• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.153-160
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• 2019

In this study, The purpose of this study is to analyze how the rating scale and review contents attributes of social network-based services and products affect consumer purchasing patterns. information provided by screening the main factors. These analyzes are closely and quickly integrated between individuals and businesses, and enable to analyze the transaction that the impact of changing consumers on consumption and purchasing through the usefulness and a priori estimates of reviews and ratings at this time when networks and smart technologies are involved in a wide range of consumer activities. For this study, hierarchical analysis (AHP) and delphi (Delphi) methods applied to classify the high end variables into usefulness, technicality and value, Each subvariable was grouped into three factors and analyzed for importance through evaluation weights. As a result, we could analyze the importance of durability, usefulness, technological innovation, and cost and quality of value. Therefore, this study is expected to provide supplementary and additional useful information to consumers and companies participating in economic activities in various ways by simultaneously analyzing the review score and the reliability of posting information provided by verifying the main factors.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.42-48
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• 2019

The significance of PNT information in the fourth industrial revolution is viewed differently in relation to the past. Autonomous vehicles, autonomous vessels, smart grids, and national infrastructure require sustainable and reliable services in addition to their high precision service. Satellite navigation system, which is the most representative system for providing PNT information, receive signals from satellites outside the earth so signal reception power is low and signal structures for civilian use are open to the public. Therefore, it is vulnerable to intentional and unintentional interference or hacking. Satellite navigation systems, which can easily acquire high performance of PNT information at low cost, require alternatives due to its vulnerability to the hacking. This paper proposed R-Mode (Ranging Mode) technology that utilizes currently operated navigation and communication infrastructure in terms of Signals of OPportunity (SoOP). For this, the Nationwide Differential Global Navigation Satellite System (NDGNSS), which currently gives a service of Medium Frequency (MF) navigation signal broadcasting, was used to validate the feasibility of a backup infrastructure in domestic maritime areas through simulation analysis.

• The Korean Journal of Franchise Management
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• v.10 no.1
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• pp.43-52
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• 2019

Purpose - Many companies use the Internet to conduct their business to maintain and acquire their customers. SNS is used as a site where users can create profiles, build personal networks, and then share and exchange information with others. Not only do people use SNS for their self-promotion, but they also promote their services by creating SNS pages. SNS is recognized as a medium for implementing effective advertising strategies and is being used as an important means of promoting the company. Therefore, in this study, we investigate the effect of SNS marketing characteristics of restaurant franchise firms on utilitarian value and hedonic value and examine their effects on purchase intention. Research design, data, and methodology - The data were collected from 20s-60s respondents who have used SNS for restaurant visit using Google survey. A total of 159 responses were collected and used for final analysis. Smart PLS 3.0 was used for the hypothesis test. Results - As a result of an analysis, it was shown that the influence of the playfulness and affordability of information on the utilitarian value had a significant positive effect. Interaction and up-to-date did not have a positive effect on utilitarian value. Interaction, affordability, and up-to-date have no significant positive effects on hedonic value. The playfulness of information has a positive effect on the hedonic value. Both utilitarian value and hedonic value had positive effects on purchase intention. Conclusions - The findings of this study suggest that the SNS marketers of restaurant franchisors should focus on the playfulness, affordability, and up-to-date rather than the interactivity of SNS. In marketing through SNS, the act of presenting the basis of information and enhancing the provision of information through objective criteria makes it possible to experience the practical value of information. It is necessary to develop differentiated contents which cause customers interest and fun and to induce many customers' purchase intent by providing objective and realistic information. In order to increase the customers' repurchase intentions toward the food service business, customers should maximize the hedonic value and practical value felt through information. It should also focus on providing information that customers are receptive to, rather than providing prompt information.

• The Korean Journal of Franchise Management
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• v.11 no.2
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• pp.41-51
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• 2020

Purpose: Fast food franchise companies are trying a variety of innovative services to increase their competitiveness in response to changes in population composition in the fast food market and rapid changes in consumption trends due to technological development. From this point of view, franchise companies that have focused on offline store operations are providing O2O (offline to online) service as a core service for customer convenience. This new attempt is a strategy to increase loyalty by applying an interaction method based on understanding the characteristics of new generation consumers. However, existing studies are focused on the relationship between O2O service and acceptance, so very little is known about how O2O service affects customer loyalty. Therefore, this study examines the impacts of customer involvement and relative advantages of fast food O2O service on customer brand engagement (cognitive and affective engagement) and store loyalty for MZ(Millennials - Z) generations. Research design, data, and methodology: In order to achieve the purposes of this research, several hypotheses were developed. The data were collected from 247 questionnaires in their 16-30s and were analyzed using SPSS 22.0 and SmartPLS 3.0 program. Measurement model analysis was carried out to assess convergent and discriminant validity. Also, common method bias was tested using the values of VIF (variance inflation factor). The hypotheses was tested using structural equation modeling. Result: First, involvement has a positive effect on cognitive and affective engagement. Second, relative advantages have has a positive effect on cognitive and affective engagement. Third, cognitive influences affective engagement. Finally, both cognitive and affective engagement affect store loyalty, but affective engagement has a stronger effect on store loyalty than cognitive engagement. Conclusions: In the process of consumer-brand interaction, it was confirmed that store loyalty was influenced by cognitive and affective engagement sequentially. However, the results show that affective engagement has a relatively stronger on store loyalty than cognitive engagement. Therefore, it is necessary to establish an O2O service strategy to maintain long-term loyal customers by inducing cognitive participation with high-involved consumer, as well as affective interaction, in order to obtain new customers and increase customer loyalty.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.77-88
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• 2021

