I am using the UTAUT2 model in my study. One of the reviewers of my research paper has conveyed that Harman’s one-factor test is strictly discouraged for common method variance / CMB. I have gone through the video of Prof. Gaskin using the marker variable. However, my study does not employ a “marker” variable and hence this cannot be achieved in my study.
I have gone through some of the seminal papers in which the recommended approach is summarized as follows:
1. Using a priori procedural remedies to deal with CMB
a. Single respondent and single-source biases
b. Questionnaire biases
2. Using post hoc methods to test CMB using partial correlation procedures
a. Using the assumed source of method variance (e.g. social desirability)
b. Using the marker variable (I.e. variables expected to be theoretically unrelated to at least one of the focal variables)
c. Estimate a general factor score by conducting EFA of all variables to calculate a scale score for the first (unrotated) factor and then partial out this effect by using the general factor score as a covariate.
It is also mentioned that the above approaches are based on assumptions that do not hold for many survey studies. Please suggest if there are any detailed write-ups (step-by-step procedures using SPSS/AMOS ) or videos related to using apriori and post hoc methods to test CMB.
Raja, there is a nice article by Jim Conway and Chuck Lance available via ResearchGate:
Article What Reviewers Should Expect from Authors Regarding Common M...
In this article, the authors suggest that there are three prevailing misconceptions about common method bias that can impede the progress of research:
(a) that relationships between self-reported variables are necessarily and routinely upwardly biased,
(b) that other-reports (or other methods) are superior to self-reports, and
(c) that rating sources (e.g., self, other) constitute mere alternative measurement methods.
The authors argue against these misconceptions and make recommendations
for what reviewers (and others) should reasonably expect from authors regarding common method bias.
Hope this helps, Karin
some researchers recommended to use different Likert scale for IV and DV to overcome this bias. creating a time gap for the respondents in answering the different sections in the research questions or collecting data for IV for one group of respondents(such as employees) and DV for another type of respondents( such as employers) are some of the remedies to solve the common method bias as well. Thanks
This article is certainly worth reading: https://www.researchgate.net/publication/288020168_Common_methods_variance_detection_in_business_research
I would recommend a few of these readings:
MacKenzie, S.B. and Podsakoff, P.M., 2012. Common method bias in marketing: Causes, mechanisms, and procedural remedies. Journal of retailing, 88(4), pp.542-555.
Conway, J.M. and Lance, C.E., 2010. What reviewers should expect from authors regarding common method bias in organizational research. Journal of Business and Psychology, 25(3), pp.325-334.
Siemsen, E., Roth, A. and Oliveira, P., 2010. Common method bias in regression models with linear, quadratic, and interaction effects. Organizational research methods, 13(3), pp.456-476.
Kock, N., 2015. Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration (ijec), 11(4), pp.1-10.
Hope it helps.
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