Journal of the Korean Society for Library and Information Science
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제50권4호
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pp.55-75
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2016
We analyzed the characteristics of the physicians preferred information sources and barriers through in-depth interviews. Information searches for patient treatment were subdivided into deciding patient treatment methods, understanding the latest treatment trends, and preparing presentation materials for conferences. The variables that affected the search behaviors were identified as being background knowledge on the topic, clinical experience, job title, search skills, user training, and familiarity with the library homepage. PubMed was the most preferred choice because of users' familiarity, reliability, and the vastness of information; Google was also used frequently for easy access and fast search result. The accuracy and the recentness of information were the most significant criteria. Easy interface and convenient access were also considered important due to physicians' time constraints. Searching obstacles were divided into difficulty of searching system, unfamiliar term, too vast resources, difficulty to get fulltext articles and complex advanced search features. The results of this study can be utilized as a basis for improving information service of library and curriculum development for physicians.
Journal of the Korean BIBLIA Society for library and Information Science
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제32권2호
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pp.69-99
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2021
This study aims at exploring what kinds of factors affect university students to choose video contents as information sources of serious leisure activities. Among other, It focuses on the effect of information quality and cognitive authority. This study analyzed 209 sets of data collected by conducting an online survey of university students from across the country. The implications and results of this study are as follows: First, among the sub-components of information quality, timeliness, relevance, and accuracy had a positive effect significantly on the intention of video contents use as an serious leisure information source, and among those of cognitive authority, the characteristics of platforms was the most influential one. Second, the multiple regression analysis was used to figure out that, some sub-components of cognitive authority turned out to have a positive effect significantly on the evaluation of information quality. This study has a significant meaning in that it investigated the intention of video content use with the two factors (information quality and cognitive authority), especially at this time when more and more people are enjoying video contents as an serious leisure information source.
Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.
This study examines the effects of body image and the hedonic shopping orientation of female consumers on using fashion information to purchase skinny jeans. For this purpose, an online survey was carried out during the recent year targeting female consumers who had purchased skinny jeans. A total of 464 responses were analyzed in this study. The SPSS 22.0 program was used to perform frequency analysis, factor analysis, reliability analysis, and multiple regression analysis. The results are as follows. First, interest in appearance and apparel had a significant influence on every factor of the hedonic shopping orientation, except for the relational shopping orientation, and interest in body weight had a significant effect on the enjoying, relational, and impulsive shopping orientations. Additionally, body satisfaction, except for the impulsive shopping orientation, had a significant influence on the enjoying, brand, loyalty, and relational shopping orientations; body dissatisfaction affected the brand, loyalty, relational, and impulsive shopping orientations. Second, the enjoying shopping orientation significantly influenced every factor of fashion information, and the brand shopping orientation had a positive effect on mass media information, but a negative effect on street information. Furthermore, the loyalty shopping orientation had a significant influence only on store information, the relational shopping orientation had a significant effect on both mass media and verbal information, and the impulsive shopping orientation did not exert any influence on any factors of fashion information.
Journal of Korean Society of Archives and Records Management
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제5권1호
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pp.107-136
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2005
With development of information technology that allows bidirectional exchange and access of information made possible the formation of e-Government. The e-Government and the E-Government Act established for its support provides a tool for online access of government information. This brought on many changes in the recordkeeping environment of public institutions, and also guarantees access of government information by the general public. The active disclosure of government information was re-confirmed through the Freedom of Information act that was amended in 2004, and through its contents that offer guidelines for administrative information disclosure and announcements (Prime Minister Orders No.422) As a result of this effort, Ministry of Culture and Tourism Cultural Heritage Administration provide real time update of their homepages with focus on key organizational policies and records. Such changes are expected to other various public organizations. In order for public organizations to accurately and efficiently provide information sources, and in order to provide the public with easy access to such information, development of public infrastructure along with e-Government metadata are necessary. Korea does not yet have e-government metadata that has been standardized, although "GILF Core Element" has analogous functions. However, GILS Core element has been developed without recordkeeping intent, and it has not been successful in establishing a connection with recordkeeping metadata. Therefore, in this study, criteria for e-government metadata are proposed.
