• Journal of Fashion Business
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• v.14 no.4
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• pp.10-22
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• 2010

To survive competitive global market, textile and fashion business incorporated Supply Chain Management strategy to make product and information flows fast and correct. Especially textile and fashion industry involves many complicated channels from up stream, middle stream, to down stream for delivering their production. Evaluating SCM performance is very critical to make better business profit model. Representative Scor model and BSC method are well fitted into textile and fashion business because of distributional complexity, non-financial factors to be considered, and innovative product characteristics. But there was little study to compare these two methods for textile and fashion business. Therefore, the purpose of this study was to investigate the Scor model and BSC method based upon review of literatures. The results of this study were as follows: Scor model had some strengths which were availability to apply for various industries due to standardized process, operation process emphasized, various customizable factors to compose for the company, and premise on SCM strategic execution. BSC method had some strengths which were the balance including financial and non-financial factors, qualitative analysis, and considering the goal and vision to convey organically from top to bottom of organization. The main differences between them were different scope to deal with performance estimating index from qualitative to quantitative analysis, the scope of human resources to manage, and possibility of performance comparison among companies.

• Asia Marketing Journal
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• v.14 no.1
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• pp.1-24
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• 2012

Nowadays, customer satisfaction has been one of company's major objectives, and the index to measure and communicate customer satisfaction has been generally accepted among business practices. The major issues of CSI(customer satisfaction index) are three questions, as follows: (a)what level of customer satisfaction is tolerable, (b)whether customer satisfaction and company performance has positive causality, and (c)what to do to improve customer satisfaction. Among these, the second issue is recently attracting academic research in several perspectives. On this study, the second issue will be addressed. Many researchers including Anderson have regarded customer satisfaction as core competencies, such as brand equity, customer equity. They want to verify following causality "customer satisfaction → market performance(market share, sales growth rate) → financial performance(operating margin, profitability) → corporate value performance(stock price, credit ratings)" based on the process model of marketing performance. On the other hand, Insoo Jeon and Aeju Jeong(2009) verified sequential causality based on the process model by the domestic data. According to the rejection of several hypotheses, they suggested the balance model of marketing performance as an alternative. The objective of this study, based on the existing process model, is to examine the causal relationship between customer satisfaction and corporate value performance. Anderson and Mansi(2009) proved the relationship between ACSI(American Customer Satisfaction Index) and credit ratings using 2,574 samples from 1994 to 2004 on the assumption that credit rating could be an indicator of a corporate value performance. The similar study(Sangwoon Yoon, 2010) was processed in Korean data, but it didn't confirm the relationship between KCSI(Korean CSI) and credit ratings, unlike the results of Anderson and Mansi(2009). The summary of these studies is in the Table 1. Two studies analyzing the relationship between customer satisfaction and credit ratings weren't consistent results. So, in this study we are to test the conflicting results of the relationship between customer satisfaction and credit ratings based on the research model considering Korean credit ratings. To prove the hypothesis, we suggest the research model as follows. Two important features of this model are the inclusion of important variables in the existing Korean credit rating system and government support. To control their influences on credit ratings, we included three important variables of Korean credit rating system and government support, in case of financial institutions including banks. ROA, ER, TA, these three variables are chosen among various kinds of financial indicators since they are the most frequent variables in many previous studies. The results of the research model are relatively favorable : R², F-value and p-value is .631, 233.15 and .000 respectively. Thus, the explanatory power of the research model as a whole is good and the model is statistically significant. The research model has good explanatory power, the regression coefficients of the KCSI is .096 as positive(+) and t-value and p-value is 2.220 and .0135 respectively. As a results, we can say the hypothesis is supported. Meanwhile, all other explanatory variables including ROA, ER, log(TA), GS_DV are identified as significant and each variables has a positive(+) relationship with CRS. In particular, the t-value of log(TA) is 23.557 and log(TA) as an explanatory variables of the corporate credit ratings shows very high level of statistical significance. Considering interrelationship between financial indicators such as ROA, ER which include total asset in their formula, we can expect multicollinearity problem. But indicators like VIF and tolerance limits that shows whether multicollinearity exists or not, say that there is no statistically significant multicollinearity in all the explanatory variables. KCSI, the main subject of this study, is a statistically significant level even though the standardized regression coefficients and t-value of KCSI is .055 and 2.220 respectively and a relatively low level among explanatory variables. Considering that we chose other explanatory variables based on the level of explanatory power out of many indicators in the previous studies, KCSI is validated as one of the most significant explanatory variables for credit rating score. And this result can provide new insights on the determinants of credit ratings. However, KCSI has relatively lower impact than main financial indicators like log(TA), ER. Therefore, KCSI is one of the determinants of credit ratings, but don't have an exceedingly significant influence. In addition, this study found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size, and on service companies than manufacturers. The findings of this study is consistent with Anderson and Mansi(2009), but different from Sangwoon Yoon(2010). Although research model of this study is a bit different from Anderson and Mansi(2009), we can conclude that customer satisfaction has a significant influence on company's credit ratings either Korea or the United State. In addition, this paper found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size and on service companies than manufacturers. Until now there are a few of researches about the relationship between customer satisfaction and various business performance, some of which were supported, some weren't. The contribution of this study is that credit rating is applied as a corporate value performance in addition to stock price. It is somewhat important, because credit ratings determine the cost of debt. But so far it doesn't get attention of marketing researches. Based on this study, we can say that customer satisfaction is partially related to all indicators of corporate business performances. Practical meanings for customer satisfaction department are that it needs to actively invest in the customer satisfaction, because active investment also contributes to higher credit ratings and other business performances. A suggestion for credit evaluators is that they need to design new credit rating model which reflect qualitative customer satisfaction as well as existing variables like ROA, ER, TA.

