Knowledge that Transforms

Green innovation is an organizational strategy aimed to address climate crises and create low-carbon growth, yet, its implementation remains a significant challenge. We focus on green innovation implementation (GII) and argue that GII is a distinctive strategic process. Traditional innovation implementation, centered on short-term economic growth, can be problematic as it often decouples nature from innovation in the pursuit of profit maximization. Thus, the traditional approach fails to adequately explain GII, specifically, who implements it and how they do it. We adopt a strategy-as-practice perspective and conduct a systematic review of 224 journal articles across various management fields to synthesize existing knowledge of GII. This review makes three main contributions. First, we posit that GII is theoretically distinct with unique implementation challenges: recoupling nature with innovation implementation introduces complex antecedents and environment-inclusive benefits, requiring a long-term implementation process and a broader scope. Second, we develop a framework that synthesizes practitioners, antecedents, processes, and impact of GII from three theoretical foci: (1) resource-based perspective, (2) sustainable value-driven perspective, and (3) institutional perspective. This framework complements the traditional understanding of innovation implementation by offering diverse theoretical insights on GII. Third, we propose theoretical and methodological directions for future research to advance knowledge on green innovation and provide meaningful insights on GII.

Interorganizational ecosystems require governance arrangements that can align diverse and often competing organizations around a shared value proposition. Although blockchain, as a form of digital governance, promises to facilitate large-scale collaboration by codifying and enforcing rules, decentralizing control, and ensuring verifiable data exchange, many blockchain-based interorganizational ecosystems nevertheless fail. Leveraging 155 interviews and detailed internal records from a large technology provider covering 81 interorganizational blockchain projects across 25 industries, supplemented by archival evidence on the trajectories of 196 projects and 70 podcast interviews, we develop a grounded theory explaining how governance misalignments trigger collaboration breakdowns. Specifically, we identify three underlying governance tradeoffs that expose tensions between blockchain’s network-centric rules and actor-centric needs: consistency versus flexibility in coordination, system reliance versus actor reliance in trust and control, and ecosystem utility versus member utility in incentives. These tradeoffs are amplified or attenuated by corresponding boundary conditions related to scale and cohesion (for coordination), co-opetition (for trust and control), and value logics (for incentives). Our study advances governance theory by explaining how blockchain interacts with traditional governance, shapes critical tradeoffs, and influences ecosystem success and failure. We also offer design principles to help managers navigate the inherent governance tradeoffs in ecosystem collaboration.

When employees face hostility from others, emotion regulation is needed to perform effectively but can be personally costly. On the basis of current evidence, employees both perform better and avoid well-being costs with engagement-focused regulation (i.e., modifying feelings through deep acting) rather than with disengagement (i.e., modifying or faking expressions through surface acting). Yet, emotion regulation theorizing suggests this good–bad dichotomy is an oversimplification, and no known work has simultaneously considered the performance and well-being consequences of emotion regulation strategies at the event level. To address these issues, we apply the comprehensive six-strategy emotion regulation framework to identify emergent combinations of regulation strategies used in response to hostile events. Across two studies, we find six emotion regulation profiles, with the pattern of these profiles largely replicating across samples. Study 2 reveals that profile enactment is driven by the intensity of the event and has distinct consequences for employees’ event performance and well-being. We also find the first known evidence of a trade-off, where profiles that result in the highest negative affect were also the most effective for episodic performance. Meanwhile, profiles that maintained low levels of negative affect were linked with lower event performance ratings. Thus, in contrast to the good-bad strategy dichotomy common in the emotion regulation literature, we find that enhancing event performance comes at a cost to affect, and vice versa. This high-hostility work context points to a no-win situation for employees, who must choose between maximizing event performance and minimizing personal costs.

As seven of nine planetary boundaries are breached, management scholars face an urgent challenge: how can organizations address complex social-ecological crises that transcend traditional organizational boundaries and objectives? Responding to this need, researchers have leveraged a plurality of systems perspectives, yet current approaches remain nascent and fragmented. In this paper, we review 25 years (2000–2024) of empirical sustainability management research across 17 leading journals. We identify core systems properties—interrelatedness, nestedness, non-linearity, and emergence—that collectively illuminate four critical systems-wide dynamics: equilibrium, disequilibrium, adaptation, and organized systems change. This systematic review offers scholars a unified framework for theorizing and addressing critical sustainability challenges facing organizations, society, and the planet.

Managerial mental representations (MMRs) are mental constructs that structure cognitive content to guide perception and interpretation. MMRs have been examined across a broad spectrum of management research contexts, leading to the use of numerous related terms such as “mental representation,” “schema,” “mental model,” “cognitive frame,” “cognitive map,” and “mindset.” This proliferation of terms has caused considerable definitional overlap and ambiguity. To foster definitional clarity, this review systematically analyzes 206 articles employing any of 33 MMR terms used during the past 30 years. We identify the conceptual and functional definition facets of MMRs and use them to analyze commonalities and differences among the most prominent MMR terms. We further examine both established and emerging discussions surrounding the characteristics of MMRs. Established discussions focus on MMR content and levels of analysis, while emerging discussions explore MMR permanence and implicitness. We propose suggestions to advance each conversation. Based on this comprehensive analysis, we create a guiding framework aiding future research to conceptualize MMRs and navigate terminology choices. Finally, we propose two future research directions: integrating the content and process perspectives on MMRs and applying an MMR lens to examine the emergence of artificial intelligence in organizations.

