• Title/Summary/Keyword: Online marketing

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The Relationships among Social Influence, Use-Diffusion, Continued Usage and Brand Switching Intention of Mobile Services (사회적 영향력과 모바일 서비스의 사용-확산, 그리고 지속적 사용 및 상표 전환의도 간의 관계에 대한 연구)

  • Sang-Hoon Kim;Hyun Jung Park;Bang-Hyung Lee
    • Asia Marketing Journal
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    • v.12 no.3
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    • pp.1-24
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    • 2010
  • Typically, marketing literature on innovation diffusion has focused on the pre-adoption process and only a few studies explicitly examined consumers' post-adoption behavior of innovative mobile services. Besides, prior use diffusion research has considered the variables that determine the consumers' initial adoption in explaining the post adoption usage behavior. However, behavioral sciences and individual psychology suggest that social influences are a potentially important determinant of usage behavior as well. The purpose of this study is to investigate into the effects of network factor and brand identification as social influences on the consumers' use diffusion or continued usage intention of a mobile service. Network factor designates consumer perception of the usefulness of a network, which embraces the concept of network externality and that of critical mass. Brand identification captures distinct aspects of social influence on technology acceptance that is not captured by subjective norm in situations where the technology use is voluntary. Additionally, this study explores the effect of the use diffusion on the brand switching intention, a generally unexplored form of post-adoption behavior. There are only a few empirical studies in the literature addressing the issue of IT user switching. In this study, the use diffusion comprises of rate of use and variety of use. The research hypotheses are as follows; H1. Network factor will have a positive influence on the rate of use of mobile services. H2. Network factor will have a positive influence on variety of use of mobile services. H3. Network factor will have a positive influence on continued usage intention. H4. Brand identification will have a positive influence on the rate of use. H5. Brand identification will have a positive influence on variety of use. H6. Brand identification will have a positive influence on continued usage intention. H7. Rate of use of mobile services are positively related to continued usage intention. H8. Variety of Use of mobile services are positively related to continued usage intention. H9. Rate of use of mobile services are negatively related to brand switching intention. H10. Variety of Use of mobile services are negatively related to brand switching intention. With the assistance of a marketing service company, a total of 1023 questionnaires from an online survey were collected. The survey was conducted only on those who have received or given a mobile service called "Gifticon". Those who answered insincerely were excluded from the analysis, so we had 936 observations available for a further stage of data analysis. We used structural equation modeling and overall fit was good enough (CFI=0.933, TLI=0.903, RMSEA=0.081). The results show that network factor and brand identification significantly increase the rate of use. But only brand identification increases variety of use. Also, network factor, brand identification and the use diffusion are positively related to continued usage intention. But the hypotheses that the use diffusion are positively related to brand switching intention were rejected. This result implies that continued usage intention cannot guarantee reducing brand switching intention.

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Effects of Startup Motivation, Startup Competence, and Startup Support Policy on Startup Satisfaction in Early Startup Companies : Moderating Effect of Social Support (창업동기, 창업역량 및 창업지원 정책이 창업 초기기업의 창업 만족도에 미치는 영향 : 사회적지지의 조절효과)

  • Kang, Young-chul;Ha, Kyu-soo
    • Journal of Venture Innovation
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    • v.5 no.4
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    • pp.1-21
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    • 2022
  • Entrepreneurship has been emphasized in social and national importance. However, survival rate of domestic startups is relatively low. Therefore, it is urgent to come up with a plan to increase the survival rate by improving the satisfaction level of early start-ups. In this study, we investigated the effect of start-up motivation, start-up competence, and start-up support policies of early start-up companies on start-up satisfaction and the moderating effect of social support. Startup motivation were divided into economic motivation and self-actualization motivation in detail. Start-up competence was divided into experience competency and marketing competency in detail. The start-up support policy was divided into start-up fund support and start-up consulting support. An empirical analysis was conducted by receiving online and offline questionnaires from 250 managers of early start-up companies within 7 years of founding. As a result, economic motivation, self-actualization motivation, experience competency, marketing competency, and start-up fund support had a significant positive (+) effect on start-up satisfaction. However, start-up consulting support did not have a significant effect. In addition, the size of the influence on startup Satisfaction was in the order of self-actualization motivation, experience competency, marketing competency, startup fund support, and economic motivation. The moderating effect of social support was found in economic motivation, self-actualization motivation, and experience competency. However, the moderating effect of marketing competency, start-up fund support, and start-up consulting support was not tested. Through the research results, the academic implications that self-actualization motivation and experience competency are key factors in enhancing start-up satisfaction were suggested. In addition, practical implications were suggested that it is necessary to improve the effectiveness of entrepreneurship education programs and entrepreneurship consulting support systems that can maximize the self-realization and experience capabilities of early entrepreneurs.

