Advanced Research Topics in E-Business (2025 Fall)

This course is an elective course particularly designed for the NCHU Institute of Technology Management doctoral students specialized in Electronic Commerce. Students are expected to attend all lectures and complete all coursework, including bonus assignments and course project. Attendance will not be accounted for the final score but absence without proper reason will be.

Professor John Sum is a strict person, sometimes a monster. His expectation on the behavior and the performance of a student is stringent. It is simply because John Sum has been teaching in the area of electronic commerce for more than two decades. Materials in his mind are abundant. Only some of them are extracted and complied as teaching materials.

Taking notes during the lectures. Professor John Sum is an old-fashion teacher. Students are expected to bring with a pen/pencil (with other necessary accessories) and a notebook to take notes. Students' writing is expected to be in the same speed as Professor John Sum. Capturing written notes on board by a cell phone or a pad is not allowed. Sometimes, Professor John Sum might draw diagrams on board for illustration. Only in these occasions, capturing diagrams on board by a cell phone or a pad is allowed. Still, it is expected that students will add these diagrams on their notebooks. While taking notes is not formally accounted for the final score, extra bonus could be added to a student's final score if his/her notes is as comprehensive as the contents (including the teaching materials on the homepage, written notes on board and verbal information) delivered in the lectures. Students could refer to here for tips on note-taking.

Prerequisites

1. Able to read, write, speak and listen in English.
2. Skillful in the use of word processing software for report writing and presentation.
3. Skillful in searching information over the Internet.
4. Knowledge in one of the following subjects: Principles of Computing, Computer Literacy, Introduction to Information Systems, Introduction to Computer Science, Introduction to Information Technologies or other related subjects.
   • Digital Systems, 2020.
   • Processor and Computer, 2020.
   • Operating Systems, 2020.
   • Computer Network, 2022.
5. Able to complete a coursework report its quality could be compared with a journal publication.

Course Outline

1. Topic 0: Doctoral Research.
   1. Essentials of a research.
      • Literature survey.
        • To prove that the research problem (validation of the system of hypotheses) is new. No one else did it before.
        • To prove that the research problem is valuable. If the validation is positive, the contributions are significant.
        • Act as the basis for the development of the system of hypotheses (i.e. conceptual model).
      • Statement of hypothesis, i.e. the system of hypotheses or equivalently the conceptual model.
      • Proof of correctness (equi. validation) - Research method design.
        • Determination of the data to be collected to validate the hypotheses.
        • Design of the experiment or survey for collecting data.
        • Empirical (Statistical) analysis.
        • Note that research method is research problem oriented. Different research problems might end up with different research methods.
      • Documentation and dissemination.
        • Proposals - Research plans.
        • Monographs.
        • Technical reports.
        • Wordings for the claims.
        • Future works.
      • Use of tools.
        • Analysis - Mathematical formulae and theorems.
        • Software package for mathematical analysis - Matlab, Mathematica, SPSS and SAS.
        • Software package for simulation - Matlab.
        • Word processing software - Latex, Pages and Words.
        • Drawing tools - Power Points, XFig.
      • JS experience.
        • Session lifetime distribution of Gnutella clients.
        • Gnutella is a disconnected social network.

   2. Research plans.
      • A research plan must be executable.
        • Comprehensive background survey.
        • Clear motivations and objectives.
        • Clear research method and reasonable schedule.
        • Anticipated contributions.
        • Survey paper in essence.
      • To be submitted for degree program admission only.
        • Garbage !!!
        • To fool around the admission officers.
        • It will never be executed.

   3. Literature survey (*).
      • Background of the topic.
      • Critical comments on previous works.
        • Limitations and constraints.
        • Factors overlooked or over simplified.
      • Show that the research hypothesis is worthwhile investigated.
      • Formal statement of the hypothesis.
      • Anticipated contributions if the hypothesis is correct.

   4. Research methods.
      • Mathematical proof.
      • Empirical study (Quantitative method).
        • Common in social science research.
        • Experimental design for data collection.
        • Statistical analysis and test of significance.
      • Simulations.
        • Mathematical model is too complex to be analyzed.
        • Experimental design for data collection.
        • Statistical analysis.
      • Logical analysis (Qualitative method).
      • Research method design - Problem dependent.

2. Topic I: Evolution of the principles and practices of management.
   • Increasing complexity of production process.
   • Expanding scope of quality.
   • Increasing focus on services.
   • Advancing development of technologies.
   • Observations and future trends.

3. Topic II: Service systems engineering.
   • Business development is essentially the development of a service system.
   • Framework of service systems engineering.
   • Modeling of a service system.
   • Information and technology management.

