• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.1
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• pp.1-13
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• 2017

The purpose of this study is to find out which factors determine the success of start-up in the initial market and what are the most important determinants. For the empirical analysis, the questionnaire related to the analysis of success factors for start-up success was designed according to the quantitative analysis (AHP technique). First, we selected 8 representative success factors for successful start-up in the initial market. In order to determine the degree of priority among these factors, we surveyed 12 entrepreneurs who are interested in entrepreneurship, universities, research institutes, and public officials. As a result of the empirical analysis, 51% of the funds in the tier 1 were ranked as the top priority to determine success factors. Followed by research and development (32.5%), management (8.7%) and marketing (7.8%). In particular, when each of the four items is calculated as 100 according to the result of the tier 1, and the tier 2 is converted, the foreign investment is analyzed as 43.7%. It was followed by 15.14% of R & D facilities, 14.07% of ideas, 8.7% of managerial ability, 7.29% of domestic investment, 5.85% of buyer feedback, 3.3% of development strategy and 1.95% of marketing strategy. Among the eight success factors, overseas investment items showed the closest preference to half, and it was the most important variable that determines the success or failure of market entry. The implication of this study is that many start-ups in Korea expect to receive investment and support from overseas accelerators. This means that overseas investment itself has been recognized as a start-up that makes services and products that can be used in the global market. A high preference for attracting foreign investment is due to the fact that the amount of investment is larger than that of Korea and that it can flexibly cope with the pressure on the performance compared to domestic investors. In this study, it was meaningful that we could confirm this fact through questionnaires of start-up experts. In future research, we need to find a viable alternative through studying how to provide start-up to foreign direct investment at the national level.

• Journal of the Korean Society of School Health
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• v.7 no.1
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• pp.45-55
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• 1994

The purpose of this study is to contribute to improvement of educational environment by analysing all problems related to environment around the school. To accomplish this purpose, this study was carried out by examining the problems in controlling the areas required for cleanup with 220 teachers in charging the cleanup duties of the primary and secondary schools in Taegu between June 1 and July 15, 1993 and by actually surveying the prejudical business stores around 72 primary schools between August 10 and September 20, 1993. Although most teachers answered to the questionnaires that it is necessary to cleanup the bad environment around the school, the duties of its cleanup tend not to be considered as an important matter. The teachers considered that the most prejudical business store around the school is totally the game room, and in such order as comic books' store, liquor selling shop and causing noise and pollution. 57.3% of total respondents answered that the present cleanup movements have resulted in failure mostly because of both supervising authorities' careless promotion and store owners' excessive commercial transactions. The result of actual survey in environmental and sanitary cleanup area around 72 primary schools showed that the greatest number of 1,258 prejudical stores was the video tapes shop, and then in such order as lodgings, and game rooms, while the number of prejudical store by the schools was 17.5 stores per school on the average which showed a various distribution from zero to 77 places. In general, these prejudical stores were mainly located around the schools in Jung-gu and Seo-gu areas. In addition, it was shown that the more the number of students, the more the number of the prejudical stores. In order to improve the environment around the school, it is necessary to strictly carry out the zoning system relating to the usage of land, to strongly restrict the stores without permit and abnormal stores and to establish the basis asking the city development authorities to go through the environmental evaluation. Moreover, it is absolutely required to make efforts to establish the national right sense of education, and to closely cooperate with the related authorities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.4 no.4
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• pp.45-70
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• 2009

