JAMS 2023 Award Winners

Introduction

The Journal of the Academy of Marketing Science announces the winners of a series of awards

POSTING TYPE: Journal News

Posted by: Stephanie and Charlies Nobel


Journal of the Academy of Marketing Science (JAMS) Announces 2023 Award Winners

JAMS is delighted to announce several award winners for scholarly and editorial contributions to the journal in 2023 and prior. These award winners were selected through various processes by the retiring editorial team of John Hulland, Mark Houston and Gaia Ribera and were announced at the 2024 Academy of Marketing Science meeting by incoming Editors-in-Chief: Charles Noble & Stephanie Noble.

We are deeply grateful to all the contributors who have helped JAMS achieve the highest impact factor among all Marketing journals!

Best Area Editors:

  • Frank Germann
  • Son Lam
  • Bulent Menguc
  • Cristel Russell
  • Jenny van Doorn

Best Reviewers:

  • Sascha Alavi
  • Thomas Baker
  • Francois Carrillat
  • Flora Gu
  • Hannah Kim
  • Unnati Narang
  • Ralitza Nikolaeva
  • Gretchen Ross

JAMS Sheth Foundation “Best Paper” Award

Winner:

Thorsten Hennig-Thurau, Dorothea N. Aliman, Alina M. Herting, Gerrit P. Cziehso, Marc Linder & Raoul V. Kübler, “Social interactions in the metaverse: Framework, initial evidence, and research roadmap”.

Other Finalists:

Leigh McAlister, Frank Germann, Natalie Chisam, Pete Hayes, Adriana Lynch & Bill Stewart “A taxonomy of marketing organizations”.

Christian Homburg & Moritz Tischer “Customer journey management capability in business-to-business markets: Its bright and dark sides and overall impact on firm performance”.

Young Woong Park, Glenn B. Voss & Zannie Giraud Voss “Advancing customer diversity, equity, and inclusion: Measurement, stakeholder influence, and the role of marketing”.

William Fritz, Rhonda Hadi & Andrew Stephen “From tablet to table: How augmented reality influences food desirability”.

AMS – Parasuraman Best JAMS Paper for Long-Term Impact Award

Winner:

Jorg Henseler, Christian Ringle and Marko Sarstedt, “A New Criterion for Assessing Discriminant Validity in Variance-based Structural Equation Modeling”, Volume 43 (2015).

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