Mobile telecom markets have dramatically increased in the last decade due to a remarkable subscriber base growth. The diffusion patterns of the services are a major concern for mobile carriers preparing those new services. We assume that the diffusion patterns of those services will be similar to those of previous mobile services, and discovering the diffusion patterns of those services is an essential task of mobile carriers for preparing the next mobile services. This study attempts to classify some groups which show similar diffusion patterns of mobile services. Using a traditional diffusion model, this study estimates diffusion patterns of twenty five western European countries. The estimation is based on the monthly penetration ratio of those countries from 1993 to 2004. Based on the estimation, the cluster analysis discovers that there are two different countries groups in terms of mobile diffusion pattern: high imitation countries and low imitation countries. The critical point for classifying the two groups in terms of imitation effect was 0.90. The results provide the basis for developing a causal relationship model which explains the different diffusion pattern of mobile services and planning new networks for the advanced mobile services.
Part I of this study was devoted to the electrical accelerated chloride diffusion in mortars. In this second part, natural chloride diffusion has been investigated for four types of mortars under exposure to a 0.5 mol/L NaCl solution for a period of up to 35 days. Two different types of sand were used for the production of test samples: siliceous sand (used as a reference) and limestone sand (used in this study). The effect of water to cement ratio and exposure time on the diffusion coefficients of mortars was also investigated. In this study, the total and free chloride content and penetration depth of mortar were measured after immersion, and Fick's second law of diffusion was fitted to the experimental data to determine the diffusion coefficient. Their results show that the use of crushed limestone sand in mortar had a positive effect on the chloride resistance. The apparent diffusion coefficient in all specimens was smaller than that in siliceous sand mortar. However, the chloride penetration of these mortars was increased as exposure time progressed.
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.