Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
LEARNING OUTCOMES
This is a basic level course on quantitative research methods in management studies with an emphasis on developing hands-on knowledge in executing and critically assessing survey-based studies. Different to standard courses in statistics, this course is more focused on practical implementation of a quantitative research project in the field of management studies.
The objective of the course is to advance understanding of various principles and practices of quantitative research, and to improve the students readiness to execute a research project in their own discipline.
The main learning outcomes are to gain an understanding of the uses and limitations of common tools for analyzing quantitative data and to develop competence in collecting, modeling, and interpreting quantitative data. Students will improve their capacity to interpret and critically assess methodological execution of empirical management studies. On completion of this course, students are prepared to utilize obtained methodological skills in their master s theses, doctoral dissertations, and/or other research projects.
Credits: 6
Schedule: 26.10.2020 - 27.11.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Young Ji, Kristiina Lahdenranta
Teacher in charge (applies in this implementation): Mickaël Buffart, Young Ji, Kristiina Lahdenranta
Contact information for the course (valid 11.08.2020-21.12.2112):
Instructor’s contact information | Course information |
Post-doctoral researcher Mickaël Buffart Post-doctoral researcher Kristiina Herold Post-doctoral researcher Young Ji Department of Management Studies Office Hours: Available on zoom after class | M.Sc. degree, common studies. Participation is limited to 24 students. Academic Year: 2020-2021, Period II Location: Online Language of Instruction: English |
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
Valid 01.08.2020-31.07.2022:
The course covers the fundamentals of the research process, measures development, statistical analysis and modeling of data, and quantitative approaches to research, all with a focus on issues specific to management studies and emphasis on practical experience with application of SPSS analytics software.
Topics covered in the course include survey research design from hypotheses development to data collection; reliability and validity assessment of multi-item measurement scales; exploratory factor analysis; descriptive analysis of quantitative data; hypotheses testing; linear regression; indirect effects (moderation, mediation); variable transformations. Practical examples and exercises are embedded in the course structure.Applies in this implementation:
This is a basic level course on quantitative research methods in management studies with an emphasis on developing hands-on knowledge in executing and critically assessing survey-based studies. Different from standard courses in statistics, this course is more focused on the practical implementation of a quantitative research project in the field of management studies.
The objective of the course is to advance understanding of various principles and practices of quantitative research and to improve the students’ readiness to execute a research project in their own discipline. The course covers the fundamentals of the research process, survey development, statistical analysis and modeling of data, and quantitative approaches to research, all with a focus on issues specific to management studies and emphasis on practical experience with the application of SPSS analytics software.
The main learning outcomes are to gain an understanding of the uses and limitations of common tools for analyzing quantitative data and to develop competence in collecting, modeling, and interpreting quantitative data. Students will improve their capacity to interpret and critically assess the methodological execution of empirical management studies. On completion of this course, students are prepared to utilize obtained methodological skills in their master’s theses, doctoral dissertations, and/or other research projects.
Topics covered in the course include the fundamentals of survey research design, such as hypotheses formulation and data collection; preparation of survey data, such as importation into SPSS, variable transformations, and reliability assessment of multi-item measurement scales; descriptive statistics, such as means, standard deviations, and correlations; and hypotheses tests, such as t-tests, ANOVA, linear regression, and indirect effects (moderation, mediation) analysis. Practical examples and exercises are embedded in the course structure.
Assessment Methods and Criteria
Valid 01.08.2020-31.07.2022:
100% assignments
Applies in this implementation:
ASSESSMENT AND GRADING
1. Assignments 70% (see below for further information):
- Assignment 1 (10 %): Article-based analysis (conceptual domain);
- Assignment 2 (10 %): Article-based analysis (observable domain);
- Assignment 3 (15%): Online live session exam;
- Assignment 4 (35 %): Case-based coursework project.
3. Active participation (20 %): participation in online live sessions and timely submission of SPSS exercise outputs prior to online live sessions.
