Abstract
As a research method, the survey is known to be subject to various types of biases. Nevertheless, a survey is often the most direct and cost-effective way to solicit people's opinions. We emphasize that, regardless of the data collection method, it is impossible to remove all potential biases in a research setting. Aside from adhering to research design best practice, authors are responsible for providing sufficient transparency in the reporting of their work to enhance replicability and to allow others to evaluate the validity of their research. In this paper, we develop a reporting guideline for IS survey research. Researchers conducting IS survey research can use this guide as a checklist when they prepare their manuscripts, and peer reviewers can use it to evaluate research quality and the sufficiency of reporting. We hope that similar guidelines can be developed for other IS research methods and that their use and endorsement by research outlets can motivate researchers to pay greater attention to research design and data quality.
Original language | English |
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Article number | 113136 |
Journal | Decision Support Systems |
Volume | 126 |
Early online date | 20 Aug 2019 |
DOIs | |
Publication status | Published - Nov 2019 |
Funding
Carrie has taught business information technologies, human computer interactions and game development subjects in Australia and China. She received research funds and consultancy contracts from the Department of Local Government of Queensland, Australia for projects for interactive training for skilled workers.
Keywords
- Replicability
- Reporting guidelines
- Survey