Survey of Geomorphological Resources of 'Daegu Innovation Town' Development Plan Area (대구 혁신도시 개발예정지의 지형자원 조사)
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- Journal of the Korean association of regional geographers
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- v.14 no.2
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- pp.173-188
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- 2008
In order to make comparative analysis of geomorphological changes caused by urban development, I surveyed the distribution of geomorphological resources of 'Daegu Innovation Town' development plan area. The results are as follow: (1) At the front of small valleys of back-mountains are formed small alluvial fans, and at the side of small valleys are distributed hills connected with back-mountains. (2) As small valley erode laterally hills, vertical bluffs and planner bedrock riverbed are formed, and in some riverbed are appeared mud cracks and ripple marks. (3) The depth of valley in alluvial fan of 'Sinseo District' is 7m. In Sinseocheon valley dissecting alluvial fan, fluvial terraces 2m high above riverbed are distributed. Those terraces were formed while alluvial fan was dissected after last glacial period.
COVID-19 has spread across the world in the last two years, confining people to their homes and shutting down businesses and markets. The world is currently experiencing a catastrophic economic and social crisis. To benefit people and to protect them, industries invented new products. These products were made by small and medium-sized businesses across the globe. In South Asia, there was also a rigorous lockdown, people were laid off, and SMEs adopted E-commerce to assist clients and customers. Therefore, the study aims to analyze the impact of the COVID-19 pandemic on E-commerce adoption through open innovation strategies in South Asian countries. 500 respondents were selected through an online questionnaire to collect data from different countries of South Asia. The prominent countries are; India, Pakistan, and Bangladesh. The results of the study show that perceived compatibility and complexity have a positive influence on E-commerce adoption. In normal circumstances, however, the open innovation model is feasible. Knowledge and experience sharing and management attitude have a moderate impact on E-commerce adoption. These results are beneficial for researchers and SME managers in South Asia to overcome the challenges of the COVID-19 pandemic and increase the number of skilled people employed. This study suggests that SMEs should hire skilled workers to upgrade their systems.
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.