A pair of professors from the David Eccles School of Business have been honored for their work, with Sara Malik being recognized for her teaching and Stephen Carson bringing home a notable prize for research.

Each year, the University of Utah recognizes the achievements of exceptional faculty members in teaching, research, mentorship and service. Malik, an assistant professor in Accounting, was one of six professors across campus to be honored with the Early Career Teaching Award.

“Sara’s dedication to teaching and mentorship makes her an exceptional candidate for this award,” wrote one nominator. “I’ve seen firsthand how she inspires her students, fosters a caring environment, and goes the extra mile to ensure that everyone has the support they need.”

“Professor Malik’s innovative teaching style, paired with her exceptional personality and ability to connect with students as equals rather than as subordinates, has earned her immense respect within the business student community,” added another.

She is the first business school professor to win the ECTA in 25 years.

Meanwhile, Carson — Chair and Professor in the Department of Marketing — won the Management Science Best Paper Award (Marketing), which was presented at the 19th Annual Frank M. Bass UTD Frontiers of Research in Marketing Science conference.

Carson’s paper, co-written with Linyi Li, Shyam Gopinath, was titled: “History matters: The impact of online customer reviews across product generation.” It examines how online customer reviews for one generation of a product affect sales of another generation in the same product series.

The main intriguing result is that previous generation valence has a positive impact on current generation sales; however, current generation valence has a negative impact on previous generation sales. The positive impact of previous generation valence becomes even stronger (1) as the uncertainty (standard deviation) in reviews for the current generation increases and (2) when the current generation valence is high. In contrast, it becomes weaker (1) as the uncertainty in reviews for the previous generation increases and (2) when the current generation has been on the market for a longer period of time. Other results are discussed. Our data consist of intergenerational pairs of point-and-shoot cameras on the largest online seller of such devices, Amazon.com. We estimate the current and previous generation models jointly, allowing for errors to be clustered at the daily and product levels. In addition, we address endogeneity concerns over the online word of mouth measures by using instrumental variables.