Incentivized salespeople are often responsible for CRM activities that focus not only on customer acquisition, but also maintenance activities that increase customer lifetime value. While incentives can induce effort on the incentivized tasks, a salesperson's private information about customers...

The paper broadens the focus of empirical research on salesforce management to include multitasking settings with multidimensional incentives, where salespeople have private information about customers. This allows us to ask novel substantive questions around multidimensional incentive design...

The authors address two significant challenges in using online text reviews to obtain fine-grained attribute level sentiment ratings. First, they develop a deep learning convolutional-LSTM hybrid model to account for language structure, in contrast to methods that rely on word frequency. The...

Charities often send annual “thank you letters” to express gratitude to donors, but seek to defray these costs by inviting additional donations or engagement. However, the additional asks may backfire if potential donors see the thank you message as “insincere” or “manipulative.” We...

A critical element of word of mouth (WOM) or buzz marketing is to identify seeds, often central actors with high degree in the social network. Seed identification typically requires data on the full network structure, which is often unavailable. We therefore examine the impact of WOM seeding...

This paper offers a new identification strategy for disentangling structural state dependence from unobserved heterogeneity in preferences. Our strategy exploits market environments where there is a choice-consumption mismatch. We first demonstrate the effectiveness of our identification...

In response to price dispersion across stores and price promotions over time, consumers search across both stores and time, in many retail settings. Yet there is no search model in extant research that jointly endogenizes search in both dimensions. We develop a model of search across stores and...

We study the problem of constructing coresets for clustering problems with time series data. This problem has gained importance across many fields including biology, medicine, and economics due to the proliferation of sensors for real-time measurement and rapid drop in storage costs. In...

This paper introduces the problem of coresets for regression problems to panel data settings. We first define coresets for several variants of regression problems with panel data and then present efficient algorithms to construct coresets of size that depend polynomially on 1/ε (where ε is...

The paper develops a modeling framework to study how sustainability interventions impact consumer adoption of durable goods innovation, firm profit and environmental outcomes in equilibrium. Our two period model with forward looking consumers and a monopoly firm introducing an innovation in...