• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.135-145
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• 2023

Due to the decrease in the school-age population, the number of freshmen at local college who lack basic learning skills is increasing. Thus, C college has been running a basic learning ability improvement clinic program. This paper is a case study that investigates the effect of basic learning ability improvement clinic programs on major class immersion, efficacy, and major class satisfaction. In 2022, a total of 459 students were surveyed, including 238 students who participated in online and offline classes for basic learning ability improvement clinics and 221 students who did not participate in classes. Data processing was performed using SPSS Ver. 26.0 was used. The results of this study are as follows. First, among the sub-factors of academic self-efficacy, the group participating in the basic learning ability improvement clinic showed significant differences in task difficulty preference and confidence. Second, the class participation group showed a significant difference in learning immersion in major classes. Third, the class participation group showed significant differences in all sub-factors of major satisfaction. In conclusion, it was found that the basic learning ability improvement clinic class had a significant effect on academic self-efficacy, learning immersion, and major satisfaction.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.59-87
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• 2014

In MIS field, the researches on payment services are focused on adoption factors of payment service using behavior theories such as TRA(Theory of Reasoned Action), TAM(Technology Acceptance Model), and TPB (Theory of Planned Behavior). The previous researches presented various adoption factors according to types of payment service, nations, culture and so on even though adoption factors of identical payment service were presented differently by researchers. The payment service industry relatively has strong path dependency to the existing payment methods so that the research results on the identical payment service are different due to payment culture of nation. This paper aims to suggest a successful adoption factor of noble payment service regardless of nation's culture and characteristics of payment and prove it. In previous researches, common adoption factors of payment service are convenience, ease of use, security, convenience, speed etc. But real cases prove the fact that adoption factors that the previous researches present are not always critical to success to penetrate a market. For example, PayByPhone, NFC based parking payment service, successfully has penetrated to early market and grown. In contrast, Google Wallet service failed to be adopted to users despite NFC based payment method which provides convenience, security, ease of use. As shown in upper case, there remains an unexplained aspect. Therefore, the present research question emerged from the question: "What is the more essential and fundamental factor that should takes precedence over factors such as provides convenience, security, ease of use for successful penetration to market". With these cases, this paper analyzes four cases predicted on the following hypothesis and demonstrates it. "To successfully penetrate a market and sustainably grow, new payment service should find non-customer of the existing payment service and provide noble payment method so that they can use payment method". We give plausible explanations for the hypothesis using multiple case studies. Diners club, Danal, PayPal, Square were selected as a typical and successful cases in each category of payment service. The discussion on cases is primarily non-customer analysis that noble payment service targets on to find the most crucial factor in the early market, we does not attempt to consider factors for business growth. We clarified three-tier non-customer of the payment method that new payment service targets on and elaborated how new payment service satisfy them. In case of credit card, this payment service target first tier of non-customer who can't pay for because they don't have any cash temporarily but they have regular income. So credit card provides an opportunity which they can do economic activities by delaying the date of payment. In a result of wireless phone payment's case study, this service targets on second of non-customer who can't use online payment because they concern about security or have to take a complex process and learn how to use online payment method. Therefore, wireless phone payment provides very convenient payment method. Especially, it made group of young pay for a little money without a credit card. Case study result of PayPal, online payment service, shows that it targets on second tier of non-customer who reject to use online payment service because of concern about sensitive information leaks such as passwords and credit card details. Accordingly, PayPal service allows users to pay online without a provision of sensitive information. Final Square case result, Mobile POS -based payment service, also shows that it targets on second tier of non-customer who can't individually transact offline because of cash's shortness. Hence, Square provides dongle which function as POS by putting dongle in earphone terminal. As a result, four cases made non-customer their customer so that they could penetrate early market and had been extended their market share. Consequently, all cases supported the hypothesis and it is highly probable according to 'analytic generation' that case study methodology suggests. We present for judging the quality of research designs the following. Construct validity, internal validity, external validity, reliability are common to all social science methods, these have been summarized in numerous textbooks(Yin, 2014). In case study methodology, these also have served as a framework for assessing a large group of case studies (Gibbert, Ruigrok & Wicki, 2008). Construct validity is to identify correct operational measures for the concepts being studied. To satisfy construct validity, we use multiple sources of evidence such as the academic journals, magazine and articles etc. Internal validity is to seek to establish a causal relationship, whereby certain conditions are believed to lead to other conditions, as distinguished from spurious relationships. To satisfy internal validity, we do explanation building through four cases analysis. External validity is to define the domain to which a study's findings can be generalized. To satisfy this, replication logic in multiple case studies is used. Reliability is to demonstrate that the operations of a study -such as the data collection procedures- can be repeated, with the same results. To satisfy this, we use case study protocol. In Korea, the competition among stakeholders over mobile payment industry is intensifying. Not only main three Telecom Companies but also Smartphone companies and service provider like KakaoTalk announced that they would enter into mobile payment industry. Mobile payment industry is getting competitive. But it doesn't still have momentum effect notwithstanding positive presumptions that will grow very fast. Mobile payment services are categorized into various technology based payment service such as IC mobile card and Application payment service of cloud based, NFC, sound wave, BLE(Bluetooth Low Energy), Biometric recognition technology etc. Especially, mobile payment service is discontinuous innovations that users should change their behavior and noble infrastructure should be installed. These require users to learn how to use it and cause infra-installation cost to shopkeepers. Additionally, payment industry has the strong path dependency. In spite of these obstacles, mobile payment service which should provide dramatically improved value as a products and service of discontinuous innovations is focusing on convenience and security, convenience and so on. We suggest the following to success mobile payment service. First, non-customers of the existing payment service need to be identified. Second, needs of them should be taken. Then, noble payment service provides non-customer who can't pay by the previous payment method to payment method. In conclusion, mobile payment service can create new market and will result in extension of payment market.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.123-145
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• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.1 no.2
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• pp.193-224
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• 2006

