• Title/Summary/Keyword: 서비스 요소

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Contents analyses of teaching·learning research on housing education of home economics for secondary schools (중등학교 주생활교육 교수·학습 개발연구 내용분석)

  • Joo, Hyunjung;Cho, Jaesoon;Choi, Yoori
    • Journal of Korean Home Economics Education Association
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    • v.29 no.3
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    • pp.33-48
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    • 2017
  • The purpose of this research was to analyze the contents of housing teaching learning studies in Home Economics of secondary schools since 2001. The 22 research, drawn from the database 'riss4u', were analyzed in terms of general information of the paper (studied institution & year, implementation & evaluation, subject of study & size) and specific contents of teaching learning plans (theme, curricula & textbooks, methode & # of lessons, resources). The results showed that most studies were reported during the 7th or the 2007 revised curricula period. All, except one doctoral dissertation, were master's theses from a few universities. In all studies, ranging from 2 to 15 lessons, teaching learning plans were implemented and evaluated in the class of the researcher while some were applied in other schools, too. The theme of the teaching learning plans varied but were concentrated on one out of two content elements and two out of six learning elements. The 2007 revised curriculum seems to be an important turning point, not only reinforcing the analyses of the curricular and textbooks in the analyzing stage but also facilitating the use of various methods for the lessons in the developing stage. Practical problem based model was the most frequently adopted, while cooperative learning and ICT served as fundamental although not always mentioned. Various teaching resources such as UCC, reading materials, PPT were developed for the teacher. Activity sheets were the most frequently used for the students, followed by reading materials. Because teaching learning is an essential core of education, teaching learning studies should be more actively conducted and the variety of subject topics, methods and resources should also be obtained by more researchers.

The Present Situation and Challenges of the Russian Music Industry: Centered on the Digital Sound Sources (러시아 음악 산업 현황과 과제 - 디지털 음원을 중심으로 -)

  • Kwon, ki-bae;Kim, Se-il
    • Cross-Cultural Studies
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    • v.50
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    • pp.395-424
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    • 2018
  • The purpose of this paper is to examine the current situation and background of the Russian consumer music market, where digital music sources are making great strides in the noted recent years. In addition, music storage technology, media and change are considered together in this report. Moreover, Russia is the 12th largest music market in the world. The Russian music industry is following the recent trend of the global music industry, where the digital music market is growing rapidly on many different levels. The explosive growth of the digital sound sources in Russia's music industry is attributed to the explosive increase in available consumer downloads, streaming sound source service, and the increase in the number of digital sound sources using mobile technologies due to the development of the Internet. In particular, the sales of the available and accessible streaming sound sources are expected to grow explosively by the year 2020, which is expected to account for more than 85% of total digital music sales. In other words, the spread of smartphones and the resulting changes in the lifestyle of the Russians have created these changes for the global consumer of music. In other words, the time has come for anyone to easily access music and listen to music without a separate audio or digital player. And the fact that the Russian government's strong policy on the eradication of illegal copying of music is becoming an effective deterrent, as is also the factor that led to the increase of the share of the digital sound source to increase sales in Russia. Today, the Russian music industry is leading this change through the age and process of simply adapting to the digital age. Music is the most important element of cultural assets, and it is the beneficial content, which drives the overall growth of the digital economy. In addition, if the following five improvements(First, strengthen the consciousness of the Russian people about copyright protection; Second, utilizing the Big Data Internet resources in the digital music industry; Third, to improve the monopoly situation of digital music distributors; Fourth, distribution of fair music revenues; and Fifth, revitalization of a re-investment in the current Russian music industry) are effective and productive, Russia's role and position in the world music market is likely to expand.

