EMPIRICAL RESEARCH METHODS IN BUSINESS ADMINISTRATION
FALL ‘05
Madhu Viswanathan
Office: 61 Wohlers
Ph. 333-4550
Office hours: By appointment
Class Time & Place: Wednesdays10:00 - 1:00
Availability of Assigned Material Readings for first few weeks available at 339 Wohlers
Overview
The course will aim to provide a foundation for designing and using methods to perform empirical research in business areas. The seminar will be structured around a framework of measurement principles covered in the first part of the course. Using these measurement principles as a foundation, the second part of the course will be devoted to discussing issues about specific methods listed below such as experimental designs and survey designs. The third part of the course will cover some miscellaneous issues in research methods and presentations by students.
Topics
At the heart of scientific inquiry is the ability to measure phenomena through the use of research methods. Principles of measurement relate the abstract domain of ideas, theories and hypotheses, to the operational domain of research methods. The first part of the course will cover the basics of measurement in the social sciences.
Part IPrinciples of measurement
(i) Introduction to measurement
(ii) Reliability in measurement Indicators of reliability
Assessment of reliability using data sets
(iii) Validity in measurement Indicators of validity
Assessment of types of validity including convergent, discriminant, and nomological
validity
Assessment of dimensionality using exploratory factor analysis
(iv) Understanding measurementAn in-depth examination of types
errorof measurement error, their causes, and their
consequences
(v) Using LISREL in measurementConfirmatory factor analyses
Introduction to LISREL Simultaneous assessment of measurement and theory using structural equations
(vi) Measurement applications in business
This portion of the course aims to provide a basis to view research methods from a measurement perspective as well as a working knowledge of the assessment of reliability and validity of measurement procedures. Using these measurement principles as a foundation the second part of the course will be devoted to discussing issues about specific methods listed below.
Part IISpecific research methods
(i) Validity of research designsValidity of research designs
Trade-offs between types of validity
(ii) Experimental research designsBasics of experimental designs
Types of designs Manipulation checks; demand artifacts, etc.
Applications in business
(iii) Survey research designsMeasurement error in surveys
Question wording effects Response scale effects
Applications in business
(iv) Qualitative research designsIntroduction to qualitative designs
Applications in business
The third part of the course will cover some miscellaneous issues in research methods and papers developed by students.
Part IIIPaper presentations and miscellaneous issues
Background required to take course
While the course will require students to have a background in statistics, in depth knowledge of multivariate statistics is not necessary. The assignments will require knowledge of a statistical package (preferably SPSS) to run programs such as reliability, and factor analyses.
Students in different areas of business administration are encouraged to bring in readings of interest to them for class discussion. One assignment will specifically require students to bring in applications of topic areas covered in the course.
Course requirements
(i)Class participation 40%
(The course will use a discussion format.
Students will be responsible for weekly readings and
will be expected to lead class discussions)
(ii)Assignments 10%
(The course will involve several assignments
throughout the semester including analyses and
interpretation of data sets, designing research methods,
and critically assessing specific research designs.)
(iii)Paper/Presentation & Write-up50%
(The course requirements include the completion
of a project where students will choose a set of
hypotheses of interest and develop a research
method to test the hypotheses. A paper based
on this project as well as a class presentation
will be required. Various sections of the paper
will be due during the course of the semester.
Requests for extension will not be considered
except for valid medical or personal reasons.
The project will involve application of course
material in designing the method for a study and
providing rationale for it. For example, a survey
or an experiment or a qualitative method could
be used. Data collection is encouraged but not
necessary. Further details are provided under
the assignment schedule.)
Text
Measurement Error and Research Design (2005) by Madhu Viswanathan, Sage Publications (
OVERVIEW OF SCHEDULE
Part I Principles of Measurement
August 31Introduction to measurement
The Measure development process
Introduction to reliability
September 7 Reliability (con’td)
Introduction to factor analysis
Reliability assignment due
September 14Reliability (cont’d)
Factor analysis (cont’d)
Introduction to validity
Factor analysis assignment due
Paper topic due
September 21Validity (cont’d)
Summary of reliability, factor analysis and validity
Understanding measurement error
Validity assignment due
September 28Error assignment due
Understanding measurement error
Front end of paper due
October 5Understanding measurement error
Using Structural Equation Modeling in measurement
Part IISpecific Research Methods
October 12Using Structural Equation Modeling in measurement cont’d
Measurement Applications
Validity of research designs
Participation in debate on validity
October 19Validity of research designs (cont’d)
October 26Experimental research methods (cont’d)
Overview of methods section due
November 2Survey research methods
November 9Survey research methods (cont’d)
Qualitative research methods
Details of methods sections due
Part IIIPaper presentations and miscellaneous issues
November 16Qualitative research methods (cont’d)
Miscellanoues issues
November 30Paper Presentations
December 5Final paper due
DETAILED SCHEDULE
PART I - PRINCIPLES OF MEASUREMENT
August 31
Reading assignment
Introduction to Measurement
Kerlinger, Fred N. (1986), "Constructs, Variables, and Definitions," Foundations of Behavioral Research, New York: Holt, Rinehart and Winston, 26-44.
