• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• The Korean Journal of Archival Studies
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• no.46
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• pp.153-187
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• 2015

This study aims to discuss issues about non-existent information of the information disclosure system and to provide alternative strategies for the issues. For the theoretical discussion it reviews the definitions and standards of non-existent information and analyzes legal aspects and statistical changes of non-existent information. Furthemore, in order to discuss a current status and problems of non-existent information at the central administrative agencies, it analyzes the cases of the non-existent information notification. According to analysis results, non-existent information status of the surveyed institutions is a total of 4,421 cases for three years and it shows the continuous increasing trend year after year. The number of institutions that have the number of non-existent information equal to the number of nondisclosures or over it reached about 40%. It means excluding non-existent information from the reasons of nondisclosure influenced disclose rates and nondisclosure rates of many agencies. In the type analysis of the non-existent information reasons, the most main reason, the case of not producing or receiving the requested information by public institutions takes over 75% among the whole reasons. The next reason is the case of collecting or processing information takes over 7-10%. This study found the operational issues, as analyzing notifications of non-existent information. The operational issues are 1) the incomplete explanation of non-existent information, 2) the unclear scope of the collection and processing, 3) the problem of the transfer processing, and 4) the problem of recording management. Therefore, this study suggested some improvements of the perspective and the technical and procedural aspects. First, information disclosure issues including non-existent information are to be understood as an extension of records management. Second, disclosure service should improve overall based on advanced understanding. Third, the management procedures of non-existent information should be improved. Fourth, specific guidelines for handling non-existent information should be developed.

• Management & Information Systems Review
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• v.37 no.4
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• pp.21-39
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• 2018

Today, Mobile Instant Message (MIM) has become a communication means which is commonly used by many people as the technology on smart phones has been enhanced. Among the services, KakaoGame creates much profits continuously by using its representative Kakao platform. However, even though the number of users of KakaoGame increases and the characteristics of the users are more diversified, there are few researches on the relationship between the characteristics of the SNG users and the continuous use of the game. Since the social capital that is formed by the SNG users with the acquaintances create the sense of belonging, its role is being emphasized under the environment of social network. In addition, game user's concerns about the information privacy may decrease the trust on a game APP, and it also caused to threaten about the game system. Therefore, this study was designed to examine the structural relationships among SNG users' social capital, concerns about the information privacy, flow, SNG reuse intention and recommendation intention. The results from this study are as follow. First of all, the participants' bridging social capital had a positive effect on the flow of an SNG, but the bonding social capital had a negative effect on the flow of an SNG. In addition, awareness of information privacy concern had a negative effects on the flow of an SNG, but control of information privacy concern had a positive effect on the flow of an SNG. Lastly, the flow of an SNG had a positive effect on the reuse intention and recommendation intention of an SNG. Also, reuse intention of an SNG had a positive effect on the recommendation intention. Based on the results from this study, academic and practical implications can be drawn. First, This study focused on KakaoTalk which has both of the closed and open characteristics of an SNS and it was found that the SNG user's social capital might be a factor influencing each user's behaviors through the user's flow experiences in SNG. Second, this study extends the scope of prior researches by empirically analysing the relationship between the concerns about the SNG user's information privacy and flow of an SNG. Finally, the results of this research can provide practical guidelines to develop effective marketing strategies considering them for SNG companies.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.55-69
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• 2021

For the national economic development, the participation of women in the social and economic activities is crucial. The popularization of start-ups, digital transformation, and WEconomy trends have lowered the barriers to opportunities for women to start a business and provide an environment in which women can grow faster. This paper examines the significance and process of success of women entrepreneurs and the characteristics of innovation strategies and achievements by linking the recently changing business environment of a company, factors influencing the success of women entrepreneurship, and innovation activities. To this end, four companies' cases were analyzed in the fields of distribution/service and consumer products/services, which are areas of large investment among female startups. The result shows that women entrepreneurs recognize the meaning of success as creating and continuing to create a 'corporate value through establishing a trust relationship with customers' within the 'balance between personal life and work.' In terms of the business ecosystem, women entrepreneurs strive for 'business activities based on the win-win growth of consumers, producers and sellers' for success, and rather 'focus on the process with a problem-solving approach' rather than achieving performance-oriented goals. Also through excellent power of observation, flexibility, and execution power, women entrepreneurs conduct business by adapting to changing trends. In terms of innovation activities, the innovation strategy of women-led companies puts priority on 'creating the value customers want' and focuses on innovation in the 'customer-centric business model' rather than technological innovation. As such, women-led companies show several differentiated characteristics, which enable them to create corporate value and achieve sustainable growth. The barriers to challenges and opportunities for women to start a business have been lowered, and an ecosystem has been created for female startups to grow. But why are there still so few women entrepreneurs, and the answer to where we need to close these gaps is ultimately a close analysis and investigation of the field. We must present milestones for growth steps through the accumulation of case studies of women startups that have exited. In addition, women can stand as economic agents only when the policy targets are subdivided and specific approaches to child-rearing and childcare for women entrepreneurs must be taken. This paper expects to serve as basic data for follow-up studies and become the basis of research for women entrepreneurs to grow as economic agents.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.4
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• pp.63-76
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• 2022

