• Information Systems Review
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• v.22 no.2
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• pp.25-41
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• 2020

Along with the expectation about 5G network commercialization, interests in realistic and immersive media industries such as virtual reality (VR) are increasing. However, most of studies on VR still focus on video technologies instead of factors for popularity and consumption. Thus, the main objective of this research is to identify meaningful factors, which affect the view counts of VR videos and to provide business implications of the content strategies for VR video creators and service providers. Using a regression analysis with 700 VR videos, this study tries to find major factors that affect the view counts of VR videos. As a result, user assessment factors such as number of likes and sicknesses have a strong influence on the view counts. In addition, the result shows that both general information factors (video length and age) and content characteristic factors (series, one source multi use (OSMU), and category) are all influential factors. The findings suggest that it is necessary to support recommendation and curation based on user assessments for increasing popularity and diffusion of VR video streaming.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.267-274
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• 2024

In this paper, we investigated the number of domestic patent applications by year, the number of domestic patent disclosures by year, and the number of domestic registrations by year regarding smart factories. The number of patent applications by applicant type was investigated. Based on the patents studied, it was found that the IPC appearing in the most patents was G05B 19/418. In addition, through social network analysis of smart factory patented IPCs, it was found that G05B 19/418 was the IPC with the highest degree of centrality. From the above, if the IPC of the core technology of the patent submitted for smart factory is G05B 19/418, the technology combined with G05B 23/02, that is, the technology combining "factory control" and "monitoring" is the most patented. When the IPC of the core technology was G06Q 50/04, it was confirmed that the technology combined with G06Q 50/10, that is, the technology combining "manufacturing" and "service" was the most applied for patents. Through this, it was found that in order to apply for a patent for a smart factory, it would be necessary to file a patent application that takes into account the connectivity between IPCs.

• Journal of Service Research and Studies
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• v.5 no.1
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• pp.91-103
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• 2015

We examine the information transmission between the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index, based on the returns data offered by the Korea Exchange. The data includes daily return data from 1 January 2012 to 31 December 2014. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the KT Futures Index and the SK Telecom Futures Index precede and have explanatory power the KT Spot and the SK Telecom Spot However the results also identified a greater causality and explanatory power of the KT Spot and the SK Telecom Spot over the KT Futures Index and the SK Telecom Futures Index. Secondly, the results of impulse response function suggest that the KT Futures Index show immediate response to the KT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Also the SKT Futures Index show immediate response to the SKT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of the KT Spot and SKT Spot are dependent on those of the KT Futures Index and the SK Telecom Futures Index. This implies that returns on the KT Spot and SKT Spot have a significant influence over returns on the KT Futures Index and the SK Telecom Futures Index. It contributes to the understanding of market price formation function through analysis of detached the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index.

• Journal of Service Research and Studies
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• v.9 no.3
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• pp.39-60
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• 2019

The purpose of this study is to analyze the determinants of insurance product cross selling performance. For the study, 11 insurance managers and 2 sales managers belonging to A insurance agency were selected and in-depth interviews were conducted. The analysis of the research data was done by the open coding method suggested by Strauss & Corbin(2001). As a result, 84 concepts, 28 subcategories and 10 categories were derived. The ten categories that were determinants of insurance product cross-selling performance were personal characteristics, consultation method, cross-selling ratio, sales culture, education, customer change, customer DB provision, satisfaction, business support system, and customer service. In order to verify the qualitative results, quantitative analysis was emplyed to the actual performance data of insurance planners belonging to A insurance agency during April 2016~March 2019. As a result of the analysis, the age, position, and the number of months worked in the insurance company had a statistically significant effect on the number of life insurance contracts in total insurance contracts and life insurance contracts in total insurance contracts. In addition, the age, position, and the number of months worked in the insurance company had a statistically significant negative impact on the number of non-life insurance contracts in the total number of insurance contracts and the total amount of insurance contracts in total insurance contracts. The result of this study can be an important basic data for the development of educational programs and job support systems for the training of insurance planners. Insurance companies should refer to ten categories derived from qualitative research in order to increase the performance of insurance planners and to promote long-term service. Especially, it is necessary to develop specialized education programs and job support systems so that cross sales that increase the proportion of life insurance sales increase.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.106-116
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• 2022

