• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.133-150
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• 2022

The purpose of this study was to develop a female entrepreneurial competency model. For the purpose, two Focus Group Interviews (FGI) were conducted with seven outstanding female entrepreneurs, and three expert reviews were conducted. In addition, in order to verify the validity of the provisional female entrepreneur competency model derived from the FGI and competency modeling expert review, the female entrepreneur competency model was finally confirmed through a survey of 442 female entrepreneurs. The results were as follows. First, a female entrepreneur competency model consisting of 6 competency groups and 25 competencies of entrepreneurship, emotion, business management, relationship management, strategic management, and multitasking, and 75 behavioral indicators describing each competency was developed. Second, sensibility and multitasking are competencies that reflect the characteristics of female entrepreneurs. In particular, 'social sense', which is the ability to be considerate of others in the emotional competency group and the ability to respond well to subtle nuances, and the multitasking competency group's unique strengths are women's ability to perform various tasks at the same time. The 'work-family control ability' of a female entrepreneur who maintains a balance between 'multi-tasking' and work and family is a representative competency of only female entrepreneurs. Third, the developed female entrepreneurship competency model is meaningful in that it not only increases female entrepreneurial competency so that prospective female entrepreneurs can successfully run a business through entrepreneurship education, but it also makes it easy for existing female entrepreneurs to reflect and improve their competencies. If we provide appropriate training programs to female entrepreneurs based on their competency, it will be possible to effectively enhance the entrepreneurial competency, which is the key to strengthening the competitiveness of female entrepreneurs. The female entrepreneur competency model developed through this study can provide a basis for future research on competency diagnosis and education needs analysis.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.23-35
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• 2024

This study analyzed the correlation between each of the 12 influencing factors in FAR 16.04 and the decision-making process for construction contract types, using data from a total of 2,406 DoD Construction Acquisitions spanning from 2008 to 2022. The study considered 12 independent variables, grouped into 4 Characteristics with 3 factors each. Meanwhile, all other contract types were categorized into two types: Firm-Fixed-Price (FFP) and Cost-Reimbursement Contract (CRC), which served as the dependent variables. The findings revealed that FFP contracts significantly dominated in terms of acquisition volume. In line with prevailing beliefs, logistic data analysis and Analytical Hierarchy Process (AHP) analysis of Relative Weights from Experts' Survey demonstrated that independent variables like Uncertainty of the Scope of Work and Complexity found out to be increasing the likelihood of selecting CRC. The number of contractors in the market does indeed influence the possibilities of contract decision-making between CRC and FFP. Meanwhile, the p-values of the top 3 influencing factors on CRC from the AHP analysis-namely, Appropriateness of CAS, Project Urgency, and Cost Analysis-exceeded 0.05 in the binominal regression results, rendering it inconclusive whether they significantly influenced the construction contract type decision, particularly with respect to payment methods. This outcome partly results from the fact that a majority of respondents possessed specific experiences related to the USFK relocation project. Furthermore, influencing factors in construction projects behave differently than common beliefs suggest. As a result, it is imperative to consider the 12 influencing factors categorized into 4 Characteristics areas before establishing acquisition strategies for targeted construction projects.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.109-117
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• 2013

