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Entry

Innovation: Between Ambiguity and Clarity

by
Rotem Rittblat
Federmann School of Public Policy and Governance, The Hebrew University of Jerusalem, Mount Scopus, Jerusalem 91905, Israel
Encyclopedia 2025, 5(3), 123; https://doi.org/10.3390/encyclopedia5030123
Submission received: 18 June 2025 / Revised: 22 July 2025 / Accepted: 8 August 2025 / Published: 14 August 2025
(This article belongs to the Collection Encyclopedia of Social Sciences)

Definition

This entry addresses the ongoing challenge of defining innovation within the social sciences, particularly in organizational theory. It conceptualizes innovation as a dynamic and embedded organizational phenomenon. Innovation is central to contemporary discourse, yet it remains fluid, contested, and context-dependent. Rather than viewing innovation as a fixed technical process, the entry examines how it emerges through shifting configurations of meaning, organizational structures and institutional environment. It draws on institutional, processual, and configurational perspectives. These perspectives emphasize the role of ambiguity and clarity as co-existing forces that shape innovation across multiple levels. The entry aims to clarify this ambiguity through a synthesis of typologies, theoretical frameworks, and empirical insights. In doing so, it offers a configurational lens on how innovation is shaped and interpreted across diverse organizational and institutional contexts.

1. Introduction

Innovation functions simultaneously as a foundational organizational capability and as a strategic imperative [1,2]. This is reflected in recent organizational scholarship that calls for novel approaches to theorizing the future [3] and highlights innovation as a key mechanism for enabling novel forms of organizing and responding to uncertainty [4,5].
Yet despite its central role in organizational discourse, innovation remains a deeply contested and conceptually ambiguous construct. This duality—between innovation as a normative necessity and as an analytical puzzle—sits at the heart of both academic and practical discussions.
This conceptual ambiguity can be attributed to the fact that innovation is a multidimensional and nonlinear phenomenon [6,7,8,9], and has an interdisciplinary knowledge base. Innovation research spans multiple fields—including economics, management science, sociology, geography, political science, and healthcare—each contributing distinct frameworks and assumptions [10,11,12,13,14]. It also addresses both the conceptualization of innovation and the professionalization of innovation roles.
Innovation has been studied from multiple perspectives in the literature. It has been conceptualized as a process and an outcome [2,7,8], as a social construction [8], and as a paradox [13]. Scholars have also examined it as a field-level legitimation mechanism for the adoption of new practices [15], and as a strategic approach for enabling collaboration and knowledge sharing within emerging institutional forms—such as innovation platforms designed to address societal challenges [16].
Beyond academia, innovation has become a cultural ideal, symbolizing progress, creativity, and distinctiveness [17]. This symbolic weight has supported the emergence of new practices and professional roles—such as innovation experts and managers—within the institutionalization of innovation across organizations [18,19].
However, this adoption also brings tension. Innovation embodies both novelty and continuity, which can generate confusion and uncertainty. These tensions may, in turn, hinder innovation’s institutionalization within organizations [20,21].
Despite its prominence, innovation remains a vague and inconsistent concept. It is often described as a “black box” term [22], lacking a clear and shared definition [23,24]. Its meaning shifts across disciplines, fields, and institutional settings.
For example, innovation is frequently conflated with creativity, though the two are distinct [25,26]. Creativity refers to the generation of novel and valuable ideas. Innovation, by contrast, refers to the implementation of those ideas into new products, services, or practices [27]. A related confusion involves the distinction between innovation’s outcomes and its processes [23].
This entry explores the ambiguous and paradoxical nature of innovation, emphasizing how it operates both as a conceptual puzzle and a normative necessity. To unpack this complexity, I draw on the typology of theorizing approaches developed by Cornelissen, Höllerer, and Seidl (2021) [28]. Specifically, I propose the use of configurational theorizing—an approach that examines how multiple concepts or constructs combine into distinct configurations that explain why and how innovation occurs [28] (p. 8) [29].
From this perspective, innovation should not be treated as an in isolated or singular concept. Instead, it emerges from the interplay between configurations of meaning, organizational structure, and institutional environment.
Defining innovation more precisely is essential—not only to clarify scholarly assumptions, but also to ground innovation research in specific contexts [30]. This, in turn, enhances our understanding of how innovation emerges, evolves, and becomes institutionalized.
Moreover, defining innovation matters conceptually, because it captures the interplay between change and continuity; practically, because it influences how firms, governments, and societies respond to uncertainty; and scholarly, because it is central to how we study transformation, creativity, and institutional change.
Yet, precisely because of its popularity, innovation risks becoming a vague placeholder—obscuring more than it reveals. This entry responds by shifting the focus toward how ambiguity and clarity coexist within institutional and organizational configurations.
Similarly, Splitter et al. (2023) [31] discussed “openness” not as the opposite of closure, but as an organizing principle built on the productive tension between ambiguity and structure (p. 7). Their analysis of open innovation, platforms, and government shows that openness functions within—rather than against—institutional constraints.
In parallel, this entry argues that innovation is not clarified by eliminating ambiguity, but by configuring it—translating institutional multiplicity and organizational complexity into situated forms of clarity.
This reflects March’s (1991) [32] classic distinction between exploration, which thrives on uncertainty and experimentation, and exploitation, which values efficiency, coherence, and clarity. Innovation, situated between these poles, draws its power from their tension: ambiguity fuels novelty, while clarity anchors outcomes.
O’Reilly and Tushman (2013) [33] expanded this view through the concept of organizational ambidexterity—the ability to pursue exploration and exploitation simultaneously. They argued that innovation success depends on managing the tension between ambiguity and clarity, by building structures and leadership that support both flexibility and control. In this way, ambidexterity becomes a practical expression of the configurational nature of innovation.
The entry is structured as follows. First, it introduces the key concepts, definitions, and typologies that shaped current understandings of innovation. Next, it reviews dominant theoretical perspectives and examine how they engage with complexity. It then presents a configurational approach to innovation, supported by the figure and table in the manuscript, which illustrate how ambiguity and clarity interact across different innovation types and contexts. Finally, the entry concludes by identifying key research gaps and outlining future directions for advancing a more situated and dynamic understanding of innovation.

