• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.19-37
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• 2024

Recently, companies have adopted various types of smartwork. In this study, various factors were examined to identify the main factors that can increase smartwork satisfaction, individual performance, and organizational performance. As the main variables, individual adaptability, knowledge level for smartwork, IT infrastructure level, smartwork organizational culture, and investment level in IT were selected. As a result, first, it was found that individual adaptability did not affect smartwork satisfaction and corporate performance, unlike previous studies. Second, it was found that the knowledge level for smartwork affects individual performance and organizational performance mediating smartwork satisfaction. Third, the main path of 'investment level in IT → IT infrastructure level → smartwork organizational culture → organizational performance' was found. Therefore, companies need to raise the level of knowledge for smartwork among members of the organization and educate that smartwork contributes to improving the quality of life of members. In addition, efforts should be made to build an organizational culture suitable for smartwork through IT investment and establishment of IT infrastructure.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.1
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• pp.57-73
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• 2021

The purpose of this study is to analyze the diffusion period and productivity of smartwork in an organization. Firms are increasingly interested in smartwork for non contact work and working from home because of the corona 19. The smartwork is a new technology that changes face-to-face work in an organization. It helps the work of individuals and organizations regardless of time and place. The theoretical background describes the complexity, system thinking, diffusion theory, smart work, organizational resistance, and productivity. This study analyzes the diffusion period and productivity of smart work through business simulation techniques. A simulation study progresses four stages. There are problem definition, hypothesis establishment and causal loop diagram, model construction and verification, and policy evaluation. The simulation models contain an individual's resistance variables organizational investment and leadership variables related to the operation of smartwork. The organizational investment variables include organizational culture, legal system, implement systems and technology investment. The individual resistance variables include cognitive, attitude, structure and technological resistance. The leadership includes leadership interest variables and performance linkage variables. The simulation executed the changes of a people number adopting smart work and the organizational productivity monthly. As a result of the simulation, many organization members have accepted the smart work innovation after 20 months. The organizational productivity through smart work showed very high value after 16 months. In scenario analysis, the individuals' awareness and attitude resistance showed very important variables to productivity and a personal change of smart work adoption. Meanwhile, The organizational investment showed that the high driving-force increased not productivity and the low driving-force showed decreased low productivity. Also, leadership variables showed a powerful driver for changing smart work productivity. The implication of the study has suggested extending complexity, diffusion theory and organization resistance theory based on simulation methods.