This study was conducted to compare the perceptions of the park use status, importance, and satisfaction of users in the first implemented and completed Uijeongbu Jikdong Neighborhood Park among the private park special projects carried out as a countermeasure for long-term non-execution of urban parks. To this end, in the initiated project, apartment residents and non-residents were classified according to the promotion plan, and a questionnaire research on importance and satisfaction was conducted to analyze the park use status and IPA(importance-performance analysis). First, as a result of the analysis of the current situation in terms of locational characteristics that occur during the promotion of special projects for private parks, unlike the mountainous areas, the targeted site was close to flat land, indicating that users' satisfaction with the landscape was high. Second, the access of the apartment residents in the initiated project site was easy. Thus, the use rate of residents was relatively higher than that of the non-residents. Third, differences in perception by item were identified through the analysis of IPA and the establishment of strategies. In quadrant I, among the facilities and services, installing restrooms was the priority for residents, and parking facilities and rest facilities were the priority than installing restrooms for non-residents. In quadrant II, overall scores for residents and non-residents were similar, but the distance to the park was in quadrant III due to the low level of satisfaction among non-residents. In this study, the difference in perception between residents and non-residents may cause problems in access and facilities in managing the park in the future. Therefore, it would be necessary to find a way to improve it by establishing a management strategy that takes into account the difference in the perception of residents after construction. In addition, through the results of this study, it was judged that the purpose of park development, the selection of types of parks, and the selection of plans and management indicators for each kind would be significant in the promotion of initiated projects in the planning of park development.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.172-189
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• 2023

This study investigated the potential contribution of ChatGPT, a massive language and information model, in the decision-making process of public design policies, focusing on the characteristics inherent to public design. Public design utilizes the principles and approaches of design to address societal issues and aims to improve public services. In order to formulate public design policies and plans, it is essential to base them on extensive data, including the general status of the area, population demographics, infrastructure, resources, safety, existing policies, legal regulations, landscape, spatial conditions, current state of public design, and regional issues. Therefore, public design is a field of design research that encompasses a vast amount of data and language. Considering the rapid advancements in artificial intelligence technology and the significance of public design, this study aims to explore how massive language and information models like ChatGPT can contribute to public design policies. Alongside, we reviewed the concepts and principles of public design, its role in policy development and implementation, and examined the overview and features of ChatGPT, including its application cases and preceding research to determine its utility in the decision-making process of public design policies. The study found that ChatGPT could offer substantial language information during the formulation of public design policies and assist in decision-making. In particular, ChatGPT proved useful in providing various perspectives and swiftly supplying information necessary for policy decisions. Additionally, the trend of utilizing artificial intelligence in government policy development was confirmed through various studies. However, the usage of ChatGPT also unveiled ethical, legal, and personal privacy issues. Notably, ethical dilemmas were raised, along with issues related to bias and fairness. To practically apply ChatGPT in the decision-making process of public design policies, first, it is necessary to enhance the capacities of policy developers and public design experts to a certain extent. Second, it is advisable to create a provisional regulation named 'Ordinance on the Use of AI in Policy' to continuously refine the utilization until legal adjustments are made. Currently, implementing these two strategies is deemed necessary. Consequently, employing massive language and information models like ChatGPT in the public design field, which harbors a vast amount of language, holds substantial value.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.1
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• pp.59-73
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• 2023

Objective : To examine changes in participation patterns of children with Autism Spectrum Disorder (ASD) in play activities during COVID-19 by reviewing relevant literature. Methods : This scoping review was conducted via five steps. we created a research question and searched for relevant literature published in English through CINAHL, PubMed, ERIC, MEDLINE, Google Scholar and Google search engine. After selecting the literature based on inclusion criteria, data were charted based on 10 items (i.e., author name, journal name, publication year, nation, authors' majors, research method, participant' age and gender as well as quantitative and qualitative results of study). The results were analyzed using descriptive numerical and thematic analyses. Results : After reviewing 437 articles and 152 websites, six articles were included. Theses articles were conducted by experts from various fields and countries. Five themes were highlighted in selected articles: COVID-19 resulted in (1) decreased time of outdoor play, (2) increased play time on screen, (3) increased time spent with family, (4) increased sensory difficulties, and (5) recommendations for services for children with disabilities and during COVID-19. Conclusion : This study suggests telerehabilitation programs about parental behavior strategies in order to solve difficulties in which children with ASD may experience when participating in play activities during disasters. Study results can be used as fundamental evidence to emphasize importance of play activities and to systematize role of occupational therapists and service guidelines for supporting play activities of children with disabilities in disasters.

• Journal of the Korean Society of International Agriculture
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• v.23 no.5
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• pp.465-474
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• 2011

Agricultural environment of Lam Dong province, which is located in central highland area, is totally different from that of other lower areas in Vietnam. In Lam Dong province, abundant plant resources were naturally grown such as pine trees, taxus, and wild orchids, which can grow in high mountainous area. In Lam Dong, the field proportion of perennial crops was higher than that of annual crops. However, the field proportion and yields of vegetables were highest among the all cultivated crops, estimating 38% (36,552ha) and 72% (993,082MT), respectively. Especially in Da Lat, vegetables, flowers, orchids, and industrial crops were mainly produced because this area is geographically close to Ho Chi Minh city. And also in Da Lat, 64% (8,447ha) and 36% (4,777ha) of farm fields were used for producing annual and perennial crops, respectively, and the yields of fresh vegetables in this area was estimated to 213,478MT which was 21.5% of the whole yields in Lam Dong province. Thus Korea, Taiwan, Japan, France, and Holland have invested to agriculture in Da Lat for producing and exporting flowers, vegetables, and tea. In 2009, flower cultivation area of Da Lat was over 55% in Lam Dong province and average amount of values were 9,781 million USD, which was higher than that of al other crops. Thus following strategies could be suggested for the development of agriculture in Lam Dong province. The first, agricultural cooperation with Da Lat, Lam Dong, should be characterized to horticulture and floriculture, followed by supporting both appropriate R&D techniques and equipments. And then agricultural system should be made in relationship with the local companies. Finally, agricultural cooperation program should be conducted toward the direction for both donor and recipient countries.