This conceptual paper addresses a puzzle in business collective action (BCA) research: why resource-independent firms able to pursue collective strategies alone would choose to tolerate memberships in trade associations whose outputs contradict those interests. Resolving this conundrum requires extending existing BCA research – focused on aggregation and trade-associations outputs – to consider internal organizational arrangements through which members constitute these outputs. To do so, we develop the Calculus of Tolerated Misalignment (CTM), a member-centric framework grounded in meta-organization theory. The CTM explains how, through meta-organizational features, firms mobilize internal and external leverage to moderate perceived costs of misalignment. This mechanism allows them to regulate the benefits of trade-association membership when collective outputs diverge from their individual interests. Our research advances BCA and collective-strategy scholarship by shifting focus to a constitutive logic where trade associations serve as bargaining arenas for their members. It also extends meta-organization theory by providing a dynamic model of member-level agency, conceptualizing firms’ trade-association membership as an active strategic-management process.
Intelligent technologies, that is, AI-based, computational systems that can generate, adapt, and act on outputs through forms of inference that extend beyond pre-specified rules, are increasingly implicated in how organizations learn, what they know, and how they are structured. Yet, strategy and organization scholarship has largely continued to treat technology as contextual rather than constitutive, leaving core assumptions about knowledge, social interaction, and organizational form insufficiently examined. In the call for papers, we asked researchers to remedy this by putting technology front and center in rethinking the field’s foundational building blocks. The ten contributions to this special issue take up that call and illuminate three critical ways through which intelligent technologies are reconfiguring organizations. First, intelligent technologies reshape organizational learning by moving firms from managing knowledge scarcity to navigating knowledge abundance. Second, they alter the production and validation of organizational knowledge by introducing new forms of machine-generated inference and epistemic stances that challenge established knowing practices. Third, they transform organizing itself by reshaping coordination, interaction patterns, and the structures through which collective activity is accomplished. A closing editorial synthesizes key insights and develops a research agenda for advancing strategy and organization scholarship in this new landscape.
Strategy-making increasingly depends on integrating knowledge across functional and hierarchical boundaries, often through processes mediated by material artifacts. While research shows that the material properties of individual artifacts partly shape what can be known, discussed, and decided, less is known about knowledge integration during moments when a structured strategy tool moves it through materially distinct artifacts. Drawing on an in-depth study of two strategic roadmapping projects in a large organization, we examine how transitions between artifact forms shape knowledge integration. We identify four artifact types, ephemeral, interim, stabilized, and analytical, and the transitions between materially distinct forms during which knowledge is reconstituted rather than simply carried forward. Across both projects, we identify three dynamics during these transitions: selection, surfacing, and reconfiguration. We contribute by identifying reconstitution as a knowledge-integration mechanism and by offering a tools-in-process account of how structured strategy tools work through transitions between artifact forms over time.
In the first chapter of Foundations of Social Theory , James Coleman advances a meta-theoretical framework that specifies an ideal explanatory structure for social science. This is often represented by the Coleman “bathtub,” which distinguishes three linked components: a macro-to-micro component, an individual-action component, and a micro-to-macro component. In management research, the bathtub has become a widely used heuristic for articulating microfoundational explanations. At the same time, a growing literature has criticized or rejected the bathtub as an inappropriate framework for management theorizing. This article responds to these critiques by reconstructing and defending the Colemanian project in management research. We begin by clarifying Coleman’s distinction between meta-theory and first-order theory and by situating the bathtub within his systems-oriented and interventionist conception of social explanation. We further argue that the bathtub embodies a pragmatic and generative meta-theoretical orientation that places relatively weak constraints on first-order theoretical commitments, allowing flexibility in how agency, social organization, and change are theorized. We then show how the microfoundations movement in management research illustrates this generative potential by mobilizing the bathtub across a diverse range of theoretical perspectives, extending well beyond Coleman’s own rational choice commitments. This diversity helps explain both the widespread uptake of the bathtub and its continued usefulness for management theorizing. Finally, we argue that many contemporary critiques overlook these explanatory payoffs by advancing ontology-first objections that neglect Coleman’s fundamentally methodological and explanatory concerns. Recasting the Colemanian project in this way clarifies both the value and the limits of the bathtub and highlights its continuing relevance as a flexible meta-theoretical framework for management theorizing.
