• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

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.

• Korean small business review
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• v.31 no.4
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• pp.67-93
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• 2009

The purpose of this paper is to explore the relations between financial constraints and dividend smoothing of innovative small and medium sized enterprises(SMEs) listed on Korea Securities Market and Kosdaq Market of Korea Exchange. The innovative SMEs is defined as the firms with high level of R&D intensity which is measured by (R&D investment/total sales) ratio, according to Chauvin and Hirschey (1993). The R&D investment plays an important role as the innovative driver that can increase the future growth opportunity and profitability of the firms. Therefore, the R&D investment have large, positive, and consistent influences on the market value of the firm. In this point of view, we expect that the innovative SMEs can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. And also, we expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Aivazian et al.(2006) exert that the financial unconstrained firms with the high accessibility to capital market can adjust dividend payment faster than the financial constrained firms. We collect the sample firms among the total SMEs listed on Korea Securities Market and Kosdaq Market of Korea Exchange during the periods from January 1999 to December 2007 from the KIS Value Library database. The total number of firm-year observations of the total sample firms throughout the entire period is 5,544, the number of firm-year observations of the dividend firms is 2,919, and the number of firm-year observations of the non-dividend firms is 2,625. About 53%(or 2,919) of these total 5,544 observations involve firms that make a dividend payment. The dividend firms are divided into two groups according to the R&D intensity, such as the innovative SMEs with larger than median of R&D intensity and the noninnovative SMEs with smaller than median of R&D intensity. The number of firm-year observations of the innovative SMEs is 1,506, and the number of firm-year observations of the noninnovative SMEs is 1,413. Furthermore, the innovative SMEs are divided into two groups according to level of financial constraints, such as the financial unconstrained firms and the financial constrained firms. The number of firm-year observations of the former is 894, and the number of firm-year observations of the latter is 612. Although all available firm-year observations of the dividend firms are collected, deletions are made in the case of financial industries such as banks, securities company, insurance company, and other financial services company, because their capital structure and business style are widely different from the general manufacturing firms. The stock repurchase was involved in dividend payment because Grullon and Michaely (2002) examined the substitution hypothesis between dividends and stock repurchases. However, our data structure is an unbalanced panel data since there is no requirement that the firm-year observations data are all available for each firms during the entire periods from January 1999 to December 2007 from the KIS Value Library database. We firstly estimate the classic Lintner(1956) dividend adjustment model, where the decision to smooth dividend or to adopt a residual dividend policy depends on financial constraints measured by market accessibility. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between current payout rato and target payout ratio each year. In the Lintner model, dependent variable is the current dividend per share(DPS_t), and independent variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t). We hypothesized that firms adjust partially the gap between the current dividend per share(DPS_t) and the target payout ratio(Ω) each year, when the past dividend per share(DPS_t-1) deviate from the target payout ratio(Ω). We secondly estimate the expansion model that extend the Lintner model by including the determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory. In the expansion model, dependent variable is the current dividend per share(DPS_t), explanatory variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t), and control variables are the current capital expenditure ratio(CEA_t), the current leverage ratio(LEV_t), the current operating return on assets(ROA_t), the current business risk(RISK_t), the current trading volume turnover ratio(TURN_t), and the current dividend premium(DPREM_t). In these control variables, CEA_t, LEV_t, and ROA_t are the determinants suggested by the residual dividend theory and the agency theory, ROA_t and RISK_t are the determinants suggested by the dividend signaling theory, TURN_t is the determinant suggested by the transactions cost theory, and DPREM_t is the determinant suggested by the catering theory. Furthermore, we thirdly estimate the Lintner model and the expansion model by using the panel data of the financial unconstrained firms and the financial constrained firms, that are divided into two groups according to level of financial constraints. We expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, because the former can finance more easily the investment funds through the market accessibility than the latter. We analyzed descriptive statistics such as mean, standard deviation, and median to delete the outliers from the panel data, conducted one way analysis of variance to check up the industry-specfic effects, and conducted difference test of firms characteristic variables between innovative SMEs and noninnovative SMEs as well as difference test of firms characteristic variables between financial unconstrained firms and financial constrained firms. We also conducted the correlation analysis and the variance inflation factors analysis to detect any multicollinearity among the independent variables. Both of the correlation coefficients and the variance inflation factors are roughly low to the extent that may be ignored the multicollinearity among the independent variables. Furthermore, we estimate both of the Lintner model and the expansion model using the panel regression analysis. We firstly test the time-specific effects and the firm-specific effects may be involved in our panel data through the Lagrange multiplier test that was proposed by Breusch and Pagan(1980), and secondly conduct Hausman test to prove that fixed effect model is fitter with our panel data than the random effect model. The main results of this study can be summarized as follows. The determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend policy of the innovative SMEs. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between the current payout ratio and the target payout ratio each year. In the core variables of Lintner model, the past dividend per share has more effects to dividend smoothing than the current earnings per share. These results suggest that the innovative SMEs maintain stable and long run dividend policy which sustains the past dividend per share level without corporate special reasons. The main results show that dividend adjustment speed of the innovative SMEs is faster than that of the noninnovative SMEs. This means that the innovative SMEs with high level of R&D intensity can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. The other main results show that dividend adjustment speed of the financial unconstrained SMEs is faster than that of the financial constrained SMEs. This means that the financial unconstrained firms with high accessibility to capital market can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Futhermore, the other additional results show that dividend adjustment speed of the innovative SMEs classified by the Small and Medium Business Administration is faster than that of the unclassified SMEs. They are linked with various financial policies and services such as credit guaranteed service, policy fund for SMEs, venture investment fund, insurance program, and so on. In conclusion, the past dividend per share and the current earnings per share suggested by the Lintner model explain mainly dividend adjustment speed of the innovative SMEs, and also the financial constraints explain partially. Therefore, if managers can properly understand of the relations between financial constraints and dividend smoothing of innovative SMEs, they can maintain stable and long run dividend policy of the innovative SMEs through dividend smoothing. These are encouraging results for Korea government, that is, the Small and Medium Business Administration as it has implemented many policies to commit to the innovative SMEs. This paper may have a few limitations because it may be only early study about the relations between financial constraints and dividend smoothing of the innovative SMEs. Specifically, this paper may not adequately capture all of the subtle features of the innovative SMEs and the financial unconstrained SMEs. Therefore, we think that it is necessary to expand sample firms and control variables, and use more elaborate analysis methods in the future studies.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.3 no.2
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• pp.65-88
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• 2008