2. Literature Review

2.1. Conceptualizations, Definitions, and Typologies of Innovation

Historically, the term innovation was viewed with skepticism reflecting a degree of social resistance and ambivalence [22,34]. In recent decades, however, this perception had changed dramatically. Innovation is now seen as a strategic necessity [1].
One of the earliest and most influential definitions comes from Schumpeter (1934), [34] who described innovation as “doing things differently”—an act that leads to the creation of new products, services, methods, or organizational forms. His perspective emphasized innovation as a dynamic force driving economic change.
In organizational settings, innovation is often defined relatively: what is considered new in one organization may already be established elsewhere [2]. Innovation can range from incremental change to radical transformation [35], and it increasingly underpins business models, drives development, enhances regional competitiveness, and signals national resilience [8].
Crossan and Apaydin (2010) [2] conceptualized innovation as both a process and an outcome. As a process, it involves the generation, assimilation, and implementation of ideas that create economic or social value. As an outcome, it results in new or improved products, services, and methods. This dual perspective has been influential across disciplines.
A wide range of innovation typologies has been proposed in the literature across different disciplines. For instance, Chandy and Prabhu (2010) [36] provided a foundational marketing-oriented synthesis, outlining typologies such as product versus process, radical versus incremental, and technical versus administrative innovation.
Typologies of innovation models reflect how the concept has evolved over time. Keeley et al. (2013) [23] proposed an organizing framework called the Ten Types of Innovation. These types are grouped into three key categories. The first, Configuration, refers to innovations focused on the core operational mechanisms of enterprises and business systems, such as the profit model, network, structure, and process (the term configuration in Keeley et al. (2013) [23] refers to a category of innovation types focused on a firm’s internal mechanics, such as profit model, process, and network; in this entry, configuration is used differently—as a theoretical lens informed by configurational theorizing (Cornelissen et al., 2021 [28]; Furnari et al., 2021 [29]) that explores how institutional, organizational, and symbolic elements interact to shape innovation). The second category, Offering, includes innovations in the core products and services of an organization, specifically product performance and product systems. The third category, Experience, addresses customer-facing elements, including service, channel, brand, and customer engagement. This typology is nonhierarchical and nonlinear, allowing for flexible combinations of innovation types. However, Keeley et al. (2013) [23] cautioned that analyzing organizations across all ten types can be overly broad; instead, they recommended focusing on specific platforms or areas of innovation. While Keeley et al. (2013) [23] offered a functionally oriented approach to innovation types, Cohendet and Simon (2017) [11] presented a historical typology that traces the evolution of innovation logics. Their model shifts the focus from structural dimensions to how innovation practices have transformed—from linear and closed processes to interactive internal collaboration, and eventually to open models that draw on both internal and external knowledge. This historical perspective complements functional typologies by situating innovation within broader socio-economic and institutional transformations.
Cohendet and Simon (2017) [11] identified three generations of innovation models:
  • Linear and closed innovation (World War I to mid-1980s): A sequential, internal process ending in market delivery, based on the assumption that innovation occurs within organizational boundaries [11] (p. 35).
  • Interactive and closed innovation (mid-1980s–2000s): Innovation is understood as an interactive process dependent on internal collaboration. This model emphasizes the role of organizational infrastructure in facilitating knowledge exchange: “what matters is the internal capacity of organizations to facilitate the interactions between actors…to reinforce innovative ideas” [11] (p. 39).
  • Interactive and open innovation (2000s–present): Inspired by Chesbrough’s (2006) [37] open innovation model, this approach posits that organizations innovate by leveraging internal and external knowledge sources—such as customers, universities, and startups—using both pecuniary and nonpecuniary mechanisms [38].
Together, these typologies underscore how innovation is embedded not only in technical processes but also in institutional, organizational, and cultural contexts.
Kochetkov (2023) [14] expanded this discussion by linking the evolution of innovation typologies to broader shifts in organizational logic, openness, and collaboration. He offered a historical review of innovation studies and proposed a hierarchical typology that spans individual, organizational, and institutional levels. Building on Sundbo’s (1998) [39] conceptual scheme, Kochetkov (2023) [14] introduced second-level categories such as open innovation, agile innovation, and helix models, capturing how contemporary innovation processes span sectors, actors, and knowledge systems.
This aligns with the configurational perspective developed in this entry, which conceptualizes innovation as emerging from context-specific interactions between meaning, organizational structure, and institutional environment. Like this entry, Kochetkov (2023) [14] emphasized that innovation is not reducible to a single logic or domain but instead unfolds through multiple overlapping dimensions.
Digitalization has significantly reshaped innovation research. As Kochetkov (2023) [14] noted, it has transformed the value creation chain by introducing greater openness, engaging multiple actors, and enabling nonlinear, generative outcomes. This shift highlights the need for frameworks—such as the one proposed here—that can account for configurational complexity. This view is echoed by Nambisan, Wright, and Feldman (2019) [40], who argued that digital technologies reshape not only the structure of innovation and entrepreneurship but also the logic, pace, and direction of innovation systems.
In light of these developments, the concept of the innovation ecosystem has gained prominence as a way to more holistically capture the embeddedness of institutional, organizational, and cultural contexts. Rather than treating innovation as confined within organizational boundaries, ecosystem thinking emphasizes its distributed nature across interdependent actors and institutions.
Further developing this perspective, Granstrand and Holgersson (2020) [41] provided a comprehensive conceptual review and offered a refined definition of innovation ecosystems. They defined these ecosystems as evolving institutional arrangements in which diverse actors—such as firms, universities, governments, and users—interact cooperatively and competitively to cocreate value. Their work clarified the boundaries, roles, and governance structures that distinguish ecosystems from traditional supply chains or networks, positioning them as distinct configurations within broader innovation typologies.

