• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.1-19
• /
• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Economic Analysis
• /
• v.27 no.3
• /
• pp.61-96
• /
• 2021

This study is to structurally examine the regional income disparity in Korea. It measures the regional income inducement by household consumption expenditure per unit income, and the regional interdependency of income using 2005 and 2015 Regional Input-Output Tables of 16 provincial regions of Korea. The results are as follows. Firstly, the income inducement by consumption expenditure per unit income decreased overall, mainly due to the decrease in the income inducement of other regions than due to that of their region. Secondly, in many regions, the inter-relational income dependency per unit income decreased also, this too, mainly due to the decrease in the income transfer to other region. And, the income inducement effects of consumption expenditure per unit income of Seoul and Gyeonggi, which occupy a large portion of the Korean economy, were lower than that of other regions, but took the largest portion of income inducements generated by other regions as well as by themselves and absorbed the income transfers from other regions the most. The higher income inducement and income absorption in Seoul and Gyeonggi by consumption expenditure of other regions were mainly because of the high share in service of their consumption structure, the progress in tertiarization of their industrial structure, and the high wage portion. These results also mean that viewed from the regional interdependency of income, the income of Seoul and that of Gyeonggi are highly dependent on the income of other regions. Especially, Gyeonggi which leads the overseas exports of high-tech based manufactured products, has other external factors that contribute to their high income inducement, whereas, Seoul which shows high income absorption using its inter-relations with other domestic regions based on the services, has an income-generating structure that is sensitive to other regions' economic situation. Amid overall declines in regional income inducements and in income transfers, and continuing concentrations into Seoul and Gyeonggi regions, to alleviate the regional disparity, the regional industry policies should, rather than benchmarking the policies of the two concentrated regions, enhance their own inter-regional relationships by strengthening the comparative advantage of their regionally specialized industry.

• Korean Journal of Culture and Social Issue
• /
• v.11 no.2
• /
• pp.143-181
• /
• 2005

This article examines factors that influence health and quality of life. In addition to the symptomatology and physiological functioning, the influence of the psychological functioning and interpersonal relationship on the overall health and quality of life are also investigated. Using a case-study approach, a total of 70 patients suffering from allergy or asthma were interviewed using a semi-structured questionnaire developed by the present authors. It assessed the following six areas: Cause and onset of illness, psychological functioning, health management, trust, social support received and overall health and quality of life. Based on the transactional model (Bandura, 1997; Kim & Park, 2005), the results of the case studies have been integrated and divided into three aspects: (1) Cause and onset of illness that includes physiological and environment factors; (2) mediating influences that includes psychological functioning, health management, interpersonal relationship and social support received; and (3) outcome factor that includes symptomatology, health and quality of life. The psychological functioning includes self-efficacy (self-regulated efficacy, efficacy for enlisting social support, efficacy for managing the environment, and efficacy for overcoming difficulties), positive outlook, life goals, experience of stress, and proxy control. Interpersonal relationship includes trust of family members and the physician. Health management includes receiving proper health assessment, following the advice and prescription given by the physicians, control of the environment and maintaining a healthy lifestyle. The results indicate that physiological, psychological, relational and environment factors interact with each other and affect individual's overall health and quality of life. Self-efficacy, social support received from family members, trust of physicians, and the health care system are key factors promoting healthy lifestyle and quality of life. The results indicate the need for further interdisciplinary, indigenous and cultural psychological research.

• Journal of Global Scholars of Marketing Science
• /
• v.18 no.4
• /
• pp.119-155
• /
• 2008

Customer Relationship Management(CRM) has been a sustainable competitive edge of many companies. CRM analyzes customer data for designing and executing targeted marketing analysing customer behavior in order to make decisions relating to products and services including management information system. It is critical for companies to get and maintain profitable customers. How to manage relationships with customers effectively has become an important issue for both academicians and practitioners in recent years. However, the existing academic literature and the practical applications of customer relationship management(CRM) strategies have been focused on the technical process and organizational structure about the implementation of CRM. These limited focus on CRM lead to the result of numerous reports of failed implementations of various types of CRM projects. Many of these failures are also related to the absence of marketing approach. Identifying successful factors and outcomes focused on marketing concept before introducing a CRM project are a pre-implementation requirements. Many researchers have attempted to find the factors that contribute to the success of CRM. However, these research have some limitations in terms of marketing approach without explaining how the marketing based factors contribute to the CRM success. An understanding of how to manage relationship with crucial customers effectively based marketing approach has become an important topic for both academicians and practitioners. However, the existing papers did not provide a clear antecedent and outcomes factors focused on marketing approach. This paper attempt to validate whether or not such various marketing factors would impact on relational quality and CRM performance in terms of marketing oriented perceptivity. More specifically, marketing oriented factors involving market orientation, customer orientation, customer information orientation, and core customer orientation can influence relationship quality(satisfaction and trust) and CRM outcome(customer retention and customer share). Another major goals of this research are to identify the effect of relationship quality on CRM outcomes consisted of customer retention and share to show the relationship strength between two factors. Based on meta analysis for conventional studies, I can construct the following research model. An empirical study was undertaken to test the hypotheses with data from various companies. Multiple regression analysis and t-test were employed to test the hypotheses. The reliability and validity of our measurements were tested by using Cronbach's alpha coefficient and principal factor analysis respectively, and seven hypotheses were tested through performing correlation test and multiple regression analysis. The first key outcome is a theoretically and empirically sound CRM factors(marketing orientation, customer orientation, customer information orientation, and core customer orientation.) in the perceptive of marketing. The intensification of ${\beta}$coefficient among antecedents factors in terms of marketing was not same. In particular, The effects on customer trust of marketing based CRM antecedents were significantly confirmed excluding core customer orientation. It was notable that the direct effects of core customer orientation on customer trust were not exist. This means that customer trust which is firmly formed by long term tasks will not be directly linked to the core customer orientation. the enduring management concerned with this interactions is probably more important for the successful implementation of CRM. The second key result is that the implementation and operation of successful CRM process in terms of marketing approach have a strong positive association with both relationship quality(customer trust/customer satisfaction) and CRM performance(customer retention and customer possession). The final key fact that relationship quality has a strong positive effect on customer retention and customer share confirms that improvements in customer satisfaction and trust improve accessibility to customers, provide more consistent service and ensure value-for-money within the front office which result in growth of customer retention and customer share. Particularly, customer satisfaction and trust which is main components of relationship quality are found to be positively related to the customer retention and customer share. Interactive managements of these main variables play key roles in connecting the successful antecedent of CRM with final outcome involving customer retention and share. Based on research results, This paper suggest managerial implications concerned with constructions and executions of CRM focusing on the marketing perceptivity. I can conclude in general the CRM can be achieved by the recognition of antecedents and outcomes based on marketing concept. The implementation of marketing concept oriented CRM will be connected with finding out about customers' purchasing habits, opinions and preferences profiling individuals and groups to market more effectively and increase sales changing the way you operate to improve customer service and marketing. Benefiting from CRM is not just a question of investing the right software, but adapt CRM users to the concept of marketing including marketing orientation, customer orientation, and customer information orientation. No one deny that CRM is a process or methodology used to develop stronger relationships being composed of many technological components, but thinking about CRM in primarily technological terms is a big mistake. We can infer from this paper that the more useful way to think and implement about CRM is as a process that will help bring together lots of pieces of marketing concept about customers, marketing effectiveness, and market trends. Finally, a real situation we conducted our research may enable academics and practitioners to understand the antecedents and outcomes in the perceptive of marketing more clearly.