Management control for innovation: a review and research directions

Research on management control for innovation has grown rapidly as scholars seek to understand tensions inherent in this context (Lill et al., 2021). A critical tension highlighted in the literature is the one between predictable goal achievement and creating space for freedom and flexibility that sustains innovation (Barros and Ferreira, 2019; Lövstål and Jontoft, 2017). Understanding this tension matters because it helps explain how management controls can both stifle and enable innovation. However, common ways of classifying control such as mechanisms, tools or types of use can understate what makes management control in innovation settings distinctive.

In this introductory article of the special issue we aim to explain why management controls were seen to hinder innovation, show how management controls can support innovation when designed and used in particular ways, propose a vocabulary to help researchers examine the dimensions of management control that are distinctive in innovation settings and provides examples from the papers in this Special Issue highlighting different aspects of this vocabulary which contribute to our understanding of management control in innovation settings.

Management controls are often discussed as part of the broader management process: setting objectives, choosing strategies, implementing them and then monitoring and correcting so that as little as possible goes wrong (Merchant and Otley, 2007). Because of this the term “management control” has been defined in both broad and narrow ways. Broad conceptualizations of management control can include “almost everything managers do to acquire, deploy and manage resources in pursuit of the organization’s objectives” (Merchant and Otley, 2007, p. 785). Narrower conceptualizations of management control focus more specifically on the devices and practices used to influence behavior so that actions and decisions align with organizational objectives and strategy (Merchant and Van der Stede, 2007). Malmi and Brown (2008, p. 290) have argued that researchers should “start with the managerial problem of directing employee behaviour” and thus defined management control as “Those systems, rules, practices, values and other activities management put in place in order to direct employee behaviour.”

Below, we summarize three commonly used frameworks in management control research on innovation to show how the literature has explained the ways in which controls can both constrain and enable innovation. Our purpose is not to dismiss these frameworks, but to open up space for research that examines other dimensions of management control in innovation settings.

A long-standing framework to organize research on management controls is Merchant’s (1982) object-of-control typology, which distinguishes action controls, results controls and personnel/cultural controls. Merchant and Otley (2007) summarized how this stream of literature seeks to explain how each mechanism has different strengths and weaknesses and can be designed as ‘tight’ or ‘loose’ depending on context (Merchant and Otley, 2007). Action controls aim to increase the likelihood that people do desirable actions, often by specifying accountabilities, procedures or constraints (Merchant, 1982). Results controls work by specifying desired outcomes and holding people accountable for achieving them, which depends heavily on the organization’s ability to measure results (Merchant, 1982). Personnel/cultural controls seek to align behavior more indirectly through selection, training, job design and socialization, as well as shared norms and values that support self-control and peer influence (Merchant and Otley, 2007).

A second influential framework is Simons’ (1995) levers of control framework which highlights how managers make choices about the use of belief systems, boundary systems, diagnostic controls and interactive controls. Simons (1995) argued that belief systems communicate core values and direction; boundary systems specify limits and rules; diagnostic controls monitor outcomes and correct deviations from preset standards; and interactive controls are used when top managers regularly and personally engage with subordinates’ decision activities to focus attention, stimulate dialogue and support learning. A key implication for innovation research is that these controls are not only about enforcing predictable goal achievement. Simons (1994, p. 170) explicitly notes that desirable patterns of activity can include “innovation and experimentation,” which makes the framework useful for studying how formal controls can both support and constrain innovation work (Strauß and Zecher, 2013).

A third widely used framework is Malmi and Brown’s (2008) package approach that groups management controls into five types and highlights that organizations typically rely on multiple controls operating together. Their typology distinguishes planning, cybernetic controls, reward and compensation, administrative controls and cultural controls (Malmi and Brown, 2008). Cultural controls are positioned as broad, subtle and often slow to change, providing a context for other controls. Cybernetic controls reflect a feedback logic built around measures, targets, feedback, variance analysis and the ability to modify behavior or activities. Reward and compensation controls link incentives to desired outcomes and behaviors, while administrative controls create the structural and procedural context in which other controls are exercised. This view of management control has been used to understand how multiple forms of control combine, sometimes reinforcing experimentation and learning and sometimes intensifying compliance pressures (Bedford et al., 2016; Berg and Madsen, 2020; Sharma and Sharma, 2021).

