• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Korean Journal of Veterinary Research
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• v.4 no.1
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• pp.35-42
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• 1964

1). An nanlysis was made of 3,500 postmortem diagnoses for the three years 1961 through 1963 to determine whether there was any actual incidence of avian visceral lymphomntosis in the field. Chickens autopsied, which showed gross alterations were 7.6 percent or 266 cases. The diminished incidence of the disease in second and third years seemed due to decreased total numbers of chicken flocks year by year for the reason of difficult feed supply. 2). Because chickens autopsied in this study were not clearly known of their breeds and lines, no distinct data on the incidence in various breeds were made. Some exact breeds were in too small numbers to have any statistical significance. Inconceivably, no other types of avian leukosis than visceral lymphomatosis had been observed in any appreciable number in this analysis. 3). Pathologic analysis for affected organs was made grossly and microscopically. In the gross pictures, liver, spleen, kidney, ovary, and in some case, intestine principally showed lesions, but its manifestation was variable in different organs. In such organs, livers were affected more frequently, and spleens followed next. The organs were classified and arranged according to the gross alterations, and among their distribution one-half of livers were in diffuse variety; one-fourths in nodular; about one-sevenths in mixed; and granular variety followed next. In the spleen samples, two-thirds were in diffuse variety; one-fourths in nodular; and follicular only in three cases. Ovaries almost showed follicular lesions, the diffused were less than one-fifths of total specimens. Kidneys were occurred almost in diffuse variety. And intestine showed only nodular tomors. Microscopically, 42 cases of visceral lymphomatosis composed of 24 livers, 10 spleens, 3 kidneys, 3 intestines and 2 ovaries were examined. The tumor cells were lymphoid cells showing various component in size, shape and stainability. Mitotic figures were usually present. The proportion of the component cells were various in all cases and there were variations in the distribution of the tumor cells. The types of distribution were classified according to the standard proposed by Horiuchi as nodular, infiltrative and diffuse proliferation. In cases of visceral lymphomatosis of the livers and the spleens the types of infiltrative, nodular and diffuse proliferation could be classified. In the cases of the kidneys the types of diffuse and nodular proliferation were observed. In the cases of the intestines and the ovaries the types of infiltrative and diffuse proliferation were observed respectively.

• Korean Journal of Heritage: History & Science
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• v.41 no.1
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• pp.5-19
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• 2008

Thirty six samples of Western asia glass vessel shards which were excavated from South Mound of Hwangnamdaechong were each measured for thickness, pore size and specific gravity and analyzed for ten major compositions and thirteen trace elements. The glass samples with colorless, greenish blue and dark purple blue were well classified by principal component analysis(PCA). All glass shards of Hwangnamdaechong belonged to Soda glass system ($Na_2O-CaO-SiO_2$) which have the range of 14~17% $Na_2O$ and 5~6% CaO. The corelation coefficients of (MgO, $K_2O$) and (MnO, CuO) showed above 0.90. The concentrations of thirteen trace elements apparently differentiated from colorless, greenish blue and dark blue glasses. We found that thirteen trace elements were very important indices for studying raw material of glass and the origin of glass making. Colorless glass : The specific gravity is $1.50{\pm}0.04$. Circle or oval circle pores are observed with regular direction in internal zone and the longest one is about 0.35 mm. The raw material of sodium must be the plant ash because sodium glasses contain HCLA(High CaO, Low $Al_2O_3$) and HMK(high MgO, high $K_2O$) and suggested to Sasanian glass. The total amount of coloring agent of colorless glass is below 1 % which is too small to attribute to the color. Greenish blue glass : The specific gravity is $1.58{\pm}0.04$. The fine pores which are 0.1~0.2mm are dispersed in internal zone. Sodium glasses are distributed to HCLA and HMK. Therefore the greenish blue glass also have used plant ash for raw material of sodium with the same as colorless glass. It was also suggested to the glass of Sasanian. The total amount of coloring agent of greenish blue glass is about 4% under the influence of working MnO, $Fe_2O_3$ and CuO. Dark purple blue glass : The specific gravity is $1.48{\pm}0.19$. There are rarely pores in internal zone. They are distributed to HCLA and LMK(Low MgO, Low $K_2O$) and suggested to Roman glass. The raw material of sodium is estimated to natron. The total amount of coloring agents of greenish blue is about 3% by $Fe_2O_3$ and CuO. These studies for western asia glass shards from South Mound of Hwangnamdaechong could be used in the future as the standard data which could be compared with those of other several graves in Korea and dispersed in foreign areas.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.56-67
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• 2019

