innovation management literature review

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Innovation management systems and standards: a systematic literature review and guidance for future research.

1. Introduction

2. methodology: article selection.

• As a first step, “Innovation Management” was searched as a keyword in the title, as is consistent with the current literature [ 9 , 12 , 13 , 14 ]; after combining the results from databases, 7476 outcomes were found.
• They should be peer-review published papers.
• The papers should be written in English.
• The publication dates should range from 2006 to 2020; 2006 is the year in which Spanish UNE 166002: 2006 standard was issued by the Spanish Association for Standardization and Certification, which was a major improvement in innovation management systems and standards. These characteristics excluded papers that may have had less scientific rigor, such as monographs, book chapters and other non-refereed journals.
• In the third step, the sample was reduced to 431 titles after removing duplicates from the article list.
• The fourth step, after having collected all of the results using reference management software, was to review all of the titles and abstracts in order to determine whether the basic relevance criteria were met [ 14 , 15 ], and then we excluded those beyond our context [ 12 , 16 , 17 ], i.e., articles not concerned with innovation management systems or standards were deemed irrelevant. As a result, 68 studies were accepted [ 18 ].
• Finally, we manually resumed the search and tracked citations [ 14 , 16 , 19 ], which resulted in the addition of five more articles. In the end, samples of 73 publications were collected. Table 1 shows the above-mentioned steps, and Appendix A shows a list of the relevant papers.

3. Descriptive Results: Analysis

3.1. analysis of the article years, type, effect and recurrence, 3.2. analysis of the countries of origin, 4. comprehensive review of ims/st, 4.1. group a: theoretical studies, 4.2. group b: experimental qualitative studies, 4.3. group c: experimental quantitative studies, 5. discussion.

• IMS/St needs to be studied in relation to the added values which have been mentioned for each of the new models above, in order to validate whether IMS/St (specially ISO 56000) covers each of them, and if not, to find the needed improvements for IMS/St to fulfill the needs of companies for these added values. The conformity of IMS/St with various sectors of services and industry could also be a very interesting topic for further investigation.
• Various management standards (environmental management standards, sustainability management standards, social responsibility management standards, quality management standards, etc.) have been adopted in companies. The method of the adoption of IMS/St needs to be clearly studied in order to make the adoption process successful, and to reduce opportunities for conflict between these management standards and IMS/St.
• More standard analysis of the present IMSts is still needed.
• A comparative study on IMS/St standards is still needed in order to find the strengths and weaknesses of each of them (although one paper [ 26 ] considered here did address this issue). This provides a good opportunity to develop IMS/St standards.
• The impact of IMS/St on each type of innovation still needs more research in order to give better understanding of it.
• The impact of IMS/St on innovation performance should be tested and evaluated in different sectors.
• The connection between IMS/St and value creation should be investigated.
• The impact of IMS/St on the performance of companies in detail and overall, also deserves more attention, as the impact of IMS/St is linked to the readiness of companies to invest real money in the implementation of IMS/St.

6. Conclusions

Author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Idris, M.-C.; Durmuşoğlu, A. Innovation Management Systems and Standards: A Systematic Literature Review and Guidance for Future Research. Sustainability 2021 , 13 , 8151. https://doi.org/10.3390/su13158151

Idris M-C, Durmuşoğlu A. Innovation Management Systems and Standards: A Systematic Literature Review and Guidance for Future Research. Sustainability . 2021; 13(15):8151. https://doi.org/10.3390/su13158151

Idris, M-Chukri, and Alptekin Durmuşoğlu. 2021. "Innovation Management Systems and Standards: A Systematic Literature Review and Guidance for Future Research" Sustainability 13, no. 15: 8151. https://doi.org/10.3390/su13158151

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European Journal of Innovation Management

ISSN : 1460-1060

Article publication date: 10 June 2020

Issue publication date: 27 May 2021

Innovation is considered an important stage in the process of competitiveness of companies. While there is an extensive literature in the management and innovation field that shows the characteristics that enhance a firm's ability to innovate, there is still no consensus on its determinants and nature. This study aims to advance the understanding of innovation capability (IC) by conducting a systematic review of relevant literature at the firm level.

Design/methodology/approach

The study reviews the literature by applying the categorization and contextualization of qualitative strategies. The study gathered 137 peer-reviewed papers from Scopus and Web of Science databases.

The papers were analysed and synthesized into an integrated framework that links IC with its internal and external determinants, and its consequences. In doing this, this study proposes directions for future investigations that might enlighten a better understanding of IC.

Practical implications

The study provides elements that can be useful during the design and implementation of innovative initiatives in a firm.

Originality/value

The paper jointly examines in the same model the nature, antecedents and consequences of IC. In the same vein, the framework provides the little-researched links between those themes in the IC literature.

• Consequences
• Determinants
• Innovation capability
• Literature review

Acknowledgements

The author would like to thank the anonymous reviewers for their valuable comments and suggestions.

Mendoza-Silva, A. (2021), "Innovation capability: a systematic literature review", European Journal of Innovation Management , Vol. 24 No. 3, pp. 707-734. https://doi.org/10.1108/EJIM-09-2019-0263

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The Front End of Innovation in Defense: A Comprehensive Literature Review

Submitted: 18 January 2024 Reviewed: 02 March 2024 Published: 30 April 2024

DOI: 10.5772/intechopen.1005191

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Innovation management, a multifaceted organizational process encompassing opportunities and ideas from inception to implementation, demands a systematic approach, particularly in the critical initial phase known as the Front End of Innovation (FEI). This pivotal phase significantly influences the entire innovation management chain. Despite its recognized importance, FEI in the defense sector has yet to be systematically addressed in the academic literature. Recognizing the vital role of FEI in the defense sector, this study addresses this deficiency through a systematic review, scrutinizing 24 documents from the scientific literature (Scopus and Web of Science databases) and gray literature (government defense documents). This research systematically maps key activities identified in seminal FEI models. These activities include the identification and analysis of opportunities; generation, enrichment, and screening of ideas; product concept definition; and consideration of influencing factors. Concurrently, this work aligns defense practices with established innovation models and provides valuable insights for optimizing the management dynamics of the military innovation process. Through this systematic inquiry, this study contributes to a nuanced understanding of the FEI in the defense sector, offering practical implications for enhancing defense innovation development.

• front end of innovation
• literature review

Author Information

Romullo girardi *.

• Military Institute of Engineering, Rio de Janeiro, Brazil
• INESC TEC and Faculty of Engineering, University of Porto, Porto, Portugal

Juraci Ferreira Galdino

Paulo césar pellanda.

*Address all correspondence to: [email protected]

1. Introduction

Innovation management, a complex and broad organizational process covering the entire spectrum, from identifying new opportunities and ideas to their practical implementation, poses significant challenges for managers across all organizational levels [ 1 ].

Notably, innovation seldom fails due to a lack of creativity; instead, it is the absence of discipline that plays a pivotal role in innovation failures [ 2 ]. From this perspective, Boeddrich [ 3 ] contends that systematic and structured procedures in the early phase, known as the Front End of Innovation (FEI), are imperative to avert adverse effects throughout the innovation management chain.

Multiple researchers emphasize that enhancing FEI activities contributes positively to organizational outcomes, bolstering the likelihood of successful innovation development [ 3 , 4 , 5 , 6 , 7 , 8 , 9 ]. Yet, the successful adoption of a FEI model requires considering some factors like organizational size and culture, as well as decision-making styles [ 10 , 11 ].

Despite the increasing attention to FEI as a complex and multidisciplinary field [ 12 ], the defense context of FEI has not been sufficiently addressed in the academic literature, a gap this study endeavors to address. Therefore, this research aims to unravel the dynamics of FEI in the military sector through a systematic literature review, focusing on the research question: How can the current literature on the early phase of the innovation process in defense be mapped within seminal FEI models?

This question is pertinent given the Armed Forces’ distinct organizational culture, demanding innovation to sustain high-tech operational capabilities and mainly requiring innovations capable of inducing technological surprise in the theater of operations. Aligning defense practices with established models in innovation literature can furnish invaluable insights for improving the management dynamics of the military’s initial innovation phase. Moreover, by reviewing approaches used by different countries, the study recognizes that the suitability and significance of FEI management practices can differ across national defense contexts. It emphasizes how cultural and procedural nuances impact the development and adoption of new technologies in military settings.

Structured around the research question, this paper is organized as follows: Section 2 provides a theoretical foundation on FEI, seminal FEI models, and defense peculiarities. Section 3 outlines the research methodology. Section 4 delineates the mapping of the FEI in the defense sector within seminal FEI models. Section 5 discusses salient aspects identified throughout the study. Finally, Section 6 highlights the concluding remarks, outlining directions for future research.

2. Theoretical foundation

Before exploring the current literature on the early stage of the innovation process in defense, it is essential to understand the foundational topics involved: the FEI concept, the seminal FEI models, and the unique aspects of the military sector.

2.1 Front end of innovation (FEI)

The Fuzzy Front End (FFE) refers to the earliest stage in the New Product Development (NPD) process. This term was popularized by Smith and Reinertsen [ 13 ], as pointed out by Khurana and Rosenthal [ 10 ].

In 2002, Koen et al. [ 14 ] proposed the term Front End of Innovation (FEI), considering that the adjective “fuzzy” is “mysterious, lacks accountability, and cannot be critically evaluated” ([ 14 ], p. 30). The new term dissociated the idea that the initial phase of the innovation process was nebulous and uncontrollable. In this approach, the FEI is described as “those activities that come before the formal and well-structured NPD process” ([ 14 ], p. 30).

Figure 1 illustrates the breakdown of the product innovation management process into three phases: FEI, NPD, and implementation (the commercialization of the product in the market). The circular shape of the FEI suggests that ideas should flow and iterate until the formal definition of products is developed. In contrast, the NPD phase is depicted as a series of sequential, well-structured, and chronologically ordered steps [ 14 , 15 ].

Breakdown of the product innovation management process. Source: Adapted from Koen et al. [ 14 , 15 ].

The FEI emerges as a crucial driver of positive outcomes for new products and, consequently, the overall success of the business [ 16 ]. Markham [ 6 ] underscores the profound impact of early-phase activities on product performance, emphasizing that the success of the front end stands as the strongest independent predictor of all NPD performance variables.

Selecting an appropriate FEI model requires careful consideration of various factors, including organizational size and culture, as well as decision-making style [ 10 , 11 ]. As a response to these diverse organizational needs, numerous FEI models have been developed over time, offering distinct approaches to navigate their complexities, as detailed in the next section.

