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Revealed preference in online reviews: Purchase verification in the tablet market
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2020 | Decision Support Systems | Citations: 7
Authors: He, Jiaxiu; Wang, Xin; Vandenbosch, Mark B.; Nault, Barrie R.

Abstract: The review systems of online platforms create a stream of online word-of-mouth t ... Expand

Abstract: The review systems of online platforms create a stream of online word-of-mouth that allows consumers to learn from others' purchasing experience. However, it is difficult for consumers to discern the authenticity of a review or the reviewer's level of experience with the product. Platforms can aid the authentication process by incorporating a verified purchase (VP) indication, or “badge” as is done on Amazon, in reviews where the consumer writing the review has verifiably purchased the focal product. A VP is a revealed preference for a product implying a utility-maximizing choice where the consumer writing the review has experience with the product. Combining an Amazon dataset on tablet computers with the theory of revealed preference in online reviews, we uncover a surprising new result: the proportion of VP reviews (a revealed preference) is associated with higher future sales, and the effect of the proportion of VP reviews on sales dominates the effect of the mean rating. This novel use of VP with revealed preference theory has implications for new research in the design of recommendation systems, detecting fraudulent reviews, and online profiling/privacy. Moreover, the use of a VP badge is immediately applicable to firms and platforms. Collapse

Semantic filters: revealed preference theory

Topics: tablet online review iPad price management missing data

Methods: instrumental variables estimation robustness check descriptive statistic autocorrelation analysis longitudinal research

Theories: revealed preference theory
The Experts in the Crowd: The Role of Experienced Investors in a Crowdfunding Market
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2019 | Management Information Systems Quarterly | Citations: 33
Authors: Kim, Keongtae; Viswanathan, Siva

Abstract: Using a data set on individual investments in an online crowdfunding platform fo ... Expand

Abstract: Using a data set on individual investments in an online crowdfunding platform for mobile applications, this study examines whether an early investor’s experience within the platform serves as a credible signal of quality for other investors in the crowd and, if so, under what conditions. We find that early investors with experience—particularly investors with app development experience and investors with app investment experience—have a disproportionate influence on later investors in the crowd. Investors with app development experience are likely to have better knowledge of the product and are therefore found to be more influential for “concept apps” (apps in the pre-release stage), while investors with app investment experience with a better knowledge of market performance are found to be more influential for “live apps” (apps that are already being sold in the market). Our findings show that the majority of investors in this market, the crowd, although inexperienced, are rather sophisticated in their ability to identify and exploit nüanced differences in the underlying expertise of the early investors, informational signals that align well with the informational needs they face in the different stages of a venture. In examining the ex post performance of apps, we find that apps with investments from investors with experience are positively associated with ex post app sales. More importantly, we find that investors with experience indeed have the ability to select better apps, making their investment choices credible signals of quality for the crowd. Contrary to popular perceptions of crowdfunding platforms as substitutes for traditional expert-dominated mechanisms, our findings indicate that participation by individuals with experience can be beneficial to these markets. Collapse

Semantic filters: revealed preference theory

Topics: mobile application crowdsourcing crowdfunding marketing management new product development

Methods: longitudinal research robustness check autocorrelation analysis hazard function natural language processing

Theories: lemon market theory revealed preference theory transaction cost economics
(Un)expected Bidder Behavior in Spectrum Auctions: About Inconsistent Bidding and Its Impact on Efficiency in the Combinatorial Clock Auction
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2016 | Group Decision and Negotiation | Citations: 0
Authors: Kroemer, Christian; Bichler, Martin; Goetzendorff, Andor

Abstract: The combinatorial clock auction is a two-stage auction format, which has been us ... Expand

Abstract: The combinatorial clock auction is a two-stage auction format, which has been used to sell spectrum licenses worldwide in the recent years. It draws on a number of elegant ideas inspired by economic theory. A revealed preference activity rule should provide incentives to bid straightforward, i.e., consistent with the bidders’ valuations on a payoff-maximizing package, in each round of the clock phase. A second-price rule should set incentives to bid truthfully in both phases. If bidders respond to these incentives and bid straightforward in the clock phase and truthful in the second sealed-bid stage, then the auction is fully efficient. Unfortunately, bidders might neither bid straightforward in the clock phase nor truthful on all packages in the second sealed-bid stage due to strategic reasons or practical limitations. We introduce metrics based on Afriat’s Efficiency Index to analyze straightforward bidding and report on empirical data from the lab and from the field in the British 4G auction in 2013 and the Canadian 700 MHz auction in 2014, where the bids were made public. The data provides evidence that bidders deviate significantly from straightforward bidding in the clock phase, which can restrict the bids they can submit in the supplementary phase. We show that such restrictions can have a significant negative impact on efficiency and revenue. Collapse

Semantic filters: revealed preference theory

Topics: artificial intelligence price management

Methods: simulation experiment sensitivity analysis computational algorithm laboratory experiment

Theories: revealed preference theory

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Found 3 articles

Revealed preference in online reviews: Purchase verification in the tablet market

The Experts in the Crowd: The Role of Experienced Investors in a Crowdfunding Market

(Un)expected Bidder Behavior in Spectrum Auctions: About Inconsistent Bidding and Its Impact on Efficiency in the Combinatorial Clock Auction