The content industry has been undergoing a tremendous transformation in the last two decades. We focus in this paper on recent changes in the form of social computing. Although the content industry has implemented social computing to a large extent, it has done so from a techno-centric approach in which social features are viewed as complementary rather than integral to content. This approach does not capitalize on users' social behavior in the website and does not answer the content industry's need to elicit payment from consumers. We suggest that both of these objectives can be achieved by acknowledging the fusion between content and community, making the social experience central to the content website's digital business strategy. We use data from Last.fm, a site offering both music consumption and online community features. The basic use of Last.fm is free, and premium services are provided for a fixed monthly subscription fee. Although the premium services on Last.fm are aimed primarily at improving the content consumption experience, we find that willingness to pay for premium services is strongly associated with the level of community participation of the user. Drawing from the literature on levels of participation in online communities, we show that consumers' willingness to pay increases as they climb the so-called "ladder of participation" on the website. Moreover, we find that willingness to pay is more strongly linked to community participation than to the volume of content consumption. We control for self-selection bias by using propensity score matching. We extend our results by estimating a hazard model to study the effect of community activity on the time between joining the website and the subscription decision. Our results suggest that firms whose digital business models remain viable in a world of "freemium" will be those that take a strategic rather than techno-centric view of social media, that integrate social media into the consumption and purchase experience rather than use it merely as a substitute for offline soft marketing. We provide new evidence of the importance of fusing social computing with content delivery and, in the process, lay a foundation for a broader strategic path for the digital content industry in an age of growing user participation.

Online labor platforms (OLPs) can use algorithms along two dimensions: matching and control. While previous research has paid considerable attention to how OLPs optimize matching and accommodate market needs, OLPs can also employ algorithms to monitor and tightly control platform work. In this paper, we examine the nature of platform work on OLPs, and the role of algorithmic management in organizing how such work is conducted. Using a qualitative study of Uber drivers’ perceptions, supplemented by interviews with Uber executives and engineers, we present a grounded theory that captures the algorithmic management of work on OLPs. In the context of both algorithmic matching and algorithmic control, platform workers experience tensions relating to work execution, compensation, and belonging. We show that these tensions trigger market-like and organization-like response behaviors by platform workers. Our research contributes to the emerging literature on OLPs.

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