• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.374-390
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• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.361-381
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• 2023

Research on corporate bankruptcy prediction has been focused on financial information. Since the company's financial information is updated quarterly, there is a problem that timeliness is insufficient in predicting the possibility of a company's business closure in real time. Evaluated companies that want to improve this need a method of judging the soundness of a company that uses information other than financial information to judge the soundness of a target company. To this end, as information technology has made it easier to collect non-financial information about companies, research has been conducted to apply additional variables and various methodologies other than financial information to predict corporate bankruptcy. It has become an important research task to determine whether it has an effect. In this study, we examined the impact of electronic payment-related information, which constitutes non-financial information, when predicting the closure of business operators using electronic payment service and examined the difference in closure prediction accuracy according to the combination of financial and non-financial information. Specifically, three research models consisting of a financial information model, a non-financial information model, and a combined model were designed, and the closure prediction accuracy was confirmed with six algorithms including the Multi Layer Perceptron (MLP) algorithm. The model combining financial and non-financial information showed the highest prediction accuracy, followed by the non-financial information model and the financial information model in order. As for the prediction accuracy of business closure by algorithm, XGBoost showed the highest prediction accuracy among the six algorithms. As a result of examining the relative importance of a total of 87 variables used to predict business closure, it was confirmed that more than 70% of the top 20 variables that had a significant impact on the prediction of business closure were non-financial information. Through this, it was confirmed that electronic payment-related information of non-financial information is an important variable in predicting business closure, and the possibility of using non-financial information as an alternative to financial information was also examined. Based on this study, the importance of collecting and utilizing non-financial information as information that can predict business closure is recognized, and a plan to utilize it for corporate decision-making is also proposed.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.173-187
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• 2023

The forest protection policies implemented in South Korea have resulted in the significant accumulation of forest. Moreover, the associated public interest has also been closely evaluated. As forests mature, there arises a need for forest management (FM) practices, such as thinning and harvesting. It is therefore essential to perform a scientific analysis of the long-term effects of FM. In this study, conducted in Mt. Gariwang, the effect of FM on forest succession and wood production (WP) were evaluated based on changes in aboveground biomass (AGB) using the LANDIS-II model. The FM consists of three scenarios (Selection, Shelterwood, and Two-stories), characterized based on the harvest intensity, frequency, and period. The model was applied to changes in the forest over 200 years. All scenarios show that the total AGB decreased immediately after thinning and harvesting. However, AGB recovery time differed among scenarios, with recovery to preharvest level occurring from 15 to 50 years after harvest; further, after 200 years, harvested forests had a greater total AGB than forests without FMs In particular, the changes in AGB of each species was different depending on its shade tolerance. The AGB of currently dominant shade-intolerant and mid-tolerant species decreased dramatically after harvesting. However, shade-tolerant species, dominant in the understory, continued to grow but were not harvested due to their small size. The cumulative WP for each scenario was estimated at 545.6, 141.6, and 299.9 tons/ha in Selection, Shelterwood, and Two-stories, respectively. The composition of WP differed according to harvest intensity and period. Most WP originated from shade-intolerant and mid-tolerant species in the early period. Later, most WP was from shade-tolerant species, which became dominant. The modeling approach used in this study is capable of analyzing the long-term effects of FM on changes in forests and WP. This study can contribute to decision making to guide FM methods for a variety of purposes, including WP and controlling forest composition and structure.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.174-189
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• 2015

