• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.342-353
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• 2020

The purpose of this study is to identify priority factors for improving service quality of cosmetic stores in drug stores(DRS) and department stores(DES) and to provide basic data for improving service quality of cosmetic stores by analyzing the service quality based on the Kano model and the Potential Customer Satisfaction Improvement (PCSI) Index. As a result, most items of quality factors of cosmetic stores in both stores were evaluated as attractive quality factors. As a result of PCSI Index comparison, the quality factors of 'Reliability', 'Responsiveness', and 'Empathy' items for DRS and 'Empathy' and 'Reliability' items for DES had higher priority for improvement. That is, if these factors are improved, there is a high potential to improve customer satisfaction. Through this study, practical implications were provided by identifying service quality factor classification and priorities for customer satisfaction improvement of DRS and DES. This is expected to contribute to the guidelines for improving customer satisfaction in the future.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.45-51
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• 2021

In accordance with the rapid non-face-to-face environment and mobile first strategy, the explosive increase and creation of many structured/unstructured data every year demands new decision making and services using big data in all fields. However, there have been few reference cases of using the Hadoop Ecosystem, which uses the rapidly increasing big data every year to collect and load big data into a standard platform that can be applied in a practical environment, and then store and process well-established big data in a relational database. Therefore, in this study, after collecting unstructured data searched by keywords from social network services based on Hadoop 2.0 through three virtual machine servers in the Spring Framework environment, the collected unstructured data is loaded into Hadoop Distributed File System and HBase based on the loaded unstructured data, it was designed and implemented to store standardized big data in a relational database using a morpheme analyzer. In the future, research on clustering and classification and analysis using machine learning using Hive or Mahout for deep data analysis should be continued.

• International Area Studies Review
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• v.15 no.2
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• pp.225-245
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• 2011

This study investigates the effects of justice dimensions on negative emotion, consumer satisfaction after service recovery, repurchase intention and word-of-mouth intention in a context of service recovery. Behavioral intentions(repurchase intention and word-of-mouth intention) are critical to the discount store sellers' survival and success. The research model is an extension of previous studies, especially considering more recent developments in the service recovery literature. A survey using 458 customers in China was conducted, confirmatory factor analysis was conducted to test the validity of the measurement model, and AMOS analysis approach was used to gain important insights into how customer retention in the discount store business can be ensured. The results suggest that all three dimensions of justice had negative effects on negative emotion, had positive effects on satisfaction after service recovery. Negative emotion had negative effects on recovery satisfaction. Recovery satisfaction had positive effects on repurchase intention and word-of-mouth intention. Finally, this study suggests the implications of these findings and offers directions for future research.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.70-75
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• 2018

The mounted store on an aircraft shall be subjected to an ground separation test to verify that a safe separation has been made before it is actually installed to the aircraft. In this study, ground ejection test was conducted with dummy missile to verify the stability of the drop on the land. Bomb rack unit essential to testing ground ejection test, operate at high pressure and produce a significant ejection force to push the missile away from any large orifice. Bomb rack unit modified their bombe pressure and orifice diameter to photograph the drop movement of dummy missile with high-speed camera and to analyze their drop displacement and speed. It is considered useful to provide the initial data for the ejection force analysis on aircraft with actual flight and to carry out the ground separation tests of aircraft with future developments.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.3
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• pp.31-39
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• 2023

This paper aimed to provide the basic data on consumers' awareness, behavioral patterns, and purchase methods for pet fashion(dog clothes). Research was conducted in April 2023 among 183 college students from universities in the Gyeonggi-do region. The analysis results are presented below. When asked if they think clothes are a daily necessity for dogs, 74.3% recognized clothes as a daily necessity for dogs. The biggest purpose of clothing for dogs was 'physical health (prevention of cold/heat, etc.)' with 60.1%. 96.7% of the respondents were very positive about the development prospects for the pet fashion industry. 46.4% of the subjects were currently living with a dog, and 30.6% of the subjects have lived with a dog for 'less than 1-3 years'. 93.0% of college students who live with a dog own dog clothes. As for the dog's clothing style, T-shirt styles without a slit were the most common at 33.6%. 81.0% of companion dog owners were found to dress their dogs when going out, and the most common reason was 'physical health (prevention of cold/heat, etc.)' at 76.6%. When purchasing dog clothes, 72.2% of the subjects considered 'fitting with the dog/convenience', and 27.8% were 'focusing on the companion's taste'. As for how to purchase dog clothes, 39.2% chose 'store visits and online purchases', 34.2% chose 'store visits and purchases', and 26.6% chose 'online purchases'. As for the most considered part when purchasing clothes for dogs, 51.9% identified 'design' and 39.2% identified 'material'. 80.7% of respondents said they would increase the purchase of dog clothes in the future.

