• Journal of Korea Society of Industrial Information Systems
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• v.22 no.4
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• pp.97-115
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• 2017

The Purpose of this is to Examine the Effects of Collaborative Relations of Supplier- Buyer, Sustainable Supply Chain Management(SCM) Sctivities, and Collaborative Performance in Automobile-part Companies. The Proposed Research Model is Tested using Structural Equation Modeling for Hypotheses based on the Data Collected from 274 Firms. The Results Indicate that Collaborative Relations of Supplier-buyer Positively Affect Sustainable SCM Activities. In Addition, Sustainable SCM Activities Positively Affects Collaborative Performance. The Results of the Study Show that Collaborative Relations of Supplier-buyer is Positively Associated with Sustainable SCM Activities in both Supplier and Buyer Firms. Sustainable SCM Activities have a Significant Impact on Collaborative Performance in both Parts. In Addition, Collaborative Relations of Supplier-buyer have a Significant Impact on Collaborative Performance of Buyer Firms but Supplier. This Study would Provide Useful Information for Collaboration between Supplier and Buyer to have a Long-term Strategic Relationship on Sustainable SCM Activities, which Impact on Collaborative Performance and Competitive Advantages.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.207-221
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• 2022

The shortcomings of the previous Crime Prevention Through Environmental Design (CPTED) theory in practice have led to the limitations of the conventional crime prevention design process. The purpose of this study is to analyze the graftability of the third generation CPTED theoretical framework and the Double Diamond design process from a design perspective. Thus, the third generation CPTED visualization design process is proposed to be grafted with the Double Diamond design process. In the study, the propositions, goals, strategic approaches, and liveability principles of the third-generation theoretical framework are clarified according to the relevant studies by scholars. In addition, the study identifies the limitations of conventional crime prevention design processes in terms of practicality and effectiveness, based on corrections from research in different scientific fields. On this basis, the Framework of Innovation of the British Design Council was used to clarify the benchmarks and foundations for the grafting of the third-generation theoretical framework and the Double Diamond design process. In addition, the details of the grafting are analyzed and explained in terms of phase outputs and phase activities. The significance of the study is that the third-generation CPTED visualization design process, which is grafted to the Double Diamond design process, can help residents to implement behaviors that reflect their self-worth and create a state of engagement. As well, it can inform the collaboration between design and non-design staff in CPTED projects.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.327-351
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• 2023

This paper aims to derive success factors that successfully lead an artificial intelligence (AI) project and prioritize importance. To this end, we first reviewed prior related studies to select success factors and finally derived 17 factors through expert interviews. Then, we developed a hierarchical model based on the TOE framework. With a hierarchical model, a survey was conducted on experts from AI-using companies and experts from supplier companies that support AI advice and technologies, platforms, and applications and analyzed using AHP methods. As a result of the analysis, organizational and technical factors are more important than environmental factors, but organizational factors are a little more critical. Among the organizational factors, strategic/clear business needs, AI implementation/utilization capabilities, and collaboration/communication between departments were the most important. Among the technical factors, sufficient amount and quality of data for AI learning were derived as the most important factors, followed by IT infrastructure/compatibility. Regarding environmental factors, customer preparation and support for the direct use of AI were essential. Looking at the importance of each 17 individual factors, data availability and quality (0.2245) were the most important, followed by strategy/clear business needs (0.1076) and customer readiness/support (0.0763). These results can guide successful implementation and development for companies considering or implementing AI adoption, service providers supporting AI adoption, and government policymakers seeking to foster the AI industry. In addition, they are expected to contribute to researchers who aim to study AI success models.

• Journal of Korean Library and Information Science Society
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• v.54 no.4
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• pp.335-358
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• 2023

This study analyzed the characteristics of the learning organization according to its characteristics, the operation method and size of each public library. In addition, the service quality of public libraries was investigated so that it was also analyzed the correlation between the characteristics of the learning organization and the quality of the service. To achieve the research objectives, 83 librarians and 343 users across seven public libraries in South Korea's metropolitan areas were surveyed. The investigation covered various dimensions of learning organizations: creating continuous learning opportunities, promoting inquiry and dialogue, encouraging collaboration and team learning, creating systems to capture and share learning, empowering people toward a collective vision, connecting the organization to its environment, and providing strategic leadership for learning. Also it was investigated aspects of service quality: affect of service, information control, and library as place. As a result of the study, for the learning organization characteristics, more than 3.4 out of 5 were qualified to have foundation of learning organizations. One attempted to categorize according to its operational method and size and compare learning organization differences between public libraries, however it was not easy to see the clear differences. Therefore it was judged that there might be another unidentified factor which gives an affect on learning organization. Furthermore, it was found that there was a positive correlation between learning organization traits and service quality. This study might signify by looking into how the learning organization, which is one of the post-bureaucratic organizational traits, appears in public libraries.

