Z. John Zhang

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

• Vibhanshu Abhishek, Kinshuk Jerath, Z. John Zhang (Forthcoming), Platform or Wholesale: Channel Structures in Electronic Retailing, CIST 2011.
• Martin Fritze, David Reibstein, Z. John Zhang, Cait Lamberton (Forthcoming), Capturing Consumer Crytocurrency Confidence and Bitcoin Price Dynamics.
• Z. John Zhang, Jia Liu, Eden Yin, Crossing the Chasm: It Takes a Country to Create Global Brands.
• Z. John Zhang, Yasid Soufi, Florian Kraus, Do Strategic Orientations Matter for a Really New Technology? The Case of Blockchain Projects.
• Z. John Zhang, Paola Mallucci, Tony Cui, Can Haggling Facilitate Price Collusion?.
• Z. John Zhang, Pinar Yildirim, Reto Hofstetter (Working), Rewarding Few or Many: Investigating the Impact of Rewards in Crowd-Sourcing Innovation Contests.
• Z. John Zhang, Tansev Geylani, Kinshuk Jerath (Under Revision), Competitive Store Brand Strategy in the Presence of One-Stop Shoppers.
• Z. John Zhang, Kinshuk Jerath, Serguei Netessine (Working), Can We All Get Along? Incentive Contracts to Bridge the Marketing and Operations Divide.
• Z. John Zhang, Kinshuk Jerath, Stephen Hoch (Working), In Pursuit of Retail Dominance: Market Dominance, Channel Dominance, or Both?.
• Z. John Zhang, Reto Hofstetter, Harley Krohmer, David Blatter (Working), Consumer Sensitivity to Price Increase Strategies: An Empirical Investigation.
• All Research from Z. John Zhang »

Past 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

• Wharton MBA Teaching Awards, 2023
• Wharton MBA Teaching Awards, 2022
• Finalist for the Long Term Impact Award, the INFORMS Society for Marketing Science., 2011
• Finalist for the O’Dell Award for the Most Impactful JMR Paper Five Years Later, 2007
• Wharton EMBA Electives Teaching Award., 2003
• John Little Award for the Best Paper in Marketing Science, 2001
• Frank Bass Award for the Best Dissertation Paper, 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

• How Lenovo Is Leveraging the Brand from East to West, Knowledge@Wharton - 09/21/2005

Knowledge @ Wharton

• When AI Makes Financial Decisions, Knowledge @ Wharton - 10/13/2026
• What Does It Mean to Be ‘Happy’ at Work?, Knowledge @ Wharton - 10/13/2026
• How AI Planning Could Create Financial Market Fragility, Knowledge @ Wharton - 10/13/2026
• 2026 AI Adoption Report, Knowledge @ Wharton - 10/13/2026
• Who Controls a Company’s Values After It Is Sold?, Knowledge @ Wharton - 10/09/2026
• How Lucky Strike Entertainment Is Betting on Screen-Free Experiences, Knowledge @ Wharton - 10/08/2026
• Why People Would Rather Give Nothing Than Too Little, Knowledge @ Wharton - 10/08/2026
• The Data Behind College Football’s New Era, Knowledge @ Wharton - 10/07/2026
• AI Safety Has Reached a Critical Point, Knowledge @ Wharton - 10/07/2026
• AI’s Impact on Financial Services, Knowledge @ Wharton - 10/05/2026