Abstract Organization redesign often raises a central question: Where are managers needed? A potential substitute for formal supervision by managers is interpersonal cultural alignment, which can ease coordination between colleagues. Yet prior research suggests cultural alignment may also complement formal structure. We theorize that the balance depends on coordinative complexity: Whether culturally aligned individuals benefit from common supervision hinges on how broadly they depend on others to get work done. Cultural alignment can function as a substitute for formal structure when coordinative complexity is low and as a complement when coordinative complexity is high. Focusing on one of the most tangible and consequential forms of cultural alignment—the degree to which individuals are linguistically aligned with their peers in everyday communications—we make predictions about which pairs of colleagues organizational designers will tend to bring together under, versus separate from, a shared supervisor. Using archival data from a design firm, we find support for our theory, with especially strong effects when colleagues are highly visible to their senior managers.

Abstract Decentralized Autonomous Organizations (DAOs) are attracting interest from various disciplines, particularly business and economics, and computer science. However, much like the parable of the blind men and the elephant, where each observer sees only part of the phenomenon, DAO research has largely remained fragmented across disciplines, limiting a comprehensive understanding of the potential of DAOs. This paper investigates to which extent DAO scholarship has achieved meaningful interdisciplinary integration. We address this question through an analysis of knowledge flows between Business and Economics and Computer Science, using citation network analysis, topic modelling, and outlet analysis. We find that while DAOs generate vibrant interdisciplinary discourse, the interactions remain predominantly applied and case-driven, with limited theoretical integration. By mapping interdisciplinary exchanges, we highlight key gaps and opportunities for greater synthesis across fields. We argue that strengthening the alignment between organizational and technical insights is crucial for advancing DAO research and fostering a more cohesive interdisciplinary framework.

The development of Bitcoin and its underlying technology blockchain has enabled a new phenomenon called decentralized autonomous organizations (DAOs). DAOs can be perceived as self-governing organizations whose management is based on programmed and encoded rules on a decentralized and distributed peer-to-peer network. These DAOs typically manage and allocate funds, often in the form of cryptocurrencies. However, in recent years, a variety of DAOs have been established to provide services (e.g., currency exchange, project financing), curate collections (e.g., art collections), or own and manage real assets (e.g., land). Currently, DAO literature focuses mainly on online communities managing digital assets; however, DAOs owning physical properties differ from them in localized communities, asset indivisibility, and additional complexity in collective acquisition, ownership, limited physical capacity, and decentralized governance. Such property-owning DAOs are interesting, because they fuel the transition from purely online organizations into organizations integrating with the physical world. From an organizational system theory perspective this article explores how a DAO owning properties could be designed by exploring three DAO projects that own properties. Applying a conceptual research design, we first identify DAO Design Principles obtained by traditional organizational system theory, followed by examining and describing the core organizational principles for property-owning DAOs. Based on a comprehensive discussion of the conceptual findings, we present a research agenda for further studies on DAOs owning properties.

Decisions—whether made by individuals or groups—often involve estimating quantities, a process that is subject to anchoring bias (Tversky and Kahneman in Science 185: 1124–1131, 1974). Differences in susceptibility to anchoring bias between individuals and groups have been recently explored with the result that groups appear less biased than individuals (Meub and Proeger in Theor Decis 85:117–150, 2018). However, existing studies treat groups monolithically without taking into account their network structure—the pattern of relationships among members. The present paper investigates the effects of group social network structure on anchoring bias. Using a structured survey instrument, we gathered data on competence-based trust relationships among 264 students enrolled in a university degree program. An anchoring experiment was conducted in which some of the students made estimates as individuals, while others did so in groups of different structures. The findings provide initial evidence of differences in bias levels across variously structured groups as well as relative to individuals. Groups with highly centralized trust networks (where a single person owned everyone’s trust) showed more anchoring bias than dense groups (where everyone trusted everyone else) and sparse groups (where no one trusted any other member of the group) showed more bias than dense groups. In addition, despite previous research demonstrating groups are less susceptible than individuals to anchoring bias, this study shows a higher presence of bias in both our centralized groups and sparse groups when compared to individuals, suggesting that group structure might moderate the mitigating effect of groups on anchoring bias. The research has implications for organizational behavior and social network literature. Specifically, this study contributes to the debate on anchoring bias for group decisions by highlighting the significant role of social network structure. At the same time, it contributes to the literature on network structure and performance by providing initial evidence of how network structure affects anchoring bias susceptibility. Moreover, our study contributes to management practice by alerting managers to the dangers of centralized networks, suggesting that competence-based trust plays a vital role in the resistance to anchoring bias.

The increasing adoption of artificial intelligence (AI) is reshaping the practices of human resource management (HRM). We propose a typology of HR–AI collaboration systems across the dimensions of task characteristics (routine vs. non-routine; low vs. high cognitive complexity) and social acceptability of such systems among organizational members. We discuss how organizations should design HR–AI collaboration systems in light of issues of AI explainability, high stakes contexts, and threat to employees’ professional identities. We point out important design considerations that may affect employees' perceptions of organizational fairness and emphasize HR professionals' role in the design process. We conclude by discussing how our Point of View article contributes to literatures on organization design and human–AI collaboration and suggesting potential avenues for future research.

Open organizations are structures in which members of the public engage in work for the organization. Examples include open-source software, Amnesty International, Wikipedia, and Lego communities. Much research focuses on structural design characteristics of open organizations, such as pre-specified task divisions and integration teams. These practices require the organization to a priori structure in response to its mission. Increasingly, however, open organizations like CrowdDoing and Hyperloop Transportation Technologies (HyperloopTT) require public involvement across volatile, uncertain, complex, ambiguous (VUCA) contexts. These open organizations must respond to changing political, competitive, and socio-economic events. Structural clarity is more difficult, and contributors may participate in the creative development of new technologies, new policies, and new sources of funding. Working from practices supporting participant engagement in more stable environments, we qualitatively observe HyperloopTT to understand internal practices for open organizing in more VUCA contexts. We observe four practices allowing for the flexibility, versatility, and accommodations needed for open organizing in such settings. The HyperloopTT practices allow more porosity and self-determination—not simply in how people divide and integrate tasks, but also in the exploration and experimentation of the work itself. More than task workers, we see a new class of open organizing participants: creative work designers.