2.2. Perspectives of Innovation

2.2.1. Institutional Perspective

Institutional theory highlights the key role that organizational structure and institutional environment plays in shaping organizational innovative processes [2,42]. It emphasizes the embeddedness of organizations within institutional environments on different levels of analysis: global, occupational, organizational, industrial, and interpersonal [43]. These environments consist of systems of meanings, shared understandings, formal rules, and behaviors. Actors operate within these systems, which shape the way they interpret innovation [42] (p. 2).
It is well-established that organizations must navigate multiple and often competing institutional demands [44]. Innovation, therefore, both arises from institutional contexts and contributes to their transformation [9]. However, empirical findings by Damanpour and Schneider (2006) [45] revealed that internal organizational characteristics—particularly structural features and the top managers’ attitudes—exert greater influence on innovation adoption than external environmental or demographic factors. This suggests a productive tension between institutional embeddedness and organizational agency. While innovation is shaped by field-level pressures, its actual adoption also depends on leadership orientation and internal organizational dynamics.
The neo-institutional perspective focuses on “how novel innovations or activities become established as taken-for-granted practices” [15] (p. 993). It also explores “how new kinds of activities emerge and provide a foundation for the creation of a new practice” [15] (p. 993). Through the lens of institutional work, defined as the “effects of individuals and organizational action on institutions” [46] (p. 216), actors actively participate in “creating and promulgating innovations” [15] (p. 993) and in “effecting, transforming and maintaining institutions and fields” [46] (p. 215).
Phillips (2013) [47] specified three key institutional concepts that aid our understanding of innovation: organizational field, institutional logic, and institutional distance. Organizational field is defined as a group of organizations that form an identifiable area of institutional life, including key suppliers, resources and product consumers, regulatory agents, and other organizations that produce similar services and that often communicate and share ideas. Thus, the concept of an organizational field constitutes an analytical tool because organizations in a given field share sets of practices, organizational forms, and institutional logic [47]. This shared context creates the conditions under which innovations emerge, diffuse, and become institutionalized, as organizations both compete and collaborate in the adoption of new practices.
Institutional logic, defined as “the organizing principles that shape the behavior of field participants… a set of belief systems and associated practices… [that] define the content and meaning of institutions” [48] (p. 631), helps explain how innovation gains meaning and legitimacy within organizations. There could be several coexisting logics in one organizational field [48]. This approach was developed in the foundational work of Thornton, Ocasio, and Lounsbury (2012) [49], who conceptualized institutional logics as historically contingent systems that influence attention, action, and meaning across multiple levels. This means that “what counts as rational is itself shaped by socially validated understandings and taken-for-granted assumptions” [50] (p. 262). Institutional logic serves as both a meta-theory and as a method of analysis [51], helping scholars explain how goals and coherence emerge within organizational field [48].
This view resonates with Splitter et al. (2023) [31], who conceptualized openness as an emergent institutional logic. In their account, openness operates not just as a managerial tool but as a guiding logic embedded in field-level expectations. It informs how legitimacy is constructed, how authority is structured, and how collaboration unfolds across institutional boundaries [31].
Lounsbury et al. (2021) [50] extended this by calling for a dynamic view of logic—as a constantly evolving phenomenon. Innovation, in this sense, is shaped by dominant or competing institutional logics that influence what types of change are seen as appropriate and how new practices are interpreted and implemented.
Institutional distance refers to the challenges faced by organizations operating across different national contexts. As Kostova (2020) [43] explained, “companies doing business across national borders are embedded and exposed to multiple and different institutional environments in their home and host countries, and, as a result, face unique difficulties and risks” [43] (p. 469). This includes differences in regulatory systems, cultural norms, and cognitive frameworks. Institutional distance can hinder or enable the transfer and adoption of innovation across borders, making it a key concern for multinational innovation strategy [43].
Together, these concepts demonstrate that innovation is not merely a technical process but a socially constructed and context-dependent phenomenon. Organizational fields highlight how shared contexts—including common practices, organizational forms, and institutional logics—shape the emergence, diffusion, and institutionalization of innovation. Institutional logic determines how innovation is framed, interpreted, and justified. Institutional distance explains how variations in context affect innovation outcomes in global and cross-national environments.

