• (The) Research of the performance art and culture
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• no.38
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• pp.249-275
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• 2019

Gangneung farm song is important for the ritualistic labortheatricals. Especially, in the theatrical process program, the songsof weeding, such as Haksan Odokkteggi and Ssadae, were alsoincluded to represent the agricultural ritualistic prayer for goodharvest. The use of Gangneung farm song is attractive in termsofthe circumstances. There is no chance of success as a plan simplyfor local events. As a comprehensive art, Gangneung farmsongshould simultaneously revitalize locality, representability andglobality. In this context, three directions are suggested dependingon the development progress. The second direction to the thirddirection are mainly oriented toward government-local authoritycentered support, but, in particular, the third direction should aimtobe an open archive in which the public and the contents prosumercan participate. In the production of the traditional content, OSMUmust be endlessly recreated and spread through 'diversity' and'interrelationships'. The contents utilization was discussed based on the transmissiondetails and analysis evidence of Gangneung Haksan Odokttegi. Thediversification of the way of performing farm song and the folk songs that can induce interest were proposed. Furthermore, basedon the fact that 12 songs classified into 8 work types, there-creation of the contents that focus on the playful aspect of theperforming arts was also proposed. In addition to suggestingthedesirable discourse of the performance groups, the experienceprogram development, education, public relations andcommunication reinforcement based on the narrating principlesoffarm songs, and the development and execution of farmsongprograms based on the tradition and the event demands wereproposed. While mentioning the necessity of value creation, thevitality of performing arts skills that put emotion, imagination, fun, sympathy, and etc. on the original form and the model of farmsongs should be supplemented to Gangneung Haksan Odokttegi. The independent transmission aspect of Gangneung Arirangisalso positive. There are difficulties of reduction of traditionalitydueto the designation, standardized transmission, lack of developmentof voluntary performances, and demonstration-centeredtransmission. Narrowly, we focused on the education andvitalization directions in terms of the capacity building of theconservation council itself. By embodying the essential value of theagricultural literature that farm songs possess, it can bringimpression of all worlds, all lives, communication and sharing, anddraw inspiration from the humanistic view of the world andemotion. The reconstitution of agricultural heritage, theconstruction of a storytelling linked with the concrete objects suchas Beomil National Preceptor, Gulsansa, FlagpoleSupport(Dangganjiju), Seokcheon, Hakbawi rock, and etc., andtheestablishment of fusion type farm song museum were proposed. In terms of culture industry, we requested active support fromtheinstitutions including local governments and various farmsongstorytelling creation projects.

• (The) Research of the performance art and culture
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• no.22
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• pp.223-252
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• 2011

If we remember that modern world history has built systems of meaning through the concepts "difference," "different," and "other-ness" and has constructed new identity based on opposing hierarchy, music anthropology which tried to build "difference" between the west and the non-west was thoroughly west -centered, in the sense that it has perceived the heterogeneous symbolic systems among nations, as well as the barrier between the two cultures. On the other hand, world music, which has emerged as the most attractive field in culture industry and concert-art-market by crossing over global capitals, markets, and barriers, can be considered the most post-modernist and glocal. However, it is interesting to note that world music, which has been described as post-modern and glocal, has "difference" and "different" in its basis, just like the precepts for modern music anthropology (Meintjes 1990; Guilbault 1993; Taylor 1997; Frith 2000; Feld 1988). Furthermore, one can understand that the "different" and "difference," generally termed as being "non-western," are fundamentally based on ethnic or national imagination. In this sense it is interesting and important to examine such ethnic imagination in the "non-western ethnic musics" in music anthropology and in world music. Notwithstanding the attention paid and research made by music anthropologists, they have failed to elevate the "non-western ethnic musics" to become universally communicative, and these ethnic musics were reborn as "global" and "world music," through the process of "acculturation," "derivation," and "hybridization," with the west as major site for production and consumption. Meanwhile, the audience for world music, which did not exist before the birth of world music as a term, was now born as world music emerged. They are global populace who consume the musical "difference" and "imagined ethnicity," who through their consumption are constructing new social meanings including ethnicity, race, nation, and class identity. This study, by examining current discourse, performance, and process for the world music through media and field studies and scholarly debates, attempts to understand the production and consumption of "imagined ethnicity." This will also shed light on how "ethnicity" is created and consumed, and how this is involved in the process of world music.

