“Scale purification” – the process of eliminating items from multi-item scales – is widespread in empirical research, but studies that critically examine the implications of this process are scarce. The goals of this research are threefold: to discuss the methodological underpinning of scale purification, to critically analyze the current state of scale purification in supply chain management (SCM) research and to provide suggestions for advancing the scale-purification process.
A framework for making scale-purification decisions is developed and used to analyze and critically reflect on the application of scale purification in leading SCM journals.
This research highlights the need for rigorous scale-purification decisions based on both statistical and judgmental criteria. By applying the proposed framework to the SCM discipline, a lack of methodological rigor and coherence is identified when it comes to current purification practices in empirical SCM research. Suggestions for methodological improvements are provided.
The framework and additional suggestions will help to advance the knowledge about scale purification.
This paper demonstrates that the justification for scale purification needs to be driven by reliability, validity and parsimony considerations, and that this justification needs to be based on both statistical and judgmental criteria.
The authors would like to thank Florian Kock and the participants of the 2015 CSCMP European Research Seminar for valuable feedback on previous versions of this article. They would also like to thank the editor and two anonymous reviewers for very constructive comments, and the Kühne Foundation, Switzerland, for financial support of parts of this research.
Wieland, A., Durach, C.F., Kembro, J. and Treiblmaier, H. (2017), "Statistical and judgmental criteria for scale purification", Supply Chain Management, Vol. 22 No. 4, pp. 321-328. https://doi.org/10.1108/SCM-07-2016-0230
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