In order to investigate the issue with the proper name of eshel(Tamarix aphylla) mentioned in the Bible, analysis of morphological taxonomy features of plants, studies on the symbolism of the Tamarix genus, analysis of examples in Korean classics and Chinese classics, and studies on the problems found in translations of Korean, Chinese and Japanese Bibles. The results are as follows. According to plant taxonomy, similar species of the Tamarix genus are differentiated by the leaf and flower, and because the size is very small about 2-4mm, it is difficult to differentiate by the naked eye. However, T. aphylla found in the plains of Israel and T. chinensis of China and Korea have distinctive differences in terms of the shape of the branch that droops and its blooming period. The Tamarix genus is a very precious tree that was planted in royal courtyards of ancient Mesopotamia and the Han(漢) Dynasty of China, and in ancient Egypt, it was said to be a tree that gave life to the dead. In the Bible, it was used as a sign of the covenant that God was with Abraham, and it also symbolized the prophet Samuel and the court of Samuel. When examining the example in Korean classics, the Tamarix genus was used as a common term in the Joseon Dynasty and it was often used as the medical term '$Ch{\bar{e}}ngli{\check{u}}$(檉柳)'. Meanwhile, the term 'wiseonglyu(渭城柳)' was used as a literary term. Upon researching the period and name of literature related to $Ch{\bar{e}}ngli{\check{u}}$(檉柳) among Chinese medicinal herb books, a total of 16 terms were used and among these terms, the term Chuísīliǔ(垂絲柳) used in the Chinese Bible cannot be found. There was no word called 'wiseonglyu(渭城柳)' that originated from the poem by Wang Wei(699-759) of Tang(唐) Dynasty and in fact, the word 'halyu(河柳)' that was related to Zhou(周) China. But when investigating the academic terms of China currently used, the words Chuísīliǔ(垂絲柳) and $Ch{\bar{e}}ngli{\check{u}}$(檉柳) are used equally, and therefore, it appears that the translation of eshel in the Chinese Bible as either Chuísīliǔ (垂絲柳) or $Ch{\bar{e}}ngli{\check{u}}$(檉柳) both appear to be of no issue. There were errors translating tamarix into 'やなぎ(willow)' in the Meiji Testaments(舊新約全書 1887), and translated correctly 'ぎょりゅう(檉柳)' since the Colloquial Japanese Bible(口語譯 聖書 1955). However, there are claims that 'gyoryu(ぎょりゅう 檉柳)' is not an indigenous species but an exotics species in the Edo Period, so it is necessary to reconsider the terminology. As apparent in the Korean classics examples analysis, there is high possibility that Korea's T. chinensis were grown in the Korean Peninsula for medicinal and gardening purposes. Therefore, the use of the medicinal term $Ch{\bar{e}}ngli{\check{u}}$(檉柳) or literary term 'wiseonglyu' in the Korean Bible may not be a big issue. However, the term 'wiseonglyu' is used very rarely even in China and as this may be connected to the admiration of China and Chinese things by literary persons of the Joseon Dynasty, so the use of this term should be reviewed carefully. Therefore, rather than using terms that may be of issue in the Bible, it is more feasible to transliterate the Hebrew word and call it eshel.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.2
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• pp.153-168
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• 2022

