• Title/Summary/Keyword: Statistic

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A Study on the Regional Characteristics of Broadband Internet Termination by Coupling Type using Spatial Information based Clustering (공간정보기반 클러스터링을 이용한 초고속인터넷 결합유형별 해지의 지역별 특성연구)

  • Park, Janghyuk;Park, Sangun;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.45-67
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    • 2017
  • According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

Spatial effect on the diffusion of discount stores (대형할인점 확산에 대한 공간적 영향)

  • Joo, Young-Jin;Kim, Mi-Ae
    • Journal of Distribution Research
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    • v.15 no.4
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    • pp.61-85
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    • 2010
  • Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown

    . In a result of the Bass model(I), the estimates of innovation coefficient(p) and imitation coefficient(q) are 0.017 and 0.323 respectively. While the estimate of market potential is 384. A result of the Bass model(II) for each district shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. A result of the Bass model(II) shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. In a result of spatial diffusion model(IV), we can notice the changes between coefficients of the bass model and those of the spatial diffusion model. Except for GJ, the estimates of innovation and imitation coefficients in Model IV are lower than those in Model II. The changes of innovation and imitation coefficients are reflected to spatial coefficient(${\gamma}$). From spatial coefficient(${\gamma}$) we can infer that when the diffusion in the vicinity of the diffusing center occurs, the diffusion is influenced by one in the diffusing center. The difference between the Bass model(II) and the spatial diffusion model(IV) is statistically significant with the ${\chi}^2$-distributed likelihood ratio statistic is 16.598(p=0.0023). Which implies that the spatial diffusion model is more effective than the Bass model to describe diffusion of discount stores. So the research question (1) is supported. In addition, we found that there are statistically significant relationship between similarity of retail environment and spatial effect by using correlation analysis. So the research question (2) is also supported.

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  • Clinical Application of Serum CEA, SCC, Cyfra21-1, and TPA in Lung Cancer (폐암환자에서 혈청 CEA, SCC, Cyfra21-1, TPA-M 측정의 의의)

    • Lee, Jun-Ho;Kim, Kyung-Chan;Lee, Sang-Jun;Lee, Jong-Kook;Jo, Sung-Jae;Kwon, Kun-Young;Han, Sung-Beom;Jeon, Young-June
      • Tuberculosis and Respiratory Diseases
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      • v.44 no.4
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      • pp.785-795
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      • 1997
    • Background : Tumor markers have been used in diagnosis, predicting the extent of disease, monitoring recurrence after therapy and prediction of prognosis. But the utility of markers in lung cancer has been limited by low sensitivity and specificity. TPA-M is recently developed marker using combined monoclonal antibody of Cytokeratin 8, 18, and 19. This study was conducted to evaluate the efficacy of new tumor marker, TPA-M by comparing the estabilished markers SCC, CEA, Cyfra21-1 in lung cancer. Method : An immunoradiometric assay of serum CEA, sec, Cyfra21-1, and TPA-M was performed in 49 pathologically confirmed lung cancer patients who visited Keimyung University Hospital from April 1996 to August 1996, and 29 benign lung diseases. Commercially available kits, Ab bead CEA (Eiken) to CEA, SCC RIA BEAD (DAINABOT) to SCC, CA2H (TFB) to Cyfra2H. and TPA-M (DAIICHI) to TPA-M were used for this study. Results : The mean serum values of lung cancer group and control group were $10.05{\pm}38.39{\mu}/L$, $1.59{\pm}0.94{\mu}/L$ in CEA, $3.04{\pm}5.79{\mu}/L$, $1.58{\pm}2.85{\mu}/L$ in SCC, $8.27{\pm}11.96{\mu}/L$, $1.77{\pm}2.72{\mu}/L$ in Cyfra21-1, and $132.02{\pm}209.35\;U/L$, $45.86{\pm}75.86\;U/L$ in TPA-M respectively. Serum values of Cyfra21-1 and TPA-M in lung cancer group were higher than control group (p<0.05). Using cutoff value recommended by the manufactures, that is $2.5{\mu}/L$ in CEA, $3.0{\mu}/L$ in Cyfra21-1, 70.0 U/L in TPA-M, and $2.0{\mu}/L$ in SCC, sensitivity and specificity of lung cancer were 33.3%, 78.6% in CEA, 50.0%, 89.7% in Cyfra21-1, 52.3%, 89.7% in TPA-M, 23.8%, 89.3% in SCC. Sensitivity and specificity of nonsmall cell lung cancer were 36.1%, 78.1% in CEA, 50.1%, 89.7% in Cyfra21-1, 53.1%, 89.7% in TPA-M, 33.8%, 89.3% in SCC. Sensitivity and specificity of small cell lung cancer were 25.0%, 78.5% in CEA, 50.0%, 89.6% in Cyfra21-1, 50.0%, 89.6% in TPA-M, 0%, 89.2% in SCC. Cutoff value according to ROC(Receiver operating characteristics) curve was $1.25{\mu}/L$ in CEA, $1.5{\mu}/L$ in Cyfra2-1, 35 U/L in TPA-M, $0.6{\mu}/L$ in SCC. With this cutoff value, sensitivity, specificity, accuracy and kappa index of Cyfra21-1 and TPA-M were better than CEA and SCC. SCC only was related with statistic significance to TNM stages, dividing to operable stages(TNM stage I to IIIA) and inoperable stages (IIIB and IV) (p<0.05). But no tumor markers showed any correlation with significance with tumor size(p>0.05). Conclusion : Serum TPA-M and Cyfra21-1 shows higher sensitivity and specificity than CEA and SCC in overall lung cancer and nonsmall cell lung cancer those were confirmed pathologically. SCC has higher specificity in nonsmall cell lung cancer. And the level of serum sec are signiticantly related with TNM staging.