A Study on the Application of Other Effective Area-based Conservation Measures(OECMs) for Natural Heritage - Focusing on the Old Big Trees of Natural Monument and Dangsan Ritual - (자연유산의 '기타 효과적인 지역기반 보전수단(OECMs)' 등재기준 적용 연구 - 천연기념물 노거수와 당산제를 중심으로 -)

  • Jun, Da-Seul;Shin, Hyun-Sil
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.40 no.3
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    • pp.1-9
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    • 2022
  • This study compared and reviewed the recognition determinants by applying the OECMs criteria, focusing on old big trees, plant of natural monument that are natural heritage under the national heritage system of the Cultural Heritage Administration, and the results are as follows. First, among the protected areas designated and managed by government agencies according to each protection purpose, it is necessary to actively introduce new conservation measures, OECMs, to fulfill the Biodiversity strategy for 2030 while the land area is already saturated. Second, the OECMs are geographically defined areas(CBD, 2018), not currently recognized as a protected areas, governed and managed in a way that achieves positived sustained and effective contribution to in situ conservation of biodiversity. Since the selection of term, the scope of application criteria, and the context of interpretation are inevitably different, it is necessary to separately legislate and establish related laws of the OECMs suitable for each country's situation. Third, as a result of reviewing the OECMs criteria for plant of natural monument, the final 58 potential resources were recognized. Important elements among the OECMs criteria are that buffer zones should be spaced apart from designated zones to secure a certain area, and that economic activities through commercial production should not occur and meet biodiversity standards. Among the potential candidates, 23 areas were analyzed to be geographically isolated and independent, such as Forest of Oriental Arborvitae in Do-dong, Daegu, and forest types such as Carstor Aralia of Gungchon-ri, Samcheok and Forest of Common Camellias in Maryang-ri, Seocheon. As a result of reviewing the application of OECMs criteria for plant of natural monument, it was confirmed that the functions as a traditional uses were specialized among the values of biodiversity, and ecosystem services and cultural and spiritual values were inherited through Korea's unique culture of old big trees and Dangsan ritual. In terms of biodiversity criteria, it can be used as an important factor in connecting human and natural ecosystem networks without the discovery of new species.

A Study on the Influence of Digital Experience Factors on Purchase Intention and Loyalty in Online Shopping Mall - Focusing on the Mediating Effect of Flow - (온라인 쇼핑몰에서 디지털 경험요인이 구매의도에 미치는 영향에 관한 연구 : 플로우의 매개효과를 중심으로)

  • Jung, Sang-hee
    • Journal of Venture Innovation
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    • v.3 no.2
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    • pp.147-175
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    • 2020
  • This study analyzed the effects that digital experience factors influence on purchase intention and the purchase. The study targeted an online shopping mall with a strong digital experience value among industries. The research model was derived by adding variables to independent and mediating variables according to the industry context of online shopping which is based on the theoretical background and previous studies. Product variety, price efficiency, convenience and conversation were used by terms of digital marketing mix as independent variables. Personalization has been very important factor in online shopping malls, and therefore added as a independent variable. Flow has been added as a mediating variable. Purchase and purchase intention has been used as dependent variables. For empirical testing of established research models and generalization of research results, research was conducted on online shopping malls where digital experiences are important. To do this, a survey was conducted for existing users of online shopping malls. In hypothesis testing, the hypothesis was established that product diversity, price efficiency, convenience, conversation and personalization influenced the intention to purchase online shopping. In particular, the product diversity and conversation variable were tested as the most influential factors on purchase intention. For price efficiency and personalization there were no statistically significant effect. Flow has been shown to be a partial mediator between Product variety and purchase intention in online shopping. In particular, in the case of personalization, it was tested to have a significant influence on purchase intention only when there was a flow experience called pleasure and immersion. This is because the flow experience of pleasure and immersion has played a full mediating role and significantly has affected the purchase intention, because the consumers themselves have to carry out the overall purchase journey without human help due to the nature of online. In the digital experience economy, since consumers are mostly digital consumers, where communication and sharing are the basics, they have been conducting digital word-of-mouth communication and sharing naturally before purchasing. Based on these results, theoretical and practical implications were suggested.