• The Research Journal of the Costume Culture
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• v.32 no.2
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• pp.199-214
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• 2024

Until now, research on consumers' purchasing behavior has primarily focused on psychological aspects or depended on consumer surveys. However, there may be a gap between consumers' self-reported perceptions and their observable actions. In response, this study aimed to investigate consumer purchasing behavior utilizing a big data approach. To this end, this study investigated the purchasing patterns of fashion items, both online and in retail stores, from a data-driven perspective. We also investigated whether individual consumers switched between online websites and retail establishments for making purchases. Data on 516,474 purchases were obtained from fashion companies. We used association rule analysis and K-means clustering to identify purchase patterns that were influenced by customer loyalty. Furthermore, sequential pattern analysis was applied to investigate the usage patterns of online and offline channels by consumers. The results showed that high-loyalty consumers mainly purchased infrequently bought items in the brand line, as well as high-priced items, and that these purchase patterns were similar both online and in stores. In contrast, the low-loyalty group showed different purchasing behaviors for online versus in-store purchases. In physical environments, the low-loyalty consumers tended to purchase less popular or more expensive items from the brand line, whereas in online environments, their purchases centered around items with relatively high sales volumes. Finally, we found that both high and low loyalty groups exclusively used a single preferred channel, either online or in-store. The findings help companies better understand consumer purchase patterns and build future marketing strategies around items with high brand centrality.

• Journal of Distribution Science
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• v.14 no.11
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• pp.83-90
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• 2016

Purpose - During the last two years, convenient stores (CS) are emerging as one of the most fast-growing retail trades in Korea. The goal of this work is to forecast and to analyze sales at CS using ARIMA-Intervention model (IM) and exponential smoothing method (ESM), together with sales at supermarkets in South Korea. Considering that two retail trades above are homogeneous and comparable in size and purchasing items on off-line distribution channel, individual behavior and characteristic can be detected and also relative superiority of future growth can be forecasted. In particular, the rapid growth of sales at CS is regarded as an everlasting external event, or step intervention, so that IM with season variation can be examined. At the same time, Winters ESM can be investigated as an alternative to seasonal ARIMA-IM, on the assumption that the underlying series shows exponentially decreasing weights over time. In case of sales at supermarkets, the marked intervention could not be found over the underlying periods, so that only Winters ESM is considered. Research Design, Data, and Methodology - The dataset of this research is obtained from Korean Statistical Information Service (1/2010~7/2016) and Survey of Service Trend of Korea Statistics Administration. This work is exploited time series analyses such as IM, ESM and model-fitting statistics by using TSPLOT, TSMODEL, EXSMOOTH, ARIMA and MODELFIT procedures in SPSS 23.0. Results - By applying seasonal ARIMA-Intervention model to sales at CS, the steep and persisting increase can be expected over the next one year. On the other hand, we expect the rate of sales growth of supermarkets to be lagging and tied up constantly in the next 2016 year. Conclusions - Based on 2017 one-year sales forecasts for CS and supermarkets, we can yield the useful information for the development of CS and also for all retail trades. Future study is needed to analyze sales of popular items individually such as tobacco, banana milk, soju and so on and to get segmented results. Furthermore, we can expand sales forecasts to other retail trades such as department stores, hypermarkets, non-store retailing, so that comprehensive diagnostics can be delivered in the future.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.45-56
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• 2003

In the wireless environment, according to the development of technology, which is able to obtain location information of spatiotemporal moving object, the various application systems are developed such as vehicle tracking system, forest fire management system and digital battle field system. These application systems need the data model, which is able to represent and process the continuous change of moving object. However, if moving objects are expressed by a relational model, there is a problem which is not able to store all location information that changed per every time. Also, existing data models of moving object have a week point, which constrain the query time to the time that is managed in the database such as past or current and near future. Therefore, in this paper, we propose a data model, which is able to not only express the continuous movement of moving point and moving region but also process the operation at all query time by using shape-change process and location determination functions for past and future. In addition, we apply the proposed model to forest fire management system and evaluate the validity through the implementation result.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.159-168
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• 2021

Building Information Modeling (BIM) data is a digitized construction design by worldwide construction design stands rules. Some research are being conducted to utilize blockchain for safe sharing and trade of BIM data, but there is no way to store BIM data directly in the blockchain due to the size of BIM data and technical limitation of the blockchain. In this paper, we propose a method of storing BIM data by combining a distributed file system and a blockchain. We propose two network overlays for storing BIM data, and we also propose generating the Level of Detail (LOD)-based merkle tree for efficient verification of BIM data. In addition, this paper proposes a system design for distributed storage of BIM data by using blockchain besu client and IPFS client. Our system design has a result that the processing speed stably increased despite the increase in data size.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.169-183
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• 2013

As the issue of selling wine online has been raised in an attempt to implement FTA programs in a more effective way, wine will be available online in the near future in Korea. Thus, this study aimed at identifying key factors which will contribute to reduce various kinds of risks perceived by online customers, and investigating the structural relationships between those factors and perceived risks. Site quality of online wine shop(information quality, system quality), trust in online wine shop were selected as key predictors of perceived risks and research model was established using those factors. Data were collected from those who have experienced in using online wine store, and the research model was tested using valid data. Results of testing research hypotheses using data from survey respondents showed that information and system quality exerted an impact on trust in online wine shop. It was proven that information and system quality posited an impact on time risk whereas they was not related to performance and psychological risk. In addition, trust in online wine shop was shown to be related to time risk, performance risk, and psychological risk.