Petrological and mineralogical analyses were conducted to identify minerals containing radioactive elements (uranium) in the Chiaksan gneiss complex and to confirm their association with the surrounding groundwater. Fourteen minerals were identified through the microscopic and electron microscopy (SEMEDS) investigation. The principal minerals included plagioclase, biotite, quartz, alkali feldspar, chlorite, and calcite. Minor minerals were sphene, allanite, apatite, zircon, thorite, titanite, pyrite, and galena. A small amount of thorite was observed in the size of ~1 mm within macrocrystalline allanite. Allanite, which includes a large amount of rare earth elements, appeared in three distinctive patterns. The results of the EPMA analyses indicated that macrocrystalline allanite had higher elemental contents of TiO₂~1.70 wt.%, Ce₂O₃~11.86 wt.%, FeO ~13.31 wt.%, MgO ~0.90 wt.% and ThO₂ ~1.06 wt.% with the lowest average content of Al₂O₃ 17.35 ± 2.15 wt.% (n = 7), CaO 12.13 ± 1.81 wt.% (n = 7). An allanite existing at the edge of the sphenes encompassing titanites had a higher element content of Al₂O₃ ~24.00 wt.%, Nd₂O₃ ~5.10 wt.%, Sm₂O₃~0.66 wt.%, Dy₂O₃~0.86 wt.% and Y₂O₃~1.38 wt.% with the lowest average content of TiO₂ 0.35 ± 0.21 wt.% (n = 11), Ce₂O₃ 5.25 ± 1.03 wt.% (n = 11), FeO 9.84 ± 0.26 wt.% (n = 11), MgO 0.12 ± 0.05 wt.% (n = 11), and La₂O₃ 1.49 ± 0.29 wt.% (n = 11). Allanites in a matrix of parental rocks exhibited intermediate values between the two elemental compositions mentioned above. None of the uranium-rich minerals were observed in the migmatitic gneiss within the study area. Consequently, the origin of uranium in the groundwater was not associated with the geology of the surrounding environment, but our investigation proved the existence of abundant allanites containing significant amounts of radioactive thorium and rare earth elements.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.26 no.1
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• pp.56-68
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• 1981

A maize line was selected in 1979 among 1000 Korean local maize lines collected in 1977. The selected maize line was characterized by having three to four tillers and eight to 10 ears on each individual plant. The line was assumed to have a great potential as a silage crop. The investigation was conducted as one of the serial studies on the Korean maize collected lines to provide basic information on the genetic variabilities of the multi-eared and tillered (MET) line and on other agronomic characters, prior to use the line as material for future breeding works for silage crop. The MET line and Suwon #19, single cross hybrid, as check variety were planted on May 1, 15 and 30, in three different levels of plant populations. The results obtained were summarized as follows: 1. The genetic variabilities of multi-ear and tillering habits were greater than environmental variabilities. 2. Total dry leaf weight of individual plant of MET line was also significantly higher than that of Suwon #19. 3. The mean number of tillers and ears bearing on the individual plant of MET line varied greatly with plant densities. The number of tillers and ears was on the average 2.9 and 7.0, respectively, when planted in 60cm. by 60cm. 4. The total dry matter and dried stem weight of the individual plant on MET line were comparable to those of Suwon #19. 5. The kernel weight from the individual plant of MET line was 5 to 40% less than that of Suwon #19, depending upon the plant densities. 6. The Kernel to stover ratio was higher for Suwon #19 than for the MET line. (41% to 35%). 7. The MET line had shown first tiller two weeks after planted on May 1. The second and third tillers appeared three to five days after the appearance of the first tiller. 8. The MET line was very specific in tillering habits. All the tillers were borne on the first few nodes of main stem below the soil surface. 9. The tillering habits of MET line were vigorous in the early part of the growing season, but less vigorous in the later part of the growing season. The number of efficient tillers bearing useable ears, was around two to three, when planted in 60cm. by 60cm. 10. The difference of plant height between main stem and first few tillers was around 10cm. 11. The ear size of MET line was around one-third of the major corn belt hybrids. The shape of ear of MET line was conical, with different diameter. 12. The kernel of the MET line was flinty with small soft starch patches on the endosperm part. 13. The 100 kernel weight was around 15gr., which is about one half of the major high yielding hybrids. 14. The ear height of MET line was comparatively higher than that of Suwon #19. 15. Significantly high and positive phenotypic correlation coefficients were obtained among major plant characters. 16. The growth rate of MET line was slower than that of Suwon #19. 17. MET line and Suwon #19 were both heavily infected with black streaked mosaic virus.

