• Informatization Policy
• /
• v.29 no.3
• /
• pp.61-81
• /
• 2022

This paper explores how the provided information from Enterprise Architecture (EA) affects the activities to for performing IT projects. The IT projects analyzed in this paper are projects to for developing and maintaining Korea Customs' UNI-PASS. This research was conducted based on surveys to demonstrate the effects of the information from EA on activities for IT projects. Information from EA is categorized into propriety, sufficiency and consistency. Activities for IT projects are defined as management, participation, communication, requirement management and human resource. Correlational analysis is used to measure the effects of the inf ormation on the defined activities. The analysis, which verifies the provided information by EA, does not have meaningful correlation with project management nor human resource. For public officials in charge, Sufficiency of the information produces a positive effect on decision making. For operation company, consistency of the information encourages utilization of the resources required for the project. This research suggests that strategies for performing IT projects with EA information that can support the verification of characteristic environments of each project and performance of vital activities required by the participants' roles will ensure the success of government IT projects.

• The Journal of Society for e-Business Studies
• /
• v.24 no.2
• /
• pp.71-89
• /
• 2019

In order to come up with satisfying product and improvement, firms use traditional marketing research methods to obtain consumers' opinions and further try to reflect them. Recently, gathering data from consumer communication platforms like internet and SNS has become popular methods. Meanwhile, with the development of information technology, mobile companies are launching new digital products for children to protect them from harmful content and provide them with necessary functions and information. Among these digital products, Kids Phone, which is a wearable device with safe functions that enable parents to learn childern's location. Kids phone is relatively cheaper and simpler than smartphone but it is noted that there are several problems such as some useless functions and frequent breakdowns. This study analyzes the reviews of Kids phones from domestic mobile companies, identifies the characteristics, strengths and weaknesses of the products, proposes improvement methods strategies for devices and services through SNS consumer analysis. In order to do that customer review data from online shopping malls was gathered and was further analyzed through text mining methods such as TF/IDF, Sentiment Analysis, and network analysis. Customer review data was gathered through crawling Online shopping Mall and Naver Blog/$Caf\acute{e}$. Data analysis and visualization was done using 'R', 'Textom', and 'Python'. Such analysis allowed us to figure out main issues and recent trends regarding kids phones and to suggest possible service improvement strategies based on sentiment analysis.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.12
• /
• pp.688-701
• /
• 2020

This study analyzes the characteristics and change factors of technological cooperation networks in the automotive industry. Using Social Network Analysis (SNA) of 112,009 autonomous driving-related patents filed from 2000 to 2017 by major automotive firms in the world, we investigate the structure of the technological cooperation network. Network characteristics such as density are analyzed through structural characteristic analysis among the network analysis indicators. The structural characteristics of the technology cooperation network are confirmed through analysis of status characteristic indicators, such as the degree of centrality, betweenness centrality, and closeness centrality. Results show that car makers such as Toyota and Hyundai Motors, as well as parts suppliers such as Bosch and Continental, have high-performance technology developments related to autonomous driving. The structural characteristics of the network show that companies participating in cooperative networks for autonomous driving technology development have increased in number and are diversified, and all of the status characteristics indicators have decreased. This can be interpreted as an increasing number of horizontal and complementary forms of technological cooperation between firms. In addition, it was confirmed that the number of participants in the field of autonomous driving technology has increased, and the networks have become more complex.

• The Journal of Society for e-Business Studies
• /
• v.26 no.4
• /
• pp.95-118
• /
• 2021

As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

• Journal of Technology Innovation
• /
• v.24 no.2
• /
• pp.1-20
• /
• 2016

This case is to analyze the structure of technology convergence with social network analysis. More specifically, the convergence structure among input technologies mediated with products is analyzed with 2-mode social network analysis. Products are identified in project's goal and coded as the Korea Standard Industrial Classification. The input technologies are coded as the National Science Technology Classification. The subjects were 401 R&D projects applied to '2012 Convergence Technology Development Project for Small and Medium Businesses' promoted by Korea Technology & Information Promotion Agency for Small and Medium Enterprises. IT sectors had the structure of a particular input technology connected to many products, BT sectors also had a few input technology connected to many products but most were connected to specific products. Therefore We have realized that each convergence area had different convergence structure. There were the difference of connectivity centrality between input technologies and input technologies mediated with products. For IT sectors, the embedded S/W were the highest in both cases. For BT sectors, functional cosmetic development and fermentation technology were the highest in input technologies but fermentation technology was not the highest in input technologies mediated with products. This case defines the convergence based on the real projects and the use for managing and planing projects. Therefore, this case was to make a tool to analyze and design technology convergence projects.