2.2.2. Process Perspective

Innovation does not unfold as a linear sequence of steps. Instead, it is a dynamic and iterative journey shaped by uncertainty and ambiguity [7]. Garud et al. (2013) [8] emphasized that this journey is characterized by relational, temporal, and cultural complexities. These complexities make it essential to view innovation as both contextually embedded and interpretively driven.
Expanding on this view, Garud, Gehman, and Giuliani (2014) [51] emphasized the situated and interpretive nature of entrepreneurial innovation. They focused on the co-creation of actors and contexts, arguing that innovation emerges from the contextual configuration of heterogeneous resources within institutional environments. Bathelt et al. (2017) [22] similarly highlighted the cyclical nature of innovation, reflecting the “long waves” of economic development. As a result, organizations must continuously navigate the tension between the drive for innovation and the pull of institutional stability [21] (p. 8).
Innovation is not a predictable or uniform sequence. It comprises a dynamic set of activities that often emerge sporadically and across organizational levels [7]. These activities can unfold simultaneously within organizations, networks, communities, or broader innovation ecosystems. To fully grasp these dynamics, researchers must pay close attention to the cultural, organizational, and social contexts in which innovation processes are embedded.
To understand the complexity of engaging directly with innovation, researchers must become attuned to the systems of meanings that drive and sustain innovation internally. These systems are not external influences but are embedded within innovation itself. They shape how actors interpret and enact new ideas. Thus, scholars are called to examine how actors participate in innovation and how social and institutional arrangements harness complexity “as a generative force” [8] (p. 801). Rather than viewing complexity as a barrier, this perspective frames it as a productive element of the innovation journey.
Defining innovation as a nonlinear process [7] necessitates studying the various complexities that may hinder the flow of ideas [8,45]. Relational complexity [8] (p. 792) arises from the involvement of diverse actors and material elements [8] (p. 793). Temporal complexity reflects the evolving chains of event, where something initially viewed as a failure may later be seen as valuable, or vice versa. Researchers must consider how actors perceive time and evolution in innovation. Some focus on present technologies that shape the future, while others may interpret past developments to make sense of present trends or future expectations. Narratives of innovation often serve as tools to mediate these differing temporal views and guide innovative efforts. Cultural complexity [8] (p. 795) pertains to how innovation diffuses across social groups, contexts, and regions. Innovation in one setting may not be adopted in another—or may only be adopted with significant modifications [8].
These three forms of complexity—relational, temporal, and cultural—underscore the need to manage innovation amid diverse and shifting challenges [1,52,53].
Such challenges create uncertainty, risking resource depletion and failure [52,53,54]. Entrepreneurs and innovation managers who experience failure may not be given another opportunity to pursue new initiatives. Van de Ven (2017) [7] described the innovation journey as chaotic and difficult to control, often leaving innovators with little agency or responsibility for the outcomes—whether success or failure.

