Quantitative Research Methods Seminar (Weeks 14-22)


Chee-Wee Tan [cta.itm@cbs.dk] and Michel Avital [mav.itm@cbs.dk]

Course coordinator 

The Quantitative Research Methods course is designed for doctoral students who are interested in pursuing quantitative research projects in social sciences. A primary objective of the course is to help participants in acquiring the necessary skills that will enable them to design, execute, report and critically review quantitative research in social sciences with an emphasis on management as well as the field of information systems. Participants will gain foundational knowledge of quantitative research methods and the considerations that go into the design of empirical studies employing such methods.


The course is designed as a sequence of three-hour meetings, each covering a key topic in quantitative research methods in social sciences. The meetings are in the form of participatory seminars that comprise class presentations, directed discussions and practical workshops. In addition to an appreciative and/or critical review of extant literature on quantitative research methods, the seminars seek to encourage constructive dialogue aimed at helping students to tackle research questions in a quantitative fashion, which builds on and extends contemporary knowledge. Meetings are held on a weekly basis to allow sufficient time for in-depth reading and reflection.
Given the aforementioned learning objectives, the course is designed with a heavy reading load. Reading the materials beforehand and participating actively in class assignments and dialogues are essential for getting a firm grasp of the course content. For each seminar, students should read the assigned articles and be prepared to answer questions and discuss any other issues pertaining to the assigned reading material. Furthermore, for select seminars, students will be asked to prepare 20 – 30 minutes of introductory remarks that synthesize the readings and serve as a ‘conversation starter’ for class discussion.


Individual take-home 15 pages written exam will form the basis of student performance evaluation.  The take-home exam will be based on a given quantitative data set to be analyzed by the data analytical techniques covered during the course. From the data analysis, students will be required to submit a report summarizing the key insights from the analytical results, including the reliability and validity of latent constructs, sampling errors, common method bias as well as interesting findings from analyses of measurement and structural models.

Learning objectives 

At the end of the course, students should be able to:
-    Discuss the theories and methods that were presented in class and covered by the readings
-    Design valid and rigorous quantitative studies
-    Develop instruments for quantitative data collection
-    Identify and assess data sources and data collection methods for quantitative studies
-    Assess the reliability and validity of measures
-    Demonstrate understanding of quantitative data analysis techniques
-    Interpret analytical results from quantitative studies
-    Articulate in writing a formal description of research design and research analysis

Lecture plan 
Week Data Description
14 1 April Building Blocks in Context: Theory and Theorizing, Hypotheses and Relationships, Constructs and Variables
15 8 April Measurement: Measurement Properties, Construct Validity, Scale Development and Exploratory Factor Analysis (EFA)
16 15 April Survey Research and Field Studies
17 22 April Experimental and Quasi-Experimental Research
18 29 April Sampling, Data Collection Methods, Common Method and Response Biases
19 6 May Structural Equation Modeling (SEM): Confirmatory Factor Analysis (CFA), LISREL, Regression and Partial Least Squares (PLS)
20 13 May Structural Equation Modeling (SEM): Model Specification and Second-Order Constructs
21 20 May Mediation and Moderation
22 27 May Meta-Analysis
22 30 May Project Presentation

Classes are on Tuesday 8:30-11:30 (The last class is on Friday).

Course literature 

-    DeVellis, R. F. Scale Development: Theory and Applications (Vol. 26), Sage Publications, 2011.
-    Pedhazur, E. J., and Schmelkin, L. P. Measurement, Design, and Analysis: An Integrated Approach, Psychology Press, 2013.
Supplementary Readings:
Additional articles and resources will be provided on a need-to basis.


Research Proposal Presentation [Week 22 - Friday, May 30, 2014]
For the last session of the course, students 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 the 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

PhD School 
PhD School in Language, Law, Informatics, Operations Management, Accounting and Culture
Min number of participants 
Max number of participants 
Enroll no later than 
Friday, March 28, 2014 - 12:00