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    Studies on the Species Crossabilities in the Genus Pinus and Principal Characteristics of F1 Hybrids (일대잡종송(一代雜種松)의 교배친화력(交配親和力)과 특성(特性)에 관(關)한 연구(硏究))

    • Ahn, Kun Yong
      • Journal of Korean Society of Forest Science
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      • v.16 no.1
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      • pp.1-32
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      • 1972
    • By means of the interspecific hybridization in the Sub-genus Diploxylon of the Genus Pinus, $F_1$ hybrids of Pinus rigida${\times}$elliottii, Pinus rigida${\times}$radiata, P. rigida${\times}$serotina and P. densiflora${\times}$thunbergii had been produced. And on the basis of the crossabilities of these hybrids the taxonomic affinities of these pines were examined. And the needle characteristics of these hybrid and the occurence of phenolic substances in these $F_1$ hybrid were also investigated to see the potential usefulness of these characteristics for the diagnosis of the taxonomic affinity. And, the growth performances of the $F_1$ hybrids have also been compared with those of parental species. In order to contribute to the establishment of the hybrid seed orchard the introgression phenomena between P. densiflora and P. thunbergii in the eastern coastal area have also been investigated along with the investigation of the heterozygosity of plus trees of P. densiflora growing in the clone bank in Suwon. And the results were summarized as follows. 1. On the basis of crossabilities as well as on the taxonomic affinities according to the systems of Shaw, Pilger and Duffield, it has been proven that the parental species of those hybrids are of close affinities and range of the fertile hybrid seed production rate was as high as 28-58% in the best hybrid combination (Table 13). 2. Among those hybrids, the ${\times}$ Pinus, rigiserotina hybrid seemed to be most promising in the growth performance exhibiting 109-155% more volume growth compared to the seed parent with the statistic significance of 1% level (Tables 16 and 17). 3. Notwithstanding the fact that the all of the pollen parents are cold tender, all hybrids exhibit cold hardiness as much as their seed parent and it seems to suggest that the characteristics of cold hardiness were transmitted from the seed parent. 4. Though a striking difference in needle length was observed between the parental species of each hybrid, it was difficult to distinguish each hybrid from their seed parent by the needle length except ${\times}$P. rigiserotina which is characterized by long needle which is 65% more longer than the needle of the seed parent (Table 21). 5. With regard to the anatomical characteristics of needle, the hypoderm is apparently thicker in most of the $F_1$ hybrid pines and the characteristics of resin canals are dominated by medial in most $F_1$ hybrid. And, the fibrovascular bundles were apart as were in their seed parent. Therefore it was found to be possible to distinguish the hybrids pines from their parents by the needle characteristics. And, it is to be noticed that the ${\times}$P. densithunbergii was more close to the pollen parent having RDI value of 0.73 (Fig.l, Table 22). 6. It has been demonstrated that ${\times}$P. rigielliottii, ${\times}$P. rigiradiata and ${\times}$P. rigitaeda have a phenolic substance (No.7) of light yellow at Rf-0.46, same as their seed parent, but no trace of phenolic substance was observed in their pollen parent. This fact will serve as an important criteria for early identification of hybridity in progeny testing. However, the fact that both of ${\times}$P. rigiserotina and ${\times}$P. densithunbergii exhibit the same reactions of phenolic substances as well their parental species seems to indicate the close affinities between the parental species of the respective hybrid (Fig.2, Table 23). 7. The separation and the reaction of phenolic substance developed on TLC were found to be same in the same species showing no variations between the individuals, and no variations due to tree part of sampling, tree age or pollen sources. And the reaction was also observed regardless of the not varied by the kind of developing solvent whether it is Aceton-Chloroform (3:7 v/v) or Benzene-Methanol-Acetic acid (90:16:8 v/v). 8. The introgression phenomena of natural Pinus densifiora stand in both east and west coastal area indicates that the major part of the red pines investigated are all heterozygous and the heterozygosity of pines are higher in the west coast than in the east coast(Tables 24 and 25). 9. Based on the RDI, among the plus trees of Pinus densiflora selected in Korea and Japan as well, no pure P. densiflora has been found. Since all of the sample trees of Pinus densiflora were found to be as heterozygous bearing part of the characteristics of P. thunbergii, those red pines were considered to be natural heterotic hybrid pines(Figs. 3 and 4. Tables 26 and 27).

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