• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.135-152
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• 2018

Purpose: This study attempted to analyze how the ego state of flight attendants affects their job satisfaction and customer orientation using Berne's (1966) transactional analysis and further compare the difference between job satisfaction and customer orientation depending on demographic characteristics, position, and ego state. Methods: The data was collected by using the structured questionnaires to flight attendant of major airline companies. The proposed research model is tested using 164 valid questionnaires using SPSS 23 and Smart PLS 2. Results: This research indicated the only free child ego sate among ego state factors of flight attendant was found to have a positive impact on job satisfaction. In the relationship between ego states and customer orientation, all ego state factors were found to have a significant influence on customer orientation. Conclusions: The study offered a theoretical and empirical foundation for future research by empirically identifying the relationship between ego state factors and customer orientation in the in-flight service and suggested the strategic implications to increase job satisfaction and customer orientation based on the psychology and ego state of flight attendant.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.152-159
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• 2021

Small local businesses such as corner shops and street markets have been severely impacted by the COVID-19 pandemic and declining consumption. A community currency is a local currency that can be used to exchange for one of the local currencies within an online community. Community currencies can be effective not only in supporting small businesses, but also in helping the local economy more vibrant, benefiting consumers in the community. An important goal of Community Currency is to foster a vibrant local economy by building mutually beneficial relationships between local business owners and customers. The purpose of this study was to identify how the existing community currencies of participating SMEs and self-employed in Seoul and Gyeonggi-do metropolitan areas contributed to commercial revitalization by category and to suggest a new or better approach to community currency operation. It also focused on presenting the best solutions for the future direction of mobile community currencies, measures that are better than current currency operations, revitalize the community and develop the economy.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.183-197
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• 2021

Xiaohongshu is called China's Instagram and is leading overseas product purchases and culture sharing. The purpose of this study is to investigate the structural relationship between Xiaohongshu service quality, emotional response perceived by users, and adhesion to confirm the impact on Xiaohongshu's adhesion at a time when non-face-to-face activities due to COVID-19 have increased. This study distributed and collected questionnaires from October 1st to October 7th, 2021, targeting 210 online shopping mall users. The research results were derived from a total of 206 questionnaires, excluding 4 questionnaires such as omission of record contents, and the causal relationship of the existing PAD model was attempted to be reported by revising and supplementing the existing PAD model. As a result of the study, first, it was confirmed that design among service quality had a positive effect only on ventilation during the user's emotional response. Second, it was confirmed that information among service quality had a positive effect on pleasure and ventilation among users' emotional responses. Third, it was found that security among service quality had a positive effect on pleasure among users' emotional responses. Finally, it was found that pleasure and ventilation had a positive effect on adhesion in the user's emotional response. Based on this result, it is expected that it will be used for operation on other online platforms than the plan for the development of Xiaohongshu.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.206-211
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• 2022

As the level of consumption is improved and cultural life is pursued, the consumer's consciousness structure is rapidly changing, and the demand for product selection level, variety, and quality is becoming more diverse. The restaurant economy is falling due to the prolonged COVID-19, the economic recession, income decline, and changes in population structure and lifestyle, but the Meal- kit market is growing rapidly. This study aims to identify the consumer perception of Meal-kit, which is rapidly growing as an alternative to existing meals in the fields of dining out, food, and distribution due to the development of technology and social environment using big data. As a result of the analysis, the keywords with the highest frequency of appearance were in the order of Meal-kit, Cooking, Product, Launching, and Market and were divided into 8 groups through the CONCOR analysis. We want to identify consumer trends related to the key keywords of Meal-kit, present effective data related to Meal-kit demand for Meal-kit specialized companies, and provide implications for establishing marketing strategies for differentiated competitive advantage.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.230-235
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• 2022

