Data Quality Procedures in Survey Research: An Analysis and Framework for Doctoral Program Curricula

Authors

James Burleson, California Polytechnic State University, San Luis Obispo
Gregory J. Bott, The University of Alabama
Michelle Carter, Alliance Manchester Business School
Jalal Sarabadani, San Jose State UniversityFollow

Publication Date

9-1-2023

Document Type

Article

Publication Title

Journal of Information Systems Education

Volume

34

Issue

4

First Page

418

Last Page

429

Abstract

To ensure validity in survey research, it is imperative that we properly educate doctoral students on best practices in data quality procedures. A 14-year analysis of 679 studies in the AIS “Basket of 8” journals noted undercommunication in the most pertinent procedures, consistent across journals and time. Given recent calls for improvements in data transparency, scholars must be educated on the importance and methods for ensuring data quality. Thus, to guide the education of doctoral students, we present a “5-C Framework'' of data quality procedures derived from a wide-ranging literature review. Additionally, we describe a set of guidelines regarding enacting and communicating data quality procedures in survey research.

Keywords

Data management, Doctoral program, IS curriculum, IS research

Department

Information Systems and Technology

Recommended Citation

James Burleson, Gregory J. Bott, Michelle Carter, and Jalal Sarabadani. "Data Quality Procedures in Survey Research: An Analysis and Framework for Doctoral Program Curricula" Journal of Information Systems Education (2023): 418-429.