Ã山ǿ¼é

Sang-Pil Han

Associate Professor of Information Systems
WP Carey School of Business, Arizona State University

How User Adoption of ChatGPT Influences Search Volume and Variety in Traditional Search Engines.

Date: Friday, September 27, 2024
Time: 10:30 am - 12:00 pm EDT
Location: Bronfman Building, Room 046

All are cordially invited to attend.

About:

The rise of Large Language Models (LLMs) like ChatGPT is reshaping online information retrieval, significantly altering user interactions with traditional search engines. This study, grounded in Construal Level Theory and Information Foraging Theory, delves into these changes using extensive data from Nielsen’s panels. Our findings suggest that adopting ChatGPT not only addresses immediate user queries within the platform but also encourages users to conduct broader and more frequent searches on traditional search engines. Specifically, we observe a notable 33.0% increase in users’ product-related searches on major search engines, including Google and Bing, following their adoption of ChatGPT. This surge is particularly pronounced for high-construal-level searches, such as broad product categories and general attributes, compared to low-construal-level searches that focus on specific brands. Additionally, we document an expansion in the diversity of search keywords on traditional search engines, indicating a richer and more varied search landscape. Lesser-known brands are gaining increased visibility, demonstrating a long-tail effect where LLMs promote a broader array of options. Contrary to concerns that LLMs might disrupt traditional search engines, our results indicate that they act as complementary tools, enhancing the scope and depth of user searches. These insights highlight the necessity for academics, search engine operators, and marketers to adapt strategically to the evolving dynamics of the search industry.