Across these conceptualizations of management control, a common message is that controls are not a single instrument with uniform effects. Instead, they are a set of mechanisms (Merchant, 1982; Merchant and Otley, 2007) that can shape innovation in different ways, depending on what is being controlled, how controls are used diagnostically or interactively and within or beyond boundaries (Simons, 1995) and how cultural, cybernetic, reward and administrative controls combine as a package (Malmi and Brown, 2008). This matters for research in this area because the same control device may constrain innovation when it is used to enforce compliance and reduce discretion, yet support innovation when it is used to clarify priorities, coordinate interdependence and enable learning (Lill et al., 2021).

This paper makes three contributions to the literature on management control for innovation. First, it shifts attention from classifying management controls by mechanism, use or package toward a vocabulary that helps researchers examine dimensions of management control that are especially salient in innovation settings. Second, it shows how this vocabulary makes visible six dimensions of management control that are understated in existing frameworks. Third, by mapping the Special Issue papers against these dimensions, it develops a research agenda for qualitative studies of how management control and innovation coevolve. The next section builds this argument by examining why the negative effects of management controls may persist and why a tension-based view is needed to understand how controls can both help and hinder innovation in practice (Lövstål and Jontoft, 2017).

Early work in the innovation literature often portrayed management control as problematic (Amabile, 1988; Damanpour, 1991). Formalization and compliance-oriented routines were argued to hinder experimentation and exploratory learning (Damanpour, 1991). It was also argued that management control could crowd out intrinsic motivation and creativity (Amabile, 1988). Research continues to document these constraining effects in contemporary settings. For example, Lill and Wald (2021) reported that diagnostic and boundary controls can negatively affect innovation project performance. Järvenpää et al. (2024) showed how process controls can reduce innovation possibilities in projects, and Frare and Beuren (2025) found that more mechanistic controls can dampen managers’ innovative behavior in startups.

At the same time, management accounting and control research has repeatedly shown that control can help support innovation, especially when it is used to guide attention, structure learning and balance exploration with coordination (Bisbe and Otley, 2004; Henri, 2006; Bedford, 2015). These insights have motivated a shift from treating control as mainly constraining toward analyzing how different designs and uses of control shape innovation outcomes across contexts (Barros and Ferreira, 2019; Davila, 2000; Davila et al., 2009; Henri and Wouters, 2020).

Lövstål and Jontoft (2017) showed that studies at the intersection of management control and innovation repeatedly mobilize competing demands and that these are often framed as tensions that cannot be permanently resolved. Their review highlights several persistent tensions, including freedom, flexibility and creativity versus discipline, standardization and control; organic and informal ways of working versus mechanistic and formal ways of working; long-term and exploratory innovation versus short-term objectives and financial goals; and internal development versus external development and open innovation. These competing demands can generate several mechanisms through which management controls may fail to support innovation.

First, controls can undermine motivation and risk taking when they are experienced as surveillance or as a narrow compliance demand (Amabile, 1988; Lövstål and Jontoft, 2017). When innovation work depends on experimentation, setbacks and discretionary effort, tight monitoring and sanction-focused accountability can shift attention from learning to self-protection, reducing psychological safety and willingness to explore (Lövstål and Jontoft, 2017).

Second, controls can create rigidity through formalization (Damanpour, 1991; Lövstål and Jontoft, 2017). Innovation processes often require iterative problem-solving, rapid adaptation and local judgment. Detailed rules, standardized procedures and gatekeeping routines may increase reliability, but they can also slow response, reduce variation and lock teams into early assumptions (Burns and Stalker, 1961; Lövstål and Jontoft, 2017).

Third, controls can produce short-termism when measurement and evaluation emphasize near-term results (Lövstål and Jontoft, 2017). Innovation typically spans multiple time horizons and contains long periods where progress is ambiguous. If targets and performance evaluation focus on short-term efficiency, managers may deprioritize exploratory work, defer investments or over-select ‘safe’ projects (March, 1991; Bedford, 2015; Lövstål and Jontoft, 2017).

