• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.193-204
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• 2022

Smart card data is representative mobility data and can be used for policy development by analyzing public transportation usage behavior. This paper deals with the problem of classifying metro stations using metro usage patterns as one of these studies. Since the previous papers dealing with clustering of metro stations only considered traffic among usage behaviors, this paper proposes clustering considering traffic time as one of the complementary methods. Passengers at each station were classified into passengers arriving at work time, arriving at quitting time, leaving at work time, and leaving at quitting time, and then the estimated shape parameter was defined as the characteristic value of the station by modeling each transit time to Weibull distribution. And the characteristic vectors were clustered using the K-means clustering technique. As a result of the experiment, it was observed that station clustering considering pass time is not only similar to the clustering results of previous studies, but also enables more granular clustering.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.265-274
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• 2024

This study aims to explore the relationship between product assortment, streaming airtime, streaming hits views, and sales performance, while examining the moderating effects of weekends versus weekdays. The data used for the analysis consists of 2023 live commerce streaming information provided by Labangba Data Lab. A PLS(Partial Least Squares) model was employed because all variables were measured using formative indicators. The key findings are as follows: First, product assortment positively influences streaming hits views. Second, streaming airtime has a negative impact on streaming hits views. Third, streaming hits views positively affect sales performance. Finally, a positive moderating effect of weekends and weekdays on the relationship between streaming hits views and sales performance was identified. The study concludes with a discussion of theoretical and practical implications.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.25 no.3
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• pp.79-87
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• 2019

The degree of cosmetic's oxidation depends on the storage conditions and external conditions when using the product. The microbial contamination and oxygen exposure often results in the quality deterioration of cosmetics. In addition, the problem is that consumers often use cream-type cosmetics, which have short expiration period (6-12 months), even after the product is expired. When using the deteriorated cosmetics, it can be fatal to consumers' safety including some symptoms such as folliculitis, rashes, edema, and dermatitis. Therefore, it is necessary to develop sealed smart packaging for cosmetics to prevent the deterioration of cosmetics and improve consumer safety. In this study, we have developed smart packaging design for cosmetics that can measure the surrounding environment and expiration date for the cosmetics in the real time. In addition, the smart packaging includes sensor, which are linked to the mobile application. Users can find out the measurement results through the application. Also, the packaging design and functions were set up based on the survey results by the user and feasible model can be produced based on user choice. The measurement in the three environment has been done after manufactured the sensor, PCB, and mobile application. As a result, it works normally within a certain range under all three environmental conditions. It is believed that the information on expiration dates and storage environment can be efficiently delivered to the consumers through developed cosmetics smart packaging and applications. The development of UI/UX design for consumer is further studied. The UX/UI design of the application plays an essential role in achieving this goal through the commercialization the cosmetic products in the wide range.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.83-101
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• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.1-18
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• 2019

Due to the great advances in e-Marketplace and changes in type of items purchased from the online market, it has been dramatically increased the demand of the storage and transportation under the special conditions such as restricted temperature. Especially, the cold chain needs the way to transparently measure and monitor the entire network in realtime because it has a very complicated structure and requires totally different criteria at the every different steps and items. In this research, it has been presented the performance evaluation metrics to make contract using service level agreement (SLA), the way to apply the smart contract based on blockchain, the structure of blocks, service platform and application in order to build cold chain which can prevent the risk factors by measuring and sharing information in realtime using block chain technology. In addition, we have proposed the way to store the measured performance and reputation of each player in the block using smart contract based on SLA. With the presented framework, all players including service providers as well as users can secure the information for making the rational decisions. When the service platform is actually built and operated, it seems possible to secure the information in transparently and realtime. Also, it is possible to prevent the risk factors or prepare the preemptive plans to react on them.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2511-2519
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• 2015

In maritime logistics, the technology for transmitting status information has been greatly developed, but it has not been available in general logistics environment or it is impossible to support two-way communication as it simply receives and transfers a container's information. In particular, to support two-way communication in all sections of the global maritime logistics, the address value, which can identify the tag, should be managed. In this context, to improve the 433 MHz-based RFID, the project called "DASH 7" has been conducted in recent years. However, it has stopped proceeding because of its slow progress, including the standardization and development of references. In this paper, we introduced an active IP-RFID system configuration for real-time communication in global maritime logistics using a two-way communication-which is characteristic of an IP-applying virtual address values in the RFID tag, and proposing its process and function. When you apply the IP-RFID system proposed in this paper, not only real-time status tracking in the maritime logistics area is possible, but it is also applicable for controlling the tag.

