• Asia pacific journal of information systems
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• v.17 no.2
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• pp.29-47
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• 2007

Owing to the rapid growth of using the Internet, not only click-and-mortar companies but also brick-and-mortar ones have been expanding their distribution channels into online, Moreover, since online channels are more attractive than offline ones in control and maintenance, switching customers into online ones is emerged as one of very important managerial issues in a view of reduction of cost as well as expansion of services. However, the switched customers should be faced by uncertainties which could not have been experienced in offline. Specifically, in online channels, buyers and sellers are separated temporally and spacially and there are always so many kinds of threat for security as well as not enough systems and conventions for them yet. Therefore, trust has been considered as one of the most critical mechanisms for resolution of such uncertainties in online transactions. However, it is not easy to build and maintain the relationships in online since most of them are virtual and indirect generally. Therefore, in order to switch offline customers into online ones, it is very important to make strategies based on identification of the relationship between online transaction and offline trust which has been built in offline business. Generally offline trust, which has been built independent of online, could not include trust for online-dependent activities such as payment security during or after transactions, while most of online trust include it. Therefore, a customer with high offline trust does not always perceive high security and assure safe transactions. Accordingly, while online trust, where technical capabilities for online security is one of main bases, includes control trust implicitly or explicitly, offline trust does not. However. in spite of such clear discrimination and independence between offline trust and perceived security, there can be the significant dependency between these two beliefs. The customers with high offline trust believe that the company would do some activities for online security for customers' safe transactions since it has been believed of doing well for customers' trust. Theoretically, users' perception of security is interpreted as a kind of control trus, which is trust for company's technical control capacities in order to resolve technical uncertainties in online. Therefore, the relationship between two beliefs can be considered as transference from offline trust to another type trust. that is, control trust. The objective of this study is to analyze the effect of offline trust on online transaction uses mediated by perceived security. For this purpose, we suggest a research model based on technology acceptance model (TAM). Reuse intention is adopted as a dependent variable and TAM is modified by adding perceived risk (PR) as well as two beliefs of using Internet banking, perceived usefulness (PU) and perceived ease of use (PEOU). Moreover, perceive security (PS) is adopted as an external variable for PR and PU, while offline trust (OT) is an antecedent of PS. For an empirical test, sampling from 108 visitors to the banks in Daegu, Korea, we analyze our model by partial least square (PLS) approach. In result, our model is shown to explain 51.4% of the variance in reuse intention and all hypothesis are supported statistically. A theoretical implication of this study is to identify a role of PS between offline trust and reuse intention of using online transaction services. According to our result, PS can be considered as a mediation variable for bridging between two different concepts: trust that explains social aspects of customers and companies, and TAM that explains customers' reuse intention.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.99-124
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• 2012

