Research Overview:
My research studies how consumers and firms search for and learn from information, and how the stochastic environment created by dynamic information or evolving preferences can affect competitive behaviors. I examine the impact of information acquisition in B2B contexts such as sales, collaborations, and SaaS, as well as on firm’s market research, pricing, entry, and positioning strategies.
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Job Market Paper:

•  How to Make an Offer? A Stochastic Model of the Sales Process.    [Working Paper]

        Many firms rely on salespersons to communicate with prospective customers. Such person-to-person interaction allows for two-way discovery of product fit and flexibility on price, which are particularly important for business-to-business transactions. In this paper, I model the sales process as a game in which a buyer and a seller discover their match sequentially while bargaining for price. The match between the product’s attributes and the buyer’s needs is revealed gradually over time. The seller can make price offers without commitment, and the buyer decides whether to accept or wait. Players incur flow costs and can leave at any moment. The discovery process creates a hold-up problem for the buyer that causes him to leave too early and results in inefficient no-trades. This can be alleviated by the use of a list price that puts an upper bound on the seller’s offers. A lower list price encourages the buyer to stay while reducing the seller’s bargaining power. But in equilibrium the players always reach agreement at a discounted price. The model thus provides a novel rationale for the pattern of “list price - discount” observed in sales. I examine whether the seller should commit to a fixed price or allow bargaining. When the seller’s flow cost is high relative to the buyer’s, both players are willing to participate in discovery if and only if bargaining is allowed. In such a case, bargaining leads to a Pareto improvement, which explains the prevalent use of bargaining in sales. If the buyer has private information on his outside option, the model predicts that, counter-intuitively, the buyer with a higher net value for the product pays a lower price. The paper expands the bargaining literature by adding a discovery process that introduces a hold-up problem as well as making the product value stochastic.
 
Working Papers:

• Bargaining between Collaborators of a Stochastic Project.    [Working Paper]

         Many business activities require collaboration between firms. The expected surplus generated by the collaboration can evolve stochastically due to changing market conditions, arrival of new information, or discovery of fit between the collaborators. For the project to be implemented, both collaborators have to agree to implement as well as to agree on how the surplus is split. To understand this scenario, I study a model of bilateral bargaining between two symmetric players with a stochastic surplus. The proposer can make repeated offers without commitment to the responder, and they switch roles after some time to allow for counter-offers. The frequency of the counter-offers determines the relative bargaining power at each moment. The paper finds that, when the outside option is irrelevant, players implement the project with efficient delay. Upon implementation, the responder receives a larger share of the surplus than she receives under a static surplus. If the outside option is relevant, the collaboration is inefficient due to a hold-up problem faced by the responder. The model captures different bargaining procedures through varying the frequency of counter-offers, which affects the collaboration outcome. Increasing the frequency of counter-offers improves social efficiency by balancing the bargaining power. Furthermore, bargaining with more frequent counter-offers can lead to Pareto improvements; the proposer benefits too because the increase in efficiency can outweigh the loss of bargaining power. The paper makes a step in understanding how bargaining affects collaboration and why agents may choose to bargain in one way versus another.
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• The Effect of Label Informativeness on Price Sensitivity in the Cigarettes Market.   [Abstract]

        Cigarettes are sold in different strengths, commonly categorized as regular, light, or ultralight. In 2009, Congress passed Tobacco Control Act (TCA) which banned tobacco companies from communicating product strengths to consumers on any marketing or packaging materials. Cigarette companies continue to sell products of different strengths by using less informative color codes, i.e., relabeling Marlboro Light to Marlboro Gold or Camel Light to Camel Blue. Different brands do not use the exact same color codes, creating room for confusion. This paper investigates the effect of such change in label informativeness on consumer choices. Using a panel of smokers from 2007 to 2012, I find a sharp decline in price elasticity after the passage of TCA. This observation is robust to specifications that account for potential changes in consumer heterogeneity, state dependence, price endogeneity, or limited attention/consideration sets. These results suggest that consumers perceive the products as more differentiated after the cigarettes labels changed from strengths to color codes. This paper provides new evidence on the linkage between product labeling and consumer choice.

Works in Progress:

• Entry and Positioning with Sequential Market Research.

        Before entering a new market, a firm has to decide where to position its product amid uncertain consumer preferences. Firms can collect data through market research and make inference on consumer preferences. Information arrives sequentially, forcing firms to decide whether to conduct more research or position under the current information. A monopoly collects more information before entry as data and inference become cheaper and faster, and all uncertainty is eliminated in the limit. This limiting result does not hold if there is competition. When conducting research, firms have to weigh the benefit of more information against the risk of opponent entering at the preferred location first. This puts an upper-bound on the amount of information firms collect even as the cost of learning approaches zero. Thus the fight for being the first-mover prevents firms from fully utilizing the benefit of “big data”.
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• Evolving Preferences, Repeated Purchase, and Returns. (with J. Miguel Villas-Boas)

        We study the repeated purchase and return behaviors of a buyer with evolving preferences for a product with finite lifetime. For example, buyers of enterprise software or cloud computing services experience changing demand for these services. The SaaS or pay-as-you-go business models allow buyers to pay only when the demand is high. However, in reality, SaaS firms often require buyers to sign contracts, thus practicing a very coarse version of pay-as-you-go. We examine the relationship between the lifetime of the product, or contract length in the case of SaaS, and the lifetime value of the customer. We solve for the optimal pricing and contracting strategy. A buyer may learn more about the product when they own it than when they do not. In such a case, the buyer's behavior depends on her past purchases: the buyer has a lower purchasing threshold if she owned the product recently. This effect can explain why retention is easier than acquisition without explicit difference in cost.
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• Dynamic Re-positioning with Competition. (with J. Miguel Villas-Boas)