• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.160-166
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• 2021

Due to rapid environmental-change pharmaceutical industry, sales strategy for sales survival of pharmaceutical company is necessary. In accordance with the rapid development of medicine and advancement of efforts to secure the market, competition among pharmaceutical companies make an effort to achieve their goals. However, due to various negative influence of inside and outside, this field is getting a difficult occupation. Even when securing and training new employees with quite a bit of expense and time, the rate of surviving employees over 1 year is decreasing. For this, the researcher suggested major research result through actual investigation by utilizing survey technique, and a plan to enhance pharmaceutical company salespersons' core competence and raise sales achievement. As the research result, company culture strongly influences salespersons' sales ability. We defined the formation of organizational culture, which influences communication culture where smooth communication is made in the company, also, definite and exact evaluation in promoting work, and trust formation between upper and lower organization, is important, which should be reflected in the company field.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.207-213
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• 2021

Informatization and digital transformation across industries are big trends in the world. However, although a few food groups are investing in informatization on a pilot basis, informatization is still delayed in related industries, such as distribution, logistics, etc. Therefore, consumers often are not able to have easy access to detailed information about products. In this paper, to improve these problems, we propose a fresh food logistics solution that adopts Proof of Nonce (PoN) consensus algorithm with Internet of Thing (IoT) technology. The recently developed PoN algorithm dramatically reduces a time for generating a block and is suitable for a platform that collects and services real-time information. We expect to improve their trust in the platform by preventing forgery/falsification of information recorded in real time through this paper.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.142-151
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• 2022

In this paper, a model combined with explanatory artificial intelligence (xAI) models was presented to secure the reliability of machine learning-based sentiment analysis and prediction. The applicability of the proposed model was tested and described using the IMDB dataset. This approach has an advantage in that it can explain how the data affects the prediction results of the model from various perspectives. In various applications of sentiment analysis such as recommendation system, emotion analysis through facial expression recognition, and opinion analysis, it is possible to gain trust from users of the system by presenting more specific and evidence-based analysis results to users.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.177-184
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• 2022

The purpose of this study is to provide implications by conducting research on brand benefits for skiwear brand customers. For this purpose, a structural equation model was established and empirical research was conducted by selecting brand convenience as a hygiene variable and brand emotion, brand satisfaction, and repurchase intention as endogenous variables. In order to analyze the general characteristics of the subjects, frequency analysis was conducted using SPSS 25 and Cronbach's alpha analysis was conducted using the same statistical program. Confirmatory factor analysis and path analysis were conducted using AMOS 21. In addition, the benefits of skiwear brand, which is an independent variable, were composed of two sub-dimensions, and psychological benefits rather than functional benefits were found to have a stronger impact on brand emotion, suggesting practical implications.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1187-1188
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• 2023

인공지능·데이터·클라우드 등 혁신적인 기술로 새로운 사회 구조를 만드는 시대가 도래하면서 현 정부 핵심 국정과제 중 하나로 디지털플랫폼정부(DPG) 구현이 언급되었다. DPG는 수많은 공공 데이터를 관리하고 있으며, 중요·민감 데이터의 안전성을 유지하기 위한 신보안체계로서 '제로트러스트'를 고려하고 있다. 하지만 DPG에 제로트러스트 보안 개념을 적용하고자 할 경우 기업이나 정부 기관 대상의 제로트러스트와 달리 DPG는 참여 주체(정부, 민간 기업, 일반 국민 등)가 다양하고 민간 클라우드 활용을 지향하는 만큼, 이러한 특징을 고려하여 아키텍처를 설계해야 한다. 따라서, 본 논문에서는 DPG에 제로트러스트 보안 아키텍처를 도입할 경우, 고려해야 할 점을 제시한다.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.154-163
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• 2023

With the rapid development of AI technology, ChatGPT and other AI content creation tools are becoming common, and users are becoming curious and adopting them. These tools, unlike search engines, generate results based on user prompts, which puts them at risk of inaccuracy or plagiarism. This allows unethical users to create inappropriate content and poses greater educational and corporate data security concerns. AI content detection is needed and AI-generated text needs to be identified to address misinformation and trust issues. Along with the positive use of AI tools, monitoring and regulation of their ethical use is essential. When detecting content created by AI with an AI content detection tool, it can be used efficiently by using the appropriate tool depending on the usage environment and purpose. In this paper, we collect data on AI content detection tools and compare and analyze the functions and characteristics of AI content detection tools to help meet these needs.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.129-139
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• 2024

