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Quantitative Research Methods Seminar - 5 ECTS
Coruse Coordinator: Professor Michel Avital
Department of Digitalization, CBS
Facult
Associate Professor Qiqi Jiang
Department of Digitalisation (DIGI), CBS
Professor Michel Avital
Department of Digitalisation (DIGI), CBS
This course covers essential quantitative methods for the social sciences, with a focus on Information Systems research. It introduces a range of quantitative research designs, including experiments (e.g., controlled randomized trials, field experiments, and natural experiments), empirical research designs, and multimethod and mixed-method approaches that draw on numerical, behavioral, and psychometric measures. The course concludes with a critical examination of how quantitative research is reviewed and evaluated, emphasizing the rigor, validity, and quality of quantitative studies.
Learning Objectives
At the end of the course, students should be able to:
- § Explain the theories and methods that were presented in class and covered by the readings
- § Design theoretically sound and methodologically rigorous quantitative studies
- § Identify and assess appropriate data sources and data collection methods for quantitative studies
- § Apply quantitative data analysis techniques and interpret results
- § Critically evaluate and review quantitative research studies
- § Communicate quantitative research design, analysis, and findings in
- writing
Structure and Format
The course is designed as a sequence of seminars spanning roughly two weeks, each covering a key topic on quantitative research methods in social sciences. The meetings take the form of participatory seminars that include class presentations, guided discussions, and practical workshops. In addition to an appreciative and/or critical review of extant literature on quantitative research methods, the seminars encourage constructive dialogue aimed at helping students tackle research questions quantitatively, building on and extending contemporary knowledge.
Given the aforementioned learning objectives, the course involves a substantial reading load. Completing the assigned readings in advance and actively participating in class discussions and activities are essential for developing a solid understanding of the course content. For each seminar, students are expected to read the assigned articles beforehand and come prepared to answer questions, engage in discussion, and address other issues related to the assigned readings.
Prerequisite Statistical Software Tools
Prior to the first class, please obtain, install, and get familiar (using the online tutorials) with the basic operation of the required statistical software application: STATA
Required
§ STATA [Downloadable from http://my.cbs.dk
Evaluation
Students’ performance will be evaluated based on an individual take-home written exam of up to 10 pages and a research proposal presentation. Assessment is on a pass/fail basis. Passing all individual homework assignments is a prerequisite for taking the exam. If necessary, a re-take exam will be administered approximately one month later.
Workload
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Class lectures |
40 Hours |
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Class preparation including homework assignments |
80 Hours |
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Project presentation preparation |
4 Hours |
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Exam and exam preparation |
16 Hours |
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TOTAL |
140 Hours |
*1 ECTS = 28 hrs
Homework Assignments
Two mandatory individual written homework assignments, each limited to a maximum of two pages, are designed to reinforce key analytical techniques and provide opportunities for deeper learning and reflection. The assignments address research motivation, research design, sampling strategy, causal inference, and selected concepts in quantitative methods.
Assignment 1: Review the article by Sandberg and Alvesson (2011). Discuss when gap spotting is an appropriate way to motivate research and when it is not. Support your discussion with explicit examples or references to relevant articles published in MISQ, ISR, or Management Science. Due: xx
Assignment 2: Review a provided manuscript. Critically evaluate both the theoretical reasoning and the empirical analysis. Due: xx
Submit the homework assignments via the Assignments section in Canvas by the due date.
Research Proposal Presentation [Week 13]
For the last session of the course, each student will be expected to prepare a presentation that outlines the design of a quantitative empirical study for investigating their domain of interest or any other contemporary or emerging topic in social sciences. The purpose of the presentation is to familiarize students with the practical steps involved in conducting quantitative empirical studies. The presentation should incorporate the following elements:
- Selected topic to be investigated via quantitative research models
- Significance of the selected topic
- Prior research on the selected topic
- Research question(s) to be answered based on the selected topic
- Theoretical model and hypotheses for answering the research question(s)
- Quantitative research strategy being adopted to validate the theoretical model and hypotheses
- Instruments for data collection
- Possible data source(s)
- Proposed data analytical technique(s) to be utilized
- Potential contributions to theory and practice
Submit the presentation via the Assignments section in Canvas. Due: Monday, Week 13.
Written Exam
The exam will take the form of an individual, take-home written exam, with a maximum length of 10 pages.
What can you work on?
· Identify a research topic that you would like to work on. There is no predetermined or stipulated topic. Choose a topic that genuinely interests you.
· Provide clear and compelling motivation for the research.
What must you do?
· Conduct a thorough literature review of the topic, with an explicit focus on papers published within the last ten years.
· Propose a quantitative research method. Multimethod and mixed-methods approaches are also acceptable, provided that they include a quantitative component.
· Explain in detail how you would conduct the empirical investigation. The discussion of the research design and method should be comprehensive and specific.
· Briefly explain how you would analyze the data collected. No actual data collection or analysis is required.
· Discuss the study’s potential contributions to both theory and practice.
What level of quality is expected?
