Digitizing doctor demand: The impact of online reviews on doctor choice
| Authors | Luca, Vats |
| Year | 2013 |
| Type | Working Paper |
| Abstract | We present empirical evidence for the impact of patient reviews on consumers' physician choices. Our study is based on ZocDoc.com - a unique website that integrates patient reviews, and appointment scheduling for physicians on one platform. Using ZocDoc we construct a novel data set consisting of all reviews written for primary care physicians in Manhattan, New York. We then pair these reviews with data on appointments that are booked through ZocDoc, during February-May, 2013. Our data suggest that patient reviews are becoming an important source of reputation for physicians. About 25% of New York primary care physicians are now listed on ZocDoc, and 84% of them have at least 5 reviews. Because ZocDoc displays each physician's rounded average rating to patients, we can use regression discontinuity to identify the causal impact of patient ratings on patient demand. We find that half a star improvement in ratings, on a scale of 1 to 5 stars, leads to a 10% increase in the likelihood, at the mean, that a doctor will fill an appointment. |
| URL | https://www.aeaweb.org/conference/2014/retrieve.php?pdfid=55.%20Accessed%205/23/18 |
| Tags | Archival Empirical | Consumer Decisions |
Peer effects and loan repayment: Evidence from the Krishna default crisis
| Authors | Breza |
| Year | 2012 |
| Type | Working Paper |
| Abstract | Around the world, microfinance ties borrowers together using group repayment meetings, shared oaths and often, joint liability. Microfinance institutions (MFIs) have invested heavily in building social capital and generally boast stellar repayment rates. However, recent repayment crises have fueled speculation that peer effects might also reinforce default behavior. I estimate the causal effect of peer repayment on individuals' repayment decisions in the absence of joint liability following a district-level default in which 100% of borrowers temporarily defaulted on their loans and after which borrowers gradually decided whether to repay. Because the defaults occurred simultaneously, the timing of the shock induced variation in repayment incentives both at the individual and peer group levels. Individuals (or peer groups) near the end of their 50-week loan cycles were closest to receiving new loans and had the strongest incentives to repay; those who had recently received disbursements had the weakest. Using the variation in the peer group's incentives to instrument for peer repayment, I find that if a borrower's peers shift from full default to full repayment, she is 10-15pp more likely to repay. Last, I present a dynamic discrete choice model of the repayment decision to estimate the net benefit of the peer mechanism to the MFI. Repayers' positive influence on others (not non-repayers' negative influence) mainly drives the effect. Thus, peer effects actually improve repayment rates relative to a counterfactual without peer effects. |
| URL | https://www0.gsb.columbia.edu/mygsb/faculty/research/pubfiles/6030/Draft_2013_april_v2.pdf |
| Tags | Archival Empirical | Financing- and Investment Decisions (Individual) |
Reviews, reputation, and revenue: The case of Yelp.Com
| Authors | Luca |
| Year | 2011 |
| Type | Working Paper |
| Abstract | Do online consumer reviews affect restaurant demand? I investigate this question using a novel dataset combining reviews from the website Yelp.com and restaurant data from the Washington State Department of Revenue. Because Yelp prominently displays a restaurant's rounded average rating, I can identify the causal impact of Yelp ratings on demand with a regression discontinuity framework that exploits Yelp's rounding thresholds. I present three findings about the impact of consumer reviews on the restaurant industry: (1) a one-star increase in Yelp rating leads to a 5-9 percent increase in revenue, (2) this effect is driven by independent restaurants; ratings do not affect restaurants with chain affiliation, and (3) chain restaurants have declined in market share as Yelp penetration has increased. This suggests that online consumer reviews substitute for more traditional forms of reputation. I then test whether consumers use these reviews in a way that is consistent with standard learning models. I present two additional findings: (4) consumers do not use all available information and are more responsive to quality changes that are more visible and (5) consumers respond more strongly when a rating contains more information. Consumer response to a restaurant's average rating is affected by the number of reviews and whether the reviewers are certified as "elite" by Yelp, but is unaffected by the size of the reviewers' Yelp friends network. |
| URL | https://ssrn.com/abstract=1928601 |
| Tags | Archival Empirical | Consumer Decisions |