Avoiding bias and fallacy in survey research: A behavioral multilevel approach

Mikko Ketokivi*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

38 Citations (Scopus)


Much like researchers in general management and organization theory interested in organization‐level phenomena, operations management researchers theorize and analyze entire operational systems, such as factories, supply chains, airports, or hospital wards. In discussing threats to measurement validity, we tend to focus on motivational factors such as social desirability, acquiescence, and other self‐serving biases. In this paper, I seek to complement these discussions by examining the broader question of how individual‐level responses can provide information on system‐level traits. In an empirical illustration, I apply multilevel factor analysis to examine the factor structure of organizational commitment in a sample of 2,355 informants embedded within 265 manufacturing plants. The conclusion is that understanding the multilevel essence of theoretical concepts is crucial and that confounding levels may lead to inferences that are not only biased but—much worse—fallacious.
Original languageEnglish
Peer-reviewed scientific journalJournal of Operations Management
Issue number4
Pages (from-to)380-402
Number of pages23
Publication statusPublished - 2019
MoE publication typeA1 Journal article - refereed


  • 512 Business and Management
  • fallacy
  • measurement
  • multilevel factor analysis
  • respondent bias
  • survey research


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