· The written product is expected to meet the quality standards of a top-tier academic conference, such as ICIS or AOM. You may think of the paper as being comparable in scope to a short paper or research-in-progress paper.
· The research design should be developed in detail, including the quantitative method, operationalization of key constructs, validity considerations, and other relevant methodological choices.
The exam submission is due on Friday, Week 16, and should be submitted through the Assignments section in Canvas. If necessary, a re-take exam will be administered about one month later.
Course Plan and Required Text
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# |
Time/ 2027 |
Topic and Readings |
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1 |
Week 9 Monday, 8:00 – 11:40 |
Introduction to Quantitative Research Methods 1. MIS Quarterly Editorial (March 2025): Quantitative Behavioral IS Research – A Look Back and a Look Forward, pp. iii-xviii. 2. Lee, J. K., Park, J., Gregor, S. and Yoon, V. (2001) Axiomatic Theories and Improving the Relevance of Information Systems Research, Information Systems Research, 32(1), pp. 147-171. 3. Shaver, J. M. (2021) Evolution of Quantitative Research Methods in Strategic Management, in Strategic Management: State of the Field and its Future, edited by Irene M. Duhaime et al., chapter 1.3. 4. Bettis, R., Gambardella, A., Helfat, C., and Mitchell, W. (2014) Editorial: Quantitative Empirical Analysis in Strategic Management, Strategic Management Journal, 35, pp. 949-953. |
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2
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Week 9 Thursday, 8:00-17:00
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Research question and theoretical contribution 1. Sandberg, J., and Alvesson, M. (2011) Ways of Constructing Research Questions: Gap-spotting or Problematization, Organization, 18(1), pp. 23-44. 2. MIS Quarterly Editorial (March 2023): Producing Significant Research, 47(1), pp. i-xv. 3. Carton, A. M. (2025) The Six Dimensions of Strong Theory, Organization Science, article in advance. 4. Crittenden, V. L. and Peterson, R. A. (2011) Ruminations About Making a Theoretical Contribution, AMS Review, 1, pp. 67-71. 5. Information Systems Research Editorial (2024) On Crafting Effective Theoretical Contributions for Empirical Papers in Economics of Information Systems: Some Editorial Reflection, 35(3), pp. 917-935. 6. Tsang, E. W. K. (2009) Commentary – Assumptions, Explanation, and Prediction in Marketing Science: “It’s the Findings, Stupid, Not the Assumption”, Marketing Science, 28(5), pp. 986-990. 7. Nordenflycht, A. v. (2023) Clean up Your Theory! Invest in Theoretical Clarity and Consistency for Higher-Impact Research, Organization Science, 34(5), pp. 1981-1996. |
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Research Design 1. Edmondson, A. C., and McManus, S. E. (2007) Methodological Fit in Management Field Research, Academy of Management Review, 32(4), pp. 1155-1179. 2. Grunow, D. (1995) The Research Design in Organization Studies: Problems and Prospects, Organization Science, 6(1), pp. 93-103. 3. Miller, K. D., and Tsang, E. W. K. (2010) Testing Management Theories: Critical Realist Philosophy and Research Methods, Strategic Management Journal, 32, pp. 139-158. |
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3
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Week 9 Friday, 8:00-17:00
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Behavioral and Psychometric Measurements 1. Weber, R. (2021) Constructs and Indicators: An Ontological Analysis, MIS Quarterly, 45(4), pp. 1644-1678. 2. Graebner, M. E., Knott, A. M., Lieberman, M. B., and Mitchell, W. (2023) Empirical Inquiry without Hypotheses: A Question-driven, Phenomenon-based Approach to Strategic Management Research, Strategic Management Journal, 44, pp. 3-10. Research articles: 3. Uzunca, B., and Cassiman, B. (2023) Entry Diversion: Deterrence by Diverting Submarket Entry, Strategic Management Journal, 44, pp. 11-47. 4. Ho, E. H. (2021) Measuring Information Preferences, Management Science, 67(1), pp. 126-145. 5. Falk, A., Becker, A., Dohmen, T., Huffman, D., and Sunde, U. (2023) The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences, Management Science, 69(4), pp. 1935-1950. |
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Foundation of Experimental Design 1. Levine, S. S., Schilke, O., Kacperczyk, O., and Zucker, L. G. (2023) Primer for Experimental Methods in Organization Theory, Organization Science, 34(6), pp. 1997-2025. 2. MIS Quarterly Editorial (Sep 2022): Causality Meets Diversity in Information Systems Research, pp. i-xvii. Research articles: 3. Hvalshagen, M., Lukyanenko, R., and Samuel, B. M. (2023) Empowering Users with Narratives: Examining the Efficacy of Narratives for Understanding Data-Oriented Conceptual Models, Information Systems Research, 34(3), pp. 890-909. 4. Xiong, R., Athey, S., Bayati, M., and Imbens, G. (2024) Optimal Experimental Design for Staggered Rollouts, Management Science, 70(8), pp. 5317-5336. |
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4
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Week 11 Thursday, 8:00-17:00
