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Development and Validation of the Social Entrepreneurship Measurement Tools: From an Organizational-Level Behavioral Perspective (사회적기업가정신 척도 개발 및 타당화 연구: 조직차원의 행동적 관점에서)

  • Cho, Han Jun
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.3
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    • pp.97-113
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    • 2023
  • In order to generalize the social entrepreneurship model with cooperation orientation and increase the possibility of using the model, this study developed a measurement tool and tested it with 389 executives of social enterprises. For the development of the measurement tool, preliminary measurement items were formed through review of previous studies, and a questionnaire was tentatively composed of 40 measurement items in five areas through an expert panel review of the measurement items. A total of 389 questionnaires were collected by conducting a questionnaire survey targeting Korean social enterprise managers, and exploratory and confirmatory factor analysis were conducted using 375 questionnaires that could be analyzed. Five factors for 24 items were derived through exploratory factor analysis and reliability analysis. Through a series of analysis processes including primary and secondary confirmatory factor analysis, the model fit of the newly constructed social entrepreneurship research model was confirmed, and the validity and reliability of the measurement tools were verified. As a result of this study, the model fit of the social entrepreneurship model(social value orientation; innovativeness; pro-activeness; risk-taking; cooperation orientation) is verified, thereby improving the theoretical explanatory power of social entrepreneurship research and at the same time providing the basis and basis for theoretical expansion of follow-up research. The study proved the possibility of generalizing the social entrepreneurship model with added cooperation orientation, and at the same time, the measurement tool used in this study was widely used as a tool to measure social entrepreneurship theoretically and practically. In addition, it was confirmed that the cooperation orientation is manifested in corporate decision-making and activity behaviors for resource mobilization and capacity building, opportunity and performance creation, social capital and network reinforcement, and governance establishment of social enterprises.

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The Pattern Analysis of Financial Distress for Non-audited Firms using Data Mining (데이터마이닝 기법을 활용한 비외감기업의 부실화 유형 분석)

  • Lee, Su Hyun;Park, Jung Min;Lee, Hyoung Yong
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.111-131
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    • 2015
  • There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

Strategy for Store Management Using SOM Based on RFM (RFM 기반 SOM을 이용한 매장관리 전략 도출)

  • Jeong, Yoon Jeong;Choi, Il Young;Kim, Jae Kyeong;Choi, Ju Choel
    • Journal of Intelligence and Information Systems
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    • v.21 no.2
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    • pp.93-112
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    • 2015
  • Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

A Study on the Improvement of Flexible Working Hours (탄력적 근로시간제 개선에 대한 연구)

  • Kwon, Yong-man
    • Journal of Venture Innovation
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    • v.5 no.3
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    • pp.57-70
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    • 2022
  • In modern industrial capitalism, the relationship between the provision of work and the receipt of wages has become an important principle governing society. According to the labor contract, the wages provided by entrusting the right to dispose of one's labor to the employer are directly compensated, and human life should be guaranteed and reproduced with proper rest. The establishment of labor relations under free contracts represents a problem in protecting workers, and accordingly, the maximum of working hours is set as a minimum right for workers, and the standard for minimum rest is set and assigned. The reduction of working hours is very important in terms of the quality of life of workers, but it is also an important issue in efficient corporate activities. As of 2020, Korea has 1,908 hours of annual working hours, the third lowest among OECD 37 countries in the happiness index surveyed by the Sustainable Development Solution Network(SDSN), an agency under the United Nations. Accordingly, the necessity of reducing working hours has been recognized, and the maximum working hours per week has been limited to 52 hours since 2018. In this situation, various working hours are legally excluded as a way to maintain the company's value-added creation and meet the diverse needs of workers, and Korea's Labor Standards Act restricts flexible working hours within three months, flexible working hours exceeding three months, selective working hours, and extended working hours. However, in the discussion on the application of the revised flexible working hours system in 2021 and the expansion of the settlement unit period recently discussed, there is a problem with the flexible working hours system, which needs to be improved. Therefore, this paper aims to examine the problems of the flexible working hours system and improvement measures. The flexible working hours system is a system that does not violate working hours even if the legal working hours are exceeded on a specific day or week according to a predetermined standard, and does not have to pay additional wages for excessive overtime work. It is mainly useful as a form of shift work in manufacturing, sales service, continuous business or electricity, gas, water, and transportation for long-term operations. It is also used as a way to shorten working hours, such as expanding holidays through short working days. However, if the settlement unit period is expanded, it is disadvantageous to workers as the additional wages that workers can receive will not be received. Therefore, First, in order to expand the settlement unit period currently under discussion, additional wages should be paid for the period expanded from the current standard. Second, it is necessary to improve the application of the flexible working hours system to individual workers to have sufficient consultation with individual workers in a written agreement with the worker representative, Third, clarify the allowable time for extended work during the settlement unit period, and Fourth, limit the daily working hours or apply to continuous rest. In addition, since the written agreement of the worker representative is an important issue in the application of the flexible working hours system, it is necessary to secure the representation of the worker representative.