This article investigates which types of the strategies announced by the listed firms contribute to enhancing the long-term performance of the companies. Since 2002, Korean Exchange adopted the "faire disclosure policy" which mandates that all publicly traded companies must disclose material information to all investors at the same time. Thanks to the policy, Korean investors can, now, easily access the board's decision on management strategies on the same day the decision is made. If the companies trustfully carry out their announced strategies, we can decide which types of strategies actually enhance or deteriorate the long-term performance, simply by comparing the announced strategies and the firm's performance. The sample companies are confined to 60 firms that became listed in the KOSDAQ market through back-door listing from 2003 to 2005. Using only the newly listed companies, we can avoid the interference on the long-term performance of the strategies pursued before the event date. This often holds true, for many companies radically modify their strategies after the listing. Furthermore, the back-door listing companies serve our purpose better than IPO companies do, because the former tend to have a variety of announcement within a given period of time beginning the listing date. Using these sample companies, this article analyzes the effect on one year buy-and-hold returns and abnormal buy-and-hold returns after the listing of the various types of strategies announced during the same period of time. The results show that those evidences of restructuring such as 'reduction of capital' and 'resignation of incumbent board members', actually contribute to the increase in adjusted long-term stock returns. Those strategies which can be view as evidence of new investment such as 'increase in tangible assets', 'acquisition of other companies', do also helps the stockholders better off. On the contrary, 'increase in bank loans', 'changes of CEO' and 'merger' deteriorate the equity value. The last findings let us to presume that the back-door listing companies appear to use the bank loans for value-reducing activities; the change in CEO is not a sign of restructuring, but rather a sign of failure of the restructuring; another merger carried out after back-door listing itself is also value-reducing activity. This article's findings on reduction of capital, merger and bank loans oppose the results of the former empirical studies which analyze only the short-term effect on stock price. Therefore, more long-term performance studies on public disclosures are in order.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.611-635
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• 2014

Information systems (IS) have become ubiquitous and changed every aspect of how people live their lives. While some IS have been successfully adopted and widely used, others have failed to be adopted and crowded out in spite of remarkable progress in technologies. Both the technology acceptance model (TAM) and the IS Success Model (ISSM), among many others, have contributed to explain the reasons of success as well as failure in IS adoption and usage. While the TAM suggests that intention to use and perceived usefulness lead to actual IS usage, the ISSM indicates that information quality, system quality, and service quality affect IS usage and user satisfaction. Upon literature review, however, we found a significant void in theoretical development and its applications that employ either of the two models, and we raise research questions. First of all, in spite of the causal relationship between intention to use and actual usage, in most previous studies, only intention to use was employed as a dependent variable without overt explaining its relationship with actual usage. Moreover, even in a few studies that employed actual IS usage as a dependent variable, the degree of actual usage was measured based on users' perceptual responses to survey questionnaires. However, the measurement of actual usage based on survey responses might not be 'actual' usage in a strict sense that responders' perception may be distorted due to their selective perceptions or stereotypes. By the same token, the degree of system quality that IS users perceive might not be 'real' quality as well. This study seeks to fill this void by measuring the variables of actual usage and system quality using 'fact' data such as system logs and specifications of users' information and communications technology (ICT) devices. More specifically, we propose an integrated research model that bring together the TAM and the ISSM. The integrated model is composed of both the variables that are to be measured using fact as well as survey data. By employing the integrated model, we expect to reveal the difference between real and perceived degree of system quality, and to investigate the relationship between the perception-based measure of intention to use and the fact-based measure of actual usage. Furthermore, we also aim to add empirical findings on the general research question: what factors influence actual IS usage and how? In order to address the research question and to examine the research model, we selected a mobile campus application (MCA). We collected both fact data and survey data. For fact data, we retrieved them from the system logs such information as menu usage counts, user's device performance, display size, and operating system revision version number. At the same time, we conducted a survey among university students who use an MCA, and collected 180 valid responses. A partial least square (PLS) method was employed to validate our research model. Among nine hypotheses developed, we found five were supported while four were not. In detail, the relationships between (1) perceived system quality and perceived usefulness, (2) perceived system quality and perceived intention to use, (3) perceived usefulness and perceived intention to use, (4) quality of device platform and actual IS usage, and (5) perceived intention to use and actual IS usage were found to be significant. In comparison, the relationships between (1) quality of device platform and perceived system quality, (2) quality of device platform and perceived usefulness, (3) quality of device platform and perceived intention to use, and (4) perceived system quality and actual IS usage were not significant. The results of the study reveal notable differences from those of previous studies. First, although perceived intention to use shows a positive effect on actual IS usage, its explanatory power is very weak ($R^2$=0.064). Second, fact-based system quality (quality of user's device platform) shows a direct impact on actual IS usage without the mediating role of intention to use. Lastly, the relationships between perceived system quality (perception-based system quality) and other constructs show completely different results from those between quality of device platform (fact-based system quality) and other constructs. In the post-hoc analysis, IS users' past behavior was additionally included in the research model to further investigate the cause of such a low explanatory power of actual IS usage. The results show that past IS usage has a strong positive effect on current IS usage while intention to use does not have, implying that IS usage has already become a habitual behavior. This study provides the following several implications. First, we verify that fact-based data (i.e., system logs of real usage records) are more likely to reflect IS users' actual usage than perception-based data. In addition, by identifying the direct impact of quality of device platform on actual IS usage (without any mediating roles of attitude or intention), this study triggers further research on other potential factors that may directly influence actual IS usage. Furthermore, the results of the study provide practical strategic implications that organizations equipped with high-quality systems may directly expect high level of system usage.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.5
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• pp.93-104
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• 2019

