• International Journal of Advanced Culture Technology
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• 제8권2호
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• pp.192-203
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• 2020

Although the market demand for cold-chain logistics of agricultural products in China is growing rapidly, the technology and scale of cold-chain logistics in China still lag behind the developed countries, resulting in large energy consumption. In our country, many authors have studied the efficiency of cold-chain logistics by using analytic hierarchy process and data envelopment method, but they haven't eliminated the influence of environmental factors and random error factors on the efficiency of cold-chain logistics, and most of them are limited to regional research. Therefore, in this paper, the three-stage DEA method is used. Based on the green logistics idea, firstly, the efficiency of 29 listed logistics enterprises in China is analyzed. Secondly, this paper uses SFA model to exclude the influence of environment and error factors on the analysis results, taking the enterprise's operating years, local GDP and the proportion of cold chain assets as environmental variables. Finally, this paper estimates the efficiency value again by adjusting the input value. The results are as follows: the main reason of high efficiency enterprises is to achieve scale efficiency. So the scale of assets should be maintained or appropriately expanded. At the same time, the economic development and the number of years of enterprise establishment will significantly affect the efficiency of cold-chain logistics. The influence of these environmental variables on the accuracy of the analysis conclusion should be fully considered.

• The Journal of Asian Finance, Economics and Business
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• 제8권8호
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• pp.553-563
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• 2021

Customer value has long been believed to be a direct trigger for increased tourist satisfaction, but as a mediating variable, it still needs to be proven further. This paper aims to examine the causal relationship between research variables, as well as to examine the role of customer value as a mediating variable in the relationship between service quality, brand quality, tourism products, customer value, and tourist satisfaction with tourists' objects. The population is tourists who visit tourist sites/destinations in the Gianyar Regency on the island of Bali, Indonesia, and the sample size is 270 respondents, selected through random sampling. Structural equation modeling (SEM), a multivariate statistical analysis technique, is used to analyze the causal relationships between variables. The results show that the model is accepted, and customer value is proven to be a positive mediating variable. The results also show that service quality, brand quality, and tourism products have an effect on customer value. This provides insight into the practical implications for tourism managers to increase the brand quality of tourist attractions as well as increase the professionalism and quality of tour guide services. This, in turn, will increase customer value and increase tourist satisfaction.

• Journal of the Korean Data and Information Science Society
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• 제27권4호
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• pp.969-977
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• 2016

야외에서 재배되는 주요 채소류의 생산에 대한 기상변화의 영향력이 점차 커지고 있다. 기상변화로 인한 농작물 생산량의 변화는 공급과 수요의 불안정과 물가안정의 불안요소로 작용하고 있다. 본 논문에서는 패널회귀모형을 이용하여 기상상태에 따른 마늘의 생산량을 추정하였다. 2006년부터 2015년까지의 마늘 주산지 15곳의 10a당 마늘 생산량과 해당 지역의 기상자료를 사용하였다. 7가지 기상요인 (평균기온, 평균최저기온, 평균최고기온, 누적강수량, 누적일조시간, 평균상대습도, 평균지면온도)의 월별 (1월-12월)자료인 총 84개 기상변수중 다중회귀분석 단계선택방법을 통하여 7가지 기상변수를 선택하여 패널회귀모형에 사용하였다. 고정효과 모형과 확률효과 모형을 구분하는 하우스만 검정을 통하여 확률효과 모형으로 분석한 결과 평균최고기온 (1월), 누적강수량 (3월, 10월), 누적일조시간 (4월, 10월)등이 마늘 생산량 추정에 유의한 변수로 나타났다. 또한 연도별로 추정된 생산량 추정값의 추이가 실제 생산량과 동일한 추세를 보이고 있어 제안된 패널 회귀 모형이 잘 적합됨을 확인할 수 있다.

• Journal of Preventive Medicine and Public Health
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• 제57권4호
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• pp.399-406
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• 2024

Objectives: This study developed a causal relationship model of herb use from observational data and analyzed the direct and indirect effects of herb use on health according to the model. Methods: A cross-sectional study was conducted with 400 participants aged 26-59 years, selected through multistage random sampling. The instruments used for data collection included demographic information, herb use, health literacy (HL), perceived social support, societal values, and attitudes toward herb use. The conceptual model, hypothesized based on prior evidence, was tested using confirmatory factor analysis through structural equation modeling. Path coefficients were estimated using the maximum likelihood method. Results: The final model utilized empirical data, which showed that perceived social support had the most significant impact on herb use. This was followed by HL, positive attitudes toward herbal remedies, and societal values, with coefficients of 0.31, 0.18, and 0.16, respectively. When analyzing variables that indirectly affected herb use, it was clear that positive attitudes, perceived social support, and societal values significantly influenced herb use through HL, with influence coefficients of 0.08, 0.16, and 0.04, respectively. Together, these variables accounted for 68% of the variance in herb use. Conclusions: The findings from this study can be utilized to develop and implement strategies that guide the use of herbal products, ultimately aiming to improve human health.

