• Journal of the Korean Society of Clothing and Textiles
• /
• v.40 no.1
• /
• pp.131-147
• /
• 2016

This study investigated the relationship between fashion behavior, impression management behavior, and career success. A conceptual model and hypotheses were established based on theoretical linkages between the constructs. Thereafter, empirical data were collected using a set of questionnaires. For this reason, the sample was taken from 720 office workers' who worked at 14's Korea Enterprise, 697 of which was used for an empirical analysis (sample: men over 30 years of age and more than three years continuous service). This study conducted an exploratory factor analysis and confirmatory factor analysis for the validity test. Cronbach's alpha test is used for the reliability test. Moreover, PLS structural equation modeling (SEM) was employed to test hypothesized relationships in the conceptual model (SPSS 20.0 window/Smart PLS 3.0). This study shows that the proposed model is reasonably fit to the actual data. The following results were obtained from the analyses. First, fashion behavior and impression management behavior is positively related to career success. The result shows that economics of the fashion behaviors sub-types were statistically more significant to influence career success. The self-focused of the impression management behavior sub-types were more than statistically significant to influence career success. This finding has great implications to understand self-management behavior and the career success of male office workers.

• Journal of Digital Convergence
• /
• v.20 no.1
• /
• pp.129-139
• /
• 2022

This study aims to identify which factors affect successful big data system construction, identify the relationship between the factors, and identify the success model and success factors necessary for public institutions to build big data systems. Therefore, the preceding and related studies related to this study were reviewed, and success factors for the establishment of a big data system were derived based on this. As a research method, a survey was conducted on users of institutions that have established or planned to build a big data system, and a structural equation (AMOS) was conducted to verify the impact relationship between success factors. As a result of the analysis, organizational support factors, development support factors, user support factors, information quality, service quality, system quality, use, and net benefit were derived as success factors for building big data systems, and a success model was presented. This can be seen as significant and academic contributions in that it is the first study of the success model for building an information system reflecting big data characteristics, and it is expected that this study will be used as basic data for building a big data system in public institutions in the future.

• The Journal of Korea Robotics Society
• /
• v.15 no.4
• /
• pp.398-403
• /
• 2020

Robot's throwing control is difficult to accurately calculate because of air resistance and rotational inertia, etc. This complexity can be solved by using machine learning. Reinforcement learning using reward function puts limit on adapting to new environment for robots. Therefore, this paper applied deep reinforcement learning using neural network without reward function. Throwing is evaluated as a success or failure. AI network learns by taking the target position and control policy as input and yielding the evaluation as output. Then, the task is carried out by predicting the success probability according to the target location and control policy and searching the policy with the highest probability. Repeating this task can result in performance improvements as data accumulates. And this model can even predict tasks that were not previously attempted which means it is an universally applicable learning model for any new environment. According to the data results from 520 experiments, this learning model guarantees 75% success rate.

• The Journal of Information Systems
• /
• v.18 no.2
• /
• pp.127-150
• /
• 2009

Although many employees in the logistics/small package express companies are using mobile information systems. there is little research on the individual impacts of adopting mobile information systems in the distribution area. Therefore, this study attempts to develop the research model to evaluate individual impacts on using mobile information systems which are frequently utilized in logistics and small package express companies. In order to propose the research model, we attempt to incorporate technology acceptance model and IS success model to evaluate individual impacts on using mobile information systems. To verify the research model, we collected 225 data from staffs who have mobile IT system in distribution and logistics area. We also verified the validity and reliability by using SEM(structural equation modeling). As a results, we found that system use, cognitive judgement and attitude can be the key variables to improve individual impacts by using mobile information system. We further found that perceived usefulness can be ere of the Imp factors to improve the individual impacts. Based on out findings, we can understand that this research model can provide a deeper understanding of individual impacts of mobile information systems.

