• Journal of Digital Convergence
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• v.9 no.4
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• pp.201-211
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• 2011

As the spacetime restriction free business becomes possible in compliance with the wide spread of social media through rapid propagation of smart phones and remote working etc., the positive activity for successful smart work implementation by major countries and many enterprises are being deployed. Korea which falled behind other advanced countries for adoption of smartwork needs to make double efforts in the forthcoming smartwork business area to be a continuous leading country as it used to be in the past IT area. Compare with traditional smartwork 1.0, future smartwork 2.0 is more creative, innovative and human/nature friendly. Smartwork 2.0 is the way of working to maximize the creativity by involving outside cooperators' capability and conforming to human sensitivity and emotion. This study suggests the management models proper to the future smartwork environment. This study will review the existing enterprises, government operation and rethink about the efficient management models in the rapidly changing smart work environment.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.49-66
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• 2018

This research explores a value chain structure of VR-AR media including user's perception, uses, and evaluation. The purpose of this research focused on factor analysis and the relationship among user's VR-AR adoption motivations and utilities. This research explores correlation between personal value and using motivation. This study was to identify the value structure of respondent on VR-AR usages based on means-end chain theory. The research used structured APT laddering questions and 251 data was analysed. Through such analysis, category difference by stage and relationship difference were identified and hierarchical value map was compared. There are four different value ladders: first is attributes, functional consequences, psychological consequences, and final value. This study is based on the analysis of the value chain structure factors that affect VR and AR use behavior (attributes, functional benefits, psychological benefits, use value), 'Hierarchical Value Map' between users' The purpose of the model is to construct a model. For this, 'means-end chain theory' was applied to measure the causal relationship between personal value and VR related use behavior. In order to solve this research problem, 135 people were analyzed through the structured questionnaire using the AR and VR content fitness measure and the second APT laddering, and the use of VR-AR : 1) Functional benefits; 2) Psychological benefits; 3) Means to reach value, 4) Objective value chain structure was identified. The results show that VR users tried to smooth the social life through the new virtual reality audiovisual element, the newness of experience, fun, and pleasure through the departure of reality, vividness of experience, and leading fashion. The AR fitness was a game and a new program, and the value of interacting with other people and the value of 'periwinkle' played an important role through the vividness and peripheral interaction of AR, It was an important choice. The important basic values of users' VR and AR selection were correlated with psychological attributes of interaction with others, achievement, happiness and favorable values.

• 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