This study is to select an optimal object detection algorithm for designing a self-checkout counter to improve the inconvenience of payment systems for products without existing barcodes. To this end, a performance comparison analysis of YOLO v2, Tiny YOLO v2, and the latest YOLO v5 among deep learning-based object detection algorithms was performed to derive results. In this paper, performance comparison was conducted by forming learning data as an example of 'donut' in a bakery store, and the performance result of YOLO v5 was the highest at 96.9% of mAP. Therefore, YOLO v5 was selected as the artificial intelligence object detection algorithm to be applied in this paper. As a result of performance analysis, when the optimal threshold was set for each donut, the precision and reproduction rate of all donuts exceeded 0.85, and the majority of donuts showed excellent recognition performance of 0.90 or more. We expect that the results of this paper will be helpful as the fundamental data for the development of an automatic payment system using AI self-service technology that is highly usable in the non-face-to-face era.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.159-176
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• 2021

In this study, we performed a comparative analysis of the sentiment value for the tourists in USA, China, and Korea on the COVID19 pandemic era to explore and find out the features of the tourists by using online reviews. We collected a total of 243,826 online hotel reviews for metropolitan city and vacation spot in the three countries to compare the features between the business and the vacation trips. We collected the online reviews into the tow groups from Jan. 1, 2019 to Nov. 31, 2019 for before COVID19 pandemic and from Apr. 1, 2020 to Deb 28, 2021 for during COVID19. Online reviews were categorized into 6 dimensions using LDA model. Sentiment analysis were presented for 6 dimensions by utilizing a lexicon base. We proposed an approach to analyzing the importance of each attribute by applying 6-dimensional sentiment values to conjoint analysis. Our empirical analysis showed that the proposed approach could explore and find out the changed features of travelers during the COVID19 pandemic.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.36-40
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• 2022

Many parts of life have been changed due to the unprecedented coronavirus outbreak, and Noncontact has now become a general culture of society around the world. Also, many years later, after the Fourth Industrial Revolution, it is now deeply embedded in the human lifestyle. The purpose of this paper's research is to investigate the metaverse perception before and after Corona. It was confirmed that the number of metaverse, the central keyword, was 70971 before Corona, but 261767 after Corona, which was more than three times the frequency. In addition, it was confirmed that the number of COVID-19, the reference point of this study, increased significantly to 1,9236 during the pre-COVID-19 period. Through this, it can be inferred that the metaverse accelerated and developed significantly after the corona. Metaverse about Keywords such as cryptocurrency, cryptocurrency, coin, and exchange appeared before Corona, and the word frequency ranking for blockchain, which is an underlying technology, was high, but after Corona, the word frequency ranking fell significantly as mentioned above. As such, it was confirmed that keywords for metaverse were changing before and after Corona, and as such, Consumers' perceptions were also changing.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.41-46
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• 2022

The purpose of this study is to confirm and analyze the impact on consumers through big data keyword analysis on weak food. For data collection, web documents, blogs, news, cafes, intellectuals, academic information, and Google Web, news, and Facebook provided by Naver and Daum were used as analysis targets. The data analysis period was set from January 2018 to December 2021. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analyzed and visualized using the Netdraw function among UCINET6 programs. In addition, CONCOR analysis was conducted to derive clusters for similar keywords. As a result of analyzing yakseon food with keywords, a total of 35,985 cases of collected data were derived. Through this, it was confirmed that medicinal food affects consumers. Furthermore, if a business model is created and developed through yakseon food, it will be possible to lead the popularization of yakseon food.

• The Korean Journal of Franchise Management
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• v.14 no.2
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• pp.31-46
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• 2023

Purpose: Brand communication plays an important role in the credibility of consumer behavior as it enhances brand equity. This study investigates the effects of brand communication (firm-created communication, consumer-generated communication) on brand awareness, brand attitude, brand loyalty in the hotel business sector by applying the SOR theory (stimulus-organism-response theory). Research design, data, and methodology: This study was analyzed in a quantitative way using the survey results of 400 customers who had experience of visiting hotels. In this study, SmartPLS 4.0 was used to evaluate the research model. The reliability, convergent validity, and discriminant validity of the measurement tool were verified. Result: Result was found that consumer-generated communications had a positive effect on brand awareness and brand attitude, whereas firm-created communications had a significant effect on brand awareness. In addition, brand awareness had a positive effect on both brand attitude and brand loyalty. Finally, brand attitude was found to have a positive effect on brand loyalty. Conclusions: This study redefines the concept of where chain hotel groups should focus when providing consumers with information about their brands and services. As a result, the conceptual framework of brand communication to increase new customer visits to the hotel brand has been expanded.