Since technological innovation, adoption, and diffusion is a fundamental engine for a company's competitiveness and in turn a nation's industrial development, diffusion of technological innovation has been one of popular research themes to many researchers and scholars for decades. Especially, in today's knowledge-based economy, the IT technology became a fundamental infrastructure for a nation and thus their impact on a nation's economy has grown to be tremendous. This paper investigates the patterns of technological diffusion of 16 telecommunications services. Firstly, we identify the optimal diffusion model which represents the 15 IT innovation best in terms of goodness-of-fit. Secondly, based on the best model identified we cluster the 16 IT innovations according to their diffusion characteristics such as penetration rate and diffusion speed. Lastly, we categorize the innovations in terms of technology (voice-based innovation and data-based innovation) and demand (household-use and business-use) attributes, and compare their diffusion patterns and found some meaningful difference in diffusion patterns. We hope the result helpful to corporate managers as well as policy makers in relevant areas.
Turbulence greatly influence on atmospheric flow field. In the atmosphere, turbulence is represented as turbulent diffusion coefficients. To estimate turbulent diffusion coefficients in previous studies, it has been used constants or 2-level method which divides surface layer and Ekman layer. In this study, it was introduced Smagorinsky method which estimates turbulent diffusion coefficient not to divide the layer but to continue in vertical direction. We simulated 3-D flow model and TKE equation applied turbulent diffusion coefficients using two methods, respectively. Then we showed the values of TKE and the condition of each term to TKE. The results of Smagorinsky method were reasonable. But the results of 2-level method were not reasonable. Therefor, it had better use Smagorinsky method to estimate turbulent diffusion coefficients. We are expected that if it is developed better TKE equation and model with study of computational method in several turbulent diffusion coefficients for reasonably turbulent diffusion, we will able to predict precise wind field and movements of air pollutants.
The Bass model is the most widely used model in research of new product diffusion because it presents a nice explanation on the diffusion process of new products. However, it has a limitation that its performance of fitness is lower as the available data become less and also, the diffusion curve is bell-shape and so, it can not represent the various diffusion patterns. Recently, a two-pieces Bass model is developed and applied to analyze diffusion of 10 products. The results are encouraging in terms of fitness. However, diffusion pattern is not dealt with in the paper. In this paper, analysis of diffusion pattern is in depth addressed in two-pieces Bass model. It is shown that the diffusion curves are divided into 3 types with respect to the peak adoption rate and each type is divided into 2 types further. Takeoff time of a diffusion process is analyzed by using the inflection point and regime-change time where it represents the point that imitation and innovation parameters change. Empirical studies for 68 products(28 domestic products and 40 USA products) are performed to analyze the diffusion pattern. Findings are that diffusion patterns of all products except 1 USA product show type I and regime-change time becomes shorter as the introduction time of the product is later in domestic products and regime-change time can be regarded as a takeoff time in 47% of total 68 products.
Journal of Information Technology Applications and Management
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v.17
no.2
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pp.187-205
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2010
This study takes a holistic approach to understand the diffusion of IPTV services by combining the adoption-diffusion model and the use-diffusion model of innovation. IPTV service, a leading digital converged application coupling media content with telecommunications, has been recently launched commercially in Korea. We created a structural model of adoption-diffusion, using the perceived easeof-use and usefulness of TAM(Technology Acceptance Model) as mediating variables, and a structural model of use-diffusion, with the rate of use and the variety of use as mediating variables. To empirically analyze these models, non-users of IPTV were surveyed using the adoption-diffusion model to identify factors influencing their intention to subscribe to the service. Meanwhile, users of IPTV were surveyed using the use-diffusion model to determine the factors that influence their satisfaction with the service and their intention to re-use it. Under the adoption-diffusion model, we found that trialability, household innovativeness and perceived risk were the determinants of user satisfaction with IPTV, and perceived ease-of-use, the mediating factors. Under the use-diffusion model, complementarity and communication were shown to be the determinants of users' satisfaction with IPTV, and variety of use, the mediating factor. We also found that consumers' intention to re-use IPTV was strongly influenced by its relative advantage and perceived risk.
Journal of The Korean Society of Agricultural Engineers
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v.50
no.4
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pp.27-37
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2008
It is most serious problem which is various occurs from the agricultural concrete structure and off shore concrete structure the problem which it comes to think is deterioration of the concrete which is caused with the corrosion of the reinforcing steel which is caused by with permeation of the water and the sea water. Specially the off shore concrete structure has been deteriorated by the steel reinforcement corrosion. The latex modified concrete(LMC) was adds latex in the plain concrete as the latex has increase the durability of concrete. This study were accomplished to the estimate the diffusion coefficient of LMC, and the time dependent constants of diffusion. The average chloride diffusion coefficient was estimated. Also, the average chloride diffusion coefficient was compared with diffusion coefficient test results of 28 curing days. The test results indicated that the average chloride diffusion coefficient could closely estimate the test results of the diffusion coefficient test results of 28 curing days.