A Regression-Model-based Method for Combining Interestingness Measures of Association Rule Mining (연관상품 추천을 위한 회귀분석모형 기반 연관 규칙 척도 결합기법)

  • Lee, Dongwon
    • Journal of Intelligence and Information Systems
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    • v.23 no.1
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    • pp.127-141
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    • 2017
  • Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

Customer Behavior Prediction of Binary Classification Model Using Unstructured Information and Convolution Neural Network: The Case of Online Storefront (비정형 정보와 CNN 기법을 활용한 이진 분류 모델의 고객 행태 예측: 전자상거래 사례를 중심으로)

  • Kim, Seungsoo;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.221-241
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    • 2018
  • Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

Electronic Word-of-Mouth in B2C Virtual Communities: An Empirical Study from CTrip.com (B2C허의사구중적전자구비(B2C虚拟社区中的电子口碑): 관우휴정려유망적실증연구(关于携程旅游网的实证研究))

  • Li, Guoxin;Elliot, Statia;Choi, Chris
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.3
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    • pp.262-268
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    • 2010
  • Virtual communities (VCs) have developed rapidly, with more and more people participating in them to exchange information and opinions. A virtual community is a group of people who may or may not meet one another face to face, and who exchange words and ideas through the mediation of computer bulletin boards and networks. A business-to-consumer virtual community (B2CVC) is a commercial group that creates a trustworthy environment intended to motivate consumers to be more willing to buy from an online store. B2CVCs create a social atmosphere through information contribution such as recommendations, reviews, and ratings of buyers and sellers. Although the importance of B2CVCs has been recognized, few studies have been conducted to examine members' word-of-mouth behavior within these communities. This study proposes a model of involvement, statistics, trust, "stickiness," and word-of-mouth in a B2CVC and explores the relationships among these elements based on empirical data. The objectives are threefold: (i) to empirically test a B2CVC model that integrates measures of beliefs, attitudes, and behaviors; (ii) to better understand the nature of these relationships, specifically through word-of-mouth as a measure of revenue generation; and (iii) to better understand the role of stickiness of B2CVC in CRM marketing. The model incorporates three key elements concerning community members: (i) their beliefs, measured in terms of their involvement assessment; (ii) their attitudes, measured in terms of their satisfaction and trust; and, (iii) their behavior, measured in terms of site stickiness and their word-of-mouth. Involvement is considered the motivation for consumers to participate in a virtual community. For B2CVC members, information searching and posting have been proposed as the main purpose for their involvement. Satisfaction has been reviewed as an important indicator of a member's overall community evaluation, and conceptualized by different levels of member interactions with their VC. The formation and expansion of a VC depends on the willingness of members to share information and services. Researchers have found that trust is a core component facilitating the anonymous interaction in VCs and e-commerce, and therefore trust-building in VCs has been a common research topic. It is clear that the success of a B2CVC depends on the stickiness of its members to enhance purchasing potential. Opinions communicated and information exchanged between members may represent a type of written word-of-mouth. Therefore, word-of-mouth is one of the primary factors driving the diffusion of B2CVCs across the Internet. Figure 1 presents the research model and hypotheses. The model was tested through the implementation of an online survey of CTrip Travel VC members. A total of 243 collected questionnaires was reduced to 204 usable questionnaires through an empirical process of data cleaning. The study's hypotheses examined the extent to which involvement, satisfaction, and trust influence B2CVC stickiness and members' word-of-mouth. Structural Equation Modeling tested the hypotheses in the analysis, and the structural model fit indices were within accepted thresholds: ${\chi}^2^$/df was 2.76, NFI was .904, IFI was .931, CFI was .930, and RMSEA was .017. Results indicated that involvement has a significant influence on satisfaction (p<0.001, ${\beta}$=0.809). The proportion of variance in satisfaction explained by members' involvement was over half (adjusted $R^2$=0.654), reflecting a strong association. The effect of involvement on trust was also statistically significant (p<0.001, ${\beta}$=0.751), with 57 percent of the variance in trust explained by involvement (adjusted $R^2$=0.563). When the construct "stickiness" was treated as a dependent variable, the proportion of variance explained by the variables of trust and satisfaction was relatively low (adjusted $R^2$=0.331). Satisfaction did have a significant influence on stickiness, with ${\beta}$=0.514. However, unexpectedly, the influence of trust was not even significant (p=0.231, t=1.197), rejecting that proposed hypothesis. The importance of stickiness in the model was more significant because of its effect on e-WOM with ${\beta}$=0.920 (p<0.001). Here, the measures of Stickiness explain over eighty of the variance in e-WOM (Adjusted $R^2$=0.846). Overall, the results of the study supported the hypothesized relationships between members' involvement in a B2CVC and their satisfaction with and trust of it. However, trust, as a traditional measure in behavioral models, has no significant influence on stickiness in the B2CVC environment. This study contributes to the growing body of literature on B2CVCs, specifically addressing gaps in the academic research by integrating measures of beliefs, attitudes, and behaviors in one model. The results provide additional insights to behavioral factors in a B2CVC environment, helping to sort out relationships between traditional measures and relatively new measures. For practitioners, the identification of factors, such as member involvement, that strongly influence B2CVC member satisfaction can help focus technological resources in key areas. Global e-marketers can develop marketing strategies directly targeting B2CVC members. In the global tourism business, they can target Chinese members of a B2CVC by providing special discounts for active community members or developing early adopter programs to encourage stickiness in the community. Future studies are called for, and more sophisticated modeling, to expand the measurement of B2CVC member behavior and to conduct experiments across industries, communities, and cultures.