Our aim is to shift research from whether management controls exist to how control arrangements are configured, enacted and recalibrated as innovation unfolds. The TRAPPS vocabulary reframes the relationship between management control and innovation as one that is continually shaped through Temporal, Reflexive, Adaptive, Performative, Pluralist and Strategic dimensions. While the use of these does not eliminate the tensions identified by Lövstål and Jontoft (2017) it provides an analytical pathway showing how tensions could be examined using qualitative methodologies, which we present in the following section.

Drawing on our combined expertise and a targeted reading of management control research on innovation (including the six papers contained in this Special Issue), we found a vocabulary that highlights six dimensions that we believe have become especially salient in innovation settings. These dimensions are Temporal, Reflexive, Adaptive, Performative, Pluralist and Strategic (see the summary of the six dimensions in Table 1). We are not proposing that research in this area needs to contain all these dimensions, but instead want to provide a way for researchers to examine innovation settings that may not have been visible using our current management control frameworks.

While the innovation-control literature contains a strong functionalist/positivist position (tight/loose control, levers of control, management control system packages), we also found that innovation contexts have socially constructed dynamics such as performativity (Revellino and Mouritsen, 2015) and pluralism (Jørgensen and Messner, 2010). Our TRAPPS vocabulary is designed to highlight areas where new research can emerge. Thus, we present the TRAPPS vocabulary of six dimensions to complement current management control frameworks by highlighting questions that may be missed when controls are treated as tools or mechanisms.

Temporal – Innovation unfolds across time and space where activities take place. These different time horizons can cause control practices to have different effects over time (Toldbod and Laursen, 2024) and across the locations where activities are carried out (Quattrone and Hopper, 2005). Temporal attention asks how controls shape pacing, sequencing and time-based trade-offs and how control requirements change across stages of innovation (Pan Fagerlin and Lövstål, 2020; Bedford, 2015). The temporal dimension also highlights how controllability shifts across time horizons, which in turn changes what control makes actionable (Chua et al., 2026).

Reflexive – Innovation settings are often exposed to the unintended consequences of control, including gaming and risk aversion. A reflexive stance questions what control is doing and is it doing what we thought. Thus, reflexive attention is about how managers and employees notice the consequences of control, questioning assumptions and redesigning controls in light of experience (Alvesson et al., 2008; Siti-Nabiha, 2009; Schneider, 2015). This resonates with ideas on organizational learning, including the need to question underlying goals and routines rather than only correcting deviations (Argyris and Schön, 1978). Research has also illustrated reflexive attention by showing how actors may reconsider what controllability should mean after experiencing the consequences of earlier choices, prompting revisions (Chua et al., 2026).

Adaptive – Because innovation paths are uncertain, controls often need to be reconfigured as situations change and new information emerges which results in evolving roles for management control (Akroyd and Maguire, 2011). Adaptive attention asks how control practices are recombined, loosened, tightened or redirected as projects pivot, as partners change or as uncertainty shifts (Henri and Wouters, 2020; Pan Fagerlin et al., 2026). Chua et al. (2026) illustrated adaptive control by showing how controllability boundaries can be tightened in some areas, loosened in others and even introduced where none existed as actors adjust the system in response to emerging problems. This also aligns with work on dynamic capabilities that emphasizes reconfiguring organizational resources as environments change (Teece et al., 1997).

Performative – Management controls are not only instruments that represent innovation, but they also help produce it. Thus, measures, targets and calculative devices are part of the sociomaterial arrangements through which innovation is defined, stabilized and made actionable (Callon, 1998; Latour, 2012). An attention to Performative aspects of control therefore asks how practices participate in assembling what counts as “valuable” innovation by framing problems, making some possibilities visible and comparable and rendering others less attractive. As these devices circulate, they can enroll actors, align interests and shape the pathways through which resources and attention are allocated (Callon, 1998; Latour, 2012). In this way, controls can be enabling through coordination but also restrictive by narrowing the space for innovation (Vosselman, 2022; MacKenzie, 2006).

Pluralist – Innovation often involves multiple stakeholder groups with different interests and evaluative criteria, including customers, regulators, communities and partners. An attention to pluralist aspects of management control asks how controls incorporate, translate or exclude viewpoints and how accountability is negotiated across organizational boundaries (Dillard and Roslender, 2011; Lövstål and Jontoft, 2017; Merchant and Otley, 2007).