All assignments need to be completed in order to pass the course.
Final grade (0 to 5) is based on cutoff points below:
0-50 points = 0
50-59 points = 1
60-69 points = 2
70-79 points = 3
80-89 points = 4
90-100 points = 5
All assignments have to be returned and a final course presentation made in order to get a final grade for the course.
Note that turning in-class assignments is considered an acknowledgment of guidelines on scholastic honesty and academic integrity.
ASSIGNMENTS
Assignment 1: Article-based analysis (conceptual domain), 10 points available
Assignment 2: Article-based analysis (observable domain), 10 points available
Assignment 3: Online live session exam, 15 points available
Assignment 4: Case-based coursework project, 35 points available
- Assignment 1 (10 %): Article-based analysis (conceptual domain);
Workload
Valid 01.08.2020-31.07.2022:
Contact teaching 36h
Independent work 124h
Total 160h (6 ECTS)
DETAILS
Study Material
Valid 01.08.2020-31.07.2022:
Compulsory readings: Articles included in the syllabus.
Recommended readings (both textbooks are recommended, although not compulsory, for completing the course assignments): Field, A. (2009) Discovering Statistics Using SPSS. Sage Publications Ltd: London, UK.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014 or any earlier edition) Multivariate data analysis. Pearson Education Limited: Essex, UK.Applies in this implementation:
Compulsory pre-readings (read before the first lecture)
Liu, W., Tangirala, S., Lam, W., Chen, Z., Jia, R. T., & Huang, X. (2015). How and when peers’ positive mood influences employees’ voice. Journal of Applied Psychology, 100(3), 976-989. https://doi.org/10.1037/a0038066
Sliter, M., Kale, A., & Yuan, Z. 2014. Is humor the best medicine? The buffering effect of coping humor on traumatic stressors in firefighters. Journal of Organizational Behavior, 35: 257–272. https://doi.org/10.1002/job.1868
Umphress, E. E., Bingham, J. B., & Mitchell, M. S. (2010). Unethical behavior in the name of the company: The moderating effect of organizational identification and positive reciprocity beliefs on unethical pro-organizational behavior. Journal of Applied Psychology, 95(4), 769-780. https://doi.org/10.1037/a0019214
To download, log in to Aalto’s electronic management research database (http://web.lib.aalto.fi/en/edata/?cmd=list), choose a database such as Google Scholar or EBSCO e-books, and search for each of the articles above.
Readings covered in class
See “Details on the schedule” for specific book chapters associated with each lecture.
Field, A. (2009) Discovering Statistics Using SPSS. Sage Publications Ltd: London, UK.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014 or any earlier edition) Multivariate data analysis. Pearson Education Limited: Essex, UK.
Other recommended readings
Survey research design
Bono, J. E., & McNamara, G. 2011. Publishing in AMJ – Part2: Research design. Academy of Management Journal, 54(4): 657-660.
Sparrowe, R. T., & Mayer, K. 2011. Publishing in AMJ – Part4: Grounding hypotheses. Academy of Management Journal, 54(6): 1098-1102.
Zhang, Y., & Shaw, J. D. 2012. Publishing in AMJ – Part5: Crafting the methods and results. Academy of Management Journal, 55(1): 8-12.
Podsakoff, P. M., MacKenzie, S. B., Jeong-Yeon, L., & Podsakoff, N. P. 2003. Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5): 879-903.
Measurement scales
Tang, J., Kacmar, K. M., & Busenitz, L. 2012. Entrepreneurial alertness in the pursuit of new opportunities. Journal of Business Venturing, 27: 77-94.
Busenitz, L., Gomez, C., & Spencer, J. 2000. Country institutional profiles: Unlocking entrepreneurial phenomena. Academy of Management Journal, 43(5): 994-1003.
Benzing, C., Chu, H. M., & Kara, O. 2009. Entrepreneurs in Turkey: A factor analysis of motivations, success factors, and problems. Journal of Small Business Management, 47(1): 58-91.
