Knowledge that Transforms

The theory of platform envelopment rests on network effects as the key mechanism for value creation, which nonetheless receives mixed support for its efficacy in determining competitive outcomes. We argue that the value of network effects depends on matching quality, which is a function of platform-specific algorithm technology and market-level data-driven learning. In formalizing these conceptualizations, we analyze a model that demonstrates how an entrant with a superior algorithm technology may outcompete an incumbent possessing a user base advantage, a strategy we call “algorithm envelopment.” By considering specific characteristics of data-driven learning, our analysis leads to propositions regarding the entry barriers for the enveloper, illuminating how learning may overshadow or interact with network effects in impacting the enveloper’s market selection decisions. We also show that market selection may be contingent on whether algorithm envelopment is instituted through competition or mergers, suggesting an interdependence between “where to enter” and “how to enter.” Finally, we explore the welfare effects of algorithm envelopment. We extend the recent debate on “data network effects” and show how teasing apart network effects, data-driven learning, and algorithm technology in envelopment attacks can generate novel implications for incumbency advantages, yield insights into platform diversification, and inform antitrust policymaking.

Since Shane and Venkataraman's (2000) seminal paper, entrepreneurship research has been preoccupied with the exploitation of entrepreneurial opportunities.Lewis, Bruton and Shepherd (2024) (LBS hereafter) fruitfully shift focus from "which opportunities are exploited to which opportunities are not" (p.11).Trying to answer why-not questions is critical to advancing theoretical understanding of how nonactual but desirable futures can be realized.As importantly, understanding why the needs of marginalized consumers are not served is imperative for building more inclusive capitalist societies.LBS address this lacuna by providing several conceptual innovations.They explain that market inefficiencies are grounded in structural disadvantage resulting from social closure, segregation, and stereotyping of marginalized consumers.This insight is not only radical for

While the importance of promoting greater equality is widely recognized in management theory and practice, it has yet to be built into the core business process of value creation. To date, research on gender equality in management has either taken the dominant model of value creation as given or, from a critical perspective, viewed value creation as fundamentally incompatible with equality. In this paper, we instead develop a new approach to value creation to address gender equality. To do this, we advance a theory of feminist value creation that draws on social reproduction theory located within materialist feminism. We offer a feminist reconceptualization of value creation in terms of the nature of value, its valuation, and underpinning values, such as to successfully integrate within value creation the “private sphere” of socially reproductive work in addition to the “public sphere” of paid and productive work. We also theorize the material and cultural processes of transformation needed to move toward feminist value creation, and the intra-, inter-, and extra-organizational influences that will affect the likelihood of such a transition. We conclude by elaborating on our contributions to research on gender equality in management and value creation.

Research on organizational learning emphasizes that slow learning fosters exploration and encourages recombination of knowledge and practices. However, the role that slow learning plays in the spread of knowledge in organizations remains underexplored. This gap is important because the learning mode that actors apply to select practices is critical for organizational performance gained through mutual learning. We identify two key learning modes: success-based (learning from successful peers) and norm-based (conforming to majority views). We analytically distill our insights into six propositions that explore how variations in learning modes, learning speeds, and network centrality shape organizational learning outcomes. Our findings reveal a critical coupling between learning modes and speed: Norm-based learners should adopt slow learning, while success-based learners should always learn faster. Contrary to prior studies emphasizing organizational structure, we show that effective knowledge utilization is primarily driven by the interaction of learning modes and speeds. Hierarchy emerges as a factor only when mixed learning modes interact with varying speeds. These insights enrich our understanding of slow learning by highlighting its contingent value in knowledge selection and assimilation. Our study offers testable predictions and practical guidance for organizational design in contexts such as multinational retail chains, manufacturing firms, and franchise organizations.

Deliberative democracy is a prominent political approach that is increasingly attracting the interest of management scholars. While many deliberative democracy scholars acknowledge that expertise improves the epistemic quality of deliberation, some have recognized that experts can become “problematic participants” in deliberations. Through an analysis of Henrik Ibsen’s ([1882] 2007) play An Enemy of the People, I discuss four difficulties of including expertise in public deliberation: manipulations in the deliberative setting, exploitation of the vulnerability of experts, disregard for the limitations of expertise, and inability to translate and enroll. I also argue that the play’s ending leads readers to question the practicality of expert withdrawal. Furthermore, characters in the play suggest two other possibilities for overcoming the obstacles associated with expertise: “epistocracy,” and finding new ways to increase deliberation and participation. To advance this latter option, I call for a bidirectional view of translation, following scholars in both deliberative democracy and science and technology studies, and underscore the complexities of building trust when boundary crossing between expertise and non-expertise. These insights enrich the stream of management studies using deliberative democracy, and reinforce recent claims that management scholars should be more involved in the public sphere.

We develop a process model of how and why entrepreneurial framing can lead to deception and result in the loss of legitimacy in new ventures. We draw on the literature on framing and temporal construal theory to theorize how the emergence of a gap between expectations set during start-up and the realities that entrepreneurs encounter during implementation can trigger entrepreneurial deception when audiences seek concrete details in exchange for their continued support. Entrepreneurs may engage in further deception and moral disengagement to the extent that the gap remains as they pursue harder-to-accomplish stretch goals to maintain support. We also theorize what happens when entrepreneurial deception is publicly called out, resulting in a potentially catastrophic loss of legitimacy. Overall, we offer a cautionary note on entrepreneurship by exploring one aspect of its dark side.

Resilience research has extensively addressed how organizations cope with disruptive events and their immediate impact. The focus of this research has been on how organizations “bounce back” to a pre-disruption state. However, organizations are also challenged to “bounce forward” toward unprecedented and uncertain futures in the wake of disruptive events without losing sight of their pasts. In this article, we develop a trajectory model of organizational resilience that focuses on how actors project temporal trajectories of responses toward disruptive events, reconstitute the trajectories in immediate response to the event, and reconfigure the trajectories toward the ensuing future. The model addresses the need to distinguish combinations of probability and the impact of disruptive events in organizational resilience research. We develop a typology of disruptive events from ecological research representing a distinct combination of probability and impact, labeled stochastic events, probabilistic transformations, and tipping points. We examine critical transitions in the trajectory model at which organizational resilience may or may not materialize. We conclude by considering the implications for theorizing organizational resilience between organizational levels and between different disruptive events, and for temporal organizational theorizing.