A study on the prediction of korean NPL market return (한국 NPL시장 수익률 예측에 관한 연구)
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- 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.
The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.
Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.
In MIS field, the researches on payment services are focused on adoption factors of payment service using behavior theories such as TRA(Theory of Reasoned Action), TAM(Technology Acceptance Model), and TPB (Theory of Planned Behavior). The previous researches presented various adoption factors according to types of payment service, nations, culture and so on even though adoption factors of identical payment service were presented differently by researchers. The payment service industry relatively has strong path dependency to the existing payment methods so that the research results on the identical payment service are different due to payment culture of nation. This paper aims to suggest a successful adoption factor of noble payment service regardless of nation's culture and characteristics of payment and prove it. In previous researches, common adoption factors of payment service are convenience, ease of use, security, convenience, speed etc. But real cases prove the fact that adoption factors that the previous researches present are not always critical to success to penetrate a market. For example, PayByPhone, NFC based parking payment service, successfully has penetrated to early market and grown. In contrast, Google Wallet service failed to be adopted to users despite NFC based payment method which provides convenience, security, ease of use. As shown in upper case, there remains an unexplained aspect. Therefore, the present research question emerged from the question: "What is the more essential and fundamental factor that should takes precedence over factors such as provides convenience, security, ease of use for successful penetration to market". With these cases, this paper analyzes four cases predicted on the following hypothesis and demonstrates it. "To successfully penetrate a market and sustainably grow, new payment service should find non-customer of the existing payment service and provide noble payment method so that they can use payment method". We give plausible explanations for the hypothesis using multiple case studies. Diners club, Danal, PayPal, Square were selected as a typical and successful cases in each category of payment service. The discussion on cases is primarily non-customer analysis that noble payment service targets on to find the most crucial factor in the early market, we does not attempt to consider factors for business growth. We clarified three-tier non-customer of the payment method that new payment service targets on and elaborated how new payment service satisfy them. In case of credit card, this payment service target first tier of non-customer who can't pay for because they don't have any cash temporarily but they have regular income. So credit card provides an opportunity which they can do economic activities by delaying the date of payment. In a result of wireless phone payment's case study, this service targets on second of non-customer who can't use online payment because they concern about security or have to take a complex process and learn how to use online payment method. Therefore, wireless phone payment provides very convenient payment method. Especially, it made group of young pay for a little money without a credit card. Case study result of PayPal, online payment service, shows that it targets on second tier of non-customer who reject to use online payment service because of concern about sensitive information leaks such as passwords and credit card details. Accordingly, PayPal service allows users to pay online without a provision of sensitive information. Final Square case result, Mobile POS -based payment service, also shows that it targets on second tier of non-customer who can't individually transact offline because of cash's shortness. Hence, Square provides dongle which function as POS by putting dongle in earphone terminal. As a result, four cases made non-customer their customer so that they could penetrate early market and had been extended their market share. Consequently, all cases supported the hypothesis and it is highly probable according to 'analytic generation' that case study methodology suggests. We present for judging the quality of research designs the following. Construct validity, internal validity, external validity, reliability are common to all social science methods, these have been summarized in numerous textbooks(Yin, 2014). In case study methodology, these also have served as a framework for assessing a large group of case studies (Gibbert, Ruigrok & Wicki, 2008). Construct validity is to identify correct operational measures for the concepts being studied. To satisfy construct validity, we use multiple sources of evidence such as the academic journals, magazine and articles etc. Internal validity is to seek to establish a causal relationship, whereby certain conditions are believed to lead to other conditions, as distinguished from spurious relationships. To satisfy internal validity, we do explanation building through four cases analysis. External validity is to define the domain to which a study's findings can be generalized. To satisfy this, replication logic in multiple case studies is used. Reliability is to demonstrate that the operations of a study -such as the data collection procedures- can be repeated, with the same results. To satisfy this, we use case study protocol. In Korea, the competition among stakeholders over mobile payment industry is intensifying. Not only main three Telecom Companies but also Smartphone companies and service provider like KakaoTalk announced that they would enter into mobile payment industry. Mobile payment industry is getting competitive. But it doesn't still have momentum effect notwithstanding positive presumptions that will grow very fast. Mobile payment services are categorized into various technology based payment service such as IC mobile card and Application payment service of cloud based, NFC, sound wave, BLE(Bluetooth Low Energy), Biometric recognition technology etc. Especially, mobile payment service is discontinuous innovations that users should change their behavior and noble infrastructure should be installed. These require users to learn how to use it and cause infra-installation cost to shopkeepers. Additionally, payment industry has the strong path dependency. In spite of these obstacles, mobile payment service which should provide dramatically improved value as a products and service of discontinuous innovations is focusing on convenience and security, convenience and so on. We suggest the following to success mobile payment service. First, non-customers of the existing payment service need to be identified. Second, needs of them should be taken. Then, noble payment service provides non-customer who can't pay by the previous payment method to payment method. In conclusion, mobile payment service can create new market and will result in extension of payment market.