Electronic Data Interchange(EDI) has the potential to improve business operations by expediting the exchange of business documents. It will also provide substantive operational and strategic benefits to the trading firms. However, the successful implementation of EDI systems requires the mutual trust and cooperation between the trading firms. The extent of EDI diffusion and performance depends on inter-organizational, intra-organizational, as well as innovation factors. Researches based on the sociopolitical process framework in the use of IT, organizational theory, resource dependence theory, and innovation diffusion theory have identified 3 inter-organizational variables(transaction climate, dependence, external IS expert support) and 4 intra-organizational variables(strategic IS planning, infrastructure, top management support, education/training,), and 3 innovation variables(compatibility, relative advantage, cost) that affect EDI diffusion. In this study, a multi-dimensional measure on EDI diffusion has been developed to capture the external and internal integration. Then, the influence of these 10 variables on the extent to which the EDI adopting firms pursue diffusion has been examined. Whether more diffusion leads to superior performance has also been studied. International trade managers from 107 firms in the trade industry participated in a field survey. The results based on a structural equation model(SEM), developed using AMOS, provide quite a strong support for the hypothesized relations. Both education/training and IT infrastructure influenced external and internal diffusion of EDI systems. Internal diffusion of EDI enables the adopting firms to improve operational and strategic performance, whereas external diffusion contributes only to operational performance.
Journal of the Korean Applied Science and Technology
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v.24
no.1
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pp.79-85
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2007
The diffusion behavior of phenol, toluene and benzoic acid in aqueous SDS solution was examined. It showed a similar experimental results for phenol and toluene. The diffusion coefficients of the solutes were characterized by the presence of two distinct regions: below the cmc and above the cmc. For phenol and toluene, it remained approximately unchanged when the SDS concentration was below the cmc. Above the cmc there was an apparent decrease in the diffusion coefficients of the two solutes with increasing SDS concentration. However, for benzoic acid the diffusion behavior was different from that of phenol and toluene. The diffusion coefficient of benzoic acid decreased slightly with increasing SDS concentration, however the diffusion coefficient was almost constant above the cmc. For benzoic acid the diffusion behavior was dependent on the joint contribution of benzoic acid molecules as well as the benzoate ions.
Proceedings of the Korea Database Society Conference
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2010.06a
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pp.165-180
/
2010
This study takes a holistic approach to understanding the diffusion of IPTV services by combining the adoption-diffusion model and the use-diffusion model of innovation. IPTV service, a leading Digital converged application coupling media content with telecom, has been recently launched commercially in Korea. We created a structural model of adoption-diffusion, using the perceived ease-of-use and usefulness of TAM(Technology Acceptance Model) as mediating variables, and a structural model of use-diffusion, with the rate of use and the variety of use as mediating variables. To empirically analyze these models, non-users of IPTV were surveyed using the adoption-diffusion model to identity factors influencing their intention to subscribe to the service. Meanwhile, users of IPTV were surveyed using the use-diffusion model to determine the factors that influence their satisfaction with the service and their intention to fe-use it. Under the adoption-diffusion model, we found that trialability, household innovativeness and perceived risk were the determinants of user satisfaction with IPTV, and perceived ease-of-use, the mediating factors. Under the use-diffusion model, complementarity and communication were shown to be the determinants of users' satisfaction with IPTV, and variety of use, the mediating factor. We also found that consumers' intention to re-use IPTV was strongly influenced by its relative advantage and perceived risk.
A diffusion process is often the main mechanism of soil gas/vapor movement in the vadose zone. The diffusion coefficients in the porous soil media are different from those in the free air phase by the reduction of available area for diffusion, tortuous diffusion path and variable cross section area along the diffusion path. To take account those effects of the diffusion process in the porous media, usually the terms of effective diffusion coefficient and tortuosity are have been used. However, as there are many differents definitions for the tortuosity, when the term of tortuosity is used, it is necessary to examine it throughly. Moreover, there are many different equations for the effective diffusion coefficient according to the investigators and the differences in the values of effective diffusion coefficients between the equations are not insignificant, the selection of the equation should be done with caution. In this paper, the different definitions of effective diffusion coefficient are examined and discussed. As well as definitions, the lots of availabe models for the diffusion coefficient in terms of porosities are compared. Also, the constrictiviy which explains the effect of cross sectional area change over the diffusion path was discussed.
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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