Sampling data from organizations and humans associated with those organizations is essential to organizational research. Much of what we know about organizations is based on such work. However, this empirical foundation may be compromised, calling into question the field’s theoretical and empirical findings. Studies often sample data from relatively similar, narrow contexts, so a lack of sample diversity accumulates in the discipline. To conceptualize this lack of sample diversity and examine its prevalence across research publications, we conduct a pre-registered systematic review of articles from 2018 to 2022 in six top management journals and another systematic review of articles from 2013 to 2022 in six additional journals (not pre-registered). Our review assesses sample country diversity while also exploring within-country factors that are relatively under or oversampled, such as the size or industry of the sampled organization. We find a lack of sample diversity, for instance, a strong bias toward WEIRD (Western, educated, industrialized, rich, and democratic) samples and an underrepresentation of small and medium-sized enterprises in organizational research. Based on the findings and past work, we introduce a conceptual framework for sample diversity along three dimensions: the sample’s geographical, organizational, and personnel contexts. Additionally, we discuss factors that contribute to a lack of sample diversity and propose guidelines for authors, reviewers, and editors to enhance it. Overall, this article seeks to improve the robustness and relevance of theoretical and empirical organizational research, thereby preventing the formulation of misinformed policies and practices in both organizational settings and broader societal contexts.

Modern organizations frequently expect their employees to exhibit high creativity while facing considerable job insecurity. Although it is often assumed that job insecurity diminishes individual creativity, the empirical findings on this relationship are not consistent. The present study aims to scrutinize this assumption and to address such inconsistencies. To do so, we cast both job insecurity and creativity as multidimensional constructs, and we examine key mechanisms and boundary conditions of their linkages. Results from both a longitudinal (Study 1) and a time-lagged multisource survey study (Study 2) illustrated a negative indirect relation between quantitative job insecurity and radical creativity via diminished career commitment. For qualitative job insecurity, by contrast, there was a negative indirect relation with incremental creativity via reduced organizational identification. Moreover, Study 2 revealed distinct moderators for these associations. Employees’ turnover risk propensity buffered the indirect connection between quantitative job insecurity and radical creativity, whereas Confucian traditionality mitigated the indirect relation between qualitative job insecurity and incremental creativity. These findings shed new light on the important role of job insecurity for individual employees’ creative performance and advance our theoretical understanding of the complexities underlying these linkages.

Entrepreneurial affect has emerged as a burgeoning area of study, with a wealth of articles demonstrating that affect, broadly conceptualized, plays an important part in entrepreneurial life. While a few affective phenomena, such as passion and positive and negative affect, are primarily driving the affective revolution in entrepreneurship, a wide range of additional forms of affect, from momentary feelings to enduring affective dispositions, have been found to influence entrepreneurs’ judgments, decision-making, attitudes, and behaviors in distinct parts of the entrepreneurial process. Moreover, entrepreneurs’ affective experiences and displays of these experiences influence entrepreneurial behaviors and investors’ decision-making. Although this is an exciting time for work on entrepreneurial affect, several theoretical and empirical inconsistencies impede further knowledge accumulation. To assess how and why affect is critical to entrepreneurship, to clarify the theoretical inconsistencies, and to provide an integrative framework, we conduct a systematic review of 276 published empirical and conceptual articles on entrepreneurial affect. In doing so, we analyze how various affective phenomena (e.g., emotions, moods, sentiments), along with their discrete forms (e.g., anger, grief, happiness), influence and are influenced by specific stages of the entrepreneurial process. We conclude that while this body of research confirms that entrepreneurship is an emotional endeavor, the collective approach has thus far obscured a more detailed and useful understanding of affect in each stage of the entrepreneurial process. We examine the theoretical and empirical approaches taken to date and lay out an agenda for future scholars, thus bolstering the affective revolution in entrepreneurship.

In this editorial, we discuss and define the “future of work” as a phenomenon and research area, and outline avenues for further research at the conceptual and empirical level. We first offer a brief review of the different streams of research that study the future of work, both in management and organization studies and in adjacent fields. We then elaborate on what we see as the most promising avenues for research on the future of work, organized around five questions of what, when, who, how, and why. That is, research on the future of work needs to clarify its assumptions about (1) the phenomena it considers within scope; (2) the temporality associated with these phenomena; (3) which future of work actors it is about and whom it is for; (4) the methods and data types used to be able to study the future empirically; and (5) desired impact and envisioned outcomes. We discuss how moving beyond techno-determinism, depoliticization, and a present-day focus could open up new and important avenues for further research on the near and distant future of work. We conclude with some specific examples of research questions and methods.

Signaling theory is about decision-making and communication. It describes scenarios where signalers send observable signals that carry credible information about unobservable qualities. When decision-makers have incomplete or imperfect information, signals can help them make better decisions. The power of a signal, though, lies in its cost, with the best signals being highly costly for low-quality signalers and less costly for high-quality signalers. Given the centrality of these ideas in the organizational sciences, we examine management studies that use signaling theory to help explain phenomena that occur within and among organizations. Our review draws attention to how signaling theorists have introduced important complexities to the signaling process, uncovered theoretical boundary conditions of signaling, described new actors within signaling systems, and demonstrated novel ways to apply signaling theory to understand behavior in an array of research contexts involving a wide range of organizational stakeholders. We also offer ideas about how scholars can account for costs when they apply the theory, extend the theory in more organizational settings, and create abstract extensions of the theory’s major concepts. Our intent is to provide researchers with a panoramic perspective on the state of signaling theory and inspire further development so that we can collectively advance signaling theory as much in the next decade as it has advanced in the last.