Strategic – Finally, the strategic dimension asks how controls encode priorities through the articulation of purpose, along with commitments and constraints, and how they enable both intended and emergent directions through the resource allocation routines that make strategy consequential in day-to-day actions (Bessant and Tidd, 2015; Simons, 1994; Simons, 1995). Choices need to be made about where to search, what to fund and what not to pursue, while also remaining open to emergent opportunities and strategy that unfolds through learning and adjustment (Davila, 2005; Bessant and Tidd, 2015; Biswas and Akroyd, 2022).

In Section 4, we show how the papers in this Special Issue provide examples of these dimensions, and how the TRAPPS vocabulary can generate sharper research questions in innovation settings.

The papers in this Special Issue illustrate how the TRAPPS vocabulary can be used to analyze management control for innovation. Table 2 highlights how the Special Issue papers foreground the TRAPPS vocabulary which helps surface different analytical questions about management control in innovation settings. We then draw on selected examples from the papers to develop insights around the six TRAPPS dimensions.

The temporal dimension is visible when innovation unfolds across different phases, time horizons and spaces as management controls evolve as a project progresses. Liboriussen and Jakobsen (2026) showed temporal dynamics not only through iterative budgeting, but also through how the accountant’s “Socratic maieutics” creates time and space for curators to develop ideas that resolve financial problems while protecting artistic ambitions. Wijethilake et al. (2026) showed how cultural controls in Sri Lankan public–private partnerships evolve over multiple time periods as partnerships mature, ownership structures change and political priorities shift, producing different innovation trajectories. Ippolito et al. (2026) likewise foreground temporality showing how an accountability-oriented control package is stratified over time as new IT modules are layered in, with each layer reshaping performance monitoring and reporting needs. Kanzari et al. (2026) similarly highlighted a continuous process in which the introduction of eco-innovation led to changes in practices and then to the pursuit of a technology innovation, accompanied by adaptations in costing techniques. Beusch et al. (2026) also foreground temporality by tracing how sustainable innovation unfolds over a decade across interorganizational settings, with controls supporting different sustainability trajectories over time. Toldbod and Laursen (2026) foreground time within open innovation by showing that belief and interactive controls play a stronger role in the front-end phase, while boundary and diagnostic controls are largely absent.

The reflexive dimension becomes apparent when actors reflect on the consequences of existing controls and revise them as learning accumulates. Liboriussen and Jakobsen (2026) foreground reflexivity as the management accountant’s dialogical and reflective questioning prompts the curatorial team to reassess problems, values and feasible solutions as learning develops. Kanzari et al. (2026) showed reflexive dynamics as eco-innovation alters an organization’s value creation model, which then challenges established costing techniques and prompts a shift from traditional full costing toward life cycle costing, including life cycle costing configured for multiple use cycles. Beusch et al. (2026) also invited a reflexive reading by reconsidering assumptions about diagnostic and interactive controls, showing that diagnostic controls can support both compliance and learning while interactive controls remain limited in fostering change. Toldbod and Laursen (2026) showed an asymmetrical effect that includes intensive belief and interactive controls, which expand the depth of innovation while the lack of boundary and diagnostic controls reduce breadth as partners exit.

The adaptive dimension highlights how management controls are reconfigured as innovation paths shift, uncertainty changes and interdependencies expand beyond organizational boundaries. Wijethilake et al. (2026) showed cultural controls adapting on an ongoing basis to political interference, market competition and sustainability pressures, rather than operating as stable, fixed systems. Ippolito et al. (2026) described an organization in which management controls evolve organically as information needs change and as an innovative information technology supports data integration and transforms heterogeneous data into usable information. Kanzari et al. (2026) also showed adaptation as calculative practices are reframed through the integration of traces of changing value creation, extending their boundaries as eco-innovation evolves. Beusch et al. (2026) illustrated adaptation in interorganizational sustainable innovation, where company-centric boundary systems are challenged and adjusted in response to collaboration across organizational interfaces. Toldbod and Laursen (2026) added that, particularly at the front end of open innovation, financial and strategic justification becomes necessary to sustain collaboration and keep exploration moving.