• 한국식품영양학회지
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• 제27권3호
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• pp.393-399
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• 2014

The purpose of this study is to analyze the LOHAS tendency of new seniors' and its effects on the attitude and purchase intention for environmental-friendly food materials. Data were collected through a questionnaire survey from random sample of 162 senior customers in Seoul and Kyunggi area. The LOHAS tendency of new seniors can be divided into three factors; environmental-friendly, sustainability and sociality. Environmental problems affected the environmental-friendly factor the most while manufacturing techniques for sustainable products and recycling habits were key variables for the sustainability factor. The idea of companies sharing their value system of LOHAS tendency was the most significant for the sociality factor. Each of these LOHAS tendency factors influenced the purchase intention of the new seniors.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1048-1052
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• 2008

Difficulties in developing process of Liquid Crystal Display(LCD) products such as frequent design modifications, various design requirements, and short-term development period bring on the need of integrated design approach that is efficient and easy to handle. Back Light Unit(BLU) of the LCD, which drastically affects the optical performance of LCD products, is divided into in-coupling part and out-coupling part. Serration of the in-coupling part flattens the light received from point light sources and dot pattern of the out-coupling part regularizes the light sent to screen. Therefore, the optical performance of a LCD product is largely influenced by the shape of serration and the arrangement of dot pattern. In this research, a new design approach which enables to improve the optical performance of LCD products and overcome the prementioned difficulties in developing process of LCD products is proposed. The shape of serration is parameterized to 3 parameters and out-coupling part is partitioned into 10 partitions to apply the optimization technique to this problem. 3 parameters for the shape of serration and densities of 10 partitions are used as design variables in the design optimization. Optical simulation tool named SPEOS is used to evaluate the optical performance of the LCD product. Since the optical simulation uses the random ray tracing technique, numerical noise may possibly be included in the simulation process. To solve the problem caused by numerical noise, the PQRSM which can stably find the solution of the noise problem is used in this research.

• 마케팅과학연구
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• 제19권2호
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• pp.17-26
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• 2009

As the lifestyle of consumers changes and the need for various products increases, new products are being developed in the market. Each household owns various home appliances which are purchased through the choice of a decision maker. These appliances include not only large-sized products such as TV, refrigerator, and washing machine, but also small-sized products such as microwave oven and air cleaner. There exists latent correlation among possession of home appliances, even though they are purchased independently. The purpose of this research is to analyze the effect of demographic factors on the purchase and possession of each home appliances, and to derive some relationships among various appliances. To achieve this purpose, the present status on the possession of each home appliances are investigated through consumer survey data on the electric and energy product. And a multivariate probit(MVP) model is applied for the empirical analysis. From the estimation results, some appliances show a substitutive or complementary pattern as expected, while others which look apparently unrelated have correlation by co-incidence. This research has several advantages compared to previous literatures on home appliances. First, this research focuses on the various products which are purchased by each household, while previous researches such as Matsukawa and Ito(1998) and Yoon(2007) focus just on a particular product. Second, the methodology of this research can consider a choice process of each product and correlation among products simultaneously. Lastly, this research can analyze not only a substitutive or complementary relationship in the same category, but also the correlation among products in the different categories. As the data on the possession of home appliances in each household has a characteristic of multiple choice, not a single choice, a MVP model are used for the empirical analysis. A MVP model is derived from a random utility model, and has an advantage compared to a multinomial logit model in that correlation among error terms can be derive(Manchanda et al., 1999; Edwards and Allenby, 2003). It is assumed that the error term has a normal distribution with zero mean and variance-covariance matrix ${\Omega}$. Hence, the sign and value of correlation coefficients means the relationship between two alternatives(Manchanda et al., 1999). This research uses the data of 'TEMEP Household ICT/Energy Survey (THIES) 2008' which is conducted by Technology Management, Economics and Policy Program in Seoul National University. The empirical analysis of this research is accomplished in two steps. First, a MVP model with demographic variables is estimated to analyze the effect of the characteristics of household on the purchase of each home appliances. In this research, some variables such as education level, region, size of family, average income, type of house are considered. Second, a MVP model excluding demographic variables is estimated to analyze the correlation among each home appliances. According to the estimation results of variance-covariance matrix, each households tend to own some appliances such as washing machine-refrigerator-cleaner-microwave oven, and air conditioner-dish washer-washing machine and so on. On the other hand, several products such as analog braun tube TV-digital braun tube TV and desktop PC-portable PC show a substitutive pattern. Lastly, the correlation map of home appliances are derived using multi-dimensional scaling(MDS) method based on the result of variance-covariance matrix. This research can provide significant implications for the firm's marketing strategies such as bundling, pricing, display and so on. In addition, this research can provide significant information for the development of convergence products and related technologies. A convergence product can decrease its market uncertainty, if two products which consumers tend to purchase together are integrated into it. The results of this research are more meaningful because it is based on the possession status of each household through the survey data.