• Journal of Distribution Science
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• v.14 no.2
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• pp.41-45
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• 2016

Purpose - Finding an optimal path is an essential component for the design and operation of smart transportation or logistics network. Many applications in navigation system assume that travel time of each link is fixed and same. However, in practice, the travel time of each link changes over time. In this paper, we introduce a new transportation problem to find a latest departing time and delivery path between the two nodes, while not violating the appointed time at the destination node. Research design, data, and methodology - To solve the problem, we suggest a mathematical model based on network optimization theory and a backward search method to find an optimal solution. Results - First, we introduce a dynamic transportation problem which is different with traditional shortest path or minimum cost path. Second, we propose an algorithm solution based on backward search to solve the problem in a large-sized network. Conclusions - We proposed a new transportation problem which is different with traditional shortest path or minimum cost path. We analyzed the problem under the conditions that travel time is changing, and proposed an algorithm to solve them. Extending our models for visiting two or more destinations is one of the further research topics.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.17-27
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• 2020

With the continuous development and application of Internet technology, in recent years, new technologies such as cloud computing, big data, the Internet of Things, and AI are becoming more and more familiar to the general public. The development of a digital society has entered a new period of development. In this paper, we used on the 2018 annual data of 50 listed companies with blockchain concept stocks in China. Using data envelopment analysis (DEA) to study and analyze the input-output efficiency, it can be concluded that the input-output efficiency of 50 listed companies is very different. Inefficient companies are as high as 62%. Most companies have a large room for improvement in input-output efficiency due to uneconomical scale or inefficient technology. In order to better improve the company's input-output efficiency, one must improve the efficiency of resource utilization, optimize the company's research and development costs and the input and management of technical personnel; the second is to increase technological innovation and business innovation.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.127-136
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• 2020

The purpose of this study is to measure the productivity of fisheries in China's coastal areas (including inland and marine fisheries) and to analyze the factors influencing the development of fishery economy in each province by comparing regional differences. The input indicators used for efficiency analysis are fish farms, ships and staff numbers, and the output indicators are fish catch and net income. In this paper, we used six years of data from 2013-2018 and DEA-Malmquist index was used to analyze the efficiency of coastal fisheries production in 11 areas of China's coast. According to the analysis from 2013 to 2018, the fishery output efficiency in China's coastal areas has improved to some extent, but most provinces and regions are characterized by technological progress, and the technological efficiency still needs to be further improved. The conclusion can provide reference for the development planning and policy measures of regional fishery industry in China's coastal areas.

• Journal of Distribution Science
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• v.12 no.9
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• pp.73-82
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• 2014

Purpose - This study aims to illustrate the relationship between demographic factors and perceived risk types, supposing that Korean customers tend to postpone buying or hesitate to purchase the new version of hand sets, because of an early buying risk. Research design, data, and methodology - In addition to existing perceived risk types, the authors introduced an early buying risk. In order to measure each variable, also, the study has employed a five-point Liker-scale. To increase research reliability and validity, the research adopted an exploratory factor analysis, a confirmatory factor analysis, and one-way ANOVA. Results - First, there were statistically significant differences between financial risk and the group. Second, there weren't any statistically significant differences between the group means among the four perceived risk types (Performance Risk, Social Risk, Psychological Risk, and Physical Risk) and 4 factors (Gender, Age, Job, and Education). Lastly, job is apparently differentiated from others (Gender, Age, and Education). Conclusions - The authors found that customers regarded an early buying risk as one of the important perceived risk types, when purchasing a hand set.