• Journal of the East Asian Society of Dietary Life
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• v.17 no.5
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• pp.671-677
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• 2007

This study examined the relationship between chlorophyll(Chl) and ascorbic acid(ASA) as an index of freshness for vegetables, when the general consumers purchase several kinds of vegetables at the market. The leaves and fruits of several types of vegetables were divided into top, middle, and basal sections. Chl was determined by a spectrophotometer, and ASA was analyzed by high-performance liquid chromatography. For the vegetable sections, we found that Chl and ASA levels were highest in the top sections, followed by the middle, and were lowest in the basal portions. For the relationship between Chl and ASA in vegetables, there were seven classifications including high Chl(above 80mg/100g of fresh weight) and high ASA(above 80 mg/100 g of fresh weight) for mallow, and kail; the second group had high Chl and low ASA(below 80 mg), such as in spinach, burdock, and perilla leaves; the third group contained medium Chl($40{\sim}80mg$) and medium ASA($40{\sim}80mg$) levels, such as for gonddalbee, angelica, pumpkin leaf and coriander; the fourth group had medium Chl and low ASA levels, as in crown daisy and lettuce; the fifth group contained low Chl(below 40 mg) and high ASA, such as in hot peppers and parsley; the sixth group had low Chl and medium ASA levels, and included broccoli, pak choi, and sweet peppers; finally the seventh group contained low Chl and low ASA levels, as in dropwort, young radishes, shallots, cucumbers and swiss chard.

• The Journal of Information Systems
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• v.26 no.3
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• pp.63-90
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• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• Knowledge Management Research
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• v.22 no.4
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• pp.87-101
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• 2021

ESG Investment is emerging as a trend and common sense in the financial market. ESG Investment is an investment method that simultaneously pursue social sustainability and investment returns from a long-term perspective by reflecting non-financial factors such as environment, society and governance in addition to corporate financial performance in investment decisions. This study checked how the characteristics of ESG investment have been changed after Covid-19. Afterwards, it was confirmed that Covid-19 actually acted as a negative factor in the securities market by applying VAR model. At the same time, it was demonstrated that ESG indices of the US and Korea outperformed their benchmark in terms of return and risk during the pandemic regime. The result of this study hints that the importance of ESG investment will be unchanged after Covid-19. At the same time, it suggests that managers should avoid passive ESG management and engage in strategic ESG management based on knowledge management.

• Journal of Distribution Science
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• v.14 no.6
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• pp.107-118
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• 2016

Purpose - Over 90% of Domestic logistics industry is small enterprise and they are experiencing growth stagnation due to price-based competition structure rather than constructing logistics service of high added value. In order to get over this situation and pursue the development of logistics industry, strengthening its competitiveness, through inter-enterprise cooperative network build-up, would be a key alternative. Therefore, in this study, an index for measuring inter-enterprise cooperation level of Joint logistics business will be developed as a typical collaborative business model in logistics industry. Moreover, a strengthening competitiveness method suggests a developmental step and a key management index to mature in logistics industry. Research Design, Data, Methodology - This study is an index development research for measuring inter-enterprise cooperation level of logistics industry. Such a level was measured by performing a survey by targeting enterprises that participated in Joint logistics business. The targeting enterprises are typical cooperative models in logistics industry. Measurement items were developed which were based on the presented items in existing research. Question items were composed of selection type questions as answering Yes/No. They measures implementation status of corporate activity and detailed activity items measuring qualitative level. Total samples were based on 116 enterprise samples including 90 logistics enterprises and 26 shippers. In addition, by evaluating the importance for Joint logistics business recognition with personnel working level, the weight of measuring variable was extracted. This study has built an assessment tools (LPCI) on Joint logistics business cooperation level in a situation where there are no previous studies on joint logistics business, this study is meaningful for other studies. Results - As a result of analyzing LPCI presented in this study, the score of logistics enterprise was represented as 59.9 points based on full score of 100 points and that of shippers as 47.2 points and cooperation level among enterprises participated in Joint logistics business was revealed to be very low. In particular, as a result of measuring the importance between logistics enterprise and shippers, the difference by each measurement standard was represented among those enterprises. This difference is considered to be a key factor that cooperative operational conformity between logistics enterprises and shippers is represented to be low. Conclusions - As most joint logistics business, being promoted at present, is sharing facility and information with joint logistics business, it is hard to find such a joint logistics business in reality based on cooperative business model in main cooperation agents. Therefore, competitiveness of logistics industry could be strengthened by promoting joint logistics business based on their mutual cooperation among enterprises. In other words, it is to secure sustainable competitiveness of joint logistics business together with creation of new market by inter-enterprise cooperation based on integration of basic logistics business.

