Common method bias: Difference between revisions

From CEOpedia | Management online
(The LinkTitles extension automatically added links to existing pages (<a target="_blank" rel="noreferrer noopener" class="external free" href="https://github.com/bovender/LinkTitles">https://github.com/bovender/LinkTitles</a>).)
m (Text cleaning)
 
(2 intermediate revisions by the same user not shown)
Line 1: Line 1:
{{infobox4
|list1=
<ul>
<li>[[Critical incident technique]]</li>
<li>[[Longitudinal study]]</li>
<li>[[Social network analysis]]</li>
<li>[[Attributable risk]]</li>
<li>[[Analysis of variance]]</li>
<li>[[Fishbein model]]</li>
<li>[[Principal component analysis]]</li>
<li>[[Qualitative market research]]</li>
<li>[[Leniency error]]</li>
</ul>
}}
'''Common [[method]] bias''' is a type of [[systematic error]] that occurs when people respond to surveys or questionnaires in a consistent and predictable way. This type of bias typically occurs when a single method is used to collect data from respondents, such as a questionnaire or an interview. This type of bias can lead to inaccurate, skewed or unreliable results, as respondents may be influenced by the same variables or respond to questions in the same way. From a [[management]] perspective, common method bias should be identified and addressed to ensure that research results are accurate and meaningful. This can be done by using multiple methods for data collection, such as surveys, interviews, focus groups and observation, to reduce the potential for bias.
'''Common [[method]] bias''' is a type of [[systematic error]] that occurs when people respond to surveys or questionnaires in a consistent and predictable way. This type of bias typically occurs when a single method is used to collect data from respondents, such as a questionnaire or an interview. This type of bias can lead to inaccurate, skewed or unreliable results, as respondents may be influenced by the same variables or respond to questions in the same way. From a [[management]] perspective, common method bias should be identified and addressed to ensure that research results are accurate and meaningful. This can be done by using multiple methods for data collection, such as surveys, interviews, focus groups and observation, to reduce the potential for bias.


Line 37: Line 22:
* Common method bias can lead to a lack of detail in the data, as the same questions are asked to all respondents.
* Common method bias can lead to a lack of detail in the data, as the same questions are asked to all respondents.


==Suggested literature==
{{infobox5|list1={{i5link|a=[[Sampling error]]}} &mdash; {{i5link|a=[[Sample selection bias]]}} &mdash; {{i5link|a=[[Data collection methods]]}} &mdash; {{i5link|a=[[Small sample size]]}} &mdash; {{i5link|a=[[Qualitative research techniques]]}} &mdash; {{i5link|a=[[Leniency error]]}} &mdash; {{i5link|a=[[Quantitative market research]]}} &mdash; {{i5link|a=[[Social desirability bias]]}} &mdash; {{i5link|a=[[Critical incident technique]]}} }}
 
==References==
* Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). ''[http://personal.psu.edu/jxb14/M554/articles/Podsakoffetal2003.pdf Common method biases in behavioral research: a critical review of the literature and recommended remedies]''. Journal of applied psychology, 88(5), 879.
* Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). ''[http://personal.psu.edu/jxb14/M554/articles/Podsakoffetal2003.pdf Common method biases in behavioral research: a critical review of the literature and recommended remedies]''. Journal of applied psychology, 88(5), 879.
* Chin, W. W., Thatcher, J. B., & Wright, R. T. (2012). ''[https://uh-ir.tdl.org/bitstream/handle/10657/6246/Chin_2012_AssessingCommonMethodBias.pdf?sequence=1&isAllowed=y Assessing common method bias: Problems with the Ulmc technique]''. MIS quarterly, 1003-1019.
* Chin, W. W., Thatcher, J. B., & Wright, R. T. (2012). ''[https://uh-ir.tdl.org/bitstream/handle/10657/6246/Chin_2012_AssessingCommonMethodBias.pdf?sequence=1&isAllowed=y Assessing common method bias: Problems with the Ulmc technique]''. MIS quarterly, 1003-1019.
[[Category:Quality_management]]
[[Category:Quality_management]]
[[Category:Methods and techniques]]
[[Category:Methods and techniques]]

Latest revision as of 18:30, 17 November 2023

Common method bias is a type of systematic error that occurs when people respond to surveys or questionnaires in a consistent and predictable way. This type of bias typically occurs when a single method is used to collect data from respondents, such as a questionnaire or an interview. This type of bias can lead to inaccurate, skewed or unreliable results, as respondents may be influenced by the same variables or respond to questions in the same way. From a management perspective, common method bias should be identified and addressed to ensure that research results are accurate and meaningful. This can be done by using multiple methods for data collection, such as surveys, interviews, focus groups and observation, to reduce the potential for bias.

Example of common method bias

  • A common example of common method bias is when a researcher uses the same questionnaire to collect data from participants. For example, if a researcher uses a questionnaire asking participants to rate their level of satisfaction with a product, respondents may be more likely to give higher ratings if the same survey is used multiple times. This could lead to inaccurate results, as respondents may be influenced by the familiarity of the survey.
  • Another example of common method bias is when a researcher interviews participants using the same approach, such as asking the same questions in the same order. This can lead to respondents giving the same answers due to the familiarity of the questions, which can lead to inaccurate results.
  • A third example of common method bias is when a researcher uses the same type of observation to gather data. For example, if a researcher observes participants using the same method every time, it can lead to respondents behaving in a way that they think the researcher expects. This can lead to inaccurate results, as the behavior of the participants may be influenced by the familiarity of the observation method.

Types of common method bias

Common method bias can be categorized into several types, including self-reporting bias, response bias, interviewer bias, and observational bias.

  • Self-reporting bias occurs when respondents provide inaccurate or incomplete information due to a lack of knowledge, or a desire to present themselves in a favorable light.
  • Response bias occurs when respondents are influenced by the interviewer's behavior or expectations, or when they provide responses that conform to societal expectations or stereotypes.
  • Interviewer bias occurs when researchers allow their own opinions or expectations to influence the data collection process.
  • Observational bias occurs when researchers are influenced by their own preconceived notions, expectations, or biases when observing or recording data.

Common method bias can lead to inaccurate and unreliable results, as it can influence the data collection process:

  • People may respond to questions in the same way due to the use of a single method, leading to inaccurate results.
  • Respondents may be influenced by the same variables, such as social desirability, leading to skewed results.
  • Data collection methods that rely on self-reported information are prone to common method bias, as people may not accurately report their feelings or experiences.
  • Respondents may have difficulty expressing their true thoughts or feelings due to the limited number of questions used in the survey.
  • Common method bias can lead to a lack of diversity in the data, as the same questions are asked to all respondents.
  • The data collected may be biased due to a lack of control over the environment in which the survey is conducted.
  • Common method bias can lead to a lack of detail in the data, as the same questions are asked to all respondents.


Common method biasrecommended articles
Sampling errorSample selection biasData collection methodsSmall sample sizeQualitative research techniquesLeniency errorQuantitative market researchSocial desirability biasCritical incident technique

References