• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Culinary science and hospitality research
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• v.22 no.7
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• pp.112-130
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• 2016

In this study the moisture content and chromaticity of fresh made lotus leaf powder added Cheongpomuk to utilize various efficacy of lotus leaf for processed food, as well as chromaticity, moisture content change, texture, total phenolic compound content, DPPH radical scavenging ability and preference of lotus leaf powder added Cheongpomuk with different storage period have been measured and analyzed. From the texture of lotus leaf powder added mung bean as per the storage period, the hardness of fresh Cheongpomuk were $0.38g/cm^2$ from control group, $0.40g/cm^2$ from CCD 1% group, $0.42g/cm^2$ from CCD 3% group, $0.37g/cm^2$ from CCD 5% group, $0.42g/cm^2$ from GGD 1% group, $0.39g/cm^2$ from GGD 3% group, $0.35g/cm^2$ from GGD 5% group, $0.39g/cm^2$ from JLD 1% group, $0.33g/cm^2$ from JLD 3% group, and $0.32g/cm^2$ from JLD 5% group. It has shown that JLD 5% group was the lowest, while CCD 3% group and GGD 1% group were the highest, and there were significant differences among sample groups. For DPPH radical scavenging ability, that of GLD 5% group was 22 times higher than that of control group. In addition, the tendency was increasing by increasing the adding rate of lotus leaf powder though there was some tolerance among sample groups. For total phenolic compound content, that of control group was 6.65 mg CE/100 g, and others were 7.48 mg CE/100 g from CCD 1% group, 15.82 mg CE/100 g from CCD 3% group, 20.15 mg CE/100 g from CCD 5% group, 15.55mg CE/100 g from GGD 1% group, 23.02 mg CE/100 g from GGD 3%, 26.95 mg CE/100 g from GGD 5% group, 3.92 mg CE/100 g from JLD 1% group, 16.72 mg CE/100 g from JLD 3%, and 26.58 mg CE/100 from JLD 5% group. From the analyzing result of responses for color and scent, taste, elasticity, and total preference of lotus leaf powder added Cheongpomuk between two panel groups, there was significant difference for the color, higher from professional cooking instructor group, but there were no significant difference between two groups for all other factors among professional cooking instructors and cooking department students. According to the results, it is expected that various functional foods can be developed by utilizing lotus leaf powder, depending on the growth condition and cultural environment of each region by adding 3% of lotus leaf powder, would be the most suitable recipe for Cheongpomuk.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.5
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• pp.321-327
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• 2006

In Korea, there is a growing competitive for water resources between industrial, domestic and agricultural consumer, and the environment as many other OECD countries. The demand on water use is also affecting aquatic ecosystems particularly where withdrawals are in excess of minimum environmental needs for rivers, lakes and wetland habits. OECD developed three indicators related to water use by the agriculture in above contexts : the first is a water use intensity indicator, which is expressed as the quantity or share of agricultural water use in total national water utilization; the second is a water stress indicator, which is expressed as the proportion of rivers (in length) subject to diversion or regulation for irrigation without reserving a minimum of limiting reference flow; and the third is a water use efficiency indicator designated as the technical and the economic efficiency. These indicators have different meanings in the aspect of water resource conservation and sustainable water use. So, it will be more significant that the indicators should reflect the intrinsic meanings of them. The problem is that the aspect of an overall water flow in the agro-ecosystem and recycling of water use not considered in the assessment of agricultural water use needed for calculation of these water use indicators. Namely, regional or meteorological characteristics and site-specific farming practices were not considered in the calculation of these indicators. In this paper, we tried to calculate water use indicators suggested in OECD and to modify some other indicators considering our situation because water use pattern and water cycling in Korea where paddy rice farming is dominant in the monsoon region are quite different from those of semi-arid regions. In the calculation of water use intensity, we excluded the amount of water restored through the ground from the total agricultural water use because a large amount of water supplied to the farm was discharged into the stream or the ground water. The resultant water use intensity was 22.9% in 2001. As for water stress indicator, Korea has not defined nor monitored reference levels of minimum flow rate for rivers subject to diversion of water for irrigation. So, we calculated the water stress indicator in a different way from OECD method. The water stress indicator was calculated using data on the degree of water storage in agricultural water reservoirs because 87% of water for irrigation was taken from the agricultural water reservoirs. Water use technical efficiency was calculated as the reverse of the ratio of irrigation water to a standard water requirement of the paddy rice. The efficiency in 2001 was better than in 1990 and 1998. As for the economic efficiency for water use, we think that there are a lot of things to be taken into considerations to make a useful indicator to reflect socio-economic values of agricultural products resulted from the water use. Conclusively, site-specific, regional or meteorogical characteristics as in Korea were not considered in the calculation of water use indicators by methods suggested in OECD(Volume 3, 2001). So, it is needed to develop a new indicators for the indicators to be more widely applicable in the world.