Our society has long been talking about necessity for innovation. Since companies in particular need to carry out business innovation in their overall processes, they have attempted to apply many innovation factors on sites and become to pay more attention to their innovation. In order to achieve this goal, companies has applied various information technologies (IT) on sites as a means of innovation, and consequently IT have been greatly developed. It is natural for the field of IT to have faced another revolution which is called cloud computing, which is expected to result in innovative changes in software application via the Internet, data storing, the use of devices, and their operations. As a vehicle of innovation, cloud computing is expected to lead the changes and advancement of our society and the business world. Although many scholars have researched on a variety of topics regarding the innovation via IT, few studies have dealt with the issue of could computing as IT. Thus, the purpose of this paper is to set the variables of innovation attributes based on the previous articles as the characteristic variables and clarify how these variables affect "Performance Expectancy" of companies and the intention of using cloud computing. The result from the analysis of data collected in this study is as follows. The study utilized a research model developed on the innovation diffusion theory to identify influences on the adaptation and spreading IT for cloud computing services. Second, this study summarized the characteristics of cloud computing services as a new concept that introduces innovation at its early stage of adaptation for companies. Third, a theoretical model is provided that relates to the future innovation by suggesting variables for innovation characteristics to adopt cloud computing services. Finally, this study identified the factors affecting expectation and the intention to use the cloud computing service for the companies that consider adopting the cloud computing service. As the parameter and dependent variable respectively, the study deploys the independent variables that are aligned with the characteristics of the cloud computing services based on the innovation diffusion model, and utilizes the expectation for performance and Intention to Use based on the UTAUT theory. Independent variables for the research model include Relative Advantage, Complexity, Compatibility, Cost Saving, Trialability, and Observability. In addition, 'Acceptance for Adaptation' is applied as an adjustment variable to verify the influences on the expected performances from the cloud computing service. The validity of the research model was secured by performing factor analysis and reliability analysis. After confirmatory factor analysis is conducted using AMOS 7.0, the 20 hypotheses are verified through the analysis of the structural equation model, accepting 12 hypotheses among 20. For example, Relative Advantage turned out to have the positive effect both on Individual Performance and on Strategic Performance from the verification of hypothesis, while it showed meaningful correlation to affect Intention to Use directly. This indicates that many articles on the diffusion related Relative Advantage as the most important factor to predict the rate to accept innovation. From the viewpoint of the influence on Performance Expectancy among Compatibility and Cost Saving, Compatibility has the positive effect on both Individual Performance and on Strategic Performance, while it showed meaningful correlation with Intention to Use. However, the topic of the cloud computing service has become a strategic issue for adoption in companies, Cost Saving turns out to affect Individual Performance without a significant influence on Intention to Use. This indicates that companies expect practical performances such as time and cost saving and financial improvements through the adoption of the cloud computing service in the environment of the budget squeezing from the global economic crisis from 2008. Likewise, this positively affects the strategic performance in companies. In terms of effects, Trialability is proved to give no effects on Performance Expectancy. This indicates that the participants of the survey are willing to afford the risk from the high uncertainty caused by innovation, because they positively pursue information about new ideas as innovators and early adopter. In addition, they believe it is unnecessary to test the cloud computing service before the adoption, because there are various types of the cloud computing service. However, Observability positively affected both Individual Performance and Strategic Performance. It also showed meaningful correlation with Intention to Use. From the analysis of the direct effects on Intention to Use by innovative characteristics for the cloud computing service except the parameters, the innovative characteristics for the cloud computing service showed the positive influence on Relative Advantage, Compatibility and Observability while Complexity, Cost saving and the likelihood for the attempt did not affect Intention to Use. While the practical verification that was believed to be the most important factor on Performance Expectancy by characteristics for cloud computing service, Relative Advantage, Compatibility and Observability showed significant correlation with the various causes and effect analysis. Cost Saving showed a significant relation with Strategic Performance in companies, which indicates that the cost to build and operate IT is the burden of the management. Thus, the cloud computing service reflected the expectation as an alternative to reduce the investment and operational cost for IT infrastructure due to the recent economic crisis. The cloud computing service is not pervasive in the business world, but it is rapidly spreading all over the world, because of its inherited merits and benefits. Moreover, results of this research regarding the diffusion innovation are more or less different from those of the existing articles. This seems to be caused by the fact that the cloud computing service has a strong innovative factor that results in a new paradigm shift while most IT that are based on the theory of innovation diffusion are limited to companies and organizations. In addition, the participants in this study are believed to play an important role as innovators and early adapters to introduce the cloud computing service and to have competency to afford higher uncertainty for innovation. In conclusion, the introduction of the cloud computing service is a critical issue in the business world.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.487-493
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• 2019

This study examines the ratio of R&D expenses in intangible assets for pharmaceutical companies, and determines whether these expenses affect the firm value among companies listed on the KOSDAQ. The research subjects included annual R&D expenses of 39 pharmaceutical companies listed on the KOSDAQ between 2011 and 2017. The survey was achieved via "Panel Data Model" with "Tobin Q" as an independent variable, and the ratio of R&D expenses in intangible as a dependent variable. Results of the study conclude that the ratio of R&D expenses in intangible assets of KOSDAQ pharmaceutical companies negatively influence the Tobin Q (Enterprise Value). A large proportion of intangible assets indicates increased R & D investment, and the operating profit is likely to be low due to the high debt ratio, thereby negatively impacting the enterprise value. This study further investigates whether the existing researches are based on researches that identify the total value of R & D expenditure. Results determine a significant relationship between enterprise value and R & D expenditure.