2.2.3. Innovation Management

Innovation management—defined as the ways in which new ideas are organized, shaped, and implemented—must mediate both technical and institutional dimensions. These dimensions fundamentally influence whether innovation succeeds or fail [55]. Another view emphasizes that the field of innovation management has delved deeply into “what the everyday work of innovation entails” [56] (p. 139)
Birkinshaw et al. (2008) [20] identified four main theoretical perspectives for studying innovation–management processes. First is the fashionable perspective, which views innovation as a fashionable trend and addresses the “dynamic interplay between users and providers of management ideas” [20] (p. 825). Managerial fashions are transitory collective beliefs that may be explained through the combination of several approaches: the rational approach, which attributes the existence of management fashions to the competitive environment in which executives operate, their need for forecasts, and to organizations in search of new ideas; the dynamic nature of management, which motivates executives to adopt managerial fads; and the institutional approach, which views the adoption of management trends as imitation that organizational decision makers undertake because they operate in uncertainties and under workloads [57]. New fashions evolve from preceding trends, thus minimizing organizational uncertainty. Fashions appear independently, but the impact they make merges them into singular trends. The literature distinguishes between fashion and fad, viewing them as based on two social processes with different implications. A fad is defined as collective behavior that emerges out of combinations between several powers such as actors’ reciprocal imitation, weakening institutional constraints, and the distribution of languages identified with the uniqueness of fashion. Fashion, by contrast, is defined as a product of supply and demand ratios on a market of knowledge [58]. Second is the cultural perspective [20] (p. 825), which examines ways in which the organizational culture shapes innovation when observed from inside the organization. According to this perspective, it is impossible to change prevailing organizational situations, which explains why innovation–management processes make no actual changes but merely strengthen existing situations. The third perspective is the rational one [20] (p. 825). It focuses on the actions of individual key actors in the innovation–implementation processes. According to this approach, individuals promote and implement innovative solutions for specific issues that challenge their organizations [20]. Last is the institutional perspective [20] (p. 826), a dominant vein of research in Sociology and Organizational Studies [59,60]. While Section 2.2.1 provided a broader overview of institutional theory as it relates to the emergence, diffusion, and legitimation of innovation across organizational fields, Birkinshaw et al. (2008) [20] adopted a more focused application. They applied the institutional perspective to examine how organizational conditions—particularly external legitimacy pressures and mimetic isomorphism, the tendency of organizations to imitate others perceived as successful—shape the creation, adoption, and institutionalization of new management practices. This approach extends the broader institutional insights presented in the Section 2.2.1. Institutional Perspective by highlighting the specific mechanisms through which management innovation itself becomes institutionalized within organizations.
The study of innovation management is a stream within innovation theory [47]. It has evolved to address issues such as the complexity of innovation, the factors that motivate it, and the strategies decision makers employ to enhance organizational performance. Researchers in this field examine topics including innovation success, the diversity of innovation forms, and the contextual complexities that shape innovation processes. However, recent literature has paid less attention to internal organizational dynamics and social processes that influence innovation [47].
While managerial and organizational studies offer insights into the context in which innovation occurs, sociological perspectives focus on how innovation emerges through organizational and social arrangements—or how it reinforces those arrangements [61]. More research is needed on how internal dynamics, such as institutional context, practice adoption, and organizational identities, shape innovation. Here, institutional theory serves as one of the key frameworks for examining innovation [47].
Innovation management refers to the development and application of new managerial practices, processes, or structures aimed at advancing future organizational goals [20]. This can be studied in two levels. At the abstract level, the focus is on new managerial ideas and knowledge bodies. At the operational level, the focus is on the actual application of processes, roles, intra-organizational routines [20], tools of knowledge management, and relations with academia [2].
This growing emphasis on innovation–management capabilities reflects various drivers: customers’ expectations, training programs, and the role of consultants, managers, and policymakers. This institutionalization of innovation management is formalized in the ISO 56002 standard [62], which defines an innovation–management system as: “a set of interrelated and interacting elements, aiming for the realization of value. It provides a common framework to develop and deploy innovation capabilities, evaluate performance, and achieve intended outcomes” [62]. Despite this progress, evaluating and measuring innovation remains a major challenge for organizations [63,64].