To achieve the age of 30,000 dollars GNP, The business with speed will hold a more crucial point than the business with scale, and the mass consumption market will be transformed and changed into the niche market. Moreover, it will not be easy for the company without the peculiar and creative technology to survive in the severe competition. Under these circumstances, The innovative company which knows how to use this new paradigm will select the better position in the changing market. Innovation type SMEs are contributing in maintaining the international competitiveness of domestic economy by serving high-tech and the promotion of employment. Also, Innovation type SMEs have the most important economic leverage in our domestic economy. It's a source of the growth in domestic economy. Therefore, A lot of countries have been trying to support innovation type SMEs (with a small capital and high-tech). And many countries also try to protect and promote the innovation type SMEs. Especially the Korean government is also promoting innovation type SMEs in many ways, because the future of innovation type SMEs are not bright. This study explored the three innovative SEMs and studied 1) entrepreneur characteristics, 2) the industry environment, 3) competitive strategies, and 4) resources and capabilities of organization, which have been considered as the success factors for entrepreneurial firms. This study also holds that the characteristics of entrepreneurs is one of the most important factor to impact the success of innovative SMEs. Most of entrepreneurs have started their business with high education career and field experiences and have high intentions in developing new/high techonologies, challenging spirits, and clear vision and goals. The innovative SMEs with small kinds of products and services, narrow market, and small resources are more sensitively impacted by the environment especially. But the SMEs which entered into market early could have the comparative excellencies in their market to survive and grow in the future. They also have competitive advantages in the market using differentiation strategies by technology innovation. Technology innovation and differention strategies are one of the success factors in SMEs, They entered into the niche market using this weapons. The capabilities of changing organization to their changing environment, the open orgarnization culture, the continuous employment education, and the building the organic organization are also success factors of innovative SMEs. The SMEs with the simple organization structure can make fast decisions and operate with the autonomous and flexible ways. These only three cases will not shown successful factors of over 12,000 Innovation type SMEs in Korea and this study of Innovation type SMEs is insufficient from all aspects. But this study have many implications for the future research and the entrepreneurs ready for their business.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.97-115
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• 2008