Nunnally, Jum C., and Ira H. Bernstein (1994), "Introduction," Psychometric Theory, New York: McGraw Hill, Chapter 1, 3-30.
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 1-10.
The Measure Development Process
Churchill, Gilbert A., Jr. (1979), "A Paradigm for Developing Better Measures of Marketing Constructs," Journal of Marketing Research, 16 (February), 64-73, (Read pages 64-68, i.e., pages 195-199 on the reprinted version).
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 11-18.
Introduction to Reliability
Devellis, Robert F. (1991), Scale Development: Theory and Applications, Sage Publications Inc., 51-90.
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 18-29.
September 7
Reliability assignment due (available at - scale in Page 15 of Viswanathan book)
Reading assignment
Reliability (cont’d)
Devellis, Robert F. (1991), Scale Development: Theory and Applications, Sage Publications Inc., 12-42.
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 18-29.
Introduction to Factor Analyses
Hair, Joseph F., Jr. et al. (1979), Multivariate Data Analysis, Tulsa, Oklahoma: Petroleum Publishing Company, Chapter 6, 223-253.
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 29-35.
September 14
Paper topic due
Factor analyses assignment due (available at
Reading assignment
Reliability (cont’d)
Devellis, Robert F. (1991), Scale Development: Theory and Applications, Sage Publications Inc., 12-42.
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 18-29.
Factor Analyses (cont’d)
Hair, Joseph F., Jr. et al. (1979), Multivariate Data Analysis, Tulsa, Oklahoma: Petroleum Publishing Company, Chapter 6, 223-253.
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 29-35.
Introduction to Validity
Churchill, Gilbert A., Jr. (1979), "A Paradigm for Developing Better Measures of Marketing Constructs," Journal of Marketing Research, 16 (February), 64-73, (Read pages 69-73, i.e., pages 200-204 on the reprinted version).
Nunnally, Jum C., and Ira H. Bernstein (1994), “Validity,” Psychometric Theory (3rd ed.), New York: McGraw-Hill, 83-113.
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 61-75.
September 21
Validity assignment due (Pages 63-65 of the Viswanathan book are used for this assignment)
Reading assignment
Validity (cont’d)
Campbell, Donald T. and Donald W. Fiske (1959), "Convergent and Discriminant Validation by the Multitrait-Multimethod Matrix," Psychological Bulletin, 56 (March), 100-122.
Reliability, Factor analysis, and Validity - Summary
Devellis, Robert F. (1991), Scale Development: Theory and Applications, Sage Publications Inc., 12-42.
Hair, Joseph F., Jr. et al. (1979), Multivariate Data Analysis, Tulsa, Oklahoma: Petroleum Publishing Company, Chapter 6, 223-253.
Churchill, Gilbert A., Jr. (1979), "A Paradigm for Developing Better Measures of Marketing Constructs," Journal of Marketing Research, 16 (February), 64-73.
Nunnally, Jum C., and Ira H. Bernstein (1994), “Validity,” Psychometric Theory (3rd ed.), New York: McGraw-Hill, 83-113.
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 1-35; 61-75.
Understanding Measurement Error
Viswanathan (2005), “What is Measurement Error?,” Measurement Error and Research
Design, CA: Sage Publications, Chapter 2, 97-134.
Viswanathan (2005), “What Causes Measurement Error?,” Measurement Error and
Research Design, CA: Sage Publications, Chapter 3, 135-148.
September 28
Front end of paper due
Error assignment due (Pages 123-134 of Viswanathan text)
Reading assignment
Understanding Measurement Error
Viswanathan (2005), “What is Measurement Error?,” Measurement Error and Research
Design, CA: Sage Publications, Chapter 2, 97-134.
Viswanathan (2005), “What Causes Measurement Error?,” Measurement Error and
Research Design, CA: Sage Publications, Chapter 3, 135-148.
Viswanathan (2005), “Can Empirical Procedures Pinpoint Types of Measurement Error?,”
Measurement Error and Research Design, CA: Sage Publications, Chapter 4, 149-
159.
