• Journal of Information Technology Applications and Management
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• v.11 no.4
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• pp.61-85
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• 2004

It is tried that evaluation areas and items of information system in public sector are derived ration-ally and its weight value call be applied differently to type of information system to enhance validity and objectiveness of measurement in evaluating IS in this research. To obtain the goal of this research, firstly, five sectors - system sector, user sector, organization and management sector, the degree of strategic contribution to IS, and the degree of optimizing re-source in IS - are categorized based on broadly reviewing previous theoretical and practical research. Secondly, IS type in public sector is divided into internal operation one and customer oriented one that is object of the IS, and divided into application oriented and IT infrastructure oriented which are influence by IS. Thirdly, evaluation areas and its items are measured by 5 point scales (Likert summated scales) in addition to analysis of validity and reliability to improve objectiveness of establishing evaluation areas and its items. Fourthly, the weight values in the evaluation areas and its items are derived by using analytic hierarchy process. According to the results of analysis of weight value through AHP, it were found to be 30.4% to organization and management sector. 25.5% to degree of strategic contribution, 21.0% to user sector, 13.5% to degree of optimization of resource management, and 9.6% to system sector. and. different weight values each of the four IS type are proposed which establishing in this research. The main implications of this study is that the criteria by which IS in public sector can be categorized 4 ones is suggested and The weighted evaluation for four types of IS based on the AHP analysis enables proposing an objective evaluation method of IS in public sector for considering individual IS characterics.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.225-236
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• 2014

Productivity of public organizations was far older due to issue more difficult to measure than private organizations. Unlike the private sector, the public sector is a diverse and sometimes conflicting objectives (efficiency, effectiveness, equity, democracy, etc.) exist, it is difficult to measure productivity in a single index. Many departments of government is intricately interrelated and sometimes produced by the joint efforts, it is difficult to allocate performance, incentives and accountability to among departments. And there is the difficulty of collecting data on the productivity indicators of public organizations. Despite these difficulties, we developed a productivity index system and measuring method to systematically introduce the concept of productivity in the local administration. In this paper, the productivity and the productivity index measurement practices of local governments conducted annually from 2011 on was deep into research. First, the report found examples of the governments of the developed countries, productivity measurement, then the way MOPAS(Ministry of Public Administration and Security) measure productivity index of local governments, success factors, the implications were in-depth analysis. Finally, in order to enhance productivity and competitiveness municipalities studied ways to take advantage of the productivity index.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.237-248
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• 2006

Nowadays, the administration is strongly driving self-innovation including public sector to solve problems continuously pointed out as issues of public sector such as the low management achievement, the low productivity and costliness structure, the low ability coping with market changes and ineffectiveness in managing organization. The core of such renovation is the systematic performance management. Provincial public enterprises are also required to furnish system that can measure management results accurately and make payment according to measured results under autonomous management system to raise management efficiency and strengthen competitive power. In this paper, we design framework for measuring management results of provincial public enterprises based on Balanced Scorecard and show the example applied to Gwangiu Metropolitan City Environmental Installations Corp (GEIC).

• Journal of Digital Convergence
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• v.8 no.4
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• pp.205-213
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• 2010

In this days, information resources are very important in the organization. So, Many public institutions as well as private companies eager to IRM(information resource management). Especially, one of core elements in this IRM is server's performance. Determinating server's performance is a big issue of an acquired organization. In this paper, we examine the key performance issue of server purchase and then we proposed the three measurement method of sever's performance that is considered environment of public sector.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.417-422
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• 2009

It is important to verify the validity of indicators assessing PMIS(Public Management Information System) effectiveness in academic research as well as practical affairs. As people invest in the field of Information Technology(IT) or IT system, private corporations are interested in investment in IT and it's business value. Moreover, the need of evaluating effectiveness on the investment in IT with the limited national budget are on the increase in public sector. Therefore, it is necessary to define the construct of PMIS(Public Management Information System) effectiveness so that we systematically compare and measure performance of public informatization project processed by each public organizations. It needs to develop indicators and verify the construct validity of them. we verified the construct validity of indicators assessing PMIS(Public Management Information System) effectiveness on the Administration DB Construction Projects.

