The concept of HSA (Home Service Aggregator) is derived from performing the energy IT business efficiently as well as successfully launcing a new service based on BPL (Broadband over Power Line). The HSA business using a BPL can extend the field of energy industry and an give a chance to create a new demand by consumer-oriented services. This study focuses on the exact evaluation of HSA business using BPL, and reasonable trusty evaluation should be the first step to launch the HSA business. In this study, the categories of cost are comprised of equipment (mainly RSM and MGW) cost, instalation cost, and maintenance cost. AMR (Automatic Meter Reading), internet integration billing service, integration charging service, internet service, sorority service, and electricity safety are listed for benefit. In this study, the ROI of HSA business is 0.9594, which is less than 1. However, that value does not consider the electricity safety benefit which is classified as a social benefit. Therefore, the value can be above 1 if it includes social and private benefits.
Youn, Yeu Young;Park, Deok Hie;Lim, Young Hee;Cho, Hye Sung
Analytical Science and Technology
/
v.22
no.5
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pp.376-385
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2009
In our study, the accuracy for measurement of seventeen 2,3,7,8-substituted PCDDs/PCDFs in certified reference material (CRM) which is the sample of homogeneous sediment matrix taken from an area known to have significant chemical contamination, particularly PCBs (polychlorinated biphenyls), was evaluated. Though the methodology in this study followed the official method of unintentionally produced persistent organic pollutants (UPOPs) announced by the Ministry of Environment of the Republic of Korea in 2007, there were slight changes using additional purification step by activated carbon column because the interferences of sample were not sufficiently removed when only multi-silica column and alumina column have been used for purification. The |En| number proposed by the Korea Research Institute of Standards and Science was used for a valuation basis of the accuracy. The |En| numbers of seventeen 2,3,7,8-substituted PCDDs/PCDFs have been indicated as 1 and below, they were decided "Pass" in this test, when DB-5MS column and SP-2331 column were used together. Because 1,2,3,7,8-PeCDD and #169-HxCB were not separated on DB-5MS column, the ions of 1,2,3,7,8-PeCDD were selected at M/M+2 instead of M+2/M+4 suggested by EPA 1613. It is possible to distinguish them in HRGC/HRMS analysis.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.2
no.2
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pp.49-68
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2007
This paper develop self pre-checkup lists for the validity of business model as web business starters can utilize to open business. In particular, self pre-checkup lists invented by Dr. Bruce Merrifield, is reapplied and modified in appropriate to internet shopping mall business. This paper complete many literature reviews to identify appropriate factors of evaluation such as about the characters of internet business, business validity testing theory for internet business model, pros and cons of e-business and startup ventures, factor analysis of technology valuation, and pros and cons for internet shopping mall. This paper define six different factors; scale of sales, the growth rate of market, competitiveness, risk portfolio, industry upside down, and social conditions, as the factors of evaluating the business attractiveness. Meanwhile, it define characters of CEO, content's power, mutual inclusion, commerce, fulfillment, marketing power as the factors of business appropriateness. This paper also conducts several case studies; company I, D, G of applying the former model. This paper sort out internet business model in imaginations by utilizing self pre-checkup lists of business evaluation. Also, the outcomes of evaluation is expected to provide meaningful future business implications.
Kwang Bae Yoon;Sunryoung Kim;Seokwan Cheong;Jinhong Lee;Jae Hwa Tho;Seung Hyun Han
Korean Journal of Environmental Biology
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v.40
no.3
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pp.307-315
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2022
In terms of habitat conservation, it is essential to develop a habitat assessment system that can evaluate not only the suitability of the current habitat, but also the health and stability of the habitat. This study aimed to develop a methodology of habitat quality assessment for endangered species by analyzing various existing habitat assessment methods. The habitat quality assessment consisted of selecting targeted species, planning of assessment, selecting targeted sites, assessing performance, calculating grade, and expert verification. Target sites were selected separately from core and potential habitats using a species distribution model or habitat suitability index. Habitat assessment factors were classified into ecological characteristic, landscape characteristic, and species-habitat characteristic. Ecological characteristic consisted of thirteen factors related to health of tree, vegetation, and soil. Landscape characteristic consisted of five factors related to fragment and connectivity of habitat. Species-habitat characteristic consisted of factors for evaluating habitat suitability depending on target species. Since meanings are different depending on characteristics, habitat quality assessment of this study could be used by classifying results for each characteristic according to various assessment purposes, such as designation of alternative habitats, assessment of restoration project, and protected area valuation for endangered species. Forest habitat quality assessment is expected to play an important role in conservation acts of endangered species in the future through continuous supplementation of this system in regard to quantitative assessment criteria and weighting for each factor with an influence.