• Asia Marketing Journal
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• v.14 no.1
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• pp.53-81
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• 2012

Constructing attractive bundle offers depends on more than an understanding of the distribution of consumer preferences. Consumers are also sensitive to the framing of price information in a bundle offer. In classical economic theory, consumers' utility should not change as long as the total price paid stays same. However, even when total prices are identical, consumers' preferences toward a bundle product could be different depending on the format of price presentation and the locus of price discount. A weighted additive model predicts that the impact of a price discount on the overall evaluation of the bundle will be greater when the discount is assigned to the more important product in the bundle(Yadav 1995). Meanwhile, a reference dependent model asserts that it is better to assign a price discount to a tie-in component that has a negative valuation at its current offer price than to a focal product that has a positive valuation at its current offer price(Janiszewski and Cunha 2004). This paper has expanded previous research regarding price discount presentation format, investigating the reasons for mixed results of prior research and presenting new mechanisms for price discount framing effect. Prior research has hypothesized that bundling is used to sell a tie-in component with an offer price above the consumer's reference price plus a focal product of the same offer price with reference price(e.g., Janiszewski and Cunha 2004). However, this study suggests that bundling strategy can be used for increasing product's attractiveness through the synergy between components even when offer prices of bundle components are the same with reference prices. In this context, this study employed various realistic bundle sets with same price between offer price and reference price in the experiment. Hamilton and Srivastava(2008) demonstrated that when evaluating different partitions of the same total price, consumers prefer partitions in which the price of the high-benefit component is higher. This study determined that their mechanism can be applied to price discount presentation formats. This study hypothesized that price discount framing effect depends not on the negative perception of tie-in component with offer price above reference price but rather on the consumers' perceived consumption benefit in bundle product. This research also hypothesized that preference for low-benefit discount mechanism is that perceived consumption benefit reduces price sensitivity. Furthermore, this study investigated how consumers' concern for quality in a price discount--a factor not considered in previous research--influences price discount framing. Yadav(1995)'s experiment used only one magazine bundle of relatively low quality uncertainty and could not show the influence of perceived uncertainty of quality. This study assumed that as perceived uncertainty of quality increases, the price sensitivity mechanism for assigning the discount to low-benefit will increase. Further, this research investigated the moderating effect of uncertainty of quality in price discount framing. The results of the experiment showed that when evaluating different partitions of the same total price and the same amount of discounts, the partition that discounts in the price of low benefit component is preferred to the partition that decreases the price of high benefit component. This implies that price discount framing effect depends on the perceived consumption benefit. The results also demonstrated that consumers are more price sensitive to low benefit component and less price sensitive to high benefit component. Furthermore, the results showed that the influence of price discount presentation format on the evaluation of bundle product varies with the perceived uncertainty of quality in high consumption benefit. As perceived uncertainty of quality gradually increases, the preference for discounts in the price of low consumption benefit decreases. Besides, the results demonstrate that as perceived uncertainty of quality gradually increases, the effect of price sensitivity in consumption benefit also increases. This paper integrated prior research by using a new mechanism of perceived consumption benefit and moderating effect of perceived quality uncertainty, thus providing a clearer explanation for price discount framing effect.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.19-26
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• 2023

Hydrogen, a clean energy source free of COx emissions, is poised to replace fossil fuels, with its usage on the rise. Despite its high energy content per unit mass, hydrogen faces limitations in storage and transportation due to its low storage density and challenges in long-term storage. In contrast, ammonia offers a high storage capacity per unit volume and is relatively easy to liquefy, making it an attractive option for storing and transporting large volumes of hydrogen. While NH₃ decomposition is an endothermic reaction, achieving excellent low-temperature catalytic activity is essential for process efficiency and cost-effectiveness. The study examined the effects of different zeolite types (5A, NaY, ZSM5) on NH₃ decomposition activity, considering differences in pore structure, cations, and Si/Al-ratio. Notably, the 5A zeolite facilitated the high dispersion of Ni across the surface, inside pores, and within the structure. Its low Si/Al ratio contributed to abundant acidity, enhancing ammonia adsorption. Additionally, the presence of Na and Ca cations in the support created medium basic sites that improved N₂ desorption rates. As a result, among the prepared catalysts, the 15 wt%Ni/5A catalyst exhibited the highest NH₃ conversion and a high H₂ formation rate of 23.5 mmol/g_cat·min (30,000 mL/g_cat·h, 600 ℃). This performance was attributed to the strong metal-support interaction and the enhancement of N₂ desorption rates through the presence of medium basic sites.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.17-30
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• 2022

