Projects
Projects:
1. Program summaries of six ongoing research projects
Project 1: Apply signaling theory to understand knowledge transfer success in online communities: model construction and empirical research
Plan summary:
After the "Personal Data Protection Law" was officially launched, although personal data infringement incidents occurred one after another, we found that everyone's attitude towards personal data protection is not consistent. Some people think that the legal deterrent is too strong, and some people think that the penalties are too light and ineffective. Since hospitals often collect, process, utilize and destroy personal data, it is very important to understand the factors that influence the attitude of medical information service users towards personal data protection.
However, past studies lacked exploration of this research question. Therefore, this study explores why medical information service users have different attitudes towards personal data protection, and discusses what factors cause medical information service users to have different attitudes towards personal data protection, for further research and understanding.
This study is based on the privacy computing theory and combines it with the technological threat avoidance theory to construct a research model; and through empirical research, it understands the important factors that affect medical information service users' different attitudes towards personal data protection. Finally, this study puts forward academic and practical suggestions and provides reference for stakeholders.
Plan 2: Research on tax governance mechanisms in the big data environment: taking the correlation analysis of abnormal patterns that violate tax compliance as an example
Plan summary:
In recent years, the application of big data has not only swept across industries in various countries and become an emerging business trend, but its related issues have also triggered a wave of research and become the focus of attention from all walks of life. In addition to its diverse applications in various fields, big data is also a very important development strategy for our government in fiscal and taxation governance. Through the related technologies of big data analysis, it can not only help the government solve fiscal and taxation problems, but the analysis results can also be used as a reference for tax governance decision-making, so that the government can accurately and effectively control the national fiscal situation with the help of big data.
Therefore, based on the above needs, this research is guided by the strategy of Gowin's Vee Knowledge Map. Specifically, the research purposes have four goals: first, to explore the abnormal patterns and causes of tax compliance violations; second, to analyze the occurrence, importance, and relevance of abnormal patterns in dynamic data; third, to develop a tax governance framework and mechanism in a big data environment; and fourth, to verify the feasibility of applying this mechanism in tax governance.
The expected results of this study are that in terms of society, the analyzed abnormal pattern data that violates tax compliance can be used as a reference for government finance and taxation units to understand the tax compliance profile of business units; in terms of the national economy, the analyzed abnormal pattern data and correlation significance can provide the government with a basis for formulating tax audit policies; in terms of academics, the research processes and analysis methods constructed can strengthen the research and development energy and knowledge development of academia in the field of big data.
Project 3: Chiayi County and City Regional Innovation Application Research Project – Electric Vehicles
Summary:
Taiwan's electric vehicle industry has entered a critical stage of popularization. The development of electric vehicles will significantly achieve the benefits of energy conservation and carbon reduction. In order to push electric vehicle-related industries to the market's maturity curve, the team will cooperate with the government to promote electric motorcycle systems, supplement common standards related to electric vehicle services, and implement industry consensus to accelerate the popularization of the service market.
In the next 3 to 5 years, the team will build a green energy smart environment and a low-carbon, high-value environment that meets Taiwan's daily transportation needs and industrial goals. The goals of the 107-year plan include:
1. Deepen the 106 electric scooter sharing service model and spread it to the short-term active population groups in the Yun-Chia-Chiayi area.
2. Promote the electric scooter sharing service industry ecosystem and propose the optimal organizational structure, operating model, and capital increase operation plan for new ventures.
3. Develop an opening and promotion mechanism for the electric scooter sharing platform system and service model.
4. Analyze the application of using blockchain technology to strengthen the trust mechanism within electric scooter sharing ecosystems, reduce the interference of intermediaries in the value transfer process, disclose information while ensuring privacy, and provide joint decision-making space in services while protecting individual rights and interests.
Plan 4: Development and application of intelligent wealth management software robots
Summary:
Compared with financial professionals, intelligent wealth management software robots have the ability to transcend human physical and psychological limitations (for example, they are not disturbed by emotions and stress, will not get sick, will not engage in irrational behaviors such as chasing highs and chasing lows, and transcend shortcomings of human limited rationality and judgment errors, etc.), as well as the advantages of providing services anytime and anywhere.
This research project will use artificial intelligence (AI) technologies such as expert systems, neural networks, machine learning and deep learning, and case-based reasoning to construct modules for customer characteristics classification, fund investment, insurance investment, foreign exchange investment, and investment portfolio analysis. The front-end of AI wealth management application modules will use physical robots and online software smart agents to provide customers with the highest quality intelligent wealth management services.
Plan 5: Research and development of artificial intelligence platform for banking industry information security management in the financial technology environment
Summary:
In recent years, with the rise of the FinTech financial technology economic industry, the banking industry has considered how to use emerging technologies to support service innovation, corporate transformation, product optimization, and maximize the effectiveness of internal audits. This has become an important trend for enterprises to strengthen their competitiveness.
However, due to the convenience, speed, ubiquity, and globalization of technology, many problems often arise during the transaction process of financial products or services, which need to be prevented through effective information security governance. The purpose of this project is to develop an artificial intelligence platform for information security management in the banking industry as a financial internal control tool for checking abnormal operations in the banking industry.