• Food Science of Animal Resources
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• v.29 no.6
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• pp.726-735
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• 2009

This study was conducted to investigate the Warner-Bratzler shear force (WBS), sarcomere length, total collagen contents and consumer tests of different cuts of Hanwoo beef based on quality grade. Five cuts [Cheggt (striploin), Dngsim (loin), Moksim (chuck roll), Udoon (top round), Yanggi (brisket)] were obtained from Hanwoo beef (bulls and steers, 24-30 months old) and grouped by their quality grades ($1^{++}$, $1^+$, 1, 2 and 3). The WBS values of chuck cut in $1^{++}$, $1^+$ and 1 quality grade groups were 5.47 (kg/0.5 $inch^2$), 5.46 (kg/0.5 $inch^2$) and 6.54 (kg/0.5 $inch^2$), respectively, which were significantly lower than those of chuck in quality grade 3, which was 8.41 (kg/0.5 $inch^2$) (p<0.05). The sarcomere length of the quality grade groups were significantly longer for brisket (3.72 ${\mu}m$) of $1^{++}$ quality grade than for that of 3 quality grade brisket (p<0.05). Brisket of $1^{++}$ and 2 quality grade had significantly greater sarcomere lengths than strip loin and top round in the same quality grade (p<0.05). The total collagen contents of strip loins in the $1^{++}$, $1^+$, and 1 quality grade groups (1.17, 1.18 and 1.14 g/100 g, respectively) were significantly lower than those of the 3 quality grade group (1.63 g/100 g) (p<0.05). The overall sensory scores of tenderness and juiciness for the five cuts of $1^{++}$ quality grade were significantly higher than those of the other quality grade (p<0.05). Among the five cuts, loin had the highest tenderness and juiciness scores (p<0.05), whereas top round had the lowest tenderness and juiciness scores (p<0.05). Overall, there were significant differences in the WBS and sensory properties among quality grades and cuts (p<0.05). However, the sarcomere length and total collagen contents of chuck roll, top round and loin did not differ among quality grades.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.197-218
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• 2019

In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.1-8
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• 2022

In order to manufacture feed suitable for consumer use and provide feed value information, we analyzed the feed components of the four main forage rice varieties by plant parts harvested 30 days after heading. The contents of the six feed ingredients were significantly different (p<0.05) among harvested parts. In the panicle, the crude protein (CP) (6.97%) and lignin (3.11%) were the highest, while the crude ash (CA) and neutral detergent fiber (NDF) contents were significantly lower, resulting in a total digestible nutrient (TDN) content of 77.29%, which is higher than that of the stem (64.82%) and leaf blade and sheath (LBS) (63.57%) (p<0.05). In contrast, the content of crude fat (CF) did not differ significantly among parts (p<0.05). In panicles from 'Jonong', 'Nokyang' and 'Yeongwoo', the TDN content of each cultivar was 78.48-79.07%, with no significant difference among the varieties. In 'Mogwoo' (Mw), the CP content was 8.70%, which was much higher than that of other varieties (p<0.05). In particular, the Mw TDN content was slightly lower in the panicle (72.95%) but higher in the stem (75.37%) and LBS (66.49%) than in the other varieties. The CA, NDF, acid detergent fiber (ADF), and lignin contents were also very low compared to other varieties; therefore, the feed value of the stem and LBS was excellent. In addition, the total dry matter weight (DMW) was 123 g per hill, which was much higher than 82-105 g per hill for other varieties. The distribution of DMW by part was LBS (56.9 g), stem (36.8 g), and panicle (29.3 g), and because the parts, except the panicles, were much higher than the 43-57% of other varieties (grain straw ratio: 76%), rice straw is advantageous in terms of quantity and feed value when used as forage on farms. The relative feed value (RFV) of the four cultivars ranged from 86.79-403.74 across all parts, and hay of grade 3 or higher with an RFV of 100 or more increased with delayed heading in both stems and LBS. This is due to the accumulation of starch into grains during ripening, which supports the observation that the RFV of the early flowering 'Jonong' and 'Nokyang' panicles increased.

• Journal of the East Asian Society of Dietary Life
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• v.21 no.6
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• pp.934-947
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• 2011

