Dealing with consumer uncertainty: Online consumer reviews and what makes them helpful

Online shopping has become very prevalent in average consumer's daily life. Electronic retailing comes with many conveniences for consumers. Being able to share information about the purchased product is among these conveniences. This is done through writing Online Consumer Reviews. Online Consumer Reviews can decrease consumer uncertainty by providing information about the product quality. Furthermore, many online retailers implemented a "helpfulness" feature to help potential customers find valuable reviews easily. This creates an opportunity to find out what kind of information tends to decrease the consumer uncertainty, in other words, what makes a helpful review? To answer this question, consumer review data from BestBuy and IMDb was scraped and transformed. Then the data was inquired in the light of Search and Experience goods paradigm, Negativity Bias and Prospect Theory. Hypotheses were tested by Tobit Regression. The results were both expected and unexpected. It was found that information sharing for Search goods is very important and consumers need more elaboration when a review is rated negatively. Additionally, reviews with negative sentiments were found to be more helpful leading to the presence of Negativity Bias. On the other hand, such strong support for Negativity Bias were not observed for Experience goods. The implication of these results is that consumers should participate in more both writing and voting reviews at least for Search Goods. This way consumers can get the best quality products with respect to their budgets. Besides, this optimized behavior might lead to increased social welfare because of the decreased information asymmetry between producers and consumers. Keywords Natural Language Processing, Information Economics, Behavioral Economics, Web Scraping, Online Consumer Reviews