The objective of this study was to reconstruct spatial information using the results of the investigation and evaluation of the health of the living organisms, habitat, and water quality at the investigation points for the aquatic ecosystem health of the Nakdong River basin, to support the rational decision making of the aquatic ecosystem preservation and restoration policies of the Nakdong River basin using spatial analysis techniques, and to present efficient management methods. To analyze the aquatic ecosystem health of the Nakdong River basin, punctiform data were constructed based on the position information of each point with the aquatic ecosystem health investigation and evaluation results of 250 investigation sections. To apply the spatial analysis technique, the data need to be reconstructed into areal data. For this purpose, spatial influence and trends were analyzed using the Kriging interpolation(ArcGIS 10.1, Geostatistical Analysis), and were reconstructed into areal data. To analyze the spatial distribution characteristics of the Nakdong River basin health based on these analytical results, hotspot(Getis-Ord Gi, $G^*_i$), LISA(Local Indicator of Spatial Association), and standard deviational ellipse analyses were used. The hotspot analysis results showed that the hotspot basins of the biotic indices(TDI, BMI, FAI) were the Andong Dam upstream, Wangpicheon, and the Imha Dam basin, and that the health grades of their biotic indices were good. The coldspot basins were Nakdong River Namhae, the Nakdong River mouth, and the Suyeong River basin. The LISA analysis results showed that the exceptional areas were Gahwacheon, the Hapcheon Dam, and the Yeong River upstream basin. These areas had high bio-health indices, but their surrounding basins were low and required management for aquatic ecosystem health. The hotspot basins of the physicochemical factor(BOD) were the Nakdong River downstream basin, Suyeong River, Hoeya River, and the Nakdong River Namhae basin, whereas the coldspot basins were the upstream basins of the Nakdong River tributaries, including Andong Dam, Imha Dam, and Yeong River. The hotspots of the habitat and riverside environment factor(HRI) were different from the hotspots and coldspots of each factor in the LISA analysis results. In general, the habitat and riverside environment of the Nakdong River mainstream and tributaries, including the Nakdong river upstream, Andong Dam, Imha Dam, and the Hapcheon Dam basin, had good health. The coldspot basins of the habitat and riverside environment also showed low health indices of the biotic indices and physicochemical factors, thus requiring management of the habitat and riverside environment. As a result of the time-series analysis with a standard deviation ellipsoid, the areas with good aquatic ecosystem health of the organisms, habitat, and riverside environment showed a tendency to move northward, and the BOD results showed different directions and concentrations by the year of investigation. These aquatic ecosystem health analysis results can provide not only the health management information for each investigation spot but also information for managing the aquatic ecosystem in the catchment unit for the working research staff as well as for the water environment researchers in the future, based on spatial information.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

• The Korean Nurse
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• v.36 no.1
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• pp.77-96
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• 1997

The duty shifts of hospital nurses not only affect nurses' physical and mental health but also present various personnel management problems which often result in high turnover rates. In this context a study was carried out from October to November 1995 for a period of two months to find out the status of hospital nurses' duty shift patterns, and preferred duty hours and fixed duty shifts. The study population was 867 RNs working in five general hospitals located in Seoul and its vicinity. The questionnaire developed by the writer was used for data collection. The response rate was 85.9 percent or 745 returns. The SAS program was used for data analysis with the computation of frequencies, percentages and Chi square test. The findings of the study are as follows: 1. General characteristics of the study population: 56 percent of respondents was (25 years group and 76.5 percent were "single": the predominant proportion of respondents was junior nursing college graduates(92.2%) and have less than 5 years nursing experience in hospitals(65.5%). For their future working plan in nursing profession, nearly 50% responded as uncertain The reasons given for their career plan was predominantly 'personal growth and development' rather than financial reasons. 2. The interval for rotations of duty stations was found to be mostly irregular(56.4%) while others reported as weekly(16.1%), monthly(12.9%), and fixed terms(4.6%). 3. The main problems related to duty shifts particularly the evening and night duty nurses reported were "not enough time for the family, " "afraid of security problems after the work when returning home late at night." and "lack of leisure time". "problems in physical and physiological adjustment." "problems in family life." "lack of time for interactions with fellow nurses" etc. 4. The forty percent of respondents reported to have '1-2 times' of duty shift rotations while all others reported that '0 time'. '2-3 times'. 'more than 3 times' etc. which suggest the irregularity in duty shift rotations. 5. The majority(62.8%) of study population found to favor the rotating system of duty stations. The reasons for favoring the rotation system were: the opportunity for "learning new things and personal development." "better human relations are possible. "better understanding in various duty stations." "changes in monotonous routine job" etc. The proportion of those disfavor the rotating 'system was 34.7 percent. giving the reasons of"it impedes development of specialization." "poor job performances." "stress factors" etc. Furthermore. respondents made the following comments in relation to the rotation of duty stations: the nurses should be given the opportunity to participate in the. decision making process: personal interest and aptitudes should be considered: regular intervals for the rotations or it should be planned in advance. etc. 6. For the future career plan. the older. married group with longer nursing experiences appeared to think the nursing as their lifetime career more likely than the younger. single group with shorter nursing experiences ($x^2=61.19.