• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.4
• /
• pp.163-172
• /
• 2022

This study investigates the IPI (Information Protection Intention) of DHS (Digital Healthcare Service) providers by introducing PMT (Protection Motivation Theory). This study examines the effects of protection motivation, such as threat appraisal and coping appraisal, on IPI, such as ICI(Induction Control Intention) and SDI(Self Defense Intention). The research model, based on the PMT, adopted severity, vulnerability, reaction efficacy and self-efficacy as independent variables. The research model was validated through quantitative research, a survey of 222 DHS providers in South Korea, using structural equation modeling. The results show that (1) a clear awareness of the consequences of security threats increases the understanding of DHS providers on the severity of closure of healthcare information, and thus may decreases abuse of DHS by providers; (2) user confidence and satisfaction on the security system may make them be confident that they can handle the closure of healthcare information by themselves; and (3) although DHS providers are realizing the consequences of closure of healthcare information, they think that they are unlikely to encounter such situations. As a result of this study, venture companies that provide DHS need to provide contents that can continuously increase providers' security level in order to increase providers' information protection intention. It suggests that IPI is important through trust of healthcare service providers.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.25-38
• /
• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Asia pacific journal of information systems
• /
• v.18 no.3
• /
• pp.91-121
• /
• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

• Journal of Intelligence and Information Systems
• /
• v.27 no.3
• /
• pp.95-112
• /
• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Korean Business Review
• /
• v.4
• /
• pp.355-383
• /
• 1991

1. The Purpose of This study research: The focus of marketing until recently has simply been on sales which means the transfer of goods from the producer to the consumer and on profits therefrom. However, the excess supply of goods due to the expansion of the economy and the resulting fierce competition between companies have changed the nature of marketing. Maximizing consumers' satisfaction and establishing marketing mix strategies for market subdivision and penetration into the target market are now significant roles of the marketing manager. In addition, with regard to company management, information within the company which had been collected, managed and processed sporadically indegrated manner. The purpose of this research on marketing information systems in connection with the above will be to seek ways enabling us to create an efficient and integrated information system for an entire company. 2. The Method and Scop of This Stdudy: Marketing information systems, as a part of management information systems, shall be examined based on relevant theoretical literature. The research process shall be generally developed as follows: 1) The basic structure of the marketing information systems, including its fundamental purpose and necessity, shall be examined. 2) The method for a specific plan shall be presented through fundamental marketing strategy concepts and marketing decision-making. 3) A general model shall be presented based on examinations of various mod els used for marketing information systems and on research of the models' relationship with management information systems. 4) The direction of development shall be presented as the basis for gradual development following examination of the scope, pertinent issues, and means of improvement of the marketing information systems. 3. Summary and Conclusion: As the competition among the enterprises has become keen and thus the management of the contemporary enterprises shows the tendencies of uncertainty as well as complexity, all the managers must make the correct and prompt decision of their mind. Otherwise, the danger which will lead to and failure in the failure in the business may befall to the enterprise. Though computer system and information related techniques have the endless potentiality for the improvement of the enterprise, those are granted only to the enterprise which will be able to manage the computer system and information related techniques. In the contemporary industrial society, the need to a managerial information system has been increasing because all the complicated information can be stored, disposed and managed by the efficient method. And the marketing information system is also the integrated system which has been formed and developed through the efficient mixture of all the constituent elements including the definition of marketing research as the definition of the information system has been enlarged due to the reason shown above. The common point of the two systems is the man machine system functioning to help the efficient decision of the mind by introducing the computer system on the basis of user manager centered thought in order to provide informations to be useful in operation and management of the organization and the function of the mind decision. The purpose for the marketing information system lies in making the utmost use of marketing information available in the course of the mind decision. The reason why the contemporary enterprises necessitate the marketing information system are as follows: 1) The stages of the business operation are expanded wide to the world. 2) As the living standards of the consumers have been on the rise, the enter prise has to satisfy the consumer's "wants" than simple "needs".

• Management & Information Systems Review
• /
• v.28 no.1
• /
• pp.1-24
• /
• 2009

Electronic commerce markets have been increasing rapidly, which has resulted in parallel growth in the door-to-door delivery service industry. The door-to-door delivery service industry is projected to be more competitive, due to the large amount of companies that are already established and the fact that several leading multinational logistics companies are rushing into the domestic market. This is a critical period for the companies which are attempting to obtain a competitive advantage. Previous research on door-to-door delivery services has been undertaken, in relation to strategic exploration, political proposals, and user satisfaction. However, there is a lack of practical studies focused on the information systems of door-to-door service companies and its decisive roles have been undertaken. This study aims to investigate, compare, and analyze the information systems of door-to-door delivery service companies. Also, the study proposes developmental direction of how the information systems should be improved. In order to accomplish the purpose of this study, first, we examined previous research on door-to-door delivery services and their information systems. Second, we investigated and analyzed the information systems of four leading domestic companies by conducting interviews. Third, we compared and identified factors of the information systems that could be improved. Finally, we proposed its developmental direction. As a result of the study, the information systems of door-to-door delivery service companies required to provide classified services using diverse tools and develop the optimized routing model to reduce logistics costs.