Logistic regression and analysis of categorical data
Morschett, D. 2006. Firm-specific influences on the internationalization of after-sales service activities in foreign markets. Journal of Service Marketing, 20(5): 309-323.
Advanced reading:
Hult, G. T., Ketchen, D. J., Griffith, D. A., Finnegan, C. A. et al. 2008. Data equivalence in cross-cultural international business research: assessment and guidelines. Journal of International Business Studies, 39: 1027-1044.
Substitutes for Courses
Valid 01.08.2020-31.07.2022:
Replaces courses 80E80100 and 26E24000 Quantitative research methods. Please note that you can take either one of the courses.
Registration for Courses
Valid 01.08.2020-31.07.2022:
via WebOodi
Applies in this implementation:
PREREQUISITES
This is an intensive course that requires a substantial commitment from students. You must be comfortable with all of the following issues. If in doubt, please contact the instructors for any required clarification.
- The course is designed for students who want to gain practical knowledge about doing quantitative management research. This involves carrying out multiple computer assignments, taking part in online class discussions, and working independently on the provided case-study assignment during the live sessions. We expect you to be an active part of the learning process and ensure that your schedule allows you to attend all lectures.
- It is your responsibility to ask for clarification during the lectures and practice sessions (or after them, or during office hours) if something is not clear.
- There are four assignments to be returned during the course. You must be prepared to present and discuss the completed work in the class and contribute to other students’ learning. In addition, a successful study strategy involves keeping up with the readings as we go. Your schedule should allow for this.
- The course reading package consists of scientific articles. Unavoidably some parts are demanding, technically as well as language-wise.
- We expect that you have read all the required pre-readings (three journal articles specified under “Compulsory pre-readings) before the first lecture. When reading the articles, please pay particular attention to their Hypotheses, Methods, and Result sections.
- The course assignments require quantitative analysis skills and judgment which reflect the knowledge gained in the class and through independent work on the assigned reading. The assignments may not have a single correct answer and are graded for quality, as reflected in the rigorous execution, strong argumentation of the choices you make, and clarity of reporting.
SPSS AND OTHER TECHNICAL REQUIREMENTS
To make sure that all sessions run smoothly, we require everyone to perform the following technical preparations prior to the first session:
Make sure you will have a high-speed, reliable internet connection during each session.
Make sure you will have a reliable computer with a camera and microphone ready for use each session.
Download and install SPSS as soon as possible. First, click the following link: https://download.aalto.fi and choose "Software for students' home computers." Next, download and install "IBM SPSS Statistics Desktop v26." Important: Make sure to choose "authorized user license" when installing SPSS. For troubleshooting, contact servicedesk@aalto.fi. as soon as possible.
Open SPSS at least once prior to the first session to make sure that it is operating correctly without error messages.
Note that acquiring SPSS is required to complete the SPSS exercises which you will be assigned to complete prior to online live sessions.
FURTHER INFORMATION
Further Information
Valid 01.08.2020-31.07.2022:
Max 24 students. Participants are selected based on their program status, according to the following priority order:
1. MIB / Strategy / Global Management / CEMS
2. Other School of Business students
3. Other Aalto students
Students must attend the first lecture to ensure their place in the course.
There is compulsory lecture attendance (85 %), including the last day of the course, when the group presentations are made.Applies in this implementation:
PREREQUISITES
This is an intensive course that requires a substantial commitment from students. You must be comfortable with all of the following issues. If in doubt, please contact the instructors for any required clarification.
- The course is designed for students who want to gain practical knowledge about doing quantitative management research. This involves carrying out multiple computer assignments, taking part in online class discussions, and working independently on the provided case-study assignment during the live sessions. We expect you to be an active part of the learning process and ensure that your schedule allows you to attend all lectures.
- It is your responsibility to ask for clarification during the lectures and practice sessions (or after them, or during office hours) if something is not clear.
- There are four assignments to be returned during the course. You must be prepared to present and discuss the completed work in the class and contribute to other students’ learning. In addition, a successful study strategy involves keeping up with the readings as we go. Your schedule should allow for this.
