Although extant research has studied incumbent resistance to digital platforms, it provides little understanding about when grassroots collective action by other ecosystem stakeholders against the digital platform is likely. In this paper, we identify the scope conditions detailing when local stakeholders can initiate grassroots collective action against the digital platform, a unique context characterized by fast growth, distributed innovation, role flexibility, and direct local connectivity, and propose viable solutions. Our conceptual framework suggests that grassroots collective action against the digital platform is most likely when the digital platform operates with localized scarce assets or localized precarious labor and when actors express their grievances through formalized channels. We combine business model design and stakeholder management perspectives to develop design-based solutions that involve a multisided business model structure, an inclusive stakeholder value proposition, and an ecosystem-centered governance. We call the combination of such design efforts relational business model design. To the incipient theory of digital platforms, we contribute a stakeholder-centered view of platform business models operating within local ecosystems, bridging research on collective action and stakeholder management with strategic management of platforms.

Not all misinformation is created equal. It can adopt many different forms like conspiracy theories, fake news, junk science, or rumors among others. However, most of the existing research does not account for these differences. This paper explores the characteristics of misinformation content compared to factual news—the “fingerprints of misinformation”—using 92,112 news articles classified into several categories: clickbait, conspiracy theories, fake news, hate speech, junk science, and rumors. These misinformation categories are compared with factual news measuring the cognitive effort needed to process the content (grammar and lexical complexity) and its emotional evocation (sentiment analysis and appeal to morality). The results show that misinformation, on average, is easier to process in terms of cognitive effort (3% easier to read and 15% less lexically diverse) and more emotional (10 times more relying on negative sentiment and 37% more appealing to morality). This paper is a call for more fine-grained research since these results indicate that we should not treat all misinformation equally since there are significant differences among misinformation categories that are not considered in previous studies.

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