Open Strategy (OS) aims to make strategy-making more inclusive. Yet its focus on breadth (engaging many voices) often neglects depth (ensuring those voices count), risking tokenism that undermines durability. To address this deficit, we juxtapose the broad-but-shallow approach of OS with the deep-but-narrow practices of traditional workplace democracy (TWD). From this, we develop a two-by-two framework that reveals four archetypes of inclusion in strategy-making. The framework positions most OS practices as Consultative Strategizing (high breadth, low depth) and TWD as Negotiated Strategizing (low breadth, high depth). To overcome its depth deficit, we propose mechanisms that embed depth in OS without sacrificing breadth, such as the formalization of roles and the delegation of decision rights. Such a synthesis allows moving toward more effective and resilient forms of inclusion, including Co-Governed Strategizing (high breadth, high depth), thereby ensuring that inclusion in strategy-making is both meaningful and durable.
Innovation-oriented public-private partnerships are central to collaborative innovation, yet we know little about how governmental involvement reshapes firms' organizational learning. This article develops a multilevel framework explaining how governments-as collaborators and institutional rule makers-shape firms' learning behavior. We argue that governmental participation operates through three governance mechanisms: changes in appropriability incentives, constraints on feasible governance instruments, and information credibility. These mechanisms shape learning across organizational, interorganizational, and population levels. Governments shift firms toward exploitation within public-private partnership domains while encouraging exploration beyond them, favor knowledge accessing over acquisition, and strengthen complementarities between experiential and vicarious learning. These effects are moderated by knowledge diversity, public-private knowledge overlap, and institutional quality. By integrating organizational learning with governance perspectives, this study explains how public institutions systematically configure firms' learning in collaborative innovation.
As artificial intelligence capabilities expand beyond pattern recognition to theoretical insight generation, interpretive qualitative research confronts a question of epistemic responsibility: how can scholars integrate artificial intelligence capabilities while remaining accountable for their theoretical interpretations? This essay proposes "interpretive orchestration" as a framework that transforms researchers from analysts into skilled orchestrators of human-artificial intelligence collaboration. The framework addresses two challenges that become opportunities. The translation challenge of articulating tacit knowledge (theoretical orientations, contextual understanding, and embodied intuition) into forms that artificial intelligence can process deepens researchers' awareness of their own expertise. The judgment challenge of evaluating artificial intelligence-generated patterns for theoretical significance highlights the accountability our scholarly communities require, particularly through "1.5-order data": patterns invisible to human perception yet requiring human interpretation for recognized theoretical significance. Three strategic models guide this orchestration: Socratic tension surfaces implicit assumptions through deliberate contradiction; Euclidean documentation enables reproducible analysis through systematic context-building; Vitruvian mastery reads across independent analytical passes for synthetic insight. By embracing orchestration, researchers discover that artificial intelligence can amplify rather than replace human capability. The future of interpretive research lies neither in rejecting artificial intelligence nor surrendering to automation but in systematic approaches to human-artificial intelligence collaboration that preserve the scholarly accountable judgment our communities require while drawing on artificial intelligence's capacity to generate theoretical insights across scales humans cannot process alone.
Where does a CEO’s management style come from? We explore a CEO’s development of a strategic recipe called counter-cyclical strategy, where CEOs undertake proactive investments during industry downcycles in preparation for subsequent upcycles to strengthen their firms’ competitive positions. We theorize that CEOs who began their careers during downcycles are more likely to implement counter-cyclical strategies when they encounter subsequent industry downcycles. This imprinting effect is reinforced through the CEO’s accumulation of contrarian experiences, i.e., positive performance outcomes of the CEO’s counter-cyclical strategies. Empirical evidence from the entire career histories of 305 unique CEOs since 1977 and their counter-cyclical investment records in the US semiconductor industry between 2001 and 2020 supports the hypotheses. This study reconciles managerial career imprinting perspectives with managerial experiences and learning in a fast-changing, cyclical industry.
