• Korean Journal of Heritage: History & Science
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• v.53 no.4
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• pp.136-149
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• 2020

It is generally believed that Douglas Fir timber imported from North America is used in repair work for Korean wooden heritage sites due to an insufficient supply of extra-large sized Korean pine timber. Based on this understanding in the cultural heritage repair field, Cultural Heritage Repair Business Entities ("CHRBE") prefer North American Douglas Fir timber which is more easily acquired on the market than large Korean pine timber. However, if CHRBE use large quantities of foreign-origin wood in the heritage repair field, this presents the threat of negative domestic impacts on cultural heritage such as breaching the preservation principal and ultimately weakening material authenticity. Therefore, this study aims to investigate the current supply status of large Korean pine timber through examination of existing research, interviews with experts engaged in CHRBE, and timber mills. With this information, the authors seek to identify whether the market supply of large Korean pine timber is indeed insufficient or not. In addition to this, this paper identifies the reasons why large Korean pine timber is not widely used if such timber supply is actually sufficient. In order to propose suggestions regarding the issues above, the authors study the distribution channel for large Korean pine timber and the price spectrum of this timber through examination of price information from the public agencies under the Korea Forest Service, research papers from the Cultural Heritage Administration, and estimation documents from timber mills. This paper also identifies two main opinions about why Korean timber has not been commonly used in the Korean heritage repair field. The first opinion is that the supply of large Korean pine timber really is insufficient in Korea. However, the second opinion is that it is hardly used due to inappropriateness of the government's procurement and estimation system, despite the fact that the supply of the timbers on the market is actually sufficient. Through the aforementioned research, this paper comes to the conclusion that the second opinion has strong grounds in many aspects. In terms of suggestions, alternative routes are proposed to stimulate the use of large Korean pine timber via supply by the 'Korea Foundation for Traditional Architecture and Technology' and surveys of the price spectrum of the timber, etc.

• Asia Marketing Journal
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• v.11 no.4
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• pp.95-119
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• 2010

Although there have been many studies regarding the inconsistency between consumers' attitudes and behavior, prior research has almost exclusively focused on the relationship between the attitude before behavior and the initial behavior. Relatively little research has been conducted on consumer satisfaction after purchase and post-purchase behavior. This research proposed that the relationship between satisfaction and post-purchase behavior is moderated by consumers' psychological characteristics such as need for cognitive closure(NCC) and temporal self-construal(SC). The need for cognitive closure refers to individuals' desire for a firm answer to a question and an aversion toward ambiguity. We assumed the need for cognitive closure as a major moderating variable because it is judged that the requirement for cognition clearly varies between when a consumer repurchases the same product and seeks a new alternative. Individuals who tend to end cognition due to time constraints or inappropriate conditions may display considerable cognitive impatience or impulsivity and has a higher probability in repurchasing the same product than a consumer without such limitations. They would avoid further consideration for new alternatives and the likelihood of the repurchase for prior alternative would increase. As hypothesized, significant moderating effect of the NCC was confirmed. This result gives a significant implication for a corporate to establish effective marketing strategies. For a corporate or product brand that has been occupying the market after entering the market earlier, it would be effective to maintain need for cognitive closure high in the existing consumers and thereby preventing the consumers from being interested in the new alternatives. On the other hand, new brands that have just entered the market need to lower the potential consumers' need for cognitive closure so that the consumers can be interested in new alternatives. Along with need for cognitive closure, temporal self-construal also turned out to moderate the satisfaction-repurchase. temporal SC reflects the extent to which individuals view themselves either as an individuated entity or in relation to others. Consumers under a temporarily independent SC would repurchase former alternative again according to their prior satisfaction and evaluation. In contrast, consumers in temporal interdependent SC tended to switch to a new alternative because they value interpersonal relationships above anything else and have a tendency to rely heavily on in-group opinions. When they are confronted with additional opinions, it is highly probable that he/she will choose a new product as an alternative. By proving the impact that temporal self-construal has on repurchasing behavior, this study is providing the marketers with new standards for establishing successful promotional strategies. For example, if the buyer and the user is the same for a product, it would be effective for the seller to convince the consumer to make decision subjectively by encouraging temporal independent self-construal. On the contrary, in the case where the purchase is made by an individual but the product is consumed by a group of people. For example, a housewife is more likely to choose the products or brands that her husband or children prefer rather than the ones that she likes by herself. In that case, emphasizing how the whole family can be satisfied and happy about the product would be effective for promoting repurchase.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.197-218
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• 2019