In digital marketing, the strategic use of emojis in social media advertising, particularly on the Xiaohongshu app, significantly influences consumer acceptance and purchase behavior. This study examines the impact of emoji-laden advertisements and the role of brand metaphorical warmth on consumer perceptions. Employing a tailored questionnaire, the research explores how emojis affect brand advertisement reception, filling a gap in empirical research on emoji advertising effectiveness. Findings indicate that emojis, when used judiciously, enhance consumer acceptance and contribute to a positive brand perception. However, excessive use may undermine trust. Brand metaphorical warmth emerges as a crucial factor, suggesting that emojis can effectively convey warmth, fostering a deeper emotional connection with consumers. These insights offer practical implications for refining social media marketing strategies, advocating for a balanced approach to emoji usage in advertisements to optimize engagement and influence consumer behavior.

• Journal of Distribution Science
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• v.18 no.1
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• pp.107-121
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• 2020

Purpose: Shared mobility services are the most notable in the shared economy; however, they have yet to be activated in Korea due to various regulations and conflicts amongst stakeholders. Nevertheless, shared mobility has become an irresistible trend of the times, as it can cause a great deal of economic and environmental benefits. In this vein, the purpose of this study is to contribute to the revitalization of shared mobility services in Korea and to provide service providers with implications for developing consumer-oriented marketing strategies. Research design, data and methodology: Based on the reasons that the users do not use shared mobility service, the factors influencing the behaviors of shared mobility users are structured and analyzed in a reliable, technical and procedural manner. To this end, the theory of reasoned action (TRA) of Ajzen and Fisbbein, the initial trust model (ITM), task technology fit (TTF) and switching cost (SC) are adopted. A total of 202 questionnaires were collected from the respondents who were aware of shared mobility. Then statistical processing of the collected data used SmartPLS(v.3.2.8), a PLS-SEM (Partial Least Squares Structural Equation Modeling) analysis program. The steps of the analysis are as follows. First, a PLS-Algorithm analysis was performed to evaluate the measurement model, and a Bootstraping and Blindfolding analysis was performed to evaluate the structural model and verify the hypotheses. Second, a multi-group analysis (PLS-MGA) was conducted to further analyze the differences depending on whether or not users experienced shared mobility service. Results: The results showed that initial trusts model (ITM) and task technology fit (TTF) have positive effects on users' behaviors through the mediation of the intention to use. As opposed to the assumption, switching costs did not have negative moderating effects in relation to the intention to use and users' behaviors. The influence of IT self-efficacy was significant, depending on the prior experience to use shared mobility services. Conclusions: This study will contribute to the revitalization of domestic shared mobility services and the formulation of service providers' marketing strategies. In future studies, there is a need to explore, reconstruct, and validate factors other than the impact factors of the shared mobility services used in this research model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1087-1101
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• 2013

Most people are connected to Social Network Services (SNS) through smart devices. Social Network Services are tools that transport information fast and easily. It does not care where he or she comes from. A lot of information circulates and is shared on Social Network Services. but Social Network Services faults are magnified and becoming a serious issue. For instance, malicious users generate multiple IDs easily on Facebook and he can use personal information of others on purpose, because most people tend to undoubtedly accept friend requests. In this paper, we have specified research scope to Facebook, which is one of most popular Social Network Services in the world. We propose a way of minimizing the number of malicious actions on Facebook from malignant users and malicious bots by setting criteria and applying reputation system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.17-25
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• 2018

Recently, with the development of ICT technology and the rapid spread of smart devices, a huge amount of information is being generated. The recommendation system has helped the informant to judge the information from the information overload, and it has become a solution for the information provider to increase the profit of the company and the publicity effect of the company. Recommendation systems can be implemented in various approaches, but social information is presented as a way to improve performance. However, no research has been done to utilize trust cluster information among users in the recommendation system. In this paper, we propose a method to improve the performance of the recommendation system by using the influence between the intra-cluster objects and the information between the trustor-trustee in the cluster generated in the online review. Experiments using the proposed method and real data have confirmed that the prediction accuracy is improved than the existing methods.