Franchise businesses in South Korea have contributed to economic growth and job creation, and its growth potential remains very high. However, despite such virtues, domestic franchise businesses face many problems such as the instability of franchisor's business structure and weak financial conditions. To solve these problems, the government enacted legislation and strengthened franchise related laws. However, the strengthening of laws regulating franchisors had many side effects that interrupted the development of the franchise business. For example, legal regulations regarding franchisors have had the effect of suppressing the franchisor's leadership activities (e.g. activities such as the ability to advocate the franchisor's policies and strategies to the franchisees, in order to facilitate change and innovation). One of the main goals of the franchise business is to build cooperation between the franchisor and the franchisee for their combined success. However, franchisees can refuse to follow the franchisor's strategies because of the current state of franchise-related law and government policy. The purpose of this study to explore the effects of franchisor's leadership style on franchisee's commitment in a franchise system. We classified leadership styles according to the path-goal theory (House & Mitchell, 1974), and it was hypothesized and tested that the four leadership styles proposed by the path-goal theory (i.e. directive, supportive, participative and achievement-oriented leadership) have different effects on franchisee's commitment. Another purpose of this study to explore the how the level of franchisee's self-efficacy influences both the franchisor's leadership style and franchisee's commitment in a franchise system. Results of the present study are expected to provide important theoretical and practical implications as to the role of franchisor's leadership style, as restricted by government regulations and the franchisee's self-efficacy, which could be needed to improve the quality of the long-term relationship between the franchisor and franchisee. Quoted by Northouse(2007), one problem regarding the investigation of leadership is that there are almost as many different definitions of leadership as there are people who have tried to define it. But despite the multitude of ways in which leadership has been conceptualized, the following components can be identified as central to the phenomenon: (a) leadership is a process, (b) leadership involves influence, (c) leadership occurs in a group context, and (d) leadership involves goal attainment. Based on these components, in this study leadership is defined as a process whereby franchisor's influences a group of franchisee' to achieve a common goal. Focusing on this definition, the path-goal theory is about how leaders motivate subordinates to accomplish designated goals. Drawing heavily from research on what motivates employees, path-goal theory first appeared in the leadership literature in the early 1970s in the works of Evans (1970), House (1971), House and Dessler (1974), and House and Mitchell (1974). The stated goal of this leadership theory is to enhance employee performance and employee satisfaction by focusing on employee motivation. In brief, path-goal theory is designed to explain how leaders can help subordinates along the path to their goals by selecting specific behaviors that are best suited to subordinates' needs and to the situation in which subordinates are working (Northouse, 2007). House & Mitchell(1974) predicted that although many different leadership behaviors could have been selected to be a part of path-goal theory, this approach has so far examined directive, supportive, participative, and achievement-oriented leadership behaviors. And they suggested that leaders may exhibit any or all of these four styles with various subordinates and in different situations. However, due to restrictive government regulations, franchisors are not in a position to change their leadership style to suit their circumstances. In addition, quoted by Northouse(2007), ssubordinate characteristics determine how a leader's behavior is interpreted by subordinates in a given work context. Many researchers have focused on subordinates' needs for affiliation, preferences for structure, desires for control, and self-perceived level of task ability. In this study, we have focused on the self-perceived level of task ability, namely, the franchisee's self-efficacy. According to Bandura (1977), self-efficacy is chiefly defined as the personal attitude of one's ability to accomplish concrete tasks. Therefore, it is not an indicator of one's actual abilities, but an opinion of the extent of how one can use that ability. Thus, the judgment of maintain franchisee's commitment depends on the situation (e.g., government regulation and policy and leadership style of franchisor) and how it affects one's ability to mobilize resources to deal with the task, so even if people possess the same ability, there may be differences in self-efficacy. Figure 1 illustrates the model investigated in this study. In this model, it was hypothesized that leadership styles would affect the franchisee's commitment, and self-efficacy would moderate the relationship between leadership style and franchisee's commitment. Theoretically, quoted by Northouse(2007), the path-goal approach suggests that leaders need to choose a leadership style that best fits the needs of subordinates and the work they are doing. According to House & Mitchell (1974), the theory predicts that a directive style of leadership is best in situations in which subordinates are dogmatic and authoritarian, the task demands are ambiguous, and the organizational rule and procedures are unclear. In these situations, franchisor's directive leadership complements the work by providing guidance and psychological structure for franchisees. For work that is structured, unsatisfying, or frustrating, path-goal theory suggests that leaders should use a supportive style. Franchisor's Supportive leadership offers a sense of human touch for franchisees engaged in mundane, mechanized activity. Franchisor's participative leadership is considered best when a task is ambiguous because participation gives greater clarity to how certain paths lead to certain goals; it helps subordinates learn what actions leads to what outcome. Furthermore, House & Mitchell(1974) predicts that achievement-oriented leadership is most effective in settings in which subordinates are required to perform ambiguous tasks. Marsh and O'Neill (1984) tested the idea that organizational members' anger and decline in performance is caused by deficiencies in their level of effort and found that self-efficacy promotes accomplishment, decreases stress and negative consequences like depression and emotional instability. Based on the extant empirical findings and theoretical reasoning, we posit positive and strong relationships between the franchisor's leadership styles and the franchisee's commitment. Furthermore, the level of franchisee's self-efficacy was thought to maintain their commitment. The questionnaires sent to participants consisted of the following measures; leadership style was assessed using a 20 item 7-point likert scale developed by Indvik (1985), self-efficacy was assessed using a 24 item 6-point likert scale developed by Bandura (1977), and commitment was assessed using a 6 item 5-point likert scale developed by Morgan & Hunt (1994). Questionnaires were distributed to Korean optical franchisees in Seoul. It took about 20 days to complete the data collection. A total number of 140 questionnaires were returned and complete data were available from 137 respondents. Results of multiple regression analyses testing the relationships between the each of the four styles of leadership shown by the franchisor as independent variables and franchisee's commitment as the dependent variable showed that the relationship between supportive leadership style and commitment (