2014
DOI: 10.1016/j.dss.2014.07.004
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Why Amazon uses both the New York Times Best Seller List and customer reviews: An empirical study of multiplier effects on product sales from multiple earned media

Abstract: a b s t r a c t Keywords: Multiplier effects of earned media Electronic word of mouth Social media Traditional media Integrated marketing communication (IMC) Digital ecosystemIn today's dynamic media landscape, products are reviewed by consumers in social media and reported by journalists in traditional media. This paper will focus on the relationship among the two types of "earned" media and product sales. Previous studies have focused on either traditional or social earned media, but rarely both. We will aim… Show more

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Cited by 42 publications
(18 citation statements)
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“…The second major area is empirical research showing that media coverage provides free publicity that can have similar effects as paid advertising. This free publicity can significantly increase the number of consumers who are interested in a product, person, or experience (Bao & Chang, 2014; Ogilvy, 2015; Ridout & Smith, 2008; Stephen & Galak, 2012). Notably, even negative coverage can have this effect (Ahluwalia, Burnkrant, & Unnava, 2000; Berger, Sorensen, & Rasmussen, 2010; Ridout & Smith, 2008).…”
Section: The Consequences Of Media Coverage Of Mass Killingsmentioning
confidence: 99%
“…The second major area is empirical research showing that media coverage provides free publicity that can have similar effects as paid advertising. This free publicity can significantly increase the number of consumers who are interested in a product, person, or experience (Bao & Chang, 2014; Ogilvy, 2015; Ridout & Smith, 2008; Stephen & Galak, 2012). Notably, even negative coverage can have this effect (Ahluwalia, Burnkrant, & Unnava, 2000; Berger, Sorensen, & Rasmussen, 2010; Ridout & Smith, 2008).…”
Section: The Consequences Of Media Coverage Of Mass Killingsmentioning
confidence: 99%
“…Consumers draw on cues such as the price (Rao & Monroe, 1989), brand name (Aaker & Keller, 1990), and country of origin (Verlegh & Steenkamp, 1999) to infer quality, as well as on popularity and market share (Cialdini, Reno, & Kallgren, 1990;Hellofs & Jacobson, 1999). For example, they are more likely to download songs that have been downloaded many times previously (Salganik, Dodds, & Watts, 2006), buy books that appear on a bestseller list (Bao and Chang 2014;Sorensen 2007), order popular dishes in a restaurant (Cai, Chen, & Fang, 2009), and engage in late bidding to increase the chance of winning auctions as the number of viewers and bids increases (Kamins, Noy, Steinhart, & Mazursky, 2011). People also are willing to pay more for apps that appear in a top 100 list (Carare, 2012) and prefer to dine in restaurants with longer queues (Raz & Ert, 2008).…”
Section: Inferring Personal Features From Observed Purchasesmentioning
confidence: 99%
“…They contended that this requires analyzing the value proposition for customers of these companies in order to acquire the needed data from digital-savvy consumers for research purposes. In these circumstances, well-known multinational companies like Coca Cola, Amazon, eBay, and Proctor and Gamble (P&G), among others, have been regarded as perfect examples of companies that have-by virtue of Internet technologies-fruitfully shifted from brick and mortar strategies to brick and click techniques [15,16].…”
Section: Introductionmentioning
confidence: 99%