• Management & Information Systems Review
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• v.12
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• pp.137-160
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• 2003

The association between accounting earnings and the stock price of an entity is the subject that has been most heavily researched during the past 25 years in accounting literature. Researcher's common finding is that there are positive relationships between accounting earnings and stock prices. However, the explanatory power of accounting earnings which was measured by $R^2$ of regression functions used was rather low. To be connected with these low results, The prior studies propose that there will be additional information, errors in variables. This study investigates empirically determinants of earnings response coefficients(ERCs), which measure the correlation between earnings and stock prices, using earnings level / change, as the dependent variable in the return/earnings regression. Specifically, the thesis tests whether the factors such as earnings persistence, growth, systematic risk, image, information asymmetry and firm size. specially, the determinable variables of ERC are explained in detail. The image / information asymmetry variables are selected to be connected with additional information stand point, The debt / growth variables are selected to be connected with errors in variables. In this study, The sample of firms, listed in Korean Stock Exchange was drawn from the KIS-DATA and was required to meet the following criteria: (1) Annual accounting earnings were available over the 1986-1999 period on the KIS-FAS to allow computation of variables parameter; (2) sufficient return data for estimation of market model parameters were available on the KIS-SMAT month returns: (3) each firm had a fiscal year ending in December throughout the study period. Implementation of these criteria yielded a sample of 1,141 firm-year observation over the 10-year(1990-1999) period. A conventional regression specification would use stock returns(abnormal returns) as a dependent variable and accounting earnings(unexpected earnings) changes interacted with other factors as independent variables. In this study, I examined the relation between other factors and the RRC by using reverse regression. For an empirical test, eight hypotheses(including six lower-hypotheses) were tested. The results of the performed empirical analysis can be summarized as follows; The first, The relationship between persistence of earnings and ERC have significance of each by itself, this result accord with one of the prior studies. The second, The relationship between growth and ERC have not significance. The third, The relationship between image and ERC have significance of each by itself, but a forecast code doesn't present. This fact shows that image cost does not effect on market management share, is used to prevent market occupancy decrease. The fourth, The relationship between information asymmetry variable and ERC have significance of each by. The fifth, The relationship between systematic risk$(\beta)$ and ERC have not significance. The sixth, The relationship between debt ratio and ERC have significance of each by itself, but a forecast code doesn't present. This fact is judged that it is due to the effect of financial leverage effect and a tendency of interest.

• Journal of Technologic Dentistry
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• v.34 no.4
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• pp.433-445
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• 2012

