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...

We propose a model for word of mouth (WoM) management where a firm has two tools at hand: referral rewards and offering a free contract. Current customers' incentives to engage in WoM can affect the contracting problem of a firm in the presence of positive externalities of users. Formally, we...

We incorporate word of mouth (WoM) in a classic Maskin-Riley contracting problem, allowing for referral rewards to senders of WoM. Current customers' incentives to engage in WoM can affect the contracting problem of a firm in the presence of positive externalities of users. We fully characterize...

We incorporate word of mouth (WoM) in a classic Maskin-Riley contracting problem, allowing for referral rewards to senders of WoM. Current customers' incentives to engage in WoM can affect the contracting problem of a firm in the presence of positive externalities of users. We fully characterize...

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...