• Journal of Christian Education in Korea
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• v.74
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• pp.273-294
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• 2023

The purpose of this study is to use K-MOOC, which has limitations in utilization because it is centered on theory delivery, to derive tasks to activate the teaching methods of instructors, and to implement the derived tasks using the metaverse platform. to develop a prototype. According to the purpose of the study, the study was conducted as follows. First, from October 4 to November 15, 2022, a Delphi survey was conducted on 21 experts with experience of consulting, research, class development, and operation related to the K-MOOC project. Second, in order to realize the tasks in the teaching method field derived from the Delphi survey, matching with the teaching method class model elements to result of Delphi survey was applied was carried out. Finally, based on the results of expert Delphi and the elements of the class model applicable to the metaverse platform, a teaching method was developed. Through the process of the study, a total of 16 detailed items were derived for the teaching method-related tasks for the activation of K-MOOC: support strategic tasks, teaching method competency, aspect of class design, evaluation and sharing of learning outcomes. By applying the metaverse, the teaching model elements for K-MOOC revitalization were derived from four categories: self-directed repetition, individualized problem solving, practice opportunity expansion, and immediate feedback, and matched with the first 16 detailed items. A four-step teaching model was completed: course attendance (step 1), mission analysis by individual level (step 2), sharing of mission solutions (step 3), and mission evaluation and feedback (step 4). Through the results of this study, the possibility of using the metaverse as a teaching practice platform was confirmed even in terms of the introduction and development of specialized techniques.

• The Korean Journal of Franchise Management
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• v.2 no.1
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• pp.134-151
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• 2011

The strategy for brand alliance is a new type of franchise to iron out the problems like the hotel restaurant's structural contradiction and decreasing profits caused by keen competition with external restaurants. This study is purposed to present the decisive factors for the brand alliance throughexamining the correlations between the brand restaurant designation standards and the expected effects from local low- and mid-priced hotel's brand alliance. The questionnaires were distributed to instructors and professors who have experience in teaching the food and beverage sections at college's hotel and tourism departments and 100 specialists at managerial level of a hotel's food and beverage parts.This survey was conducted for 20 days from December 2 to 22, 2004 and analyzed by independent t-test and canonical correlation analysis. The findings of this survey are as follows.Firstly, the service of the expected effect factors of the brand alliance was recognized relatively high by the specialists in hotel industry, while the sales effect factor of restaurant designation standards was recognized higher by the academic experts.The specialists of the hotel industry recognized the factors of menu and corporate culture higher than the academic experts. Secondly, the entire factors of the brand restaurant designation standards showed a correlation with the whole factors of the restaurant designation standards.In particular, the 'menu' factor presented the most influential to the expected effects of brand alliance.The factors of 'risk reduction' and 'synergy effect' exerted the strongest effect on the restaurant designation standards, which indicated the mutual correlation between the expected effect of brand alliance and the restaurant designation standards. Based on this study, the correlation between the expected effect of brand alliance and brand restaurant designation standards may play a primary role to choose a partner for the brand alliance, a decisive factor for the success.The execution of the brand alliance or the method to designate the alliance partner may vary from the hotel's desirable effects when the brand alliance is determined.In other words, the partner designation standards should be corresponding to the expected effects from the brand alliance between hotel and brand restaurant, and the academic and industrial experts' perceived differences in the expected effects of brand alliance and restaurant designation standards should be clarified to display the direction of decision-making and find the potential risks.

• The Journal of Bigdata
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• v.7 no.2
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• pp.153-172
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• 2022

Online shopping has transformed and rapidly grown the entire market at the forefront of wholesale and retail services as an effective solution to issues such as digital transformation and social distancing policy (COVID-19 pandemic). Small business owners, who form the majority at the center of the online shopping industry, are constantly collecting policy changes and market trend information to overcome these problems and use them for marketing and other sales activities in order to overcome these problems and continue to grow. Objective and refined information that is more closely related to the business is also needed. Therefore, in this paper, through the collection and analysis of big data information, which is the core technology of digital transformation, key variables are set in product classification, sales trends, consumer preferences, and review information of online shopping malls, and a method of using them for competitor comparison analysis and business sustainability evaluation has been prepared and we would like to propose it as a service. If small and medium-sized businesses can benchmark competitors or excellent businesses based on big data and identify market trends and consumer tendencies, they will clearly recognize their level and position in business and voluntarily strive to secure higher competitiveness. In addition, if the sustainable growth of the online shopping mall operator can be confirmed as an indicator, more efficient policy establishment and risk management can be expected because it has an improved measurement method.