The performative dimension draws attention to how calculative practices and information infrastructures shape what becomes visible, valued and acted upon in innovation work. Liboriussen and Jakobsen (2026) showed how budgeting practices, used as an epistemic method, shaped the evolution of an innovative exhibition project by creating meeting points where accounting data and artistic interpretations were jointly worked through, supporting both creativity and innovation. Wijethilake et al. (2026) also surface performative dynamics through its semiotic framing of the state’s “knowledge-based economy” discourse as a meta-object of governance that shapes and reshapes the culture of innovation. Ippolito et al. (2026) showed how management controls shape information systems and, conversely, how information systems influence management controls and the organization, particularly through monitoring and oversight activities that restructure accountability. Kanzari et al. (2026) mobilized performativity arguing that accounting and measurement practices not only represent transactions but can construct the reality they aim to reflect, sometimes disciplining eco-innovation within existing frames while also generating drifts that amplify innovation. Kanzari et al. (2026) also specified the performative mechanism by tracing how eco-innovation leaves “traces” linked to changes in customer-value creation that become integrated into calculative practices. As these traces are incorporated, calculative practices extend their boundaries and trigger actions that drive eco-innovation. Importantly, when calculative practices reveal potential economic value destruction, they trigger “drift” in eco-innovation and lead to rethinking roles, responsibilities and how value is created, producing an amplifying effect and a further cycle of adaptation in calculative practices. Beusch et al. (2026) highlighted how diagnostic controls and metrics can generate change in sustainable innovation contexts and shows that diagnostic controls can play a dual role by supporting both compliance (exploitation) and learning (exploration), while interactive controls remain limited in fostering change.

The pluralist dimension is foregrounded when innovation involves multiple stakeholder groups, competing logics and negotiated forms of accountability. Liboriussen and Jakobsen (2026) revealed a form of joint accountability between the management accountant and exhibition curators, where budget meetings helped manage both financial and artistic responsibilities. They further illustrate how plural values are negotiated in practice, as budgeting operates as a boundary-setting device that supports accountability while preserving artistic values within financial constraints. Wijethilake et al. (2026) showed how state, market, professional and labor logics coexist in public–private partnerships and are mediated through cultural controls rather than resolved through formal hierarchies or contracts. Ippolito et al. (2026) argue that public sector and healthcare settings highlight the multiplicity of objectives and the need for performance reporting to address diverse audiences and accountability demands. Kanzari et al. (2026) also pointed to plural evaluative criteria, as calculative practices must accommodate both environmental value creation and economic consequences. Beusch et al. (2026) showed that sustainable innovation relies on engagement within and between industrial organizations and external actors, supported by combinations of belief, interactive, boundary and diagnostic controls. Toldbod and Laursen (2026) demonstrated the challenges of plurality in open innovation, where Unilever’s collaboration with partners suffered from limited boundary and diagnostic controls that would have supported shared understanding, contributing to partner exit and an asymmetric pattern in which controls increased the depth of innovation while reducing breadth.

The strategic dimension concerns how management controls highlight direction, priorities and resource commitments that shape which innovation paths are pursued and sustained. Liboriussen and Jakobsen (2026) showed budgets and successive calculations as a way of ensuring compliance with allocated resources while fostering a shared understanding of the project narrative and the associated accounting models. Wijethilake et al. (2026) showed cultural controls aligning organizational identity and direction with the state’s knowledge-based economy agenda, signaling acceptable innovation approaches in a politically mediated setting. In Ippolito et al. (2026), IT-enabled performance information strengthens planning controls and allows managers to assess the effectiveness of strategic decisions regarding chronic care management. The creation of chronic-patient risk stratification is also presented as useful for health management strategies, linking control infrastructures to strategic direction. Kanzari et al. (2026) further showed how calculative practices shape strategic direction by focusing managerial attention on specific issues and technological priorities. Beusch et al. (2026) highlighte3d how sustainability-related controls facilitate initiatives such as circularity and emissions reduction that align with industrial strategies, and how alignment across belief, boundary and diagnostic controls can support sustainable innovation. Toldbod and Laursen (2026) also pointed to the strategic dimension, as partner commitment depended on a clear justification of the project’s value and benefits, showing how controls can shape whether open innovation efforts remain viable.

