• Journal of Digital Convergence
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• v.15 no.10
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• pp.339-348
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• 2017

This study was conducted to examine the differences of anger expression style and cognitive characteristics among adolescents depending on the level of game addiction and game engagement. 420 high school boys were administered the Game Addiction/Engagement Scale, Behavioral Anger Response Questionnaire to measure anger expression style, and Irrational Belief Scale to measure cognitive characteristics. The results of correlation analyses showed that addiction had positive correlations with all the irrational belief factors and behavior anger factors except for assertion and avoidance. Engagement was positively correlated with all the variables except for direct anger-out, avoidance, and self-downing. Participants were divided into three groups depending on the level of addiction and engagement. Addiction high risk-low engagement group showed the lowest scores on support-seeking and the highest scores on diffusion and self-downing. Addiction high risk-high engagement group showed the highest scores on direct anger-out. Based on these findings, it was suggested that counselling strategies for adolescents at high risk of game addiction need to be varied depending on the level of game engagement.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.5
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• pp.79-92
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• 2019

When asked about the success factors of successful entrepreneurs and celebrities, he says he was lucky. The remarkable fact is that the attitude about luck is different. However, despite the fact that the belief that we believe is lucky is actually a dominant concept, there has not been much scientific verification of luck. In this study, we saw good luck not being determined randomly by the external environment, but by being able to control luck through the internal attributes of individuals. This study is significant that we have empirically elucidated what kind of efforts have gained good luck, whereas previous research has largely ended in vague logic where luck ends up with an internal locus of control among internal entrepreneurial qualities and efforts can make a successful entrepreneur. We introduced the concept of good luck belief to avoid confirmation bias, which is, to interpret my experience in a direction that matches what I want to believe, and used a good luck belief questionnaire in previous studies and tried to verify that those who have a good belief can increase entrepreneurial opportunity capability through planned happenstance skills. The reason for choosing the entrepreneurial opportunity capacity as a dependent variable was based on the conventional research, that is, the process of recognizing and exploiting the entrepreneurial opportunity is an important part of the entrepreneurship research For empirical research, we conducted a questionnaire survey of a total of 332 people, and the results of the analysis turned out that the belief of good luck has all the positive impacts of planned happenstance skills' sub-factors: curiosity, patience, flexibility, optimism and risk tolerance. Second, we have shown that only the perseverance, optimism, and risk tolerance of planned happenstance skills' sub-factors have a positive impact on this opportunity capability. Thirdly, it was possible to judge that the sub-factors of planned happenstance skills, patience, optimism, and risk tolerance, had a meditating effect between belief in luck and entrepreneurial opportunity capability. This study is highly significant in logically elucidating that people in charge of business incubation and education can get the specific direction when planning a training program for successful entrepreneur to further enhance the entrepreneurial opportunity ability, which is an important ability for the entrepreneur's success.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.184-191
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• 2020

Using 850 disclosures of individual executive compensation from 2014 to 2017, this study examines the impact of female auditors on the sensitivity of executive compensation-performance relation. The major findings as follow: First, Female auditors have positive effects on the sensitivity of executive compensation to performance, implying that when auditors are appointed to be females who are more ethical, of high moral development, risk averse and conservative as well, they play an efficient monitoring role in aligning executive compensation to performance. Second, the monitoring effects of female auditors on the sensitivity of executive compensation to performance are significant when they are full time employed, suggesting that gender-based differences are more likely to be realized on the condition that they are in position to commit to their jobs for their owns. The results overall support that female auditors exercise efficient monitoring roles in aligning executive compensation to performance in Korean listed firms. The research contribute to complement the study of gender effects on corporate decision making, which have been focused on gender diversity of the board, by providing empirical evidence of the impact of female auditors on the sensitivity of executive compensation-performance relation.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.472-482
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• 2012

There are many investors in the stock market, and more and more people get interested in the stock investment. In order to avoid risks and make profit in the stock investment, we have to determine several aspects using various information. That is, we have to select profitable stocks and determine appropriate buying/selling prices and holding period. This paper proposes a data mining tool for the investors' decision support. The data mining tool makes stock investors apply machine learning techniques and generate stock price prediction model. Also it helps determine buying/selling prices and holding period. It supports individual investor's own decision making using past data. Using the proposed tool, users can manage stock data, generate their own stock price prediction models, and establish trading policy via investment simulation. Users can select technical indicators which they think affect future stock price. Then they can generate stock price prediction models using the indicators and test the models. They also perform investment simulation using proper models to find appropriate trading policy consisting of buying/selling prices and holding period. Using the proposed data mining tool, stock investors can expect more profit with the help of stock price prediction model and trading policy validated on past data, instead of with an emotional decision.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Asia Marketing Journal
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• v.12 no.4
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• pp.55-78
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• 2011

Recently strategic alliance between business firms has become prevalent to overcome increasing competitive threats and to supplement resource limitation of individual firms. As one of allianced sales promotion activities, a new type of discount program, so called "Alliance Card Discount", is introduced with the partnership of credit cards and loyalty cards. The program mainly pursues short-term sales growth by larger discount scheme while spends less through cost share among alliance partners. Thus this program can be regarded as cost efficient discount promotion. But because there is no solid evidence that it can really deliver profitable sales growth, an empirical study for its effects on sales and profit should be conducted. This study has two basic research questions concerning the effects of allianced discount program ; 1)the possibility of sales increase 2) the profitability of the discount driven sales. In F&B industry, sales increase mainly comes from increased guest count. Especially in family restaurants, to increase the number of guests we need to enlarge the size of visitor group (number of visitors for one group) because customers visit by group in a special occasion. And because they pay the bill by group(table), the increase of sales per table is a key measure for sales improvement. The past researches for price & discount sensitivity and reference discount rate explain that price sensitive consumers have narrow reference discount zone and make rational purchase decision. Differently from all time discount scheme of regular sales promotions, the alliance card discount program only provides the right to get discount like discount coupon. And because it is usually once a month opportunity given by the past month usage level, customers tend to perceive alliance card discount as a rare chance to get. So that we can expect customers try to maximize the discount effect when they use the limited discount opportunity. Considering group visiting practice and low visit frequency of family restaurants, the way to maximize discount effect should be the increase the size of visit group. And their sensitivity to discount and rational consumption behavior defer the additional spending for ordering high price menu, even though they get considerable amount of savings from the discount. From the analysis of sales data paid by alliance discount cards for four months, we found the below. 1) The relation between discount rate and number of guest per table is positive : 25% discount results one additional guest 2) The relation between discount rate and the spending per guest is negative. 3) However, total profit amount per table is increased when discount rate is increased. 4) Reward point accumulation & redemption did not show any significant relationship with the increase of number of guests. These results suggest that the allianced discount program substantially contributes to sales increase and profit improvement by increasing the number of guests per table. Though the spending per guest is decreased by discount rate increase, the total amount of profit per table is improved. It seems the incremental profit by increased guest count offsets the profit decrease. Additional intriguing finding is the point reward system does not have any significant impact on the increase of number of guest, even if the point accumulation & redemption of loyalty program are usually regarded as another saving offers by customers. In sum, because it is proved that allianced discount program with credit cards and loyalty cards is effective to both sales drive and profit increase, the alliance card program could be recommended as strategically buyable program.