October 5
Revisit error assignment
Reading assignment
Using Structural Equation Modeling in measurement
Viswanathan (2005), “What is Measurement?,” Measurement Error and Research Design,
CA: Sage Publications, Chapter 1, 35-61.
Ecob, Russell, and Peter Cuttance, “An overview of structural equation modeling,” Structural Modeling By Example: Applications in Educational, Sociological, and Behavioral Research, Peter Cuttance and Russell Ecob (eds.), NY: Cambridge University Press.
Long, Scott, Confirmatory Factor Analysis, Sage Publications Inc., 1983, pages 11-34.
Long, Scott, Covariance Structure Models: An Introduction to LISREL, Sage Publications Inc., 1983, pages 11-24.
Anderson, James C. and David W. Gerbing (1988), "An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment," Journal of Marketing Research, 25 (May), 186-192.
Judd, Charles M., Jessor, Richard, and Donovan, John E. (1986). Structural equation models and personality research. Journal of Personality, 54 (1), 149-198.
Understanding Measurement Error cont’d
Viswanathan (2005), “How Can Measurement Error be Identified and Corrected For in
Measure Development?,” Measurement Error and Research Design, CA: Sage Publications, Chapter 5, 161-196.
PART II - SPECIFIC RESEARCH METHODS
October 12
Using Structural Equation Modeling in measurement cont’d from previous part
Bollen, K. A., & Lennox, R. (1991). Conventional wisdom on measurement: A structural equation
perspective. Psychological Bulletin,110(2), 305–314.
Viswanathan (2005), “How Do Measures Differ?,” Measurement Error and Research
Design, CA: Sage Publications, Chapter 7, 228-238.
Measurement Applicationscont’d from previous part
Viswanathan (2005), “What are Examples of Measures and Measurement Across Various
Disciplines?,” Measurement Error and Research Design, CA: Sage Publications,
Chapter 8, 239-288.
Assignment: Debate on validity
Reading assignment
Validity of research designs
Cook, Thomas D. and Donald T. Campbell, "Validity," Quasi-Experimentation: Design & Analysis Issues for Field Settings, 37-94.
Calder, Bobby J. et al. (1981), "Designing Research for Application," Journal of
Consumer Research, 8 (September), 197-207.
Lynch, John G., Jr. (1982), "On the External Validity of Experiments in Consumer Research," Journal of Consumer Research, 9 (December), 225-239.
Lynch, John G., Jr. (1983), "The Role of External Validity in Theoretical Research," Journal of Consumer Research, 10 (June), 109-111.
Calder, Bobby J. et al. (1983), "Beyond External Validity," Journal of Consumer Research, 10 (June), 112-114.
October 19
Reading assignment
Validity of research designs (cont’d)
McGrath, Joseph E. and David Brinberg (1983), "External Validity and the Research Process: A Comment on the Calder/Lynch Dialogue," Journal of Consumer Research, 10 (June), 115-124.
Berkowitz, Leonard and Edward Donnerstein (1982), "External Validity is More Than Skin Deep," American Psychologist, 37 (March), 245-257.
Mook, Douglas G. (1983), "In Defense of External Invalidity," American Psychologist, (April), 379-387.
Ellsworth, Phoebe C. (1977), From Abstract Ideas to Concrete Instance: Some Guidelines for Choosing Natural Research Settings,” American Psychologist, 604-615.
Viswanathan (2005), “How Does Measurement Error Affect Research Designs?,”
Measurement Error and Research Design, CA: Sage Publications, Chapter 10, 307-
310; 329-336; 343-346.
October 26
Overview of methods section of paper due
Reading assignment
Experimental Research Designs
Perdue, Barbara C. and John O. Summers (1986), "Checking the Success of Manipulations in Marketing Experiments," Journal of Marketing Research, 23 (November),317-326.
Greenwald, Anthony G. (1976), "Within Subjects Designs: To Use or Not to Use?" Psychological Bulletin, 83(2), 314-320.
Viswanathan (2005), “How Does Measurement Error Affect Research Designs?,”
Measurement Error and Research Design, CA: Sage Publications, Chapter 10, 307-
310; 315-336; 340-343.
November 2
Reading assignment
Survey Research Designs
Viswanathan (2005), “How Does Measurement Error Affect Research Designs?,”
Measurement Error and Research Design, CA: Sage Publications, Chapter 10, 310-
315; 337-339.
Fowler, Floyd, “Designing Questions to be Good Measures,” Survey Research Methods, Sage Publications Inc., pages 69-93.
Schwarz, Norbert, and Hans-Jurgen Hippler (1991), "Response Alternatives: The Impact of their Choice and Presentation Order," in Paul B. Biemer et al. (eds.), Measurement Error in Surveys, 41-56, Wiley: NY.