In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

• Asia Marketing Journal
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• v.14 no.1
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• pp.1-24
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• 2012

Nowadays, customer satisfaction has been one of company's major objectives, and the index to measure and communicate customer satisfaction has been generally accepted among business practices. The major issues of CSI(customer satisfaction index) are three questions, as follows: (a)what level of customer satisfaction is tolerable, (b)whether customer satisfaction and company performance has positive causality, and (c)what to do to improve customer satisfaction. Among these, the second issue is recently attracting academic research in several perspectives. On this study, the second issue will be addressed. Many researchers including Anderson have regarded customer satisfaction as core competencies, such as brand equity, customer equity. They want to verify following causality "customer satisfaction → market performance(market share, sales growth rate) → financial performance(operating margin, profitability) → corporate value performance(stock price, credit ratings)" based on the process model of marketing performance. On the other hand, Insoo Jeon and Aeju Jeong(2009) verified sequential causality based on the process model by the domestic data. According to the rejection of several hypotheses, they suggested the balance model of marketing performance as an alternative. The objective of this study, based on the existing process model, is to examine the causal relationship between customer satisfaction and corporate value performance. Anderson and Mansi(2009) proved the relationship between ACSI(American Customer Satisfaction Index) and credit ratings using 2,574 samples from 1994 to 2004 on the assumption that credit rating could be an indicator of a corporate value performance. The similar study(Sangwoon Yoon, 2010) was processed in Korean data, but it didn't confirm the relationship between KCSI(Korean CSI) and credit ratings, unlike the results of Anderson and Mansi(2009). The summary of these studies is in the Table 1. Two studies analyzing the relationship between customer satisfaction and credit ratings weren't consistent results. So, in this study we are to test the conflicting results of the relationship between customer satisfaction and credit ratings based on the research model considering Korean credit ratings. To prove the hypothesis, we suggest the research model as follows. Two important features of this model are the inclusion of important variables in the existing Korean credit rating system and government support. To control their influences on credit ratings, we included three important variables of Korean credit rating system and government support, in case of financial institutions including banks. ROA, ER, TA, these three variables are chosen among various kinds of financial indicators since they are the most frequent variables in many previous studies. The results of the research model are relatively favorable : R², F-value and p-value is .631, 233.15 and .000 respectively. Thus, the explanatory power of the research model as a whole is good and the model is statistically significant. The research model has good explanatory power, the regression coefficients of the KCSI is .096 as positive(+) and t-value and p-value is 2.220 and .0135 respectively. As a results, we can say the hypothesis is supported. Meanwhile, all other explanatory variables including ROA, ER, log(TA), GS_DV are identified as significant and each variables has a positive(+) relationship with CRS. In particular, the t-value of log(TA) is 23.557 and log(TA) as an explanatory variables of the corporate credit ratings shows very high level of statistical significance. Considering interrelationship between financial indicators such as ROA, ER which include total asset in their formula, we can expect multicollinearity problem. But indicators like VIF and tolerance limits that shows whether multicollinearity exists or not, say that there is no statistically significant multicollinearity in all the explanatory variables. KCSI, the main subject of this study, is a statistically significant level even though the standardized regression coefficients and t-value of KCSI is .055 and 2.220 respectively and a relatively low level among explanatory variables. Considering that we chose other explanatory variables based on the level of explanatory power out of many indicators in the previous studies, KCSI is validated as one of the most significant explanatory variables for credit rating score. And this result can provide new insights on the determinants of credit ratings. However, KCSI has relatively lower impact than main financial indicators like log(TA), ER. Therefore, KCSI is one of the determinants of credit ratings, but don't have an exceedingly significant influence. In addition, this study found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size, and on service companies than manufacturers. The findings of this study is consistent with Anderson and Mansi(2009), but different from Sangwoon Yoon(2010). Although research model of this study is a bit different from Anderson and Mansi(2009), we can conclude that customer satisfaction has a significant influence on company's credit ratings either Korea or the United State. In addition, this paper found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size and on service companies than manufacturers. Until now there are a few of researches about the relationship between customer satisfaction and various business performance, some of which were supported, some weren't. The contribution of this study is that credit rating is applied as a corporate value performance in addition to stock price. It is somewhat important, because credit ratings determine the cost of debt. But so far it doesn't get attention of marketing researches. Based on this study, we can say that customer satisfaction is partially related to all indicators of corporate business performances. Practical meanings for customer satisfaction department are that it needs to actively invest in the customer satisfaction, because active investment also contributes to higher credit ratings and other business performances. A suggestion for credit evaluators is that they need to design new credit rating model which reflect qualitative customer satisfaction as well as existing variables like ROA, ER, TA.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of Distribution Research
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• v.16 no.4
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• pp.65-93
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• 2011