4. Topic III: Intelligent technologies.
   • Introduction to AI and machine learning.
   • Current applications of AI/ML.
   • Future applications of AI/ML.
   • Ethical and safety issues in the usages of AI/ML systems.

5. Topic IV: Platform Economy Contents are extracted from the MBA thesis of Ka-Ka Cheung.
   • Definition of platform.
   • Institutive perception of 'Platform'.
   • Platform-oriented thinking in EC.
   • Platform competitions.

6. Topic V: Computational XYZ.
   • Large language models.
   • Computational biology; computational economics; computational neuroscience.
   • Computational intelligence.
   • Computational linguistics.
   • Computational marketing and computational organization theory.
   • Computational social science.
   • Computational thinking and computational science.
   • Different from the areas of 'analogue computing', 'digital computing', 'neural computing' ('neurodynamic computing'), 'quantum computing', 'statistical computing', 'thermodynamic computing' ('probabilistic computing').

7. Topic VI: Other topics.
   • Journal papers in any hot topic in electronic business.
   • Journal papers in any advanced topic in electronic business.

Reading List

Works To Do

• Assignments/ Class exercises.
• Course project: Progress report (written and oral) and final report (written and oral).

Assignments/Lecture Diary

1. Class Exercise 01 (ARTEC 2022).
2. Class Exercise 02 (ARTEC 2022).
3. Class Exercise 03 (ARTEC 2022) (20221024 Version).
4. Assignment 1 (ARTEC 2023).
5. Prepare a homepage of yourself, in which your assignment solution files and project report (written report and presentation slides) are linked for download (ARTEC 2023).
6. Assignment 2 (ARTEC 2023).
7. Lecture Diary (October 11, 2023; October 18, 2023).

Project (Individual)

Project Types

1. Case Study. Each student has to select an AI tool and complete a survey report including the following issues. The survey report could be a case study. Based on your experience in the use of an AI tool for solving a real problem, write a report elucidating what you have done and what you have encountered. Below is a list of tentative contents for this type of report.
   1. Describe what are the usages of the tool? The content should be based on your personal experience.
   2. Describe the problem(s) you have encountered when you are using the tool. You need to ensure that the problem(s) is(are) due to your incapability.
   3. Describe how you overcome the problem(s).
   4. What technologies (including both AI and non-AI) have been applied in the tool?
   5. (*) Explain why the problem(s) exists (exist).
2. Topic Survey. Another type of survey report is topic survey. Student could select an AI topic and write a survey paper elaborating the concepts, theories and applications in it. If you are interested in any content introduced in the lecture and want to delve, you could write a survey report elaborating such content.
3. Others. If you are not clear on a topic to be surveyed, please discuss with John Sum.

Submissions

1. Submit a written progress report and your presentation slides before Week 8 and give an oral presentation of the written report on Week 8.
2. Submit a final report and your presentation slides before Week 16 and give an oral presentation of the final report on Week 16.

• Progress report.
  • Email heading: ARTEC2025_Progress_Report_5111027804
  • Filename (written report): ARTEC2025_Progress_Report_5111027804.docx
  • Filename (slides): ARTEC2025_Progress_Report_Slides_5111027804.pptx
• Final report.
  • Email heading: ARTEC2025_Final_Report_5111027804
  • Filename (written report): ARTEC2025_Final_Report_5111027804.docx
  • Filename (slides): ARTEC2025_Final_Report_Slides_5111027804.pptx

Project Assessment

Further Information

Further details on the course project can be found in here.

Use of AI Tools

AI tools, like ChatGPT and Google Gemini, might have limitations in 'avoiding misinformation (resp. incomplete information)' and 'avoiding plagiarism'. Moreover, Google Gemini is designed not to give any reference (equivalently, source) of the content displaced to the users. Students have to be aware of these.

ChatGPT, Google Gemini and other AI text generators are very good in paraphrasing. Using these tools to paraphrase your assignments and project reports are highly encouraged.

You are allowed to use AI tools, like ChatGPT and Google Gemini, for your assignments and project reporting. In the first step, you have to complete your assignment or the project report based upon your own writing. In the second step, you could use those AI tools to paraphrase the contents of your assignments and reports.

WARNING: For any part of the content (respectively, any word) you have put in an assignment or report, I will ask for your reason and explanation why this part of content (respectively, the specific word) has to be added. If you fail to do so, your assignment (respectively, group project) score will be zero. Nevertheless, your assignment (respectively, group project) score will be zero if you fail to give the source for any part of the content you have added in your assignment (respectively, group project).