• Asia Marketing Journal
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• v.12 no.2
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• pp.155-175
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• 2010

Most of the service industries including finance and telecommunications have become matured and saturated. The competitions have become severe while the differences among brands become smaller. Therefore maintaining good relationships with customers has been critical for the service providers. In case of credit card and debit card, the similar patterns are shown. It is important for them to maintain good relationships with customers, and therefore, they have used marketing program which provides customized services to customers and utilizes the membership programs. Not only do they build and maintain good relationships, but also highlight their brands from the emotional aspects. For example, KB Card or Hyundai Card uses well-known designers' works for their credit card design. As well, they differentiate the designs of credit cards to stress on their brand personalities. BC Card introduced the credit card with perfume that a customer would like. Even though the credit card is small and not shown to public easily, it becomes more important for those companies to touch the customers' feelings with the brand personalities and their images. This is partly because of changes in consumers' lifestyles. Y-generations becomes highly likely to express themselves in many different ways and more emotional than X-generations. For the Y-generations, therefore, even credit cards in the wallet should be personalized and well-designed. In line with it, credit cards with good design can be seen as an example of brand identity, where different design for each customer can be used to recognize the membership groups that customers want to belong. On the other hand, these credit card companies offer the special treatment benefits for those customers who are heavy users for the cards. For example, those customers who love sports will receive some special discounts when they use their credit cards for sports related products. Therefore this study attempted to explore the relationships between relational benefits, brand identification and loyalty. It has been well known that relational benefits and brand identification lead to loyalty independently from many other studies, but there has been few study to review all the three variables all together in a research model. Furthermore, as reviewed above, in the card industry, many companies attempt to associate the brand image with their products to fit their customers' lifestyles while relational benefits are still playing an important role for their business. Therefore in our research model, relational benefits, brand identification, and loyalty are all included. We focus on the mediating effect of brand identification. From the relational benefits perspective, only special treatment benefit and confidence benefit are included. Social benefit is not applicable for this credit card industry because not many cases of face-to-face interaction can be found. From the brand identification perspective, personal brand identity and social brand identity are reviewed and included in the model. Overall, the research model emphasizes that the relationships between relational benefits and loyalty will be mediated by the effect of brand identification. The effects of relational benefits which are confidence benefit and special treatment benefits on loyalty will be realized when they fit to the personal brand identity and social brand identity. In the research model, therefore, the relationships between confidence benefit and social brand identity, and between confidence benefit and personal identity are hypothesized while the effects of special treatment benefit on social brand identity and personal brand identity are hypothesized. Loyalty, then, is hypothesized to have positive relationships with personal brand identity and social brand identity. In addition, confidence benefit among the relational benefits is expected to have a direct, positive relationship with loyalty because confidence benefit has been recognized as a critical factor for good relationships and satisfaction. Data were collected from college students who have been using either credit cards or debit cards. College students were regarded good subjects because they are in Y-generation cohorts and have tendency to express themselves more. Total sample size was two hundred three at the beginning, but after deleting those data with many missing values, one hundred ninety-seven data points were remained and used for the model testing. Measurement items were brought from the previous literatures and modified for this research. To test the reliability, using SPSS 14, chronbach's α was examined and all the values were from .874 to .928 exceeding over .7. Using AMOS 7.0, confirmatory factor analysis was conducted to investigate the measurement model. The measurement model was found good fit with χ²(67)=188.388 (p= .000), GFI=.886, AGFI=.821, CFI=.941, RMSEA=.096. Using AMOS 7.0, structural equation modeling has been used to analyze the research model. Overall, the research model fit were χ²(68)=188.670 (p= .000), GFI=.886, AGFI=,824 CFI=.942, RMSEA=.095 indicating good fit. In details, all the paths hypothesized in the research model were found significant except for the path from social brand identity to loyalty. Personal brand identity leads to loyalty while both confidence benefit and special treatment benefit have a positive relationships with personal and social identities. As well, confidence benefit has a direct positive effect on loyalty. The results indicates the followings. First, personal brand identity plays an important role for credit/debit card usage. Therefore even for the products which are not shown to public easy, design and emotional aspect can be important to fit the customers' lifestyles. Second, confidence benefit and special treatment benefit have a positive effects on personal brand identity. Therefore it will be needed for marketers to associate the special treatment and trust and confidence benefits with personal image, personality and personal identity. Third, this study found again the importance of confidence and trust. However interestingly enough, social brand identity was not found to be significantly related to loyalty. It can be explained that the main sample of this study consists of college students. Those strategies to facilitate social brand identity are focused on high social status groups while college students have not been established their status yet.

