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He was awarded the prestigious 2018 Emerald Literati Outstanding Paper Award for co-authoring an article published in the leading journal Supply Chain Management: An International Journal.

The Emerald Literati Network Awards for Excellence rewarded the Information & Operations Management department Professor and holder of the Chair of Supply Chain and Operations Management at ESCP’s Berlin campus, for the paper entitled Statistical and Judgmental Criteria for Scale Purification, co-written with Andreas Wieland (Copenhagen Business School) , Joakim Kembro (Lund University) and Horst Treiblmaier (MODUL University, Vienna).

Scale purification is the process of eliminating items from multi-item scales, which is widespread in empirical research. “The assessment of whether items should be retained or eliminated (“scale purification”) is a vital part of the process of measuring theoretical constructs in empirical research that uses latent variables. Failures in this step – either by removing ‘good’ items or by not removing ‘bad’ items – result in constructs that are not sufficiently represented by the corresponding set of items. Quite importantly, this might severely impact the conceptual foundation of any research project,” the authors wrote.

In this publication, they discuss the methodological underpinning of scale purification, critically analyse the current state of scale purification in supply chain management (SCM) research, and provide suggestions for advancing the process. “While the lack of coherent guidelines on the scale-purification process is not specific to supply chain management (SCM), their absence poses a challenge to researchers in our discipline and filling this gap was thus necessary,” Christian Durach explains.
In order to do so, he and his co-authors developed a framework for making scale purification decisions, and used it to analyse and critically reflect on the application of scale purification in leading SCM journals. The results of their research highlight the need for rigorous scale purification decisions based on both statistical and judgmental criteria, and that the justification for scale purification in leading SCM journals needs to be driven by reliability, validity and parsimony considerations. “A lack of methodological rigor and coherence was identified when it comes to current purification practices in empirical SCM research by applying the proposed framework to the SCM discipline, he adds.” The framework and additional suggestions for methodological improvements provided by the authors, should help to advance the knowledge about scale purification.
What makes it even more interesting is that it is not only relevant for the SCM field, but for empirical research in general.

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