The paper investigates early stage “modern” grocery retail adoption in an emerging market using primary household level panel data on grocery purchases in India's largest city, Mumbai. Specifically, we seek insight on which socioeconomic class is more likely to adopt, and why. We model...

Prior to a new product launch, marketers need to infer how demand will respond to various levels of marketing mix variables in order to set an appropriate marketing plan. A critical challenge in estimating marketing mix responsiveness from historical data is that the observed decisions were...

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...

We randomize advertising content motivated by the psychology literature on sympathy generation and framing effects in mailings to about 185,000 prospective new donors in India. We find significant impact on the number of donors and amounts donated consistent with sympathy biases such as the...

Charities routinely send “thank you letters” and small gifts to express gratitude to donors but seek to defray these costs by making additional asks for donations and/or engagement. But the “ask for more” can backfire if potential donors perceive persuasive intent in the expression of...

We randomize advertising content motivated by the psychology literature on sympathy generation and framing effects in mailings to about 185,000 prospective new donors in India. We find significant impact on the number of donors and amounts donated consistent with sympathy biases such as the...

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...

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...

The Internet has dramatically reduced search costs for customers through tools such as shopbots. The conventional wisdom is that this reduction in search costs will increase price competition leading to a decline in prices and profits for online firms. In this paper, we provide an argument for...

The Internet has dramatically reduced search costs for customers through tools such as shopbots. The conventional wisdom is that this reduction in search costs will increase price competition leading to a decline in prices and profits for online firms. In this paper, we provide an argument for...