• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Journal of Korean Society of Forest Science
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• v.32 no.1
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• pp.36-63
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• 1976

The purpose of this study is to elucidate the genetic variation of the natural forest of Pinus densiflora. Three natural populations of the species, which are considered to be superior quality phenotypically, were selected. The locations and conditions of the populations are shown in table 1 and 2. The morphological traits of tree and needle and some other characteristics were presented already in our first report of this series in which population and family differences according to observed characteristics were statistically analyzed. Twenty trees were sampled from each populations, i.e., 60 trees in total. During the autumn of 1974, matured cones were collected from each tree and open-pollinated seeds were extracted in laboratory. Immediately after cone collection, in closed condition, the morphological characteristics were measured. Seed and seed-wing dimensions were also studied. In the spring of 1975, the seeds were sown in the experimental tree nursery located in Suweon. And in the April of 1976, the 1-0 seedlings were transplanted according to the predetermined experimental design, randomized block design with three replications. Because of cone setting condition. the number of family from which progenies were raised by populations were not equal. The numbers of family were 20 in population 1. 18 in population 2 and 15 in population 3. Then, each randomized block contained seedlings of 53 families from 3 populations. The present paper is mainly concerned with the variation of some characteristics of cone, seed, needle, growth performance of seedlings, and chlorophyll and monoterpene compositions of needles. The results obtained are summerized as follows. 1. The meteorological data obtained by averaging the records of 30 year period, observed from the nearest station to each location of populations, are shown in Fig. 3, 4, and 5. The distributional pattern of monthly precipitation are quite similar among locations. However, the precipitation density on population 2, Seosan area, during growing season is lower as compared to the other two populations. Population 1. Cheong-song area, and population 3, Pyong-chang area, are located in inland, but population 2 in the western seacoast. The differences on the average monthly air temperatures and the average monthly lowest temperatures among populations can hardly be found. 2. Available information on the each mother trees (families) studied, such as age, stem height, diameter at breast height, clear-bole-length, crown conditions and others are shown in table 6,7, and 8. 3. The measurements of fresh cone weight, length and the widest diameter of cone are given in Tab]e 9. All these traits arc concerned with the highly significant population differences and family differences within population. And the population difference was also found in the cone-index, that is, length-diameter ratio. 4. Seed-wing length and seed-wing width showed the population differences, and the family differences were also found in both characteristics. Not discussed in this paper, however, seed-wing colours and their shapes indicate the specificity which is inherent to individual trees as shown in photo 3 on page 50. The colour and shape are fully the expression of genetic make up of mother tree. The little variations on these traits are resulted from this reason. The significant differences among populations and among families were found in those characteristics, such as 1000-seed weight, seed length, seed width, and seed thickness as shown in table 11. As to all these dimensions, the values arc always larger in population 1 which is younger in age than that of the other two. The population differences evaluated by cone, seed and seed-wing sizes could partly be attributed to the growth vigorousity. 5. The values of correlation between the characteristics of cone and seed are presented in table 12. As shown, the positive correlations between cone diameter and seed-wing width were calculated in all populations studied. The correlation between seed-wing length and seed length was significantly positive in population 1 and 3 but not in population 2, that is, the r-value is so small as 0.002. in the latter. The correlation between cone length and seed-wing length was highly significant in population 1, but not in population 2. 6. Differences among progenies in growth performances, such as 1-0 and 1-1 seedling height and root collar diameter were highly singificant among populations as well as families within population(Table 13.) 7. The heritability values in narrow sense of population characteristics were estimated on the basis of variance components. The values based on seedling height at each age stage of 1-1 and 1-0 ranged from 0.146 to 0.288 and the values of root collar diameter from 0.060 to 0.130. (Table 14). These heritability values varied according to characteristics and seedling ages. Here what must be stated is that, for calculation of heritability values, the variance values of population was divided by the variance value of environment (error) and family and population. The present authors want to add the heritability values based on family level in the coming report. It might be considered that if the tree age is increased in furture, the heritability value is supposed to be altered or lowered. Examining the heritability values studied previously by many authors, in pine group at age of 7 to 15, the values of height growth ranged from 0.2 to 0.4 in general. The values we obtained are further below than these. 8. The correlation between seedling growth and seed characteristics were examined and the values resulted are shown in table 16. Contrary to our hypothetical premise of positive correlation between 1-0 seedling height and seed weight, non-significance on it was found. However, 1-0 seedling height correlated positively with seed length. And significant correlations between 1-0 and 1-1 seedling height are calculated. 9. The numbers of stomata row calculated separately by abaxial and adaxial side showed highly significant differences among populations, but not in serration density. On serration density, the differences among families within population were highly significant. (Table 17) A fact must be noted is that the correlation between stomata row on abaxial side and adaxial side was highly significant in all populations. Non-significances of correlation coefficient between progenies and parents regarding to stomata row on abaxial side were shown in all populations studied.(Table 18). 10. The contents of chhlorophyll b of the needle were a little more than that of chlorophyll a irrespective of the populations examined. The differences of chlorophyll a, b and a plus b contents were highly significant but not among families within populations as shown in table 20. The contents of chlorophyll a and b are presented by individual trees of each populations in table 21. 11. The occurrence of monoterpene components was examined by gas liquid chromatography (Shimazu, GC-1C type) to evaluate the population difference. There are some papers reporting the chemical geography of pines basing upon monoterpene composition. The number of populations studied here is not enough to state this problem. The kinds of monoterpene observed in needle were ${\alpha}$-pinene, camphene, ${\beta}$-pinene, myrcene, limonene, ${\beta}$-phellandrene and terpinolene plus two unknowns. In analysis of monoterpene composition, the number of sample trees varied with population, I.e., 18 families for population 1, 15 for population 2 and 11 for population3. (Table 22, 23 and 24). The histograms(Fig. 6) of 7 components of monoterpene by population show noticeably higher percentages of ${\alpha}$-pinene irrespective of population and ${\beta}$-phellandrene in the next order. The minor Pinus densiflora monoterpene composition of camphene, myrcene, limonene and terpinolene made up less than 10 percent of the portion in general. The average coefficients of variation of ${\alpha}$-pinene and ${\beta}$-phellandrene were 11 percent. On the contrary to this, the average coefficients of variation of camphene, limonene and terpinolene varied from 20 to 30 percent. And the significant differences between populaiton were observed only in myrcene and ${\beta}$-phellandrene. (Table 25).