Testing and Controlling for Common Method Variance: A Review of Available Methods

Abstract

Several studies have debated over the prevalence of Common Method Variance (CMV) in organizational research. This paper highlights various procedural and statistical remedies to assess and control common method variance in any organizational study. It has been recognized that Common Method Variance (CMV) may significantly influence the research findings if it is not controlled properly through procedural and statistical remedies. However, researchers usually do not use all procedural remedies to remove potential impacts of CMV. Therefore, statistical remedies are strongly suggested to control and remove effects of CMV from data analysis. We have mentioned some common and effective statistical remedies from existing literature that have been widely used and recommended to control the effects of CMV. Moreover, we also discuss the challenge of CMV in relation to entrepreneurship studies and illustrate the problem utilizing an analysis of entrepreneurial competencies and business growth. In addition, we describe the possible solutions for minimizing the impact of common method bias by using the combination of several methods. This study strongly recommends using both procedural and statistical remedies to test and control the impacts of CMV from the research study.

The Influence of Information, Brand, Medical Representatives and Sales Promotion on Physician Prescribing Decision

“…This study utilised several tests to evaluate the issue of common method bias (CMB), for instance, Harman's one‐factor test and statistical correlations matrix, even though numerous procedures were employed to reduce the risks of CMB, such as reverse wording of questions, clarifying items and ensuring confidentiality of the respondents. In fact, CMB leads to the wrong internal consistency that is an apparent correlation between variables that results from their common source . The Harman's single factor was used to determine the presence of CMB .…”

“…In fact, CMB leads to the wrong internal consistency that is an apparent correlation between variables that results from their common source. [52] The Harman's single factor was used to determine the presence of CMB. [54] Using the SPSS v 19, the results showed the first factor (34.70%) did not account for a substantial amount of CMB, which is <50% the cutoff value (Table 1).…”

Sustainable business model innovation and acceptance of its practices among Spanish entrepreneurs

“…To prevent potential biases common in entrepreneurial studies analyzing entrepreneurs' competencies (Tehseen, Ramayah, & Sajilan, 2017) and their impact in business outcomes (growth, success, and TBL), we opted to follow the recommendations of Tehseen et al (2017) and chose some of their procedural controls as we shared the entrepreneurial context and technique of analysis. To prevent potential biases common in entrepreneurial studies analyzing entrepreneurs' competencies (Tehseen, Ramayah, & Sajilan, 2017) and their impact in business outcomes (growth, success, and TBL), we opted to follow the recommendations of Tehseen et al (2017) and chose some of their procedural controls as we shared the entrepreneurial context and technique of analysis.…”

“…To collect our data, we developed a questionnaire to be distributed and administered online. To prevent potential biases common in entrepreneurial studies analyzing entrepreneurs' competencies (Tehseen, Ramayah, & Sajilan, 2017) and their impact in business outcomes (growth, success, and TBL), we opted to follow the recommendations of Tehseen et al (2017) and chose some of their procedural controls as we shared the entrepreneurial context and technique of analysis. As for procedural remedies and to reduce ambiguity and complexity of item formulations, we tested the initial versions of the questions with nine experts, 11 and versions of the draft questionnaire were sent out in two waves to a sample population of 998 entrepreneurs.…”

“…As for procedural remedies and to reduce ambiguity and complexity of item formulations, we tested the initial versions of the questions with nine experts, 11 and versions of the draft questionnaire were sent out in two waves to a sample population of 998 entrepreneurs. These tests helped us to limit the time spent in each section, and as suggested (Tehseen et al (2017), pp. 146-147), we also included different formats of response (e.g., randomly presenting the items or introducing supplementary binary items) for some of the constructs (particularly the dependent variable).…”