• Title/Summary/Keyword: 산업혁명

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The Case on Valuation of IT Enterprise (IT 기업의 가치평가 사례연구)

  • Lee, Jae-Il;Yang, Hae-Sul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.8 no.4
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    • pp.881-893
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    • 2007
  • IT(Information Technology)-based industries have caused a recent digital revolution and the appearance of various types' information service, being largely expanded toward info-communication device company, info-communication service company, software company etc.. Therefore, the needs to evaluate the company value of IT business for M&A or liquidation are growing tremendously. Unlike other industries, however, IT industry has a short lift cycle and so it doesn't have not only a company value-evaluating model for general businesses but the objective one for IT companies yet. So, this thesis analyzes various value-evaluating technique and newly rising ROV. DCF, the change method of company's cash flow including tangible assets into future value, had been applied during the past industrialization economy era and has been persuasively applied to the present. However, the DCF valuation has no option but to make many mistakes because IT companies have more intangible assets than tangible assets. Accordingly, it is ROV, recognized as the new method of evaluating companies' various options normally and quantitatively, that is brought up recently. But the evaluation on the companies' various options is too subjective and theoretical up to now and due to the lack of objective ground and options, it's not possible to be applied to reality. In this thesis, it is found that ROV is more accurate than DCF, comparing DCF and ROV through four examples. As the options applied to ROV are excessively limited, we tried to develop ROV into a new method by deriving five invisible value factors within IT companies. Therefore, on this occasion, we should set up the basic valuation methods on IT companies and should research and develop an effective and various valuation methods suitable to each company like an internet-based company, a S/W developing enterprise, a network-related company among IT companies.

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New Perspectives on Sunday School of Korean Church for Next Generation (다음 세대와 한국교회 주일학교의 새 전망)

  • Kim, Jeong Joon
    • Journal of Christian Education in Korea
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    • v.67
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    • pp.11-44
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    • 2021
  • In the early 21st century, the global COVID-19 pandemic, which has arisen during the development of the technological science of the Fourth Industrial Revolution, has been a great challenge in all fields including politics, economy, industry, education and religion in Korean society. To prevent the spread of the COVID-19 epidemic, the Korean government announced 'social distancing guidelines,' focused on the 'prohibition of three conditions'(crowd, closeness, airtight) for safety reasons. These quarantine guidelines made it more difficult for Korean churches and Sunday schools to operate. In general, looking at the statistical data of the major denominations of the Korean Church in the second half of the 20th century, shows that the Church has entered a period of stagnant or declining growth. Data also show that the number of students attending Sunday School is decreasing. The researcher identified four causes of the crisis faced by the Korean church and Korean Sunday school entering the 21st century. These trends are influenced by the tendencies of postmodernism, the deconstruction of modern universalism, the certainty and objectivity of knowledge, and the grand narrative and worldview of diffusion. Moreover, it is a phenomenon in which the young population decreases in contrast to the increasing elderly population in the age of population cliff in Korean society. Sunday Schools are also facing a crisis, as the youth population, who will become the future heroes of the Korean church, is declining. Finally, constraints of Church and Sunday school education activities are due to COVID-19 Pandemic. As analysis shows the loss of the Church's educational vision and a decrease in the passion for education. Accordingly, the researcher suggests four new strategies for the next generation of Korean Sunday schools, whose ranges from 200 members or less; this range covers the majority of Sunday School program run by churches in Korea. First, in the age of postmodernism, a time of uncertainty and relativism, Christian Societies requires teachers who are certain of absolute Christian truth and faith. Second, in an era of declining population cliffs for younger generations, a shift to a home-friendly Sunday school paradigm is needed. Third, during the COVID-19 pandemic, educational activities must appropriately utilize face-to-face and non-face-to-face communication. Finally, even in difficult times, Korean Sunday school should nevertheless remember the Lord's great commandment(Matthew 28:18-20) and restore the vision and passion of education to announce and teach the gospel. The researcher hopes that this study will provide small, positive steps in rebuilding Korean Sunday school educational activities for future generations in difficult times.