2.2 Seminal FEI models

In an integrative literature review, Pereira et al. [ 12 ] found that 26% of articles related to FEI contributed in terms of frameworks, models, processes, tools, and methodologies, exemplifying endeavors to structure the early phase of the innovation process in specific contexts.

While recent contributions are significant, seminal works have produced models that served as reference points for structuring the FEI. Table 1 provides an overview of the four seminal models identified by Pereira et al. [ 12 , 20 ].

Seminal FEI models.

Source: Adapted from Pereira et al. [ 12 , 20 ].

Stage 0 (Discovery) : In this inaugural stage, the organization actively generates ideas for new products.

Gate 1 (Idea screen) : Ideas undergo a concise evaluation based on strategic, feasibility, and market criteria. Financial considerations are deferred at this point. Accepted ideas proceed to the next phase.

Stage 1 (Scoping) : The accepted idea transitions into a project, initiating a dual evaluation process:

Market evaluation : Involves research, user contact, and conceptual testing to determine market size and acceptance.

Technical evaluation : Encompasses feasibility, costs, and development timelines.

Gate 2 (Second screen) : Comprehensive information from market and technical evaluations prompts a reassessment of the project’s viability. If approved, the project advances to the next stage.

Stage 2 (Build business case) : Positioned just before product development, this stage involves:

Assessing the project’s attractiveness.

Defining clear objectives.

Conducting market, technical, operational, and financial evaluations.

Gate 3 (Development) : A pivotal decision point where the organization determines resource allocation for project development [ 17 , 18 ].

The FEI within the stage-gate model. Source: Adapted from Cooper [ 17 ].

Pre-Phase Zero : This initial phase concentrates on the continuous identification of opportunities within the organization. It involves generating ideas and conducting technological and market analyzes. When a promising opportunity is identified, it triggers the transition to Phase Zero. The authors emphasize that this phase should occur continuously within the organization.

Phase Zero : This phase is initiated when Pre-Phase Zero identifies a promising opportunity. Its primary objective is to define the concept of a new product.

Phase One : Following the conceptualization of the new product, Phase One focuses on analyzing feasibility and planning the project to initiate the NPD process formally. It is crucial to maintain a constant interface with the organization’s product and portfolio strategy throughout the entire process.

Three Phase Front End model. Source: Khurana and Rosenthal [ 11 ].

The New Concept Development (NCD) model, proposed by Koen et al. [ 14 , 15 ], is a theoretical construction composed of the three fundamental concepts: controllable activities, “engine” and influencing factors. Controllable activities represent the elements that the organization can control. The “engine” encompasses the controllable aspects of the organization that are responsible for driving the activities of the FEI. Finally, the influencing factors are variables that have an impact on the FEI and are relatively outside of the organization’s control [ 14 , 15 ]. Table 2 details the structure of the NCD model. In the structure of the NCD model, organizational capabilities are classified as an influencing factor because they usually change very slowly and are therefore uncontrollable. Alternatively, organizational capabilities can be incorporated into the “engine” to the extent that the organization can modify and control them [ 14 ].

Structure of the NCD model.

Source: Koen et al. [ 14 ].

The model proposed by Reid and De Brentani [ 19 ] provides a unique focus on disruptive innovations, highlighting their distinct entry into the organization compared to incremental innovations. According to this model, disruptive innovations typically originate from the external environment. Figure 4 illustrates how the front end of the innovation process initiates its flow based on information from the external environment, involving the identification of unstructured problems and the recognition of opportunities. This model emphasizes that disruptive innovations follow a distinctive path, with the FEI process being strongly influenced by external inputs. The opportunities identified undergo thorough analyzes and decisions at various organizational levels before being formally integrated into an NPD project [ 19 ].

The Fuzzy Front End of new product development for discontinuous innovations. Source: Reid and De Brentani [ 19 ].

The seminal models presented – Cooper’s Stage-Gate Model, Khurana, and Rosenthal’s Three Phase Front End Model, Koen et al.’s New Concept Development (NCD) Model, and Reid and De Brentani’s Model for Discontinuous Innovations – vary in focus, approach, depth, and structuring of activities. Despite these differences, a common thread emerges as they collectively address the FEI through key activities: identification and analysis of opportunities, generation, enrichment, and screening of ideas, product concept definition, and consideration of influencing factors (encompassing the outside world, market and technology information, scenario planning, competitive analysis, and organizational issues such as culture, leadership, strategy, portfolio, and capabilities).

The ultimate objective of these FEI activities is to formulate a well-defined product concept before entering the formal NPD stage. Table 3 establishes the correspondence between FEI activities and the structures of the seminal models.

FEI activities and their relationship with the seminal models.

To mitigate potential ambiguities in the interpretation of certain terms related to the FEI, Table 4 provides standardized reference definitions. This table serves as a reference guide, providing clear and standardized definitions for key terms associated with the FEI, enhancing clarity and consistency in their interpretation.

Definitions for terms related to the FEI.

2.3 Defense sector

High technological level : The defense industry requires substantial investments in research, development, and innovation to create sophisticated products such as aircraft, ships, weapons, and systems. These must operate safely and reliably under severe conditions [ 25 ], often characterized as Complex Products and Systems (CoPS). CoPS involve customization, production in small quantities by a few companies, integration of diverse knowledge areas, and a lifecycle spanning decades [ 26 ].

Technological duality : Innovations developed for military purposes may have civilian applications (spin-off) and vice versa (spin-in) [ 27 , 28 ]. Dual-use technologies, like GPS and the Internet, initially developed for defense, now find widespread civilian applications.

Governmental dependence : The defense market is highly regulated and relies on government contracts, resulting in a strong dependence on public resources. From a demand perspective, the defense market operates as a monopsony, with the State being the primary purchaser of goods and services [ 29 , 30 , 31 ].

High market concentration : Global defense market dominance by a few companies leads to limited competition and protectionist practices. Oligopolies in the defense market can collude, manipulate prices, limit competition, or engage in practices like dumping [ 32 ] to control strategic interests [ 31 , 33 ].

Vulnerability to geopolitical issues : The demand for defense equipment is influenced by geopolitical conflicts and international relations, resulting in a volatile market subject to sudden changes. Companies may exploit geopolitical issues for financial or strategic reasons, impacting commitments during times of national crisis [ 31 , 34 ].

In summary, the defense sector is characterized by its strategic importance, technological advancement, dual-use nature, governmental dependence, market concentration, and vulnerability to geopolitical issues. This situation is a combination of a monopoly/oligopoly, where a few major global players dominate the supply, and a monopsony, where the State centralizes the demand. Recognizing these peculiarities highlights the need for a comprehensive exploration of FEI dynamics within the defense sector.

3. Methodology

Databases : Scopus and Web of Science (WoS), aligning with the methodology outlined by Ferreira et al. [ 36 ].

Search string : The search string was crafted by combining key terms related to the FEI and the defense sector. The FEI-related terms were derived from a frequency analysis of authors’ keywords, following the methodology of Ferreira et al. [ 36 ]. To capture the comprehensive scope of the defense sector, terms related to aerospace were also incorporated, acknowledging that certain countries treat both topics as a unified strategic theme. For instance, the United States has the U.S. Space Force under its Department of Defense [ 37 ]. The search was conducted on September 21, 2023, focusing on terms found in the title, abstract, and keywords:

Scopus database: TITLE-ABS-KEY((“front end of innovation” OR “front-end of innovation” OR “front end innovation” OR “front-end innovation” OR “fuzzy front end” OR “fuzzy front-end”) AND (“military” OR “defense” OR “defense” OR “navy” OR “army” OR “air force” OR “aerospace” OR “aeronautic*” OR “astronautic*” OR “avionics”)).

WoS database: TS = ((“front end of innovation” OR “front-end of innovation” OR “front end innovation” OR “front-end innovation” OR “fuzzy front end” OR “fuzzy front-end”) AND (“military” OR “defense” OR “defense” OR “navy” OR “army” OR “air force” OR “aerospace” OR “aeronautic*” OR “astronautic*” OR “avionics”)).

Inclusion criteria : publications in English, Portuguese, or Spanish were considered, and the accessibility of the entire document was taken into account. Additionally, the publication had to address explicitly the FEI in the defense context.

The academic literature search yielded five documents from the Scopus database and two from WoS. Upon analysis, one redundancy was identified, resulting in six unique documents. Subsequently, it was observed that two articles did not meet the inclusion criteria, leaving four documents within the review scope. Following this initial search, the snowball technique was applied to identify relevant documents citing or cited by the selected publications. Additional efforts were made to explore works authored by the selected publications’ authors, uncovering three more documents.

In parallel with the academic literature search, the exploration of government defense management agencies’ websites led to the identification of 17 more documents. Therefore, while the academic literature contributed documents presenting general aspects of FEI in the defense sector, the gray literature addressed defense management in specific nations, ensuring representation across continents and encompassing both developed and developing countries. The nations (or alliances) covered included Australia, Brazil, China, India, NATO (North Atlantic Treaty Organization), the United Kingdom, the United States, and South Africa.

Thus, a total of 24 documents were selected for review. It is noteworthy that, during the research, no review works similar to this article were found. The steps of the review are represented in summary in Figure 5 , using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) diagram, a tool for presenting the flow of information through the different phases of a systematic literature review [ 38 ].

Stages of the systematic literature review. Source: Adapted from Page et al. [ 38 ].

4. Front end of innovation in the defense sector

The investigation of FEI in the defense sector is structured based on content mapping of the selected review documents, focusing on key FEI activities outlined in Section 2.2. These activities include the identification and analysis of opportunities; generation, enrichment, and screening of ideas; product concept definition; and consideration of influencing factors.

4.1 Identification and analysis of opportunities

The identification and analysis of opportunities serve as the primary catalyst for the FEI process. It occurs when an organization recognizes a gap, whether related to business or technology issues. This gap represents the difference between the current state and a desired future state, presenting an opportunity that can be exploited to gain a competitive advantage, address a threat, solve a problem, or enhance a situation [ 14 ]. As stressed by Khurana and Rosenthal [ 11 ], the phase of identifying and analyzing opportunities should be an ongoing and continuous process within an organization.

In the defense sector, the identification and analysis of opportunities are intricately tied to Capability-Based Planning (CBP), a central process in strategic defense management [ 39 , 40 ]. This strategic planning paradigm, initially utilized in the United States Nuclear Program during the 1960s, saw broader adoption by the U.S. Department of Defense in 2001, becoming a reference for armed forces worldwide [ 41 ]. From this standpoint, Table 5 provides a mapping of the phase of identification and analysis of opportunities within the documents reviewed.

