Loading...
Paper Number
1009
Paper Type
Completed
Description
Although the use of cross-sectional surveys is widespread in Information Systems (IS) research and related disciplines, few papers address the survey development process. In order to ensure a standardized approach, comparable and valid results, as well as to guide researchers in quantitative research methods, this paper presents a framework for the survey development process in IS. Based on a Design Science Research (DSR) methodology, the framework was derived from a structured literature review of leading IS journals and refined by three focus group discussions among IS experts. The framework includes several steps and considerations on the sample size, variable selection, their order in the survey, protection against bias, ensuring validity and reliability, and testing before administering the survey with a focus on documentation and reporting. Our framework supports quantitative research by providing a structured approach to create reliable and credible surveys.
Recommended Citation
Mehler, Maren; Ellenrieder, Sara; Turan Akdag, Merve; Wagner, Amina; and Benbasat, Izak, "A Framework for Developing Cross-Sectional Surveys" (2023). ICIS 2023 Proceedings. 6.
https://aisel.aisnet.org/icis2023/generalis/generalis/6
A Framework for Developing Cross-Sectional Surveys
Although the use of cross-sectional surveys is widespread in Information Systems (IS) research and related disciplines, few papers address the survey development process. In order to ensure a standardized approach, comparable and valid results, as well as to guide researchers in quantitative research methods, this paper presents a framework for the survey development process in IS. Based on a Design Science Research (DSR) methodology, the framework was derived from a structured literature review of leading IS journals and refined by three focus group discussions among IS experts. The framework includes several steps and considerations on the sample size, variable selection, their order in the survey, protection against bias, ensuring validity and reliability, and testing before administering the survey with a focus on documentation and reporting. Our framework supports quantitative research by providing a structured approach to create reliable and credible surveys.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
02-General