Moments of Impact
Smith faculty are shaping policy, business and society through influential research and public service. From AI and insurance reform to pay equity and public pensions, they’re winning top awards and earning national recognition for impact and innovation across disciplines.
ISSIP Honors Smith’s Roland Rust for ‘Advancing Service Innovation'
Smith’s Roland Rust has been named a 2025 ISSIP Fellow for pioneering contributions to service research, including founding key conferences and journals, and advancing AI scholarship in the field. He ranks among the world’s top 100 business research scientists.
Name That Tune: Smith Professor Combines Academic Rigor, Entrepreneurial Application and Musical Innovation
Associate Professor Daniel McCarthy blends rigorous research with creative teaching tools—like music—to make marketing analytics memorable. His focus on customer-based valuation, real-world applications, and student engagement helps transform complex concepts into impactful, real-life learning experiences.
Identifying Competitors in Geographical Markets Using the CSIS Method
Businesses with physical footprints – hotels, retailers, and restaurants – must identify the competitors that matter most. Traditional approaches using brand tier or proximity often fail in dynamic or asymmetric markets. We introduce the Conditional Sure Independence Screening (CSIS) method to marketing to identify true competitors based on their pricing influence on a focal firm’s demand. CSIS is computationally efficient, robust to spatial mis-specifications, and effective for identifying, asymmetric, even non-local, and segment-specific competition.
The Tax Revenue and Problem-Gambling Balancing Act
Research co-authored by associate professor Dan McCarthy finds that online sports betting legalization has led to a rise in irresponsible gambling, especially among lower-income individuals. The study highlights financial risks and calls for safeguards to mitigate potential societal harm.
The Language of Buying: Deciphering AI Conversations
Marketing PhD student Ziting Liao, with faculty Liye Ma and Wendy Moe, developed a model predicting purchase intent from AI assistant interactions. By analyzing language patterns, the tool helps advertisers better target consumers and optimize strategies based on intent.