Approaches to identification and analysis of opportunities within the review documents.

4.2 Generation, enrichment, and screening of ideas

According to Koen et al. [ 14 ], the generation and enrichment of ideas follow the identification and analysis of opportunities. An idea, as conceptualized by the authors, represents the most preliminary form of a new product or service, typically outlining a high-level vision for the planned solution related to the identified opportunity [ 14 ]. Cooper [ 17 ], in the stage-gate model, underscores that ideas for new products must undergo initial screening, known as gate 1, before being integrated into an organization’s project [ 17 ]. Reid and De Brentani [ 19 ] also stress the importance of a formal analysis of opportunities/ideas at the corporate level before progressing to the project level [ 19 ].

In the defense sector, as outlined in Table 6 , the identification of the need for a new product occurs when a capability gap analysis indicates the necessity for a new materiel solution. This triggers the formal process of acquiring a defense product. Table 6 provides a mapping of the phase of generation, enrichment, and screening of ideas within the reviewed documents.

Approaches to idea generation, enrichment, and screening within the review documents.

4.3 Product concept definition

According to Koen et al. [ 14 ], a well-defined product concept should entail a comprehensive configuration, offering both written and visual descriptions that encapsulate the primary features, customer benefits, and a broad understanding of the required technologies. This stage in product development represents the final step preceding the formal NPD process [ 14 ]. The models proposed by Khurana and Rosenthal [ 11 ], Reid and De Brentani [ 19 ], and Cooper [ 17 ] also emphasize the significance of product concept development, feasibility analysis, project planning, and decision-making as crucial prerequisites before formally entering the NPD phase.

In the defense sector, the Armed Forces commonly adopt the systems engineering lifecycle concept to structure their acquisition processes [ 56 ]. Within this framework, the product concept undergoes development through a top-down approach, comprising two distinct phases: logical description (problem domain) and physical description (solution domain). The logical or functional description essentially outlines the intended functionalities of the new product from the user’s perspective, providing an operational view. Building upon the logical description, the physical description then defines the high-level architecture of the product elements, encompassing systems, subsystems, assemblies, and/or components, from a technical perspective [ 57 , 58 , 59 ]. Table 7 provides a mapping of the product concept definition phase within the reviewed documents.

Approaches to product concept definition within the review documents.

4.4 Consideration of influencing factors

According to Koen et al. [ 14 ], influencing factors are variables that impact FEI and are relatively outside the organization’s control. Table 8 maps the influencing factors considered in the review documents.

Influencing factors within the review documents.

5. Discussion

After presenting the review results, it is essential to delve deeper into key findings and considerations identified throughout the study.

5.1 Synthetic diagnosis of the results

Table 9 provides a condensed overview, offering a synthetic diagnosis of the results derived from the review. It succinctly outlines FEI activities in the defense sector and establishes connections with the influencing factors under consideration.

FEI activities in the defense sector.

5.2 Peculiarities of FEI in the defense sector

After systematically mapping the FEI in defense sector against established FEI models, several distinct aspects specific to the military context have emerged, as shown in Table 10 .

Peculiarities of FEI in the defense sector.

5.3 Contributions to the FEI literature

Use of systems engineering approach : The defense sector prominently employs systems engineering activities during the early phase of military innovation. This approach encompasses requirements engineering and systems lifecycle management, aspects not explicitly emphasized in traditional FEI models.

Relevance of technological duality, criticality, and maturity : Concepts such as technological duality, criticality, and maturity play a crucial role in military FEI. These factors, while not extensively covered in established FEI models, are instrumental in decision-making processes, risk mitigation, and the strategic development of defense capabilities.

Organizational capabilities as the “engine” of FEI : In contrast to seminal NPD models that classify organizational capabilities as influencing factors, the defense sector integrates organizational capabilities as a fundamental component of the FEI “engine.” Capability-based planning is a central element in identifying and analyzing opportunities, as well as in generating, enriching, and screening ideas.

“Implementation” of military innovation : The implementation of military innovation necessitates a broader interpretation compared to traditional FEI models. In defense, implementation occurs when a new or improved product is seamlessly integrated into the capability’s portfolio of an Armed Force. This integration involves adjustments in various non-technological aspects, emphasizing the symbiosis between technological and doctrinal advancement.

Continuity in project leadership : Recognizing the high turnover of military leaders and the extended durations of defense projects, the continuity of leadership emerges as a critical consideration. Seminal FEI models do not explicitly address managing leadership continuity in NPD project planning.

Moreover, it is noteworthy that recent contributions in the FEI literature have started to delve deeper into the alignment between organizational strategy and FEI activities. Unlike seminal models that treat this issue generically, recent works, such as the integrative ontologies developed by Pereira et al. [ 20 ] and Castro and Ferreira [ 72 , 73 ], provide management artifacts designed to align organizational strategic vision with FEI activities. Employing the design science paradigm, these artifacts integrate constructs, models, methods, and instantiations, thereby enriching the strategic dimension of FEI literature.

5.4 Contributions to the defense literature

The defense sector, encompassing products ranging from CoPS to mass-produced items, presents a unique challenge due to its diverse complexity and production volume [ 74 ]. While the CoPS research area has an established connection with systems engineering literature, the realm of mass-produced products aligns more closely with the theoretical foundations of the FEI literature. Notably, defense documents predominantly draw from the CoPS approach, sparingly incorporating principles from mass production. However, recognizing that the military context spans both worlds, the integration of these approaches becomes crucial, and mapping established FEI models within the dynamics of the initial phase of the military innovation process serves as a valuable step in achieving this harmonization.

Moreover, the FEI literature, characterized by well-defined seminal models and recent integrative ontologies (as discussed in the previous section), contrasts with the more heterogeneous nature of the systems engineering literature. The latter encompasses diverse authors, countries, organizations, and standardization bodies, each adhering to distinct management models with unique nomenclatures and structures [ 43 , 44 , 45 , 47 , 48 , 54 , 55 , 57 , 58 , 59 ]. In this context, the FEI literature emerges as a unifying force, facilitating the creation of a common representation of knowledge related to the early stage of the military innovation process. This not only streamlines communication among specialists, decision-makers, managers, researchers, entrepreneurs, and other stakeholders in the defense field but also promotes greater efficiency in navigating the diverse landscape of defense innovation.

5.5 Limitations

Selection of seminal FEI models : The identification of seminal FEI models relied on findings from Pereira et al. [ 12 , 20 ] and co-citation analysis of FEI-related works available in the Scopus and WoS databases. Alternative criteria for model selection might yield a different set of seminal documents, potentially influencing the analysis.

Data collection in gray literature : The exploration of gray literature related to FEI in the military sector was constrained by the availability of documents on government websites of defense management agencies. This limitation could result in an incomplete representation of the landscape.

Scope of mapping : The review presented an initial mapping of FEI in the defense sector within seminal models. A more comprehensive and structured mapping could be achieved through the adoption of more robust methodological approaches, such as the design science paradigm [ 75 , 76 ]. This suggests that there is potential for a more in-depth and detailed examination of FEI activities in the defense sector.

Acknowledging these limitations is essential for a nuanced understanding of the scope and implications of the study, guiding future research endeavors in this domain.

6. Conclusion

This study aimed to comprehensively explore the dynamics of FEI in the defense sector through a systematic review encompassing 24 documents from both academic and gray literature. By analyzing seminal FEI models, the research mapped key activities within the defense context, including the identification and analysis of opportunities, generation, enrichment, and screening of ideas, product concept definition, and consideration of influencing factors.

The study’s contributions extend to both FEI and defense literature, introducing original perspectives. Notably, it emphasized the systems engineering approach, national strategic focus, technological duality, technological criticality, technological maturity, organizational capabilities as the “engine”, the unique concept of “implementation” in military innovation, and the importance of continuity in project leadership.

Acknowledging limitations, such as the criteria for selecting seminal FEI models, constraints in accessing gray literature, and the preliminary nature of the mapping, the study calls for future research to employ more robust methodologies, like the design science paradigm [ 75 , 76 ], for an in-depth understanding of the initial phase of the military innovation process.

In conclusion, this research lays a foundation for further exploration and synthesis of knowledge, contributing to the advancement of both FEI theory and its application in the defense sector.

Acknowledgments

This work was supported by the Brazilian Army (Atv PCENA V23-011).

We thank Dr. João José Pinto Ferreira (INESC TEC and Faculty of Engineering, University of Porto) for his expertise and help in writing the manuscript.

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Innovation projects management: a systematic literature review

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 Purpose: To highlight how the theme innovation unfolds within the scope of project management and how both have been addressed in scientific literature in the last two decades Methodology: This research is a Systematic Literature Review, where procedures were applied in the selection of articles in Scopus and Web of Science databases, for the identification and interpretation of the main publications on the topic in the scientific literature, seeking to understand its relevance and evolution the last twenty years. Findings: The obtained sample, based on the Web of Science (WoS) and Scopus databases, totaled 13 articles from different sectors and areas of knowledge, with a predominance of publications linked mainly to the research and development area, with greater progress in innovation projects. Practical Implications: This research contributes to improving the understanding of the benefits of the practice of managing innovation projects. Social implications: The findings of this ...

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Systematic review of institutional innovation literature: towards a multi-level management model

• Published: 02 February 2022
• Volume 73 , pages 731–785, ( 2023 )

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• Hameeda A. AlMalki 1 &
• Christopher M. Durugbo 1  

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Institutional innovation creates smart institutions that idiosyncratically thrive in a world of exponential change. Through policy-driven interventions and experiential learning, managers of institutions become adept at delivering praxis- and crisis-driven innovations required for survival and success. Similarly, the management of institutional innovation remains an interest in research due to links of this form of innovation to economic growth, and the demands of on-going major socioeconomic transformations due to technological advances, increased occurrences of major crises, and emerging socioeconomic challenges. Accordingly, a key question arising from the literature concerns the range of determinants and priorities that influence institutional innovation for delivering society value. Thus, the onus is on scholarship to capture and advance knowledge for harnessing the potency of institutional innovation. The purpose of this article is to analyse the current state of research on institutional innovation. Using the systematic review methodology, we identify and critically appraise 485 peer-reviewed scientific publications between 1969 and 2021. The review finds key determinants and management priorities with a view to developing a multi-level management model of institutional innovation. Guided by insights from the review, the article sets a research agenda for future management studies of institutional innovation.