The purpose of this study is to analyze the impact of the characteristics of start-up CEOs on the performance of investment attraction from the perspective of Series A investment. The results of the study are as follows. First, when the educational level of start-up CEOs was high and startup CEOs had start-up experience and investment attraction experience, venture investors such as venture capital had a significantly positive (+) effect on the investment for start-ups. This was systematically significantly positive even when control variables were introduced. When start-up CEOs had work experiences, there was no significantly positive effect on the total investment amount for start-ups but a significantly positive (+) effect on the average investment amount. Second, the standardization coefficient of total investment amount was larger in the case of start-up experience than that in the case of investment attraction experience while the standardization coefficient of average investment amount was larger in the case of investment attraction experience than that in the case of start-up experience. This suggests that the start-up experience is important for the total investment amount while the investment attraction experience is important for the average investment amount. Third, when the sales of start-ups were high at the time of Series A investment, the total investment amount and the average investment amount were also significantly high. Even if early start-ups are less profitable or have losses, the start-ups with a certain level of sales seem to be attractive investment targets for venture capital. The results of this study are useful for the investment decisions of venture capital and the financing strategies of start-ups. The implications for pre-CEOs preparing for start-ups art that the total amount of investment will increase if they have expertise through degree acquisition, challenge start-ups, gain start-up experience and implement investment attraction. Even if CEOs of start-ups do not have start-up experience, the average amount of investment for start-ups can increase if they have work experience in related industries.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.1-25
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• 2008

Ⅰ. Introduction Retailers in the 21st century are being told that future retailers are those who can execute seamless multi-channel access. The reason is that retailers should be where shoppers want them, when they want them anytime, anywhere and in multiple formats. Multi-channel access is considered one of the top 10 trends of all business in the next decade (Patricia T. Warrington, et al., 2007) And most firms use both direct and indirect channels in their markets. Given this trend, we need to evaluate a channel equity more systematically than before as this issue is expected to get more attention to consumers as well as to brand managers. Consumers are becoming very much confused concerning the choice of place where they shop for durable goods as there are at least 6-7 retail options. On the other hand, manufacturers have to deal with category killers, their dealers network, Internet shopping malls, and other avenue of distribution channels and they hope their retail channel behave like extensions of their own companies. They would like their products to be foremost in the retailer's mind-the first to be proposed and effectively communicated to potential customers. To enable this hope to come reality, they should know each channel's advantages and disadvantages from consumer perspectives. In addition, customer satisfaction is the key determinant of retail customer loyalty. However, there are only a few researches regarding the effects of shopping satisfaction and perceptions on consumers' channel choices and channels. The purpose of this study was to assess Korean consumers' channel choice and satisfaction towards channels they prefer to use in the case of electronic goods shopping. Korean electronic goods retail market is one of good example of multi-channel shopping environments. As the Korea retail market has been undergoing significant structural changes since it had opened to global retailers in 1996, new formats such as hypermarkets, Internet shopping malls and category killers have arrived for the last decade. Korean electronic goods shoppers have seven major channels : (1)category killers (2) hypermarket (3) manufacturer dealer shop (4) Internet shopping malls (5) department store (6) TV home-shopping (7) speciality shopping arcade. Korean retail sector has been modernized with amazing speed for the last decade. Overall summary of major retail channels is as follows: Hypermarket has been number 1 retailer type in sales volume from 2003 ; non-store retailing has been number 2 from 2007 ; department store is now number 3 ; small scale category killers are growing rapidly in the area of electronics and office products in particular. We try to evaluate each channel's equity using a consumer survey. The survey was done by telephone interview with 1000 housewife who lives nationwide. Sampling was done according to 2005 national census and average interview time was 10 to 15 minutes. Ⅱ. Research Summary We have found that seven major retail channels compete with each other within Korean consumers' minds in terms of price and service. Each channel seem to have its unique selling points. Department stores were perceived as the best electronic goods shopping destinations due to after service. Internet shopping malls were perceived as the convenient channel owing to price checking. Category killers and hypermarkets were more attractive in both price merits and location conveniences. On the other hand, manufacturers dealer networks were pulling customers mainly by location and after service. Category killers and hypermarkets were most beloved retail channel for Korean consumers. However category killers compete mainly with department stores and shopping arcades while hypermarkets tend to compete with Internet and TV home shopping channels. Regarding channel satisfaction, the top 3 channels were service-driven retailers: department stores (4.27); dealer shop (4.21); and Internet shopping malls (4.21). Speciality shopping arcade(3.98) were the least satisfied channels among Korean consumers. Ⅲ. Implications We try to identify the whole picture of multi-channel retail shopping environments and its implications in the context of Korean electronic goods. From manufacturers' perspectives, multi-channel may cause channel conflicts. Furthermore, inter-channel competition draws much more attention as hypermarkets and category killers have grown rapidly in recent years. At the same time, from consumers' perspectives, 'buy where' is becoming an important buying decision as it would decide the level of shopping satisfaction. We need to develop the concept of 'channel equity' to manage multi-channel distribution effectively. Firms should measure and monitor their prime channel equity in regular basis to maximize their channel potentials. Prototype channel equity positioning map has been developed as follows. We expect more studies to develop the concept of 'channel equity' in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.51-69
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• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• 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.