• 한국정보시스템학회지:정보시스템연구
• /
• 제27권1호
• /
• pp.133-151
• /
• 2018

Purpose Global fintech industry is proliferating. Although domestic investment in fintech service is also increasing fast, user acceptance of fintech payment service seems slower than expected. Previous fintech literature mainly focuses on overall characteristics and technical aspects of fintech including security issues and explores factors affecting the service adoption. This study aims to examine crucial factors affecting user's resistance intention to fintech payment service adoption. The research model was formulated based on innovation diffusion theory and status quo bias theory and validated empirically. Design/methodology/approach The proposed research model was empirically validated with 149 responses from college students who have used fintech payment service. The component-based SEM was employed for data analysis. Findings The significant findings are as follow. First, compatibility has significant negative effect and complexity, and perceived risk has a positive effect on user resistance. Second, institutional trust does not show a significant effect on user resistance but has an indirect effect through the mediation of trust in service provider. Finally, trust in service provider shows the significant negative effect on user resistance.

• 한국정보과학회논문지:시스템및이론
• /
• 제32권11_12호
• /
• pp.675-681
• /
• 2005

노이즈 함수는 난수의 추가를 통해 실제 자연현상에 대한 애니메이션을 더욱 더 실감나게 하는 방법으로 쓰여 왔다. 본 연구에서는 노이즈의 통계적 특징은 보존하면서, 사용자가 원하는 제약에 맞는 결과 값을 산출하는 방법을 제시한다. 이상적 형태의 통계 값과, 실제 노이즈 함수의 편향치의 통계 값의 차이를 최소화 하는 최적화 기법을 통해 노이즈의 성질을 유지하면서 손쉽게 제어를 할 수 있는 방법을 제안하고자 한다. 이 방법을 통해 노이즈가 적용된 애니메이션이나 모양에 대한 세부적인 제어가 가능하다.

• 한국IT서비스학회지
• /
• 제21권4호
• /
• pp.1-26
• /
• 2022

Recently, the number of cases of purchasing food online has been increased, especially in the open market. Therefore, we examined the characteristics of status quo bias and switching costs in the open market. Also, in this study, the causal relationship between the characteristics of status quo bias and switching costs, switching costs and switching intention in the open market was investigated. The analysis result consists of four parts as follows. First, in the open market, rational decision making, which belongs to the characteristics of status quo bias, was found to have a positive (+) effect on time switching cost among switching costs, but did not have a positive (+) effect on economic and psychological switching cost. Second, cognitive misperceptions was consistent with the assumption that it have a positive (+) effect on all of the economic, time, and psychological switching cost, which are switching costs in the open market. Third, psychological commitment was found to have a positive (+) effect on economic and time switching cost among switching costs, but did not have a positive (+) effect on psychological switching cost. Fourth, psychological switching cost, which belongs to switching costs in the open market, was found to have a negative (-) effect like the hypothesis set in switching intention. However, it was found that economic and time switching cost did not have a negative (-) effect on switching intention. This study subdivided the switching costs into three dimensions and compared the degree of influence on the switching intention, and the degree of influence was different for each dimension. Therefore, it was found that when switching from the existing open market to the new open market, it is not possible to simply judge that the switching costs directly has a negative (-) effect on the switching intention or does not.

• 대한공간정보학회지
• /
• 제23권4호
• /
• pp.43-48
• /
• 2015

본 논문은 DGNSS(Differential GNSS) 위치정확도 향상을 위한 PRC(Pseudo-Range Correction) 보정정보 모델링에 관한 연구내용이다. PRC는 DGNSS 기법을 이용하여 측위정확도를 향상시키기 위해 사용되는 보정정보로써 사용자가 통신망을 통해 수신한 뒤 사용된다. 그러나 일시적인 통신두절이나 신호간섭 등으로 인해 위치정확도가 급격히 저하되는 일이 발생한다. 그래서 본 논문에서는 이러한 현상을 방지하기 위해 PRC 보정정보를 다항식 곡선접합 방정식을 이용하여 모델링하고 그 정확도를 평가하였다. 모델링 매개변수를 이용하여 계산한 PRC 추정값과 실제 기준국 수신기에서 생산되는 관측값간의 차이를 계산한 결과 GPS의 경우에는 평균 0.1m, RMSE는 1.3m로 나타났고 대부분의 위성들이 ${\pm}1.0m$ 이내의 편향오차와 3.0m 이내의 RMSE를 보였다. GLONASS의 경우에는 평균 0.2m이고 대부분 ${\pm}2.0m$ 이내에 분포하였다. RMSE는 2.6m로 나타났고 다수의 위성들이 3.0m 이내에 분포하였다. 이런 결과는 모델링을 통해 산출한 추정값이 사용자의 위치정확도를 유지하는데 유효하게 사용될 수 있음을 보였다. 그러나 고도각이 낮은 영역에서 두 값의 차이가 크게 나타나 이에 대한 연구를 추가적으로 수행할 필요성이 있다.