• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.523-531
• /
• 2021

This study aims to examine the role of social media marketing on the performance of micro-, small and medium-sized enterprises (MSMEs) during the COVID-19 pandemic. This research method uses a quantitative approach and the analytical tool used is Structural Equation Modeling (SEM) based on Partial Least Square. The sampling technique used purposive sampling and the sample in this study was MSMEs who use social media for marketing. The social media used are Facebook, Instagram, and Whatsapp. The number of samples in this study was 254 MSMEs. Data collection used online questionnaires. The research findings show that the use of social media marketing is influenced by compatibility, perceived usefulness, and perceived ease-of-use. The results of this study indicate that the use of social media for marketing has a positive effect on the performance of MSMEs, especially in increasing sales, customer relationships, productivity, and creativity. This means that the better the management of social media for marketing, the better the performance of MSMEs will be. The theoretical contribution to this research is built on the TAM and UTAUT theories and their impact on social media marketing on MSMEs in developing countries that are living through the COVID-19 pandemic.

• Journal of Korea Society of Industrial Information Systems
• /
• v.12 no.5
• /
• pp.173-182
• /
• 2007

e-Learning can be seen as not only one of Internet based information systems which can provide education services, but also one of teaching-learning methods which can implement self-directed learning. This paper tests factors affecting the e-Learning performance based on information systems success model and self-efficacy theory using a field study. Questionnaires are collected from 216 students who are enrolling a e-learning class using online survey. The results are following: first, the service quality and self-efficacy are significant predictors of use intention, but system quality and information quality are not. second, the system quality, information quality, service quality and self-efficacy are significant predictors of user satisfaction. Third, use intention and user satisfaction are found to be a strong predictor of the learning performance.

• International Journal of Knowledge Content Development & Technology
• /
• v.11 no.3
• /
• pp.81-112
• /
• 2021

In this study, users' perceptions and concerns about digital information resources were investigated, focusing on impediments to the use of digital resources, to devise measures for improvement by identifying factors that hinder the use of digital information resources. To achieve the purpose of the study, the research identifies the inconvenien ce factors and establishes the user inconvenience list based on prior research and the current status survey. Based on the derived list, a survey was conducted on users of public libraries. Through this study, it was found that the use of digital information resources can be enhanced by improving the internal library system. Specifically, it refers to improving search performance and accessibility of digital data, providing one-stop services for digital information resources through the operation of an integrated data management system, conducting customized user education, and establishing a digital information resource preservation system, e.g. web archiving. Also, improving the external environment and system, such as contracting with more libraries for digitized data use agreements, strengthening support, unifying the names and classifications of digital information resources, and simplifying the procedure for using digital information resources, is of great importance.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.4
• /
• pp.17-24
• /
• 2016

In this paper, we propose a AH LSU(Advanced Hybrid QoS Routing Link State Update) Algorithm that improves the performance of Hybrid LSU(Hybrid QoS Link State State Update) Algorithm with statistical information of flow holding time in network. AH LSU algorithm has had both advantages of LSU message control in periodic QoS routing LSU algorithm and QoS routing performance in adaptive LSU algorithm. It has the mechanism that calculate LSU message transmission priority using the flow of statistical request bandwidth and available bandwidth and include MLMR(Meaningless LSU Message Removal) mechanism. MLMR mechanism can remove the meaningless LSU message generating repeatedly in short time. We have evaluated the performance of the MLMR mechanism, the proposed algorithm and the existing algorithms on MCI simulation network. We use the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.12
• /
• pp.171-178
• /
• 2017

Investigations into family-friendly company culture have been carried out for various companies and conglomerates. But there has never been such investigation for police organization, so this investigation is intended to see the effect on organizational commitment and job performance of the organization culture that makes use of family-friendly program for the police organization. To this end, how the internal factors of family-friendly organization culture affects organization commitment and job performance is empirically analyzed with structural equation modeling. And it is found that family-friendly program has significant effect on organizational life and welfare, and the welfare, in return, is found to have significant effect on job performance.