• Journal of Korean Society of Forest Science
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• v.14 no.1
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• pp.1-20
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• 1972

The trend and achievements of forest genetics research in abroad were investigated through observation tours and reference work and following facts were found to be important aspects which should be adopted in the forest genetics research program in Korea. Because of world wide recognization on the urgency of taking a measure to reserve some areas of the representative forest type on the globe before the extingtion of such forest type as the results of continuous exploitations of the natural forests to meet the timber demand all over the world, it is urgently needed to take a measure to reserve certain areas of natural stand of Pinus koraiensis, Pinus parviflora, Pinus densiflora f. erectra, Abies koreana, Quercus sp., Populus sp., etc. as gene pool to be used for the future program of forest tree improvement. And the genetic studies of those natural forest of economic tree species are also to be performed. 1. Increase of the number of selected tree for breeding purpose. Because of the fact that the number of plus tree at present is too small to carry out selection program for tree improvement, particularly for the formation of source population for recurrent selection of parent trees of the 2nd generation seed orchard it is to be strongly emphasized to increase the number of plus tree by alleviating selection criteria in order to enlarge the population size of plus trees to make the selection program more efficient. 2. Progeny testing More stress should be placed on carrying out progeny testing of selected trees with open pollinated seeds. And particular efforts are to be made for conducting studies on adult/juvenile correlation of important traits with a view to enable to predict adult performances with some traits revealed in juvenile age thus to save time for progeny testing. 3. Genotype-environment interaction Studies on genotype and environment interaction should be conducted in order to elucidate whether the plus trees selected on the good site express their superiority on the poor site or not and how the environment affect the genotype. And the justification of present classification of seed distribution area should be examined. 4. Seed orchard of broad leaf tree species. Due to the difficulty of accurate comparison of growth rate of neighbouring trees of broad leaf tree species in natural stand, it is recommended that for the improvement of broad leaf trees a seedling seed orchard is to be made by roguing the progeny test plantation planted densely with control pollinated seedlings of selected trees. 5. Breeding for insect resistant varieties. In the light of the fact that the resistant characteristics against insect such as pine gall midge (Thiecodiplosis japonensis U. et I.) and pine bark beetle (Myelophilus pinipera L.) are highly correlated with the amount and quality of resin which are known as gene controlled characteristics, breeding for insect resistance should be carried out. 6. Breeding for timber properties. With the tree species for pulp wood in particular, emphasis should be placed upon breeding for high specific gravity of timber. 7. Introduction of Cryptomeria and Japanese Cypress In the light of the fact that the major clones of Cryptomeria are originated from Yoshino source and are being planted up to considerably north and high elevation in Japan, those species should be examined on their cold resistance in Korea by planting them in further northern part of the country.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.59-88
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• 2008

Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.