While the six TRAPPS dimensions may be observable across organizational settings, they become structurally central in innovation environments which are characterized by uncertainty, experimentation, evolving time horizons and competing evaluative logics. Innovation unfolds across multiple phases where outcomes are uncertain and performance is difficult to specify ex ante, making temporal coordination, reflexive learning and adaptive redesign necessary as controls are reassessed and reconfigured in response to shifting innovation paths (Bedford, 2015; Lövstål and Jontoft, 2017; Toldbod and Laursen, 2024; Pan Fagerlin et al., 2026). At the same time, the performative effects of accounting become more pronounced as measures and targets shape what is recognized as valuable innovation while also directing attention and impacting resource allocation (Callon, 1998; MacKenzie, 2006; Vosselman, 2022). Stakeholders also have different expectations which require controls to mediate competing values and accountability demands across organizational and interorganizational settings (Dillard and Roslender, 2011; Merchant and Otley, 2007; Lövstål and Jontoft, 2017). Strategic direction is therefore not simply implemented through control but continuously constructed through prioritization and resource commitments that stabilize innovation trajectories (Davila, 2005; Simons, 1994, 1995). In this sense, innovation does not merely provide a context for applying control systems; it exposes the dynamic, evolving and negotiated nature of control itself, which the TRAPPS vocabulary is designed to capture as different dimensions become especially salient in distinct innovation settings.

Building on the TRAPPS vocabulary, future research could more explicitly align research design with the distinctive features of each dimension and the conditions under which innovation unfolds. The Temporal, Reflexive, Adaptive, Performative, Pluralist and Strategic dimensions all point toward the need for in-depth, longitudinal field-based research capable of capturing how management control and innovation coevolve over time. Innovation rarely progresses in linear or predictable ways; its effects often become visible only across extended periods, as projects move through phases of exploration, experimentation, consolidation and scaling (Fried, 2017). Longitudinal case study designs are therefore uniquely suited to examining how control practices are introduced, contested, modified and stabilized, and how their consequences accumulate and reshape organizational priorities (Bedford, 2015; Lövstål and Jontoft, 2017). These approaches also enable researchers to observe how reflexive learning emerges, how adaptive reconfigurations unfold and how plural expectations are negotiated in practice, consistent with traditions in organizational learning and reflective redesign (Argyris and Schön, 1978; Langley et al., 2013).

However, the pursuit of such research raises institutional challenges. Longitudinal and carefully crafted field-based studies take time to mature, yet contemporary academic environments often privilege rapid publication outputs. This tension is particularly salient for management accounting scholars seeking to understand evolving organizational processes. Research on management control in innovation contexts requires sustained immersion, trust-building and iterative engagement with organizational actors (Ahrens and Chapman, 2006; Eisenhardt, 1989; Yin, 2018). We therefore call for greater support from governments, funding bodies and commercial and nonprofit organizations to create collaborative research schemes, fellowships and scholarship programs that make long-term engagement feasible. Such initiatives could help realign incentives to value depth, quality and theoretical contribution over speed and quantity. In this sense, advancing TRAPPS-informed research is not only a methodological concern but also an institutional one, requiring structural support for scholarship that unfolds over time.

Within the TRAPPS vocabulary, the strategic dimension presents a distinct opportunity for further problematization. Strategy has a long and evolving intellectual history in business scholarship, from early structural and planning traditions (Chandler, 1962; Ansoff, 1965), to competitive positioning (Porter, 1980) and later to emergent and processual perspectives (Mintzberg, 1978). In management accounting research, strategy has often been operationalized through performance measurement and resource allocation mechanisms (Simons, 1995; Davila, 2005). Yet in contemporary innovation contexts, strategy increasingly unfolds across networks and collaborative arrangements rather than through centralized planning. A systematic and critical literature review that revisits how the concept of strategy has evolved over decades could renew its meaning and relevance for innovation settings, particularly in relation to how control practices shape direction, prioritization and commitment. Longitudinal studies could then examine different aspects of these situations.

