The talk addresses three crucial issues for the science and management of large-scale collaborative knowledge work: (1) maintaining contributor motivation over the long-run, (2) understanding the role of authority structures in peer-production, (3) fostering inclusion to reap the rewards of crowd diversity.

This paper addresses how strategies to leverage the high scalability of knowledge resources reshape unit-level performance and human capital management in multi-unit organizations. Using a wave of acquisitions in the private higher education in Brazil, the paper shows that being acquired by groups whose strategies rely on standardizing knowledge, promoting distance learning, and professionalizing management leads acquired units to specialize their relationships with faculty while increasing the scale and scope of service provision.

In the live-streaming environment, chat can engage the audience and make the main content more enjoyable but also sabotage the main content with trolling. We study the effect of the intervention of not allowing the audience to participate in the chatroom for a certain duration on user-generated content qualities in Twitch platform.

Ad blocking is a growing practice across the internet—more than 750 million devices block ads worldwide. Publishers have adapted to these tools by adjusting ad and content quality, negotiating with ad blocking groups to whitelist less intrusive ads, and directly employing workarounds to ad blocking technology. We argue the economic motivations for each of these responses varies according to publishers’ monetization strategies and user bases.

In the “Summit Gathering” stage of our Just Digital Future project, we’ll come together as a community for a virtual event to dig into the problem of tech inequality and identify opportunities for change.

Can AI recognize innovation? We operationalize arguments from the philosophy of creativity and theory of innovation literatures to argue that three different types of scientific innovation — combinational, exploratory, and transformative — can be distinguished by generative algorithms in an unsupervised, data-driven manner.

Who is likely to resist algorithmic advice? Across 11 online studies and over 2,400 participants, we find that individuals that rely on their intuitive cognitive style prefer more advice from human (vs. algorithmic) advisors.

We run a field experiment to quantify the economic returns to data and informational externalities associated with algorithmic recommendation relative to human curation in the context of online news.

Using computational linguistics to construct measures of organizational culture from employee resume data, I show that the firms that produce the most breakthrough innovations use more quantitative tools, but use them as one tool in a diverse epistemic toolkit.

Abstract Data-intensive technologies, like AI, are increasingly widespread. We argue that the direction of innovation and growth in data-intensive economies may be crucially shaped by the state because: (i) the state is a key collector of data and (ii) data is sharable across uses within firms, potentially generating economies of scope. We study a prototypical…

The Harvard Business Analytics Conference will explore analytics and AI, new operational foundations of business.