2020年度

＜概要/Course Content Summary＞

THIS SYLLABUS IS TENTATIVE AND SUBJECT TO CHANGE　　
　
To create breakthrough Marketing strategy, marketing practitioners must build deeper, more complete knowledge of their customers, partners and the environments within which marketing occurs. When properly applied, quantitative, qualitative and web-based analytics tools offer marketing executives such insights. Because of this, an understanding of the various research methods used in marketing research, and working knowledge of how to apply these to actual business challenges will be provided in this course. 　
　
Course contents will be delivered through traditional lectures, followed by lab-based exercises using two of the most popular Marketing Research software packages, SPSS, Atlas.ti and Google Analytics. This course will also include a number of seminar-style discussions to ensure the shared understanding of the concepts presented. A final research project will be used to apply all of the methods and tools presented throughout this course.　

＜到達目標/Goals,Aims＞

The purpose of this course is to provide students with a deep understanding of the fundamental practice of marketing research as it relates to the development of Marketing strategy. Students will learn both how to conduct such research projects by themselves as well as how to effectively manage the collection of both quantitative and qualitative marketing research data by an internal or outside agency. 　
Specifically, students will gain the following skills and knowledge after successfully completing this course:　
1)An in-depth understanding of the basic methodologies of quantitative & qualitative marketing research　
2)The ability to identify important and relevant research problems and to craft these into a business-oriented research brief　
3)Direct, hands-on working knowledge of how to plan, implement and analyze data using various marketing research techniques.　
4)Develop deep insights from the use of data analysis software packages　
5)The capability to create and convincingly present their analysis and insights 　
6)The confidence to manage an in-house or external Market Research organization to conduct such projects 　

＜授業計画/Schedule＞

*Please note: Students who prefer will be given an instructor-assigned Research Problem and Question.　
　
Throughout the semester additional articles and reading assignments may be provided 　
　

＜成績評価基準/Evaluation Criteria＞

Case Assignments: The grading criteria and point allocation for each case assignment will be clearly marked on all case assignment documents at the time that they are assigned. All responses will be graded based on the depth of understanding presented in each student's analysis and solutions.　
Class contribution: Grading evaluations will be made based upon the value of each student's contribution during the course lectures as well as how much understanding a student displays in their project-related presentations and reports. Attendance is required for every class session and will be taken at the start of each session. Students who come late will not receive credit for that class session. If you are unable to attend, please email the course professor in advance explaining the reason for your absence. 　
Final Project Report and Presentation: Grading criteria and point allocation for each element included in the final project report and presentation will be distributed at the time that they are assigned. Reports and Presentations will be graded based on the analyses conducted and the depth of understanding presented in each of the group's deliverables. Peer evaluations will be given for the final group project to fairly assess the individual contribution of each team member. 　

＜テキスト/Textbook＞

In addition to our course textbook, the following three case studies are required reading for this course:　
Microsoft: Launching the Smart Watch: http://cb.hbsp.harvard.edu/cb/search/microsoft%2520smart%2520watch?Ntk=HEMainSearch&N=0　
Building Brand Community on the Harley-Davidson Posse Ride: 　
http://cb.hbsp.harvard.edu/cb/web/product_detail.seam?E=28716&R=501015-PDF-ENG&conversationId=436043　

＜参考文献/Reference Book＞

Required Software: IBM SPSS Statistics, Atlas.ti　
　
In addition to our course textbook and statistical analysis software, the following case study and its supplementary Excel spreadsheet are required reading for this course:　
Air France Internet Marketing: http://cb.hbsp.harvard.edu/cb/web/product_detail.seam?E=488156&R=KEL319-PDF-ENG&conversationId=1159906　
Air France Internet Marketing Spreadsheet Supplement: 　
http://cb.hbsp.harvard.edu/cb/web/product_detail.seam?R=KEL321-XLS-ENG&conversationId=1159861　

＜参照ＵＲＬ/URL＞

＜備考/Remarks＞

Plagiarism and work ethic policy　
・All Global MBA/Doshisha Business School students (and students enrolled in courses offered by Doshisha Business School) Business are expected to uphold a high standard of professional work ethic.　
・This includes agreeing to a policy on plagiarism. All material presented in written reports must be clearly and accurately referenced with consistent use of a style as designated by the course instructor and a full reference list must be included. Where no style is specified by a course instructor, students should follow Harvard “Author-Date” style referencing.　
・Doshisha Business School takes plagiarism very seriously. Detected cases of unintentional plagiarism could result a score of zero for that assessment item and/or a failing grade for that course. In any case, student should expect to be penalized for insufficient referencing in their written work.　
・Detected cases of intentional plagiarism could result in a failing grade for that course, being called before the Program Director or the Dean of Doshisha Business School, and/or possibly of other punishment regarding enrollment status as a student.　
・Where group work is involved, all team members will endeavor to work consistently, participate fully, and communicate regularly with colleagues. Care should be taken in research and writing, as plagiarism on a group report may result in your entire team receiving an automatic fail.