EARNINGS AND RATINGS AT GOOGLE ANSWERS

I. INTRODUCTION Most research on Internet transactions considers online markets as forums to facilitate the sale of physical goods (Ellison and Fisher Ellison 2009; Goolsbee and Chevalier 2003). Sometimes the Internet is analyzed as a market for matching workers and firms for an ordinary real-world employment relationship (Kuhn 2004). But certain Web sites can also supplement or even replace in-person employment relationships. This is the approach at Google Answers, a web-based service that facilitates paid matches between "answerers" (who have answers or research skills) and "askers" (who offer payment for answers to their respective questions). I analyze all questions and answers from the inception of the Google Answers service through November 2003, and I find notable trends in answerer behavior: More experienced answerers provide answers with the characteristics askers most value, receiving higher ratings as a result. Answerer earnings increases in experience, consistent with learning on the job. Answerers who focus on particular question categories provide answers of higher quality but earn lower pay per hour (perhaps reflecting a lack of versatility). Answers provided during the business day receive higher payments per hour (a compensating differential for working when outside options are most attractive), but more experienced answerers tend to forego these opportunities. II. LITERATURE AND CONTEXT Google Answers is distinctive in that its entire service and entire employment relationship occur online. (In contrast, most online sales processes anticipate offline functions such as packing and sending merchandise.) In some respects, this online-only environment eases analysis: A researcher may see the answerer's entire service, letting the researcher fully assess quality. (In contrast, an eBay seller's quality generally is unobservable or only partially observer to a researcher.) Nonetheless, Google Answers does not provide all data researchers might seek. For example, although Google Answers receives answerers' resumes and geographic locations as part of the application process, Google Answers does not share this data with the general public. Chen, Ho, and Kim (2008) address these constraints through field experiments that pay Google Answers answerers to address questions posed by the authors, allowing measurement of the effects of varying prices and gratuities parameters on answerers' responses. Beyond Chen, Ho, and Kim, others have also examined Google Answers. Rafaeli, Raban, and Ravid (2005) present summary statistics of 2002-2004 answers. Regner (2005) finds that social preferences and reputation influence askers' choice to provide optional gratuities to answerers. Adamic et al. (2008) study answer quality and reputation at the competing (though unpaid) service Yahoo! Answers. III. METHODOLOGY AND DATA SET All data for my analysis comes from the Google Answers Web site, http://answers.google.com, as it stood in November 2003. I wrote software to extract questions, answers, and profiles from the Answers site, forming a database of more than 40,000 questions and answers. With only a few exceptions, (1) I observe all Google Answers questions and answers posted through November 2003. (2) For each question asked, I observe the question itself (text and title), the question's categorization within Google Answers' taxonomy, the time at which the question was asked, the payment amount offered by asker to answerer, and the asker's username. For answered questions, I observe the time at which the question was answered, the answer (including length in characters, and number of included URLs), and the answerer's username. When the asker rated the answer, I observe the rating; when the asker offered a gratuity to the answerer, I observe the amount of the gratuity. Google Answers allows an answerer to "lock" a question--obtaining the temporary exclusive fight to answer it for the following 4-8 hours (depending on question price). …