2.3. Innovation and Complexity

The process perspective (Section 2.2.2) highlights the nonlinear and complex nature of innovation, which is shaped by temporal, relational, and cultural complexities [8]. These complexities intersect with institutional pressures, creating dynamic tensions that influence how innovation unfolds over time.
Facilitating innovation within institutionalized fields—defined earlier as a structured arena where organizations share common practices, organizational forms, and institutional logics—is inherently challenging. In such contexts, the drive for innovation often clashes with prevailing norms and expectations, leading to a persistent tension between exploration and exploitation, as conceptualized by March (1991) [32].
“Exploration” refers to activities such as search, experimentation, and novelty. In contrast, “exploitation” emphasizes efficiency, stability, and the refinement of existing competencies. This duality reflects a deeper institutional paradox: innovation is simultaneously enabled and constrained by institutional forces. On the one hand, institutions provide the structures, norms, and legitimacy needed to support innovation; on the other hand, these same forces can entrench stability and conformity, thereby limiting the scope for radical or unconventional change [13,60].
This paradox echoes debates in institutional theory, particularly around institutional logics, where multiple, sometimes conflicting belief systems shape what is considered rational or legitimate innovation [47,50].
Organizations that attempt to manage these contradictory demands are often described as “ambidextrous” [65] (p. 671). Building on March’s (1991) [32] exploration–exploitation framework, O’Reilly and Tushman (2013) [33] argued that organizational ambidexterity—the capacity to simultaneously pursue incremental improvements and radical innovation—is essential for long-term adaptability in dynamic environments. Their work highlights the importance of both structural and leadership capabilities in managing the tensions inherent in innovation processes.
From a sociological perspective, this paradox is even more pronounced. Institutionalization can normalize innovation to the point where it becomes a routine expectation, yet this very routinization can strip innovation of its transformative potential. DiMaggio and Powell (1983) [60], drawing on Weber’s (1958) [66] metaphor of the “iron cage,” argued that bureaucratization and isomorphic pressures often lead to organizational uniformity, thereby reducing opportunities for genuine novelty.
Drori (2018) [67] demonstrated this institutional constraint in the context of universities—setting typically celebrated as hubs of creativity. She showed how professionalization and managerial logics may paradoxically limit creative expression. Similarly, Kupp et al. (2017) [68] argued that routinized innovation practices risk converting creativity into a standardized, imitable performance. Miron-Spektor and Erez (2011) [69] went even further, noting that organizations may reject the most novel ideas when these conflict with dominant logics or existing structures.
In summary, facilitating innovation is deeply entangled in institutional paradoxes that both support and constrain creativity. These paradoxes are not peripheral; they are central to understanding the ambiguous character of innovation. Recognizing this duality—between institutional stability and the pursuit of novelty—helps explain why innovation continues to be a powerful yet elusive goal in contemporary organizational life.
The clash between the forces that promote change and those that preserve stability is analytically valuable. It provides a lens through which researchers can observe and assess shifts in collective understanding and action within institutional fields [70]. Understanding the conditions that shape institutional environments is, therefore, critical, as these can either hinder or enable the emergence and adoption of innovative ideas and practices [70].

3. Ambiguity and Clarity: A Configurational View

A configurational lens allows us to understand innovation not as a singular concept, but as a composite of institutional meanings, organizational forms, and strategic practices.
This perspective enables researchers and practitioners to navigate the tension between ambiguity and clarity in a productive manner.
For example, in a tech startup, innovation might be shaped by a configuration of entrepreneurial logic, agile workflows, and a disruption narrative. In contrast, in a public health organization, it may be embedded within bureaucratic procedures, compliance norms, and evidence-based policy constraints.
Splitter et al. (2023) [31] further advanced a configurational understanding of organizational phenomena by conceptualizing openness as an organizing principle that reconfigures institutional logics, field-level practices, and strategic orientations—paralleling the configurational view of innovation developed here. Their framework highlights that openness, much like innovation, does not emerge from isolated variables but from interdependent configurations shaped by institutional contexts.
As argued throughout this entry, innovation resists simple categorization. It encompasses a wide array of meanings, logics, and practices, making it inherently ambiguous. Rather than resolving this ambiguity, a configurational view embraces it as a central characteristic. Drawing on organizational theory [28], this perspective suggests that innovation emerges not from isolated causes, but through the interaction of multiple institutional, organizational, and strategic elements that form distinct configurations.
This aligns with the configurational style of theorizing described by Furnari et al. (2021) [29], which emphasizes how interdependent constructs combine to form meaningful, context-specific explanations. Rather than relying on linear causal models, this approach allows scholars ‘complexify’ innovation by examining conceptual clusters and underlying mechanisms.
Figure 1 illustrates how types of innovation emerge through distinct configurations of meaning, organizational structure, and institutional environment. Ambiguity arises where meanings are multiple, institutions are contested, and structures are fluid or emergent. Clarity, by contrast, emerges when meanings stabilize, structures formalize, and institutional logics align.