When we look into the market economy of our country recently, we learn that the mind of consumption after IMF crisis is very shrunk and the market is led into a serious slump of consumption. For an approach to survive the contraction of the market and the market competition, enterprises command a variety of sales promotion strategy, out of which presentation is a sales promotion strategy to give the same product. The price-discounted strategy through the provision of donation commodity may induce the temporarily-discounted commodity not to be sold to the consumers or make a damage of the images of the brand, or arouse the price war against other companies, or lower the sense of the quality of the commodity. Therefore, it is necessary for a company to meet the end users' demand and also maintain the evaluation of the quality on the consumers' products highly. Therefore, in this study, we have attempted to study and analyze the consumers' satisfaction level and reliability on the donation goods in order to suggest the orientation of the presentation promotion strategy in accordance with the changes of the sales market. In addition, we tried to understand how the recognition, consumers' satisfaction level and reliability on the presentation goods had on the repurchase. With such objectives in this study, we could make an analogy of the following significance and suggestion of study. Firstly, in order to survive a serious competition market, enterprises must execute the product presentation along with diverse events instead of commanding the sales promotion strategy through a simple product presentation. This strategy can be an alternative to lower the danger a person-to-person product presentation may bring about. That is to say, we shall not lower the quality and value of the products but enhance a new image to customers through a product donation occasion together with an event as a new marketing pioneering method. Secondly, during the period of the current economic depression, if a company provides the consumers with an opportunity free of charge through the present special event period and the practical events, it will affect the advertising effect of the goods, the introduction of the customers and customers' repurchase. For this purpose, the company has to heighten customers' preferences by selecting the items customers are liable to prefer and closely analyze the consumers' response and market for such an objective. Thirdly, with the internet age, as the market has a tendency to increase In the number of consumers who do shopping in the internet, the marketing strategy has to build up the strategy of the presentation product instead of a simple offline strategy. For example, a company shall have to draw attention or attraction from end users who intend to do shopping through the online by a product planning expo or a presentation product corner. Fourthly, the excessive sale promotion strategy of presentation products may bring about even a reverse effect on the value of the goods or consumers' attitude as seen above. Therefore, a company has to relay' the value as to the price' to the consumers instead of the sales promotion strategy of donation products just for a temporary sales volume. Conclusively, even if we put the value with a reasonable price through the presentation product strategy in the past, we shall have construct the strategy by providing some plus factors in the price such as the provision of the upgraded products or services instead of just presentation, or the invitation of the events related to diverse events or culture arts from now on.

• 한국벤처창업학회:학술대회논문집
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• 2007.04a
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• pp.375-404
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• 2007

When we look into the market economy of our country recently, we learn that the mind of consumption after IMF crisis is very shrunk and the market is led into a serious slump of consumption. For an approach to survive the contraction of the market and the market competition, enterprises command a variety of sales promotion strategy, out of which presentation is a sales promotion strategy to give the same product. The price-discounted strategy through the provision of donation commodity may induce the temporarily-discounted commodity not to be sold to the consumers or make a damage of the images of the brand, or arouse the price war against other companies, or lower the sense of the quality of the commodity. Therefore, it is necessary for a company to meet the end users' demand and also maintain the evaluation of the quality on the consumers' products highly. Therefore, in this study, we have attempted to study and analyze the consumers' satisfaction level and reliability on the donation goods in order to suggest the orientation of the presentation promotion strategy in accordance with the changes of the sales market. In addition, we tried to understand how the recognition, consumers' satisfaction level and reliability on the presentation goods had on the repurchase. With such objectives in this study, we could make an analogy of the following significance and suggestion of study. Firstly, in order to survive a serious competition market, enterprises must execute the product presentation along with diverse events instead of commanding the sales promotion strategy through a simple product presentation. This strategy can be an alternative to lower the danger a person-to-person product presentation may bring about. That is to say, we shall not lower the quality and value of the products but enhance a new image to customers through a product donation occasion together with an event as a new marketing pioneering method. Secondly, during the period of the current economic depression, if a company provides the consumers with an opportunity free of charge through the present special event period and the practical events, it will affect the advertising effect of the goods, the introduction of the customers and customers' repurchase. For this purpose, the company has to heighten customers' preferences by selecting the items customers are liable to prefer and closely analyze the consumer's response and market for such an objective. Thirdly, with the internet age, as the market has a tendency to increase in the number of consumers who do shopping in the internet, the marketing strategy has to build up the strategy of the presentation product instead of a simple offline strategy. For example, a company shall have to draw attention or attraction from end users who intend to do shopping through the online by a product planning expo or a presentation product corner. Fourthly, the excessive sale promotion strategy of presentation products may bring about even a reverse effect on the value of the goods or consumers' attitude as seen above. Therefore, a company has to relay 'the value as to the price' to the consumers instead of the sales promotion strategy of donation products just for a temporary sales volume. Conclusively, even if we put the value with a reasonable price through the presentation product strategy in the past, we shall have construct the strategy by providing some plus factors in the price such as the provision of the upgraded products or services instead of just presentation, or the invitation of the events related to diverse events or culture arts from now on.