As relationship between buyer and seller has been brought closer and long-term relationship has been more important in B2B markets, the importance of service and service convenience increases as well as product. In homogeneous markets, where service offerings are similar and therefore not key competitive differentiator, providing greater convenience may enable a competitive advantage. Service convenience, as conceptualized by Berry et al. (2002), is defined as the consumers' time and effort perceptions related to buying or using a service. For this reason, B2B customers are interested in how fast the service is provided and how much save non-monetary cost like time or effort by the service convenience along with service quality. Therefore, this study attempts to investigate the impact of service convenience on relationship factors such as relationship satisfaction, relationship commitment, and relationship performance. The purpose of this study is to find out whether service convenience can be a new antecedent of relationship quality and relationship performance. In addition, this study tries to examine how five-dimensional service convenience constructs (decision convenience, access convenience, transaction convenience, benefit convenience, post-benefit convenience) affect customers' relationship satisfaction, relationship commitment, and relationship performance. The service convenience comprises five fundamental components - decision convenience (the perceived time and effort costs associated with service purchase or use decisions), access convenience(the perceived time and effort costs associated with initiating service delivery), transaction convenience(the perceived time and effort costs associated with finalizing the transaction), benefit convenience(the perceived time and effort costs associated with experiencing the core benefits of the offering) and post-benefit convenience (the perceived time and effort costs associated with reestablishing subsequent contact with the firm). Earlier studies of perceived service convenience in the industrial market are none. The conventional studies that have dealt with service convenience have usually been made in the consumer market, or they have dealt with convenience aspects in the service process. This service convenience measure for consumer market can be useful tool to estimate service quality in B2B market. The conceptualization developed by Berry et al. (2002) reflects a multistage, experiential consumption process in which evaluations of convenience vary at each stage. For this reason, the service convenience measure is good for B2B service environment which has complex processes and various types. Especially when categorizing B2B service as sequential stage of service delivery like Kumar and Kumar (2004), the Berry's service convenience measure which reflect sequential flow of service deliveries suitable to establish B2B service convenience. For this study, data were gathered from respondents who often buy business service and analyzed by structural equation modeling. The sample size in the present study is 119. Composite reliability values and average variance extracted values were examined for each variable to have reliability. We determine whether the measurement model supports the convergent validity by CFA, and discriminant validity was assessed by examining the correlation matrix of the constructs. For each pair of constructs, the square root of the average variance extracted exceeded their correlations, thus supporting the discriminant validity of the constructs. Hypotheses were tested using the Smart PLS 2.0 and we calculated the PLS path values and followed with a bootstrap re-sampling method to test the hypotheses. Among the five dimensional service convenience constructs, four constructs (decision convenience, transaction convenience, benefit convenience, post-benefit convenience) affected customers' positive relationship satisfaction, relationship commitment, and relationship performance. This result means that service convenience is important cue to improve relationship between buyer and seller. One of the five service convenience dimensions, access convenience, does not affect relationship quality and performance, which implies that the dimension of service convenience is not important factor of cumulative satisfaction. The Cumulative satisfaction can be distinguished from transaction-specific customer satisfaction, which is an immediate post-purchase evaluative judgment or an affective reaction to the most recent transactional experience with the firm. Because access convenience minimizes the physical effort associated with initiating an exchange, the effect on relationship satisfaction similar to cumulative satisfaction may be relatively low in terms of importance than transaction-specific customer satisfaction. Also, B2B firms focus on service quality, price, benefit, follow-up service and so on than convenience of time or place in service because it is relatively difficult to change existing transaction partners in B2B market compared to consumer market. In addition, this study using partial least squares methods reveals that customers' satisfaction and commitment toward relationship has mediating role between the service convenience and relationship performance. The result shows that management and investment to improve service convenience make customers' positive relationship satisfaction, and then the positive relationship satisfaction can enhance the relationship commitment and relationship performance. And to conclude, service convenience management is an important part of successful relationship performance management, and the service convenience is an important antecedent of relationship between buyer and seller such as the relationship commitment and relationship performance. Therefore, it has more important to improve relationship performance that service providers enhance service convenience although competitive service development or service quality improvement is important. Given the pressure to provide increased convenience, it is not surprising that organizations have made significant investments in enhancing the convenience aspect of their product and service offering.