- The course reading package consists of scientific articles. Unavoidably some parts are demanding, technically as well as language-wise.
- We expect that you have read all the required pre-readings (three journal articles specified under “Compulsory pre-readings) before the first lecture. When reading the articles, please pay particular attention to their Hypotheses, Methods, and Result sections.
- The course assignments require quantitative analysis skills and judgment which reflect the knowledge gained in the class and through independent work on the assigned reading. The assignments may not have a single correct answer and are graded for quality, as reflected in the rigorous execution, strong argumentation of the choices you make, and clarity of reporting.
SPSS AND OTHER TECHNICAL REQUIREMENTS
To make sure that all sessions run smoothly, we require everyone to perform the following technical preparations prior to the first session:
Make sure you will have a high-speed, reliable internet connection during each session.
Make sure you will have a reliable computer with a camera and microphone ready for use each session.
Download and install SPSS as soon as possible. First, click the following link: https://download.aalto.fi and choose "Software for students' home computers." Next, download and install "IBM SPSS Statistics Desktop v26." Important: Make sure to choose "authorized user license" when installing SPSS. For troubleshooting, contact servicedesk@aalto.fi. as soon as possible.
Open SPSS at least once prior to the first session to make sure that it is operating correctly without error messages.
Note that acquiring SPSS is required to complete the SPSS exercises which you will be assigned to complete prior to online live sessions.
Details on the schedule
Applies in this implementation:
Date
Topic
Readings
1.
26.10.2020
9.15-10:30
&
10:30
Online live session:
Introduction to the course
Pre-recording:
Quantitative research design in management studies.
Field A. (2018) 5th ed. Chapter 1 & 2
or
Field A. (2009) 3rd ed. Chapter 1 & 2
2.
28.10.2020
9.15-12.00
Pre-recordings (2 videos):
Fundamentals of survey research & Introduction to SPSS
and
T-tests & ANOVA
Survey research & SPSS:
Field A. (2018) 5th ed. Chapter 4 & 8
or
Field A. (2009) 3rd ed. Chapter 3 & 6
T-tests & ANOVA:
Field A. (2018) 5th ed. Chapter 10 & 12
or
Field A. (2009) 3rd ed. Chapter 9 & 12
3.
30.10.2020
9.15-12.00
Online live session:
SPSS practice (descriptive statistics, t-test, ANOVA)
Questions regarding Assignment 1
4.
02.11.2020
9.15-12.00
Pre-recordings (2 videos):
Regression analysis I: Simple and multiple regression
Regression analysis II: Assumptions of linear regression
Field A. (2018) 5th ed. Chapter 9
or
Field A. (2009) 3r d ed. Chapter 7
5.
04.11.2020
9.15-12.00
Pre-recording:
Regression analysis III: Logistic regression, Mediation, and Moderation
Logistic regression:
Field A. (2018) 5th ed. Chapter 20
or
Field A. (2009) 3rd ed. Chapter 8
also covered in
Hair et al. Chapter 5
Mediation:
Field A. (2018) 5th ed. Chapter 11
Moderation:
Field A. (2018) 5th ed. Chapter 11
also covered in
Hair et al. Chapter 4
6.
06.11.2020
9.15-12.00
Online live session:
SPSS practice (regression analysis I & II)
Questions regarding Assignment 2
7.
09.11.2020
9.15-12.00
Online live session:
SPSS practice (regression analysis III)
Recap of Assignment 1 & 2 & Interactive office hour
8.
18.11.2020
9.15-12.00
Thesis research incubator seminar a
9.
20.11.2020
9.15-12.00
Assignment 3: online live session exam.
10.
25.11.2020
9.15-12.00
Group presentations I
11.
27.11.2020
9.15-12.00
Group presentations II
- Teacher: Buffart Mickaël
- Teacher: Ji Young
- Teacher: Lahdenranta Kristiina