The Kilts Family Faculty Research Prize for Excellence in Marketing

Awarded biennially, the Kilts Family Faculty Research Prize for Excellence in Marketing recognizes a member of Chicago Booth's faculty for exceptional research, teaching, or other notable achievements in the field of marketing.

Past Recipients

Berkeley Dietvorst

2024 Winner

Berkeley J. Dietvorst, associate professor of marketing

Beidi Hu, Celia Gaertig, and Berkeley J. Dietvorst, "How Should Time Estimates Be Structured to Increase Customer Satisfaction?"

This paper by Hu, Gaertig, and Dietvorst is part of Berkeley's larger research agenda on aligning algorithms with consumer preferences, a crucial topic for firms using recommendation systems, navigation apps, and other tools. This paper demonstrates where more research is needed to better understand these preferences so that algorithms serve consumers better. Berkeley's work suggests that tailoring algorithms to user preferences in specific domains, rather than using generic statistical functions, can benefit organizations. The crucial insight is that core algorithm components are often designed without considering user preferences, potentially leading to misalignment. This implies companies can improve customer satisfaction by acknowledging the inherent uncertainty in predictions. This work has direct implications for any consumer-facing time estimation systems, and it outlines practical changes that companies can make to increase consumer satisfaction with algorithmically-derived estimates.

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2024 Winner
Avner Strulov Shlain

2022 Winner

Avner Strulov-Shlain, associate professor of marketing

Avner Strulov-Shlain, “More than a Penny’s Worth: Left Digit Bias and Firm Pricing”

Avner's paper takes an effect from the behavioral economics literature called the "left digit bias" that causes firms to use 99-ending prices ($4.99 rather than $5.00) and examines how it affects firms' profitability when used effectively and when used ineffectively. First, he measures the size of the bias using demand data from over three thousand products. Given this bias, he then finds that firms (retailers) engage in mispricing, acting as though they underappreciate 99-ending prices' effects on profitability. The paper has clear theoretical relevance (other left digit bias papers are mostly about consumer behavior, the demand side—this paper is also about firms) and practical relevance, insofar as retailers forgo 1 to 4 percent of gross profits by not capitalizing on left digit bias. The paper demonstrates technical elegance by presenting a model of left-digit-biased demand, which in turn, gives us the estimate of foregone retailer profitability.

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2022 Winner