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1 Introduction

For institutions like governments and businesses, pressures to stay abreast with social changes and scientific advances in society, serve as the impetus for innovation, Footnote 1 i.e., institutional innovation, which changes not only global competition but also the basis of competition itself within, and between institutions. Existing viewpoints on institutional innovation expand management strategy and policy horizons for institutions to include processes such as supply chain management, product innovation, and customer relationship management. These viewpoints redefine roles and relationships across independent entities to accelerate and amplify learning and to reduce risks (Hagel and Brown 2013 ; Fuentelsaz et al. 2018 ; Gretchenko et al. 2018 ). The institutional innovation perspective also depends on mechanisms for building scalable, long-term trust-based relationships through learning capabilities (Hao and Yunlong 2014 ; Chittoor et al. 2015 ; Phornlaphatrachakorn 2019 ) and increasing awareness of environmental pressures (Chu et al. 2018 ; Tang et al. 2020a ). Consequently, institutional innovation underpins the government, educational, training, and corporate policies that solve complex social problems, particularly through systematic collaborations between government agencies, universities, industries, and users.

In the management literature, the main problem for institutional innovation research remains questions on the legitimacy of institutions (Tingey and Webb 2020 ) and the necessary characteristics of novel initiatives that address socio-economic challenges such as income inequality (Biurrun 2020 ). Fittingly, there is on-going and increasing theoretical and empirical interest in the determinants of innovation (Molina-Morales and Mas-Verdu 2008 ; Li et al. 2020 ). For this line of inquiry, an important focus is on a working hypothesis that conformance to institutional frameworks underpinned by innovation has the potential to deliver societal value (Ventura et al. 2020 ; Chebrolu and Dutta 2021 ). Such frameworks highlight the dynamic nature of institutional environments, context-specific nature of innovations, and proactivity of innovators within institutions. Another area of interest (e.g. Pfister et al. ( 2021 ) and Tang et al. ( 2020b )), lies in understanding the priorities of institutions for managing the increasingly sophisticated policy toolbox used by governments to facilitate institutional innovation for public sector composition, creation of tax credits, investment in indigenous talent, intellectual property strategies, environmental protection regulations, funding for research and enterprise, etc. Here, the emphasis is on the nature of deep innovation and reviews of institutional structures needed to sustain livelihoods during times of historic change (Beunen and Kole 2021 ; Gongbuzeren et al. 2021 ; Hughes et al. 2021 ). In view of these on-going interests, there is a need to review and capture the current state of research on institutional innovation regularly for advancing domain knowledge and highlighting paths for future research.

The aim of this article is to review existing literature on institutional innovation based on a systematic approach. The review examines the trends of research methodologies and theories in studies, analyses key determinants, and synthesises management priorities for institutional innovation. Using knowledge captured from the review process, the article proposes a multi-level management model and sets a research agenda that challenges management researchers to advance the field of institutional innovation.

For this review, the interest lies in enriching the on-going work by researchers, managers, and policymakers to analyse the main determinants and priorities of institutional innovation. Such analysis remains critical for two reasons. First , innovation management studies that link institutional factors to economic growth contribute to a well-established domain of management research. This domain remains the focus of current studies (Jiang and Zhang 2020 ; Edwards and King 2021 ) to underscore the role of new ventures, market creation, inclusivity, and assistance afforded by institutions for the growth of economies and technological trajectory. Here, innovative activities within institutions act a central force to economic growth because they determine sharing rules within society and complement other growth explanations such as frugality, resilience, geography, trade, and capital (Gande et al. 2020 ; Tomizawa et al. 2020 ; Nkundabanyanga et al. 2020 ). Second , the world is at the brink of a major socioeconomic transformation due to the effects of technological revolutions like Industry 4.0, increased occurrences of major crises (e.g., natural disasters, health emergences, regional conflicts, terrorism, and economic recessions), and emerging challenges associated with climate change, rise of populism and geo-political tensions, environmental biodegradation, and rising inequality. Coping with this transformation remains complex and challenging. With thin mind, this review intends to contribute to management research and discourse on institutional innovation based on the rationale that a multi-level management model of institutional innovation could deepen and enhance understanding of determinants and priorities for supporting economic growth and confronting emerging challenges of major socioeconomic transformations. This review confronts the following research question:

What are the main determinants and management priorities of institutional innovation in the literature?

The remainder of this review proceeds as follows. The next section gives an overview of institutional innovation, followed by the review methodology and findings on key determinant and management priorities, respectively. The review then presents the multi-level management model followed by a discussion of potential future questions and challenges for management research on institutional innovation.

2 Institutional innovation: an overview

Institutions are social constructs defined as “the rules of a society or of organisations that facilitate coordination among people by helping them form expectations which each person can reasonably hold in dealing with others” (Ruttan and Hayami 1984 , p. 204). These rules govern behaviour, produce more long-standing facets of human systems, and steer societies along specific development paths (McCann 2004 ; Woodhill 2010 ) but depend on the will and creativity of individuals (Shaffer 1969 ). Through formal (e.g. laws) and informal (e.g. social norms) mechanisms, institutions concomitantly emerge from and determine socio-economic exchanges (North 1991 ; Scott 2006 ) within public and private spheres of human endeavour. In this context, some researchers argue that ‘institutional void’, i.e. the absence of formal institutional mechanisms, triggers the use of informal institutional mechanisms for guiding and supporting interactions (Raghubanshi et al. 2021 ). An alternate view argues that the emergence of institutions stems from constant-cause (same factors) and path-dependence (different factors) explanations (Parrado 2008 ). Recognising that institutions are ‘rules of the game’ (North 1990 ; Edquist 2006 ; Scott 2006 ), recent studies (e.g. Chebrolu and Dutta ( 2021 ) and Hughes et al. ( 2021 )) argue that radical perturbations, such as the Coronavirus Disease 2019 (COVID-19) pandemic, are ‘game changers’ that cause socio-economic distress and disrupt the status quo. Yet, these perturbations also pose opportunities for innovation to reimagine existing institutions and to transform the supportive ecosystems of such institutions.

According to Hagel and Brown ( 2013 , p. 4), institutional innovation is a shift from scalable efficiency to scalable learning, such that organisations “can become more adept at generating richer innovations at other levels, including products, services, business models, and management systems”. Similarly, Raffaelli and Glynn ( 2015 , p. 409) define institutional innovation as “novel, useful, and legitimate change that disrupts, to varying degrees, the cognitive, normative, or regulative mainstays of an organisational field”. For Li et al. (2020b; p.115801), institutional innovation is “the creation of a new and more effective system to encourage people’s behaviour, and the realisation of social sustainable development and innovation under the existing production and living environment”. This form of innovation emerges from injections of investments and initiatives reinforced by policies and strategies as posited by the ‘institutional-pump’ model (Durugbo et al. 2020a ), which contrasts with technology-push and market-pull theories on innovation (Martin 1994 ), as summarised by Fig.  1 . For instance, ‘pumps’ of investment underscore directed actions that implement institutional changes proposed via contracts, internalisation, regulation, and referendums (Polopolus 1969 ; Hug 2005 ).

Comparing the institutional-pump model to technology-push and market-pull theories of innovation (Durugbo et al. 2020a )

Using systems thinking, Johannessen ( 2008 ) attempts to explain changes due to institutional innovation along pattern, functional, historical, and cybernetic forms of causal processes. The author suggests these different processes account for legitimacy taken for granted (cognitive) or engrained in social pressures from institutional actors (normative). Similarly, Woodhill ( 2010 ) applies a systems complexity standpoint to argue for institutional innovation capacity that involves navigating complexity; learning collaboratively; engaging politically; and being self-reflective. Irrespective of the characterisation, institutional innovation as a concept has some lawful implications for organisational actors. Like other innovations, institutional innovation concerns novelty and utility, but differs in that it is also “legitimate, credible and appropriate” (Raffaelli and Glynn 2015 , p. 407). Institutional innovation rose to prominence due to development in sectors such as healthcare and manufacturing, with research on the subject gaining traction in the mid-1970s. Major management changes spurred by research undertaken in England and Wales in 1963 and 1973 as well as in France and North America account for most of this growing interest (Sewell et al. 2005 ). Here, insights provided from studies over the years underscore how institutions stimulate innovation to reduce uncertainties, coordinate the use of knowledge, mediate conflicts, and provide incentives.

Literature offers three main viewpoints on institutional innovation, as compared by Table 1 . The first viewpoint, induced institutional innovation (Ruttan and Hayami 1984 ; Ruttan 1989 , 2006 ), posits that resource imbalances due to institutional constraints motivates a dialectic interaction between demand for and supply of innovation. This interaction also considers the influence of technological and cultural changes in society. Here, innovators harness potential opportunities associated with overcoming institutional disequilibrium due to changes in market sizes, government rules, etc. (Grabowski 1991 ; Godden 1991 ; Ruttan 2006 ). The next viewpoint, continuous institutional innovation, notes the rapid advances and waves in technological breakthroughs (Li et al. 2020 ; Xie and Yang 2021 ) that improve democratic governance (Biggs 2008 ; Fung 2012 ). These breakthroughs emerge from and deliver provisioning in four main forms: (i) technological infrastructure that enact innovative policies; (ii) high technology that engineer complex solutions; (iii) computer-based information systems that enable innovative business processes; and (iv) digital technologies that enhance service delivery (Durugbo et al. 2020a ). The third viewpoint, collective institutional innovation (Hargrave and Van De Ven 2006 ), uses social movement and technology innovation literature to argue for a model of collective action for change that is field-dependent and occurs according to the exchanges between actors within the field. The viewpoint also highlights four perspectives on institutional innovation involving adaption, diffusion, design, and collection action—according to varying actor level foci and reproduction/ construction modes of change.

