• (The) Korean Journal of Advertising
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• v.27 no.4
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• pp.71-90
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• 2016

Managers of firms often wonder whether advertising expenditure is a mere expense or an investment with foreseeable future returns. When top management makes a decision on the level of advertising expense, it must consider whether an increase in advertising spending will positively affect brand loyalty and the increased brand loyalty will positively affect profitability and firm value. We investigate the industry-specific effects of advertising spending on marketing and the effect of loyalty on financial performances using top companies in Korea, specifically, 184 firms' data from year 1998 to 2014. The empirical results of a fixed effect model indicate that the effects of advertising on customer satisfaction index and loyalty on the firms' financial performance are positive. In service industry, unlike manufacturing industry, advertising has a significantly positive effect Brand Loyalty. In addition, Brand Loyalty had positive impacts on ROA and ROE as profitability index, and Tobin's q, a market-value index. The research results suggest that advertising in service industry should be considered as customer satisfaction investment and the increased Brand Loyalty as a profit for present and a business investment for the future respectively.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.151-180
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• 2003

We examine the interdependence of the major Asia-Pacific stock markets including S&P 500, FTSE 100, Kualar Lumpur Composite, Straits Times, Hang Seng, NIKKEI 225 and KOSPI 200 from October 4, 1995 to March 31,2000. The analysis employs the vector-auto-regression, Granger causality, impulse response function and variance decomposition using daily returns on the national stock market indices. The findings in this paper indicate that the volatilities of all countries has grown after IMF crisis, while there is no significance in cointegration test of both total period and sub-periods. This result implies that investors are able to get abnormal returns by investment diversification according to the portfolio theory. We find that while the effect from NIKKEI 225 to others is relatively weak, the interdependence from S&P 500 to other countries is strong. Also we find that the strong effect from Straits Times to Hang Seng exists. This study suggests that there is slight feedback relation between KOSPI 200 and Kualar Lumpur Composite, Straits Times, Hang Seng stock market.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.6
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• pp.97-109
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• 2011

Korea introduced the cooperation charge on conservation of ecosystem for minimizing damage of ecosystem due to development projects and their effects and for preparing resources for natural environment conservation projects. Advanced countries have made efforts by expanding investment in natural environment conservation and restoring projects to promote prevention of global warming and improvement of biological diversity, are establishing nationwide strategies and plans. To examine the reality of projects by returns of the cooperation charge on conservation of ecosystem, microsite projects in schools and public facilities take the largest share while their project budgets are only about 100~300 KRW, relatively small, which might be attributable to budget restrictions in accordance with the calculating method of levying cooperation charge on conservation of ecosystem and problems of project proceeding in the system of returning fund for projects in general. The conclusion which this study suggests on invigoration of cooperation charge on conservation of ecosystem and its operation are as followings. First, although the cooperation charge on conservation of ecosystem has been introduced in 2001, the amount of imposition per unit area remains unchanged. It is desirable to increase the amount into $1,400KRW/m^2$ as of August, 2011 as the price index has been continuously rising for the past 10 years and the upward adjustment of imposition per unit area should be notified by the decree of the Ministry of Environment every January. Second, the ceiling amount of the cooperation charge on conservation of ecosystem should be abolished. Now the ceiling amount is defined as 1 billion KRW but it was found that there was not any ceiling amount specified according to the comparative analysis of similar systems with the Korean environmental improvement fund. The ceiling should be abolished so that medium level businesses are carried out and ecosystem recovering projects in the true sense of the word can be made smoothly. Third, weight should be introduced in calculating amounts in accordance with ecologic and economic values. Harmony between development and environment can be achieved by applying differentiated weights of constant regional coefficient by use zone and ecologic and economic values. Continuous efforts of improving cooperation charge on conservation of ecosystem should be made more than anything else so that projects by returns of cooperation charge on conservation of ecosystem get effectiveness.

• Journal of Digital Convergence
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• v.3 no.2
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• pp.73-116
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• 2005

When people contact the government they can use a variety of channels. That is, they go in person to an office, use a telephone service, access information via the Internet, send a letter, or use a third party. Since the Australian Government first recognised the potential of online technology to improve service delivery in its 1997 Investing for Growth statement, it has articulated its policies and strategies for e-government in a number of papers. E-government involves government agencies delivering better programs and services online through the use of new information and communication technologies. The policy papers included Government Online-The Commonwealth's Strategy, launched in April 2000, and a new framework for e-government, Better Services. Better Government, launched in November 2002. Most recently, the Government released Australia's Strategic Framework for the Information Economy in July 2004. These papers outlined the broad directions and priorities for the future of e-government in Australia, and sought to maintain the momentum of agencies' actions under Government Online. One of its key objectives was for agencies to achieve greater efficiency in providing services and a return on their investments in ICT (Information and Communication Technology)-based service delivery. They also stated that investing in e-government should deliver tangible returns, whether they take the form of cost reductions, increased efficiency and productivity, or improved services to business and the broader community Implementation of the Government policy has led to considerable agency investment in ICT-based service delivery. However government policy also requires managers to ensure that program and service delivery is efficient and effective. Efficient and effective use of ICT has the potential to improve service delivery and to make financial savings. This paper outlines how people are using the channels to contact the government in Australia. It also examines the level of satisfaction they have with those services and their preferences and expectations. In addition, this paper aims at identifying the methods used by Australian Government to measure the efficiency and effectiveness of their delivery of services, and at assessing the adequacy of these methods.