Under the supervision of this intelligent information security platform, it is possible to improve the banking industry's deficiencies in information security governance, poor internal control and auditing, and inability to implement regulatory compliance, thereby enhancing the capability of banking industry information security governance to control risks and improve operations. The results of this research will help our country promote the development of the intelligent financial technology market and accumulate scientific research energy in artificial intelligence.
Plan 6: Research on the development and application of intelligent financial compliance robots
Summary:
The development of Fintech has created many convenient and innovative services for the financial market, but it has also brought more diverse compliance and financial crime risks, which is why Regulation Technology (RegTech) was born. Its goals are to reduce operating costs, improve risk management and control capabilities, and prevent financial crimes, making it a key project for the development of the Fintech ecosystem.
This project uses the establishment of financial compliance data warehouses, text mining technology, and artificial intelligence learning mechanisms to develop a set of intelligent legal compliance technology robots. It is expected that this system can be flexible, fast, integrated, and analytical, and can be widely used.
It will collect relevant supervision mechanisms and regulations as well as cases of financial crime and fraud, and use text mining and artificial intelligence technology to achieve fraud pattern analysis and risk warning, so as to become a good helper for legal compliance and internal control auditors in the financial industry facing the Fintech environment.
2. Applied Research
(1) Big data analysis of cooperative enterprises
(2) Big data analysis of EasyCard
(3) Big data analysis of financial and taxation information
(4) Big data analysis of electric vehicles
(5) Medical big data analysis
(6) Huiban big data analysis
(7) Partner companies combine big data analysis with EasyCard
(8) Cooperating enterprises combine big data analysis of financial and taxation information
(9) Cooperating enterprises combine electric vehicle big data analysis
(10) Cooperating companies combine medical big data analysis
(11) Cooperating enterprises cooperate with Huiban to conduct big data analysis
3. Cooperation plan
(1) Visited the Information Center of the Ministry of Finance to discuss follow-up cooperation matters on April 27, 2016. Visited the Information Center of the Ministry of Finance and discussed the cooperative research issues on November 11, 2016.
(2) Xi'an Jiaotong University cooperation in 2016.
4. Research plan
(1) Hong Jia Motorcycle Shop Electric Motorcycle Business Transformation and Upgrade Preliminary Planning Study in 2019 (Department of Industrial Technology, Ministry of Economic Affairs)
(2) Development of Innovative Entrepreneurship Courses and Linkage with Core Industries in 2019 (Ministry of Education's Higher Education Deep Plowing Project)
(3) Application of Signal Theory to Understand the Success of Knowledge Transfer in Online Communities: Model Construction and Empirical Study (3/3) (MOST106-2410-H-194-020-MY3)
(4) Tainan Innovation Incubation Base (Minzhi Meeting Hall) Professional Event Management in 2018 (Industrial Technology Research Institute; Tainan Government Economic Development Bureau)
(5) Development of Innovative Entrepreneurship Courses and Linkage with Core Industries in 2018 (Ministry of Education's Higher Education Deep Plowing Project)
(6) Application of Signal Theory to Understand the Success of Knowledge Transfer in Online Communities: Model Construction and Empirical Study in 2018 (2/3) (MOST106-2410-H-194-020-MY3)
(7) Chiayi Regional New Venture Application Research Project – Electric Vehicles in 2017 (Industrial Technology Research Institute)
(8) Application of Signal Theory to Understand the Success of Knowledge Transfer in Online Communities: Model Construction and Empirical Study (1/3) in 2017 (MOST106-2410-H-194-020-MY3)
(9) Application of Social Media to Promote the Success of C2C E-commerce: The Application of Social Capital Theory in 2016 (MOST105-2410-H-194-058-)
(10) Promotion of 4G Mobile Commerce Application Services for SMEs – Research and Data Collection on "IT Governance for Future Society" in 2016 (Taipei Computer Association)
(11) Ministry of Science and Technology funding for Professor Shin-Yuan Hung of the 20th Asia-Pacific Conference on Information Management, June 27 to July 1, 2016 (105-2916-I-194-002-A1)
(12) Postdoctoral Research by Hsiang-Lin Wu – Understanding the Factors Influencing the Success of Corporate Knowledge Transfer: A Model Construction and Empirical Study from the Perspectives of Knowledge Recipients and Contributors in 2015 (3/3) (MOST104-2811-H-194-004)
(13) Factors Influencing Different Attitudes of Corporate Employees towards Personal Data Protection in 2015 (MOST104-2410-H-194-069-)
(14) Understanding the Factors Influencing the Success of Corporate Knowledge Transfer: A Model Construction and Empirical Study from the Perspectives of Knowledge Recipients and Contributors in 2015 (3/3) (MOST102-2410-H-194-095-MY3)
(15) Understanding the Factors Influencing the Success of Corporate Knowledge Transfer: A Model Construction and Empirical Study from the Perspectives of Knowledge Recipients and Contributors in 2015 (3/3) (MOST102-2410-H-194-095-MY3)
(16) Understanding an Integrated Model for Small Online Merchants to Continue Using Social Commerce in 2014 (MOST103-2410-H-194-069-)
(17) Understanding the Factors Influencing the Success of Corporate Knowledge Transfer: A Model Construction and Empirical Study from the Perspectives of Knowledge Recipients and Contributors in 2014 (2/3) (MOST102-2410-H-194-095-MY3)
(18) Global Shopping Center Cooperation Project in 2016
(19) University Local Practice Alliance Project in 2016