{\;}p=.000;{\;}x^2=41.55.{\;}p=.000$). The reason given for their future career plan regardless of length of future service, was predominantly "personal growth and development" rather than financial reasons. For further analysis, the group those with the shorter career plan appeared to claim "financial reasons" for their future career more readily than the group who consider the nursing job as their lifetime career$(x^2$= 11.73, p=.003) did. This finding suggests the need for careful .considerations in personnel management of nursing administration particularly when dealing with the nurses' career development. The majority of respondents preferred the fixed day shift. However, further analysis of those preferred evening shift by age and civil status, "< 25 years group"(15.1%) and "single group"(13.2) were more likely to favor the fixed evening shift than > 25 years(6.4%) and married(4.8%)groups. This differences were statistically significant ($x^2=14.54, {\;}p=.000;{\;}x^2=8.75, {\;}p=.003$). 7. A great majority of respondents(86.9% or n=647) found to prefer the day shifts. When the four different types of duty shifts(Types A. B. C, D) were presented, 55.0 percent of total respondents preferred the A type or the existing one followed by D type(22.7%). B type(12.4%) and C type(8.2%). 8. When the condition of monetary incentives for the evening(20% of salary) and night shifts(40% of. salary) of the existing duty type was presented. again the day shift appeared to be the most preferred one although the rate was slightly lower(66.4% against 86.9%). In the case of evening shift, with the same incentive, the preference rates for evening and night shifts increased from 11.0 to 22.4 percent and from 0.5 to 3.0 percent respectively. When the age variable was controlled. < 25 yrs group showed higher rates(31.6%. 4.8%) than those of > 25 yrs group(15.5%. 1.3%) respectively preferring the evening and night shifts(p=.000). The civil status also seemed to operate on the preferences of the duty shifts as the single group showed lower rate(69.0%) for day duty against 83. 6% of the married group. and higher rates for evening and night duties(27.2%. 15.1%) respectively against those of the married group(3.8%. 1.8%) while a higher proportion of the married group(83. 6%) preferred the day duties than the single group(69.0%). These differences were found to be statistically all significant(p=.001). 9. The findings on preferences of three different types of fixed duty hours namely, B, C. and D(with additional monetary incentives) are as follows in order of preference: B type(12hrs a day, 3days a wk): day shift(64.1%), evening shift(26.1%). night shift(6.5%) C type(12hrs a day. 4days a wk) : evening shift(49.2%). day shift(32.8%), night shift(11.5%) D type(10hrs a day. 4days a wk): showed the similar trend as B type. The findings of higher preferences on the evening and night duties when the incentives are given. as shown above, suggest the need for the introductions of different patterns of duty hours and incentive measures in order to overcome the difficulties in rostering the nursing duties. However, the interpretation of the above data, particularly the C type, needs cautions as the total number of respondents is very small(n=61). It requires further in-depth study. In conclusion. it seemed to suggest that the patterns of nurses duty hours and shifts in the most hospitals in the country have neither been tried for different duty types nor been flexible. The stereotype rostering system of three shifts and insensitiveness for personal life aspect of nurses seemed to be prevailing. This study seems to support that irregular and frequent rotations of duty shifts may be contributing factors for most nurses' maladjustment problems in physical and mental health. personal and family life which eventually may result in high turnover rates. In order to overcome the increasing problems in personnel management of hospital nurses particularly in rostering of evening and night duty shifts, which may related to eventual high turnover rates, the findings of this study strongly suggest the need for an introduction of new rostering systems including fixed duties and appropriate incentive measures for evenings and nights which the most nurses want to avoid, In considering the nursing care of inpatients is the round-the clock business. the practice of the nursing duty shift system is inevitable. In this context, based on the findings of this study. the following are recommended: 1. The further in-depth studies on duty shifts and hours need to be undertaken for the development of appropriate and effective rostering systems for hospital nurses. 2. An introduction of appropriate incentive measures for evening and night duty shifts along with organizational considerations such as the trials for preferred duty time bands, duty hours, and fixed duty shifts should be considered if good quality of care for the patients be maintained for the round the clock. This may require an initiation of systematic research and development activities in the field of hospital nursing administration as a part of permanent system in the hospital. 3. Planned and regular intervals, orientation and training, and professional and personal growth should be considered for the rotation of different duty stations or units. 4. In considering the higher degree of preferences in the duty type of "10hours a day, 4days a week" shown in this study, it would be worthwhile to undertake the R&D type studies in large hospital settings.