Institutional innovation is important for accelerating economic activities and contributes to added economic value. This is because this form of innovation shapes the behaviour of organisations (Edquist 2006 ) and motivates institutional actors to plan modifications that spur a variety of collective activities carefully (Schickler 2001 ; Veiga et al. 2020 ). Institutions also favour innovation because the process gives rise to stability necessary for fluid knowledge exchanges and learning processes (Carlsson 1997 ). In discussions concerning the role of innovation for economic growth, recent research accentuates the need to explore selective forms of interventions that support internationalisation in spheres of education (Foray and Woerter 2021 ; Fumasoli and Rossi 2021 ), the public sector (Buchheim et al. 2020 ), and business (Hernández et al. 2021 ). Some key areas of interest for interventions include fostering innovative work behaviour (AlEssa and Durugbo 2021 ), and reducing barriers (Hueske and Guenther 2015 ). Using transformative policies, pro-innovation institutions also attempt to address inequality in economic systems (Biurrun 2020 ; Perry 2021 ), manage immigrant integration that boosts cultural diversity (Nyseth and Ventura López 2021 ), and confront the conflating challenges of energy development and environmental protection (Gao et al. 2020 ). Yet, institutional innovation is difficult and faces unease, disagreement, and conflict due to the dynamic nature and tension between institutional persistence and innovative change (Hargadon and Douglas 2001 ). Evidence also suggests that the application of innovation generates additional risks for some institutions (e.g. financial institutions) due to the peculiar complex nature of delivered services (Mishchenko et al. 2021 ). Furthermore, there are arguments that institutional innovation negatively creates “certain structural and distributional biases” against the backdrop of economic value for institutional actors and participants (Farrell and Runge 1983 ). Such biases threaten the legitimacy and question the efficacy of the innovation by institutions.

Although, related reviews adopt the systematic approach to review institutional change research (van der Heijden and Kuhlmann 2017 ; Bakir and Gunduz 2017 ), the work presented in this article is unique in its focus on institutional innovation. Motivated by the need to deepen knowledge on institutional innovation determinants and priorities, the review presented in this article, seeks to enrich the discourse on factors and actions required for managing institutional innovation and revising existing institutional structures.

3 Methodology

Motivated by RQ , this article applies the systematic review methodology (Khan et al. 2003 ) to analyse research studies on institutional innovation. The process for this review, shown in Fig.  2 , consists of three main phases: planning, conducting, and reporting (Kitchenham and Charters 2007 ; Durugbo et al. 2020b ). Planning the review involves creating an initial protocol that concretises and formalises the review plan. Table 2 outlines the review protocol concerning the context for the research, the specific research questions, the planned search strategy, and the criteria for publication selection.

Systematic literature review process (Kitchenham and Charters 2007 )

Conducting the review is the phase entailing the selection of studies, quality assessment to include studies, data extraction and monitoring, and the data synthesis. Selection concentrates on sources available on two online databases. First, Scopus ( https://www.scopus.com ), which is a scientific search engine with the most inclusive coverage of published peer-reviewed research. The database provides access to over 26,000 + scientific, technical, and medical (STM) journal titles from over 7000 + publishers. Second, Web of Science ( www.webofscience.com ), which is a citation database that tracks and provides access to over 171 million records with about 1.9 billion cited references. Using Scopus and Web of Science, the review identifies, screens, and accumulates sources related to institutional innovation. The search process for the review applies a range of search strings to identify and screen sources based on titles, keywords, and abstracts of articles. The specific strings that serve as the basis for this review are “institution AND innovation”, “innovation AND institution”, “institution innovation”, and “institutional innovation”. This search generated 1600 and 1515 results on Scopus and Web of Science respectively, and further refined searches limiting results to journal articles published in English produced 983 and 893 results on Scopus and Web of Science, respectively. Cross-referencing to identify duplicates and screening for relevance yielded 485 articles published between 1969 and 2021 that serve as the basis for this review. Figure  3 shows the yearly distribution of the review articles, indicating a growing trend and interest in the topic, particularly in the past 7 years. The review relies on empirical and theoretical peer reviewed journal articles as the main inclusion criteria. Consequently, this process excludes conference proceeding papers, doctoral dissertations, master’s theses, textbooks, and unpublished working papers.

Yearly distribution of institutional innovation publications

For reporting the review , data analysis initially presents trends and classifications of studies. This phase derives data from preceding steps to inspect, clean, transform, and model review data on methodologies and theories within studies. Figure  4 a shows that the main methodologies used in the literature are case studies (171 articles), econometric models based on longitudinal panel data (111 articles), surveys based mainly on cross-sectional data (52 articles), and essays involving critiques, discussions, and historical analyses (50 articles). The review also contains studies using mixed methods (29 articles), literature reviews (24 articles), conceptual pieces (25 articles), decision analysis using techniques such as simulation and multi-criteria decision analysis (12), experimentation (5 articles), action research (4 articles), and meta-analysis (3 articles).

Analysis of review data according to a methodologies and b management theories used in studies

The analysis also finds, as shown in Fig.  4 b, strong theoretical underpinnings for institutional innovation studies, with institutional theory, rather unsurprisingly, dominating coverage with use in 95 sources (82 usages in isolation and an additional 13 usages from the 28 studies with multiple theories). Some other theories used in the literature include systems of innovation, transaction cost, resource-based view, absorptive capacity, dynamic capabilities, regulatory focus, and social network theories, as presented by Table 3 . The reporting phase also involves a synthesis of the findings, consistent with the research protocol, and geared towards presenting the extracted data in a manner that is coherent with the review objective and intended outcomes (Kitchenham and Charters 2007 ). Synthesis during the review is descriptive and intended to present clusters and outlines of the key determinants and management priorities for institutional innovation. In establishing the determinants, the review creates categories of concepts that serve as the phenomena investigated. For management priorities, the review applies clustering to capture themes that underscore focal points for management and interventions to enhance institutional innovation. Applying conceptual and thematic analysis is consistent with the systematic review methodology (Khan et al. 2003 ; Durugbo 2020 ) and enables the review to present the findings in a form suitable for dissemination. The next section reports the findings of the synthesis of articles.

4 Main determinants of institutional innovation

Literature suggests institutional innovation management exists in four main contexts: organisational, environmental, social, and governmental. These innovation contexts strengthen the contribution of intangible resources (e.g., proximity, relational capital, cooperation, and learning) as sources of economic growth. Constructs such as the quadruple helix (Schütz et al. 2018 ), Footnote 2 posit on actors and systems for these contexts with institutions pursuing radical (Gao et al. 2015 ; Martínez-Pérez et al. 2019 ; Qing et al. 2019 ; Ventura et al. 2020 ), incremental (Vermeulen et al. 2007b ), and in some cases, frugal (Kunamaneni 2019 ; Ananthram and Chan 2021 ; Jayabalan et al. 2021 ) innovations.

Organisational innovation presents the core context for institutional innovation, harnessing the potentials of open and technological innovations, and delivering breakthrough processes and products in areas such as healthcare (Laurell 2018 ), finance (Boulanger and Gagnon 2018 ), and education (Sein-Echaluce et al. 2017 ; Boroujerdi et al. 2020 ; Thani et al. 2021 ). Delving into complexities of intra- and inter-organisational innovation underlines the significance of new ventures and enterprise (Fuentelsaz et al. 2018 ), innovativeness and innovative behaviour (Sun et al. 2017 ; Da Silva 2019 ), and innovative investment and funding (Huston et al. 2015 ) for sustaining economic growth of cities and communities. With increasing awareness of an emergent environmental crisis, institutions also pursue environmental (green and eco forms of) innovations aimed at sustainable development (Adomssent and Michelsen 2006 ; Wang et al. 2019a ). Eco-friendly energy sources (e.g., solar, hydro and wind) and practices (e.g. reverse logistics) afford institutions with opportunities for enhancing nature's resilience to environmental pressures and for promoting responsible and accountable use of natural resources (Huang and Yang 2014 ; Polzin et al. 2016 ; Chen et al. 2018 ). This context motivates studies of management strategies such as stringent environmental regulations (Chu et al. 2018 ; Yao et al. 2019 ), reverse logistics (Aguilera-Caracuel and Ortiz-de-Mandojana 2013 ; Huang and Yang 2014 ), brand equity (Yao et al. 2021 ), and mobilisation of private finance (Polzin et al. 2016 ). Additionally, institutions chase social innovations in efforts to address complex social problems such as income inequality, poverty alleviation, urban mobility, and persistent societal and endemic violent conflicts. The intent is to create societal value (Turker and Vural 2017 ) and promote social enterprise (Kolk and Lenfant 2015 ; Venugopal and Viswanathan 2019 ) in conflict-affected areas plagued by institutional gaps. Co-creating and legitimating social innovation (Onsongo 2019 ; Kumari et al. 2020 ) becomes paramount as institutions explore agents of social change for sectoral diffusion patterns (Peirce 1991 ; Windrum et al. 2018 ) along with empowerment in public welfare for marginalised citizens and local communities that creates opportunities for positive change (Andersen and Bilfeldt 2017 ). Governmental (regulatory or policy (Costa-Font and Puig-Junoy 2007 )) innovation involves initiatives by governments that seek to confront discrepancies between the existing and attainable quality of life for citizens (Shaffer 1969 ). These discrepancies stem from issues surrounding employability, inequality in advanced economies, over-concentration of wealth for few at the top of the income distribution (Biurrun 2020 ; Fumasoli and Rossi 2021 ). Examples of policy innovations include the New Deal legislation of the 1930s that generated economic value in the form of reduced risk and increased rewards for farmers (Farrell and Runge 1983 ) and the Federal Reserve Act of 1913 for supporting bankers (Ferderer 2003 ). Intergovernmental bodies also implement policy innovation, e.g., the Birds and Habitats Directives that targets the sustainable conservation of natural habitats and species (Beunen and Kole 2021 ). Traditionally the mode for socioeconomic advances by contemporary societies (Rickards et al. 1996 ; Tingey and Webb 2020 ), recent studies highlight the increasing use of innovative policy toolboxes by local, national, and regional governments of emerging economies (May 2008 ; Helleiner and Wang 2018 ; Tang et al. 2020b ) for boosting collaboration (Gachie 2020 ) and effectiveness (Rodríguez-Pose and Zhang 2020 ).

In view of these contexts, this analysis of the literature identifies four categories of determinants for institutional innovation: (i) institutional quality and control, (ii) institutional diversity and reputation, (iii) institutional value and output, and (iv) institutional reform and improvement. Table 4 summarises these key determinants, and the next subsections outline the main concepts within the categories.