A study on the developmental plan of Alarm Monitoring Service (기계경비의 발전적 대응방안에 관한 연구)

  • Chung, Tae-Hwang;So, Seung-Young
    • Korean Security Journal
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    • no.22
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    • pp.145-168
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    • 2010
  • Since Alarm Monitoring Service was introduced in Korea in 1981, the market has been increasing and is expected to increase continually. Some factors such as the increase of social security need and the change of safety consciousness, increase of persons who live alone could be affected positively on Alarm Monitoring Service industry. As Alarm Monitoring Service come into wide use, the understanding of electronic security service is spread and consumer's demand is difficult, so consideration about new developmental plan is need to respond to the change actively. Electronic security system is consist of various kinds of element, so every element could do their role equally. Alarm Monitoring Service should satisfy consumer's various needs because it is not necessary commodity, also electronic security device could be easily operated and it's appearance has to have a good design. To solve the false alarm problem, detection sensor's improvement should be considered preferentially and development of new type of sensor that operate dissimilarly to replace former sensor is needed. On the other hand, to settle the matter that occurred by response time, security company could explain the limit on Alarm Monitoring System to consumer honestly and ask for an understanding. If consumer could be joined into security activity by security agent's explanation, better security service would be provided with mutual confidence. To save response time the consideration on the introduction of GIS(Global Information System) is needed rather than GPS(Global Positioning System). Although training program for security agents is important, several benefits for security agents should be considered together. The development of new business model is required for preparation against market stagnation and the development of new commodity to secure consumer for housing service rather than commercial facility service. for the purpose of those, new commodity related to home-network system and video surveillance system could be considered, also new added service with network between security company and consumer for a basis is to be considered.

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Establishing a marketing strategy model for academic-industrial cooperation between companies and universities (기업과 대학간의 산학협력마케팅 전략모델 구축에 관한 연구)