Methodologically, TRAPPS also invites researchers to broaden the repertoire of qualitative approaches used in fieldwork. Interviews and document analysis remain foundational, but they can be complemented by observational and ethnographically inspired methods that capture everyday practices, interactions and sensemaking processes (Alvesson et al., 2008; Ahrens and Chapman, 2006). Attention to discourse, language and narratives can reveal how innovation priorities are constructed and legitimized, while the inclusion of artifacts, visuals and calculative devices as empirical material can illuminate how accounting practices performatively shape organizational attention and value creation (Callon, 1998; MacKenzie, 2006; Vosselman, 2022). These types of data sources would be particularly valuable in settings where innovation is embodied, experiential and culturally embedded.

Empirically, the TRAPPS vocabulary encourages expansion beyond traditional corporate and industrial innovation settings such as product innovation (Davila, 2000), to examine innovation in the arts (Lampel et al., 2000), crafts (Wu et al., 2025), sports (Carlsson-Wall et al., 2016), fashion (Davila and Ditillo, 2017) and other creative industries. We believe that these offer fertile ground for examining how management control practices interact with identity, culture and meaning. These contexts often involve tensions between creative autonomy and resource constraints, making them particularly suitable for studying the performative and plural dimensions of control. Similarly, innovation linked to human wellbeing, sustainability and the preservation of human creativity in the age of artificial intelligence raises important questions about how control practices shape not only performance but also purpose (George et al., 2023). Exploring such domains can deepen our understanding of how accounting participates in the construction of organizational priorities and cultural meaning (Miller, 1994).

At the same time, there is a strong need for more non-Western empirical cases (Hopper et al., 1999; Uddin and Hopper, 2001; Wickramasinghe and Alawattage, 2007). Much of the management accounting and control literature remains grounded in Western organizational contexts, which may limit understanding of how control practices evolve across different institutional, cultural and socioeconomic settings. In particular, innovation carries with it power dynamics and can be used to dominate and marginalize communities (Hopper and Bui, 2016; Gallhofer and Haslam, 2004; Alawattage and Wickramasinghe, 2009).

Finally, while the TRAPPS vocabulary is intentionally open and empirically oriented, this can also be seen as a limitation. It foregrounds process, practice and methodological direction more than a single theoretical anchor. Future research could build on the TRAPPS vocabulary by integrating insights from indigenous theories, institutional theories, interpretive perspectives and performativity research to deepen understanding of how control shapes innovation, identity and organizational practices over time. By encouraging sustained field engagement, methodological pluralism and broader empirical scope, the TRAPPS vocabulary provides a foundation for a research agenda that is attentive to complexity, temporality and the evolving nature of innovation in contemporary organizations. For practitioners, the TRAPPS vocabulary reframes management control as an enabling infrastructure for innovation rather than a constraint.

Our review and the papers in this Special Issue show that management control evolves across phases of experimentation, development and scaling. Managers and entrepreneurs can benefit from treating budgets, performance measures and accountability structures as provisional and revisable, using them to guide attention and support learning. The performative insight is especially important as it influences what organizations choose to measure, which then shapes what is seen as valuable and worthy of investment. This is particularly relevant in settings where value is uncertain or socially oriented. The TRAPPS vocabulary also highlights the importance of balancing multiple stakeholder expectations and using control systems to signal priorities and direction.

In this paper, we argue that management control in innovation settings must balance a central tension between reliable goal attainment and the freedom and flexibility required for experimentation. The literature shows that management controls can both constrain and enable innovation, and that outcomes depend on the design and use of multiple controls operating together. To support future research, we introduced the TRAPPS vocabulary as a way to highlight six dimensions of management control that become especially salient in innovation settings. We believe that the TRAPPS dimensions can be used either independently or alongside established frameworks to examine the distinctive problems that arise as organizations manage innovation over time. Overall, the TRAPPS vocabulary encourages researchers to treat management control for innovation as an evolving, contested and constructive practice and to carry out research that explains when and why management controls restrict innovation, when they enable it and how both effects can coexist in the same setting.

The authors would like to thank the two reviewers and QRAM Editor Sumit Lodhia for their constructive feedback. The authors also thank Editors Emeriti Lukas Goretzki and Thomas Ahrens for all their support for the Special Issue. In addition, the authors are grateful to Stephen Jollands, Basil Tucker and Martine Cools for their constructive comments on earlier versions of this paper. Any remaining errors are the responsibility of the authors.