Research Trend Analysis Using Bibliographic Information and Citations of Cloud Computing Articles: Application of Social Network Analysis (클라우드 컴퓨팅 관련 논문의 서지정보 및 인용정보를 활용한 연구 동향 분석: 사회 네트워크 분석의 활용)

  • Kim, Dongsung;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.20 no.1
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    • pp.195-211
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    • 2014
  • Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

Directions of Implementing Documentation Strategies for Local Regions (지역 기록화를 위한 도큐멘테이션 전략의 적용)

  • Seol, Moon-Won
    • The Korean Journal of Archival Studies
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    • no.26
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    • pp.103-149
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    • 2010
  • Documentation strategy has been experimented in various subject areas and local regions since late 1980's when it was proposed as archival appraisal and selection methods by archival communities in the United States. Though it was criticized to be too ideal, it needs to shed new light on the potentialities of the strategy for documenting local regions in digital environment. The purpose of this study is to analyse the implementation issues of documentation strategy and to suggest the directions for documenting local regions of Korea through the application of the strategy. The documentation strategy which was developed more than twenty years ago in mostly western countries gives us some implications for documenting local regions even in current digital environments. They are as follows; Firstly, documentation strategy can enhance the value of archivists as well as archives in local regions because archivist should be active shaper of history rather than passive receiver of archives according to the strategy. It can also be a solution for overcoming poor conditions of local archives management in Korea. Secondly, the strategy can encourage cooperation between collecting institutions including museums, libraries, archives, cultural centers, history institutions, etc. in each local region. In the networked environment the cooperation can be achieved more effectively than in traditional environment where the heavy workload of cooperative institutions is needed. Thirdly, the strategy can facilitate solidarity of various groups in local region. According to the analysis of the strategy projects, it is essential to collect their knowledge, passion, and enthusiasm of related groups to effectively implement the strategy. It can also provide a methodology for minor groups of society to document their memories. This study suggests the directions of documenting local regions in consideration of current archival infrastructure of Korean as follows; Firstly, very selective and intensive documentation should be pursued rather than comprehensive one for documenting local regions. Though it is a very political problem to decide what subject has priority for documentation, interests of local community members as well as professional groups should be considered in the decision-making process seriously. Secondly, it is effective to plan integrated representation of local history in the distributed custody of local archives. It would be desirable to implement archival gateway for integrated search and representation of local archives regardless of the location of archives. Thirdly, it is necessary to try digital documentation using Web 2.0 technologies. Documentation strategy as the methodology of selecting and acquiring archives can not avoid subjectivity and prejudices of appraiser completely. To mitigate the problems, open documentation system should be prepared for reflecting different interests of different groups. Fourth, it is desirable to apply a conspectus model used in cooperative collection management of libraries to document local regions digitally. Conspectus can show existing documentation strength and future documentation intensity for each participating institution. Using this, documentation level of each subject area can be set up cooperatively and effectively in the local regions.

Categorizing Quality Features of Franchisees: In the case of Korean Food Service Industry (프랜차이즈 매장 품질요인의 속성분류: 국내 외식업을 중심으로)

