Organizational knowledge is essential for sustained competitive advantage, yet it naturally depreciates over time. Traditional rule-based technologies help counter this erosion by serving as stable repositories of knowledge. In contrast, machine learning (ML) systems—an increasingly prevalent and relied-upon technology—introduce new risks. Because their predictive models depend on historical training data, ML systems are vulnerable to model drift: a gradual misalignment with evolving operational realities that creates recurring needs for human-led repair. We develop a multilevel process model showing how and when repeated cycles of ML use and repair can unintentionally accelerate organizational knowledge depreciation. In doing so, we highlight the distinct vulnerabilities of ML systems, challenge the conventional view of technologies as stable repositories of knowledge, and emphasize the importance of deliberate human engagement alongside automation to sustain organizational knowledge over time.

Current assumptions about theorization as a prerequisite for the diffusion of new ideas and practices are still largely shaped by an understanding of communication that predates the increasing prevalence of multimodality. We argue that this has led scholars to equate effective theorization with effective content rather than to adequately focus on expression and the ways in which communicative context matters for theorization. In this article, we draw on insights from social semiotics to reconceptualize effective theorization as a question of multimodal design (i.e., the conjunction of content and expression). By placing deliberate attention on the thus far overlooked role of expression, we identify three ideal types of multimodal theorization—expository, balanced, and suggestive—and develop propositions on how, and under what conditions, each of them has the greater potential to be effective for diffusion. Our theory development updates and expands upon the limits of verbal theorization, analyzing the affordances of multimodal expression in relation to characteristics of ideas and practices, audiences, genres of text, and the legitimacy of theorists. We further contribute to multimodal research by developing a systematic approach that distinguishes between “weak” and “strong” multimodality. Finally, we develop implications for related forms of academic and lay theorizing.

This paper advances a model of moral ambiguity in entrepreneurial action. Our model specifies the mechanisms surrounding moral responsibility, moral motivation, and the moral threshold through which perceived moral ambiguity shapes action. Specifically, we theorize (a) the interpretative elements that steer how the entrepreneur attributes moral responsibility and establishes moral motivation, (b) how multiple opposing interpretations can create attributional or motivational moral ambiguity, and (c) how the entrepreneur can process such ambiguity to make moral judgment. We then discuss how our model extends prior work on both ethics in entrepreneurship and moral approbation theory, and we outline research opportunities on moral ambiguity and judgment.

Although prior research has documented that some necessity-motivated ventures grow, and later develop into what researchers have traditionally called “opportunity-driven” ventures, the existing dichotomous framework offers no theoretical explanation for how this transition occurs. We build on the actualization view of entrepreneurship to describe the process by which an entrepreneur’s underlying needs—basic, psychological, and self-fulfillment needs—motivate both the desired future states that they envision, and their evaluation of the actions and conditions necessary to actualize the futures they imagine. We then extend actualization theory beyond the identification and evaluation of opportunities to include venture creation. We describe how needs effect the identification of key milestones, the pace at which milestones must be reached, and the level of uncertainty that entrepreneurs are willing to bear. In doing so, we illustrate how basic needs motivation leads to the selection of imitative or replicative actions, but that subsequent needs actualization can free necessity entrepreneurs to pursue voluntary forms of entrepreneurship once their basic needs have been met. Our model invites scholars to go beyond describing the antecedents and outcomes of necessity entrepreneurship, to research aimed at understanding the process through which necessity entrepreneurs transition to more voluntary forms of venturing.

We develop new theory to explain the apparent mystery that societal crises recurringly and consistently give rise to extreme growth outlier organizations that reach prominent positions in their industries and markets. We argue that societal crises increase demand for the market offerings of a minority of organizations, which can help the negatively affected majority of economic agents adapt to the crisis conditions. Because the majority of economic agents struggle, this externally-enabled minority simultaneously benefits from mutually reinforcing improvements to resource supply and institutional legitimation—advantages that are usually not bestowed on organizations that experience demand surges under non-crisis conditions. We further argue that societal crises with a broad scope, sudden onset, and extended duration provide sufficient enablement to make extreme growth possible for a select few organizations. Finally, we argue that organizations must be internally dispositioned to leverage resource expansibility, flexibility, and distributability to actualize this external enablement. Our theory about the occurrence of crisis-enabled extreme growth outliers extends emerging conversations around the important minority of organizations that benefit from crises’ overall detrimental effects. It also invites more research into the essential and systematic impact of environmental changes on economic activity to extend existing agent-based theories.