Research-All

In consumer goods markets, theory shows that it is generally profitable for sellers to use search-deterrence strategies to alter buyer search. These results rely on agents’ reacting solely to the economic content of these pressure tactics, ignoring any behaviorally based responses search deterrence may evoke. To test the validity of this assumption, this paper examines an experimental market where profit-maximizing strategy dictates that sellers should exercise one form of search deterrence, exploding offers. Sellers demonstrate a reluctance to use such offers against human buyers, but they are less reluctant to use them against computerized buyers. Human buyers are three times more likely to deviate from optimal strategy by rejecting rather than accepting these offers. Survey responses are consistent with other-regarding-preference-based reasons for sellers’ actions but not buyers’. Taken together, these results suggest the benefits of tactics that rely on pressuring decision-makers may be more nebulous than previously thought.

  • Identify Brand Satiation Using Purchase Data (With Venkatesh Shankar) (recent version)

In product categories such as yogurt, cereal and candy, consumers are likely to be satiated after frequent consumption of the same brand, leading to variety-seeking and switching to other brands. Prior research has modeled satiation mostly using consumption and preference data, but most firms have access to only purchase data. Identifying satiation and estimating satiation effect using purchase data remain a significant challenge. We provide rich evidence supporting effects of satiation using a scanner data set in a yogurt market and develop a Hidden Markov Model in which households may be temporarily stay in an unobserved “satiation” state. The results show that households may be occasionally satiated for a certain brand, and there is significant difference among the satiation probabilities for brands. Our Hidden Markov Model explains consumer satiation better than benchmark models.

Maintaining strong periodic shopping trips may be not easy for households, because they face uncertainties from consumption, external shock and other schedule conflicts. While the routinization of production makes households more efficient, the routinzation of shopping trips brings little benefit. What are the implications for those households who remain strong revisit patterns? We propose a distribution-wise measure of households’ revisit periodicity strength, and investigate its impacts on product choices using scanner datasets. The product-market level analysis shows that households with strong periodic revisit patterns are associated with weaker consumer inertia and have more product switches recorded. The data is consistent with the explanation that those households seek compensatory variety in product choice due to unobserved constraints in timing choice.

  • Explain Heterogeneity in State Dependence using “Fundamental” Switches (recent version)

This paper investigates state dependence effects in frequently purchased product markets. I use consumers’ switching behavior in different product categories to provide necessary variation and test whether the variation may explain differences in consumers’ responses to previous purchases and other relevant marketing variables. I find that part of the variation in switching behavior is stable: they explain a significant portion of consumers’ state dependence in different categories and different years consistently. The finding provides a different way to look at household switches, and contributes to the literature of estimating state dependence in the consumer goods market.

  • Does Trustworthiness Matter in an Optimal Contract? (With Debing Ni and Kaiming Zheng) (recent version)

This paper considers a modified principal-agent environment, where the agent makes costly work effort in exchange for wage, and the principal chooses a combination of fixed rate and piece rate transfer to the agent in hope for higher effort. Because the principal in our environment is liability constrained and because the production is subjected to great uncertainty, she suffers from significant efficiency loss with self-regarding agents. However, the agent may be potentially reciprocal. In our specific theoretic setting, by triggering some agents’ reciprocity preference, the principal may achieve a better outcome. Is it possible that principals reward agents’ trustworthiness and “trustworthy” agents improve labor market efficiency? We test the modified principal-agent model using a lab experiment. We find that, compared with a market with self-regarding agents, the market witnesses significant higher offers of fixed rate wage. Estimations on agents’ effort choice confirms the effects of both positive and negative reciprocity. It reveals that negative reciprocity has a greater impact on efforts and thus on principals’ wage offers. The estimated reciprocity reference point decreases over the experiment in the social information sessions, but not in the individual information sessions. Only at later rounds, principals’ offer are correlated with the trustworthiness level of the agents.

  • The Effect of Product (Aesthetic) Update on Sellers’ Pricing Strategies (with Kang Wang)

This paper investigates online sellers’ promotion strategies under product updates. Because consumers are forward looking for future price or product quality changes, they may decide to delay their purchase. Such behavior imposes great pressure on small online business; especially when they hold inventory for last generation products. We show that small online sellers should incorporate different forms of product updates into their promotion decisions. Using an e-commerce transaction dataset on iPhone transactions, we find evidence that the average price discount of an old generation before a cross-generation update (with aesthetic redesign) is significantly larger, compared with that before a within-generation update.

  • Customers’ shopping behavior on the E-commerce Platform (with Lengyang Wang)

Utilizing a transaction-based dataset, we hope to investigate some purchase patterns on E-commerce platforms (which cannot be studied previously).  Our mission is to think of a reasonable way that customers make choices on the platform. With an reasonable choice structure, we may address problems such as comparing gender differences in online purchasing behavior.