Background: In modern society, the importance of Public Design has become increasingly significant in contributing to the enhancement of urban functionality and the quality of life of citizens. Smart Public Facilities have played a pivotal role in enriching user experience by improving accessibility, convenience, and safety, and in elevating the value of the city. This research recognizes the importance of Public Facilities and explores the potential of Smart Public Facilities in solving urban challenges and progressing towards sustainable and Inclusive cities. Method: The literature review comprehensively examines existing theories and research results on Smart Public Facilities. The case study analyzes actual examples of Smart Public Facilities implemented in cities both domestically and internationally, drawing out effects, user satisfaction, and areas for improvement. Through analysis and discussion, the results of the case studies are evaluated, discussing the potential development of Smart Public Facilities. Results: Smart Public Facilities have been found to bring positive changes in various aspects such as urban management, energy efficiency, safety, and information accessibility. In terms of urban management, they play a crucial role in optimization, social Inclusiveness, environmental protection, fostering citizen participation, and promoting technological innovation. These changes create a new form of urban space, combining physical space and digital technology, enhancing the quality of life in the city. Conclusion: This research explores the implications, current status, and functions of Smart Public Facilities in service and design aspects, and their impact on the urban environment and the lives of citizens. In conclusion, Smart Public Facilities have brought about positive changes in the optimization of urban management, enhancement of energy efficiency, increased information accessibility, User-Centric design, increased interaction, and social Inclusiveness. Technological innovation and the integration of Public Facilities have made cities more efficient and proactive, enabling data-based decision-making and optimized service delivery. Such developments enable the creation of new urban environments through the combination of physical space and digital technology. The advancement of Smart Public Facilities indicates the direction of urban development, where future cities can become more intelligent, proactive, and User-Centric. Therefore, they will play a central role in Public Design and greatly contribute to improving the urban environment and the quality of life of citizens.
On October 31, 2023, the revision of the Medical Technologist Act made it mandatory to complete field training courses in order to obtain a license as a radiologic technologist. Therefore, we would like to survey the actual situation of field training in medical institutions to inform the revised Medical Technologist Act and propose improvement measures to increase the effectiveness of field training. A survey was conducted from March to April, 2023, among radiologic technologists working in medical institutions. The questionnaire was sent through a form on a domestic portal site, Company N, and 120 respondents completed it. Eighty-two respondents, or 68.3 percent, had experience in educating on-the-job training students. 58% of the respondents were aware of the fact that the amendment to the Act on Medical Technologist etc. made field training mandatory to obtain a radiologic technologist license. In accordance with Article 9 of the Medical Technologist Act, which prohibits unlicensed persons from practicing, 50% of the respondents were aware that those who are in training to complete an education course equivalent to the license they are seeking to obtain at a university or other institution are allowed to practice as medical Technologists. When asked what is currently taught during fieldwork, 6% of respondents said that they are required to perform radiation-generating activities in addition to observing, guiding patients, and positioning and moving patients. When asked about the future direction of education as fieldwork becomes mandatory for licensure, 77% of respondents said that they will teach more than they currently do. When asked about the appropriate total length of fieldwork, 35% said 12 weeks and 480 hours, 33% said 8 weeks and 320 hours, and 27% said 16 weeks and 640 hours. It can be seen that the current on-the-job training is inadequate according to various regulations, and students' satisfaction is low. However, with the revision of the Act on Medical Technologists, field training has become mandatory to obtain a license as a radiologist, and it is necessary to improve the educational conditions of field training. Therefore, it is necessary to comply with the Nuclear Safety Act and the Rules on the Safety Management of Diagnostic Radiation Generating Devices, introduce standardized training objectives and evaluation systems, designate training hospitals and radiologists in charge of training, and introduce extended training periods and simulation exercises to internalize field training.
The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.
Introduction As consumers' purchase behavior change into a rational and practical direction, the discount store industry came to have keen competition along with rapid external growth. Therefore as a solution, distribution businesses are concentrating on developing PB(Private Brand) which can realize differentiation and profitability at the same time. And as improvement in customer loyalty beyond customer satisfaction is effective in surviving in an environment with keen competition, PB is being used as a strategic tool to improve customer loyalty. To improve loyalty among PB users, it is necessary to develop PB by examining properties of a customer group, first of all, quality level perceived by consumers should be met to obtain customer satisfaction and customer trust and consequently induce customer loyalty. To provide results of systematic analysis on relations between antecedents influenced perceived quality and variables affecting customer loyalty, this study proposed a research model based on causal relations verified in prior researches and set 16 hypotheses about relations among 9 theoretical variables. Data was collected from 400 adult customers residing in Seoul and the Metropolitan area and using large scale discount stores, among them, 375 copies were analyzed using SPSS 15.0 and Amos 7.0. The findings of the present study followed as; We ascertained that the higher company reputation, brand reputation, product experience and brand familiarity, the higher perceived quality. The study also examined the higher perceived quality, the higher customer satisfaction, customer trust and customer loyalty. The findings showed that the higher customer satisfaction and customer trust, the higher customer loyalty. As for moderating effects between PB and NB in terms of influences of perceived quality factors on perceived quality, we can ascertain that PB was higher than NB in the influences of company reputation on perceived quality while NB was higher than PB in the influences of brand reputation and brand familiarity on perceived quality. These results of empirical analysis will be useful for those concerned to do marketing activities based on a clearer understanding of antecedents and consecutive factors influenced perceived quality. At last, discussions about academical and managerial implications in these results, we suggested the limitations of this study and the future research directions. Research Model and Hypotheses Test After analyzing if antecedent variables having influence on perceived quality shows any difference between PB and NB in terms of their influences on them, the relation between variables that have influence on customer loyalty was determined as Figure 1. We established 16 hypotheses to test and hypotheses are as follows; H1-1: Perceived price has a positive effect on perceived quality. H1-2: It is expected that PB and NB would have different influence in terms of perceived price on perceived quality. H2-1: Company reputation has a positive effect on perceived quality. H2-2: It is expected that PB and NB would have different influence in terms of company reputation on perceived quality. H3-1: Brand reputation has a positive effect on perceived quality. H3-2: It is expected that PB and NB would have different influence in terms of brand reputation on perceived quality. H4-1: Product experience has a positive effect on perceived quality. H4-2: It is expected that PB and NB would have different influence in terms of product experience on perceived quality. H5-1: Brand familiarity has a positive effect on perceived quality. H5-2: It is expected that PB and NB would have different influence in terms of brand familiarity on perceived quality. H6: Perceived quality has a positive effect on customer satisfaction. H7: Perceived quality has a positive effect on customer trust. H8: Perceived quality has a positive effect on customer loyalty. H9: Customer satisfaction has a positive effect on customer trust. H10: Customer satisfaction has a positive effect on customer loyalty. H11: Customer trust has a positive effect on customer loyalty. Results from analyzing main effects of research model is shown as