Competitive dynamics research has provided a better understanding of the strategic interplay between competitors. However, scholars have given limited attention to examining how firms respond to competitors who introduce a disruptive change in strategy, forcing each competitor in the industry to decide how or if they will respond. In this study, we focus on four possible responses: (1) an imitative response, when a firm decides to replicate its competitors’ strategy by developing the requisite capabilities; (2) a preventative response, when a firm develops capabilities aimed at mitigating the impact of the disruptive strategy; (3) a combined response, when it pursues both imitative and preventative responses; and (4) neither response. We theorize that when responding to a disruptive change in strategy, the deployment of an imitative (preventative) response will be positively (negatively) associated with firm performance, while a combined response will be the least effective. In addition, we examine recent firm performance and relevant competitive experience as important contextual moderators. Using a sample of competitive interactions between teams in the National Football League responding to the disruptive strategy known as the West Coast offense, we test these hypotheses. Our findings offer practical guidance to firms by identifying how different responses shape performance outcomes and by clarifying the contextual conditions under which responses are most successful.
We examine whether firms appoint former politicians to corporate boards in response to financial performance feedback. Integrating the behavioral theory of the firm with research on corporate political connections, we argue that performance feedback does not translate mechanically into political board appointments. Instead, the effect of performance deviations on the appointment of political directors is moderated by the ideological character of the political environment. Using data on Spanish listed firms from 1990 to 2023, we find that performance deviations from aspiration levels are associated with a lower likelihood of appointing former politicians. However, populist ideology moderates this baseline relationship. Far-left populism attenuates and can reverse the negative association at higher levels, whereas far-right populism reinforces it, particularly under below-aspiration performance. Our study contributes to research on performance feedback, nonmarket strategy, and political connections by showing that firms’ governance responses to performance discrepancies depend on the ideological form institutional uncertainty takes.
What distinguishes contemporary intelligent technologies is that they produce knowledge claims that are grounded in logics quite different from those that have historically underpinned professional expertise and organizational decision making. AI systems rely on computational modeling, statistical inference, and large-scale data infrastructures. The outputs they generate are not simply new pieces of information; they are claims about what is likely, optimal, or true that are derived from patterns in data rather than from embodied experience, disciplinary training, or situated judgment. As such, they begin to unsettle established epistemic foundations within organizations, professions, and fields. This dynamic cannot be adequately described using the prevailing vocabularies of adoption, automation, augmentation, or digital transformation. Those frameworks presume that new technologies are incorporated into existing structures of authority and expertise. What we are observing is more consequential. Intelligent technologies introduce alternative bases of knowing that can rival, displace, or reconfigure existing ones. Accordingly, we propose viewing organizations not as information-processing entities but as arenas where competing epistemic regimes contend for legitimacy. In this view, organizational life involves ongoing struggles over what counts as credible evidence, who is authorized to interpret it, and how decisions ought to be justified. This shift in perspective opens a research agenda that focuses on how organizations manage clashes between computational and professional modes of reasoning, how authority is redistributed when algorithmic outputs gain standing, and how strategic action unfolds in contexts where the grounds of knowing themselves are in dispute.
Interest is growing in understanding the antecedents of reconciling exploration and exploitation, or ambidexterity. Research on the antecedents of ambidexterity has focused on formal organizational design (i.e. temporal cycles or structural means) or individual abilities (e.g. cognitive flexibility). However, research has overlooked the fact that individual abilities do not operate in a vacuum; how individuals perceive a situation can activate the abilities needed for ambidexterity. Thus, we bring a novel situational perspective to the study of ambidexterity. We examine how a manager's situational perception of their capacity to influence others and control outcomes (i.e. sense of power) affects their ambidexterity. Across three studies with middle managers, we show that a higher sense of power increases ambidextrous behavior; cognitive flexibility emerges as a key mechanism explaining this relationship. We highlight the crucial role of situational perception in ambidexterity and open up opportunities for better understanding situational antecedents of important organizational behaviors.
Previous research has widely recognized the importance of network diversity for entrepreneurial success. In this article, we look at the role of institutional intermediaries in this context, which provide another way to embed new ventures in their local environment. We propose two ways entrepreneurs engage with multiple entities in their localities-(a) by developing personal networks that connect with different actors and (b) by affiliating with institutional intermediaries-and examine how the two ways interplay to influence new venture performance. A longitudinal survey of 165 entrepreneurs in China found that the diversity of entrepreneurs' personal networks is positively related to new venture performance among those affiliated with public incubators, but not among those affiliated with private incubators. While private incubators can substitute diverse networks, public incubators complement diverse personal networks to improve new venture performance. The study makes new theoretical contributions to the literature on entrepreneurial networks and institutional intermediaries and provides implications for navigating entrepreneurial ecosystems.
