Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.16
no.6
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pp.157-175
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2021
This study categorized 3,214 companies out of the tech firms supported by the Korea Technology Finance Corporation's "technology guarantee scheme" through technology assessment from 2017 to 2019 into Fourth Industrial Revolution-related companies and general SMEs. The impact of the management characteristics of these 1,752 tech firms on the determination of high-growth firms was then empirically analyzed. This study used the OECD(2007) definition to define a "high-growth firm" as "an enterprise with average revenue growth greater than 20% per annum, over a two-year period." As the two sample groups showed non-normal distribution, this study conducted the Mann-Whitney U test, a nonparametric test, to analyze the mean differences and bivariate logistic regression in which the normality assumption is less stringent. The independent variables include fundamental characteristics; a regional dummy; a technological level dummy; and the capabilities of company representatives, human capital, and technological innovation. The corresponding sub-variables are representatives' level of education and experience in the same industry, full-time workers, research personnel, the extent of intellectual property rights, investment in research and development, firm age, total assets, region_metropolitan area, region_central region, technological level_high technology, and technological level_medium technology. As a result, the research hypothesis about representatives' level of experience in the same industry, full-time workers, total assets, and technological level_high technology was supported for the Fourth Industrial Revolution-related companies. For the general SMEs, the research hypothesis about representatives' level of experience in the same industry, research personnel, total assets, and region_metropolitan area was supported.
The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.
This study investigates the recommendation for tax accounting services used in many companies. In particular, it aims to create guidelines for small businesses with fewer than 100 employees, which are relatively difficult to manage in terms of cost or time. We surveyed 100 corporate officials on basic business information, such as the number of employees, job titles, and business type, as well as the type of tax accounting service, the recommended score for the service, the reason for the score, and other opinions related to tax accounting services. In particular, the recommendation score seeks to obtain more effective results by using the Net Promoter Score method, which is known to be more effective in understanding customer opinions than general customer satisfaction surveys. The survey revealed a Net Promoter Score for a recommendation of -33 points, lower than the general Net Promoter Score. It also indicated that tax accounting services need improvement. Specifically, the opinions of the respondents who gave a non-recommendation score were as follows: "Not inconvenient or comfortable," "It was just okay," "I don't know if it would be helpful," and "There is no differentiation and there are no special alternatives." We concluded that an improved service for raising recommendation scores was necessary. This survey focused on recommendations for companies with fewer than 100 employees; future studies should incorporate larger companies and more variables.
Wee Seong Seung;Lee MinCheol;Kim Jin Min;Shin Yong Tae
KIPS Transactions on Software and Data Engineering
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v.12
no.3
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pp.117-124
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2023
Through reorganization in 2008, The ministry of Agriculture, Food and Rural Affairs integrated management of the food industry by transferred functions which was scattered in the Ministry of Health and Welfare, and established comprehensive policies covering the primary, secondary, and tertiary industries. In the agricultural industry sector, new business concepts such as smart farm and food tech have recently emerged alongside the fourth industrial revolution. In order for the Ministry of Agriculture, Food, and Rural Affairs to develop appropriate policies for the fourth industrial revolution, it is necessary to accurately estimate the size of agricultural and livestock-related businesses. In 2017, the Ministry of Agriculture, Food, and Rural Affairs initiated research for the agriculture, livestock and food industry's special classification, which was approved by the National Statistical Office in 2020. The estimation of the agriculture, livestock and food industry's size based on special classification is crucial because it has a substantial impact on the formulation and significance of policies. In this paper, the appropriate rate was derived from samples extracted from the special classification and the Korean standard industrial classification. Proposed are a method for estimating the population of the agricultural and livestock food industry, as well as a method for calculating the appropriate rate that more accurately reflects the population than the method currently in use.
Due to the recent and rapid globalization, logistics outsourcing has expanded globally and is seen as a means of creating a robust logistics system. However, many businesses continue to have difficulties with their logistics outsourcing contracts, which compels them to reinstate the logistics function for internal management. This study aims to investigate how organizational capabilities of logistics service providers (LSPs), notably flexibility, integration, innovation, and technological capabilities, impact on the logistics outsourcing success in Ugandan food processing firms. Using a structured questionnaire survey, cross-sectional data collected from 211 food processing firms in Kampala - Uganda were analyzed by partial least squares-structural equation modeling (PLS-SEM) using SmartPLS 3.3.7 software to examine the theorized relationships. The study findings revealed that whereas the technological and innovation capabilities positively and significantly influence logistics outsourcing success, the effects of flexibility and integration capabilities were insignificant. Additionally, the importance-performance map analysis (IPMA) reveals that the technological capability is a priority capability, followed by the innovation capability if logistics outsourcing success is to be achieved. Conversely, flexibility and integration capabilities are of low priority.
