• Journal of Service Research and Studies
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• v.12 no.4
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• pp.125-138
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• 2022

This study has examined the effect of cognitive resource on purchase intention of scarcity products according to the level of need for cognitive closure. In order to find out the effect on purchase intention for products that are presented a shopping environment is supposed, where various timing of consumer promotion reward exist, and where consumers can easily access and experience a lot of cognitive changes. the effect of how these two influences are adjusted according to the level of need for cognitive closure (NFCC). The study divide into two experiments. Research analyzes the behavioral differences of consumers for scarcity message products according to cognitive resource level with a moderating effect of NFCC. As a result of the study, Research according to the level of cognitive resource, when applied scarcity message product showed a negative effect of the cognitive resource (self-regulating resource) depletion level on the purchase intention of high-involvement product with scarcity message (Hypothesis 1). Consumers' purchase intention for limited products was higher at the non-depleted level than at the cognitive resource depletion level, and this difference was found statistically significant. Next, as a result of examining the difference according to the level of NFCC, the difference in the influence of cognitive resource level on purchase intention of scarcity products was found to be statistically significant where the NFCC was low (Hypothesis 2).

• Journal of Digital Convergence
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• v.20 no.1
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• pp.335-341
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• 2022

This is a descriptive research study to confirm the relationship between communication types, emotional labor, and job stress of nurses in small and medium-sized hospitals and to identify factors affecting job stress. The study was conducted on 192 nurses randomly selected from small and medium-sized hospitals located in G Metropolitan City. A structured questionnaire was used as a research tool for measuring communication types, emotional labor, and job stress, and the data were collected from August 20 to September 10, 2019. The results of the study are as follows. The subject's communication type averaged 3.55±0.31 points, emotional labor 3.21±0.59 points, and job stress 3.44±0.52 points. Job stress showed a statistically significant negative correlation with friendly communication among the types of communication, and a statistically significant positive correlation with emotional labor. Factors affecting job stress included gender, total clinical experience, and emotional labor, showing an explanatory power of 28.0%. It is considered that an efficient management strategy for emotional labor is needed to reduce the job stress of nurses in the future.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.449-455
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• 2022

The Colony of Selaginella involvens (Sw.) Spring in Sanyang-myeon, Mungyeong-si, can be divided into five types, and in the past, it was said that Selaginella involvens (Sw.) Spring formed colonies throughout the colony and grew naturally, but now it remains only in some sections. It was found that the Selaginella involvens (Sw.) Spring colony was damaged by artificial and natural factors, and as an artificial factor, the Selaginella involvens (Sw.) Spring was proven to be effective for medicinal and cremation, and many people were damaging the Selaginella involvens (Sw.) Spring colony without permission. Naturally, vines thrive and Selaginella involvens (Sw.) Spring die, and the reality is that the entire colony of Selaginella involvens (Sw.) Spring is in danger of being damaged if maintenance is not performed. On the other hand, there are sections that reproduce with symbiosis with some herbaceous plants, so it is necessary to plan and implement conservation strategies. In order to preserve the Selaginella involvens (Sw.) Spring colony, CCTV is needed to prevent artificial damage, and on the contrary, install facilities such as fences can easily burn up and create worse scenery, so it can preserve the good environment, restore recoverable areas, and install supplementary buffer zones.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.153-173
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• 2022

This study analyzes yelp's online restaurant reviews written in 2019 and explores the factors influencing the decision of the usefulness for online reviews in the restaurant consumption decision process. Specifically, factors expected to affect review usefulness are classified according to the Elaboration Likelihood model. Also, it is assumed that the price range of the restaurant would have a moderating role. For the analysis, datasets provided by yelp.com in February 2020 are used. Among the datasets, online reviews of businesses located in Nevada in the US and belonging to the Food and Restaurant categories are targeted. As a result of the negative binomial regression analysis, it is confirmed that the central cues including review depth and readability and the peripheral cues including review consistency, reviewer popularity, and reviewer exposure positively affect the review usefulness. It is also confirmed that the influences of antecedents that affect the review restaurant prices moderate the effect of the central and peripheral cues on the review usefulness. It also provides implications for the need for price-differentiated review management strategies by review platforms and restaurant businesses.

