This editorial introduces the special section on Advances in Computational Advertising. We define computational advertising, as well as discuss the historical background and conceptualization of the computational advertising field. We describe the unique thought leadership forum (TLF) model that was developed to facilitate new research collaboration among scholars from varying academic disciplines, methodological and disciplinary perspectives, and different expertise to examine important and timely issues related to computational advertising and to set a forward-looking research agenda for the next decade and beyond. Five articles resulting from the TLF project and included in this special section are briefly discussed. Then, we identify future challenges and opportunities of computational advertising and propose future research directions.
Bibliographical noteFunding Information:
We thank Journal of Advertising Editor-in-Chief Shelly Rodgers for her leadership and support, and Ron Faber, Jaideep Srivastava, and Stewart Pearson for their review of an earlier version of this article and valuable input. We also acknowledge contributions of all the reviewers who reviewed the submitted articles and provided constructive feedback and suggestions. The Hubbard School of Journalism and Mass Communication at the University of Minnesota provided financial support for the conference and hosted the three-day event. Thank you to Jay Kandampully, editor of the Journal of Service Management, and Venky Shankar, former editor of the Journal of Interactive Marketing, for advice on organizing the TLF. Thank you also to Joe Yun and the members of TLF Team 5 for helping create Table 1, and Joe Konstan for discussion about our closing comments.
© 2020 The Author(s). Published with license by Taylor and Francis Group, LLC.