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• Article | Marketing Science | July–August 2020

  Price Bargaining and Competition in Online Platforms: An Empirical Analysis of the Daily Deal Market

  Lingling Zhang and Doug J. Chung

  The prevalence of online platforms opens new doors to traditional businesses for customer reach and revenue growth. This research investigates platform choice in a setting where prices are determined by negotiations between platforms and businesses. We compile a unique and comprehensive dataset from the U.S. daily deal market, where merchants offer deals to generate revenues and attract new customers. We specify and estimate a two-stage supply-side model in which platforms and merchants bargain on the wholesale price of deals. Based on Nash bargaining solutions, our model generates insights into how bargaining and competition jointly determine the price and firm profits. Our results show that there is systematic variation in bargaining power between platforms and merchants with different characteristics. By working with a bigger platform, merchants enjoy a larger customer base, but they are subject to lower margins due to less bargaining power during negotiations. Our counterfactual results quantify the value of platforms for merchants and show that merchants with lower bargaining power benefit more by working with a smaller platform. Regarding the impact of price negotiations on platform competition, we estimate that roughly 11% of the deals on a smaller platform are attributable to the platform’s lower level of revenue sharing.

  Keywords: business-to-business marketing; platform competition; Two-Sided Markets; price bargaining; daily deals; structural model; Two-Sided Platforms; Competition; Price; Negotiation;

  Citation:

  Zhang, Lingling, and Doug J. Chung. "Price Bargaining and Competition in Online Platforms: An Empirical Analysis of the Daily Deal Market." Marketing Science 39, no. 4 (July–August 2020): 687–706.  View Details

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• Article | Foundations and Trends® in Marketing | 2020

  A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?

  Doug J. Chung, Byungyeon Kim and Niladri B. Syam

  Personal selling represents one of the most important elements in the marketing mix, and appropriate management of the sales force is vital to achieving the organization’s objectives. Among the various instruments of sales management, compensation plays a pivotal role in motivating and incentivizing sales agents. This monograph reviews the evolution of research in sales compensation and discusses future trends and opportunities. Specifically, it examines the managerial relevance of the theoretical foundations, discussing the underlying reasons for their applicability (or lack thereof) in practice. Furthermore, the monograph surveys recent empirical methods—including field experiments and structural econometrics—that are practical for analyzing sales agents’ behavior under various compensation systems. It also discusses prominent areas of future research in the midst of a changing sales environment. In particular, this monograph sheds light on how the use of big data, machine learning, and artificial intelligence can affect sales strategy formulation and, thus, sales compensation systems to better motivate and incentivize an organization’s sales force.

  Keywords: Sales compensation; sales management; Sales strategy; principal-agent theory; structural econometrics; Field Experiments; Machine learning; artificial intelligence; Salesforce Management; Compensation and Benefits; Motivation and Incentives;

  Citation:

  Chung, Doug J., Byungyeon Kim, and Niladri B. Syam. "A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?" Foundations and Trends® in Marketing 14, no. 1 (2020): 1–52.  View Details

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• Teaching Note | HBS Case Collection | December 2019 (Revised March 2020)

  Sales Force Management at Nobel Ilac

  Doug J. Chung

  Teaching Note for HBS No. 519-067.

  Citation:

  Chung, Doug J. "Sales Force Management at Nobel Ilac." Harvard Business School Teaching Note 520-057, December 2019. (Revised March 2020.)  View Details

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