For economic impact analysis on a R&D project of high-yield groundwater development in Jeju conducted by KIGAM from 2004 to 2007, benefit/cost ratio(BCR), net present value(NPV), and internal rate of return(IRR) were calculated by contingent valuation method(CVM), production function analysis, domestic water market analysis and technology factor analysis. Measurable direct impact parameters among the major outputs of this R&D project consisted the estimation 4 high-yield and high mineral groundwater reserve in Jeju. Annual use of the reserve by piped water and bottled water was estimated as 12.23 million ton and its monetary value was calculated as 293.4 million dollar in 2006 year value applied of 5.5% discount rate. Economic impact of this R&D project in NPV of year 2006, with applying a discount rate of 5.5%, was identified and estimated as 13.66 million dollar in NPV, 4.05 points in BCR, and 22.74% in IRR, respectively. Additional early launch benefit was 5.58 million dollar. Even increased of the 1% discount rate, NPV of this R&D project was also positive as 12.18 million dollar and BCR was 3.71.
The advent of the Internet and related Web technologies has created an easily accessible link between a firm and its customers, and has provided opportunities to a firm to use information technology to support supplementary after-sale services associated with a product or service. It has been widely recognized that supplementary services are an important source of customer value and of competitive advantage as the characteristics of the product itself. Many of these supplementary services are information-based and need not be co-located with the product, so more and more companies are delivering these services electronically. Net-based customer service, which is defined as an Internet-based computerized information system that delivers services to a customer, therefore, is the core infrastructure for supplementary service provision. The importance of net-based customer service in delivering supplementary after-sale services associated with product has been well documented. The strategic advantages of well-implemented net-based customer service are enhanced customer loyalty and higher lock-in of customers, and a resulting reduction in competition and the consequent increase in profits. However, not all customers utilize such net-based customer service. The digital divide is the phenomenon in our society that captures the observation that not all customers have equal access to computers. Socioeconomic factors such as race, gender, and education level are strongly related to Internet accessibility and ability to use. This is due to the differences in the ability to bear the cost of a computer, and the differences in self-efficacy in the use of a technology, among other reasons. This concept, applied to e-commerce, has been called the "e-commerce divide." High Internet penetration is not eradicating the digital divide and e-commerce divide as one would hope. Besides, to accommodate personalized support, a customer must often provide personal information to the firm. This personal information includes not only name and address, but also preferences information and perhaps valuation information. However, many recent studies show that consumers may not be willing to share information about themselves due to concerns about privacy online. Due to the e-commerce divide, and due to privacy and security concerns of the customer for sharing personal information with firms, limited numbers of customers adopt net-based customer service. The limited level of customer adoption of net-based customer service affects the firm profits and the customers' welfare. We use a game-theoretic model in which we model the net-based customer service system as a mechanism to enhance customers' loyalty. We model a market entry scenario where a firm (the incumbent) uses the net-based customer service system in inducing loyalty in its customer base. The firm sells one product through the traditional retailing channels and at a price set for these channels. Another firm (the entrant) enters the market, and having observed the price of the incumbent firm (and after deducing the loyalty levels in the customer base), chooses its price. The profits of the firms and the surplus of the two customers segments (the segment that utilizes net-based customer service and the segment that does not) are analyzed in the Stackelberg leader-follower model of competition between the firms. We find that an increase in adoption of net-based customer service by the customer base is not always desirable for firms. With low effectiveness in enhancing customer loyalty, firms prefer a high level of customer adoption of net-based customer service, because an increase in adoption rate decreases competition and increases profits. A firm in an industry where net-based customer service is highly effective loyalty mechanism, on the other hand, prefers a low level of adoption by customers.
