• Information Systems Review
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• v.22 no.2
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• pp.77-99
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• 2020

Smart speaker is a device that provides an interactive voice-based service that can search and use various information and contents such as music, calendar, weather, and merchandise using artificial intelligence. Since AI technology provides more sophisticated and optimized services to users by accumulating data, early smart speaker manufacturers tried to build a platform through aggressive marketing. However, the frequency of using smart speakers is less than once a month, accounting for more than one third of the total, and user satisfaction is only 49%. Accordingly, the necessity of strengthening the user experience of smart speakers has emerged in order to acquire a large number of users and to enable continuous use. Therefore, this study analyzes the user experience of the smart speaker and proposes a method for enhancing the user experience of the smart speaker. Based on the analysis results in two stages, we propose ways to enhance the user experience of smart speakers by model. The existing research on the user experience of the smart speaker was mainly conducted by survey and interview-based research, whereas this study collected the actual review data written by the user. Also, this study interpreted the analysis result based on the smart speaker user experience dimension. There is an academic significance in interpreting the text mining results by developing the smart speaker user experience dimension. Based on the results of this study, we can suggest strategies for enhancing the user experience to smart speaker manufacturers.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.67-84
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• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Management & Information Systems Review
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• v.31 no.1
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• pp.221-246
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• 2012

The study examines the effects that non-audit service and firm's ownership structure might have on the value relevance directly or indirectly. This investigation is based on prior research which suggests that the audit firms' non-audit services is likely to adversely affect investors' perceptions of the credibility of financial reporting and that corporate governance are likely to mitigate the adverse this kind of non-audit services effects. The sample consists of non-banking firms listed on the Korea Exchange that reported annual financial statements over the period from 2004 to 2008. In the setting, stock returns as proxy for capital market response, auditor quality(measured as the discretionary accruals) is endogenously determined. This study employs a structural equation model to take into account the endogenous variables under study. The analysis influences through the path analysis that ownership structure suppress the market response through audit quality and also the non-audit service have influence on the market response through audit quality. The results of this study contribute to the literature in the following ways. First, this provides direct evidence that there is a negative association between audit firms' client importance and the value relevance. Second, the findings that the negative association is attenuated for audit quality support the findings of prior studies which present that corporate governance provide higher credibility of financial reports.

• Journal of Distribution Science
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• v.13 no.9
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• pp.47-57
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• 2015

Purpose - The aim of this paper is to investigate the explanatory power of the Pecking-order theory (the cost of financing increases with asymmetric information) among Korean retail firms from the perspective of debt capacity. According to the Pecking-order theory, a firm's first preference is to use internal funds for its capital needs, its next preference is the issuance of debt, and its last preference is the issuance of equity; this is due to the information asymmetry problem between existing shareholders and investors. However, prior empirical studies, such as Lemmon and Zender (2010), argue that the entire sample test for the Pecking-order theory could be misleading due to the different levels of debt issuance capability of each of the individual firms; in fact, they confirm that the explanatory power of the Pecking-order theory improves after taking into account the differences in debt capacity of the U.S. firms they examined. This paper implements a case study approach among Korean retail firms to examine the relationship between debt capacity and the explanatory power of the Pecking-order theory in Korea. Research design, data, and methodology - This study uses the sample of public retail firms on the Korea Composite Stock Price Index (KOSPI) from the time period of 1990 to 2013. We gather related financial and accounting statements from the financial information firm WISEfn. Credit rating information is provided by the Korea Investor Service. We employ the models of Lemmon and Zender (2010) and Son and Kim (2013) to measure a firm's debt capacity. Their logit models use the rating dummy variable as a dependent variable and incorporate other firm characteristics as independent variables to estimate debt capacity. To test the Pecking-order theory, we adopt variants of the financing deficit model of Shyam-Sunder and Myers (1999). In the test of the Pecking-order theory, we consider all of the changes in total debt obligations, current debt obligations, and long-term debt obligations. Results - Our main contribution to the literature is our confirmation of the predicted relationship between debt capacity and the explanatory power of the Pecking-order theory among Korean retail firms. The coefficients on financing deficits become greater as a firm's debt capacity improves. This is consistent with the results of Lemmon and Zender (2010). The coefficients on the square of the financing deficits are also negative for the firms in the largest debt capacity group, which is also consistent with the predictions in prior literature. Conclusions - This study takes a case study approach by examining Korean retail firms. We confirm that the Pecking-order theory explains the capital structure of retail firms more appropriately, after taking into account the debt capacity of each firm. This result suggests the importance of debt capacity consideration in the testing of the Pecking-order theory. Our result also implies that there has been a potential underestimation of the explanatory power of the Pecking-order theory in existing studies.

• Management & Information Systems Review
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• v.36 no.1
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• pp.291-307
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• 2017

This study analyzes the effects of global diversification level on discretion accruals and firm value. In order to verify the hypothesis of this study, the sample of securities companies was selected from 2012 to 2015, and the final sample is 2,139 firm-year. The results of this paper are as follows : First, discretionary accruals increased as the diversification level increased. We conducted an additional analysis as to whether the increase in information asymmetry due to international diversification affects discretionary accruals. As a result, the increase of information asymmetry due to international diversification increased discretionary accruals. This analysis is consistent with EI Mehdi and Seboui(2001)'s study. Second, we analyze the impact of international diversification on corporate value. In previous studies, there was no consistent conclusion about the relationship between international diversification and firm value(Christophe and Pfeiffer, 2002; Denis and Vost, 2002; Bodnar and Wenintrop, 1997; Bodnar et al., 2003). Therefore, this study hypothesizes that the increase in discretionary accruals, which have been driven by international diversification, will have an impact on firm value. Aa a result of the analysis, we found that the increase in discretionary accruals due to diversification declines the firm value. This means that the increase in discretionary accruals due to diversification is utilized as and opportunistic means by taking individual gain of managers.