• Smart Media Journal
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• v.12 no.5
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• pp.36-45
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• 2023

Recently, in digital agriculture, the types and utilization of greenhouses based on IoT are spreading, and greenhouses are being modernized, enlarged, and even factoryized using smart technology. However, a specific standardization plan has not been proposed according to the equipment for data collection in the smart greenhouse and the size or shape of the greenhouse. In other words, there is a lack of standard data for facility equipment, such as the type and number of sensors and equipment according to the size of the greenhouse, the type of greenhouse construction film and materials suitable for crops and carbon neutrality. Therefore, in this study, the suitability of the implementation, installation and quantity of IoT equipment for data collection was tested, and some standard technologies were presented through the implementation of data collection and communication methods. In addition, impact strength, tensile, tear, elongation, light transmittance, and lifespan issues for PE, PVC, and EVA, which account for about 90% of existing greenhouses, were presented, and the shape, size, and environmental problems of greenhouses made of films were presented. presented in the text. In this research paper, a standardized carbon-neutral modular smart greenhouse using nano-material film was implemented as a solution to environmental problems such as greenhouse size, farm crop type, greenhouse lifespan, and film, and its performance with existing greenhouses was analyzed and presented. Through this, we propose a modularized greenhouse that can be expanded or reduced freely without distinction in the size of the greenhouse or the shape of farmhouse crops, and the lifespan is extended and standardized. Finally, the average characteristics of greenhouses using existing PE, PVC, and EVA films and the characteristics of greenhouses using new carbon-neutral nanomaterials are compared and reviewed, and a plan to implement an expandable IoT greenhouse that supports carbon neutrality is proposed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.389-394
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• 2023

In recent years, use of machine automation is rising in the industry. Ships also obtain machine condition information from sensor as digital information. However, on ships, crew members regularly surveil the engine room to check the condition of equipment and their information through analog gauges. This is a time-consuming and tedious process and poses safety risks to the crew while on surveillance. To address this, engine room surveillance using an autonomous mobile robot is being actively explored as a solution because it can reduce time, costs, and the safety risks for crew. Analog gauge reading using an autonomous mobile robot requires digitization for the robot to recognize the gauge value. In this study, image processing techniques were applied to achieve this. Analog gauge images were subjected to image preprocessing to remove noise and highlight their features. The center point, indicator point, minimum value and maximum value of the analog gauge were detected through image processing. Through the straight line connecting these points, the angle from the minimum value to the maximum value and the angle from the minimum value to indicator point were obtained. The obtained angle is digitized as the value currently indicated by the analog gauge through a formula. It was confirmed from the experiments that the digitization of the analog gauge using image processing was successful, indicating the equivalent current value shown by the gauge. When applied to surveillance robots, this algorithm can minimize safety risks and time and opportunity costs of crew members for engine room surveillance.

• 한국노년학
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• v.31 no.2
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• pp.277-290
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• 2011

The present study examined the impact of work stress and job satisfaction on intention to leave among staff including social workers, nurses, and care workers. The study subject included 235 staff in a welfare organization that provides long-term care services. Data was analyzed using multiple linear regression. The findings of the study show that work stress and job satisfaction affect intention to leave in the context of welfare organizations. Demographic variables were not the main focus of this study and thus these results are incidental. Staff with higher levels of work stress were more likely to think about leaving, while those with grater job satisfaction were less likely. There were several limitations in this study. Generalizability of the findings are limited to staff working in the province of Jeonnam. The results have important implications for the development of strategies to minimize turnover intention in long-term care. Reducing the intent to leave is desirable for issues of both cost reduction and quality of care. Managers could perhaps start to consider decreasing work overload assigned to staff. This study also provides some insight into the work status of new staff. Clearly this finding needs to be explored in further research studies. A more comprehensive model is likely required to adequately explain intention to leave the job.

• Asia Marketing Journal
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• v.11 no.3
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• pp.57-89
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• 2009