The entrepreneurship can be a source of national growth potential as behavioral tendencies of people who seek innovation, take risks of failure, and proactively respond to opportunities. In particular, in the economic situation of Korea where growth has been stagnated, it is necessary to strengthen the entrepreneurship of women which is relatively lower than men's in order to activate the start-up and economic participation of the whole people. In this regard, this study focuses not only on gender differences in entrepreneurship but also on the hidden impact of social contexts that cause gender differences in entrepreneurship. Specifically, this study examined the moderating effects of childbirth, a factor that reflects the social context of Korea in the relationship between gender and entrepreneurship. According to the results of the model that includes the interaction effect of these variables in addition to the independent effects of gender and childbirth, the gender effect disappeared, while the significant effect of both the childbirth variable and the interaction variable of gender and childbirth were confirmed. Furthermore, according to additional analysis, which identified the differences in entrepreneurship by creating four types of treatment groups based on gender and childbirth status, entrepreneurship was significantly lower in the 'female and childbirth' group than in all other groups. The difference between the remaining treatment groups was not statistically significant. These results indicate that differences in entrepreneurship levels between men and women overlap not with the unique trait of men and women, but with the social contextual effects of Korea, where women are under the full burden of childbirth and parenting. This study suggests implications that effective policy measures to promote women's entrepreneurship or economic activity should be taken by taking into account the social context of Korea that suppresses women's entrepreneurial behavior.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.47-58
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• 2019

This paper is brought to analyze an impact of coaching activities over entrepreneur with respect to entrepreneurs' personal characteristics on the performance of Startups focusing on entrepreneur's awareness conversion effect. In particular, the situation of falling focus of serious startup failure on uncoachable obstinate entrepreneur among the several causes of startup failures, this paper define the research mission of reducing this risk by inducing coaching types of cooperations between senior entrepreneur having serial successful startup experiences and beginning entrepreneur. This paper carry out literature reviews chiefly on startup coaching researches rather than mentoring studies because coaching stressing on self-oriented problem defining and solving by entrepreneur actively tend to be more effective than mentoring relying on mentor's guideline passively as solving startup's main upcoming problems. This paper implement four related researches. First, the impact analysis of entrepreneur's personal characteristics on coaching activities, second, influences of entrepreneurs environmental factors on them, Third, impact of coaching activities on entrepreneur's awareness conversion effect, Fourth, how strongly this conversion effect contributing on the performance of startup. As results of empirical research, first, this paper prove that entrepreneur's environmental factors impact positively on coaching activities over entrepreneur although failing on validating on significant impact of entrepreneur's personal characteristics on coaching activities. Second, this paper prove that coaching activities positively influence on entrepreneur's awareness conversion, hence ultimately positively on the performance of startups. As conclusion, this paper validate that coaching activities over entrepreneur through inducing on the conversion of entrepreneur's awareness lead entrepreneur to setting the bar high and accountable planning of business milestone. This paper contribute on delivering policy implication that government initiatin action-oriented training program for entrepreneurs should accept the module of coaching session to produce more effective results.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Korea Science and Art Forum
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• v.20
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• pp.147-158
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• 2015