• Health Policy and Management
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• v.23 no.2
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• pp.152-161
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• 2013

Korea has a single National Health Insurance program and all citizens are covered under this program, accounting 97% of the population, approximately 50 million people. Claims submitted by Health care providers are reviewed by Health Insurance Review and Assessment (HIRA) for the reimbursement. HIRA database contains not only individual beneficiary's information, but also healthcare service information such as diagnosis, procedures, prescriptions and tests for them. HRA database has gained attention as importance source for research due to its rich healthcare information and the demand of HIRA database has increased. Due to its tremendous size, however, researchers have had problems in accessing the database to conduct research. To meet this demand, we conducted a study to develop the inpatient sample data from HIRA database for research. This study has two purposes: 1) to determine a needed sample size; 2) to test reliability and validity of the sample data. We determined an adequate sample size to ensure representativeness and generality with additional consideration for convenience of calculation. The minimum sample size was 729,904 for the generality, and 488,861 for representativeness. After considering the convenience of calculation, our final sample size was 13% of the population, which was about 7.7 million beneficiaries. Age (5 years interval) and gender were used as stratification variables for sampling. In order to examine whether this sample data appropriately reflect population, we tested the reliability and validity of the sample data. From the sample data, we computed average expenditure of total claims per inpatient for 2011, frequency of top 30 disease, estimation of the number of stroke patients from the sample data, and then compared them to those from the population. Results confirmed reliability and validity of the sample data.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.493-503
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• 2014

A hierarchical classification scheme, which can reduce the spectral ambiguity and also reflect crop cultivation patterns from past land-cover maps, is presented for the purpose of the early production of crop classification maps in large-scale crop areas. Specifically, the effects of mixed pixels are minimized not only by applying a hierarchical classification approach based on different spectral characteristics from crop growth cycles, but also by considering temporal contextual information derived from past crop cultivation patterns. The applicability of the presented classification scheme was evaluated by a case study of Iowa State in USA with time-series MODIS 250 m Normalized Difference Vegetation Index(NDVI) data sets and past Cropland Data Layers(CDLs). Corn and soybean, which are major crop types in the study area and also display spectral similarity, could be properly classified by applying different classification stages and accounting for past crop cultivation patterns. The classification result by the presented scheme showed increases of minimum 7.68%p and maximum 20.96%p in overall accuracy, compared with one based on purely spectral information. In addition, the combination of temporal contextual information during classification was less affected by the number of NDVI data sets and the best overall accuracy of 86.63% was achieved. Thus, it is expected that this classification scheme can be effectively used for the early production of large-area crop classification maps in major feed-grain importing countries.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.1-8
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• 2015

The data of fair value hierarchy is expected to contain different degree of measurement error, information asymmetry, and information risk by the level of hierarchy. Thus, this study examines how hierarchy of fair value discriminately influences on companies' cost of capital. Through regression analysis of corporations listed from 2011 to 2014, it turns out that the regression coefficient of level 1 and 2 of fair value variable vary their rank by cost of capital types, while level 3 contains the highest regression coefficient for every cost of capital variable. In addition, further study of how the relevance between cost of capital and the fair value hierarchy gets affected by market risk management level and audit quality finds no consistent results. However, by analyzing the effect of coincident interaction through the convergence of market risk management and audit quality, when audit quality and market risk management level are high, the effect of relieving cost of capital of Level 3 gets the highest. In conclusion, fair value hierarchy data seems to affect discriminately on cost of capital by involved information risk, and the information risk could decrease by the level of market risk management and audit quality.

• Journal of Industrial Convergence
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• v.18 no.1
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• pp.25-33
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• 2020

South Korea entered an aged society phase in 2017 with the elderly accounting for 14% or higher of the entire population. It is expected to enter a super-aged society phase in 2026. The mobility handicapped, including the disabled and the elderly, are expected to grow continuously, and the demand for transport service for the mobility handicapped will definitely increase further. Thus, there is thus a need for various research to increase the utilization rate of low-floor buses among the mobility handicapped. This study analyzed the locations of getting on and off transportation means, time of departure and arrival, purpose of use, and frequency of use by the day among the mobility handicapped by making use of the information about their use of special transport service run by the mobility support center for the mobility handicapped. The study then proposed a method of selecting locations for low-floor bus stops to reflect the distribution and need of getting on and off transportation means among the mobility handicapped with such spatial analysis techniques as geocoding, overlapping analysis, buffer analysis, and generate tessellations. Finally, the study selected 228 locations for low-floor bus stops in Cheonan and reported a need to add 35 low-floor bus stops after eliminating the ones where the locations overlapped the old ones.

• Management & Information Systems Review
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• v.32 no.4
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• pp.127-153
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• 2013

The trend of China's industry has been changed from manufacturing industry based on cheap labor market to service industries gradually as a whole. The investment of Korean corporations toward Chines service industry is gradually being increased. The importance of Chinese service industry related taxations such as business tax and value-added tax are growing. This study, therefore, examines the changes of investment environment and does the business tax and VAT of growing importance in China. From the point of view that the taxation on services is mainly related to the business tax or VAT, this study, also, examines the changes of present condition of investment and corresponding trends of the Korean corporations, in accordance with the domestic investment environment changes tied to the business tax and the VAT in China. With regard to the business tax and the VAT, this study looks into their features and tax requisition and also makes comparison between them and VAT of Korea. This study examines the problems and situations from the cases of separation, integration and trial integration of the business tax and VAT, and also does the development direction of the above two taxation and the corresponding strategy of Korea and her companies The purpose of this study is to provide information about the changing trends of investment environment and the business tax and VAT and to present corresponding plan for the corporations advancing into China.