• Journal of Digital Convergence
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• v.14 no.6
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• pp.187-197
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• 2016

This research analyzed the relationship and the interaction effect between information understandability and information acquisition level in accordance with government's official message presentation types, in other words, press release in text form, infographic that visualize a large amount of information, and webtoon that helps to understand convoluted information in interesting ways. As a result of research, it was confirmed that there exist both main effect and interaction effect in official message types presented by government and information understandability according to the environmental awareness. In addition, the main effect per each variable was confirmed between official message types presented by government and information understandability according to the environmental awareness; however, the interaction effect per each variable was not confirmed. Such research result is meaningful in that it provides the government with basic data in obtaining the effectiveness and usefulness of the information dependent of the official message types presented by government to the information consumer facing the era of government 3.0.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.183-193
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• 2014

Korean personal data(information) protection law requires privacy policies post on every website. According to recent survey results, users' interests on these policies are low due to these policies' low readability and accessibility. This study proposes a layout that effectively conveys online privacy policy contents, and assesses its impact on information understandability, vividness, and recognition of users. Studies on privacy policies and layouts, media richness theory, social presence theory, and usability are used to develop the new layered approach. Using experiments, three major layouts are evaluated by randomly selected online users. Research results shows that information understandability, vividness, and recognition of privacy policies in the revised-layered approach are higher than those of in the text-only or table-based layouts. This study implies that employing visual guides like icons on privacy policy layouts may increase users' interest in those policies.

• Korean Management Science Review
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• v.18 no.1
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• pp.135-145
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• 2001

In recent environment of dynamic management, there is growing recognition that information and knowledge management systems are essential for efficient/effective decision making by CEO. To cope with this situation, we suggest the Data-Miming scheme as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder’s point of view and EVA (Economic Value-Added), which represents shareholder’s point of view. To mine the new information & Knowledge discovery, we applied the improved genetic algorithms that consider predictability, understandability (lucidity) and reasonability factors simultaneously, we use a linear combination model for GAs learning structure. Although this model’s predictability will be more decreased than non-linear model, this model can increase the knowledge’s understandability that is meaning of induced values. Moreover, we introduce a random variable scheme based on normal distribution for initial chromosomes in GAs, so we can expect to increase the knowledge’s reasonability that is degree of expert’s acceptability. the random variable scheme based on normal distribution uses statistical correlation/determination coefficient that is calculated with training data. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS (Korea Investors Services Financial Analysis System).

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.489-500
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• 2009

This research takes a user-centered approach to define relevance, the core concept in information retrieval. The literature on relevance has identified numerous factors affecting such a judgment. We examined the model of user relevance judgment that describes the relationship between user relevance criteria and different types of relevance with information search task. We consider 7 criteria of user relevance-topicality, novelty, reliability, understandability, specificity, richness, and interest-and 3 type of user relevance-cognitive relevance, situational relevance, and affective relevance. Data were collected from a semi-controlled survey and analyzed by a structural equation modeling. As a result, topicality and reliability were found to be the essential relevance criteria in all information retrieval tasks. In the fact search task, topicality, reliability, novelty, richness, and interest were found to be significant. In the problem solving search task, topicality, reliability, understandability, and specificity were found to be significant. In the decision making search task, topicality, reliability, novelty, understandability, richness, specificity, and interest were found to be significant. In addition, the relationships between types of user relevance were determined. This research made theoretical and practical contributions to the field of information retrieval by identifying a definite model of user relevance judgment.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.1-16
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• 2021

The health functional food market continues to grow, and according to that trend, the subdivision sales of personalized health functional foods, which have been legally prohibited, will be operated as a special regulatory pilot project. Personalized health functional food recommendations have a variety of personalized indicators to consider, and it is believed that algorithmic methods will be needed to proceed in a customized manner considering all of them. This study aims to contribute to the development of the AI-based health functional food recommendation service by studying factors that affect the use of the AI-based health functional food recommendation service. This paper analyzed the intention of use for AI-based health functional food recommendation service based on the information system success model and Technology Acceptance Model. This study considered information quality factors, service quality factor, and system quality factor as independent variables influencing perceived usefulness, perceived ease of use and trust. For empirical analysis, 406 questionnaires were used and the collected data were performed using AMOS 22.0 and SPSS 22.0. Research has shown that the accuracy, timeliness, empathy and availability have a positive effect on usefulness. Understandability and availability has been shown to have a positive effect on ease of use. The accuracy, understandability, empathy and availibility has been shown to have a positive impact on Trust. Usefulness, ease of use and trust all have been shown to have a positive influence on intention of use.