Cloud computing is getting a lot of attention by many people and businesses due to IT environmental changes such as the proliferation of smart devices, the increase of digital data, and the cost of IT resources. More individuals use personal cloud computing services for storing and managing information and data. Therefore, this study proposed determinants that are expected to have an influence on evaluating the value of cloud computing based on the value-based adoption model, examining the relationship between the continuous use intention of cloud computing. Results of the study show that usefulness, convenience of information access, extensibility had a positive impact on perceived value while privacy concerns and costs had a negative impact on perceived value. In addition, perceived value was found to have a significant effect on the intention to continue use of cloud computing. Finally, trust was found to have a significant effect on the perceived value and the intention to continue use of cloud computing. The findings are expected to provide useful information for understanding the factors that individual users consider important in the steadily growing cloud computing market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.283-289
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• 2021

Many people with disabilities have shown interest in artificial intelligence speakers that serves as the main hub of the smart home. Therefore, the purpose of this study was to identify the intention of people with disabilities to use such speakers. The focus is on those with physical disabilities, a segment that accounts for the largest number of disability types. Based on the theoretical model of technology acceptance, the effect of perceived ease of use and perceived usefulness of artificial intelligence speakers by people with disabilities was analyzed using Structural Equation Modeling (SEM). Research has confirmed that the technology acceptance model is suitable for identifying the intention to use artificial intelligence speakers by people with disabilities, and specifically that the perceived ease of use has a significant impact on usefulness. Furthermore, the perceived ease of use for people with disabilities did not have a statistically significant effect on their intent to use whereas the perceived usefulness was shown to have a significant effect on the same. This study is meaningful as a foundation for developing customized artificial intelligence speaker services and improving the use of artificial intelligence speakers by people with disabilities.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences

• Journal of the Korea Institute of Building Construction
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• v.21 no.3
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• pp.231-239
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• 2021

Entering the era of the fourth industrial revolution, information and communication technologies such as CCTV, home network systems and equipment are being used in the construction industry. In particular, in order to increase the autonomy of information and communication technologies in apartments, the government has announced an administrative revision of information and communication-related laws, and companies are focusing on developing technologies such as smart home services. In addition, most domestic and foreign studies on the information and communication work were mainly conducted on technology and management. However there is a lack of research on physical defects affecting the quality of ICT. Therefore, this study collected the defect data registered in the project management system of three domestic construction companies and classified them according to the standards of the Enforcement Decree of the Apartment House Management Act. According to the analysis of the frequency of defects work type, 88.10% of defects occurred in home network equipment work. In addition, analysis of defects type in the four detailed works showed the highest number of operation error. The cause was analyzed and prevention measures and countermeasures were presented in parts of design, construction, and maintenance. The results of this study will improve the quality of apartment housing and be used as basic data for future research on practical defect minimization and prevention measures.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.319-325
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• 2021

With the advancement of wireless technology and the rapid growth of the infrastructure of mobile communication technology, systems applying AI-based platforms are drawing attention from users. In particular, the system that understands users' tastes and interests and recommends preferred items is applied to advanced e-commerce customized services and smart homes. However, there is a problem that these recommendation systems are difficult to reflect in real time the preferences of various users for tastes and interests. In this research, we propose a Fuzzy-AHP-based movies recommendation system using the Gated Recurrent Unit (GRU) language model to address a problem. In this system, we apply Fuzzy-AHP to reflect users' tastes or interests in real time. We also apply GRU language model-based models to analyze the public interest and the content of the film to recommend movies similar to the user's preferred factors. To validate the performance of this recommendation system, we measured the suitability of the learning model using scraping data used in the learning module, and measured the rate of learning performance by comparing the Long Short-Term Memory (LSTM) language model with the learning time per epoch. The results show that the average cross-validation index of the learning model in this work is suitable at 94.8% and that the learning performance rate outperforms the LSTM language model.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.