Purpose: In order to validate empirically the theoretical model of this study subjects, who were limited in Andong gun, Youngyang gun, Uiseong gun, Bonghwa gun, Chilgok gun, Cheongsong gun according to residence-specified distribution and over aged 65, were focused to the elderly in rural areas with geographical characteristics where they have difficulties in accessibility of dental facilities and dental care. Methods: The collected data were analyzed by the SPSS 19.0 program. First, the frequency analysis was performed for each independent variable and the dependent variable. Second, reliability analysis and correlation analysis were conducted for daily living skills and Biomedical Vigilance. Third, multivariate analysis was performed in terms of and the post-administration management. Fourth, multiple regression analysis was performed to identify the factors affecting the post-management of dentures and the period of using dentures. Results: By results of the multiple regression analysis, the elder the subjects are(${\beta}$ = 0.03), the lower their income activities are(${\beta}$ = -0.18), the smaller their monthly allowances are(${\beta}$ = -0.16), the worse their daily activity skills are(${\beta}$ = -0.12), the more they were mounted their dentures by an unlicensed contractor(${\beta}$ = 0.07), and the more they cost to their dentures(${\beta}$ = 0.14), the longer the period of use dentures are. And the beneficiaries of Basic Livelihood Security(${\beta}$ = -0.14) who got free denture business are shorten the period of using dentures. According to multiple regression analysis for post management of dentures, the independent variables like the health education(${\beta}$ = 0.24), smoking(${\beta}$ = -0.18), periodic oral examination(${\beta}$ = 0.13), dentures mounted by an unlicensed contractor(${\beta}$ = -0.13) are shown statistically significant results. In that study subjects are taking part in health education and non-smokers, they are likely to have more chances to post management for their dentures like periodic oral examination. However the subjects who were weared their denture by an unlicensed contractor get less chance to post management for their dentures. Conclusion: As the elderly who want to wear denture are increasing due to the denture insurance for the elderly, the need for oral health education for the elderly is an urgent request, especially continuos education for the way of use their dentures and follow-up management for the elderly who were already mounted their dentures. And also, the need for more systematic researches is requested for securing objective data.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Journal of Navigation and Port Research
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• v.33 no.7
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• pp.491-500
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• 2009

In order to attract more transshipment cargoes, Busan Port Authority (BPA) has, since 2003, adopted the volume incentive policy by which more than US$ 10 million annually have been paid back to shipping lines that were called at the port. However, having been a transshipment port for the Northeast region of China, the port of Busan has come under threat from bold Chinese port development projects, notably Shanghai, as northern Chinese regionnl ports place more emphasis on building facilities capable of handling growing trade volumes. Undoubtedly this would lead to a decline in transshipment container traffic moved via Busan. The purpose of this paper is to identify some core factors that have been affecting the increase of transshipment cargoes of Busan and further to recommend BPA an improved incentive scheme with which more T/S cargoes can be attracted into the port of Busan To clarity the reason why T/S cargoes have increased in the port of Busan, several steps are made as follows: The first step is to make a quantitative model for explaining the development of T/S cargoes during the last decade. The second step is to define the dependent and the independent variables for multiple regressions after testing variable significance. For this, data collection and the accuracy of validation have been done by the direct interview with the experienced staffs in shipping companies of both domestic and foreign country. After validating the model with collected data, the final step is to find variables which are explaining the model mostly. In conclusion, 2 variables were clearly identified as core factors that explain well the development of T/S cargoes in the port of Busan: 'Mohring effect' and total cost. It is strongly recommended, by an empirical study, that an incentive scheme be changed to a way which more feeder vessels rather than mother vessels can reduce their direct costs to call in the port of Busan.

• Journal of Distribution Science
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• v.12 no.8
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• pp.113-121
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• 2014