4.1 Institutional quality and control

Topically, the most investigated category of determinants and independent variables is institutional quality and control that influences efficiency and dexterity of innovation inputs. Studies focus on institutional quality because empirical evidence suggests this concept influences the ability of firms to acquire advanced technologies (Wu et al. 2016 ; Kawabata and Camargo Junior 2020 ) along with the probability, capacity, and intensity of innovation (Rodríguez-Pose and Zhang 2020 ; Mosconi and D’Ingiullo 2021 ). Total quality management (TQM) offers a critical paradigm for ensuring quality (Wiklund et al. 2003 ; Sharma et al. 2010 ; Kasperavičiūtė-Černiauskienė and Serafinas 2018 ) while control is a determinant that investigative studies generally agree on but underscore in varying research foci. Examples of these control foci include institutional gatekeepers (Ferguson and Carnabuci 2017 ), institutional structures (Fischer and Tello-Gamarra 2017 ), institutional governance (Bekhet and Latif 2018 ), and internal control quality (Ruan and Liu 2021 ). However, the most stressed quality and control determinants are patent systems characterised by high levels of formalism (Barros 2015 ; Ervits and Zmuda 2018 ) and intended for managing Intellectual Property Rights (IPR) (Malva et al. 2013; Huang et al. 2017 ; Hou et al. 2018 ). An alternative but complementary perspective in the literature identifies ownership as a mechanism for quality (Yi et al. 2017 ) due to links with strategic human resource management that support innovation-oriented business strategies (Cooke and Saini 2010 ). Research also suggests that institutional strategies embed control in an array of managerial tools, such as institutional support systems that prioritise quality controls for shaping R&D efforts within innovation systems, especially in terms of labour productivity and patenting behaviour (Fischer and Tello-Gamarra 2017 ). In these circumstances, managerial sense-making (Lee and Yoo 2008 ; Weber et al. 2019 ) remains essential to achieving sound long-term performance, on which the legitimacy and sustainability of the selective governance constellation rest.

Although researchers agree on the importance of high performing and pro-innovation institutions, the spotlight on quality and control determinants tend to vary. Measuring efficacy and changeability offers the main interest for some researchers (Bennett and Nikolaev 2020 ; Afshari-Mofrad et al. 2021 ), while others analyse factors related to innovation performance (Asiedu et al. 2020 ; Bentzen et al. 2021 ; Godlewska 2021 ) or the performance of institutional entities such as firms (Li et al. 2020 ; Hussen and Çokgezen 2021 ), and universities (Sharma and Sharma 2021 ). The latter interest informs the use of analytical constructs like the quadruple helix, which add a layer of network control for engagement (Schütz et al. 2018 ; Kang and Jiang 2020 ). This layer taps into huge potentials for high quality collaborative innovation for confronting grand challenges (e.g., climate change and urban mobility) facing modern societies.

4.2 Institutional diversity and reputation

Next, institutional diversity and reputation offer the next category of determinants investigated by researchers. Here, the emphasis remains on understanding the roles of heterogeneous (de Zubielqui et al. 2015 ) and diverse (van Wijk et al. 2019 ) actors in mobilising the emotional energy and reflexive awareness necessary to disrupt the status quo, generate (and negotiate) alternatives, and embed solutions in institutional contexts to produce profound change. Diversity foci vary in several studies with interests including urban diversity (Smith and Thomas 2015 ), firm-university partnership diversity (Whitley 2014 ), and environmental technology diversity (Aragon-Correa and la Hiz 2016 ). These authors recognise variations in the idiosyncratic capabilities of firms for acquiring and allocating resources (Li 2015 ; Kang and He 2018 ) and how these capabilities influence the ability of institutions to generate environmental, social, and economic value for stakeholders (Yeung 2015 ). For some studies, inequality entrenched in long-standing institutional arrangements is a diversity management challenge for strategies to foster gender inclusivity (Krech 2020 ) and policies to redress social inequality and poverty (Zapata-Cantu and González 2021 ). More broadly, highlighted as a puzzle for management scholars, understanding the link between institutional innovation and inequality (Biurrun 2020 ) is a research focus accentuated by recent macroeconomic shocks due to the global financial crisis of 2007–2008 and COVID-19 pandemic. Due to these shocks and radical perturbations, some researchers (Tomizawa et al. 2020 ; Hughes et al. 2021 ) differ in their opinions on the role of diversity, arguing for emphasis on alternate inclusive institutional arrangements that foster inequality due to the breakdown of institutions stemming from major socio-economic and technological transformations in society.

In the literature, institutional reputation contains intrinsic ties to diversity (Wu et al. 2015 ) and indicates success (d’Agostino and Scarlato 2019 ). Reputation, in this context, concerns institutional (and organisational) credibility and integrity as viewed by a wide spectrum of stakeholders, including citizens, governmental agencies, customers, and industry. While strong institutional policies build reputation for top-down, up-and-up implementations, focus on organisational level reputation offers a bottom-up, divide-and-conquer alternative. Considering these prospects, researchers examine how carefully considered innovation strategies enable organisations to boost their reputation (Pesti et al. 2019 ) for attracting top talent (de la Mothe 2004 ; Dahm et al. 2021 ), and how institutional information and externalities influence institutional reputation (de Zubielqui et al. 2015 ).

4.3 Institutional value and output

Insights from the literature suggest that the category for institutional value and output offers the most investigated dependent variables for institutional innovation. In the context of institutions, some researchers with ‘contributory foci’ measure innovation outputs (e.g., using patent numbers and citations (Kim et al. 2019 ), revenues of new products (Hou et al. 2019 ), and costs of equity capital (Lui et al. 2016 ), while arguing that these outputs are part of a multi-faceted structure involving knowledge creation and diffusion (Kwan and Chiu 2015 ). In contrast, some studies with ‘critical foci’ investigate the decline of innovative outputs in the context of ties to policy efforts (Kunamaneni 2019 ), technology use (Mohsen et al. 2021 ), and the political economy of micro-level institutions (Haggard and Zheng 2013 ). There are also studies with ‘consequential foci’ examining the significance of the institutional environment from which organisations operate (Barasa et al. 2017 ) and the nature of collaboration between institutional entities (e.g., multinational companies and small-sized life science companies) for harnessing entrepreneurial and creative capacities (Styhre and Remneland-Wikhamn 2016 ).

Value, which is more inherently beneficiary-oriented and relational, also preoccupies researchers (Styhre and Remneland-Wikhamn 2016 ; Cestino and Berndt 2017 ), for public value creation that enhances the life of citizens (Yang 2016 ) and customer value propositions in transaction rules that benefit clients, buyers, end-users, and so on (Wallman 2009 ). Overall, determinants in this category strive for an integration of community indicators and government performance management in an iterative cycle of engagement, legitimacy, and execution, with structural developments across borders between civil society, politics, and administration.

4.4 Institutional reform and improvement

Institutional reform and improvement describe a category of determinants essential for transformative processes (i.e., methodical, management and process innovation) within institutions in such a way that different modus operandi and modus vivendi respect human rights, maintain the rule of law, and are accountable to constituents. Primarily the focus of earlier studies (Polopolus 1969 ; Ruttan and Hayami 1984 ; Grabowski 1988 ) and more recent discussions and conceptualisations (Sus 2019 ; Hughes et al. 2021 ; Perry 2021 ), interest in this category centres on discourse surrounding the genesis and metamorphosis of institutions. Earlier works stress the role of agents of change (Ebegbulem 1974 ; Pred 1978 ) while more recent expositions give prominence to the implementation of ambitious projects (Williams 2002 ; Chien 2007 ), and transparent public–private partnerships (Zhang and Tan 2019 ; Oppong and Andrews 2020 ; Yu 2020 ). Similarly, the nature of change varies among scholars with debates that highlight differing emphasis on socioeconomic and political change (Halpern 2005 ), change in the new power topology (Clapp et al. 2016 ), technological change (Mia 2020 ; Perry 2021 ), managerial change (Parrado 2008 ), and technical change for economic development and knowledge acquisition processes (Oyelaran-Oyeyinka 2006 ; Ruttan 2006 ). Some studies argue that reform for institutional improvement is crucial, not only to boost quality levels of outputs (Azadegan et al. 2013 ) but also procedurally to ensure quality exchanges within cooperative networks (Brinckmann 1998 ). However, other researchers offer a contrasting perspective that considers negative impacts of limits and constraints such as institutional voids in areas of inadequate support (Turker and Vural 2017 ), triggering a rethinking and reimagining of existing formal institutional frameworks (Onsongo 2019 ; Chebrolu and Dutta 2021 ).

Regional policies embed reform and deliver disruptive (hence economic) capabilities and capacities for improvements. In literature, capabilities tend to represent the most essential determinant in institutional innovation (Sawang et al. 2017 ), and even though this determinant spans different categories of determinants in literature as shown in Table 4 , the reform and improvement category heightens the role of capabilities. Insights from policy making and the development of technical standards advance this line of reasoning (Smink et al. 2015 ) as policy makers wrestle with necessary blends of heterogeneous actions (radical or incremental) (Turker and Vural 2017 ; Ventura et al. 2020 ), agents (internal or external) (Villavicencio et al. 2015 ), and arrangements (formal or informal) (Fischer and Tello-Gamarra 2017 ) for successful innovations. Capacities and other conditions for successful institutional reforms also preoccupy scholars with policy suggestions for eased foreign direct investment (McCarthy et al. 2014 ) and entrepreneurial endeavours that transcend the institutional constraints of national innovation systems (Hung 2000 ). Some studies view national and local reform in the context of structural and behavioural logics that legitimise social meanings required for reform and improvement (Lazer et al. 2011 ; Waldorff 2013 ; Kooijman et al. 2017 ), with scholars analysing speeds and directions of radical innovation. Although varied in focus, there is somewhat of a consensus on the role of reform and improvements for realising substantial economic growth, and for overcoming challenges of unemployment, inequality, and deprivation.

5 Management priorities for institutional innovation

Synthesis of review data finds six management priorities for enhancing institutional innovation. This review determines these priorities based on appraising management contributions within the literature. These priorities are: (i) network engagement, externalities, and relationships (NEER), (ii) institutional logic, capabilities, and constraints (ILCC), (iii) economic conditions, policies, and intermediaries (ECPI), (iv) institutional strategies, ownership, and governance (ISOG), (v) technology readiness, transfer, and support (TRTS), and (vi) institutional synergies, incentives, and entrepreneurship (ISIE). Table 5 summarises these priorities and the next subsections outline their importance.

5.1 Network engagement, externalities, and relationships

The first of the priorities, NEER, reflects the growing significance of managerial social networks for institutional innovation (Kraft and Bausch 2018 ) in relation to transdisciplinary and interdisciplinary engagement within institutional networks (Blättel-Mink and Kastenholz 2005 ; Moore 2011 ) and ecosystems (Boisvert et al. 2013 ). This thematic group considers dynamics of organisational networks (Hage and Hollingsworth 2000 ; Schøtt and Jensen 2016 ), domesticated market networks (Van Bockhaven et al. 2015 ), inter-organisational relations (Nooteboom 2000 ), innovation networks (Lyu et al. 2019 ), connectedness of regional institutions (Liu 2016 ), networking practices (Minh and Hjortsø 2015 ), and cohesive networks (Kraft and Bausch 2018 ). Here, there are management interests in social capital (Nieto and González-Álvarez 2014 ; Smith and Thomas 2015 ), social and institutional trust (Audretsch et al. 2018 ; Didenko et al. 2020 ), and relationship ties that include managerial ties (Gao et al. 2017 ; Ventura et al. 2020 ) and social ties (Chen et al. 2021 ).