• Design & Manufacturing
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• 제15권1호
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• pp.48-56
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• 2021

The quality of products produced by injection molding process is greatly influenced by the process variables set on the injection molding machine during manufacturing. It is very difficult to predict the quality of injection molded product considering the stochastic nature of manufacturing process, because the process variables complexly affect the quality of the injection molded product. In the present study we predicted the quality of injection molded product using Artificial Neural Network (ANN) method specifically from Multiple Input Single Output (MISO) and Multiple Input Multiple Output (MIMO) perspectives. In order to train the ANN model a systematic plan was prepared based on a combination of orthogonal sampling and random sampling methods to represent various and robust patterns with small number of experiments. According to the plan the injection molding experiments were conducted to generate data that was separated into training, validation and test data groups to optimize the parameters of the ANN model and evaluate predicting performance of 4 structures (MISO1-2, MIMO1-2). Based on the predicting performance test, it was confirmed that as the number of output variables were decreased, the predicting performance was improved. The results indicated that it is effective to use single output model when we need to predict the quality of injection molded product with high accuracy.

• 대한원격탐사학회지
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• 제37권5_3호
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• pp.1405-1423
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• 2021

강우 현상은 물 순환과 에너지 순환의 주요 요소 중 하나이며 강우량 추정은 수자원 확보와 수재해 예측 및 피해 감축에 매우 중요한 역할을 한다. 위성 기반 강우량 추정은 시공간적으로 고해상도인 자료를 통하여 넓은 지역을 연속적으로 감시할 수 있다는 장점이 있다. 본 연구에서는 Himawari-8 Advanced Himawari Imager(AHI) 수증기 채널(6.7 ㎛), 적외 채널(10.8 ㎛)과 기상 레이더 Column Max (CMAX) 합성장을 이용하여 기계학습 기반 정량적 강우량 추정 모델을 개발하였다. 기계학습 기법으로는 랜덤 포레스트(Random Forest, RF)를 사용하였으며 기상 레이더 반사도(dBZ)와 Z-R식으로 변환한 강우강도(mm/hr)를 타겟으로 하는 모델을 구축하여 비교하였다. 레이더 강우강도를 통해 검증하였을 때 임계성공지수(Critical Success Index, CSI)는 0.34, Mean-Absolute-Error (MAE) 4.82 mm/hr였다. GeoKompsat-2(GK-2A) 강우강도 산출물, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) 산출물과 비교하였을 때 강우 유무 분류에서 CSI 21.73%, 10.81%, 강우강도 정량적 평가에서 MAE 31.33%, 23.49% 높은 성능을 보였다. 강우량 산출물을 지도화 한 결과, 실제 강우강도 분포와 유사한 분포를 모의하여 기존 산출물 대비 높은 정확도의 강우량을 추정했다.

• 수산경영론집
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• 제47권2호
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• pp.15-32
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• 2016

The Association of Southeast Asian Nations(ASEAN) has been the most essential organization in Asia. In spite of the world economic crisis, Southeast Asian countries have shown fast economic growth since 2000, and they have been actively expanding investments and trades especially with major countries. Research on competitiveness in ASEAN market has spawned an increasingly large literature, but empirical research on the determinants of Korea's export to ASEAN is limited. The purpose of this study is to draw out the determinant of Korean fisheries export to ASEAN by carrying out a panel analysis. For achieving such a purpose, pooled OLS, Hausman Test, Fixed Effect, Random Effect are performed. The last 20 years' data over the period of 1995 to 2014 concentrated on the ASEAN 6 countries such as Indonesia, Malaysia, Philippine, Singapore, Thailand, Vietnam is used in this study. Amount of aquatic products export to ASEAN is used as the dependent variable; real exchange rate, real GDP, relative price level and GDP per capita are used as the explanatory variables and FTA as dummy variable. Empirical results show that fixed-effect analysis is the best model among all the models. As the fixed effect model shows, real exchange rate, real GDP, GDP per capita and dummy variable(FTA) play positive and statistically significant roles in fisheries export to ASEAN, while price variable plays a negative and statistically significant role to the dependent variable.