The Global Framework on Climate Services (GFCS) will guide the development of climate services that link science-based climate information and predictions with climate-risk management and adaptation to climate change. GFCS structure is made up of 5 pillars; Observations/Monitoring (OBS), Research/ Modeling/ Prediction (RES), Climate Services Information System (CSIS) and User Interface Platform (UIP) which are all supplemented with Capacity Development (CD). Corresponding to each GFCS pillar, the Commission for Agricultural Meteorology (CAgM) has been proposing "Global Initiatives in AgroMeteorology" (GIAM) in order to facilitate GFCS implementation scheme from the perspective of AgroMeteorology - Global AgroMeteorological Outlook System (GAMOS) for OBS, Global AgroMeteorological Pilot Projects (GAMPP) for RES, Global Federation of AgroMeteorological Society (GFAMS) for UIP/RES, WAMIS next phase for CSIS/UIP, and Global Centers of Research and Excellence in AgroMeteorology (GCREAM) for CD, through which next generation experts will be brought up as virtuous cycle for human resource procurements. The World AgroMeteorological Information Service (WAMIS) is a dedicated web server in which agrometeorological bulletins and advisories from members are placed. CAgM is about to extend its service into a Grid portal to share computer resources, information and human resources with user communities as a part of GFCS. To facilitate ICT resources sharing, a specialized or dedicated Data Center or Production Center (DCPC) of WMO Information System for WAMIS is under implementation by Korea Meteorological Administration. CAgM will provide land surface information to support LDAS (Land Data Assimilation System) of next generation Earth System as an information provider. The International Society for Agricultural Meteorology (INSAM) is an Internet market place for agrometeorologists. In an effort to strengthen INSAM as UIP for research community in AgroMeteorology, it was proposed by CAgM to establish Global Federation of AgroMeteorological Society (GFAMS). CAgM will try to encourage the next generation agrometeorological experts through Global Center of Excellence in Research and Education in AgroMeteorology (GCREAM) including graduate programmes under the framework of GENRI as a governing hub of Global Initiatives in AgroMeteorology (GIAM of CAgM). It would be coordinated under the framework of GENRI as a governing hub for all global initiatives such as GFAMS, GAMPP, GAPON including WAMIS II, primarily targeting on GFCS implementations.

• Journal of agricultural medicine and community health
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• v.37 no.1
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• pp.12-22
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• 2012

Objectives: This study aimed to compare the nutritional risk, health status and depression levels of young-old (65-74 years) and old-old (75-84 years) women on low-income. Methods: A total of 624 elderly women, each over 65 years of age, participated in this study under the auspices of a community social center. Data were collected from June to August 2011 by means of personal interviews which employed questionnaires. The research tools used in this study were the nutritional risk measuring Mini Nutritional Assesment (MNA) by Kim (2000), perceived health status developed by Lawton et al. (1982), Elderly Depression Criterion developed by Sheikh & Yesavage (1985). The collected data were analyzed using the SPSS WIN 12.0 Program. Results: Nutritional risk, perceived health status and depression levels showed a significant difference between young-old and old-old. There was a positive correlation between nutritional risk and depression and a negative correlation between nutritional risk and perceived health status. A 38.2% variance in depression levels of young-old and a 29.7% variance in depression levels of old-old were explained by perceived health status, nutritional risk and the number of people living together. Conclusion: The findings demonstrate variances in depression levels among low - income women differing in age. As a result, the outcomes of this study ought to be employed in the development of future programs aimed at promoting the health of elderly women.

• KDI Journal of Economic Policy
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• v.14 no.1
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• pp.3-36
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• 1992

"Corporate control by owners" characterizes the current structure of ownership, control and management of big business groups in Korea. It has become an ever more serious obstacle for the Korean economy to end its distinctive "personal capitalism" and to transform the current system into people's capitalism. The current issue, the deconcentration of ownership, through the course of heated debates should be treated from an integrated perspective. That is, the debate should center on the concentration of economic power and it effects on national economy, instead of sticking to the issue of ownership-control issue per se. This paper, by referring to the historical experiences and development paths which advanced countries have already traveled, analyzes the respective aspects of the concentration issue in a rather descriptive and taxonomist manner - market concentration, business diversification, ownership concentration, integrated management of conglomerates, i.e., managing in groups' unit, and the roles of financial institutions. The government policies against the concentration of economic power have so far focused on the size of big business groups and their diversification activities. The two major policy measures are restrictions on cross-ownership and excess capital investment by big business groups, and controls on their credit deals. This paper strongly suggests that the government should change its current priorities in targeting its policies against concentration. The government should reduce the regulations on size and diversification, and focus its policies on substantial dispersion of corporate ownership. The efficacy of government intervention in the management and control of business enterprises seems quite dubious and even anachronistic given the extent of maturity of Korean firms. Therefore, it should be noted that the current regulation-oriented stance taken by the government against the management style of big business groups should be suppressed, as it has assumed some a priori and typical pattern in advance in directing big business groups, such as independent and specialized management in respective firms' unit. This paper, also, raises the need for introducing new regulations on inter-sectoral diversifications between finance, industry and the press.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.60 no.3
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• pp.318-332
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• 2015

