JAMS Q & A Measurement

We spoke with the guest editors of the upcoming JAMS Special Issue on Measuring Important Marketing Constructs to learn more about the inspiration behind this topic and their goals for advancing the field. In this Q&A, they discuss why strong construct measurement is essential for theory development, the importance of managerial relevance, and offer practical advice for scholars pursuing measurement-related research.

Guest Editors
John Hulland, University of Georgia
Kevin L. Sample, University of South Carolina
David M. Hardesty, University of Kentucky

Read the full Call for Papers: https://link.springer.com/journal/11747/updates/27810448
Submission Window: June 1, 2026 - July 31, 2026

1.     What motivated you to create this special issue on measuring important marketing constructs?

To properly study important phenomena it is critical to clearly define key constructs and establish appropriate measures. The majority of papers published in JAMS (and other Marketing journals) are focused primarily on testing relationships between constructs (i.e., testing theory), taking the adequacy of construct measures more or less for granted. In contrast, relatively little research focused on establishing strong measures for key constructs is published. The intent of our special issue, then,  is to emphasize the importance of finding/creating suitable measures.

2.     How important is managerial relevance in the submissions for this special issue?

Like all submissions to JAMS, the papers submitted to this special issue will be evaluated (in part) for their contributions to managerial practice. This is an important element in strong, publishable research.

3.     What advice would you give to scholars interested in contributing to measurement-related research?

Clearly define the construct(s) you seek to operationalize, and then carefully develop measures that reflect the construct definition(s). The latter requires completion of  a multi-step process that ensures both the reliability and validity of your measures. It is critically important to not cut corners while completing this process; the quality of measures generated will often be severely compromised as a result of rushing. Clearly differentiating the new measure from existing measures and demonstrating the superior predictive validity of the new measure compared to existing measures are critical to establish the need for the new measure.