Z. John Zhang

Z. John Zhang
  • Tsai Wan-Tsai Professor
  • Professor of Marketing
  • Founding Director, Penn Wharton China Center

Contact Information

  • office Address:

    754 Jon M. Huntsman Hall
    3730 Walnut Street
    University of Pennsylvania
    Philadelphia, PA 19104

Research Interests: channel and retail management., competitive strategies, market entry, targeted pricing and other pricing strategies

Links: CV

Overview

Professor Z. John Zhang’s research focuses on targeted pricing and other pricing strategies, competitive strategies, market entry and channel and retail management. Recent work probed the complex, unintended pitfalls of targeted pricing – the process of targeting a competitor’s customers with lower prices – in the fast-moving Internet age. Zhang’s research suggested that while this approach isn’t for every business, it can be an effective tool under the right circumstances. Zhang also provided guidelines to help companies understand when targeted pricing might play an effective role in their marketing strategy.

Professor Zhang’s research has been published in top-tier academic journals including Marketing Science, Management Science and the Journal of Marketing Research. He also serves as Area Editor for Marketing Science, Management Scienceand Quantitative Marketing and Economics, and has won numerous academic and teaching awards.

Professor Zhang currently teaches Marketing Management to EMTM students, and Pricing Strategies to undergraduate and MBA. He also teaches pricing strategies to executives in China in Chinese.

Professor Zhang received a PhD and MA in economics from the University of Michigan , a PhD and MA in History and Sociology of Science and Technology from the University of Pennsylvania , and a BA in Engineering Automation from Huazhong University of Science and Technology in Hubei, China.

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Research

Current Projects: Targeting and channel strategies; behavior-based targeted pricing; demand collection systems.

  • Z. John Zhang, Yunchuan Liu, Sunil Gupta (Working), Sherlock Holmes’ Dog and Retail Online Expansion.

  • Z. John Zhang, Fred Feinberg, Aradhna krishna (Working), Should Price Increases Be Targeted?.

    Abstract: Firms in many industries experience protracted periods of pricing power, the ability to successfully enact price increases. In these situations, firms must decide not only whether to raise prices, but to whom. Specifically, in a competitive context, they must determine whether it is more profitable to increase prices across-the-board or to a specific segment of their customer base. While selective price decreases are ubiquitous in practice (e.g., better deals to potential new customers by phone carriers; better deals to current customers by various magazines), to our knowledge selective price increases are relatively rare. We illustrate the benefits of targeted price increases, and, as such, we expand the repertoire of firms' promotional policies. To that end, we explore a scenario where two competing firms must decide whether to increase prices to the entire market or only to a specific segment. Targeted price increases (TPI), i.e., being offered an unchanged price (selectively) when others are subject to price increases, can be offered to Loyals (those who bought from the firm in the previous period) or Switchers (those who did not). The effects of TPIs are estimated through a laboratory experiment and an associated stochastic model, each allowing for both rational (Loyalty, Switching) and behaviorist (Betrayal, Jealousy) effects. We find that TPIs can indeed yield beneficial results (greater retention for Loyals or greater attraction of Switchers) and greater profits in certain circumstances. Results for TPI are additionally benchmarked against those for targeted price decreases and are found to differ. The range of effects stemming from the experiment can be used in a competitive analysis to yield equilibrium strategies for the two firms. In this case, we find that—depending on the magnitude of the price increase, market shares of the two firms, and price knowledge across consumer segments—a firm may wish to embrace targeted price increases in some situations, to institute across-the-board price increases in others, and to not enact any price increases in still others. We show that a firm can sacrifice considerable profit if it settles on a suboptimal pricing strategy (e.g., wrongly instituting an across-the-board increase), favors the wrong segment (e.g., Switchers instead of Loyals), or ignores "behaviorist" effects (Betrayal or Jealousy).

  • Yuxin Chen and Z. John Zhang (Working), Targeted Pricing and Channel Management.

  • Z. John Zhang and Dongsheng Zhou (Working), The Art of Price War: a Perspective from China.

  • Yunchuan Liu and Z. John Zhang (Working), The Benefit of Targeted Pricing in a Channel.

  • Yuxin Chen, Yogesh Joshi, Jagmohan Raju, Z. John Zhang (Forthcoming), A Theory of Combative Advertising, Marketing Science, 2006.

  • Vibhanshu Abhishek, Kinshuk Jerath, Z. John Zhang (Forthcoming), Platform or Wholesale: Channel Structures in Electronic Retailing, CIST 2011.