Network partnerships within this theme consider managing interactions in public–private (Kidd 1996 ; Rosário et al. 2013 ), state-market (Yu 2020 ), and industry-academia (Krishnan and Jha 2012 ) partnerships. Literature also provides other network arrangements in the form of collaborations among industry, university, and research institutions (Yingbo et al. 2010 ), R&D collaborations (Hou et al. 2019 ), helix innovation networks (Schütz et al. 2018 ), public research institutions (Fritsch and Schwirten 1999 ), university-industry links (Kunamaneni 2019 ), and multi-level institutional linkages (Rodima-Taylor et al. 2012 ). Significant in institutional collaborations and partnerships is the role of institutional actors (Lounsbury and Crumley 2007 ; Chen 2018 ) who substantially influence the creation of new practice, innovation capability, commercialisation of new technology, and institutional arrangements. Specifically, research studies allude to network actors such as executive and middle managers (Radaelli et al. 2017 ), beneficiaries (Llopis and D’Este 2016 ), fierce competitors (Frey et al. 2012 ), suppliers (Nordberg et al. 2003 ), external actors (Sun et al. 2017 ), and elites (Geels 2004 ). These salient actors play a role in shaping innovation networks by influencing the preservation of socioeconomic order and investment in innovation. With this in mind, some studies concentrate on the multi-faceted nature of institutional actors through probes of actor perceptions, activities, and diversity (Lynn et al. 1996 ; van Wijk et al. 2019 ), institutional learning (Buttoud et al. 2011 ), and the increasing use of innovation ‘offshoring’ that creates global innovation networks (Desai 2009 ).

This theme also prioritises the management of institutional knowledge–related imperatives stemming from network interactions. Example of these imperatives are knowledge externalities (d’Agostino and Scarlato 2019 ), knowledge spirals (Sein-Echaluce et al. 2017 ), and knowledge acquisition (Rutherford 2001 ; Chittoor et al. 2015 ; Liao 2018 ) that influence innovation orientation. There are also interests in links between knowledge and creativity (Boudreaux 2017 ), new knowledge bases (Asheim and Coenen 2006 ; Rolfstam 2012 ), and the knowledge infrastructure that facilitates knowledge creation, diffusion, and accumulation in institutions (Hamdouch and Moulaert 2006 ; Gittelman 2006 ; Iqbal 2021 ).

5.2 Institutional logic, capabilities, and constraints

The second priority is ILCC , which encompasses configuration- and proficiency-related management for problem solving and optimising decisions under constraints. Contributions in this thematic grouping consider improvements in the configurations of institutional logic (Kooijman et al. 2017 ; Cinar and Benneworth 2021 ), institutional logic differences (Azadegan et al. 2013 ; Llopis and D’Este 2016 ), interplay of logics (Vickers et al. 2017 ), service dominant logic (SDL) and servitization (Cestino and Berndt 2017 ), and legacies (Baark 2007 ). Grounding these logics are distinctive capabilities (Kunamaneni 2019 ) in areas of governance structures (Rasiah et al. 2016 ), forecasting and planning of skilled labour (Gretchenko et al. 2018 ), institutional readiness (Webster and Gardner 2019 ), and so on. These sources offer a discourse suggesting diversity of capabilities as a source of innovative strength for institutions. Thus, context assumes an important role for institutional innovation with varying interests in institutional (Colwell and Narayanan 2010 ; Lindelöf 2011 ), country (Lee and Yoo 2008 ), and cultural (McCarthy et al. 2014 ; Piana et al. 2015 ) contexts.

Yet, empirical evidence suggests these positive enabling priorities may possess negative constraining concerns contingent on circumstances. For instance, there are studies on institutional inhibitors such as organisational slack (Malen and Vaaler 2017 ), institutional voids (Turker and Vural 2017 ; Onsongo 2019 ), and institutional misalignments (Bunduchi et al. 2015 ). This contradiction motivates studies on institutional environments with focus on corporate governance (Yi et al. 2012 ), and professional resistance (Radaelli et al. 2017 ). Institutional theory also posits on isomorphic, coercive, normative, and mimetic pressures as affecting environments that enact institutional innovation with interests in links with religion (Assouad and Parboteeah 2018 ), and alliances (Alexander 2012 ). The complexity of environments within which institutions operate also elevates the importance of designs for innovation systems and new international ventures (Hargrave and Van De Ven 2006 ; Boudreau and Lakhani 2016 ).

5.3 Economic conditions, policies, and intermediaries

ECPI is the next priority with themes detailing management of production and consumption conditions. Financial management lies at the heart of economic imperatives for commercialisation, investment, managerial incentives, costs, profitability, and shareholding in terms of institutional innovation. These imperatives motivate research interest, particularly in relation to financial (Vermeulen et al. 2007b ) and microfinance (Elle 2017 ) services for addressing concerns such as investment horizons (Kim et al. 2019 ), economic returns (Heher 2006 ), transaction costs (Aziz et al. 2019 ), and financial fraud (Yang et al. 2017 ). These constructs aid in examining innovation outputs (e.g., patents), composition of the firms in joint ventures, and investment objectives for incremental and radical innovation.

Economic policies are themes involving guidelines, procedures, or processes for achieving rational objectives and outcomes. Policies considered within the literature include public (Adebowale 2012 ; Doblinger et al. 2016 ; Allen et al. 2020 ), innovation (Liu et al. 2011 ; May and Schedelik 2019 ), community (Molnár 2004 ), institutional (Niosi 2010 ), technology (Harding 2000 ; George and Prabhu 2003 ; Vasudeva 2009 ), and antitrust (Hart 2001 ) policies. Effective management under these policies depend on legitimacy, investment efforts, risk-taking behaviour, technological stalemate, and evolutionary trajectories. Studies also identify institutional intermediaries (Watkins et al. 2015 ; Landoni 2017 ) and their economic impact on innovativeness for climate change, innovative capability for public procurement, brokering knowledge in networks, and commercialisation of technologies.

5.4 Institutional strategies, ownership, and governance

ISOG is the management priority that steers and coordinates efforts towards enhancing innovation levels and improving institutional performance. In this context, institutional innovation scholarship proposes governing procedures and practices in concepts of governance structure (Whitley 2000 ; Casper and Matraves 2003 ), governance institution quality (Bekhet and Latif 2018 ), financial governance (Hyvärinen 2006 ), corporate governance (Yoshikawa et al. 2007 ; Yang et al. 2017 ), participatory governance (Forde 2020 ; Kalinowski 2020 ), and institutional arbitrage (Clausen 2014 ). Challenges to empower stakeholders spur increasing shifts from government to governance (Nielsen et al. 2004 ; Clapp et al. 2016 ) with goals of gaining legitimacy from transformational and executive leadership that facilitates institutional change and reform (Williams 2002 ; Asiedu et al. 2020 ). The literature also accentuates institutional strategies (Brinckmann 1998 ; Villavicencio et al. 2015 ; Smink et al. 2015 ), legitimacy (Hung and Whittington 2011 ), open innovation strategies (Kitagawa and Robertson 2011 ; Smink et al. 2015 ; Abramov et al. 2019 ), strategic transactions and dialogue (Wallman 2009 ), offshoring innovation strategies (Sartor and Beamish 2014 ), and growth strategies (Koh 2006 ). For other scholars, ownership of rights and control serves as the foundation for strategies on institutional innovativeness. Here, the interest of research lies in the mechanisms that structure institutional ownership (Cooke and Saini 2010 ; Yi et al. 2017 ), equity ownership and institutional investors (Sakaki and Jory 2019 ), and state ownership (Yi et al. 2017 ).

5.5 Technology readiness, transfer, and support

The next management priority is TRTS , which plays a crucial role in institutional innovation levels and economic progress for countries (Clark 2002 ). The suggestion is that technology readiness to fulfil the needs of institutions remains a focal point for research (Webster and Gardner 2019 ; Markey-Towler 2020 ; Mohsen et al. 2021 ), and motivates studies on technology co-evolution, employment relations, institutional conflicts (Hung 2000 ; Costa and Horn 2021 ), and technological institutional reform (Clark 2002 ). In some technology readiness studies, researchers focus on technology development (Lee 2012 ) and available technological capabilities (la Hiz et al. 2019 ) for global innovations. Authors also explore institutional readiness in the context of technological foresight for facing future challenges (Quiroga and Martin 2017 ). From earlier emphasis on adoption and rejection stemming from institutional bandwagon pressures, the debate in the literature somewhat shifts to diffusion trajectories of continuous self-propagating technological innovation by institutions (Matzner 1985 ; Abrahamson and Rosenkopf 1993 ; Nagamatsu et al. 2006 ). Examples of these technologies include big data analytics (Yau and Lau 2018 ), telemedicine (Oborn et al. 2021 ), electronic cash transfers (Zhang and Putzel 2016 ), the Internet of Things (Xie and Yang 2021 ), and smart contracts based on financial technologies (Mishchenko et al. 2021 ).

In furtherance of readiness, technology transfer and support tend to play crucial roles in institutions of some emerging economies and sectors with low technological intensity. Empirical evidence in some studies link technology transfer to innovation diffusion patterns (Zweifel 1995 ; Kwon et al. 2009 ; Barbosa and Faria 2011 ) and knowledge transfer (Mason and Wagner 1999 ). Other studies consider internationalisation (Kumar et al. 2013 ; Suzuki 2015 ) and innovation offshoring (Rosenbusch et al. 2019 ) in the context of technological barriers and institutional arbitrage strategies. Within the literature, IPR is a technology-related concept crucial to supporting innovation. Here, the focus is on patents as a protection entity with research examining IPR in terms of geographical indicators (Juk and Fuck 2015 ), rights (Malva et al. 2013; Huang et al. 2017 ), sources (Abereijo et al. 2009 ), patent behaviour (Barros 2015 ), and domain-spanning patent applications (Ferguson and Carnabuci 2017 ). Management challenges confronted within existing IPR research for institutional innovation include patenting strategies, infringements of property rights, and new SME production and knowledge recombination strategies.