  • Yun, Jeong-Keun
    • Journal of Distribution Science
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    • v.12 no.4
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    • pp.65-72
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    • 2014
  • Purpose - Because of the emphasis on the necessity of academic-industrial cooperation between companies and universities, there are various ongoing academic-industrial cooperation programs led by the government. As government actively supports such cooperation as policy,and universities vitalize new technology development, academic-industrial cooperation between companies and universities is being recognized as an important growth engine for companies the competitiveness of academic-industrial cooperation is also attracting more interest. The government has vitalized human resource fostering, practical R&D, and technology transfer to companies since 2012 by executing a "leading university fostering project for academic-industrial cooperation." Based on an organic interlink among universities, industry, and research institutes, the government also created and is promoting several models of such cooperation between companies and universities to support shared growth of industry and local universities. The purpose of academic-industrial cooperation is growth and benefit fromtechnology development, technical cooperation, and technology transfer between companies and universities. Research design, data, and methodology - As more academic-industrial cooperation efforts are ledby companies due to the limitation in technology-focused commercialization cooperation, the academic-industrial cooperation system became fragmented and it is losing the potential for future advancement. Specifically, as differences between universities grow, academic-industrial cooperation between companies and universities based on new technology from universities is finding difficulty advancing,while systematic support from companies to enhance the performance of businesses created by academic-industrial cooperation is also insufficient. Accordingly, this study established a growth model for the advancement of academic-industrial cooperation between companies and universities and suggested a plan to strengthen the competitiveness and promote the future advancementof academic-industrial cooperation between companies and universities by analyzing the current situation of such cooperation and diagnosing its issues. Results - This study explored the concept and current status of academic-industrial cooperation relationships and analyzed related issues. For such cooperative organizations to be competitive, the employment environment of professional human resources for academic-industrial cooperation should be improved and measures to secure professional resources should be taken as early as possible. Though the academic-industrial cooperation now is being led by government, there is a limitation based on business models, which require creation of profit; however, an academic-industrial cooperation model still cannot stand alone without the support of government. This study also pointed out that a having only a plan to build competitiveness of companies and universities for academic-industrial cooperation is not sufficient. Conclusions - In order to increase the competitiveness of academic-industrial cooperation, a detailed growth-sharing model for academic-industrial cooperation should be developed, and there should be more joint development processes for the advancement of such cooperation in which the need for technology development can be verified in advance. In addition, beyond focusing on technology-focused academic-industrial cooperation, a network between companies and universities searching for ideas for academic-industrial cooperation in the fields of human and social aspects should be created. A new academic-industrial model linking current cooperation between companies and universities to the local area should be built based on such academic-industrial cooperation in human and social fields.

A Study on the Current Status and Future Prospection of the Electronic Payment Infrastructure -Focusing on the e-L/C and SWIFT TSU- (전자결제 인프라 현황과 향후 전망 -전자신용장과 SWIFT TSU를 중심으로-)

  • Kim, Tae-Hwan
    • International Commerce and Information Review
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    • v.14 no.3
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    • pp.585-610
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    • 2012
  • There have been various attempt to offer commercial service of electronic payment. Actually, however, there has been few electronic payment model that are being used commercial service. Among them, it is estimated that only TSU(Trade Service Utility) of SWIFT will be succeed in providing commercial service possibility. In Korea e-L/C Distribution & Management System was constructed and become the first e-L/C service on a global basis via e-Trade Facilitation 3 Years Project and then started offering the world first e-L/C service. Some scholars have insisted the opinion that SWIFT L/C means e-L/C, but such opinion may be wrong because SWIFT L/C means the L/C advised by SWIFT(Society for Worldwid Interbank Financial Telecommunication) under the condition that a series of procedure from the issuance of L/C to the advice is done by SWIFT system. Because perfect e-L/C should be organically connected by SWIFT network and also, the e-L/C business between overseas banks and their customers should be organically linked with each other. The purpose of this paper is contribute to the commercialization of e-L/C distribution system by studying the current status of infrastructure concerned with domestic and overseas electronic payment and future e-payment infrastructure, seeking to be introduced internationally by doing things.

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Application of Machine Learning to Predict Weight Loss in Overweight, and Obese Patients on Korean Medicine Weight Management Program (한의 체중 조절 프로그램에 참여한 과체중, 비만 환자에서의 머신러닝 기법을 적용한 체중 감량 예측 연구)