Personal service robots, a type of social robot that has emerged with the aging population and technological advancements, are undergoing a transformation centered around technologies that can extend independent living for older adults in their homes. For older adults to accept and use social robot innovations in their daily lives on a long-term basis, it is crucial to have a deeper understanding of user perspectives, contexts, and emotions. This research aims to comprehensively understand older adults by utilizing a mixed-method approach that integrates quantitative and qualitative data. Specifically, we employ the Van Kaam phenomenological methodology to group conversations into nine categories based on emotional cues and conversation participants as key variables, using voice conversation records between older adults and social robots. We then personalize the conversations based on frequency and weight, allowing for user segmentation. Additionally, we conduct profiling analysis using demographic data and health indicators obtained from pre-survey questionnaires. Furthermore, based on the analysis of conversations, we perform K-means cluster analysis to classify older adults into three groups and examine their respective characteristics. The proposed model in this study is expected to contribute to the growth of businesses related to understanding users and deriving insights by providing a methodology for segmenting older adult s, which is essential for the future provision of social robots with caregiving functions in everyday life.
The Journal of the Korea institute of electronic communication sciences
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v.18
no.4
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pp.701-708
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2023
Local governments are required to take measures to prevent occupational accidents under Articles 4(2) and 4(3) of the Occupational Safety and Health Act, and this study suggested the necessity of establishing an IT-based integrated safety and health information sharing system for serious accident reduction and safety and health management through the case of Incheon Metropolitan City. Recently, as local governments have established labor and health ordinances and basic plans, the need for an independent integrated safety and health management system based on local industrial characteristics has increased. It is necessary to establish a cooperation and support system with basic local governments and hub institutions, share integrated safety and health information with related institutions and organizations, and play a pivotal role in regional safety and health management by managing occupational accident statistics and implementing basic policies. The system through local governments' safety and health management will reduce serious accidents in the region, and the comprehensive safety and health management system for small businesses and projects ordered by local governments will strengthen the operability of the site, which will be effective in preventing critical accidents and industrial accidents.
Journal of the Korea Society of Computer and Information
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v.28
no.8
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pp.175-186
/
2023
In this paper, we aim to build a gentrification analysis model and examine its characteristics, focusing on the point at which rents rose sharply alongside the recovery of commercial districts after the gradual resumption of daily life. Recently, in Korea, the influence of social distancing measures after the pandemic has led to the formation of small-scale commercial districts, known as 'hot places', rather than large-scale ones. These hot places have gained popularity by leveraging various media and social networking services to attract customers effectively. As a result, with an increase in the floating population, commercial districts have become active, leading to a rapid surge in rents. However, for small business owners, coping with the sudden rise in rent even with increased sales can lead to gentrification, where they might be forced to leave the area. Therefore, in this study, we seek to analyze the periods before and after by identifying points where rents rise sharply as commercial districts experience revitalization. Firstly, we collect text data to explore topics related to gentrification, utilizing LDA topic modeling. Based on this, we gather data at the commercial district level and build a gentrification analysis model to examine its characteristics. We hope that the analysis of gentrification through this model during a time when commercial districts are being revitalized after facing challenges due to the pandemic can contribute to policies supporting small businesses.
Journal of the Korean Regional Science Association
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v.39
no.3
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pp.13-34
/
2023
Jeju is making multifaceted efforts to foster and attract businesses in order to increase its GRDP, which is only at the level of 1% nationwide. A firm's choice of location selection is such a significant decision that it can affect the growth of the firm. The concentration of firm locations in one region means that the characteristics of the region conduce to corporate profit maximization. Therefore, the analysis of the characteristics of regions preferred by firms and the reflection of the results thereof in policies for attracting firms will be helpful in inducing regional innovation and development. This study investigates the distribution of firm locations in Jeju, and analyzes the effects of regional characteristics on the determination of firm location by using the conditional logit model. The analysis results indicate that Jeju has various kinds of firms concentrated, regardless of the industry type, and a large economically active population in thinly populated areas. Additionally, firms in the knowledge-based industry tend to locate in areas where more firms in the same field are located in Jeju. This study is significant in that it is the basic analysis of the determinants of firm location in Jeju, which has never carried out, for the purpose of establishing policies for firm and industry promotion and local development in Jeju.
The Journal of the Convergence on Culture Technology
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v.9
no.1
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pp.183-190
/
2023
This study is a study on the effect of university students' entrepreneurship education service quality on educational satisfaction and entrepreneurship intention. Although various entrepreneurship education is being operated at universities, there is not much research on entrepreneurial intentions. In this study, in order to analyze the factors for increasing the entrepreneurial intention, the effect of the service quality of entrepreneurship education on educational satisfaction and entrepreneurial intention was examined. In order to achieve the purpose of this study, questionnaires were distributed to university students in Daegu and Gyeongbuk, and statistical analysis of 298 questionnaires that were faithfully answered was conducted using SPSS 22. TA is a result of multiple regression analysis on the effect of start-up education service quality on educational satisfaction, tangibility, responsiveness, certainty, and empathy had a significant effect, but reliability did not have a significant effect, and educational satisfaction had a significant effect on entrepreneurship intention. Recently, start-up businesses in Korea have been revitalized, and various programs such as start-up education, start-up support policies, and commercialization support are emerging. Since the quality of educational service for start-up at universities affects the will to start a business, service quality capabilities should be strengthened to increase educational satisfaction.
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