  • Byun, Sook-Eun;Cho, Eun-Seong
    • Journal of Distribution Research
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    • v.16 no.1
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    • pp.95-115
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    • 2011
  • Food service is the major part of franchise business in Korea, accounting for 69.9% of the brands in the market. As the food service industry becomes mature, many franchisees have struggled to survive in the market. In general, consumers have higher levels of expectation toward service quality of franchised outlets compared that of (non-franchised) independent ones. They also tend to believe that franchisees deliver standardized service at the uniform food price, regardless of their locations. Such beliefs seem to be important reasons that consumers prefer franchised outlets to independent ones. Nevertheless, few studies examined the impact of qualify features of franchisees on customer satisfaction so far. To this end, this study examined the characteristics of various quality features of franchisees in the food service industry, regarding their relationship with customer satisfaction and dissatisfaction. The quality perception of heavy-users was also compared with that of light-users in order to find insights for developing differentiated marketing strategy for the two segments. Customer satisfaction has been understood as a one-dimensional construct while there are recent studies that insist two-dimensional nature of the construct. In this regard, Kano et al. (1984) suggested to categorize quality features of a product or service into five types, based on their relation to customer satisfaction and dissatisfaction: Must-be quality, Attractive quality, One-dimensional quality, Indifferent quality, and Reverse quality. According to the Kano model, customers are more dissatisfied when Must-be quality(M) are not fulfilled, but their satisfaction does not arise above neutral no matter how fully the quality fulfilled. In comparison, customers are more satisfied with a full provision of Attactive quality(A) but manage to accept its dysfunction. One-dimensional quality(O) results in satisfaction when fulfilled and dissatisfaction when not fulfilled. For Indifferent quality(I), its presence or absence influences neither customer satisfaction nor dissatisfaction. Lastly, Reverse quality(R) refers to the features whose high degree of achievement results in customer dissatisfaction rather than satisfaction. Meanwhile, the basic guidelines of the Kano model have a limitation in that the quality type of each feature is simply determined by calculating the mode statistics. In order to overcome such limitation, the relative importance of each feature on customer satisfaction (Better value; b) and dissatisfaction (Worse value; w) were calculated following the formulas below (Timko, 1993). The Better value indicates how much customer satisfaction is increased by providing the quality feature in question. In contrast, the Worse value indicates how much customer dissatisfaction is decreased by providing the quality feature. Better = (A + O)/(A+O+M+I) Worse = (O+M)/(A+O+M+I)(-1) An on-line survey was performed in order to understand the nature of quality features of franchisees in the food service industry by applying the Kano Model. A total of twenty quality features (refer to the Table 2) were identified as the result of literature review in franchise business and a pre-test with fifty college students in Seoul. The potential respondents of our main survey was limited to the customers who have visited more than two restaurants/stores of the same franchise brand. Survey invitation e-mails were sent out to the panels of a market research company and a total of 257 responses were used for analysis. Following the guidelines of Kano model, each of the twenty quality features was classified into one of the five types based on customers' responses to a set of questions: "(1) how do you feel if the following quality feature is fulfilled in the franchise restaurant that you visit," and "(2) how do you feel if the following quality feature is not fulfilled in the franchise restaurant that you visit." The analyses revealed that customers' dissatisfaction with franchisees is commonly associated with the poor level of cleanliness of the store (w=-0.872), kindness of the staffs(w=-0.890), conveniences such as parking lot and restroom(w=-0.669), and expertise of the staffs(w=-0.492). Such quality features were categorized as Must-be quality in this study. While standardization or uniformity across franchisees has been emphasized in franchise business, this study found that consumers are interested only in uniformity of price across franchisees(w=-0.608), but not interested in standardizations of menu items, interior designs, customer service procedures, and food tastes. Customers appeared to be more satisfied when the franchise brand has promotional events such as giveaways(b=0.767), good accessibility(b=0.699), customer loyalty programs(b=0.659), award winning history(b=0.641), and outlets in the overseas market(b=0.506). The results are summarized in a matrix form in Table 1. Better(b) and Worse(w) index indicate relative importance of each quality feature on customer satisfaction and dissatisfaction, respectively. Meanwhile, there were differences in perceiving the quality features between light users and heavy users of any specific franchise brand in the food service industry. Expertise of the staffs was labeled as Must-be quality for heavy users but Indifferent quality for light users. Light users seemed indifferent to overseas expansion of the brand and offering new menu items on a regular basis, while heavy users appeared to perceive them as Attractive quality. Such difference may come from their different levels of involvement when they eat out. The results are shown in Table 2. The findings of this study help practitioners understand the quality features they need to focus on to strengthen the competitive power in the food service market. Above all, removing the factors that cause customer dissatisfaction seems to be the most critical for franchisees. To retain loyal customers of the franchise brand, it is also recommended for franchisor to invest resources in the development of new menu items as well as training programs for the staffs. Lastly, if resources allow, promotional events, loyalty programs, overseas expansion, award-winning history can be considered as tools for attracting more customers to the business.

