How Does Bargaining Power Affect How We Shop?

Women Leading Research 2019: Lingling Zhang

Mar 18, 2019

SMITH BRAIN TRUST – Online platforms can see a direct correlation between the amount of bargaining power and platform size with merchants, new research from the University of Maryland’s Robert H. Smith School of Business shows.

A new study co-authored by Maryland Smith assistant professor Lingling Zhang investigates how the prevalence of online platforms opens doors for traditional businesses to innovate — that is, get lengthier customer reach and revenue growth. 

Their research examines platform choice in a context where prices are determined by negotiations between platforms and businesses, mimicking real-life models. And the results suggest a smaller platform is relatively more valuable to merchants with lower bargaining power, providing implications for platform choice.

“The daily deal market is a representative platform business, and price bargaining is an important element in the interactions between platforms and merchants,” they wrote. 

Bargaining power was defined as the additional ability of each party to influence the share of surplus. The results indicate smaller merchants who thus have less bargaining power benefit more by working with a smaller platform.

The experiment examined determinants of price setting and profit splitting between platforms and business users, as well as the extent to which price bargaining affected platform competition.

Zhang and her co-author used data from the U.S. daily deal market, with known platforms such as Groupon and LivingSocial that connect a merchant and consumer through sale of a daily assortment of discounted goods and services. 

Their research showed that bargaining and competition throughout the market jointly determines price and firm profits.

“By working with a bigger platform, merchants enjoy a larger customer base,” the researchers wrote. “But they are subject to lower margins due to less bargaining power during negotiations. Our results reveal the underlying primitives that determine pricing and the profit split between the platforms and merchants.”

Both a demand-side model and a supply-side model were used to track how platforms and merchants negotiate when platforms set the deal price.

The researchers’ scientific model for study allowed prices to be jointly determined by platforms and merchants, mimicking how platforms and merchants bargain to mutually agree upon a wholesale price, and then the sales began for tracking of theoretical data. 

Ultimately, the market proved largely to be a duopoly competition between Groupon and LivingSocial, where much of the data was generated.

“The daily deal business is a multibillion-dollar market in the U.S. alone and is even more profitable in developing economies, making it an important market to study in its own right,” they wrote.

Read more: Zhang, L.L., & Chung, D.J. (2018). Price Bargaining and Channel Selection in Online Platforms: An Empirical Analysis of the Daily Deal Market.

Lingling Zhang is an assistant professor of marketing at the University of Maryland’s Robert H. Smith School of Business.

Research interests: The effect of marketing strategies using data-driven empirical models; digital and multi-channel marketing; and econometric modeling of large quantity field data.

Selected accomplishments: Presented research at the INFORMS Marketing Science Conference and the Marketing Dynamics Conference; Fellow, American Marketing Association-Sheth Foundation Doctoral Consortium.

About this series: Maryland Smith celebrates Women Leading Research during Women’s History Month. The initiative is organized in partnership with ADVANCE, an initiative to transform the University of Maryland by investing in a culture of inclusive excellence. Other Women's History Month activities include the eighth annual Women Leading Women forum on March 5, 2019.

Other fearless ideas from:  Rajshree Agarwal  |  Ritu Agarwal  |  T. Leigh Anenson  |  Kathryn M. Bartol  |  Christine Beckman  |  Margrét Bjarnadóttir  |  M. Cecilia Bustamante  |  Jessica M. Clark  |  Rellie Derfler-Rozin  |  Waverly Ding  |  Wedad J. Elmaghraby  |  Rosellina Ferraro  |  Rebecca Hann  | Amna Kirmani  |  Hanna Lee  |  Hui Liao  |  Jennifer Carson Marr  |  Wendy W. Moe  |  Courtney Paulson  |  Louiqa Raschid  |  Rebecca Ratner  |  Rachelle Sampson  |  Debra L. Shapiro  |  M. Susan Taylor  |  Niratcha (Grace) Tungtisanont  |  Vijaya Venkataramani  |  Janet Wagner  |  Yajin Wang  | Liu Yang  |  Jie Zhang  |  Lingling Zhang



About the Expert(s)

Professor Zhang received her doctorate in Marketing from Harvard Business School in 2016. She is interested in studying competitive marketing strategies using empirical models including industrial organization. Her research focuses on business-to-business marketing, multi-channel marketing, and digital marketing. She has presented research at the INFORMS Marketing Science Conference and the Marketing Dynamics Conference. She teaches statistical programming in the MS Marketing Analytics program and marketing research in the undergraduate program.

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