Cox, Eli (1980), “The Optimal Number of Response Alternatives in a Scale: A Review,” Journal of Marketing Research, 17, 407-422.
Viswanathan (2005), “How Do Measures Differ?,” Measurement Error and Research
Design, CA: Sage Publications, Chapter 7, 213-228.
November 9
Details of methods section of paper due
Reading Assignment
Cox, Eli (1980), “The Optimal Number of Response Alternatives in a Scale: A Review,” Journal of Marketing Research, 17, 407-422.
Qualitative Research methods
Hirschman, Elizabeth C. (1986), “Humanistic Inquiry in Marketing Research: Philosophy, Method, and Criteria,” Journal of Marketing Research, 23, 237-49.
Papers from guest speakers
November 16
Reading assignment
Qualitative research (cont’d)
Hirschman, Elizabeth C. (1986), “Humanistic Inquiry in Marketing Research: Philosophy, Method, and Criteria,” Journal of Marketing Research, 23, 237-49.
Viswanathan (2005), “What is the Role of Measurement in Science?,” Measurement Error
and Research Design, CA: Sage Publications, Chapter 11, 347-382.
Papers from guest speakers
November 30
Paper Presentations
December 5
Final paper due
ASSIGNMENT SCHEDULE
This assignment schedule excludes reading assignments which are listed in detail earlier. Data sets for assignments are available at
September 7Reliability assignment due
Factor analyses assignment due
September 15Validity assignment due
Paper topic due
September 21Error assignment due
September 28Front end of paper due(i.e., conceptualization & hypotheses)
October 12Participation in debate on validity
October 26Overview of methods section due(i.e., rough draft)
November 9Details of methods section due(i.e., stimuli, questionnaire, etc.)
November 30Paper Presentations
December 5Final paper due
Informal assignments include the provision of papers which are applications of a particular topic area to you for class discussion. These papers can ideally be given to me 1-2 weeks before scheduled class discussion on that topic. Areas in which papers are invited include (i) measurement applications, (ii) experimental research methods, (iii) survey research methods, and (iv) qualitative research methods. In addition, students are encouraged to suggest papers for any topic covered during the semester as well as for any additional topics.
At the beginning of the semester, each student can give me 3-5 papers that reflect your present research interests. This is important to enable me to educate myself on your interests. Choose papers that are different enough to cover a range of your interests.
Throughout the latter part of the semester, we will also have discussions of each person’s class project. These discussions will provide a useful forum to obtain feedback on your individual projects and monitor your own progress.
DESCRIPTION OF ASSIGNMENTS
Details of some weekly assignments will be provided during the course of the semester.
Reading assignments
In terms of reading assignments, students are expected to read assigned material and be prepared to lead class discussion. As you learn the material, write down questions that come to mind. Also, try to work through examples during reading and raise these examples in class discussion. I will provide a set of discussion questions for each week about a week in advance. However, we do not need to be constrained by these questions alone. Students are strongly encouraged to raise questions at appropriate times in the discussion. Class participation will involve both raising questions and attempting to answer questions raised.
Project
The project will consist of several phases that are listed below. You are encouraged to discuss your project with me during the course of the semester. Several assignments pertaining to the project are due during the course of the semester. These assignments are intended to facilitate feedback and ensure completion of the paper based on the project.
(i) Identify theory/past research that will form the basis for your paper. While in-depth discussion and theorizing is not central to the purpose of this paper, it is important that you are clear about the rationale/theory for the hypotheses for purposes of designing the method. Further, you need to know past research in terms of methodological issues in order to provide support for your own method.
(ii) Develop and state the hypotheses that you are going to test. Parts i and ii are due on September 28.
(iii) Develop the overall design and provide the rationale for choosing it to test your hypotheses.
(iv) Clearly describe the independent and dependent variables and their operationalizations. As a part of the paper you are required to develop a multiple-item measure for at least one variable which should have at least five items.
Parts iii and iv are due on October 26.
(v) Provide complete details of all materials to be used. If you are using a questionnaire, the complete questionnaire must be presented. If you are conducting an experiment, all materials should be presented. The paper should provide support for choice of materials. The final paper should contain an appendix where all materials are presented. The reader should be able to go out and collect data immediately using the information provided. Describe all details such as the participants in the study, the exact procedure to be employed, etc., along with rationale for your choice. As you consider your paper, make sure you have addressed the issues we cover in class such as reliability, validity, internal versus external validity, etc.. These principles should be used to develop your method and also to provide support for your choices.
Part v is due on November 9.
(vi) Describe the data analyses that you would perform on the data including assessment of reliability, validity, usage of LISREL, etc.