• Cartoon and Animation Studies
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• s.51
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• pp.181-201
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• 2018

The cartoon industry in Korea has continued to decline due to the contraction of published comics market and decrease in the number of comic books rental stores until the 2000s when it rapidly started to experience qualitative changes and quantitative growth due to the emergence of webtoon. The market size of webtoon industry, valued at 420 billion won in 2015, is expected to grow to 880.5 billion won by 2018. Notably, most cartoonists who draw cartoon strips are using digital devices and producing scripts in data, thereby overcoming the geographical, spatial and physical limitation of contents. As a result, a favorable environment for the creation of local ecosystems is generated. While the infrastructures of human resources are steadily growing by region, cartoon industries that are supported by the government policy have shown good performance combined with factors of creative infrastructures in local areas such as webtoon experience centers, webtoon campuses and webtoon creation centers, etc. Nevertheless, it is true that cartoon infrastructures are substantially based on a capital area which leads to an imbalanced structure of cartoon industry. To see the statistics, companies of offline cartoon business in Seoul and Gyeonggi Province make up 87%, except for distribution industry. In addition, companies of online cartoon business which are situated outside of Seoul and Gyeonggi Province form merely 7.5%. Studies and research on local webtoon are inadequate. The existing studies on local webtoon usually focus on its industrial and economic values, mentioning the word "local" only sometimes. Therefore, this study looked into the current status of local webtoon of the present time for the current state of local cartoon ecosystem, middle and long-term support from the government, and an alternative in the future. Main challenges include the expansion of opportunities to enjoy cartoon cultures, the independence of cartoon infrastructure, and the settlement of regionally specialized cartoon cultures. It means that, in order to enable the cartoon ecosystem to settle down in local areas, it is vital to utilize and link basic infrastructures. Furthermore, it is necessary to consider independence and autonomy beyond the limited support by the government. Finally, webtoon should be designated as a culture, which can be a new direction of the development of local webtoon. Furthermore, desirable models should be continuously researched and studied, which are suitable for each region and connect them with regional tourism, culture and art industry. It will allow the webtoon industry to soft land in the industry. Local webtoon, which is a growth engine of regions and main contents of the fourth industrial revolution, is expected to be a momentum for the decentralization of power and reindustrialization of regions.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.227-245
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• 2023

As offline company and online·mobile startups meet in an untact shopping environment, competition among companies in untact shopping is increasing. In this situation, companies need their own clear strategy to create customer value. In particular, it is very important to focus on 'customer experience' to establish such a strategy in an untact shopping environment. Customer experience refers to all processes in which consumers meet and experience a company or brand at a touch point. In this processes consumers decide whether to continue to use the company and brand. In this situation, it is thought that it will be meaningful for research to examine the customer experience of untact shopping. Therefore, this study aimed to examine the customer experience of untact shopping, which is used by all generations after COVID-19, through experience quality, and to examine the impact on the expectation-confirmation Model of untact shopping. The results of this study are as follows. First, as a result of examining whether interaction quality, information quality, and outcome quality affect expectation-confirmation it was found that all qualities except interaction quality affect expectation matching. Second, as a result of examining whether interaction quality, information quality, and outcome quality affect perceived usefulness, it was found that all qualities except interaction quality had an effect. Next, as a result of applying the expectation confirmation model to the untact shopping environment and examining whether the expectation confirmation has an effect on use satisfaction, it was found that there was a positive effect. As a result of examining whether perceived usefulness affects use satisfaction, it was found to have a positive effect. As a result of examining whether perceived usefulness affects expectation confirmation, it was found that there is a positive effect. Finally, as a result of examining whether perceived usefulness affects the intention to continue using untact shopping, it was found to be positive. Next, as a result of examining the effect of use satisfaction on trust, it was found that there was a positive effect. Finally, as a result of investigating whether trust has an effect on the intention to continue using, it was found that there is a positive effect. Looking at the important results especially, information quality was found to have the greatest influence.