• Journal of Global Scholars of Marketing Science
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• v.20 no.2
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• pp.208-218
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• 2010

Internet has grown fast and become one of the most important retail channels now. Various types of Internet retailers, hereafter etailers, have been introduced so far and as one type of Internet shopping mall, 'surrogate Internet shopping mall' has been prosperous and attracting consumers in the domestic market. Surrogate Internet shopping mall is a unique type of etailer that globally purchases well-known brand goods that are not imported in the market, completes delivery in the favor of individual buyers, and collects fees for these specific services. The consumers, who are usually interested in purchasing high-end and unique but not eligible brands, have difficulties to purchase these items overseas directly from the retailers or brands in other countries due to worries of payment failure and no address available for their usually domestic only delivery. In Korea, both numbers of surrogate Internet shopping malls and the magnitude of sales have been growing rapidly up to more than 430 active malls and 500 billion Korean won in 2008 since the population of consumers who want this agent shopping service is also expending. This etail business concept is originated from 'surrogate-mediated purchase' and this type of shopping agent has existed in many different forms and also in wide ranges of context level for quite a long time. As marketers face their individual buyers' representatives instead of a direct contact with them in many occasions, the impact of surrogate shoppers on consumer's decision making has been enormously important and many scholars have explored various range of agent's impact on consumer's purchase decisions in marketing and psychology field. However, not much rigorous research in the Internet commerce has been conveyed yet. Moreover, since as one of the shopping agent surrogate Internet shopping malls specifically connect overseas brands or retailers to domestic consumers, one specific character of the mall's, image of surrogate buying country, where surrogate purchases are conducted in, may play an important role to form consumers' attitude and purchase intention toward products. Furthermore it also possibly affects various dimensions of perceived risk in consumer's information processing. However, though tremendous researches have been carried exploring the effects of diverse dimensions of country of origin, related studies in Internet context has been rarely executed. There have been some studies that prove the positive impact of country of origin on consumer's evaluations as one of information clues in product manufacture descriptions, yet studies detecting the relationship between country image of surrogate buying origin and product evaluations rarely undertaken regarding this specific mall type. Thus, the authors have found it well-worth investigating in this specific retail channel and explored systematic relationships among focal constructs and elaborated their different paths. The authors have proven that country image of surrogate buying origin in the mall, where surrogate malls purchase products in and brings them from for buyers, not only has a positive effect on consumers' product evaluations including attitude and purchase intention but also has a negative effect on all three dimensions of perceived risk: product-related risk, shipping-related risk, and post-purchase risk. Specifically among all the perceived risk, product-related risk which is arisen from high uncertainty of product performance is most affected (${\beta}$= -.30) by negative country image of surrogate buying origin, and also shipping-related risk (${\beta}$= -.18) and post-purchase risk (${\beta}$= -.15) get influenced in order. Its direct effects on product attitude (${\beta}$= .10) and purchase intention (${\beta}$= .14) are also secured. Each of perceived risk dimension is proven to have a negative effect on purchase intention through product attitude as a mediator (${\beta}$= -.57: product-related risk ${\rightarrow}$ product attitude; ${\beta}$= -.24: shipping-related risk ${\rightarrow}$ product attitude; ${\beta}$= -.44: post-purchase risk ${\rightarrow}$ product attitude) as well. From the additional analysis, the paths of consumers' information processing are shown to be different based on their levels of product knowledge. While novice consumers with low level of knowledge consider only perceived risk important, expert consumers with high level of knowledge take both the country image, where surrogate services are conducted in, and perceived risk seriously to build their attitudes and formulate decisions toward products more delicately and systematically, which is in line with previous studies. This study suggests several pieces of academic and practical advice. Precisely, country image of surrogate buying origin does affect on