The Effect of Information Search Knowledge and Shopping Value on On-line External Information Search Behavior (온라인 외부정보탐색 이용행동에 대한 정보탐색 지식과 쇼핑추구가치의 효과)

  • Hwang, Yun-Yong;Lee, Chang-Won;Choi, Nak-Hwan
    • Journal of Global Scholars of Marketing Science
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    • v.14
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    • pp.17-37
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    • 2004
  • This research is speak that is tendencious in comprehension of external consumer information search behavior using on-line external information source to consumers who use on-line that is used as corporations' main strategic means. That is, classify consumer groups which was atomized according to type inflict consumer's information search knowledge level and shopping value study which use on-line, and decision factors of information search that these groups can influence a difference or each group which use information sources grasped what it is. Result that investigate information search knowledge level difference about study finding on-line information source utilization used mainly portal site, comparison site, auction site. And, utilization shopping pursuit value group used information source by portal site, auction site, niche shopping mall site and hedonic shopping pursuit value group used information source by portal site, auction site, shopping mall site. It confirmed that all variables(i.e. consumer-based variable and web site-based variable) are influencing variously in on-line external information search types. Finally, we proposed different way to erect strategic model about consumers that use on-line with study finding that see.

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An Analysis of Success Factors in Internet Shopping Malls (인터넷 쇼핑몰구축의 성공요인에 대한 분석)

  • 진영배;권영식
    • Journal of the Korea Computer Industry Society
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    • v.2 no.12
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    • pp.1495-1504
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    • 2001
  • The main purpose of this research is to show Internet shopping mall the strategic way with the analysis of success factors in Internet shopping malls. To achieve the above purpose, the success factors and variables were defined by the survey of the reference. Sample malls for the research un selected of shopping malls registered in yahoo, Lycos, Empas and Hanmir regardless of their type and class, and did an online-survey of their operation. From the above method, the following results are deduced. First, there are five factors in the success of Internet shopping malls: the effectiveness of customer management the effectiveness of marketing. the competitiveness of product-sales, the convenience of use, the credibility of product. Second, the effectiveness of marketing is positively related to the number of member, visitors, and sales. Third, the credibility of product is negatively related to the number of member, visitors, and sales. At the end, the number of member and visitor are positively related to sales. This result could provide the managers with highly relevant managerial issues. The implication of the study are discussed and futher research directions are proposed.