After acquisitions, target CEOs are often pushed into a second fiddle role, experiencing a drop in relative standing that contributes to high turnover. These transitions hinge on post-acquisition hierarchies and expectations of deference, making traits linked to dominance consequential. We argue that second fiddle strain arises when trait-based dominance cues clash with these expectations, making the arrangement difficult for both target CEOs and acquiring executives to accept and sustain. Extraverted target CEOs are especially likely to generate such strain because their outgoing and dominant style conflicts with expected restraint. Because acquiring CEOs are central to enacting post-acquisition hierarchies, this strain is shaped by their extraversion. Highly extraverted acquiring CEOs more securely occupy the dominant position and grant greater behavioral latitude, easing constraints on extraverted target CEOs, whereas less extraverted acquiring CEOs rely more on formal authority, tightening these constraints, increasing target CEO turnover. Evidence from US acquisitions supports these arguments.
In this article, we depart from prior research, which has typically focused on the acquiring firm CEO, and adopt a behavioral agency perspective to examine how self-interested target CEOs' equity wealth shapes acquisition premium decisions. We argue that deal-specific windfall gains upon the acquisition announcement trigger immediate upward shifts in CEOs' reference points, heightening risk aversion and motivating value-preserving behavior. Using a sample of 435 acquisitions from 1994 to 2020, we find that larger windfall gains are associated with smaller increases in final acquisition premiums. The type of prospective wealth available to the CEO moderates this effect: organizational prospects, such as strong revenue growth, weaken the pull of loss aversion and encourage more aggressive bargaining, whereas personal prospects, such as post-acquisition retention, amplify loss aversion. Our findings highlight the behavioral consequences of sudden wealth shocks and reveal how different forms of prospective value shape target CEOs' influence over acquisition outcomes.
In this essay, I argue that mainstream organization theory (OT) scholars have failed to include intelligent technologies in their theorizing and that this omission is making the core of OT increasingly irrelevant in a world of organizations constituted by cloud computing, blockchain, social media, and artificial intelligence. I begin by examining three of the most active areas of research in mainstream OT-institutional theory, organizational identity, and sensemaking-and argue that theorizing in all three areas has not been updated sufficiently to reflect the central role of intelligent technologies in the phenomena they theorize. I go on to discuss some of the reasons mainstream OT scholars have missed the boat on intelligent technologies including (1) early framings of technology as exogenous to organizations; (2) a fascination with the ideal; (3) the ubiquity and invisibility of intelligent technologies in modern organizations; and (4) a lack of interest in technology among mainstream OT scholars. I close with some suggestions for steps that OT scholars might take to resolve this challenging situation.
Paradox theory increasingly acknowledges power, yet we still lack a clear account of how power dynamics shape the lived experience and constitution of organizational paradox. Addressing the question 'what is the role of power in shaping organizational paradoxes?' we develop a power-performative model grounded in Clegg's circuits of power to show how tensions become enacted, legitimized or suppressed through interactions, institutions and material infrastructures. The article contributes to paradox theory by (1) articulating an ontology of paradox as performed through situated, multilevel power relations; (2) theorizing how power dynamics influence when and how tensions are surfaced, framed or rendered invisible; and (3) advancing a critical, reflexive agenda that asks whose contradictions are recognized, whose are silenced and with what organizational effects.
Organizations often rely on deliberative groups-committees, taskforces, boards-to make decisions, yet deliberation's effectiveness remains contested. When can deliberation help a group outperform the average or even the best individual in the group? We propose that the value of deliberation depends on how the network structure of the group shapes informational influence (which promotes updating beliefs based on perceived expertise) and normative influence (which drives conformity to gain social approval). Using an agent-based model, we show that deliberation can help groups achieve strong synergy effects (i.e. outperform the best individual in the group) if members typically recognize each other's relative expertise at better than chance levels, and when the network structure neither isolates any members nor allows for clustering and cliques. Moreover, introducing a few actors into the network who are impervious to conformity (such as AI agents) can improve group decision quality even if these actors are no better than random chance at recognizing expertise. We draw implications for how to compose and structure group deliberation processes to improve the chances of obtaining effective decisions.