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Field Experiment Design 1. Bail, Christopher A., et al. Exposure to opposing views on social media can increase political polarization. Proceedings of the National Academy of Sciences 115.37 (2018): 9216-9221. 2. Wager, S., and Xu, K. (2021) Experimenting in Equilibrium, Management Science, 67(11), pp. 6694-6715. 3. Jung, J., Sun, T., Bapna, R., and Golden, J. M. (2025) Social Learning in Prosumption: Evidence from a Randomized Field Experiment, Management Science, 71(1), pp. 538-552. 4. Lee, K., Jin, Q., Animesh, A., and Ramaprasad, J. (2022) Impact of Ride-Hailing Services on transportation Mode Choices: Evidence from traffic and transit Ridership, MIS Quarterly, 46(4), pp. 1875-1900. |
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Natural Experiment 1. Zhang, X., & Zhu, F. (2011). Group size and incentives to contribute: A natural experiment at Chinese Wikipedia. American Economic Review, 101(4), 1601-1615. 2. Lu, Y., Wu, J., Tan, Y., and Chen, J. (2022) Microblogging Replies and Opinion Polarization: A Natural Experiment, MIS Quarterly, 46(4), pp. 1901-1937. 3. Chen, J., He, S., and yang, X. (2024) Platform Loophole Exploitation, Recovery Measures, and User Engagement: A Quasi-Natural Experiment in Online Gaming, Information Systems Research, 35(4), pp. 1609-1633. 4. Deodhar, S.J., Babar, Y., and Burtch, G. (2022) The Influence of Status on Evaluations: Evidence from Online Coding Contests, MIS Quarterly, 46(4), pp. 2085-2110. |
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5
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Week 11 Friday, 8:00-17:00
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Empirical Research Design 1. Kitchens, B. Johnson, S. L., and Gray, P. (2020) Understanding Echo Chambers and Filter Bubbles: The Impact of Social Media on Diversification and Partisan Shifts in News Consumption, MIS Quarterly, 44(4), pp. 1619-1649. 2. Salge, C. A., Karahanna, E., and Thatcher, J. B. (2022) Algorithmic Processes of Social Alertness and Social Transmission: How Bots Disseminate Information on Twitter, MIS Quarterly, 46(1), pp. 229-259. 3. Bao, C., Bardhan, I. R., Singh, H., Meyer, B. A., and Kirksey, K. (2020) Patient-Provider Engagement and its Impact on Health Outcomes: A Longitudinal Study of Patient Portal Use, MIS Quarterly, 44(2), pp. 699-723. |
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Multimethod and Mixed Methods 1. Valentine, J., Novelli, E., and Agarwal, R. (2024) The Theory-based View and Strategic Pivots: The Effects of Theorization and Experimentation on the Type and Nature of Pivots, Strategy Science, 9(4), pp. 433-460. 2. Khern-am-nuai, W. Hashim, M. J., Pinsonneault, A., Yang, W., and Li, N. (2023) Augmenting Password Strength Meter Design Using the Elaboration Likelihood Model: Evidence from Randomized Experiments, Information Systems Research, 34(1), pp. 157-177. 3. Kacperczyk, O., Younkin, P., and Rocha, V. (2023) Do Employees Work Less for Female Leaders? A Multi-Method Study of Entrepreneurial Firms. Organization Science, 34(3), pp. 1111-1133. |
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6 |
Week 13 Thursday, 8:00-11:40 |
Project Presentation |
Registration deadline and conditions
The registration deadline is 18 December 2026. If you wish to cancel your registration, it must be done by this date. By this deadline, we determine whether there are enough registrations to run the course or decide who should be offered a seat if we have received too many registrations.
Payment methods
Ensure you choose the correct payment method when finalizing your registration:
Information about the Event
Date and time Monday 22 February 2027 at 08:00 to Thursday 25 March 2027 at 11:00
Registration Deadline Thursday 14 January 2027 at 23:55
Location
Howitz - room HOW5.23 (fifth floor)
Howitz 60
Frederiksberg
DK-2000
Organizer
Nina Iversen, CBS PhD School
Phone +45 3815 2475
ni.research@cbs.dk
Event Location
About CBS PhD School
Copenhagen Business School (CBS) offers a range of PhD courses, covering the scientific disciplines of the school. The courses include research design, publication techniques, research methods such as qualitative or quantitative methods, and specialisation courses in eg. organisational analysis, marketing and political science.
Most courses are organised as intensive week-long courses, but other formats are applied as well. The courses are open to PhD students from other countries and institutions, but some prerequisites may apply. Please see the individual course descriptions.
The PhD courses are offered in English and are for PhD students only.
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Event Location
About CBS PhD School
Copenhagen Business School (CBS) offers a range of PhD courses, covering the scientific disciplines of the school. The courses include research design, publication techniques, research methods such as qualitative or quantitative methods, and specialisation courses in eg. organisational analysis, marketing and political science.
Most courses are organised as intensive week-long courses, but other formats are applied as well. The courses are open to PhD students from other countries and institutions, but some prerequisites may apply. Please see the individual course descriptions.
The PhD courses are offered in English and are for PhD students only.