• Environmental and Resource Economics Review
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• v.19 no.2
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• pp.383-411
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• 2010

Climate change and related policies and regulations influence the performance of the firms in various ways. Climate change influences corporate competitiveness through physical impacts, GHG regulations, changes in asset values, demand shift, etc. Therefore, corporate competitiveness could be maintained by reducing vulnerability to climate change and adapting to new circumstances. Without effective responses to the challenges, the firms would have difficulties in maintaining their competitiveness in the market and the cost of national economy will significantly increase as well. Even though it seems fairly easy to understand the meaning of competitiveness, deriving the driving forces of and measuring changes in competitiveness are complicated and disputable processes. A common way to overcome it is to develop a 'competitiveness index'. The objective of this study is to derive the main factors influencing corporate competitiveness related to climate change and develop 'competitiveness index' reflecting those factors. The index will make contribution to enhance the response capacity of the firms to climate change and increase the effectiveness of climate change policies for the industry by providing a quantitative tool to measure the changes in corporate competitiveness related to climate change.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.4
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• pp.915-923
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• 2007

Recently we can see many cases that the CRM Systems are implemented and operated in Hospitals. The reason for such situation is the management environments in medical service market is changing rapidly one hand, and on the other hand the competitions among the Hospitals became more severe. In this paper we try to present the factors and weights as index for the measurement of Hospital CRM's System Performance. To achieve this goal, we derived the primary factors for the success of the CRM Systems based on the precedent researches, and futhermore carry out the verification of the rightness of those factors. For the verification of the rightness of the factors, we employ the Structured-Model-Analysis Method of AMOS. This enhance the meaning of the analysis result of the factors. And we use the AHP method to compare the importance grade of each success factors, because the comparison of importance level of each success factor is very crucial for the measurement of the Hospital CRM's system performance. As a result, we derived the primary factors and analyzed the weights in this paper, which might be used as the guiding Index for the measurement of the Hospital CRM' System Performance.

• Journal of Korea Port Economic Association
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• v.33 no.3
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• pp.91-104
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• 2017

This paper examines the export structure of Gwangyang Port and evaluates its comparative advantage from 2005 to 2016 using the Comparative Advantage by Countries (CAC) index. It is found that: (i) Gwangyang Port has a comparative advantage in HS 39 and HS 28, an unstable comparative advantage in HS 29 but a comparative disadvantage in HS 72; and (ii) 4 items have the common features of losing their comparative advantage. Constant market share analysis allows one to evaluate why the exports of one region may grow faster than world exports. This consists of the commodity composition effect, the scale effect, and the competitive effect. Constant market share analysis shows that the commodity composition effect influences exports negatively while the scale effect does exports positively. Shift-share analysis can help evaluate the change in a region's performance relative to the nation over a given period of time. The result indicates that HS 28 has not only favorable industrial mix effect but high competitive share effect, while HS 29 has unfavorable industrial mix effect as well as low competitive share effect. This paper also reveals that industrial mix effect of HS 39 is positive but its competitive share effect is negative, whereas the former is negative but the latter is positive in case of HS 29.

• International Commerce and Information Review
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• v.19 no.2
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• pp.3-24
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• 2017

The level of ICT in the country affects economic performance as a basic infrastructure that has a significant impact on the competitiveness of the country. With the proliferation of globalization, ICT-related economic activities such as electronic trade are becoming more active, and the importance of ICT in the country is increasing. This study sought to analyze the impact of ICT level on the economic performance of the nation by subdividing it into three dimensions: accessibility, usage, and utilization skill. In particular, we sought to find ways to effectively resolve the digital divide between developed and developing countries by analyzing the difference in economic impact of ICT level. Furthermore, we tried to verify whether the government regulation and firm's nature of competitive advantage in the international markets play a moderating role in the economic impacts of ICT in the country. As a result of panel analysis with data collected from ITU, WEF and World bank national ICT level has consistently significant influence on economic growth in terms of access and usage. In addition, it was confirmed that the competitive advantage of companies in developed countries and the government regulation in developing countries have a significant moderating effect on the relationship between ICT level and economic growth.