An Exercise Rehabilitation Field Revitalization Plan for Promoting Elderly Sport for All (노인생활체육 진흥을 위한 운동재활분야 활성화 방안)

  • Cho, Kyoung-Hwan
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.4
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    • pp.305-319
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    • 2020
  • A The purpose of this study was to determine the present state of the exercise rehabilitation field, promote elderly sport for all, and present a revitalization program for higher quality of life for the elderly in the coming era of the Fourth Industrial Revolution and aged society. Literature review was performed to analyze the actual conditions of the activities for elderly sport for all and the relevant field of exercise rehabilitation, analyze the elderly health and welfare and elderly sport for all programs, and present a plan for revitalizing the field of exercise rehabilitation to promote elderly sport for all. First, it is necessary to reinforce the awareness and promotion of the need and importance of exercise rehabilitation in inducing seniors to participate in sport for all. Second, it is necessary to make it compulsory to place sport leaders for seniors at such places as elderly leisure and welfare centers and promote expertise in managing elderly health guidance efficiently through cooperation with welfare workers. Third, it is necessary to make it compulsory to take exercise rehabilitation and similar subjects in the curriculums of sport for all, elderly sport welfare, and silver welfare sport as well as the subject of volunteering activities at such places as elderly leisure and welfare centers with the aim of giving opportunities for career choice. Fourth, it is necessary to develop characterized exercise rehabilitation programs at senior welfare centers, community centers for the elderly, and elderly classes and employ experts equipped with exercise event and exercise rehabilitation capabilities as itinerant lecturers to contribute to the government's job creation policies through cooperation between the Ministry of Culture, Sports, and Tourism (MOCST) and the Ministry of Health and Welfare (MOHW). Fifth, it is necessary to make a greater investment in research and development required for elderly sport for all. Sixth, it is necessary to develop and distribute various exercise rehabilitation treatment videos and guidelines that seniors can use for themselves. This is associated with the fifth one; in particular, it is urgent to devise measures against Coronavirus 19. Seventh, it is necessary to reduce inefficiency and budget waste caused by overlapped tasks by establishing a new elderly sports promotion organization through adjustment by MOCST and MOHW; it is also necessary to increase the functions of organization establishment with the aim of reinforcing the education area, which involves post-retirement health care, exercise rehabilitation, safety accident prevention, and virus.

A Study on Moltmann's Creationism and the Ecological Integrity of Christian Education (몰트만의 창조론과 기독교교육의 생태학적 통전성 고찰)

  • Lee, Hyangsoon
    • Journal of Christian Education in Korea
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    • v.70
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    • pp.107-140
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    • 2022
  • This study is a review of the role of Christian education in the face of ecological crisis and the task of its recovery from the perspective of Moltmann's creation theory. Mankind has achieved epoch-making industrial development through several industrial revolutions. However, as a result, the ecosystem has suffered severe physical aches and has reached the point of revealing anomalies. In the face of such destruction and suffering of the ecosystem, Christian education needs to approach the ecological sensitivity toward the natural world more holistically and present a practical alternative. Moltmann reminds us that today's growing exploitation of nature by humans stems from a human-centered ecological consciousness that the world belongs to humans. At the same time, it suggests a transition to a God-centered ecological world consciousness. 'A community of creation', 'the fellowship of the Triune God', and 'eschatological new creation through the Sabbath' are key concepts that integrate God-centered ecological world consciousness. Based on Moltmann's creation theory, this article examines the ecological sensibility that Christian education should pursue from the point of view of the sacramental creative community, and reviews the role and practical alternatives of Christian education. Through this, it was derived that the world, including humans, is not owned by humans, but is a sacramental community that is built together toward the end as a part of nature and reveals the glory of God. In addition, it was suggested that Christian education need to be recognized as a suffering subject which mediates humanity and the nature of the mutual fellowship of reconciliation. in the fellowship of God. Sabbath keeping education, which celebrates God's creation and aims for the completion of the eschatological creation, will become a practical area for Christian education to practice for the restoration of the collapsed ecosystem. Moltmann's creation theory is significant in that it provides a meaningful Christian educational insight to restore the ecological environment as well as interest in the ecological environment that has been overlooked or ignored by Christian education.

Classification of Service Quality for HMR unmanned store business (HMR 무인매장 서비스 품질 분류에 관한 연구)

