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Discussant: Evan Rawley NET Conference April 20, 2007

GEOGRAPHY AND ELECTRONIC COMMERCE: Measuring convenience, selection and price by Chris Forman, Anindya Ghose and Avi Goldfarb. Discussant: Evan Rawley NET Conference April 20, 2007. A VERY GOOD PAPER. Nice idea to address convenience, selection and price in an integrated manner

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Discussant: Evan Rawley NET Conference April 20, 2007

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  1. GEOGRAPHY AND ELECTRONIC COMMERCE: Measuring convenience, selection and priceby Chris Forman, Anindya Ghose and Avi Goldfarb Discussant: Evan Rawley NET Conference April 20, 2007

  2. A VERY GOOD PAPER • Nice idea to address convenience, selection and price in an integrated manner • Great data • Very clever to blend data from Amazon.com with data on new store openings • Interesting results • Evidence that geographic location of offline retailers has a meaningful effect on online sales. Particularly strong effects for popular items. • Broad support for the long tail theory of online retailing and Salop’s (1979) notion of spatially differentiated markets • Well written • A pleasure to read

  3. COMMENTS ON HYPOTHESES • Hypotheses emphasize the impact of distance to offline retailers on online substitution, but empirical findings are not based on variation in distance. • H6 (effects show be larger for fiction versus non-fiction) is non-intuitive. Why do consumers want to browse fiction more than non-fiction?

  4. OPERATIONALIZATION OF ENTRY MATTERSSome Confusion As to What Exactly is Being Tested • Entry defined as “whether a discount store or large bookstore entered location j prior to time t” (p.14) • In the extreme (e.g., all entry in the first month and all books in the top 10 changed in the month following entry) the tests are pooled cross-sections rather than differences-in-differences. • If entry is really “ever entry” then demand results seem more likely to be related to heterogeneous time-varying demand characteristics of markets rather than supply shocks. • Also raises the issue of censoring with respect to the number of offline retailers.

  5. ENDOGENOUS ENTRY CHOICE IS A THREAT TO CAUSAL INFERENCE • Is the offline retailers’ location choice correlated with local market demand characteristics that vary over time? • Example: Retailer locates in exurbs because of space and growing population. If exurban dwellers are systematically different from urban dwellers in the sense that their preferences are less stable over time then the relationship between offline entry and changes in demand patterns may be correlations rather than causal relationships. • Describe locations where entry occurred. Match control and treatment groups by similarity of locations. City x miles New location

  6. UNOBSERVED HETEROGENEITY IN PRICING MAY CONFOUND PRICE AND CONVENIENCE EFFECTS • Price is important, but we do not observe offline retailer prices. Analysis assumes offline retail price is always undiscounted. • Do offline retailers systematically discount prices when they enter? Particularly worrying for best sellers, which may be used as loss leaders to build initial traffic. • Evidence about offline retailer entry pricing?

  7. THE IMPACT OF DISTANCE AND RETAILER CHARACTERISTICS DON’T MATCH THE STORY • Results show larger effects of entry on demand when offline retailer is within 20 miles compared to when retailer is within 5.4 miles of the center of the Amazon location of interest in 8 of 10 interactions. • Contrary to the spatial model • Discounters have a larger effect on online demand compared to large bookstores for books in the top 150-5,000. • Puzzling because discounters offer less choice than large bookstores

  8. SUMMARY OF COMMENTS • Tighter link between hypotheses and tests is desirable • Pricing results could be strengthened by evidence about offline pricing behavior • Market-level fixed effects are nice but does not completely solve the endogeneity problem • Would be interesting to understand how distance influences online offline substitution a bit better

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