Can AI Help in Ideation? A Theory-Based Model for Idea Screening in Crowdsourcing Contests-Reference-Cited by-同舟云学术

Can AI Help in Ideation? A Theory-Based Model for Idea Screening in Crowdsourcing Contests

Published:2024-01 Issue:1 Volume:43 Page:54-72
ISSN:0732-2399
Container-title:Marketing Science
language:en
Short-container-title:Marketing Science

Author:

Bell J. Jason¹^ORCID,Pescher Christian²^ORCID,Tellis Gerard J.³^ORCID,Füller Johann⁴

Affiliation:

1. Saïd Business School, University of Oxford, Oxford OX1 1HP, United Kingdom;

2. Universidad de los Andes, Las Condes, Santiago, Chile;

3. Marshall School of Business, University of Southern California, Los Angeles, California 90089;

4. University of Innsbruck, 6020 Innsbruck, Austria

Abstract

Authors test previously published theory-based models in a sample of idea-screening contests and find that efficient, automated screening is possible using easy-to-collect data.

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Marketing,Business and International Management

Link

https://pubsonline.informs.org/doi/pdf/10.1287/mksc.2023.1434

Reference56 articles.

1. Choosing among Regularized Estimators in Empirical Economics: The Risk of Machine Learning

2. Design Crowdsourcing: The Impact on New Product Performance of Sourcing Design Solutions from the “Crowd”

3. Crowdsourcing New Product Ideas over Time: An Analysis of the Dell IdeaStorm Community

4. Uniting the Tribes: Using Text for Marketing Insight

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The AI‐augmented crowd: How human crowdvoters adopt AI (or not);Journal of Product Innovation Management;2023-11-27

2. EXPRESS: When Do Marketing Ideation Crowdsourcing Contests Create Shareholder Value? The Effect of Contest Design and Marketing Resource Factors;Journal of Marketing;2023-07-18

3. Training with AI: Evidence from chess computers;Strategic Management Journal;2023-05-22