User-generated content has been hailed by some as a democratizing force that enables consumers to discuss niche products that were previously ignored by mainstream media. Nevertheless, the extent to which consumers truly prefer to use these new outlets to discuss lesser-known products as opposed to spending most of their energies on discussing widely marketed or already successful products has so far remained an open question. We explore this question by investigating how a population's propensity to contribute postconsumption online reviews for different products of the same category (motion pictures) relates to various indicators of those products' popularity. We discover that, ceteris paribus, consumers prefer to post reviews for products that are less available and less successful in the market. At the same time, however, they are also more likely to contribute reviews for products that many other people have already commented on online. The presence of these two opposite forces leads to a U-shaped relationship between a population's average propensity to review a movie postconsumption and that movie's box office revenues: moviegoers appear to be more likely to contribute reviews for very obscure movies but also for very high-grossing movies. Our findings suggest that online forum designers who wish to increase the contribution of user reviews for lesser-known products should make information about the volume of previously posted reviews a less-prominent feature of their sites.
"Recent research in the areas of information systems and marketing provides a number of insights on reviews. In terms of antecedents, studies identify the characteristics and motivations of those who write reviews   , including strategic fake reviews written on behalf of organizations  and non-strategic deceptive reviews written by individual, non-purchasers . Complementing this perspective, another stream of research examines the outcomes of reviews, finding that reviews affect aggregate consumer behavior as reflected in sales, profits, and viewership       , website and product evaluations    , competitive intelligence , and individual consumer choice   . "
[Show abstract][Hide abstract] ABSTRACT: Many online retailers and other product-oriented websites allow people to post product reviews for use by shoppers. While research indicates that these reviews influence consumers' shopping attitudes and behaviors, questions remain about how consumers evaluate the product reviews themselves. With the current research, we introduce a new methodology for identifying the review factors that shoppers use to evaluate review helpfulness, and we integrate prior literature to provide a framework that explains how these factors reflect readers' general concerns about the diagnosticity (uncertainty and equivocality) and credibility (trust and expertise) of electronic word-of-mouth. Based on this framework, we offer predictions about how the relative importance of diagnosticity and credibility should vary systematically across search and experience product types. By analyzing secondary data consisting of over 8000 helpfulness ratings from product reviews posted by shoppers on Amazon.com, we find that, while review content affects helpfulness in complex ways, these effects are well explained by the proposed framework. Interestingly, the data suggest that review writers who explicitly attempt to enhance review diagnosticity or credibility are often ineffective or systematically unhelpful. Our findings have implications for both IS developers and retailers for designing online decision support systems to optimize communication practices and better manage consumer-generated content and interactions among consumers.
Decision Support Systems 08/2015; 79. DOI:10.1016/j.dss.2015.07.009 · 2.31 Impact Factor
"Despite the high relevance of social information as a quality signal for consumers, relatively little prior research exists on biases that may appear in this context. For example, Dellarocas et al. (2010) have found that consumers are more likely to review less available and less successful products in the market but, at the same time, are also more likely to contribute reviews for products that already received a high number of reviews. Furthermore, it has been shown that reviews posted early in a product's lifetime tend to be positively biased (Li and Hitt, 2008). "
"For example, Hu et al. (2013) evaluate the relative impacts of text sentiment and star ratings on book sales at Amazon and determine that textual reviews (specifically, the two most accessible reviews – most helpful and most recent), unlike ratings, directly and significantly impact sales. Dellarocas et al. (2010) find that moviegoers show a propensity to review very obscure movies aside from very popular ones. They generalize that user review volume for lesser-known products may be increased by deliberately obfuscating the true volume of prior reviews. "
[Show abstract][Hide abstract] ABSTRACT: Based on a review of 46 research papers related to social media analytics (SMA), we develop an integrated, unifying definition of Business SMA, providing a nuanced starting point for future Business SMA research. The definition goes beyond being entirely customer-focused, encompasses both the external and internal organizational environs, and goes beyond intelligence gathering to also accommodate such business activities as sense making, insight generation, problem/opportunity detection and solution/exploitation, and decision making. Further, we identify several benefits of Business SMA, and elaborate on some of them, while presenting recent empirical evidence in support of our observations. The paper also describes several challenges facing Business SMA today, along with supporting evidence from the literature. Accordingly, this research study helps further an understanding of Business SMA and its many aspects, grounded in recent empirical work, and as a basis for further research and development.
Americas Conference on Information Systems (AMCIS) 2014, Savannah, GA, USA; 08/2014
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