the results of a brand royalty through a brand equity factors are following. The affirmative effects are revealed the perceived quality and the brand royalty in a high involvement goods, and the brand awareness are revealed a negative effect. The affirmative effects are revealed the perceived Quality and the brand associations in a low involvement goods. So, in a high involvement goods, the brand royalty is built by strong brand associations, but, in a low involvement goods, the brand royalty is built also by a perceived Quality and a brand awareness. This study have some concept of limitation. So, this study presents a future direction of research. First, a future study has to have more deep analysis for this study analyzed through a limited marketing mix factors. Second, a future research has to get mutual effects about brand equity of marketing mix factors for this study has an individual marketing decision factors. Third, for the future, a brand equity needs a research about a several goods such as services, profit or nonprofit, industrial products, culture, and so on. Forth, the research have to diversify a various data for population.

• Korean Journal of Psychosomatic Medicine
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• v.26 no.2
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• pp.77-85
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• 2018

Objectives : This study aimed to investigate the level of distress using the distress thermometer (DT) and the factors associated with distress in postoperative breast cancer (BC) patients. Methods : DT and WHOQOL-BREF (World Health Organization Quality of Life Scale Abbreviated Version) along with sociodemographic variables were assessed in patients undergoing surgery for their first treatment of BC within one week postoperatively. The distress group consisted of participants with a DT score ${\geq}4$. The prevalence and associative factors of distress were examined by descriptive, univariable, and logistic regression analysis. Results : Three hundred seven women were recruited, and 264 subjects were finally analyzed. A total of 173 (65.5%) were classified into the distress group. The distress group showed significantly younger age (p=0.045), living without a spouse (p=0.032), and worse quality of life (QOL) as measured by overall QOL (p=0.009), general health (p=0.005), physical health domain (p<0.000), and psychological health domain (p=0.002). The logistic regression analysis showed that patients aged 40-49 years were more likely to experience distress than those aged ${\geq}60years$ (Odds ratios [OR]=2.992, 95% confidence interval [CI] 1.241-7.215). Moreover, the WHOQOL-BREF physical health domain was a predictive factor of distress (OR=0.777, 95% CI 0.692-0.873). Conclusions : A substantial proportion of patients are experiencing significant distress after BC surgery. It would be expected that distress management, especially in the middle-aged patients and in the domain of physical QOL (e.g., pain, insomnia, fatigue), from the early BC treatment stage might reduce chronic distress.

• Journal of the Korean Applied Science and Technology
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• v.35 no.4
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• pp.1456-1471
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• 2018

This article discusses the nutritional requirements, reviews senior or geriatric dog nutritional evaluation, and then addresses some common nutrition-related problems in older dogs. The purpose of this study was to investigate the Physiologic change associated with aging, essential nutrients and their diseases in senior or geriatric dog subjects. According to a 2002 market research, 30% to 40% of dogs raisedin the United States are 7 years of age. In Europe the number of dogs considered to be "senior or geriatric" (>7 years of age) increased by approximately 50% between 1983 and 1995. A 2012 e-mail survey of 50,347 respondents revealed that 33.2% of dogs were 6 to 10 years of age and 14.7% were older than 11 years in the United States. The average life expectancy of dogs raised in the home is affected by health care, aging and nutrition.And, the aging process is influenced by breed size, genetics, nutrition, environment, and other factors. Although many pets remain active and youthful well into their teens, most dogs start to slow down and may show signs of aging beginning as early as 5 or 6 years of age. Improvements in the control of various diseases and in the nutrition of dogs have resulted in a gradual increase in the average lifespan of companion dogs. Nutritional goals for aging dogs include supporting health and vitality, preventing the onset or slowing the progression of age-related health disorders, and enhancing the dog's quality of life and, if possible, life expectancy. Aging brings with its physiologicchanges. Some changes are obvious, such as whitening of hair, a general decline in body and coat condition, and failing senses including sight and hearing. Other changes are less obvious, however, and these include alterations in the physiology of the digestive tract, immune system, kidneys, and other organs. Nutritional requirements can change with age. In addition, many diseases common in older dogs may be nutrient-sensitive, meaning that diet can play an important role in the management of the condition.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.163-172
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• 2019

The USLE P factor is a factor that varies depending on how croplands are managed and cultivated. Previous studies tend to overestimate the amount of soil loss because the factor was estimated from the slope of the watershed rather than the estimate of each cultivated land. In addition, the accuracy of estimating the soil loss is decreasing due to the fact that the factor is calculated without considering various conditions of cultivated land defined by Wishmeier and Smith. In order to overcome these problems, the Ministry of Environment (MOE) has proposed to establish the topsoil notification and calculate the P factor according to the cultivation methods (e.g., tillage system, support practice). However, it is required to apply the conditions proposed in the United States to domestic circumstances as it is causing uncertainties. Thus, this study selected the watersheds where soil loss was serious (Haean, Jaun, Banbyeoncheon), measured the actual slopes and slope lengths, and examined the crop, tillage systems, and support practice for each cultivated land. The P factors were recalculated considering the actual conditions of cultivated land and compared to the factors proposed by the previous studies (MOE). As the result of the study, the P factors calculated based on the previous studies were 0.8 ~ 1.0 in three watersheds. On the other hand, it is confirmed that there is a significant difference between the factors notified by MOE and estimated by reflecting the topography and cultivation methods in this study. Therefore, it is considered that the research for developing the cultivation conditions to calculate the P factor suitable for the domestic environment should be continuously carried out.

