The purposes of this study were to investigate the influences of channel assessments on the usage of multi-channels by product types, and the differences in the usage of multi-channels among product types in buying decision making process for fashion products. Data were collected from 510 consumers in their 20s to 50s with purchasing experiences through multi-channel distribution system and living in Seoul and Kyunggi province; 491 were analyzed after deleting incomplete questionnaires. Factor analysis, multiple regression analysis and one-way ANOVA were used for statistical analysis by using SPSS 18.0. The results were as follows: 5 factors were extracted for channel assessment: utility, accuracy, risk, price benefit and sharing information. Price benefits, utility and sharing information for online channel tended to influence positively on the usage of online channel and online+offline channels. Accuracy and low perceived risk of offline influenced positively on offline and on+offline channel usages. The usage levels of on-line and off-line channels for cosmetics were significantly lower than the usage levels for clothes and accessories on information search, evaluation of alternatives, and purchase stages. Significant differences were also found in the usage levels of multi-channels (on+off-line) on information search and evaluation of alternatives stages. The usage levels of the multi-channels for clothes were the highest followed by those of accessories and cosmetics in order.

The integrative approach for ecological stream health assessments was applied to a stream ecosystem using a multi-level organization from molecular level of biomarkers to community levels of bioindicators along with analysis of physical and chemical stressors. Water quality parameters of BOD, COD, TN, and TP etc were measured and physical habitat health, based on Qualitative habitat Evaluation Index (QHEI) model were analyzed. Also, Ecological stream health model, based on index of biological integrity (IBI) by fish assemblage, was developed for regional assessments and then applied to the stream. Six metric attributes of original 11 metrics were modified for a development of the model. Biomarkers of comet assay, blood chemistry, physiological parameters, and bioindicators such as organismal-, population-, community- level parameters were evaluated in this study along with eco-toxicity tests. Some stations impaired (stressed) in terms of stream health were identified by the IBI approach and also major key stressors affecting the health were identified using BOD, TN, TP, physical habitat evaluation, and eco-toxicity tests. The assessment approach of integrative ecological stream health would be used as a key tool for ecological restorations and species conservations in the degraded stream ecosystems and applied for elucidating major causes of ecological disturbances. Ultimately, this approach provides us an effective management strategy of stream ecosystems through establishments of ecological networks in various watersheds. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2013R1A1A4A01012939).

Quality function deployment (QFD) is a useful method in product design and development to maximize customer satisfaction. In the QFD, the technical attributes (TAs) affecting the product performance are identified, and product performance is improved to optimize customer requirements (CRs). For product development, determining the optimal levels of TAs is crucial during QFD optimization. Many optimization methods have been proposed to obtain the optimal levels of TAs in QFD. In these studies, the levels of TAs are assumed to be continuous while they are often taken as discrete in real world application. Another assumption in QFD optimization is that the requirements of the heterogeneous customers can be generalized and hence only one house of quality (HoQ) is used to connect with CRs. However, customers often have various requirements and preferences on a product. Therefore, a product market can be partitioned into several market segments, each of which contains a number of customers with homogeneous preferences. To overcome these problems, this paper proposes an optimization approach to find the optimal set of TAs under multi-segment market. Dynamic Programming (DP) methodology is developed to maximize the overall customer satisfaction for the market considering the weights of importance of different segments. Finally, a case study is provided for illustrating the proposed optimization approach.