Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2023 316901 Business Research Methods 1 3.0 3 ★ Liou jiann-haw GIEM
IMBA
CMGT 28 2 IMBA&IMFI&工管所&管理博合開

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2023	316901	Business Research Methods	1	3.0	3	★	Liou jiann-haw	GIEM IMBA CMGT	28	2	IMBA&IMFI&工管所&管理博合開

Course Plan：

Instructor Liou jiann-haw　Office Hours

Email jhliou@ntut.edu.tw

Last Updated 2022-12-20 09:46:38

Course Objective 本課程旨在幫助學生建立足夠的知識與技能在企業研究方法上。課程內容主要分為兩部分，第一部分將首先介紹論文架構開始，緊接著介紹如何撰寫緒論、文獻探討、研究方法、資料收集、結果分析、討論、結論及參考文獻，配合課程中的實際案例討論，指導學生應注意的論文格式與規範。本課程的第二部分則在介紹目前企業研究上常用的各種數量方法，各種數量方法的原理及其應用的領域將以實際案例解釋說明，透過上課解說演練、討論、作業、報告等方式使學生熟悉各種研究方法。主要教授的研究方法包括層級分析法、網路程序分析、TOPSIS、VIKOR、灰關聯法、決策實驗分析法、模糊理論、約略集合及基本多變量分析。所教授的各種的研究方法將以Excel進行分析與計算演練，本課程學習結束後，學生應當能具備足夠的能力使用各種研究方法於企業問題解決。 The objective of this course is to help students build up the knowledge/skills in business research methods. The content of the course can be divided by two major parts. The first part will begin from the introduction of thesis structure, followed by how to write the introduction, literature review, methodology, data collection, result analysis, discussion, remarking and reference. The format of thesis will also be illustrated by some class examples. The second part of the class will begin from the introduction of different quantity methods commonly used in business research methods today. The categories of research methods and their applicable problems are then presented using real-world case studies. Students can learn different decision-making tools through lectures, discussion, assignment, term-projects and in class practices. The main methods include AHP, ANP, TOPSIS, VIKOR, DEMATEL, Gray Relation Methods, Fuzzy Set Theory, Rough Set Theory and some basic multivariate analysis.

Course Schedule Week 1: Introduction of thesis structure and requirements Week 2-3: How to write an academic report or thesis Week 5-6: Real report/thesis discussion and practice Week 7: Analytic hierarchy process introduction and practice Week 8: Analytic network process introduction and practice Week 9: Introduction fuzzy set theory Week 10: TOPSIS method Week 11: VIKOR method Week 12-14: DEMATEL method and its hybrid methods Week 15: Introduction to data mining using rough set theory Week 16: Introduction multivariate analysis and demonstration Week 17-18: Real case practice and discussion

Evaluation and grading policy Particpation 30% Report and presemtation 25% Final 45%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:No
Journal papers

The access to curricular consultation Thueday 10-12 o'clock

The course corresponds to the SDGs

Does the course incorporate AI

Note
will announce at line group

Instructor	Liou jiann-haw　Office Hours
Email	jhliou@ntut.edu.tw
Last Updated	2022-12-20 09:46:38
Course Objective	本課程旨在幫助學生建立足夠的知識與技能在企業研究方法上。課程內容主要分為兩部分，第一部分將首先介紹論文架構開始，緊接著介紹如何撰寫緒論、文獻探討、研究方法、資料收集、結果分析、討論、結論及參考文獻，配合課程中的實際案例討論，指導學生應注意的論文格式與規範。本課程的第二部分則在介紹目前企業研究上常用的各種數量方法，各種數量方法的原理及其應用的領域將以實際案例解釋說明，透過上課解說演練、討論、作業、報告等方式使學生熟悉各種研究方法。主要教授的研究方法包括層級分析法、網路程序分析、TOPSIS、VIKOR、灰關聯法、決策實驗分析法、模糊理論、約略集合及基本多變量分析。所教授的各種的研究方法將以Excel進行分析與計算演練，本課程學習結束後，學生應當能具備足夠的能力使用各種研究方法於企業問題解決。 The objective of this course is to help students build up the knowledge/skills in business research methods. The content of the course can be divided by two major parts. The first part will begin from the introduction of thesis structure, followed by how to write the introduction, literature review, methodology, data collection, result analysis, discussion, remarking and reference. The format of thesis will also be illustrated by some class examples. The second part of the class will begin from the introduction of different quantity methods commonly used in business research methods today. The categories of research methods and their applicable problems are then presented using real-world case studies. Students can learn different decision-making tools through lectures, discussion, assignment, term-projects and in class practices. The main methods include AHP, ANP, TOPSIS, VIKOR, DEMATEL, Gray Relation Methods, Fuzzy Set Theory, Rough Set Theory and some basic multivariate analysis.
Course Schedule	Week 1: Introduction of thesis structure and requirements Week 2-3: How to write an academic report or thesis Week 5-6: Real report/thesis discussion and practice Week 7: Analytic hierarchy process introduction and practice Week 8: Analytic network process introduction and practice Week 9: Introduction fuzzy set theory Week 10: TOPSIS method Week 11: VIKOR method Week 12-14: DEMATEL method and its hybrid methods Week 15: Introduction to data mining using rough set theory Week 16: Introduction multivariate analysis and demonstration Week 17-18: Real case practice and discussion
Evaluation and grading policy	Particpation 30% Report and presemtation 25% Final 45%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No Journal papers
The access to curricular consultation	Thueday 10-12 o'clock
The course corresponds to the SDGs
Does the course incorporate AI
Note	will announce at line group