Variation Across Innovation Types

Innovation does not operate under conditions of absolute clarity or total ambiguity, but rather through a dynamic tension between the two. This productive tension is a key feature across innovation processes and typologies.
March (1991) [32] framed this as a contrast between exploration and exploitation, arguing that ambiguity is essential for reframing goals and experimenting with novel possibilities, while clarity is needed to anchor those possibilities into actionable, efficient practices [32].
Building on this, Smith and Lewis (2011) [13] described innovation as a paradoxical process, where success often depends on embracing, rather than resolving, competing logics—such as creativity vs. structure, novelty vs. continuity, and ambiguity vs. clarity. They advocated for a dynamic equilibrium that allows organizations to navigate rather than suppress these tensions [13].
Garud et al. (2013) [8] similarly argued that ambiguity is not a flaw, but a necessary condition of innovation. Especially in complex and uncertain environments, innovation unfolds through interpretive flexibility and emergent meaning-making.
This entry builds on these insights by suggesting that the ratio of ambiguity to clarity is not fixed, but varies across types of innovation and organizational contexts. Technological innovations often begin with high ambiguity (e.g., R&D uncertainty), and evolve toward greater clarity as prototypes stabilize and commercialization proceeds [32,71]. Social innovations, such as new community practices or policy interventions, typically remain ambiguous longer, due to contested meanings, stakeholder conflicts, and the interpretive flexibility required across institutional settings [72,73]. Cultural innovations [17], including shifts in norms, art, or education, often thrive on sustained ambiguity, where meanings are constantly negotiated and institutionalization may be partial or resisted. Here, ambiguity is not a weakness but a resource for engagement, reinterpretation, and symbolic differentiation. Managerial innovations (e.g., new work routines or organizational forms) often require deliberate toggling between ambiguity (for ideation) and clarity (for implementation and legitimacy) [20,57].
In this sense, ambiguity and clarity are not opposites, but co- constitutive elements of innovation. As Splitter et al. (2023) [31] showed in their work on openness, clarity is not achieved by eliminating ambiguity, but by translating complexity into context-specific coherence.
Configurations vary across organizational fields, reflecting different combinations of institutional logics, organizational routines, and strategic narratives. This view enables us to reframe ambiguity not as an analytical weakness, but as a signal of underlying complexity and the coexistence of multiple institutional logics within a single field or organization. Clarity, in this light, is the ability to map and communicate the elements that shape innovation in a specific context.
Ultimately, researchers and practitioners benefit from recognizing that innovation is not a fixed object or linear process, but a composite of interdependent meanings, structures, and practices. Configurational analysis supports this understanding by showing how different forms of innovation cohere—or fail to—within institutional arrangements.
To further illustrate the dynamics presented in Figure 1, Table 1 synthesizes how different innovation types are embedded in distinct combinations of institutional, organizational, and meaning configurations. These configurations shape the degree to which ambiguity and clarity coexist in various innovation contexts.
As illustrated in Table 1, and building on the typology by Cohendet and Simon (2017) [11], the first two configurations—Linear & Closed and Interactive & Closed—operate within well-defined institutional environments and formal organizational structures. Innovation here is driven primarily by internal capabilities and stepwise processes, aligning with stabilized meanings and coherent, efficiency-oriented institutional logics [20,47,58].
By contrast, Social and Cultural Innovations lie at the other end of the spectrum. These forms of innovation emerge within contested or pluralistic institutional environments and are often enacted by loosely structured or hybrid organizations, such as nonprofits or informal collectives [8,20,67]. In these contexts, meanings are fluid and continually negotiated, contributing to sustained ambiguity. Innovation is less about technical problem-solving and more about interpretive flexibility, symbolic reframing, and value creation [8,22].
Technological Innovation occupies a transitional position. While it often begins in states of high uncertainty—especially during the exploration and early R&D phases—it tends toward clarity as processes move toward standardization, regulatory oversight, and commercialization. This progression reflects a movement from interpretive flexibility to institutional and organizational alignment, particularly within pipeline models or open R&D frameworks in science-based sectors [7,47,62].
Similarly, Managerial and Interactive & Open Innovation types represent hybrid forms along the ambiguity–clarity spectrum. Managerial innovation, for example, often begins with experimentation and interpretive flexibility, requiring ambiguity to support novel routines and structures. However, it must eventually become routinized and formalized to gain legitimacy and widespread adoption in organizational contexts [20,62].
Interactive & Open Innovation is characterized by the coexistence of multiple actors—including public institutions, private firms, and academic organizations—that collaboratively engage in innovation processes across organizational boundaries. Rather than relying solely on internal capabilities, this model emphasizes internal and external actor networks, where knowledge is shared, recombined, and jointly developed through partnerships, platforms, and boundary-spanning arrangements [11,37,38]. Innovation here is not produced in isolation but is the outcome of cocreation across sectors and institutions, requiring mutual adaptation and negotiation of meaning. The presence of diverse institutional logics and goals can introduce ambiguity, yet repeated collaboration and interaction often lead to the emergence of shared practices, stable roles, and partially aligned expectations. This dynamic process reflects the essence of open innovation ecosystems, where innovation unfolds as a relational and configurational achievement rather than a linear or isolated effort
Innovations in stable environments with formal structures tend to show greater clarity (e.g., technological innovation), while those involving contested meanings and loosely structured actors (e.g., cultural or social innovation) reflect sustained ambiguity. Certain types (e.g., managerial or interactive-open) represent hybrid forms along this spectrum.