• Journal of Navigation and Port Research
• /
• v.38 no.6
• /
• pp.607-614
• /
• 2014

This article aims to explore and discuss research trends in global cruise industry using keyword network analysis. We visualize keyword networks in each of four groups of 1982-1999, 2000-2004, 2005-2009, 2010-2014 based on the top 20 keyword nodes' degree centrality and betweenness centrality which are selected among four centrality measurements, comparing them with frequency order. The article shows that keyword frequency collected from 240 articles published in international journals is subject to Zipf's law and nodes degree distribution also exhibits power law. We try to find out research trends in global cruise industry to change some important keywords diachronically, visualizing several networks focusing on the top two keywords, cruise and tourism, belonging to all the four year groups, with high degree and betweenness centrality values. Interestingly enough, a new node, China, connecting the top most keywords, appears in the most recent period of 2010-2014 when China has emerged as one of the rapid development countries in global cruise industry. Therefore keyword network analysis used in this article will be useful to understand research trends in global cruise industry because of increase and decrease of numbers of network types in different year groups and the visual connection between important nodes in giant components.

• Korean Journal of Social Welfare
• /
• v.52
• /
• pp.241-272
• /
• 2003

The Self-Support Program was introduced as an antipoverty policy at 2002 year in Korea. But, the Self-Support Program's negative or positive effects have been debated from diverse perspectives to the present. Thus, in this paper, we analyzed the effects of the Self-Support Program using the survey data from program participants. Even though the effects of Workfare Programs can be evaluated by various indicators(ex. income, employment status, poverty status, etc.), in our analysis the effects of the Self-Support Program are evaluated by participants' self-reliant attitudes and behaviors. Major findings are as follows. First, we found that some kinds of self-reliant attitudes(ex. work commitment, self-esteem, etc.) were build up through participation on the Self-Support program, but some kinds of self-reliant factors(job competence and skill, self-sufficiency prospect, etc.) which are more relevant to the self-sufficiency were not build up thorough it. Second, we found the positive effects of the program among people who are females, olders, less educated, more healthy, and the participants who have acquired more certificate of qualifications. Third, we also found that self-support center's job training program, adequate task matching, agency climates and intra-networks influence on the positive effects of the Self-Support Program. These findings suggest that the Self-Support Program has not been successful up to now and it's reformations are required. It means that objectives of the Self-Support Program as an anti-poverty policy must be obvious and program contents must be diverse. And also program administration systems need to be reformed in oder to raise the effectiveness of the Self-Support Program.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.103-128
• /
• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of Navigation and Port Research
• /
• v.33 no.5
• /
• pp.295-301
• /
• 2009

Recently, considerable number of bridges crossing over navigable waterways are under construction for the connection of coastal islands with mainland and the optimization of logistic system However, the most planned bridges have been initiated without paying much attention to ships safety aspects but with great emphasis on the economic factors, it has often been confronted with difficult social issues arising from opposing views and conflicts between building bodies and affected port users. The main reason for the conflicts is the lack of standards or specifications on the bridge design The proper location and scale of sea bridges are suggested in this paper considering fairway design criteria of both domestic and foreign countries, status analysis on the designs of existing and planned bridges, investigation findings of bridge-related marine accidents, the views of pilots and navigators collected through questionnaire. Since there is no general domestic or international design rules on bridge's scale, the design standards proposed in this paper may be useful at initial design stage of bridge.

• Journal of agricultural medicine and community health
• /
• v.25 no.1
• /
• pp.1-9
• /
• 2000

A public perception survey of environmental health due to small-scale industries was conducted in Sudong Myun, Namyangju City, Kyungki Do, recently being changed to industrialized rural community. This survey had the purpose to ascertain public interest, to identify public needs, and to assess participation for environmental health programs of rural community. The results of survey were as follows: 1. The rate of the respondents with factory worker 19.4% and half(53.1%) of respondents had lived nearby the factory. 2. Some respondents were not favor their neighboring factories(30.1%) and have discussed about its environmental problems in community meeting(14.4%) especially in neighborhood adjacent factories. 3. The respondents have perceived that: (1) major problems were water contamination, air pollution, nasty odor, dust, and noise (2) health problems were more serious in employees than in other residents (3) the employers were responsible for environmental problems (4) the health service should provided by public health center channel and participated by the residents (5) most important service for workers was improvement of working conditions. We hope the community environmental and/or occupational health delivery system for the employees and residents will be developed true public health center channel in a rural community on the basis of this result.