• The Mathematical Education
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• v.63 no.2
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• pp.165-186
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• 2024

Despite the growing attention on artificial intelligence-based automated scoring technology as a support method for the introduction of descriptive items in school environments and large-scale assessments, there is a noticeable lack of foundational research in mathematics compared to other subjects. This study developed an automated scoring model for two descriptive items in first-year middle school mathematics using the Random Forest algorithm, evaluated its performance, and explored ways to enhance this performance. The accuracy of the final models for the two items was found to be between 0.95 to 1.00 and 0.73 to 0.89, respectively, which is relatively high compared to automated scoring models in other subjects. We discovered that the strategic selection of the number of evaluation categories, taking into account the amount of data, is crucial for the effective development and performance of automated scoring models. Additionally, text preprocessing by mathematics education experts proved effective in improving both the performance and interpretability of the automated scoring model. Selecting a vectorization method that matches the characteristics of the items and data was identified as one way to enhance model performance. Furthermore, we confirmed that oversampling is a useful method to supplement performance in situations where practical limitations hinder balanced data collection. To enhance educational utility, further research is needed on how to utilize feature importance derived from the Random Forest-based automated scoring model to generate useful information for teaching and learning, such as feedback. This study is significant as foundational research in the field of mathematics descriptive automatic scoring, and there is a need for various subsequent studies through close collaboration between AI experts and math education experts.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.109-119
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• 2024

This study aims to contribute to the initial research on on-device AI in an environment where generative AI-based services on mobile and other on-device platforms are increasing. To derive success strategies for generative AI-based chatbot services in a mobile environment, over 200,000 actual user experience review data collected from the Google Play Store were analyzed using the LDA topic modeling technique. Interpreting the derived topics based on the Information System Success Model (ISSM), the topics such as tutoring, limitation of response, and hallucination and outdated informaiton were linked to information quality; multimodal service, quality of response, and issues of device interoperability were linked to system quality; inter-device compatibility, utility of the service, quality of premium services, and challenges in account were linked to service quality; and finally, creative collaboration was linked to net benefits. Humanization of generative AI emerged as a new experience factor not explained by the existing model. By explaining specific positive and negative experience dimensions from the user's perspective based on theory, this study suggests directions for future related research and provides strategic insights for companies to improve and supplement their services for successful business operations.

• Journal of Global Scholars of Marketing Science
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• v.19 no.3
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• pp.28-36
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• 2009

While existing literature has focused extensively on the strengths and weaknesses of the Chaebol and their ownership and governance, there have been few studies of Korean non-Chaebol firms. However, Lee, Lee and Pennings (2001) did not specifically investigate the competitive strategies that non-Chaebol firms use to survive against the Chaebol in the domestic Korean market. The motivation of this paper is to document, through four exploratory case studies, the successful competitive strategies of non-Chaebol Korean companies against the Chaebol and then offer some propositions that may be useful to other entrepreneurial firms as well as public policy makers. Competition and cooperation as conceptualized by product similarity and cooperative inter.firm relationship respectively, are major dimensions of firm.level marketing strategy. From these two dimensions, we develop the following $2{\times}2$ matrix, with 4 types of competitive strategies for non-Chaebol companies against the Chaebol (Fig. 1.). The non-Chaebol firm in Cell 1 has a "me-too" product for the low-end market while conceding the high-end market to a Chaebol. In Cell 2, the non-Chaebol firm partners with a Chaebol company, either as a supplier or complementor. In Cell 3, the non-Chaebol firm engages in direct competition with a Chaebol. In Cell 4, the non-Chaebol firm targets an unserved part of the market with an innovative product or service. The four selected cases such as E.Rae Electronics Industry Company (Co-exister), Intops (Supplier), Pantech (Competitor) and Humax (Niche Player) are analyzed to provide each strategy with richer insights. Following propositions are generated based upon our conceptual framework: Proposition 1: Non-Chaebol firms that have a cooperative relationship with a Chaebol will perform better than firms that do not. Proposition 1a; Co-existers will perform better than Competitors. Proposition 1b: Partners (suppliers or complementors) will perform better than Niche players. Proposition 2: Firms that have no product similarity with a Chaebol will perform better than firms that have product similarity. Proposition 2a: Partners (suppliers or complementors) will perform better than Co.existers. Proposition 2b: Niche players will perform better than Competitors. Proposition 3: Niche players should perform better than Co-existers. Proposition 4: Performance can be rank.ordered in descending order as Partners, Niche Players, Co.existers, Competitors. A team of experts was constituted to categorize each of these 216 non-Chaebol companies into one of the 4 cells in our typology. Simple Analysis of Variance (ANOVA) in SPSS statistical software was used to test our propositions. Overall findings are that it is better to have a cooperative relationship with a Chaebol and to offer products or services differentiated from a Chaebol. It is clear that the only profitable strategy, on average, to compete against the Chaebol is to be a partner (supplier or complementor). Competing head on with a Chaebol company is a costly strategy not likely to pay off for a non-Chaebol firm. Strategies to avoid head on competition with the Chaebol by serving niche markets with differentiated products or by serving the low-end of the market ignored by the Chaebol are better survival strategies. This paper illustrates that there are ways in which small and medium Korean non-Chaebol firms can thrive in a Chaebol environment, though not without risks. Using different combinations of competition and cooperation firms may choose particular positions along the product similarity and cooperative relationship dimensions to develop their competitive strategies-co-exister, competitor, partner, niche player. Based on our exploratory case-study analysis, partner seems to be the best strategy for non-Chaebol firms while competitor appears to be the most risky one. Niche players and co-existers have intermediate performance, though the former do better than the latter. It is often the case with managers of small and medium size companies that they tend to view market leaders, typically the Chaebol, with rather simplistic assumptions of either competition or collaboration. Consequently, many non-Chaebol firms turn out to be either passive collaborators or overwhelmed competitors of the Chaebol. In fact, competition and collaboration are not mutually exclusive, and can be pursued at the same time. As suggested in this paper, non-Chaebol firms can actively choose to compete and collaborate, depending on their environment, internal resources and capabilities.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.987-994
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• 2021

