Earticle

본 연구는 신제품 수용 시 소비자의 개인 내적요인인 혁신 저항성과 과시소비 성향의 정도에 따라 심적 시뮬레이션 효과(과정 및 결과 시뮬레이션)가 어떻게 차별적으로 작용하는지 연 구하였다. 그 결과 첫째, 혁신 저항성이 낮아 신제품 수용에 거부감이 약한 집단은 두 시뮬레이션 간 수용의도와 제품태도에서 차이가 없었지만 혁신 저항성이 높은 집단에서는 결과 시뮬레이션이 과정 시뮬레이션보다 수용의도와 제품태도 모두 긍정적인 결과를 초래하는 것으로 나타났다. 또한 혁신 저항성과 시뮬레이션 간의 이원 분산분석(2Way-ANOVA)을 통한 상호작용 분석 결과 역시 모두 유 의미 한 것으로 나타났다. 둘째, 과시소비 성향이 높은 집단에서는 시뮬레이션 간 수용의도와 제품 태도에서 차이가 없는 것으로 나타났으나, 과시소비 성향이 낮은 집단에서는 결과 시뮬레이션이 과 정 시뮬레이션보다 수용의도와 제품태도 모두 긍정적인 결과를 유도하는 것으로 나타났다. 하지만 과시 소비성향과 시뮬레이션간의 이원분산분석에서 제품 태도에는 상호작용이 유의미한 것으로 나 타났으나 수용의도에는 상호작용이 미치는 영향이 나타나지 않았다. 이상의 결과를 토대로 연구의 제한점과 후속연구의 방향을 제안하였다.

This study has explored how the mental simulation effects operate in intention of a new product adoption and in the attitude toward the new product according to the internal personal factors of consumers such as innovation resistance and conspicuous consumption when they consider an adoption of a new product. The results of the research demonstrate, firstly, that while there was no difference in the intention of adoption and the attitude toward the new product between the two simulations(process vs outcome) in the group which had little resistance to adopt a new product with a low level of innovation resistance, the group which had a higher level of innovation resistance had positive intention of adoption of new and product attitude as well as in the outcome simulation than in the process simulation. In addition, the 2-Way ANOVA of the innovation resistance and the simulations showed that the interaction was also statistically meaningful. Secondly, in the case of conspicuous consumption, there was no difference in the intention of adoption and the attitude toward the new product between the simulations in the group with a high level of conspicuous consumption, but outcome simulation was more positive in both the intentions of adoption and new product attitude in the group with a lower level of conspicuous consumption. Although the 2-Way ANOVA of the conspicuous consumption and simulation for attitude toward the new product showed that the interaction was significant, however, the interaction effects for the intention of adoption of new product was not meaningful. Based on the findings, the significance and limitations of this study and directions for future studies are discussed and proposed.

The purpose of this study was to identify the effects of nursing simulation-based practice education on learning outcome and teaching experience in nursing students. Pretest-posttest design with nonequivalent control group was utilized to analyze the effects of nursing simulation-based practice education. The subjects were 96 students of a nursing college. All subjects participated in 6 week. The data were analyzed by the SPSS win 17.0 program. The results were as follows; There were statistically significant differences in learning outcome and teaching experience effects of nursing simulation-based practice education in nursing students. In conclusion, we required nursing simulation-based practice education and small group discussion analysis of factors are associated with goal-setting skills and self-presentation skills, goal setting skills. We required nursing simulation-based practice education training to strengthen the ability of self-directed learning program utilizing the repeated study.

과학기술의 발전으로 스포츠 분야에서도 다양한 매체의 방대한 데이터가 생산되고 있으며 이 데이터 속에서 유의미한 정보를 도출하기 위해 통계적 방법을 적용하는 것은 필수적이다. 본 연구는 2023-2024 여자 프로 배구팀의 실제 경기 문자중계 데이터를 기반으로 몬테카를로 시뮬레이션을 수행하여 배구 경기 결과를 예측하고자 하였다. 문자중계 데이터를 기반으로 시뮬레이션에 필요한 변수들을 생성하고 10,000회 반복을 통한 몬테카를로 시뮬레이션을 통해 승패 예측을 시도한 결과 실제 경기 결과를 상당히 정확하게 모의함을 확인하였다. 특히, 한 팀이 압도적인 경기력을 보이는 경우, 세트 스코어의 예측 정확도가 높게 나타났으며 시뮬레이션 결과를 활용하여 맞춤형 전략 수립도 가능함을 보였다. 다만, 총 득점이 많음에도 3-2로 패배하는 경우와 같은 특수한 상황에서는 승패 예측의 정확도가 다소 낮아지는 한계점이 관찰되었으며, 향후 경기 중 발생하는 다양한 상황과 변수들 간의 복잡한 상호작용을 더욱 정교하게 모델링하기 위해서는 기존에 정량화하기 어려웠던 정성적 요인들을 객관적인 지표로 변환하여 모델에 통합할 필요가 있다.

With advancements in science and technology, a vast amount of data from various media is being generated in the field of sports. Applying statistical methods to extract meaningful information from this data has become essential. This study aimed to predict volleyball match outcomes by performing Monte Carlo simulations based on live text commentary data from the 2023-2024 women's professional volleyball season. By generating the necessary variables for the simulation from the text commentary data and conducting 10,000 iterations of Monte Carlo simulations, the study confirmed that the simulations accurately mirrored actual match outcomes. In particular, when one team demonstrated overwhelming performance, the accuracy of set score predictions was notably high, and the simulation results demonstrated the potential for developing customized strategies. However, limitations were observed in predicting outcomes in specific scenarios, such as when a team with a high total score loses 3-2. To address these limitations, future work should focus on more precisely modeling the complex interactions between various situational and variable factors by converting qualitative factors, which have been challenging to quantify, into objective indicators for integration into the model.