• Korea Journal of Hospital Management
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• v.13 no.1
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• pp.24-41
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• 2008

This research is aimed at analyzing and understanding the perception and attitudes of inpatients in a general hospital in Seoul towards the activation of private health insurance. Survey was conducted against 231 inpatients, results of which were analyzed in the methods of frequency analysis, chi square test, and logistic regression. The results are summarized as follows; First, better-educated population who finished college education at least, higher-income population, and people who had more knowledge about private health insurance showed more perception about activation of private health insurance. Second, better-educated population who finished college education at least, higher-income population, those who are insured in existing private insurance, oncological patients, and people who had more knowledge about private health insurance showed more positive attitude towards private health insurance paying for actual damages, long-term care insurance, and income security insurance. Third, age and education were the factors affecting perception about activation of private health insurance. The older the age is, perception was 1.035 times positive towards activation of private health insurance, and those who finished college education or above showed 3.148 times positive perception towards the same. Forth, surgical patients showed 1.087 times more positive attitude towards private health insurance paying for actual damages than internal medicine patients, while oncological patients showed 2.314 times more positive attitude than internal medicine patients. Further, understanding on the activation of private health insurance was 6.014 times higher in the higher understanding group than in the lower understanding group. Intention to use long-term care insurance was 2.692 times stronger in the male group than in the female group, and 3.616 times stronger in the oncological patients group than in internal medicine patients group. Further, understanding on the activation of private health insurance was 3.881 times deeper in the higher understanding group than in the lower understanding group. Intention to use income security insurance was 3.185 times stronger in those who have academic background of under the high school than those over the college, and 4.175 times higher in the group those whose monthly average income is over 4 million won than those under 4 million won. Also, intention to use income security insurance was 4.323 times higher in the group those who are insured by existing private insurances than those who are not insured by those insurances and it was 5.234 times higher in the group of oncological patients than in the group of internal medicine patients. Further, intention to use income security insurance was 3.559 times higher in the group those who thought that out-of-pocket money of the National Health Insurance is too much to bear than those it is quite endurable. Understanding on the activation of private health insurance was 4.875 times deeper in the higher understanding group than in the lower understanding group. There were some suggestions could be made based on the results of this research. First, reinforced publicity and education is needed for the low-educated or low-income group, as there are gaps in the understanding on the activation of private health insurance depending on the degree of education and income. Second, government should prepare administrative complementary measures to solve the problem of adverse selection by the consumer which is foreseen when private health insurances are activated. Third, government should suggest the desirable course of development of private health insurance items to ensure efficient use of enormous fund of private insurance market for health security of the people. Further, institutional complementary measures are needed to convert existing cancer insurances or specific disease insurances to private health insurances paying for actual damages guaranteeing against every kind of disease. Forth, it judged that, not only private health insurances paying for actual damages, but also long-term care insurances and income security insurances are prospective as fields to create fresh demand for insurance industry.

• Land and Housing Review
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• v.12 no.3
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• pp.51-65
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• 2021

There were strong criticisms against the joint development method: the redevelopment corporation and developers would achieve the whole development profit. The existing tenants who lost their housing in the site argued their right to reside in the site after the development was completed. There was also strong political pressure that the Roh Tae-woo governing administration should resolve the social inequality caused by the situation. In such circumstances, it was introduced that a certain proportion of public rental housing should be built in the redevelopment site; then the government took over the dwellings at a price of construction and allocated them to the existing tenants. The aims of this paper are to understand the rationale behind the inclusion of the public rental housing in the redevelopment sites; and to investigate to what extent the legislation was implemented appropriately. Although the legislation was introduced in Seoul from August 1989, it was not until May 2005 when it was implemented nationwide. At the beginning, there was an ambiguous rule that the number of public housing to be included should be limited to the number of households who would want to remain in the redeveloped site. In 2005 the Seoul metropolitan authority introduced a mandatory proportion; 17% of the total housing delivered in the site should be public rental homes. Since then the proportion. The proportion has been fluctuated by the political agenda of each ruling party: the conservative tended to reduce the proportion, whilst the opposition parties increased the proportion. Currently the proportion is 20% of the total stock to be built. Initially the size of the public housing was exceptionally small- less than 40 m² but it has increased up to 60 m² since 2010. The rental price was reasonably lower than market rent. The competition toward redevelopment rental housing that are vacant due to move or death of tenants was very high; it was given to one household out of nine eligible households in 2020.

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

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

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.