Introduction The e-government is concerned with using Internet and Web technologies to exchange information and services with citizens, businesses and other related organizations, and it centers on three functions, namely informational, interactive, and transactional [UN, 2001]. Many developed countries like the U.S. have been actively involved in e-government projects, since they enable both more effective public services for citizens and more efficient internal operations. Korea is among these leading countries that are planning to leverage computer and communication technologies to provide for integration of work processes and information as well as convenient access to information and services. For this reason, evaluating e-government projects is becoming a crucial issue for both researchers and policy-makers. However, most research to date has primarily focused on a model of success of an e-government system designed for citizens, overlooking internal systems specifically created for employees working in a public organization. This paper is intended to propose a model to measure the success of a Web-based information system designed for use by internal users at Chungwadae, the executive branch of Korea's central government. The paper is also aimed at applying the model to the assessment of the present system being used at Chungwadae in comparison with the preceding system. Evaluating an e-Government System The most widely cited model of information systems success today is that of DeLone and McLean[1992, 2003, 2004]. The original model states that the success of an information system can be measured using six dimensions, including system quality, information quality, use, user satisfaction, individual impact, and organizational impact. Although the ultimate success of an information system may be reflected in the impact that the system has upon individuals as well as an organization, aspects of using the system such as system use and user satisfaction can play an important role in determining the system success, because the system would be a sheer failure if users don't like and use the system. As a response to criticisms given by numerous researchers, the authors adapted their model to fit the emerging Web-based environment. The revised model[DeLone and McLean, 2003] they offered included an additional quality dimension, namely service quality, and combined individual and organizational impacts into net benefits which can also influence user satisfaction. The e-government system success model can be built around this updated model. Our model incorporates information quality, system quality, and service quality as in the DeLone and McLean model. However, the 'system use' dimension has been replaced by perceived usefulness, as suggested by Seddon[1998]. In addition, because the e-government systems that this paper focuses on are internal public systems used in government agencies, the 'net benefits' dimension has been replaced by perceived work efficiency. Based on the proposed model, a total of nine hypotheses have been formulated which we tested using an empirical analysis. Methods A questionnaire form has been created with items that are designed to examine the relationships among the variables in the model. The questionnaire has been handed over, in person, to 65 members of Chungwadae staff who are now actively using the E-Support System, the present information system created to support internal work at Chungwadae. We made arrangements to meet with each individual who agreed to participate in our survey, and helped to fill out the survey form with explanations. Of the 65 copies that were delivered, only 33 were returned, and 30 responses of these have been adopted for our analysis, since three were not valid. The extremely small sample size was due to the limited number of staff members who had adequate experience required of this study. Results We gathered data from the questionnaire survey and analyzed them using a regression analysis to test the hypotheses. As shown in the table below, the results indicated that all three dimensions of an information system’s quality are positively related to user satisfaction. However, information quality and system quality were found to be positively related to perceived usefulness, while service quality was not. In addition, perceived usefulness is not positively related to user satisfaction, implying that a user may find a system useful, but may not be satisfied with it. Finally, user satisfaction and perceived usefulness both are positively related to perceived work efficiency. This suggests that workers' positive experience with the system is important to guarantee favorable work efficiency. Conclusions We conclude that the proposed model proved useful in measuring the success of an internal information system used by a government agency. To demonstrate the applicability and usefulness of the model in the paper, we applied the model to the assessment of the present internal system used at Chungwadae in comparison with the preceding system. The results showed that the present system outperforms the preceding one in a statistically significant way. Future research will have to focus on applying the model to Korea's governmental agencies other than Chungwadae and examine whether it proves applicable in different types of governmental organizations.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.211-226
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• 2023

As we transition into the post-COVID era, economic activities that were stagnant are regaining momentum. In particular, there is a growing trend of technology entrepreneurship driven by the opportunities of digital transformation in the Fourth Industrial Revolution. However, entrepreneurship education content is struggling to keep up with the rapid pace of technological change. This study aims to emphasize the importance of entrepreneurship mentoring as a crucial component of entrepreneurship education content that requires adaptation and advancement due to the increasing demand for technology entrepreneurship. This study redefines startup mentoring, which is differentiated from general mentoring, at the present time when the demand for startups, which increases with the declining employment rate, increases, and the development of quality startup education contents and securing professional startup mentors are required. According to the start-up stage, it is divided into preliminary entrepreneurs and early entrepreneurs, and the effect of entrepreneurship knowledge and self-efficacy among start-up mentoring functions on entrepreneurial will and mentoring satisfaction is improved by empirically researching the effects of start-up mentoring functions in the case of initial entrepreneurs as a moderating effect. To confirm the importance of entrepreneurship mentoring effect for. To this end, among the mentoring functions, entrepreneurship knowledge and self-efficacy were set as independent variables, and entrepreneurial will and mentoring satisfaction were set as dependent variables. The research model was designed and hypotheses were established. In addition, empirical analysis was conducted by conducting a questionnaire survey on trainees who received entrepreneurship mentoring education at ICCE Startup School and Opus Startup School. To summarize the results of the empirical analysis, first, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on entrepreneurial will. Second, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on mentoring satisfaction. Third, it was analyzed that entrepreneurship had no significant moderating effect on entrepreneurial knowledge and entrepreneurial will. Fourth, it was analyzed that entrepreneurship had no significant moderating effect on mentoring satisfaction. Fifth, it was found that entrepreneurship had a significant moderating effect between self-efficacy and will to start a business. As a result of the research analysis, the first implication is that the mentoring function in start-up education is analyzed to produce meaningful results for both the initial entrepreneurs and the prospective entrepreneurs in the will to start a business and satisfaction. . Second, it was analyzed that there was no significant relationship between whether a business was started and the mentoring function and effect. However, it was analyzed that the will to start a business through improvement of self-efficacy through mentoring was significantly related to whether or not to start a business. turned out to be helpful. Many start-up education programs currently conducted in Korea educate both early-stage entrepreneurs and prospective entrepreneurs at the same time for reasons such as convenience. However, through the results of this study, even in small-scale entrepreneurship mentoring, it is suggested that customized mentoring through detailed classification such as whether the mentee has started a business can be a method for successful entrepreneurship and high satisfaction of the mentee.