As part of the Fire Evacuation Service scenario using mobile applications, this study aims to find the appropriate colors to be used in the interface of the application and to define and apply colors that can positively and reliably affect human unstable psychology in the course of evacuating the room in case of fire. In the situation of fire, proper design and placement of the colored escape guidance interface is important, taking into account the psychology of the occupants. However, literature and previous research have shown that colors used to induce evacuation are not suitable for effective evacuation in case of fire. In this study, the purpose of the study was to provide a color that would provide psychological stability in the event of a evacuation in consideration of the psychological issues of those who are still in need of shelter, and to use it to help induce an efficient evacuation in the event of a disaster. Using the image evaluation method, the form and color of images have been derived through frequency analysis to a number of unspecified people, and the main and secondary colors of images were analyzed through KSCA color analysis. Finally, the final application color was constructed through mutual verification between the results by comparing and analyzing the colors obtained through the image evaluation analysis results and the KSCA color analysis results. The results of the study showed that the green line can help stabilize the human mind through comparative analysis with prior research. Therefore, the main color for guiding calm and calm applications in case of fire escape is proposed in the green line. In this study, the experiment with image evaluation cannot accurately measure the effect of factors on color among complex factors. A subsequent study of this will help quantify images if it allows the subject matter of color and image to be defined to some extent through factor analysis.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.172-189
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• 2023

This study investigated the potential contribution of ChatGPT, a massive language and information model, in the decision-making process of public design policies, focusing on the characteristics inherent to public design. Public design utilizes the principles and approaches of design to address societal issues and aims to improve public services. In order to formulate public design policies and plans, it is essential to base them on extensive data, including the general status of the area, population demographics, infrastructure, resources, safety, existing policies, legal regulations, landscape, spatial conditions, current state of public design, and regional issues. Therefore, public design is a field of design research that encompasses a vast amount of data and language. Considering the rapid advancements in artificial intelligence technology and the significance of public design, this study aims to explore how massive language and information models like ChatGPT can contribute to public design policies. Alongside, we reviewed the concepts and principles of public design, its role in policy development and implementation, and examined the overview and features of ChatGPT, including its application cases and preceding research to determine its utility in the decision-making process of public design policies. The study found that ChatGPT could offer substantial language information during the formulation of public design policies and assist in decision-making. In particular, ChatGPT proved useful in providing various perspectives and swiftly supplying information necessary for policy decisions. Additionally, the trend of utilizing artificial intelligence in government policy development was confirmed through various studies. However, the usage of ChatGPT also unveiled ethical, legal, and personal privacy issues. Notably, ethical dilemmas were raised, along with issues related to bias and fairness. To practically apply ChatGPT in the decision-making process of public design policies, first, it is necessary to enhance the capacities of policy developers and public design experts to a certain extent. Second, it is advisable to create a provisional regulation named 'Ordinance on the Use of AI in Policy' to continuously refine the utilization until legal adjustments are made. Currently, implementing these two strategies is deemed necessary. Consequently, employing massive language and information models like ChatGPT in the public design field, which harbors a vast amount of language, holds substantial value.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.227-245
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• 2023