This study made an approach to the industrial exhibition space, which is a medium of marketing communication, from the position of an enterprise and consumers through the output of Space Design, and conducted it with focus on B2B transactions among specialized exhibitions. In addition, this study inquired into what factors should be considered along with space design by interpreting the purpose of participating in the exhibition and space design of the enterprise which supply capital goods, elements, related technologies and materials, etc. This study aimed at drawing the direct/indirect effect, produced by space design, on the marketing by analyzing correlation between space design and participating enterprises' marketing. Despite the marketing effect of the exhibition, which was proved by preceding research results, the reality is that exhibition-participating expenses work as considerable burden on enterprises. Particularly, booth design, which is forming the most proportion among the participating expenses, was found to have insufficient influence on visitors due to the decline in its importance among diverse factors influencing visitor's decision to visit a booth. Regardless of the business category of participating enterprises in the exhibition, the standard of exhibits was ranked as the most important consideration factor in visiting a booth. Even by business category, the standard of booth design rarely had an influence on booth visit. Booth design had an affirmative influence on participating enterprise's preference, but its influence on product purchase or business talk & contact with a participating enterprise or price was found to be extremely low. It's difficult to judge marketing success or failure of an exhibition by the form and standard of booth design. Preferably, this study infers that it's necessary to put much weight on qualitative excellence of an exhibition, which consists of participation of an enterprise in possession of excellent technologies, exhibits with higher standards and high-quality visitors with purchasing power. This study suggests that it's more effective to set up the plan for expansion of participation in exhibition by optimally regulating the proportion of space design in participating expense to increase marketing effectiveness of an exhibition. The limitations of this study, analysis of which based on the visitors to an exhibition only, requires supplementation through the follow-up research work on participating enterprises in the exhibition.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.1-22
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• 2021

Aspect Based Sentiment Analysis (ABSA), which analyzes sentiment based on aspects that appear in the text, is drawing attention because it can be used in various business industries. ABSA is a study that analyzes sentiment by aspects for multiple aspects that a text has. It is being studied in various forms depending on the purpose, such as analyzing all targets or just aspects and sentiments. Here, the aspect refers to the property of a target, and the target refers to the text that causes the sentiment. For example, for restaurant reviews, you could set the aspect into food taste, food price, quality of service, mood of the restaurant, etc. Also, if there is a review that says, "The pasta was delicious, but the salad was not," the words "steak" and "salad," which are directly mentioned in the sentence, become the "target." So far, in ABSA, most studies have analyzed sentiment only based on aspects or targets. However, even with the same aspects or targets, sentiment analysis may be inaccurate. Instances would be when aspects or sentiment are divided or when sentiment exists without a target. For example, sentences like, "Pizza and the salad were good, but the steak was disappointing." Although the aspect of this sentence is limited to "food," conflicting sentiments coexist. In addition, in the case of sentences such as "Shrimp was delicious, but the price was extravagant," although the target here is "shrimp," there are opposite sentiments coexisting that are dependent on the aspect. Finally, in sentences like "The food arrived too late and is cold now." there is no target (NULL), but it transmits a negative sentiment toward the aspect "service." Like this, failure to consider both aspects and targets - when sentiment or aspect is divided or when sentiment exists without a target - creates a dual dependency problem. To address this problem, this research analyzes sentiment by considering both aspects and targets (Target-Aspect-Sentiment Detection, hereby TASD). This study detected the limitations of existing research in the field of TASD: local contexts are not fully captured, and the number of epochs and batch size dramatically lowers the F1-score. The current model excels in spotting overall context and relations between each word. However, it struggles with phrases in the local context and is relatively slow when learning. Therefore, this study tries to improve the model's performance. To achieve the objective of this research, we additionally used auxiliary loss in aspect-sentiment classification by constructing CNN(Convolutional Neural Network) layers parallel to existing models. If existing models have analyzed aspect-sentiment through BERT encoding, Pooler, and Linear layers, this research added CNN layer-adaptive average pooling to existing models, and learning was progressed by adding additional loss values for aspect-sentiment to existing loss. In other words, when learning, the auxiliary loss, computed through CNN layers, allowed the local context to be captured more fitted. After learning, the model is designed to do aspect-sentiment analysis through the existing method. To evaluate the performance of this model, two datasets, SemEval-2015 task 12 and SemEval-2016 task 5, were used and the f1-score increased compared to the existing models. When the batch was 8 and epoch was 5, the difference was largest between the F1-score of existing models and this study with 29 and 45, respectively. Even when batch and epoch were adjusted, the F1-scores were higher than the existing models. It can be said that even when the batch and epoch numbers were small, they can be learned effectively compared to the existing models. Therefore, it can be useful in situations where resources are limited. Through this study, aspect-based sentiments can be more accurately analyzed. Through various uses in business, such as development or establishing marketing strategies, both consumers and sellers will be able to make efficient decisions. In addition, it is believed that the model can be fully learned and utilized by small businesses, those that do not have much data, given that they use a pre-training model and recorded a relatively high F1-score even with limited resources.