  • Yuxin Chen, Sridhar Moorthy, Z. John Zhang (Working), A Non-Price-Discrimination Theory of Rebates.

  • Upender Subramanian, Jagmohan Raju, Z. John Zhang (Working), Customer Value Based Management: Competitive Implications.

    Abstract: Many ?firms today quantify the value of individual customers and serve them differentially; providing better service, prices and other inducements to high value customers. We refer to this practice as Customer Value-based Management (CVM). While previous research and popular press has strongly advocated CVM, ?firms have often met with mixed results. One possible reason why actual outcomes differ from anticipated results could be that ?firms often implement CVM in a competitive environment. Our objective is to study CVM explicitly in a competitive setting. We find that while some recommendations and prescriptions from past research continue to apply in a competitive environment, some others do not. For example, we find that one of the benefits of CVM in a competitive setting is that it can discourage the rival from competing intensely, by increasing the rival’s chances of acquiring unprofitable customers. In this context, low-value customers can play an important strategic role by limiting the intensity of rival’s poaching. Consequently, ?firing low value customers or even increasing their value may prove counter-productive.

  • Z. John Zhang (Working), Dominant Retailer and Channel Coordination.

Teaching

All Courses

  • MKTG2540 - Pricing Policy

    The pricing decision process including economic, marketing, and behavioral phenomena which constitute the environment for pricing decisions and the information and analytic tools useful to the decision maker.

  • MKTG2880 - Pricing Strategies

    This course is designed to equip students with the concepts, techniques, and latest thinking on pricing issues, with an emphasis on ways in which to help a firm improve its pricing. The orientation of the course is about practice of pricing, not theory. We will focus on how firms can improve profitability through pricing, look at how firms set their prices and how to improve current practices to increase profitability. The first part of the course focuses on how to analyze costs, customers, and competitors in order to formulate proactive pricing strategies. The second part focuses on price promotions, price bundling, price discrimination, versioning, nonlinear pricing, pricing through a distribution channel, dynamic pricing, etc.

  • MKTG3990 - Independent Study

  • MKTG7540 - Pricing Policy

    The course provides a systematic presentation of the factors to be considered when setting price, and shows how pricing alternatives are developed. Analytical methods are developed and new approaches are explored for solving pricing decisions.

  • MKTG8990 - Independent Study

    A student contemplating an independent study project must first find a faculty member who agrees to supervise and approve the student's written proposal as an independent study (MKTG 899). If a student wishes the proposed work to be used to meet the ASP requirement, he/she should then submit the approved proposal to the MBA adviser who will determine if it is an appropriate substitute. Such substitutions will only be approved prior to the beginning of the semester.

  • MKTG9550 - Econ/Or Models in Mktg B

    This is a continuation of MKTG 954. This doctoral seminar reviews analytical models relevant to improving various aspects of marketing decisions such as new product launch, product line design, pricing strategy, advertising decisions, sales force organization and compensation, distribution channel design and promotion decisions. The primary focus will be on analytical models. The seminar will introduce the students to various types of analytical models used in research in marketing, including game theory models for competitive analysis, agency theory models for improving organization design and incentives within organizations, and optimization methods to improve decision making and resource allocation. The course will enable students to become familiar with applications of these techniques in the marketing literature and prepare the students to apply these and other analytical approaches to research problems that are of interest to the students.

  • MKTG9950 - Dissertation

    Dissertation

  • WH2160 - Global Modular Course

    TBD

Awards and Honors

  • Finalist for the O’Dell Award for the Most Impactful JMR Paper Five Years Later, 2007
  • Wharton EMBA Electives Teaching Award., 2003
  • Frank Bass Award for the Best Dissertation Paper, 2001
  • John Little Award for the Best Paper in Marketing Science, 2001
  • Eugene Lang Research Fellowship, Columbia University, 2000
  • Eugene Lang Research Fellowship, Columbia University, 1999
  • Rackham Fellowship, University of Michigan, 1992
  • Maas Research Fellowship, University of Michigan, 1990
  • Pensfield Fellowship, University of Pennsylvania, 1987
  • The Newcomen Award for Best Essay in History of Technology, 1987
  • Mellon Fellowship, University of Pennsylvania, 1986
  • Dean’s Fellowship, University of Pennsylvania, 1985

Activity

Latest Research

Z. John Zhang, Yunchuan Liu, Sunil Gupta (Working), Sherlock Holmes’ Dog and Retail Online Expansion.
All Research

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