• Journal of Korea Multimedia Society
• /
• v.21 no.2
• /
• pp.281-288
• /
• 2018

Crowdfunding has seen an enormous rise, becoming a new alternative funding source for emerging startup companies in recent years. Despite the huge success of crowdfunding, it has been reported that only around 40% of crowdfunding campaigns successfully raise the desired goal amount. The purpose of this study is to investigate key factors influencing successful fundraising on crowdfunding platforms. To this end, we mainly focus on contents of project campaigns, particularly their linguistic cues as well as multiple features extracted from project information and multimedia contents. We reveal which of these features are useful for predicting success of crowdfunding campaigns, and then build a predictive model based on those selected features. Our experimental results demonstrate that the built model predicts the success or failure of a crowdfunding campaign with 86.15% accuracy.

• The Journal of the Korea Contents Association
• /
• v.22 no.6
• /
• pp.680-691
• /
• 2022

Virtual farm is a kind of virtual reality for education and training, which realizes a change in attitude toward farming and aims for economic performance through revisiting the virtual farm. With the recent introduction of P2E-type virtual reality, a way to connect virtual farming experiences with practical benefits is being considered. However, few studies have been conducted on the factors that influence the success of virtual farms. Hence, the purpose of this study is to examine whether the quality of virtual farm contents and system quality affect user satisfaction with virtual farm experience based on the DeLone & McLean's IS Success Model. In addition, we will examine whether satisfaction with the virtual farm significantly contributes to the change in attitude toward farming. In addition, we demonstrate whether digital incentives contribute to the activation of P2E-type virtual farms.

• Journal of Digital Convergence
• /
• v.12 no.3
• /
• pp.127-140
• /
• 2014

This study is performed to measure a performance of IMS using Delone & McLean's Information Success Model as a practical analysis for IMS implementation and their effects. For this, I reviewed the pre-research literatures to attain the measurement factors for IMS implementation and information system success model. For inspecting the hypotheses, answered the questionaries to the IMS managers. The results are as follows: the first, to improve the user's will, they have to focus on the service quality. The second, to improve the user's satisfaction, focus on the system quality. Finally, which affect on the performance is user's will rather than satisfaction.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2010.04a
• /
• pp.435-439
• /
• 2010

The purpose of this paper is to design a new management model based on the grill-formed product charscteristic area(PCA) which specify the position of products classified by the level of market and technology. This product characteristic area is composed of 9 cells and the cases sorted by market and technology are analyzed by each cell. Conclusion of this study based on many significant results gained by the various multi-variate analysis is summarized as follows; First, it can be noted that success/failure factor and progress stages are different by each cell. Second, a new management model is designed by combining the Motive Resource, Success/Failure(S/F) factors, and Progress Stages of New Product Development. Third, success products featured a balance between marketing oriented and technically oriented activities. A new attemp that combine S/F factors with development stages by each product cell will be of great usefulness for further study.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.1
• /
• pp.123-128
• /
• 2010

To increase the chance of the success of project, it is necessary to identify the important factors influencing the performance of project. Cognitive map has been used for analysing by investigating causal links among relevant factors. A fuzzy cognitive map (FCM) is an extension of a cognitive map with the additional capability of representing feedback through weighted causal links. Project performance is influenced by several factors such as input resources, possibility of achievement, concern of others and so on. The object of this paper is to develop the project success model of enterprise using a fuzzy cognitive map approach to investigate the degree of causal relationship between project performance and these factors.

• Health Policy and Management
• /
• v.10 no.2
• /
• pp.78-102
• /
• 2000

Factors influencing the success or failure of information systems9IS) have been discussed in many literes. However, little thertical development or empirical research has examined effectiveness of information systems in health center. This study evaluates several model that contribute to IS success in bealth center. In this study, we propose a process model that exhibits several variables influence one after another. These can be classified into six different dimensions. These inclube system aspect, invidual effect. The system aspect is classified by system quality, information quality and service quality. On individual and organizational aspect, this study uses computer self-efficacy and support of top management. The results of this study are as follows: according to multiple regression analysis of user satisfaction, information quality and support of top management are statistically significant influence on user satisfaction. System quality and service quality are a partially significant influence on user satisfaction. Hypothesis 5, proposing that computer self-efficacy would relate positively to user satisfaction, ws not supported by the questionnaire results. Based on these results, information quality and support of top management are very important variables for IS success.