• Fashion & Textile Research Journal
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• v.12 no.1
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• pp.68-79
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• 2010

This study was fulfilled in the purpose of proposing construction strategies of fashion information industry through the analysis of information user's satisfaction/dissatisfaction on information quality. The research was performed through a depth interview. Data were collected from 18 fashion information users(designers and merchandisers) who were working at fashion apparel industry during October to November 2007. Results from the study showed that there were three dimensions and 18 components of satisfaction/dissatisfaction on fashion information quality: Information quality(understandability, value-added, level of detail, relevance, diversity, objectivity, completeness, accuracy, quantitativeness), Service quality(responsiveness, accessibility, cost efficiency, empathy, reliability), System quality(currency, ease of use, format, timeliness). And the information users were perceiving that there were some changes in notion of preferring information, searching for information and usage of information.

• The Journal of Information Systems
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• v.20 no.4
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• pp.1-22
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• 2011

This study addressed trust to collective intelligence for explaining the affecting factors to the intention to use of collective intelligence by dividing the object of trust into a Web site and an information source group. We explored the factors affecting user's continuance intention toward collective intelligence in the view off trust building. We made a well-structured survey of our proposed model and gained 205 cases. We analyzed the proposed research model empirically using partial least square method. The findings are summarized as follows. First, all key factors (relevance, timeless, completeness, understandability) composing of collective intelligence quality have a positive and significant impact on confirmation. Second, confirmation has a significant impact on trust toward a Web site, as well as toward an information source group. The last is that trust toward a Web site influences on continuance intention, whereas trust toward an information source group doesn't.

• Asia pacific journal of information systems
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• v.8 no.2
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• pp.37-51
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• 1998

This study attempts to draw a blueprint of risk analysis for Information Systems (IS). We introduce two main variables for measuring IS risk - business-impact intensity and IS-vulnerability index - through the investigation of information characteristics, business processes and human-related factors. IS-vulnerability index consists of two factors such as degree of openness and degree of preparedness to the threats. Based on these factors, we built two integrative frameworks for risk analysis and management: One is a conceptual framework to enhance the understandability of IS risk itself; the other is an integrative framework to improve the managerial insight of overall IS risk. We then conducted a field study to empirically validate the proposed framework using a structural equations modeling method. We found that IS maturity and business-impact intensity were positively correlated to degree of openness to the threats, while IS maturity was negatively correlated to degree of preparedness to the threats.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.53-68
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• 2015

This article aims to identify the quality factors of public data which have increased as a public issue; analyze the impact of users satisfaction in the perspective of Technology Acceptance Model (TAM), and investigate the effect of service satisfaction on the government's open policy of public data. This study is consistent with Total Data Quality Management (TDQM) of MIT, it focuses on three main qualities except Contextual Data Quality (CDQ) and includes seven independent variables : accuracy, reliability, fairness for Intrinsic Data Quality (IDQ), accessibility, security for Accessibility Data Quality (ADQ), Consistent representation and understandability for Representational Data Quality (RDQ). Basing on TAM, the research model was conducted to examine which factors affect to perceived usefulness, perceived ease of use, service satisfaction and how service satisfaction affects to the government's open policy of public data. The results showed that accuracy, fairness, understandability affect both perceived ease of use and perceived usefulness; while reliability, consistent representation, security, and accessibility affect only perceived ease of use. This article found that the influence of perceived ease of use on perceived usefulness and the influence of these two causes on service satisfaction in the perspective of TAM were significant and it was consistent with prior studies. The service satisfaction when using public data leads to the reliability of public data open policy. As an initial study on unstructured public data open policy, this article offered quality factors that pubic data providers should consider and also present the operation plan of public data open policy in the future.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.328-333
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• 2002

The deeper the hierarchy of a inheritance structure is, the better the reusability of the structure is, but the more difficult the understandability and the maintainability of it is. On the contrary, the shallower the hierarchy is, the worse the abstraction of the inheritance structure is, but the better the understandability and modifiability of it is. Therefore, it is to be desired that a deep hierarchy of a inheritance structure should be split to be shallow for the maintainability of a system. This paper proposed a complexity metric that is based on DIT and NOC of Chidamber and Kemerer, and solved the ambiguity of the metrics of them, which was pointed out by Li. The metric is a simple and heuristic one for measuring the complexity of class inheritance structures by considering the number of ancestor classes and descendant classes and the depth of inheritance hierarchy. This provides a quantitative information for assessing the complexity of a inheritance structure in splitting it.