Common Methods Bias: Does Common Methods Variance Really Bias Results?
Impact in
Classified as
- Authors
- D. Harold DotyWilliam H. Glick
- Journal
- Organizational Research Methods
In The Last Decade
doi.org/10.1177/109442819814002 →Countries where authors are citing Common Methods Bias: Does Common Methods Variance Really Bias Results?
This map shows the geographic impact of Common Methods Bias: Does Common Methods Variance Really Bias Results?. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Common Methods Bias: Does Common Methods Variance Really Bias Results? with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Common Methods Bias: Does Common Methods Variance Really Bias Results? more than expected).
Fields of papers citing Common Methods Bias: Does Common Methods Variance Really Bias Results?
This network shows the impact of Common Methods Bias: Does Common Methods Variance Really Bias Results?. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Common Methods Bias: Does Common Methods Variance Really Bias Results?.
About Common Methods Bias: Does Common Methods Variance Really Bias Results?
This paper, published in 1998, received 1.2k indexed citations . Written by D. Harold Doty and William H. Glick covering the research area of Social Psychology, Sociology and Political Science and Developmental and Educational Psychology. It is primarily cited by scholars working on Organizational Behavior and Human Resource Management (539 citations), Strategy and Management (281 citations), Sociology and Political Science (257 citations), Social Psychology (248 citations) and Management Information Systems (135 citations). Published in Organizational Research Methods.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/10.1177/109442819814002.