• The Korean Journal of Nuclear Medicine
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• v.37 no.2
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• pp.110-119
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• 2003

Purpose: Radioiodine (I-131) therapy is an effective modality to reduce both recurrence and mortality rates in differentiated thyroid cancer. Whether higher doses shows higher therapeutic responses was still debatable. The purpose of this study was to validate curve-fitting (CF) method measuring maximum permissible dose (MPD) by a biological dosimetry using metaphase analysis of peripheral blood lymphocytes. Materials and Methods: Therapeutic effects of MPD was evaluated in 58 patients (49 females and 9 males, mean age $50{\pm}11$ years) of papillary thyroid cancer. Among them 43 patients were treated with ${\Leq}7.4GBq$, while 15 patients with ${\geq}9.25GBq$. The former was defined as low-dose group, and the latter high-dose group. Therapeutic response was defined as complete response when complete disappearance of lesions on follow-up I-131 scan and undetectable serum thyroglobulin levels were found. Statistical comparison between groups were done using chi-square test. P value less than 0.05 was regarded as statistically significant. Results: MPD measured by CF method using tracer and therapeutic doses were $13.3{\pm}1.9\;and\;13.8{\pm}2.1GBq$, respectively (p=0.20). They showed a significant correlation (r=0.8, p<0.0001). Exposed doses to blood measured by CF and biological methods were $1.54{\pm}0.03\;and\;1.78{\pm}0.03Gy$ (p=0.01). They also showed a significant correlation (r=0.86, p=0.01). High-dose group showed a significantly higher rate of complete response (12/15, 80%) as compared to the low-dose group (22/43, 51.2%) (p=0.05). While occurrence of side effects was not different between two groups (40% vs. 30.2%, p=0.46). Conclusion: Measurement of MPD using CF method is reliable, and the high-dose I-131 therapy using MPD gains significantly higher therapeutic effects as compared with low-dose therapy.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.