Investing in network effects with Sameer Singh

Enterprise information systems (EIS) have been important enablers of business cross-functional processes since the 1990s. Often referred to as enterprise resource planning (ERP) systems, they were extended in line with electronic businesses for integration with suppliers and customers. Today, EIS architectures comprise, not only, ERP, supply chain, and customer relationship management systems, but also, business intelligence and analytics. We open the discussion piece by discussing how decentralization dynamics impact EIS and how such dynamics must be controlled but also harnessed to make future EIS more efficient and useful.

The CityScienceLab at the HafenCity University Hamburg investigates the urban challenges in the era of digitalization in cooperation with partners from civil society, politics, economy, and science. It pursues an inter and transdisciplinary perspective by linking technical issues with social and cultural developments.

We explore the intersection of platform governance and media policy and examine the impact of inter-and-intra-organizational behavior on platform governance and content moderation.

We talk about the so-called “Web3” movement that emerges as a reaction against the growing concentration of power to information in the hands of a few and instead proposes an open, trustless, and distributed iteration of the Internet that rests on visions of interoperation, decentralization, democratization, and user-controlled monetization.

A conversation about the legal challenges and opportunities of blockchain technology and platform ecosystems, with a specific focus on governance and trust.

Building identity, payments, and data exchange as infrastructure to scale solutions in agriculture, health, poverty, climate, and other pressing challenges promises to be one of the most compelling public interventions of this decade. But the work, as with the definition of it, is still emergent. We look forward to hearing from you to learn more ways to think about these important issues.

In most platform environments, the exclusive provision of premium content from leading creators (superstars) is used as a strategy to boost user participation and secure a competitive edge vis-à-vis rivals. In this article, we study the impact of superstar exclusive content provision on platform competition and complementors’ homing decisions. Two competing platforms facilitate interactions between consumers and suppliers, of which the latter are identified by the superstar and a fringe of complementors (e.g., independent developers, amateurs). When platform competition is intense, more consumers become affiliated with the platform favored by superstar exclusivity. This mechanism is self-reinforcing as it generates an entry cascade of complementors, and some complementors single home on the favored platform.

The burgeoning digital platforms literature across multiple business disciplines has primarily characterized the platform as a market or network. Although the organizing role of platform owners is well recognized, the literature lacks a coherent approach to understanding organizational governance in the platform context. Drawing on classic organizational governance theories, this paper views digital platforms as a distinct organizational form where the mechanisms of incentive and control routinely take center stage. We systematically review research on digital platforms, categorize specific governance mechanisms related to incentive and control, and map a multitude of idiosyncratic design features studied in prior research onto these mechanisms. We further develop an integrative framework to synthesize the review and to offer novel insights into the interrelations among three building blocks: value, governance, and design. Using this framework as a guide, we discuss specific directions for future research and offer several illustrative questions to help advance our knowledge about digital platforms’ governance mechanisms and design features.

Many recent technological advances (e.g. ChatGPT and search engines) are possible only because of massive amounts of user-generated data produced through user interactions with computing systems or scraped from the web (e.g. behavior logs, user-generated content, and artwork). However, data producers have little say in what data is captured, how it is used, or who it benefits. Organizations with the ability to access and process this data, e.g. OpenAI and Google, possess immense power in shaping the technology landscape. By synthesizing related literature that reconceptualizes the production of data for computing as ``data labor'', we outline opportunities for researchers, policymakers, and activists to empower data producers in their relationship with tech companies, e.g advocating for transparency about data reuse, creating feedback channels between data producers and companies, and potentially developing mechanisms to share data's revenue more broadly. In doing so, we characterize data labor with six important dimensions - legibility, end-use awareness, collaboration requirement, openness, replaceability, and livelihood overlap - based on the parallels between data labor and various other types of labor in the computing literature.