consumer's risk perceptions and behavioral consequences. Therefore a careful selection of surrogate buying origin is recommended. Furthermore, reducing consumers' risk level is required to blossom this new type of retail business whether its consumer are novices or experts. Additionally, since consumer take different paths of elaborating information based on their knowledge levels, sophisticated marketing approaches to each group of consumers are required. For novice buyers strong devices for risk mitigation are needed to induce them to form better attitudes and for experts selections of better and advanced countries as surrogate buying origins are advised while endorsement strategy for the site might work as a reliable information clue to all consumers to mitigate the barriers to purchase goods online. The authors have also explained that the study suffers from some limitations, including generalizability. In future studies, tests of and comparisons among different types of etailers with relevant constructs are recommended to broaden the findings.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.91-108
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• 2020

Korea's famous soccer players are steadily performing well in international leagues, which led to higher interests of Korean fans in the international leagues. Reflecting the growing social phenomenon of rising interests on international leagues by Korean fans, the study examined the overall consumer perception in the consumption of uniform by domestic soccer fans and compared the changes in perception following the transfers of the players. Among others, the paper examined the consumer perception and purchase factors of soccer fans shown in social media, focusing on periods before and after the recruitment of Heung-Min Son to English Premier League's Tottenham Football Club. To this end, the EPL uniform is the collection keyword the paper utilized and collected consumer postings from domestic website and social media via Python 3.7, and analyzed them using Ucinet 6, NodeXL 1.0.1, and SPSS 25.0 programs. The results of this study can be summarized as follows. First, the uniform of the club that consistently topped the league, has been gaining attention as a popular uniform, and the players' performance, and the players' position have been identified as key factors in the purchase and search of professional football uniforms. In the case of the club, the actual ranking and whether the league won are shown to be important factors in the purchase and search of professional soccer uniforms. The club's emblem and the sponsor logo that will be attached to the uniform are also factors of interest to consumers. In addition, in the decision making process of purchase of a uniform by professional soccer fan, uniform's form, marking, authenticity, and sponsors are found to be more important than price, design, size, and logo. The official online store has emerged as a major purchasing channel, followed by gifts for friends or requests from acquaintances when someone travels to the United Kingdom. Second, a classification of key control categories through the convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm shows differences in the classification of individual groups, but groups that include the EPL's club and player keywords are identified as the key topics in relation to professional football uniforms. Third, between 2002 and 2006, the central theme for professional football uniforms was World Cup and English Premier League, but from 2012 to 2015, the focus has shifted to more interest of domestic and international players in the English Premier League. The subject has changed to the uniform itself from this time on. In this context, the paper can confirm that the major issues regarding the uniforms of professional soccer players have changed since Ji-Sung Park's transfer to Manchester United, and Sung-Yong Ki, Chung-Yong Lee, and Heung-Min Son's good performances in these leagues. The paper also identified that the uniforms of the clubs to which the players have transferred to are of interest. Fourth, both male and female consumers are showing increasing interest in Son's league, the English Premier League, which Tottenham FC belongs to. In particular, the increasing interest in Son has shown a tendency to increase interest in football uniforms for female consumers. This study presents a variety of researches on sports consumption and has value as a consumer study by identifying unique consumption patterns. It is meaningful in that the accuracy of the interpretation has been enhanced by using a cluster analysis via convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm to identify the main topics. Based on the results of this study, the clubs will be able to maximize its profits and maintain good relationships with fans by identifying key drivers of consumer awareness and purchasing for professional soccer fans and establishing an effective marketing strategy.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.