The purpose of this study is to analyze products for good taste and convenience, which become an engine to constantly create customers. In addition, this study is aimed at investigating the relationship between the selective attributes of Home Meal Replacement, the perceived utilitarian value, and the repurchase intention, and drawing new suggestions on the Home Meal Replacement market from a new marketing perspective. Based on a total of 215 samples, this study reviewed the reliability and fitness of the research model and verified a total of 5 hypothesized using the Amos program. The result of study modeling was GFI=0.905, AGFI=0.849, NFI=0.889, CFI=0.945, and RMR=0.0.092 at the level of $x^2$=230.22 (df=126, p<0.001). First, the food quality (${\beta}$=0.221), convenience (${\beta}$=0.334), packing (${\beta}$=0.278), and employee service (${\beta}$=0.204) of home meal replacement consideration attributes had a positive (+) influence on perceived utilitarian value. Second, perceived utilitarian value (${\beta}$=0.584) had a positive (+) influence on repurchase intention. The factors to differentiate one company from other competitors in terms of the utilitarian value are the quality of food, convenience, wrapping, and services by employees. This study has illustrated the need to focus on the development of a premium menu to compete with other companies and to continue to research and develop nutritious foods that are easy to cook. Moreover, the key factors to have a distinct and constant competitive edge over other companies are the alleviation of consumer anxiety over wrapping container materials, the development of more designs, and the accumulation of service know-how. Therefore, it is necessary for a company to strongly develop the key factors based on its resources as a core capability.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Korean Society of Forest Science
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• v.34 no.1
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• pp.31-46
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• 1977

The study was made to give some helpful information for policy-making on ornamental tree cultivation by doing a survey on general situations, management analysis, and future prospects of the ornamental tree growing. The study was carried out through literature studies related to the subject, questionaire surveys, and on-the-spot investigation. The questionaire surveys could be divided into two parts: pre-questionaire survey and main-questionaire survey. In the pre-questionaire survey, the researchers intended to identify the total number of ornamental tree growers, cultivation areas in size and their locations. The questionaires were sent to each town and county administration authorities, forest cooperatives, and related organizations through-out the nation. The main-questionaires were prepared for detailed study and the questionaires were sent to 200 tree growers selected by option by taking considerations of the number of tree growers and the size of cultivating areas in regions. The main findings and some information obtained in the survey were as follows: 1. The total land for ornamental tree growing was amounted to 1,873.02 hectares and the number of cultivators was totaled to 2,717. 2. The main occupations of the ornamental tree growers were found in horticulture (41.9%), agronomy (25.9%), officialdom (11.3%), animal husbandry (6.5%), business circle(4.8%), and forestry (3.2%) in sequence. 3. The ornamental trees were cultivated mostly upperland (54.8), forest land (19.4%), rice paddy (11.3%) and others. 4. The educational training of the tree growers seemed quite high. The results of the survey indicated that a large number of tree growers was occupied by college graduates (38.7%), and then high school graduates (34.7%), middle school graduates (12.9%) in order. 5. The tree farming was undertaken as a side-job (41.9%) rather than main-job (23.4%), but a few of respondents rated as subsidiary-job (18.6%). 6. The management status classified by the rate of hired labors used was likely to belong to three categories: independant enterprise management (41.9%); half independant management (31.5%); and self-management (32.4%). 7. The majority of the tree growers sold their products to the consumers through middle-man channel (48.4%), or directly to the house-holder and detailers (13.7%), but a few of the respondents answered that they disposed of their products by bidding (11.2%) or by direct selling to the contractors (4.8%). 8. The channel cf marketing seemed somewhat complicated. The results of the survey were as: (1) producers ${\rightarrow}$consumers (22.6%) (2) producers ${\rightarrow}$field middle-men${\rightarrow}$consumers (33.1%) (3) producers ${\rightarrow}$field middle-men${\rightarrow}$first stage brokers${\rightarrow}$consumers (15.3%) (4) producers ${\rightarrow}$field middle-men${\rightarrow}$second stage middle-men${\rightarrow}$brokers${\rightarrow}$consumers (5.7%) (5) producers${\rightarrow}$field middle-men${\rightarrow}$third stage middle-men${\rightarrow}$second stage middlemen${\rightarrow}$brokers${\rightarrow}$consumers (4.8%) 9. It was responded that the margin for each stage of middle-men or brokers was assumed to be 30-50%(33.1%), 20-30%(32.3%), 50-100%(9.7%), and 100-200%(2.4%) in sequence. 10. The difference between the delivery price of consumers and field selling price of the producers seemed quite large. Majority of producers responded that they received half a price compared to the consumer's prices. 11. About two thirds of the respondents opposed to the measure of "Law on Preservation and Utilization of Agricultural Land" in which says that all the ornamental trees grown on flat agricultural lands less than 8 degrees in slope must be transplanted within three years to other places more than 8 degrees in slope. 12. The tree growers said that they have paid rather high land taxes than they ought to pay (38.7%), but come responded that land tax seemed to be appropriate (15.3%), and half of the respondents answered "not known". 13. The measures for the standardization of ornamental trees by size were backed up by a large number of respondents (57.3%), but one third of the respondents showed negative answer (29.8%). 14. About half of the respondents favored the systematic marketing through organization such as forest cooperatives (54%), but quite a few respondents opposed to organizing the systematic marketing channel (36.3%). 15. The necessary measures for permission in ornamental tree cultivation was rejected by a large number of respondents (49.2%) than those of favored (43.6%).