Objectives: The distribution of hospitals in Korea is unbalanced in terms of accessibility. Many local public health centers (PHCs) exempt out-of-pocket payments (OOPs) based on local government laws to increase coverage. However, this varies across administrative regions, as many make this exemption for the elderly, while others do not. This study aimed to evaluate the effects of the OOP exemption at local PHCs among elderly individuals. Methods: This study used online data on Korean national law to gather information on individual local governments' regulations regarding OOP exemptions. Individual-level data were gathered from the 2018 Community Health Survey and regional-level data from public online sources. Results: The study analyzed 132 regions and 44 918 elderly people. A statistical analysis of rate differences and 2-level multiple logistic regression were carried out. The rate difference according to whether elderly individuals resided in areas with the OOP exemption was 1.97%p (95% confidence interval [CI], 1.07 to 2.88) for PHC utilization, 1.37%p (95% CI, 0.67 to 2.08) for hypertension treatment, and 2.19%p (95% CI, 0.63 to 3.74) for diabetes treatment. The regression analysis showed that OOP exemption had an effect on hypertension treatment, with a fixed-effect odds ratio of 1.25 (95% CI, 1.05 to 1.48). Conclusions: The OOP exemption at PHCs can affect medical utilization in Korea, especially for hypertension treatment. The OOP exemption should be expanded to improve healthcare utilization in Korea.
With the advent of the Internet-based economy, the dramatic changes in consumption patterns have been witnessed during the last decades. The seminal change has led by Data Technology, the integrated platform of mobile, online, offline and artificial intelligence, which remained unchallenged. In this paper, I use data analysis tool (TexTom) in order to articulate the definitfite notion of data technology from Internet sources. The data source is collected for last three years (November 2015 ~ November 2018) from Google and Naver. And I have derived several key keywords related to 'Data Technology'. As a result, it was found that the key keyword technologies of Big Data, O2O (Offline-to-Online), AI, IoT (Internet of things), and cloud computing are related to Data Technology. The results of this study can be used as useful information that can be referred to when the Data Technology age comes.
The purpose of this study is to investigate the mediating effect of trust when a media broadcaster (such as a disc jockey [DJ]) acting as an information source and the content they provide during live commerce streaming affect acceptance intention. Live commerce is increasing rapidly, offering a new fashion distribution channel by supplementing possible shortcomings of existing online shopping. Data was collected for the empirical study from female consumers in their 20s who actively accepted fashion technology. Statistical analysis of the data was conducted using IBM SPSS Macro Process 3.5. First, the reliability and validity of the variables for information source characteristics, content informativeness, trust, and acceptance intention were verified, and each variable was confirmed as a single factor. Bootstrap analysis was performed using Macro Process Model 4 to reveal the effects of information source characteristics and content informativeness on acceptance intention. As a result of analyzing the mediating effect for each path model with trust as a parameter, it was found that both the direct and indirect effects of the mediating path were significant. This result means that the characteristics of information sources and content informativeness are partially mediated by trust. Therefore, to promote consumer behavior in a live commerce shopping environment, it is necessary to enhance trust. This can be achieved by a media broadcaster with fashion expertise to increase the perception of the attractiveness of the information source and to improve the usefulness of the fashion information being delivered.
The lack of customer satisfaction and trust remains a key barrier to electronic commerce. From the standpoint of online merchants, it is critical to build consumer trust by lessening sources of apprehensions and uneasiness associated with online transactions. This paper explores the relationships between customer satisfaction and intermediary's trustworthiness factors in B2C e-marketplaces. It also aims at examining the effects of consumer characteristics, including propensity to trust and Internet shopping self-efficacy, upon trust and purchase intentions. To meet the research objectives, an empirical study has been conducted by surveying 223 active e-marketplace buyers in Korea. The findings of the present research indicate that customer satisfaction positively affects all the three attributes of trustworthiness (i.e., competence, benevolence, and integrity), and more specifically it has a quite strong association with benevolence. In addition, propensity to trust has no significant influence on trust or purchasing intentions, and only affects benevolence and integrity with no direct effect on competence. Finally, Internet shopping self-efficacy was found to affect both trust and purchasing intentions, suggesting that e-marketplaces seek an online strategy designed to strengthen loyalty for customers with high self-efficacy, while they use a strategy to improve the usability and usefulness of their website to attract customers with low self-efficacy. The paper concludes with implications and directions for future research.
Smart Farm means creating new value in various fields related to agriculture, including not only agricultural production but also distribution and consumption through the convergence of agriculture and ICT. In Korea, a rental smart farm is created to spread smart agriculture, and a smart farm big data platform is established to promote data collection and utilization. It is pushing for digital transformation of agricultural products distribution from production areas to consumption areas, such as expanding smart APCs, operating online exchanges, and digitizing wholesale market transaction information. As such, although agricultural data is generated according to characteristics from various sources, it is only used as a service using statistics and standardized data. This is because there are limitations due to distributed data collection from agriculture to production, distribution, and consumption, and it is difficult to collect and process various types of data from various sources. Therefore, in this paper, we analyze the current state of domestic agricultural data collection and sharing for digital agriculture and propose a data collection and linkage method for artificial intelligence services. And, using the proposed data, we propose a deep learning-based environmental factor recommendation method.
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