4. Conclusions

This entry has argued that innovation is not merely a technical or managerial process, but a deeply embedded, institutionally contingent, and socially constructed phenomenon. Through a review of its conceptual foundations, evolving typologies, and key theoretical perspectives—including institutional, processual, and configurational lenses—it becomes clear that innovation functions as a normative ideal and a conceptual puzzle.
The inherent ambiguity of innovation is not a limitation, but a feature that reflects its multiplicity of meanings, applications, and organizational forms. A configurational perspective reveals that innovation emerge through distinct, context-dependent combinations of institutional logics, organizational structures, and meaning configurations. This view not only enriches our theoretical understanding but also supports more reflective and situated approaches to innovation in practice.
This configurational lens is concretely illustrated in Table 1, which maps how different types of innovation—technological, social, cultural, managerial—are shaped by distinct institutional environments, organizational forms, and meaning systems. These contextual dimensions influence how ambiguity and clarity coexist and vary across innovation types. Rather than treating ambiguity as a problem to be solved, this perspective reveals it as a condition that emerges differently depending on the configuration in question—structured and efficiency-oriented in some cases, interpretive and contested in others.
Clarifying innovation does not mean arriving at a single, universal definition. Instead, it involves understanding the conditions under which different configurations of innovation emerge, stabilize, and diffuse. Just as innovation unfolds through varying degrees of ambiguity and clarity, its institutionalization demands a reflexive research approach—one that recognizes ambiguity not as noise to be eliminated, but as a constitutive element of how innovation gains meaning, legitimacy, and permanence.
For scholars and practitioners alike, this calls for attentiveness to the tensions, complexities, and paradoxes that shape innovation as both a process and a symbol of transformation.

5. Limitations and Prospects for Future Research

This entry is primarily conceptual in scope and seeks to synthesize and extend existing innovation typologies through a configurational lens. While the framework is informed by empirical findings from the author’s dissertation research, it does not present empirical data, as the goal is to articulate the theoretical architecture of the approach.
The literature review focuses deliberately on foundational and midstream contributions that have shaped institutional and configurational understandings of innovation. As a result, more recent empirical or applied studies—particularly those outside the institutional tradition—may be underrepresented. This selectivity is not a methodological limitation, but a reflection of the entry’s encyclopedic and conceptual aim: to synthesize key theoretical developments and contribute to institutional theory by clarifying how innovation is configured and contested across organizational fields.
Future research may explore how the configurational interplay presented in this entry varies across institutional and sectoral contexts, or how it unfolds over time within innovation processes—particularly in response to shifting organizational structures, institutional logics, and interpretive frames.
Innovation remains a complex organizational phenomenon and constitutes a dynamically evolving field, increasingly shaped by emerging technologies such as artificial intelligence (AI). AI not only introduces new modes of automation and knowledge generation, but also reshapes the boundaries of institutional decision making, introduces new forms of ambiguity, and redefines normative expectations around innovation.
Accordingly, future research may revisit and refine the configurations proposed here to better account for the accelerating complexity and fluidity of innovation ecosystems in the digital and post-digital era.

Funding

This entry is the outcome of my dissertation research, which was supported by a Ph.D. scholarship from the Department of Sociology and Anthropology, Faculty of Social Sciences, The Hebrew University of Jerusalem. No grant numbers apply.

Conflicts of Interest

The author declares no conflicts of interest.

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Figure 1. Innovation Configurations: Navigating Ambiguity and Clarity.
Figure 1. Innovation Configurations: Navigating Ambiguity and Clarity.
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Table 1. Configurations of Innovation Across Typologies: Institutional, Organizational, and Meaning Dimensions.
Table 1. Configurations of Innovation Across Typologies: Institutional, Organizational, and Meaning Dimensions.
TypologyMeaning ConfigurationOrganizational StructureInstitutional Environment
Linear & ClosedInnovation as step-by-step delivery of technical solutions Sequential, internal process Stable, efficiency-oriented institutions
Interactive & ClosedInnovation as internal recombination of knowledgeInfrastructure for collaboration and knowledge sharingRelatively closed field emphasizing internal capacity
Interactive and open Innovation as co-creation across boundaries Internal and external actors networksCo-existence of multiple actors (public, private, academia)
Social InnovationInnovation as a social construction of public valueOften hybrid (e.g., partnerships, nonprofits)Multiple, contested logics
Cultural InnovationInnovation as symbolic transformation; reframing values and shared meaningLoosely structured collectives or individualsNormative, discursive environments
Technological InnovationInnovation as technical solutions to defined needs Often pipeline-based, but can involve open R&DRegulated by scientific or commercial standards
Managerial InnovationInnovation as restructuring work practices and new routinesExperimental then routinizedDriven by consultancy models or professional norms
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