• 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.

• Radiation Oncology Journal
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• v.22 no.4
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• pp.237-246
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• 2004

Purpose: To investigate the effects of radiation dose-escalation on the treatment outcome, complications and the other prognostic variables for glioblastoma patients treated with 3D-conformal radiotherapy (3D-CRT). Materials and Methods: Between Jan 1997 and July 2002, a total of 75 patients with histologically proven diagnosis of glioblastoma were analyzed. The patients who had a Karnofsky Performance Score (KPS) of 60 or higher, and received at least 50 Gy of radiation to the tumor bed were eligible. All the patients were divided into two arms; Arm 1, the high-dose group was enrolled prospectively, and Arm 2, the low-dose group served as a retrospective control. Arm 1 patients received $63\~70$ Gy (Median 66 Gy, fraction size $1.8\~2$ Gy) with 3D-conformal radiotherapy, and Arm 2 received 59.4 Gy or less (Median 59.4 Gy, fraction size 1.8 Gy) with 2D-conventional radiotherapy. The Gross Tumor Volume (GTV) was defined by the surgical margin and the residual gross tumor on a contrast enhanced MRI. Surrounding edema was not included in the Clinical Target Volume (CTV) in Arm 1, so as to reduce the risk of late radiation associated complications; whereas as in Arm 2 it was included. The overall survival and progression free survival times were calculated from the date of surgery using the Kaplan-Meier method. The time to progression was measured with serial neurologic examinations and MRI or CT scans after RT completion. Acute and late toxicities were evaluated using the Radiation Therapy Oncology Group neurotoxicity scores. Results: During the relatively short follow up period of 14 months, the median overall survival and progression free survival times were $15{\pm}1.65$ and $11{\pm}0.95$ months, respectively. The was a significantly longer survival time for the Arm 1 patients compared to those in Arm 2 (p=0.028). For Arm 1 patients, the median survival and progression free survival times were $21{\pm}5.03$ and $12{\pm}1.59$ months, respectively, while for Arm 2 patients they were $14{\pm}0.94$ and $10{\pm}1.63$ months, respectively. Especially in terms of the 2-year survival rate, the high-dose group showed a much better survival time than the low-dose group; $44.7\%$ versus $19.2\%$. Upon univariate analyses, age, performance status, location of tumor, extent of surgery, tumor volume and radiation dose group were significant factors for survival. Multivariate analyses confirmed that the impact of radiation dose on survival was independent of age, performance status, extent of surgery and target volume. During the follow-up period, complications related directly with radiation, such as radionecrosis, has not been identified. Conclusion: Using 3D-conformal radiotherapy, which is able to reduce the radiation dose to normal tissues compared to 2D-conventional treatment, up to 70 Gy of radiation could be delivered to the GTV without significant toxicity. As an approach to intensify local treatment, the radiation dose escalation through 3D-CRT can be expected to increase the overall and progression free survival times for patients with glioblastomas.