  • Kim, Eunjoo;Park, Young-Bae;Choi, Kahye;Lim, Young-Woo;Ok, Ji-Myung;Noh, Eun-Young;Song, Tae Min;Kang, Jihoon;Lee, Hyangsook;Kim, Seo-Young
    • The Journal of Korean Medicine
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    • v.41 no.2
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    • pp.58-79
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    • 2020
  • Objectives: The purpose of this study is to predict the weight loss by applying machine learning using real-world clinical data from overweight and obese adults on weight loss program in 4 Korean Medicine obesity clinics. Methods: From January, 2017 to May, 2019, we collected data from overweight and obese adults (BMI≥23 kg/m2) who registered for a 3-month Gamitaeeumjowi-tang prescription program. Predictive analysis was conducted at the time of three prescriptions, and the expected reduced rate and reduced weight at the next order of prescription were predicted as binary classification (classification benchmark: highest quartile, median, lowest quartile). For the median, further analysis was conducted after using the variable selection method. The data set for each analysis was 25,988 in the first, 6,304 in the second, and 833 in the third. 5-fold cross validation was used to prevent overfitting. Results: Prediction accuracy was increased from 1st to 2nd and 3rd analysis. After selecting the variables based on the median, artificial neural network showed the highest accuracy in 1st (54.69%), 2nd (73.52%), and 3rd (81.88%) prediction analysis based on reduced rate. The prediction performance was additionally confirmed through AUC, Random Forest showed the highest in 1st (0.640), 2nd (0.816), and 3rd (0.939) prediction analysis based on reduced weight. Conclusions: The prediction of weight loss by applying machine learning showed that the accuracy was improved by using the initial weight loss information. There is a possibility that it can be used to screen patients who need intensive intervention when expected weight loss is low.

Keyword-based networked knowledge map expressing content relevance between knowledge (지식 간 내용적 연관성을 표현하는 키워드 기반 네트워크형 지식지도 개발)

  • Yoo, Keedong
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.119-134
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    • 2018
  • A knowledge map as the taxonomy used in a knowledge repository should be structured to support and supplement knowledge activities of users who sequentially inquire and select knowledge for problem solving. The conventional knowledge map with a hierarchical structure has the advantage of systematically sorting out types and status of the knowledge to be managed, however it is not only irrelevant to knowledge user's process of cognition and utilization, but also incapable of supporting user's activity of querying and extracting knowledge. This study suggests a methodology for constructing a networked knowledge map that can support and reinforce the referential navigation, searching and selecting related and chained knowledge in term of contents, between knowledge. Regarding a keyword as the semantic information between knowledge, this research's networked knowledge map can be constructed by aggregating each set of knowledge links in an automated manner. Since a keyword has the meaning of representing contents of a document, documents with common keywords have a similarity in content, and therefore the keyword-based document networks plays the role of a map expressing interactions between related knowledge. In order to examine the feasibility of the proposed methodology, 50 research papers were randomly selected, and an exemplified networked knowledge map between them with content relevance was implemented using common keywords.

Effect of Supply Chain Risk Management Factors on Risk Management Strategy and Corporate Performance (공급사슬관리 리스크 요인이 위험관리전략과 기업성과에 미치는 영향)

  • Lee, Choong-Bae;Kim, Hyun-Chung
    • Journal of Korea Port Economic Association
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    • v.36 no.3
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    • pp.55-74
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    • 2020
  • With globalization and the development of information and communication technology, the supply chain is becoming more widespread and complex, which increases the occurrence and damage caused by supply chain risks. Supply chain risk management has a great impact on corporate performance through the analysis of risk factors and proactive and strategic approaches. This study aims to analyze the effects of supply chain risk factors on risk management strategies and corporate performance empirically. In the research model for empirical analysis, supply chain risk factors were classified into supply, demand, operation, network, and external environment, while the risk management strategies were divided into active and passive strategies, as well as financial and operational performance for corporate performance. The data obtained via the questionnaire were analyzed for the path of the structural equation model. As a result of the analysis, companies are actively pursuing risk management for internal risk factors, rather than external factors, in terms of internal and external risk factors, and it was found that these strategies have a significant effect on corporate performance. Therefore, in the future, companies should conduct risk management strategies more proactively and preemptively through a thorough analysis of various risk factors affecting business operations.