• Journal of Digital Convergence
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• v.19 no.2
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• pp.93-103
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• 2021

S&OP(Sales and Operations Planning) is an ongoing process of periodic planning, reviewing, and evaluation through the involvement of all key stakeholders. Within this process, performance is regularly reviewed and early warning signals are generated, so that the company can react quickly to changing market and operational environment. This paper presents a framework for effective S&OP for fair alignment, accountability, teamwork, visibility, and risk management. This framework focuses on supply chain information governance, level of information sharing through S&OP, role of S&OP as coordination mechanism, APS effectivesness as a planning tool and SCM performance. In addition, a brief case study on the operating characteristics of S&OP at three Korean firms is presented. Implications of the study finding are also provided. It will also make companies that are considering the introduction of S&OP aware of the importance of S&OP, which will provide practical guidelines for the introduction of S&OP.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.365-374
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• 2021

Recently, the high growth rate and advantages of the crowdfunding market have also led to increased participation of brands and companies, and this also applies to fashion business. Risk has been noted to be a key factor in consumer behavior in crowdfunding. With the high-risk context of crowdfunding where supporters inevitably bear to pay full amount of price before receiving the actual products. Factors enhancing or inhibiting perceived risk of crowdfunding need to be explored. The past literature on perceived risk and consumer attitudes in crowdfunding has expanded, but it has rarely covered the context of experience goods such as fashion products. In addition, the platform characteristics in relation to perceived risk should be addressed. The current study attempts to address the effect of the perceived amount of information offered in a fashion crowdfunding project on perceived risk and the intention to participate in the project. For the experiment of this study, a fictitious crowdfunding page for fashion products was set as the stimuli. A total of 240 Korean participants were recruited and their responses were statistically analyzed using SPSS 24.0 software. In the results, the greater the amount of detailed information about the fashion crowdfunding project, the higher the intention to participate the project. The greater the amount of information provided, the lower the perceived risk of consumers. Moreover, the lowered perceived risk affected the intention of participate. Perceived risk has a partial mediation in the relationship between the amount of information and intention to participate. Theoretical and managerial implications are discussed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.128-133
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• 2021

Currently, autonomous vehicle markets are commercializing a third-level autonomous vehicle, but there is a possibility that an accident may occur even during fully autonomous driving due to stability issues. In fact, autonomous vehicles have recorded 81 accidents. This is because, unlike level 3, autonomous vehicles after level 4 have to judge and respond to emergency situations by themselves. Therefore, this paper proposes a vehicle crisis detection system(VCDS) that collects and stores information outside the vehicle through CNN, and uses the stored information and vehicle sensor data to output the crisis situation of the vehicle as a number between 0 and 1. The VCDS consists of two modules. The vehicle external situation collection module collects surrounding vehicle and pedestrian data using a CNN-based neural network model. The vehicle crisis situation determination module detects a crisis situation in the vehicle by using the output of the vehicle external situation collection module and the vehicle internal sensor data. As a result of the experiment, the average operation time of VESCM was 55ms, R-CNN was 74ms, and CNN was 101ms. In particular, R-CNN shows similar computation time to VESCM when the number of pedestrians is small, but it takes more computation time than VESCM as the number of pedestrians increases. On average, VESCM had 25.68% faster computation time than R-CNN and 45.54% faster than CNN, and the accuracy of all three models did not decrease below 80% and showed high accuracy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.241-248
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• 2021

Firms have many ways to expand their businesses including M&A. Big companies in online and offline businesses show different ways of expansion with different objectives to expand their digital businesses quickly. Expansions for technical reasons are to acquire technologies they do not have while those for business reasons are M&A for offline companies to have competence in markets by acquiring online companies. Other ways of expansions include spin-off and group participation after investments for startups. Various ways of expansions are chosen because they are optimal choices depending on situations the companies face, and they have different strengths and weaknesses. To analyze the strengths and weaknesses of those options for expansion at this stage would be academically valuable, and also practically meaningful in terms of providing insights for companies' decision making in choosing opitions for expansions. M&A of online companies to make multi-channels by offline companies have risks of failing to internalize online companies and have enough synergy effects. Also, spin-off is a relatively less risky way of expansion while the speed of expansion is slower than establishing external startups with some shares of equity and making them as affiliated companies. External startups are good for speed of expansion while there are risks of legal regulations and negative awareness by the public.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.250-260
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• 2022

The purpose of this study is to verify the impact of government subsidies and technological innovation on the business performance of Chinese cultural industry enterprises. Therefore, this study takes 238 listed cultural industry enterprises in China from 2015 to 2020 as the object, collects 1175 samples, and uses Stata16 software for empirical analysis. The analysis results are as follows. First, government subsidies have a positive impact on the business performance of Chinese cultural industry enterprises. Second, government subsidies have a positive impact on the scientific and technological innovation of Chinese cultural industry enterprises. Third, scientific and technological innovation has a positive impact on the business performance of Chinese cultural industry enterprises. Fourth, scientific and technological innovation plays a partially mediating role in the relationship between government subsidies and business performance of Chinese cultural industry enterprises. Based on the research results, measures to improve the business performance of cultural industry companies are as follows. First, establish a modern cultural industry market system. Second, the government should expand financial and tax support for cultural industry companies. Third, promote the integration of cultural industries with scientific and technological innovation.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.825-834
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• 2023

The demands of people who purchase fashion products on Internet shopping are gradually increasing, and attempts are being made to provide user-friendly images with 3D contents and web 3D software instead of pictures and videos of products provided. As a reason for this issue, which has emerged as the most important aspect in the fashion web shopping industry, complaints that the product is different when the product is received and the image at the time of purchase has been heightened. As a way to solve this problem, various image processing technologies have been introduced, but there is a limit to the quality of 2D images. In this study, we proposed an automatic conversion technology that converts 2D images into 3D and grafts them to web 3D technology that allows customers to identify products in various locations and reduces the cost and calculation time required for conversion. We developed a system that shoots a mannequin by placing it on a rotating turntable using only 8 cameras. In order to extract only the clothing part from the image taken by this system, markers are removed using U-net, and an algorithm that extracts only the clothing area by identifying the color feature information of the background area and mannequin area is proposed. Using this algorithm, the time taken to extract only the clothes area after taking an image is 2.25 seconds per image, and it takes a total of 144 seconds (2 minutes and 4 seconds) when taking 64 images of one piece of clothing. It can extract 3D objects with very good performance compared to the system.

