Z. John Zhang

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

• Z. John Zhang and Gila E. Fruchter (Working), Dynamic Targeted Promotions: A Customer Retention and Acquisition Perspective. Abstract

  This research analyzes the strategic use of targeted promotions for customer retention and acquisition in a dynamic and competitive environment. We develop suitable differential games for both finite- and infinite-time problems and provide analytical solutions in each case for defensive and offensive Nash equilibrium closed-loop strategies. Our analysis shows that a firm’s optimal targeting strategies, both offensive and defensive, in a dynamic setting depend on its actual market share, the relevant redemption rate of its targeted promotions, the value of its market share increase, and the effectiveness of its targeted promotions. Optimal targeting strategies call for a firm to increase its expenditure on defensive (offensive) targeting relative to offensive (defensive) targeting, thus focusing more on customer retention (customer switching), when its market share becomes larger (smaller). These optimal strategies have the attractive feature of being an adaptive control rule. A firm can operationalize these strategies by adjusting its planned promotional incentives on the basis of the observed differences between actual and planned market shares and between actual and planned redemption rates. In the long run, a focus on customer retention is not an optimal strategy for all firms. A firm with a sufficiently large market share should stress customer retention, whereas a firm with a small market share should stress customer acquisition. When market shares are more evenly divided in a market, firms are better off in the long run if they all focus on customer acquisition. Our analysis also suggests that to build a long-run market share advantage in the age of information-intensive marketing, a firm must strive to improve its targeting effectiveness and increase its unit profit margin. We illustrate the results through a numerical example and show the trajectories of a firm’s market share, promotional expenditures, and profits as competing firms use targeted promotions optimally over time.

• Vibhanshu Abhishek, Kinshuk Jerath, Z. John Zhang (Under Review), Platform Selling or Reselling? Channel Structures in Electronic Retailing (under review).
• Yuxin Chen and Z. John Zhang (Working), Price-for-Information Effect and Benefit of Behavior-Based Targeted Pricing.
• Yunchuan Liu and Z. John Zhang (Working), Pricing Implications of ‘Click-and-Mortar’ Combo.
• 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.
• 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

• 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

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

Knowledge @ Wharton

• How Dynamic Electricity Pricing Can Improve Market Efficiency, Knowledge @ Wharton - 11/12/2024
• Is Algorithmic Management Too Controlling?, Knowledge @ Wharton - 11/12/2024
• The Hidden Cost of AI Energy Consumption, Knowledge @ Wharton - 11/12/2024
• Charitable and Political Giving | Pinar Yildirim, Knowledge @ Wharton - 11/12/2024
• The Future of Banking, Knowledge @ Wharton - 11/11/2024
• Election Statistics, Knowledge @ Wharton - 11/06/2024
• Robots Are Taking Over Low-skilled Jobs — and Changing Votes, Knowledge @ Wharton - 11/05/2024
• Crypto Politics: Liberals’ and Conservatives’ Confidence in Cryptocurrencies, Knowledge @ Wharton - 11/05/2024
• Leadership and Elections | Mike Useem, Knowledge @ Wharton - 11/05/2024
• Automation Is Harming Low-skilled Workers and Possibly Their Voting Preferences, Knowledge @ Wharton - 11/01/2024