  • Jong Won Lee
    • Journal of Service Research and Studies
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    • v.13 no.2
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    • pp.41-61
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    • 2023
  • The universal form of life in the era of the 4th industrial revolution can probably be summarized as the keyword "non-face-to-face". In particular, in terms of consumption activities, face-to-face contact is gradually changing to a system that minimizes, and offline stores are rapidly changing to non-contact services through kiosks and robots. The social structure is also changing with the passage of time, and most fundamentally, our dietary consumption patterns are changing. In particular, the increase in single-person households and the aging population are having a great impact on changes in the food service industry, which is closely related to dietary life. The HMR (Home Meal Replacement) market has grown significantly as the labor of cooking at home has decreased and the use of substitute foods has increased. As the size of the market has grown, the types of businesses that provide products have also diversified. The development of technology, non-face-to-face culture, and corporate management efficiency are intertwined, and unmanned stores are spreading recently. In this study, service quality attributes of HMR unmanned stores, where competition is gradually intensifying, are classified, and service quality classification using the Kano model and Timko's customer satisfaction coefficient are calculated to provide implications for service management based on customer satisfaction. As a result of the analysis, 'products with short cooking time' and 'variety of products (menu)' were classified as attractive qualities, and 'cleanliness inside/outside of the store' and 'products at reasonable prices' were classified as unified quality. In addition, 'convenience of self-checkout process' was classified as a natural quality, and 'convenience of in-store passage' was classified as an indifferent quality. Furthermore, when the service factor was satisfied within the HMR unmanned store, the factor with the highest satisfaction coefficient was 'product (menu) variety', and the factor with the highest dissatisfaction factor was 'convenience of self-checkout process'. Through the results of this study, it is intended to derive priorities in service quality management of HMR unmanned stores and provide strategic implications for related businesses.

A Study on the Influence of Digital Experience Factors on Purchase Intention and Loyalty in Online Shopping Mall - Focusing on the Mediating Effect of Flow - (온라인 쇼핑몰에서 디지털 경험요인이 구매의도에 미치는 영향에 관한 연구 : 플로우의 매개효과를 중심으로)

  • Jung, Sang-hee
    • Journal of Venture Innovation
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    • v.3 no.2
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    • pp.147-175
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    • 2020
  • This study analyzed the effects that digital experience factors influence on purchase intention and the purchase. The study targeted an online shopping mall with a strong digital experience value among industries. The research model was derived by adding variables to independent and mediating variables according to the industry context of online shopping which is based on the theoretical background and previous studies. Product variety, price efficiency, convenience and conversation were used by terms of digital marketing mix as independent variables. Personalization has been very important factor in online shopping malls, and therefore added as a independent variable. Flow has been added as a mediating variable. Purchase and purchase intention has been used as dependent variables. For empirical testing of established research models and generalization of research results, research was conducted on online shopping malls where digital experiences are important. To do this, a survey was conducted for existing users of online shopping malls. In hypothesis testing, the hypothesis was established that product diversity, price efficiency, convenience, conversation and personalization influenced the intention to purchase online shopping. In particular, the product diversity and conversation variable were tested as the most influential factors on purchase intention. For price efficiency and personalization there were no statistically significant effect. Flow has been shown to be a partial mediator between Product variety and purchase intention in online shopping. In particular, in the case of personalization, it was tested to have a significant influence on purchase intention only when there was a flow experience called pleasure and immersion. This is because the flow experience of pleasure and immersion has played a full mediating role and significantly has affected the purchase intention, because the consumers themselves have to carry out the overall purchase journey without human help due to the nature of online. In the digital experience economy, since consumers are mostly digital consumers, where communication and sharing are the basics, they have been conducting digital word-of-mouth communication and sharing naturally before purchasing. Based on these results, theoretical and practical implications were suggested.

The Development of an Aggregate Power Resource Configuration Model Based on the Renewable Energy Generation Forecasting System (재생에너지 발전량 예측제도 기반 집합전력자원 구성모델 개발)

  • Eunkyung Kang;Ha-Ryeom Jang;Seonuk Yang;Sung-Byung Yang
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.229-256
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    • 2023
  • The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.

Corporate Default Prediction Model Using Deep Learning Time Series Algorithm, RNN and LSTM (딥러닝 시계열 알고리즘 적용한 기업부도예측모형 유용성 검증)

  • Cha, Sungjae;Kang, Jungseok
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.1-32
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    • 2018
  • In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

Different Look, Different Feel: Social Robot Design Evaluation Model Based on ABOT Attributes and Consumer Emotions (각인각색, 각봇각색: ABOT 속성과 소비자 감성 기반 소셜로봇 디자인평가 모형 개발)

  • Ha, Sangjip;Lee, Junsik;Yoo, In-Jin;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.27 no.2
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    • pp.55-78
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    • 2021
  • Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

The Innovation Ecosystem and Implications of the Netherlands. (네덜란드의 혁신클러스터정책과 시사점)

  • Kim, Young-woo
    • Journal of Venture Innovation
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    • v.5 no.1
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    • pp.107-127
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    • 2022
  • Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.