• Korean Journal of Comparative Education
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• v.27 no.4
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• pp.187-209
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• 2017

The purpose of this study was to highlight the necessity of a conceptual reestablishment of world university evaluations. The hitherto most well-known and validated world university evaluation systems such as Times Higher Education (THE), Quacquarelli Symonds (QS) or Academic Ranking of World Universities (ARWU) primarily assess big universities with quantitative evaluation indicators and performance results in the rankings. Those Systems have instigated a kind of elitism in higher education and neglect numerous small or local institutions of higher education, instead of providing stakeholders with comprehensive information about the real possibilities of tertiary education so that they can choose an institution that is individually tailored to their needs. Also, the management boards of universities and policymakers in higher education have partly been manipulated by and partly taken advantage of the elitist ranking systems with an economic emphasis, as indicated by research-centered evaluations and industry-university cooperation. To supplement such educational defects and to redress the lack of world university evaluation systems, a new system called 'U-Multirank' has been implemented with the financial support of the European Commission since 2012. U-Multirank was designed and is enforced by an international team of project experts led by CHE(Centre for Higher Education/Germany), CHEPS(Center for Higher Education Policy Studies/Netherlands) and CWTS(Centre for Science and Technology Studies at Leiden University/Netherlands). The significant features of U-Multirank, compared with e.g., THE and ARWU, are its qualitative, multidimensional, user-oriented and individualized assessment methods. Above all, its website and its assessment results, based on a mobile operating system and designed simply for international users, present a self-organized and evolutionary model of world university evaluation systems in the digital and global era. To estimate the universal validity of the redefinition of the world university evaluation system using U-Multirank, an epistemological approach will be used that relies on Edgar Morin's Complexity Theory and Karl Popper's Philosophy of Science.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.177-188
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• 2021

On December 2015, Financial Supervisory Service(FSS) announced the four key thematic audit review areas, one of them is an appropriation of unbilled revenue. Accounting of unbilled revenue is intertwined with a percentage of completion, that is concerned about discretionary decision by manager. Therefore, if manager motivated by income-increasing manipulation is exaggerating percentage of completion, unbilled revenue is excessively recognized. This problem is caused the serious accounting issues(e.g., shock at a loss for 2013 fiscal year by some construction firms, malpractice of accounting in order-made production industry). Distrust of accounting was grown because the shipbuilding and construction industries successively went poor management and bad accounting of them is revealed. Those accounting issues were the trigger for problem recognition of unbilled revenue, they were background for the designation of appropriation unbilled revenue as thematic audit review areas by FSS. Therefore, this study verified effectiveness of thematic audit review by empirically analyzing whether designation of thematic audit review makes the firm increases conservative behavior. Conservative accounting is estimated by using Basu(1997) model. We analyzed the effect of the thematic audit review on conservative accounting of unbilled revenue by comparing with reflecting unbilled revenue or not. The sample for test consists of firm-years the manufacturing and construction industries from 2012 to 2017. The test results of this study suggested that the conservative accounting of unbilled revenue after designation of the thematic audit review was significantly increased. We also tested again by classifying whether or not it is construction industry. We found that construction industry is more conservative than the other industry only for the designated year of the thematic audit review, otherwise there was not any evidence for significantly increasing conservatism. This study contributes to the literature by empirically analysing relationship of the unbilled revenue to the thematic audit review from the perspective of the conservatism and verifying effectiveness of the thematic audit review.

• Journal of Bio-Environment Control
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• v.30 no.1
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• pp.1-9
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• 2021

This study was conducted to examine the changes of photosynthesis, growth, chlorophyll contents and functional material contents in light intensity and EC concentration of wild baby leaf vegetable, Indian lettuce (Lactuca indica L. cv. 'Sunhyang') in DFT hydroponics. The cultivation environment was 25±1℃ of temperature and 60±5% of relative humidity in growth system. At 14 days after sowing, combination effect of light intensity (Photosynthetic Photon Flux Density (PPFD 100, 250, 500 µmol·m-2·s-1) and EC level (EC 0.8, 1.4, 2.0 dS·m-1) of nutrient solution was determined at the baby leaf stage. The photosynthesis rate, stomatal conductance, transpiration rate and water use efficiency of Indian lettuce increased as the light intensity increased. The photosynthesis rate and water use efficiency were highest in PPFD 500-EC 1.4 and PPFD 500-EC 2.0 treatment. The chlorophyll content decreased as the light intensity increased, but chlorophyll a/b ratio increased. Leaf water content and specific leaf area decreased as light intensity increased and a negative correlation (p < 0.001) was recognized. Plant height was the longest in PPFD 100-EC 0.8 and leaf number, fresh weight and dry weight were the highest in PPFD 500-EC 2.0. Anthocyanin and total phenolic compounds were the highest in PPFD 500-EC 1.4 and 2.0 treatment, and antioxidant scavenging ability (DPPH) was high in PPFD 250 and 500 treatments. Considering the growth and functional material contents, the proper light intensity and EC level for hydroponic cultivation of Indian lettuce is PPFD 500-EC 2.0, and PPFD 100 and 250, which are low light conditions, EC 0.8 is suitable for growth.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.