Purpose - Recently, the number of corporations that practice environmental and social responsibility, besides engaging in traditional profit-seeking activities, has been growing steadily, as interest in Corporate Social Responsibility (CSR) is increasing. Recent research on CSR practices has identified the relationship between CSR activities and corporate value as one of the main issues in this respect. Considering that donations constitute a large proportion of a company's charitable activities, we considered the extent of donation expenses as a charitable activity in order to mitigate sample selection bias. Specifically, we analyzed the impact of donation expenses on firm value, while investigating if this impact varied in response to the level of corporate governance of firms. Research design, data, and methodology - We used non-financial firms listed on the Korean Stock Exchange, having their fiscal year end in December, and the sample period was 2006-2013. For the dependent variable, Tobin's q was used as the corporate value, and for the independent variable, donations were measured as the donation-expense-to-sales ratio. Corporate governance scores, as rated by the Korea Corporate Governance Service, were used to measure corporate governance levels because they consider the overall aspects of governance, including ownership structure, the board of directors, and the audit mechanism of individual companies. To examine the impact of donations on a company in relation to the level of corporate governance, we estimated regression models using the interaction terms of the governance dummy and donation variables. Then, we further estimated the regression models of two sub-samples that were classified according to the level of corporate governance. Similar to previous studies, the study uses variables that affect firm value, such as R&D expenditure, advertising expenses, EBITDA, debt-to-equity ratio, sales growth, company age, and company size as control variables. Results - The empirical results show that firm value significantly increased in response to an increase in donation expenses. Upon including the interaction terms of governance level dummy variables and donations, the coefficients of the interaction terms show significant positive values, while those of donation variables show significant negative values. In the strong governance sub-sample, the relationship between the donation expenses and corporate value was statistically positive (+) and significant. However, in the weak governance sub-sample, the relationship between the donation expenses and corporate value was statistically insignificant and negative (-). Conclusions - The empirical results suggest that donation expenses are significantly linked to an enhanced corporate value if firms have a good corporate governance structure. However, if the corporate governance structure is weak, the same relationship is not necessarily observed. The results of this study show that if a firm has high corporate governance, CSR practices enhance the company's reputation such that it has a positive (+) relationship with corporate value. If a firm has weak corporate governance, on the other hand, CSR practices are recognized as an agency cost and do not increase corporate value.

• Journal of IKEEE
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• v.28 no.2
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• pp.150-157
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• 2024

In this paper, we propose a novel algorithm for predicting the number of apples on an apple tree using a deep learning-based object detection model and a polynomial regression model. Measuring the number of apples on an apple tree can be used to predict apple yield and to assess losses for determining agricultural disaster insurance payouts. To measure apple fruit load, we photographed the front and back sides of apple trees. We manually labeled the apples in the captured images to construct a dataset, which was then used to train a one-stage object detection CNN model. However, when apples on an apple tree are obscured by leaves, branches, or other parts of the tree, they may not be captured in images. Consequently, it becomes difficult for image recognition-based deep learning models to detect or infer the presence of these apples. To address this issue, we propose a two-stage inference process. In the first stage, we utilize an image-based deep learning model to count the number of apples in photos taken from both sides of the apple tree. In the second stage, we conduct a polynomial regression analysis, using the total apple count from the deep learning model as the independent variable, and the actual number of apples manually counted during an on-site visit to the orchard as the dependent variable. The performance evaluation of the two-stage inference system proposed in this paper showed an average accuracy of 90.98% in counting the number of apples on each apple tree. Therefore, the proposed method can significantly reduce the time and cost associated with manually counting apples. Furthermore, this approach has the potential to be widely adopted as a new foundational technology for fruit load estimation in related fields using deep learning.

• Journal of Navigation and Port Research
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• v.39 no.1
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• pp.69-75
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• 2015

The concrete purpose of this study is to suggest actually a debt ratio to optimize the capital structure providing a kind of approach to estimate the proper debt ratio with an analytical model and empirical data in Korean shipping industry. The mathematical and analytical model is started from the first equation about ROE, return of net operating income on equity, with an independent variable, debt ratio. It is constructed with several parameters, ROS(return of operating income on sales), TAT(total assets turnover), and NFCL(net finance cost to liabilities). There could not be a certain relationship between debt ratio and ROS or TAT, while some correlation or causality between debt ratio and NFCL. In other words, most of firms with high debt ratio is likely to burden higher finance cost than others with low one. In this case, there is a linearity relationship between debt ratio and NFCL, so then the second equation considering this relation could be included within the analytical approach of this paper. To be short, if the criteria of adequate debt ratio has to be defined as some level of debt ratio to optimize ROE, the ROE could be illustrated as a quadratic equation to debt ratio from two equations. Next, this research estimated those parameters' numbers through the single regression method with data over 12 years of Korean shipping industry, and identified empirically the fact that optimal debt ratio would be approximately 400%. To conclude, if that industry's sales and operating incomes are stable, the debt ratio could be accepted until twice of 200% had forced in order to guarantee its financial safety in past time.