• Korea Trade Review
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• v.42 no.5
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• pp.113-136
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• 2017

New product preannouncement through global supply chain management and international strategic alliances is a critical issue for firm's survive and gaining the competitive advantage in the global smart-phone market. To identify the impact of exploration alliance and exploitation alliance on the short-term's Firm Performance, respectively, This study implemented the event study and the cross sectional regression analysis, focusing on the case of Galaxy Note series. Research results identified that new technologies by exploration alliance and the existing technologies through exploitation alliance have a positive effect on the short-term's performance of vendors related. Furthermore, information for the new products showed higher the excess earning rate than information related to the existing technologies. This implies the firms that provides new technologies have a stronger innovative ability than the companies serving the existing technologies, recognizing as a positive signal in the market. Finally, this study implicates that new technologies by exploration alliance enhances innovative abilities from new product preannouncement, and is a critical variable that can determines whether to survive in the market.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.241-265
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• 2023

A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.849-857
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• 2008

Technology roadmapping is one of the widely used technology planning methodologies. Using a technology roadmap, the researchers can increase the possibility of the project success by systematic management of research contents, budgets, and commercialization strategies. Currently, Ministry of Land, Transport and Maritime Affairs has a plan to increase the research fund to improve the construction industry. As a result, the number of long term research projects with more than five years of research period, is increasing. This entails the need for a methodology for the systematic planning and management of research. However, the construction industry has the characteristics that the research results should ultimately be implemented in an outdoor environment. Through processes of diverse literature reviews, questionnaire-based survey, and pilot research, this paper presents a systematic procedure for the development of construction technology roadmaps, which can consider the unique nature of the construction industry. Based on the procedure, a technology roadmap for intelligent construction monitoring is also developed.

• The Korean Journal of Franchise Management
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• v.3 no.1
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• pp.73-91
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• 2012

This study is in the purpose for the revitalization of traditional market as comparing to the relevancy between the central characteristics of a floating population going around for buying something or eating food and lots of small-sized businesses comprising of the commercial districts. The several traditional markets such as Cheonan station, Dujeong-dong, Sinbu-dong in Cheon-An city has been investigated repeatedly almost every two or three years by the Small Enterprise development Agency(SEDA) since 2001. By analyzing the raw data of those commercial districts made by SEDA, we can calculate the number of firms andthe ratio of business type of each commercial districts. In this research, the type of each business is classified into four groups such as restaurant, service, retail and the rest. Moreover, the central character of the floating population is derived from the raw data, which means the customer information about sex, age structure or the most populous time zones. From these characteristics, one commercial districts has his own specific features distinguishing from the others. The most important differences of past researches are firstly the dynamic viewpoint rather than a static one. Secondly it suggests that the relation between the central characteristics of districts and the floating population would exist. Lastly, it suggests that the interaction between both of them have a significant effect on the growth or decline of the districts and the rates of business type, other adjacent commercial districts as well. Eventually, this study provides several meaningful points for the revitalization of commercial districts to government or stakeholder such as management organization, business owners and new starter etc.

• Convergence Security Journal
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• v.22 no.2
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• pp.115-120
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• 2022

This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

• The Journal of Bigdata
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• v.8 no.1
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• pp.83-97
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• 2023

Project evaluation is the process of evaluating the progress and results of a project. Smart city projects can be divided into system components (infrastructure, services, platforms), or projects can run simultaneously for multiple services. In addition, services are developed and expanded through additional projects. In order to ensure that the smart city, which is composed of various projects, proceeds in accordance with the goals and strategies, periodic project evaluation is required during the project implementation process. The smart city project evaluation system proposed in this paper is designed to provide comprehensive and objective indicators by reflecting various factors that must be considered for projects occurring in all stages of planning, design, construction, and operation of smart cities. The indicators derived from the evaluation system can be used by decision makers to determine the direction of smart city project development. In addition, it is designed so that the performance of the project can be evaluated interim before the end of the project and the feedback obtained from it can be reflected. To introduce the application method of the smart city project evaluation system proposed in this study, the evaluation system developed in this study was applied to the smart city project case of Incheon Free Economic Zone (IFEZ). Based on the evaluation results, items that can maximize the improvement effect of each smart city project item were presented, and the direction of smart city project implementation was suggested. By utilizing a smart city project evaluation system that reflects the characteristics of smart city projects that are composed of multiple projects, comprehensive planning and management of smart city projects will be possible, and this study will serve as a reference for identifying priority improvement factors for projects.