The Yellow sea, as described in article 123 of UNCLOS, is semi-enclosed sea surrounded by the Republic of Korea, the People's Republic of China and North Korea. In addition, the Yellow Sea is one of the 66 large marine ecosystems as it contains large amounts of marine resources. According to article 194 of UNCLOS, states should be aware of rights and duties with respect to the protection and preservation of the marine environment to be engaged with countries directly as regional entity or indirectly. Therefore, the legal blank is urgent in terms of trans-boundary environmental pollutant issues. The UNDP has conducted a project called Yellow Sea Large Marine Ecosystem (YSLME) which has reached the 2^nd phase. The project has some notable achievements, namely performing joint activities on analysis of diagnostic trans-boundary issues in collaboration with China and South Korea, developing a strategic action plan based on TDA, and establishing regional strategic action plan. However, on the other hand, the project could not reflect the full participation of North Korea as a state party. As a result, the project has a limitation on effective implementation of RSAP. Therefore, this study focuses on the suggestion of a legally-binding trilateral treaty as a blue print for the next, 3^rd phase of the project. By analyzing the best practice of the Wadden Sea Trilateral Treaty case, the study verifies the validity of legislative measures on establishing and managing a legally-binding trilateral YSLME Commission. By suggesting a three phase treaty, incorporating a joint declaration by establishing the commission, the signing of the treaty, and formulating an umbrella convention and implementation arrangement, the study expects to guarantee the consistency and sustainability of the trilateral treaty regardless of political issues pertaining to North Korea.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• The Journal of Small Business Innovation
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• v.19 no.2
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• pp.53-68
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• 2016

Motivation and activities for technological learning, entrepreneurship, innovation, and creativity are driving forces of economic development in Asian countries. In the early stages of technological development, technological learning and entrepreneurship are efficient ways in which to catch up with advanced countries because firms can accumulate skills and knowledge quickly at relatively low risk. In the later stages of technological development, however, innovation and creativity become more important. This study aims to identify a) the factors (learning capabilities) that influence technological learning performance and b) barriers to enhancing innovation capabilities for the creative economy and organizations. The major part of this study is related to learning capabilities in the post-catch-up era. Based on a literature review and observations from Korean experiences, this study proposes a technological learning model composed of various influencing factors on technological learning. Three hypotheses are derived, and data are collected from Korean machine tool manufacturers. Intense interviews with CEOs and R&D directors are conducted using structured questionnaires. Statistical analysis, such as correlation and ANOVA are then carried out. Furthermore, this study addresses how to enhance innovation capabilities to move forward. Innovation enablers and barriers are identified by case studies and policy analysis. The results of the empirical study identify several levels of firms' learning capabilities and activities such as a) stock of technology, b) potential of technical labor, c) explicit technological efforts, d) readiness to learn, e) top management support, f) a formal technological learning system, g) high learning motivation, h) appropriate technology choice, and i) specific goal setting. These learning capabilities determine firms' learning performance, especially in the early stages of development. Furthermore, it is found that the critical factors for successful technological learning vary along the stages of technology development. Throughout the statistical and policy analyses, this study confirms that technological learning can be understood as an intrinsic principle of the technology development process. Firms perform proactive and creative learning in the late stages, while reactive and imitative learning prevails in the early stages. In addition, this study identifies the driving forces or facilitating factors enhancing innovation performance in the post catch-up era. The results of the preliminary case studies and policy analysis show some facilitating factors such as a) the strategic intent of the CEO and corporate culture, b) leadership and change agents, c) design principles and routines, d) ecosystem and collaboration with partners, and e) intensive R&D investment.