• Journal of Venture Innovation
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• v.6 no.3
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• pp.73-93
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• 2023

This study provides a prospect for the fast growing the smartwatch market by investigating the relationship between the satisfaction and the continuous use intention of Apple watch users, as well as the factors influencing their satisfaction. Based on the TAM, this study uses system quality, information quality, and self-efficacy as independent variables, perceived usefulness, perceived ease of use, and satisfaction as mediators, and continuous use intention as the dependent variable. We analyze the data of 256 individuals who completed an online survey with SPSS 26.0 and AMOS 26.0 software. This study conducts several tests and analyses to empirically evaluate the data including reliability analysis, factor analysis, feasibility analysis, path analysis, hypothesis verification, and mediation analysis. Our results investigate which factors may influence consumers' intention to continuously using Apple Watch devices in the future. In summary, satisfaction has a positive effect on the intention to continuously use smartwatchs. Perceived usefulness and perceived ease of use have a positive effect on satisfaction. Among the three factors (system quality, information quality, and self-efficacy), only self-efficacy has no significant impact on perceived usefulness but had a positive effect on perceived ease of use. In addition, system quality and information quality positively affect perceived usefulness, perceived ease of use, satisfaction, and continuous intention to use an Apple Watch. Taking the Apple Watch as the subject of our research topic, this study provides theoretical value by exploring the impact of user's satisfaction with their smartwatch on their continuous usage intention. This study further explains the influence of system quality, information quality, and self-efficacy on user satisfaction. Additionally, this research offers valuable insight to practitioners by confirming that information quality, system quality, and self-efficacy are important features for enhancing satisfactory user experiences which in turn may increase users' intention to continued using smartwatches.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.145-157
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• 2004

The cycle length design model of the Korean traffic responsive signal control systems is devised to vary a cycle length as a response to changes in traffic demand in real time by utilizing parameters specified by a system operator and such field information as degrees of saturation of through phases. Since no explicit guideline is provided to a system operator, the system tends to include ambiguity in terms of the system optimization. In addition, the cycle lengths produced by the existing model have yet been verified if they are comparable to the ones minimizing delay. This paper presents the studies conducted (1) to find shortcomings embedded in the existing model by comparing the cycle lengths produced by the model against the ones minimizing delay and (2) to propose a new direction to design a cycle length minimizing delay and excluding such operator oriented parameters. It was found from the study that the cycle lengths from the existing model fail to minimize delay and promote intersection operational conditions to be unsatisfied when traffic volume is low, due to the feature of the changed target operational volume-to-capacity ratio embedded in the model. The 64 different neural network based cycle length design models were developed based on simulation data surrogating field data. The CORSIM optimal cycle lengths minimizing delay were found through the COST software developed for the study. COST searches for the CORSIM optimal cycle length minimizing delay with a heuristic searching method, a hybrid genetic algorithm. Among 64 models, the best one producing cycle lengths close enough to the optimal was selected through statistical tests. It was found from the verification test that the best model designs a cycle length as similar pattern to the ones minimizing delay. The cycle lengths from the proposed model are comparable to the ones from TRANSYT-7F.

• Information Systems Review
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• v.11 no.1
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• pp.161-179
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• 2009

Nowadays an increasing number of Internet users are running individual websites as Blog or Cyworld. As this type of personal media has a great influence on communication among people, business comes to care about Network Effect, Network Software, and Social Network. For instance, Cyworld created the web service called 'Minihompy' for individual web-logs, and acquired 2.4milion users in 2007. Although many people assumed that the popularity of Minihompy, or Blog would be a passing fad, Cyworld has improved its service, and expanded its Network with various contents. This kind of expansion reflects survival efforts from infinite competitions among ISPs (Internet Service Provider) with focus on enhancing usability to users. However, Cyworld's Network Effect is gradually diminished in these days. Both of low production cost of service vendors and the low searching/conversing costs of users combine to make ISPs hard to keep their market share sustainable. To overcome this lackluster trend, Cyworld has adopted new strategies and try to lock their users in their service. Various efforts to improve the continuance and expansion of Network effect remain unclear and uncertain. If we understand beforehand how a service would improve Network effect, and which service could bring more effect, ISPs can get substantial help in launching their new business strategy. Regardless many diverse ideas to increase their user's duration online ISPs cannot guarantee 'how the new service strategies will end up in profitability. Therefore, this research studies about Network effect of Cyworld's 'Minihompy' using System-Dynamics method which could analyze dynamic relation between users and ISPs. Furthermore, the research aims to predict changes of Network Effect based on the strategy of new service. 'Page View' and 'Duration Time' can be enhanced for the short tenn because they enhance the service functionality. However, these services cannot increase the Network in the long-run. Limitations of this research include that we predict the future merely based on the limited data. We also limit the independent variables over Network Effect only to the following two issues: Increasing the number of users and increasing the Service Functionality. Despite of some limitations, this study perhaps gives some insights to the policy makers or others facing the stiff competition in the network business.