Can a Computer Vision Algorithm Predict New Product Adoption?

We examine whether machine learning can predict the success of new crowdfunding ventures based on innovative design. Results from two field studies on Kickstarter and Indiegogo show that a computer vision API that mirrors the human capacity to efficiently categorize objects predicts project success.



Citation:

Ethan Pancer, Theodore Noseworthy, and Maxwell Poole (2018) ,"Can a Computer Vision Algorithm Predict New Product Adoption?", in E - European Advances in Consumer Research Volume 11, eds. Maggie Geuens, Mario Pandelaere, and Michel Tuan Pham, Iris Vermeir, Duluth, MN : Association for Consumer Research, Pages: 222-223.

Authors

Ethan Pancer, Saint Mary’s University, Canada
Theodore Noseworthy, Schulich School of Business, York University, Canada
Maxwell Poole, Saint Mary’s University, Canada



Volume

E - European Advances in Consumer Research Volume 11 | 2018



Share Proceeding

Featured papers

See More

Featured

A1. Trusting and Acting on Chance Online

Shivaun Anderberg, University of Sydney, Australia
Ellen Garbarino, University of Sydney, Australia

Read More

Featured

Surprise! The Positive Impact of Uncertainty on the Evaluation of Experiential Purchases

Iñigo Gallo, IESE Business School
LILY JAMPOL, Queen Mary University of London
Alberto Rampullo, IESE Business School
Thomas Gilovich, Cornell University, USA

Read More

Featured

Taking a Leaf out of my Review: The Asymmetrical Link between Linguistic Similarity and Attitude Certainty for Writers and Readers of Product Reviews

Ann Kronrod, University of Massachusetts, USA
Yakov Bart, Northeastern University, USA

Read More

Engage with Us

Becoming an Association for Consumer Research member is simple. Membership in ACR is relatively inexpensive, but brings significant benefits to its members.