Rehabilitation of mining areas can reduce damage to ecosystems. However, the effects of rehabilitation on ecosystem services (ESs) and its contribution to local communities are not well known. Thus, the aims of this study were to clearly identify the ES beneficiaries affected by mining activities, to determine how the beneficiaries profit from surrounding areas in cooperation with local stakeholders, and to manage the rehabilitation areas for the ESs that the beneficiaries want. This study chose 18 ESs (4 provisioning, 7 regulating, 5 cultural, and 2 habitat services) based on The Economics of Ecosystems and Biodiversity. A semi-structured questionnaire survey using an 11-point Likert scale was conducted among 87 community residents to investigate social awareness and identify key ESs. The survey results from two local communities showed high awareness and demands mainly on cultural (mental and physical health, aesthetic appreciation, and recreation) and regulating services (local climate and air quality, and moderation of extreme events). These services were related to the daily lives of residents in local communities, provided positive benefits, and potentially improved the residents' future livelihoods. However, the average questionnaire scores were limited to 6-7 points, indicating that the benefits to local communities were meager. The residents' awareness of provisioning service was negative, even if it provided goods and profit opportunities. This indicated a disconnection between local communities and provisioning services due to forest rehabilitation that did not consider local communities that traditionally relied on specific provisioning services before the onset of mining activities. Future forest rehabilitation in abandoned mine areas must consider the welfare of local communities for sustainable use of rehabilitated forests and enhancing ESs. In this study, only a qualitative evaluation based on frequency analyses was conducted. The quantification and valuation of key ESs are warranted in the future to promote ESs from forest rehabilitation in abandoned mine areas. The study results would be useful for developing site-specific ES promotion strategies for reforesting mine areas.
This study has estimated Gyeongju National Park's natural environment and cultural relic value in the same way and then been performed to compare the size of the value. Representative method to measure environmental property is contingent valuation methods, CVM. The variables and estimated models adopted for the calculation were same and the respondents were asked by distinguishing between the amount which they would pay to preserve the natural environment and that which they were willing to pay to preserve the cultural relics. As the result, WTP(Willing to pay), the amount that they were willing to pay to preserve the natural environment of Gyeongju National Park was 17,838 won per person and that to preserve the cultural relics appeared to be 316,248 won per person. Based on this, it was estimated that the value of the natural environment with which Gyeongju National Park provided annual visitors was 47 billion won and that the annual value of the cultural relics was 845.7 billion. If the natural environment and the cultural relics value elements are united, it can be estimated that the natural environment and cultural relic value got at the time of people's first visit to Gyeongju National Park is 334,086 won and that the annual value is 893.4 billion won. In this study, the value of the cultural relics has been estimated 18 times higher than that of the natural environment. This reason was that visitors judged that a total of 66 cultural properties including 11 national treasures, 23 treasures, 13 historic places, one historic sites and scenic spot and 18 local cultural properties, etc. which were distributed in Gyeongju National Park were worth far more than the natural environment. Based on the result of this study, the operating management plan of Gyeongju National Park should include a differentiated operation strategy through consultation with relevant experts by taking into account characteristics of the physical components.
Journal of the Korean Institute of Landscape Architecture
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v.40
no.1
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pp.23-33
/
2012
In this study, how much users of Hannamkeumbuk Keumbuk Mountains are aware of Baekdaegan and its attached mountain chains, a traditional geographic system, according to Sangyungpyo and basic data like the degree of awareness and use-behaviors, etc. have been studied. In addition, the environmental value of Hannamkeumbuk Keumbuk Mountains separating the central and the southern part of Korea among attached mountain ranges, secondary mountain chains, which act as an ecosystem buffer in the Baekdudaegan Range, has been estimated at the current amount of currency. In the questions of the perception of the traditional classification standard of mountain chains and Baekdudaegan, more than 70% of respondents answered that they had heard of or known them but 66.8% werenot aware of Hannamkeumbuk Keumbuk Mountains. While the awareness for Baekdudaegan is high, the perception of its attached mountain chains was very poor. DBDC responder system and CVM, which is used widely for the value estimate method of environment goods, were used. As the result, an additional benefit got when a person visits Hannamkeumbuk Keumbuk mountains was estimated as 5,813 won. It could find out that this amount was very low compared with 51,984 won, average visit cost. It judged that the reason was that damage of environmental conditions, the monotony of the trails and progress of indiscriminate environmental destruction, etc. The results of this study will offer a new perspective on public relations activities and resource conservation of Baekdudaegan and its attached mountain chains and estimate perceptions and efficient services for visitors to HannamKeumbuk Keumbuk Mountains. This study will act as data for basic planning and management to increase the mountains' value and to preserve them. Further studies are needed to make a frame of work division and management with various organizations so that the management of Hannamkeumbuk-Keumbuk Mountains may be properly established and their value may been hanced.
This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.
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