• Journal of Digital Contents Society
• /
• v.12 no.1
• /
• pp.85-94
• /
• 2011

QoS(Quality of Service) is defined as "The collective effect of service performance which determines the degree of satisfaction of a user of the service" by ITU-T Rec. E.800. While the use of VoIP(Voice Over Internet Protocol) has been widely implemented, persistent problems with QoS are a very important sue which needs to be solved. This research is finding the assignment of VoIP QoS to deduct how to manage the control system and presenting the QoS control process and framework under NGN(Next Generation Network) environment. The trial framework is the modeling of the QoS measurement metrics, instrument, equipment, method of measurement, the series of cycle & the methodology about analysis of the result of measurement. This research underlines that the vulnerability of the VoIP protocol in relation to its QoS can be guaranteed when the product quality and management are controlled and measured systematically. Especially it's very important time to maintain the research about VoIP QoS measurement and control because the big conversion of new network technology paradigm is now spreading. In addition, when the proposed method is applied, it can reduce an overall delay and can contribute to improved service quality, in relation to signal, voice processing, filtering more effectively.

• Journal of the Korean Society for Library and Information Science
• /
• v.54 no.1
• /
• pp.115-143
• /
• 2020

This study conducted a survey on the current status and satisfaction of libraries participating in the opening hours support project in order to continue it to meet the purpose of improving information access and life welfare. To this end, a questionnaire and interview survey were conducted for those in charge of opening hours for each library, and the results are as follows. First, the opening hours support project is a project that needs a strategy that fits the characteristics of the region and the environment. Therefore, it is necessary to consider operating independently rather than relying on national support in the future through the preparation of regional-oriented operation plans. Second, it is necessary to establish a flexible operating model for opening hours that both employees and users can understand. Third, it is necessary to prepare an organizational operation plan that requires both duties and responsibilities along with the rights equivalent to existing regular employees. Fourth, in order for national public libraries in Korea to develop and implement a consistent policy for specific policies and projects, it is necessary to unify the separate public library operating system in the future. Fifth, it is necessary to prepare education and guidelines for the continuity and stable operation of the project, and to activate services other than labor costs, such as support for improving the space for the user's pleasant use.

• Korean Journal of Environment and Ecology
• /
• v.17 no.3
• /
• pp.285-294
• /
• 2003

The purpose of this paper is to provide useful knowledge for recreation management in natural park(NP) by evaluating use suitability of recreation resource. We had obtained data through a questionnaire, which surveyed 385 visitors at 6 of the 73 NP in Korea in 2001, based on stratified sampling method. We have analyzed the data using the multiple regression method. We found that 1) in bivariate analysis, the relationships between use suitability and all the recreation resources are fairly high and statistically significant. The higher the degree of recreation resources, the higher the degree of use suitability. 2) in multivariate analysis, topography, social resource(SR), cultural resource(CR), landscape, smell, color and sound(SCS) have been turned out to be statistically significant at one percent level. 3) the direction of relationship between topography, SR, CR, landscape, SCS and use suitability is same. 4) in relative contribution of the use suitability of recreation resource, level of topography has been turned out to have about 1.05, 1.56, 2.16 and 2.70 times more important than that of SCS, SR, landscape, topography, respectively This results will be used for a criterion for recreation resource evaluation and a settlement of management priority and increasing user's satisfaction.

• Journal of Digital Convergence
• /
• v.9 no.2
• /
• pp.111-129
• /
• 2011

Nowadays, the IS project is getting more and more complicated and large-scaled. Many researchers and practitioners are interested in the IS development methodologies, automated tools and techniques to decrease project failure and to increase IS project performance. This research is to seize the management level of PMO affecting on the IS project, as a new method to increase the IS project development performance. As a result of surveying the present PMO operation state with banks which are the leading industry to accept the PMO in Korea, technology support management and infrastructure management are the core functions to affect the IS performance including schedule management, quality management, and user and stakeholders' satisfaction. Also, the PMO management level is the important point of IS project success. Among the 5 levels PMI suggested, PMO can implement the project effectively at least at the third level. Korean companies introducing the PMO have to do research the PMO core functions and the management levels according to the project scale, and review the distinctive features of their organization to increase the maturity of IS project. This research has been proved through the Full Structural Equation Model. The results show that the five core functions of PMO have relationship with the IS project performance.