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Influential Factors of Digital Customer Experiences on Purchase in the 4th Industrial Revolution Era - Focusing on Moderated Mediating Effects of Digital Self Efficacy- (4차 산업혁명시대의 디지털 고객경험과 구매간 영향관계 - 디지털 자기효능감의 조절된 매개효과를 중심으로-)

  • Jung, Sang Hee;Chung, Byoung Gyu
    • Journal of Venture Innovation
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    • v.3 no.1
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    • pp.101-115
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    • 2020
  • In the era of the 4th Industrial Revolution customers living began to come out, not inside the purchase funnel. Due to the diversity of product selection and the increase in digital channels, the way customers search for information and purchase it is changing innovatively. So, the customer journey in the digital age is much more complicated than the traditional funnel model suggests. Unlike many previous studies, this study was conducted for 1,200 customers in four product groups of fashion, automobile, cosmetics, and online shopping malls. As a result of the study, we investigated how digital self-efficacy plays a role in purchasing in a series of processes in which digital experience affects customer satisfaction and finally affects purchase. As a theoretical implication, as a result of introducing and testing digital self efficacy as moderated mediation effect. the digital self-efficacy between customer satisfaction and customer loyalty were determined to play a moderated mediation effect role. As a practical implication, it was necessary to actively utilize digital marketing for customers with high digital self-efficacy, but it was suggested that customers with low digital self-efficacy need to be careful about digital marketing fatigue.

Consumer Creativity, Emergent Nature and Engagement of Co-Creation: The Moderating Roles of Consumer Motivations (소비자의 창의성, 창발성 그리고 공동가치창출 활동과의 관계: 소비자 동기요인의 조절효과를 중심으로)

  • Kang, Seong-Ho;Kang, Woo-Seong
    • Journal of Distribution Science
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    • v.14 no.12
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    • pp.107-118
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    • 2016
  • Purpose - In today's markets, new technologies such as social network systems and user generated contents have provided consumers with access to unlimited amounts of information and an ability to communicate with other consumers in the world. Specially, the massive of the internet and the development of online communities and interactive platforms offer the potential to cocreate with a large number of consumers. Significant changes in marketplace suggest that simply being consumer oriented is not enough, so firms must learn from and collaborate with consumers to create values that meet their individual and dynamic needs. In these sense, emergent perspectives in marketing highlight new opportunities for co-opting consumers as a means to define and cocreate value through their engagement. Although the importance of consumer co-creation with firms, the current literature lacks the respond to two questions: (1) who are the most competent consumers for creating the values with firm? and (2) what are the stimulaters to help the consumers engage for co-creation? To this answer the question, this research investigate how to structure consumer motivations to encourage consumers to be more engaged for co-creation and what drives a consumer to get involved to respond to a call for co-creation. Research design, data, and methodology - To empirically test the hypotheses, a survey was conducted among consumers who had experienced the co-creation including upstream, downstream, autonomous, and sponsored co-creation with the firms. We collected a total of 343 responses. After we excluded 37 questionnaire because of incomplete responses, a total of 306 questionnaire remained. Working with a sample of 306 responses in Seoul and Kwangju, hierarchical moderated regression is employed to test research hypotheses. Results - The results indicated that consumer creativity and emergent nature are positively related to engagement in co-creation including upstream, downstream, autonomous, and sponsored co-creation. Also, the relationships between consumer creativity/emergent nature and engagement in co-creation were moderated by intrinsic motivation in case of upstream and downstream co-creation. Finally, interaction effects between consumer creativity/emergent nature and extrinsic motivation were not significant. Conclusions - These results suggest that marketing managers have to consider the consumer personality such as creativity and emergent nature and stimulate the intrinsic motivation of consumer to achieve the co-creation project successfully.

Analysis of Priorities for the Provision of Book Curation Service by Teacher Librarian Using AHP (AHP를 이용한 사서교사의 북큐레이션 서비스 제공에 대한 우선순위 분석)

  • Kim, Mi-Jung;Lee, Byeong-Kee;Lim, Jeong-Hoon
    • Journal of Korean Library and Information Science Society
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    • v.51 no.3
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    • pp.303-324
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    • 2020
  • This study aims to identify priorities in book curation service that the teacher librarians perceive important through the AHP (Analytic Hierarchy Progress) method by comparing the jobs of teacher librarians with those of curators and selecting the contents and areas of book curation service provided by school libraries. For the purpose, this study categorized the book curation service areas by class and analyzed the priorities in the book curation service areas in the school libraries by applying the AHP method on the teacher librarians who are the personnel in school libraries. As a result, the priorities in the upper-tier class were turned out to be information services, improvement of expertise, information resources, management, and promotion & marketing in that order. The priorities in the lower-tier evaluation areas were shown in the order of survey & research, Q&A, self-development, exhibition, budget allocation, connecting with experts, trend analysis, reading education, human resources, planning, collaboration class, marketing services, book status, online promotion, offline promotion, and facilities & environment. Based on the results, this study suggested the following plans to provide effective book curation services in school libraries: grasping characteristics of school library users, setting classification criteria for book curation, and finding reader participation-oriented book curation service.