As offline company and online·mobile startups meet in an untact shopping environment, competition among companies in untact shopping is increasing. In this situation, companies need their own clear strategy to create customer value. In particular, it is very important to focus on 'customer experience' to establish such a strategy in an untact shopping environment. Customer experience refers to all processes in which consumers meet and experience a company or brand at a touch point. In this processes consumers decide whether to continue to use the company and brand. In this situation, it is thought that it will be meaningful for research to examine the customer experience of untact shopping. Therefore, this study aimed to examine the customer experience of untact shopping, which is used by all generations after COVID-19, through experience quality, and to examine the impact on the expectation-confirmation Model of untact shopping. The results of this study are as follows. First, as a result of examining whether interaction quality, information quality, and outcome quality affect expectation-confirmation it was found that all qualities except interaction quality affect expectation matching. Second, as a result of examining whether interaction quality, information quality, and outcome quality affect perceived usefulness, it was found that all qualities except interaction quality had an effect. Next, as a result of applying the expectation confirmation model to the untact shopping environment and examining whether the expectation confirmation has an effect on use satisfaction, it was found that there was a positive effect. As a result of examining whether perceived usefulness affects use satisfaction, it was found to have a positive effect. As a result of examining whether perceived usefulness affects expectation confirmation, it was found that there is a positive effect. Finally, as a result of examining whether perceived usefulness affects the intention to continue using untact shopping, it was found to be positive. Next, as a result of examining the effect of use satisfaction on trust, it was found that there was a positive effect. Finally, as a result of investigating whether trust has an effect on the intention to continue using, it was found that there is a positive effect. Looking at the important results especially, information quality was found to have the greatest influence.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

• Journal of Service Research and Studies
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• v.6 no.1
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• pp.83-95
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• 2016

We examine the information transmission between the Service Industrial Production Index and the Service Industrial Wholesale and Retail Index, based on the returns data offered by the Korea Bank. The data includes daily return data from January 2000 to September 2015. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the Service Industrial Production Index precede and have explanatory power the Service Industrial Wholesale and Retail Index However the results also identified a greater causality and explanatory power of the Service Industrial Wholesale and Retail Index over the Service Industrial Production Index. Secondly, the results of impulse response function suggest that the Service Industrial Production Index show immediate response to the Service Industrial Wholesale and Retail Index and are influenced by till time 5 From time 2, the impact gradually disappears. Also the Service Industrial Wholesale and Retail Index show immediate response to the Service Industrial Production Index and are influenced by till time 2.5, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of Service Industrial Production Index are dependent on those of the Service Industrial Wholesale and Retail Index. This implies that returns on the Service Industrial Production Index have a significant influence over returns on the Service Industrial Wholesale and Retail Index. It contributes to the understanding of market price formation function through analysis of detached the Service Industrial Production Index and Service Industrial Wholesale and Retail Index. Finally, our results can be used as a guide by the Korea Bank and Republic of Korea and as well as Statistics Korea.

• Journal of Service Research and Studies
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• v.10 no.1
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• pp.33-53
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• 2020

The purpose of this study is to empirically examine the causal relationship of CSR activities, customer trust and CCID, customer behavior intention(B.I) in the relationship between CSR activities and customer behavior intention(B.I) in the insurance industry, thereby enable top management of insurance company to take it in their consideration that CSR activity help link to customer behavioral intention by customer trust in them and CCID. To achieve the purpose of the study, the hypothesis was established based on preceding research and theoretical background regarding CSR, trust, CCID, behavioral intention(B.I). And this study conducted AMOS statistical analysis based on effective 526 survey data collected from insurance customers across country through online research company. The result of this empirical study is as follows. First, insurance company's CSR activity has a positive impact on customer's trust and CCID, but it did not have a direct significant effect on the customer's behavioral intention(B.I). Second, both customer's trust and CCID have a positive and significant effect on customer's behavioral intention. Third, we have also found that both Trust and CCID played a mediating role between CSR activity and B,I. Fourth, it was found that authenticity did not moderate the enfluence relationship between CSR activity and Trust, CCID. The result of this study shows that insurance company's active CSR activity increase customer trust, thereby create a sense of unity between the customer and the company, In addition, it shows that when CSR activities are mediated by customer trust and CCID, it could lead to customer behavioral intention(B.I) such as repurchasing and positive word-of-mouth activities. to others. The result of this study will contribute to the future research on CSR literature and the marketing strategy of insurance companies.