This study aims to shed light on the new insights on the cross-buying intentions in the banking industry and suggests an integrated model of the cross-buying intentions. Recently with globalization in the financial sector, financial companies are trying to retain current customers and attract new one by developing various financial products. In South Korea, this trend is especially apparent in the banking sector. Cross-selling of various financial products such as beneficiary certificates, bankasurance and etc. is becoming more important in retaining competitive advantage in Korean banking industry. However, there are few studies which are trying to find out the factors affecting cross-buying intentions and explain their interrelationships comprehensively. Based upon the previous studies, this study finds out the factors affecting cross-buying intentions and classifies them into two dimensions: affective and instrumental. Affective dimension includes trust, satisfaction and commitment. Instrumental dimension includes the factors such as geological convenience, one-stop convenience, professionality, and direct mail. The results from this study are as follow. All the factors in the affective dimension(trust, satisfaction and commitment) have significant impacts on cross-buying intentions. Also all the factors in the instrumental dimension(geological convenience, one-stop convenience, professionality, and DM) significantly affect cross-buying intentions. Some implications of this dissertation are as follow; First, this study identifies the antecedents of cross-buying intentions comprehensively. Second, this paper provides practical guidelines for the banks attempting to intensify cross-selling activities. Third, banks need to develop sophisticated plans which can consolidate the emotional ties with customers through positive service experiences as the affective dimension is important in influencing cross-buying intentions. Finally, regarding the instrumental dimesnion, the implications are: 1) Developing various new financial products in addition to traditional product such as deposits and installment savings for improving customer convenience, 2) Enhancing the professionality of employees by strengthening education programs on numbers of financial products, 3) Increasing cross-buying intentions through the DM.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.206-223
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• 2023

The introduction of Smart technologies such as Artificial Intelligence(AI) systems are have a powerful impact in a variety of industry fields. Some experts predict that smart technology will completely change people's daily life and work styles, causing technological innovation, productivity improvement, and discovery and emergence of new fields. On the one hand, this vision cannot ignore negative views and concerns. Despite many social debates about employment, such as job loss and rising unemployment, there have not been many studies based on employee experience that provide a fundamental solution to the conflict between AI and employment. Therefore, this study finds out the effects and related factors of AI concierge robots for hotel employees, focusing on the hotel industry, and how employees' perceptions of AI concierge robots affect user resistance and turnover intention. This study, conducted a questionnaire survey of 322 hotel employees who had experience working with AI concierge robots in China, and used SPSS and SmartPLS statistical analysis programs to draw conclusions. We found that hotel employees' perceptions of AI concierge robots were significantly related to user resistance and turnover intention, and this association was related to employee self-efficacy, perceived organizational support, quality of AI services and new tasks. In addition, it was found that the quality of AI concierge robots directly or indirectly had the greatest influence on user resistance and turnover intention. The findings of this study provide theoretical implications for academia and practical implications for industry practitioners.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.70-96
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• 2023

Recently, the high turnover rate of nursing staff and the problems caused by increased job stress have been highlighted as social issues, and the problem of 'Taeoom' in nursing organizations has received increasing attention. Therefore, the purpose of this study is to propose a solution to the Taeoom problem, including bullying in the nursing work environment, as there is an urgent need to find a solution to prevent and overcome this problem. For this purpose, based on the S-O-R framework and previous studies, job stress and turnover intention were derived as outcome variables of Taeoom and communication competence as an antecedent factor, and a research model was constructed with the expectation that mindfulness and social support would serve as moderating variables to help overcome this problem. Data were collected through a survey of 300 nurses who had experienced Taeoom within the past year, and the hypotheses were tested using a structural equation model. The results revealed that the higher the communication competence of nurses, the less they perceived the damage of Taeoom, and that the damage caused by Taeoom leads to turnover intention through high job stress. In addition, mindfulness and social support significantly attenuated the positive effects of burnout on job stress and job stress on turnover intention, respectively. The significance of this study is that it proposed an extended P-S-O-R framework by adding a prevention stage to the existing S-O-R framework, and further tested the moderating effects of mindfulness and social support variables. It is expected that the findings of this study will provide concrete guidelines to prevent and overcome the Taeoom problem that can be applied in practice.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.185-198
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• 2023

In marine seismic surveys, the inevitable occurrence of trace gaps in the near offset resulting from geometrical differences between sources and receivers adversely affects subsequent seismic data processing and imaging. The absence of data in the near-offset region hinders accurate seismic imaging. Therefore, reconstructing the missing near-offset information is crucial for mitigating the influence of seismic multiples, particularly in the case of offshore surveys where the impact of multiple reflections is relatively more pronounced. Conventionally, various interpolation methods based on the Radon transform have been proposed to address the issue of the nearoffset data gap. However, these methods have several limitations, leading to the recent emergence of deep-learning (DL)-based approaches as alternatives. In this study, we conducted an in-depth analysis of two representative DL-based studies to scrutinize the challenges that future studies on near-offset interpolation must address. Furthermore, through field data experiments, we precisely analyze the limitations encountered when applying previous DL-based trace interpolation techniques to near-offset situations. Consequently, we suggest that near-offset data gaps must be approached by extrapolation rather than interpolation.