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Resolving the 'Gray sheep' Problem Using Social Network Analysis (SNA) in Collaborative Filtering (CF) Recommender Systems (소셜 네트워크 분석 기법을 활용한 협업필터링의 특이취향 사용자(Gray Sheep) 문제 해결)

  • Kim, Minsung;Im, Il
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.137-148
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    • 2014
  • Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used

    . Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.

  • A study on the Success Factors and Strategy of Information Technology Investment Based on Intelligent Economic Simulation Modeling (지능형 시뮬레이션 모형을 기반으로 한 정보기술 투자 성과 요인 및 전략 도출에 관한 연구)

    • Park, Do-Hyung
      • Journal of Intelligence and Information Systems
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      • v.19 no.1
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      • pp.35-55
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      • 2013
    • Information technology is a critical resource necessary for any company hoping to support and realize its strategic goals, which contribute to growth promotion and sustainable development. The selection of information technology and its strategic use are imperative for the enhanced performance of every aspect of company management, leading a wide range of companies to have invested continuously in information technology. Despite researchers, managers, and policy makers' keen interest in how information technology contributes to organizational performance, there is uncertainty and debate about the result of information technology investment. In other words, researchers and managers cannot easily identify the independent factors that can impact the investment performance of information technology. This is mainly owing to the fact that many factors, ranging from the internal components of a company, strategies, and external customers, are interconnected with the investment performance of information technology. Using an agent-based simulation technique, this research extracts factors expected to affect investment performance on information technology, simplifies the analyses of their relationship with economic modeling, and examines the performance dependent on changes in the factors. In terms of economic modeling, I expand the model that highlights the way in which product quality moderates the relationship between information technology investments and economic performance (Thatcher and Pingry, 2004) by considering the cost of information technology investment and the demand creation resulting from product quality enhancement. For quality enhancement and its consequences for demand creation, I apply the concept of information quality and decision-maker quality (Raghunathan, 1999). This concept implies that the investment on information technology improves the quality of information, which, in turn, improves decision quality and performance, thus enhancing the level of product or service quality. Additionally, I consider the effect of word of mouth among consumers, which creates new demand for a product or service through the information diffusion effect. This demand creation is analyzed with an agent-based simulation model that is widely used for network analyses. Results show that the investment on information technology enhances the quality of a company's product or service, which indirectly affects the economic performance of that company, particularly with regard to factors such as consumer surplus, company profit, and company productivity. Specifically, when a company makes its initial investment in information technology, the resultant increase in the quality of a company's product or service immediately has a positive effect on consumer surplus, but the investment cost has a negative effect on company productivity and profit. As time goes by, the enhancement of the quality of that company's product or service creates new consumer demand through the information diffusion effect. Finally, the new demand positively affects the company's profit and productivity. In terms of the investment strategy for information technology, this study's results also reveal that the selection of information technology needs to be based on analysis of service and the network effect of customers, and demonstrate that information technology implementation should fit into the company's business strategy. Specifically, if a company seeks the short-term enhancement of company performance, it needs to have a one-shot strategy (making a large investment at one time). On the other hand, if a company seeks a long-term sustainable profit structure, it needs to have a split strategy (making several small investments at different times). The findings from this study make several contributions to the literature. In terms of methodology, the study integrates both economic modeling and simulation technique in order to overcome the limitations of each methodology. It also indicates the mediating effect of product quality on the relationship between information technology and the performance of a company. Finally, it analyzes the effect of information technology investment strategies and information diffusion among consumers on the investment performance of information technology.

    Development of Beauty Experience Pattern Map Based on Consumer Emotions: Focusing on Cosmetics (소비자 감성 기반 뷰티 경험 패턴 맵 개발: 화장품을 중심으로)

    • Seo, Bong-Goon;Kim, Keon-Woo;Park, Do-Hyung
      • Journal of Intelligence and Information Systems
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      • v.25 no.1
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      • pp.179-196
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      • 2019
    • Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.


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