Analysis of the Characteristics, Strengths, and Weaknesses of Innovation Diffusion Type in Rural Area (혁신전파 유형별 특징 및 강약점 분석)
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- Journal of Agricultural Extension & Community Development
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- v.16 no.1
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- pp.201-235
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- 2009
This study analyzed the demographic characteristics, strengths and weaknesses related to information acquisition of local innovation diffusion types. This study use ordered probit model to find strengths and weaknesses of innovation diffusion type in rural area. The individual characteristics of 'formal extension type', 'situational reaction diffusion type', 'agriculturist connection type', and 'systematic approach type', all differentiated according to innovation diffusion type, were analyzed. Following Choi & Choe(2008), immediacy, accessibility, referability, applicability, and satisfaction were the highest in the situational reaction diffusion type, systematic approach type, formal extension type, and farmers connection type, in the order. And there existed organic contexts among individual characteristics. So this study tried to analyze strengths and weaknesses of innovation diffusion type with a focus on immediacy, which emerged as the most important variable in the process of interpreting innovation diffusion. And the strengths and weaknesses of each innovation diffusion type were presented.
Diffusion of innovation is the process in which an innovation is communicated through certain channels over time among the members of a social system. The literatures have emphasized the importance of interpersonal network influences on individuals in convincing them to adopt innovations and thereby promoting its diffusion. In particular, the behavior of opinion leaders who lead in influencing others' opinion is important in determining the rate of adoption of innovation in a system. Centrality has been recognized as a good indicator that quantifies a node's influences on others in a given network. However, recent studies have questioned its relevance on various different types of diffusion processes. In this regard, this study aims at examining the effect of a node exhibiting high centrality on expediting diffusion of innovations. In particular, we considered the situation where two innovations compete with each other to be adopted by potential adopters who are personally connected with each other. In order to analyze this competitive diffusion process, we developed a simulation model and conducted regression analyses on the outcomes of the simulations performed. The results suggest that the effect of a node with high centrality can be substantially reduced depending upon the type of a network structure or the adoption thresholds of potential adopters in a network.
Object-orientation has been proposed as a promising software process innovation to improve software productivity and quality. It has not been understood clearly, however, what factors influences the diffusion of object-oriented technology in organizations. A research model was formulated and hypotheses were generated based on the literature of information technology implementation and software process innovation. To test the research hypotheses, a questionnaire survey was conducted. The results based on 121 responses from Korean companies revealed that project characteristics, use of external experts, and number of development projects are significantly related to the diffusion of object-oriented analysis and design and object-oriented programming. Innovation champion is positively related to the diffusion of object-oriented analysis and design, whereas it is not related to the diffusion of object-oriented programming language. Only project complexity was significantly related to the diffusion of visual programming language. On the other hand, organizational size was not significantly related to any object-oriented technology in this study.
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.