The maize production in South-eastern Asian countries showed a continuous increase with increasing poultry-livestock from the beginning of the 1990s to early 2010. Also the need for a new variety development of each contries was increased rapidly in the same period. Single-Cross hybrid varieties have been developed and supplied from 2001 instead of multi-cross maize varieties since 1992 in Indonesia. In Cambodia, CP group is mainly manufacturing feeds with most of the forage maize from farmers who are growing its seeds from the company. Cambodian main cultivars are varieties of multinational corporations such as DK8868 from Monsanto, NK6326, NK7328 from Syngenta and CP333 from CP group including local business company. Vietnam is the main maze importing country in South-Eastern Asia which had imported 13 times scale of amount compared to exports in average from 1990 to 2011. Vietnamese government has developed a range of varieties for improving their efficiency in production, such as the LVN-10 with political investments. Their production has been reached to 80% of the total. According to the 2012 MIFAFF (Ministry for Food, Agriculture, Forestry and Fisheries) data in Korea, domestic edible maize cultivation area was approximately 15,000ha. It showed 74,399 tons of production, 3.8% of food self-sufficiency in maize and around 0.9% of grain self-sufficiency rate. The consumption of grain is mostly rely on imports in Korea. To overcome the limit of the domestic seed market and increase maize self-sufficiency, the need to develop maze varieties for world-class is increasing at present through analyzing the market trend and prospect of the seed industry in South-eastern Asia.

• Journal of Nutrition and Health
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• v.41 no.7
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• pp.634-664
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• 2008

This study investigated the effects of the nutrition education on body weight, visceral fat and diet quality in the postmenopausal women. The subjects (n = 101) were randomly divided into two groups: Nutrition education + Exercise (NEE) group (n = 51) and Exercise only (EO) group (n = 50). Nutrition education was consisted of counseling in portion control, food selection for low carbohydrate, high fiber food items and for the improvement in micronutrient intakes and diet quality. After 6 months, the reduction in the body weight and visceral fat area was significantly greater in the NEE than in the EO group. The NEE subjects were further divided into two groups according to the amount of visceral fat area reduction; high visceral fat area loss (HVL) group with a visceral fat area reduction 2.35% or greater and low visceral fat area loss (LVL) group with a reduction less than 2.35%. In the HVL group, the reduction in body weight, BMI, percent body fat, waist to hip ratio and visceral fat area was significantly greater than that in the LVL group. We observed a significant increase in the serum HDL-cholesterol level and a decrease in systolic blood pressure, fasting blood sucrose, total and LDL-cholesterol levels in the HVL group compared to the LVL group. The energyadjusted protein, fiber, calcium, vitamin $B_6$, vitamin C, vitamin E intakes were significantly increased in the HVL compared to LVL group. The index of nutritional quality (INQ) and mean adequacy ratio (MAR) were also increased in the HVL group compared to the LVL group. These results show that our nutrition education program was an effective intervention measure for the reduction of body weight and visceral fat, blood pressure, glucose and lipid levels in the blood and also for the improvement of nutrient intake and diet quality in postmenopausal women who are overweight.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.769-781
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• 2007

Factor analysis has been usually employed in reducing quantity of data and summarizing information on a system or phenomenon. In this analysis methodology, variables are grouped into several factors by consideration of statistic characteristics, and the results are used for dropping variables which have lower weight than others. In this study, factor analysis was applied for extracting primary factors influencing multi-dam system operation in the Han River basin, where there are two multi-purpose dams such as Soyanggang Dam and Chungju Dam, and water has been supplied by integrating two dams in water use season. In order to fulfill factor analysis, first the variables related to two dams operation were gathered and divided into five groups (Soyanggang Dam: inflow, hydropower product, storage management, storage, and operation results of the past; Chungju Dam: inflow, hydropower product, water demand, storage, and operation results of the past). And then, considering statistic properties, in the gathered variables, some variables were chosen and grouped into five factors; hydrological condition, dam operation of the past, dam operation at normal season, water demand, and downstream dam operation. In order to check the appropriateness and applicability of factors, a multiple regression equation was newly constructed using factors as description variables, and those factors were compared with terms of objective function used in operation water resources optimally in a river basin. Reviewing the results through two check processes, it was revealed that the suggested approach provided satisfactory results. And, it was expected for extracted primary factors to be useful for making dam operation schedule considering the future situation and previous results.