3 research outputs found

    The Economics of Public Beta Testing

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    A growing number of software firms now rely on public beta testing to improve the quality of their products before commercial release. While the benefits resulting from improved software reliability are well recognized, some important market-related benefits have not been studied. Through word-of-mouth, public beta testers can accelerate the diffusion of a software product after its release. Additionally, because of network effects, public beta testers can increase users’ valuation of a product. In this study, we consider both reliability-related and market-related benefits, and develop models to determine the optimal number of public beta testers and the optimal duration of testing. Our analyses show that public beta testing can be profitable even if word-of-mouth and network effects are the only benefits. Furthermore, when both benefits are considered, there is significant “economies of scope”—the net profit increases at a faster rate when both word-of-mouth and network effects are significant than when only one benefit is present. Finally, our sensitivity analyses demonstrate that public beta testing remains highly valuable to software firms over a wide range of testing and market conditions. In particular, firms will realize greater profits when recruiting public beta testers who are interested in the software but unable to afford it

    An Economic Analysis of Third-Party Software Reliability Improvement using the Bug Bounty Program

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    Bug Bounty Programs (BBPs) reward external hackers for reporting software vulnerabilities. As the number of security issues caused by third-party applications has been significantly increased recently, many digital platforms are considering launching BBPs to help improve the reliability of third-party software. In this paper, we present an analytical model to examine the strategic decisions of launching and participating in a BBP for the platform and the third-party vendor, respectively. We find that the platform’s (the vendor’s) BBP launching (participation) decisions depend on two key factors: the expected loss due to security breaches and the vendor’s reliability investment efficiency. We show that the incentive of using BBP, for the platform and vendor, sometimes is inconsistent. Meanwhile, we find that using the BBP is not always socially optimal. Under certain conditions, it reduces the overall software reliability, instead of improving it, makes the platform marketplace less secure, and thus hurts end users

    The Economics of Public Beta Testing

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    A growing number of software firms now rely on public beta testing to improve the quality of their products before commercial release. While the benefits resulting from improved software reliability are well recognized, some important market-related benefits have not been studied. Through word-of-mouth, public beta testers can accelerate the diffusion of a software product after its release. Additionally, because of network effects, public beta testers can increase users’ valuation of a product. In this study, we consider both reliability-related and market-related benefits, and develop models to determine the optimal number of public beta testers and the optimal duration of testing. Our analyses show that public beta testing can be profitable even if word-of-mouth and network effects are the only benefits. Furthermore, when both benefits are considered, there is significant “economies of scope”—the net profit increases at a faster rate when both word-of-mouth and network effects are significant than when only one benefit is present. Finally, our sensitivity analyses demonstrate that public beta testing remains highly valuable to software firms over a wide range of testing and market conditions. In particular, firms will realize greater profits when recruiting public beta testers who are interested in the software but unable to afford it.This is an accepted manuscript of an article published as Jiang , Z., K. P. Scheibe, S. Nilakanta, X. Qu. "The Economics of Public Beta Testing." Decision Sciences,2017; 48(1); 150-175. 10.1111/deci.12221. Posted with permission.</p
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