• Journal of the Korean housing association
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• v.20 no.6
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• pp.57-65
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• 2009

In Korea, Housing Performance Rating Indication System was first adopted in 2006. Main purpose of the System is on developing criteria which can systematically measure the level of housing performance. Among the five categories of Housing Performance Rating Indication System, Repair Convenience is closely related to Remodeling which has been widely recognized as an alternative to the building reconstruction. Especially, as the actual housing supply level in Korea is reaching almost 100%, it is crucial to expand Long-life Housing through the effective maintenance and management. In addition, consumers should have an access to the performance ratings of apartment buildings on which they can rely on in choosing their own housings. And for construction companies, a performance code enacted by government will provide them with a standard that they can utilize in determining performance level of buildings that they build. This study examines data which has been obtained from the recent application of Housing Performance Rating Indication System and Repair Convenience category is main concern. Findings from the study will provide vital information in improving current Housing Performance Rating Indication System.

• Journal of Information Technology Services
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• v.11 no.2
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• pp.243-258
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• 2012

The G2B system is one of the important information systems in the e-government implementation. It is difficult to measure the cost reduction effect of the system introduction because there are many participants in the complex procurement processes. Previous approaches of the performance evaluation of such processes have been based on conducting some surveys and interviews with statistical methods. Therefore there have been some limitations in the verification of feasibility. Therefore this study tries to suggest a case of performance evaluation about the cost reduction in using of the G2B system by analyzing operational DB data from the G2B system. This study analyzed the procurement processes of G2B system according to 'goods' and 'facilities/services' and classified the procurement processes into 12 sub-processes. By developing an evaluation model for the cost reduction of e-procurement, we derived the whole cost reduction effect was 8,000 billon Won for the use of Korea KONEPS G2B system in 2008. Specially the cost reduction in the private sector was 6,600 billion Won. It was mainly due to the decrease of the offline visits to the related organizations to participate a bidding process. Moreover, the cost reduction of using shopping mall was 1,000 billion Won among the total 1,400 billion Won in the whole public sector. The main contribution of this paper is to show the more objective evaluation result of the use of e-procurement, which verifies the necessity of G2B system.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.171-189
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• 2011

KAs information and knowledge are increasingly becoming more important in the knowledge-driven society, knowledge management, as a very important management paradigm, is securing firm position in private and public sectors. Complying with this paradigm, government-funded research institutes in science-technology sector are actively utilizing knowledge management by employing knowledge management system and evaluating its applications' performance. The purpose of this study is to develop evaluation items and measurement indices to rationally measure knowledge management performance of the government-funded research institutes and to verify the feasibility of applying these evaluation items and indices. To achieve this research goal, the evaluation model of knowledge management performance was constructed by reviewing and integrating the existing studies, and subsequently, evaluation areas, evaluation items, measurement indices were derived from this evaluation model. Also, the feasibility analysis on the evaluation items and measurement indices was performed by means of FGI(Focus Group Interview) with the knowledge management experts belonging to Korean government-funded institutions in science-technology sector. The implications of this study are as follows : in theoretical perspective, this study has proposed a criterion frame to evaluate knowledge management performance, and has rationally drawn evaluation items and measurement indices from the criterion frame. And in practical perspective, this study has improved the validity and practicality of the measurement indices, which can lead to more reasonable and easier evaluation of knowledge management performance of the government-funded research institutes.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.173-182
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• 2023

The UAE government has set its sights on creating a smart, electronic-based government system that utilizes AI. The country's collaboration with India aims to bring substantial returns through AI innovation, with a target of over $20 billion in the coming years. To achieve this goal, the UAE launched its AI strategy in 2017, focused on improving performance in key sectors and becoming a leader in AI investment. To ensure public safety as the role of AI in government grows, the country is working on developing integrated cyber security solutions for SCADA systems. A questionnaire-based study was conducted, using the AI IQ Threat Scale to measure the variables in the research model. The sample consisted of 200 individuals from the UAE government, private sector, and academia, and data was collected through online surveys and analyzed using descriptive statistics and structural equation modeling. The results indicate that the AI IQ Threat Scale was effective in measuring the four main attacks and defense applications of AI. Additionally, the study reveals that AI governance and cyber defense have a positive impact on the resilience of AI systems. This study makes a valuable contribution to the UAE government's efforts to remain at the forefront of AI and technology exploitation. The results emphasize the need for appropriate evaluation models to ensure a resilient economy and improved public safety in the face of automation. The findings can inform future AI governance and cyber defense strategies for the UAE and other countries.

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