• Asia pacific journal of information systems
• /
• v.27 no.2
• /
• pp.126-138
• /
• 2017

The proliferation of items increased the difficulty of customers in finding the specific items they want to purchase. To solve this problem, companies adopted recommender systems, such as collaborative filtering systems, to provide personalization services. However, companies use only meaningful and essential data given the explosive growth of data. Some customers are concerned that their private information may be exposed because CF systems necessarily deal with personal information. Based on these concerns, we analyze the effects of the amount of information on recommendation performance. We assume that a customer could choose to provide overall information or partial information. Experimental results indicate that customers who provided overall information generally demonstrated high performance, but differences exist according to the characteristics of products. Our study can provide companies with insights concerning the efficient utilization of data.

• Fashion & Textile Research Journal
• /
• v.16 no.5
• /
• pp.800-810
• /
• 2014

In this study, the current status of product information of functional outdoor jackets in the hang-tags was investigated in perspective of consumer protection. Effectiveness and preferred alternatives to hang-tag information were also investigated. For the market survey, 1560 hang-tags from 676 functional outdoor jackets were investigated. For the effectiveness and preferred alternatives, 472 adults in their 20-60's were surveyed. The average number of hang-tags was 2.3 but 5.9% did not provide any product information. The contents included functional property of fabric; quality guarantee; brand introduction; product characteristics; instructions for care/usage; subsidiary material information, and they were different depending on end-use of jackets. Consumers strongly wanted explanations of the terms used in the hang-tag and could not accurately figure out the functions of the products from hang-tag information regardless of expression methods. The percentage of incorrect answer of 'figure/foreign language' method was extremely high. It is a noticeable feature of graph method that customers perceived that the graph was difficult to understand, but the percentage of correct answers was much higher than other methods, implying that graph method was possibly more useful at delivering accurate information to the customers who pursuit information. Customers strongly agreed to need of alternative methods and preferred an unified performance grade from selected functions based on the end-use of products. Customers also wanted to include the information of performance change after laundering. The results could provide practical insights to the consumers, companies, and the government to prepare proper guideline/policies for consumer protection.

• Journal of IKEEE
• /
• v.23 no.2
• /
• pp.395-402
• /
• 2019

In this paper, we implemented an Ultra-Wideband radar system using Stripmap Synthetic Apertrure Radar algorithm to recognize objects inside a box. Different window functions such as Hanning, Hamming, Kaiser, and Taylor functions to improve image recognition performance are applied and implemented to radar system. The Ultra-Wideband radar system with 3.1~4.8 GHz broadband and UWB antenna were implemented to recognize the conductor plate located inside 1m3 box. To obtain the image, we use the propagation data in the time domain according to the 1m movement distance and use the Range Doppler algorithm. The effect of different window functions to improve the recognition performance of the image are analyzed. From the compared results, we confirmed that the Kaiser window function can obtain a relatively good image.

• Journal of information and communication convergence engineering
• /
• v.20 no.2
• /
• pp.131-136
• /
• 2022

The recommendation system applied in museums has been widely adopted owing to its advanced technology. However, it is unclear which recommendation is suitable for indoor museum guidance. This study evaluated a recommender system based on social-filtering and statistical methods applied to actual museum databases. We evaluated both methods using two different datasets. Statistical methods use collective data, whereas social methods use individual data. The results showed that both methods could provide significantly better results than random methods. However, we found that the trip time length and the dataset's sizes affect the performance of both methods. The social-filtering method provides better performance for long trip periods and includes more complex calculations, whereas the statistical method provides better performance for short trip periods. The critical points are defined to indicate the trip time for which the performances of both methods are equal.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.3
• /
• pp.82-88
• /
• 2014

We study the effect of mesh reordering on Laplacian smoothing for parallel high performance computing systems. Specifically, we use the Reverse-Cuthill McKee algorithm to reorder meshes and use Laplacian Smoothing to improve the mesh quality on Nonuniform memory access architecture-based parallel high performance computing systems. First, we investigate the effect of using mesh reordering on Laplacian smoothing for a single core system and extend the idea to NUMA-based high performance computing systems.