Information Entropy as a Quality Control Tool in Survey Research

Authors

  • Dan Friesner North Dakota State University
  • Carl S. Bozman Gonzaga University
  • Matthew McPherson Gonzaga University
  • Faith Valente North Idaho College
  • Anqing Zhang George Washington University, Children’s National Medical Center

DOI:

https://doi.org/10.33423/jmdc.v17i1.5909

Keywords:

marketing development, survey design, information entropy, scale development, Tobit regression

Abstract

This manuscript assesses whether information entropy can be used to test for flaws within survey research. Under the study’s null hypothesis, a set of well-designed survey items should not exhibit systematic differences in the quantity of information – as measured by information entropy - provided by specific groups of respondents. The study was conducted within the context of a major amateur sporting event in 2018. Customer satisfaction was assessed using a survey whose core questions have been assessed repeatedly over time, and which contains two previously validated constructs. One construct (the List of Values) is unchanged from its original form. Another construct (the Basic Empathy Scale) contains two original survey items, with six additional survey items added to that construct (using the same response scale). Regression analysis indicates that the well-designed set of survey items exhibit no statistically significant differences in information entropy. The poorly designed survey items exhibit statistically significant differences in information entropy, suggesting that information entropy can be a useful quality control tool in survey design and assessment.

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Published

2023-03-22

How to Cite

Friesner, D., Bozman, C. S., McPherson, M., Valente, F., & Zhang, A. (2023). Information Entropy as a Quality Control Tool in Survey Research. Journal of Marketing Development and Competitiveness, 17(1). https://doi.org/10.33423/jmdc.v17i1.5909

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Section

Articles