Konstan paper selected as one of Most Influential Articles in 2020

Congratulations to Distinguished McKnight University Professor Joe Konstan for having his collaborative paper on computational advertising selected as one of the Most Influential Articles in 2020 by the American Academy of Advertising Journals. The paper, Challenges and Future Directions of Computational Advertising Measurement Systems, was first published in the Journal of Advertising (Volume 49 - Issue 4).

The authors (Joseph T. Yun, Claire M. Segijn, Stewart Pearson, Edward C. Malthouse, Joseph A. Konstan, Venkatesh Shankar) present a measurement system framework for computational advertising to provide a common starting point for advertising researchers to begin addressing effectiveness challenges and discuss future research questions and directions for advertising researchers.

They also identify a larger role for measurement in the rapidly growing field of computational advertising and suggest that it is no longer something that happens at the end of the advertising process; instead, measurements of consumer behaviors become integral throughout the process of creating, executing, and evaluating advertising programs.

Throughout his prestigious career, Konstan's research has addressed a variety of human-computer interaction issues, including personalization (particularly through recommender systems), eliciting online participation, designing computer systems to improve public health, and ethical issues in research online. He is probably best known for his work in collaborative filtering recommenders (the GroupLens project, which won the ACM Software Systems Award in 2011).