• 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.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.12
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• pp.1735-1740
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• 2005

Forty-two single-bearing and 42 twin-bearing mature Angus${\times}$Hereford cows were allocated, seven per cell to 3 replications of 2 stocking rates (3.2 cows/ha; medium stocking rate [MSR], and 3.8 cows/ha; high stocking rate [HSR]) to graze summer-active and winter-active pastures from late pregnancy to the weaning of their calves. Cow liveweights and growth of calves were recorded as well as estimates of pasture quantity and forage intake. Pasture quantity did not differ in the paddocks grazed by single- and twin-bearing cows during pregnancy, nor effectively did forage intake. Subsequently, intake was higher during mid-lactation especially with twin-rearing cows (25% higher than single-rearing cows at the MSR; 9% at the HSR). However, quantity of pasture decreased for twin-rearing cows and was less than that available to single-rearing cows as lactation progressed. Liveweights of twinrearing cows decreased by 16% from late pregnancy to weaning at the MSR, and by 14% at the HSR, compared to decreases of 1% for single-rearing cows. Twin calves were lighter at birth, had slower growth rates, and were lighter at weaning than single calves. In spite of weaning smaller calves twinning increased the output (kg of calf weaned) per cow and per ha, and increased the efficiency (kg calf weaned per unit of forage eaten by the cow) over single calf production by 46% at the MSR and by 58% at the HSR. Twinning also increased the marginal returns from investment in high input pastures required by the enterprise.

• The Journal of Industrial Distribution & Business
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• v.10 no.12
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• pp.35-42
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• 2019

Purpose : This study examines The impact of human resource investment in internal control on stock price crash risk. Effective internal control ensures that information provided is complete and accurate, financial statements are reliable. By overseeing management, internal control systems can reduce agency costs between management and outside parties. In Korea, firms have to disclose information about internal control systems. The working experience of human resources in internal control systems is also provided for interested parties. If a firm hires more experienced internal control personnel, it can better facilitate the disclosure of information. Prior studies reported that information asymmetry between managers and investors increases future stock price crash risk. Therefore, the longer working experience internal control personnel have, the lower probability stock crashes have. Research design, data and methodology : This study analyzed the association between the working experience of internal control personnel and crash risk using regression analysis on KOSPI listed companies for fiscal years 2016 through 2017. The sample consists of 1,034 firm-years of non-financial firms whose fiscal year end on December 31. Career spanning data of internal control personnel was collected from internal control reports. The professionalism(IC_EXP) was measured as the logarithm of the average working experience of internal control personnel in months. Negative conditional skewness(NSKEW) and down-to-up volatility (DUVOL) are used to measure firm-specific crash risk. Both measures are based on firm-specific weekly returns derived from the expanded market model. Results : We find that work experience in internal control environment is negatively related to stock price crashes. Specifically, skewness(NSKEW) and volatility (DUVOL) are reduced when firms have longer tenure of human resources in internal control division. The results imply that firms with experienced internal control personnel are less likely to experience stock price crashes. Conclusions : Stock price crashes occur when investors realize that stock prices have been inflated due to information asymmetry. There is a learning effect when internal control processes are done repetitively. Thus, firms with more experienced internal control personnel could manage their internal control more effectively. The results of this study suggest that firms could decrease information asymmetry by investing in human resources for their internal control system.

• Journal of Korean Society of Forest Science
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• v.95 no.3
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• pp.268-273
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• 2006

This study analyzed the technological change of Korean sawmill industry affected by change of factor price. An aggregate cost function has been estimated to analyze the technological change in Korean sawmill industry between 1970 and 2003 to the technical bias and scale effect. There was substitution among labour, capital, and material, especially in more elastic relation between labour and capital. In addition, domestic sawmill industry was progressed into structure which is biased to labour saving, and capital and material using because of increase of labour price. Since Korean sawmill industry's technology still exhibits an increasing returns to the scale, the large amount of investment has contributed to productivity growth, and the future productivity growth continually depend on the scale effect for some time.

• International Area Studies Review
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• v.13 no.2
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• pp.255-276
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• 2009

This article has examined the international transmission of returns among S&P500, Nikkei225 and SENSEX stock index cash markets using the daily closing prices covered from January 4, 2002 to February 6, 2009. For this purpose we employed dynamic time series models such as the Granger causality analysis and variance decomposition analysis based on VAR model. The main empirical results are as follows; First, according to Granger causality tests we find that S&P500 stock index has a significant prediction power on the changes of SENSEX and Nikkei225 stock index market and vice versa. However, US stock market's influence is dominant to the other stock markets at a significant level statistically. Second, according to variance decomposition, SENSEX stock index is more sensitive to the movement of S&P500 than that of Nikkei225 stock index. These kinds of empirical results shows that the three stock markets are integrated over times and these results will be informative for the international investors to build the world-wide investment portfolio and risk management strategies, etc.

• 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.