5.6 Institutional synergies, incentives, and entrepreneurship

The final priority is ISIE that influences the pooling of complementary resources for new ventures by institutions and institutional actors. Recognising the need for synergies to deliver new solutions and systems, researchers tend to agree on the need for co-creation (Kumari et al. 2020 ; Sharma and Sharma 2021 ), co-management (Léopold et al. 2019 ; Casagrande et al. 2021 ), and co-decisions for institutional resources (Shackleton and Raunio 2003 ). For instance, modern innovative drugs increasingly require co-development by pharmaceutical enterprises and scientific research institutions (Wang and Huang 2020 ). Thus, the complementary nature of institutions (Da Silva 2019 ), institutional roles (Garrick et al. 2011 ) and institutional arrangements (Lee and Yoo 2008 ; Corsi and Prencipe 2019 ), serves as foci for some studies seeking to improve integration and accountability in institutions.

Alternate perspectives note the need to manage convergence into cross-border innovations, symbiotic relationships, and collaborative agglomeration for regions (Singh and Allen 2006 ; Li and Xing 2020 ; Knickel et al. 2021 ). Technically, there are also enduring institutional challenges for co-generation e.g. of heat and electricity (Chartock et al. 1985 ). In these contexts, synergetic innovation serves as the mission for arrangements such as industry-university-research collaboration (Xu et al. 2020 ), and public–private partnership (Zhang and Tan 2019 ; Cechin et al. 2021 ).

For some scholars, entrepreneurship is the cornerstone of strategies for institutional innovation. However, these authors vary in their underlying viewpoints, with interests in institutional entrepreneurs (Wang and Swanson 2007 ; Jensen and Fersch 2019 ), entrepreneur roles (Tumbas et al. 2018 ), entrepreneurial mind-sets (Cowden and Bendickson 2018 ), the influence of quality on entrepreneurship (Veiga et al. 2020 ), and interfaces between entrepreneurship and marketing (Laurell 2018 ). Irrespective of the viewpoint, the necessity- and opportunity-based nature of entrepreneurs guides researchers in positing and analysing entrepreneurship links with economic growth (Galindo-Martín et al. 2020 ). Closely linked to motivating entrepreneurial endeavours within institutions is the role of incentives, which literature links to the overcoming of market failures (Tang et al. 2020b ) and the implementation of regulations (Costa-Font and Puig-Junoy 2007 ). In the literature, there are additional accounts on the importance of executive incentives (Wang and Deng 2021 ), producers’ incentives (Desmet et al. 2020 ), incentive properties of income-sharing arrangements (Tyson 1979 ), and managerial incentives (Hyvärinen 2006 ; Jun and Weare 2011 ; Tang et al. 2020a ). Yet, it is worth noting that the presence of conflicting incentives may ultimately undermine innovation efforts (Carney and Zheng 2009 ).

6 Future research directions for institutional innovation scholarship

Using insights from the literature, this review contributes to research by proposing a multi-level model for managing institutional innovation, as shown by Fig.  5 . Premised on a background of literature arguing for induced, collective, and continuous genesis of institutional innovation, and supported by injections or ‘pumps’ of investments, the model advances knowledge by summarising the findings of the review in terms of key institutional determinants and management priorities. The main argument of the model is that innovation contexts shape the key determinants within institutions and that these determinants influence management priorities for institutional innovation. Our multi-level framing of priorities, determinants, and contexts, offers a set of factors that adds to the discourse concerning the need for more holistic assessments of institutional foundations, which current research elaborates in the form of deep institutional foci (Hughes et al. 2021 ), and co-evolution processes (Costa and Horn 2021 ). However, in practice, far from suggesting a panacea for managing the challenges and opportunities in institutions, the model, through the systematic insights from the literature, offers a research perspective on potential critical factors for stage-managing and enacting organisational, social, environmental, and governmental changes via contracts, internalisation, regulation, and referendums. In this section, we use insights from the review to set a research agenda that entails three potential paths for future research.

Multi-level management model of Institutional Innovation

To begin with, a critique of the theoretical and methodological space in literature provides the first path for future studies. In this context, in current studies and as shown in Fig.  4 b, the balance of the theoretical base appears tilted towards institution-oriented theories, particularly institutional theory treated in 95 studies. This raises the prospect for more innovation studies to offset this imbalance by testing existing innovation theories (e.g., diffusion of innovation) in different contexts, examining theories with limited coverage (e.g., the Bass model) in an institutional milieu, and proposing new theories. Current determinants analysed from the review mainly consider the institutional aspects for innovation, as shown by Sect.  4 . Thus, examinations driven by more framings of innovation could generate new insights on potential innovation-oriented determinants such as creativity, mindfulness, foresight, innovative climate, etc. Methodologically , researchers seem to favour case studies, surveys, essays, and econometric analysis. To a lesser extent, the review indicates interest in the use of decision analysis, meta-analysis, action research, and field experiments. Thus, there is a need for further investigations of the conceptual space for institution innovation using lesser-applied methods along with studies applying novel methods such ethnography, online research, meta-synthesis, phenomenography, and grounded theory. Existing management priorities in the literature mainly reflect macro- and meso-level considerations of institutional innovation, particularly in the context of regional, national, sectoral, and organisational concerns. Accordingly, there is a need for further studies of micro-level considerations, i.e., individual factors that enable or inhibit institutional innovation. For instance, grounded theory or ethnography-based studies could explore and theorise on personas, personalities, and motivations of institutional actors that play major roles in inducing, coordinating collective action, or championing continuous change. Similarly, online research or phenomenography could underpin explorations on the role and factors of technology (e.g., social media) use by institutional actors in relation to embedded and established routines for innovation stages (e.g., ideation) in institutions.

In line with current studies, this review challenges researchers to explore policy void in industrialised and social contexts (Mehmood 2016 ; Onsongo 2019 ) and investigate the role of institutional mediators and factors (Laurell 2018 ; Tomizawa et al. 2020 ) in relation to institutional adaptation for regional innovations. There are also challenges to detangle institutional variations concerning how formal and informal institutions shape innovation types, practices, and processes (Chadee and Roxas 2013 ; Filiou and Golesorkhi 2016 ; Huang et al. 2017 ). Further challenges exist regarding the multi-faceted role of institutional environments that positively endorse and enable, or negatively inhibit and inactivate institutional innovations (Whitley 2000 ; Wang and Swanson 2007 ; Mueller et al. 2013 ; Wu et al. 2016 ; Fischer and Tello-Gamarra 2017 ; Nite and Washington 2017 ; Kadriu et al. 2019 ; Wu and Park 2019 ).

Derived from reflections on the management priorities of the previous section, the third path for future studies extends the synthesis from the review for topical viewpoints that strategically advance the field of institutional innovation. In the next subsections, we present these paths, detail current related efforts, and elaborate on some specific research challenges for management scholarship concerning institutional innovation.

6.1 Institutional contracting

The first challenge involves studies of institutional contracting (mainly from reflections on NEER ) that examine the process of engagement, building relationships, and bargaining with contractors for formulating and implementing contracts. Accordingly, studies of institutional contracting advance NEER management, and in the proposed model of Fig.  5 , NEER management maintains social exchanges within institutions in accordance with contingency, agency, and transaction cost theories. With increasing global trends towards privatisation, urbanisation, internationalisation, and digitalisation, the indications are that contracts remain crucial for maintaining transdisciplinary and interdisciplinary engagement within institutions. In current literature, new forms of contracts serve as the focus of innovation by agricultural institutions for contract farming (Escobal 2000 ; Bhanot et al. 2021 ) and supplier contracts with research institutions (Nordberg et al. 2003 ). There are also discussions on the value of smart contracts developed by financial institutions (Mishchenko et al. 2021 ). Although contracts are well-established as a form of institutional innovation (Polopolus 1969 ), studies on the nature of contracting remains limited. Therefore, we urge for research exploring the nature of contracting that enables institutional innovation and critical success factors of this contracting process. With evidence suggesting that contract enforcement challenges may cause the emergence of new institutions (Dimitri 2002 ), future research could theorise on and empirically investigate enforcement mechanisms for sourcing and contracting institutional innovation. Research also suggests that inadequate contracting processes account for several regulatory failures (Costa-Font and Puig-Junoy 2007 ), challenging future studies to expand on normative frameworks for contracting within institutions.

6.2 Institutional reimagining

The next challenge relates to research on institutional reimagining (from reflections on ILCC ) to offer a critical view that complements existing analytical insights from studying opportunities and challenges of induced, continuous, and collective institutional innovation. Hence, research on institutional reimagining furthers ILCC management, and in the proposed model of Fig.  5 , ILCC management involves coordinating capabilities under institutional constraints that reflect resource-based, dynamic capabilities, absorptive capacities, and institutional-pump framings. This coordination requires awareness and support for the construction of institutional narratives (Schofield 2000 ) and consciousness capabilities of new global imaginaries (Hughes et al. 2021 ). In furtherance of these efforts, we propose that researchers assess institutions critically on an on-going basis to promote transdisciplinary efforts that avert institutional stagnation when confronting societal challenges. With insights from the literature and in line with institutional theory, this review highlights the need for critical reflections on the measures and pressures that shape innovation success. Multi-level analysis could aid in uncovering the micro, meso, and macro levels that are critical to promoting success and averting collapse of institutions. Critiques could also compare up-and-up and divide-and-conquer strategic plans to highlight instances of wasteful tax-and-spend policies.

Recognising the threat of institutional obsolescence discussed in early research (Polopolus 1969 ; Shaffer 1969 ), we also propose future research on the collapse of institutions, in the context of failed institutional logics for innovation to capture reasons, detail lessons learnt, review existing policy toolboxes, and reimagine failed institutions. For instance, the collapse of financial institutions in 2008 and economic collapse due to the COVID-19 are instances of institutional collapse with negative global consequences. Thus, this line of research could strive to analyse innovation determinants for recovery or reconstruction of institutions. Questions guiding such research efforts include ‘how can governments innovatively reconstruct collapsed institutions?’ and ‘what structural and behavioural attributes contribute to the collapse of institutions?’ Future research could also use insights from lessons learnt to provide innovative forecasting tools to avert institutional collapse.

6.3 Institutional intelligence

Another challenge for studies involves analysing institutional intelligence (from reflections on ECPI ). Research concerning institutional intelligence encompasses assessments of the data analytic capacities (e.g. big data analytics (Yau and Lau 2018 )) that harness the potentials of institutional information, and the intelligent intermediaries (Chen et al. 2015 ) that facilitate innovation, particularly in relation to recruiting, retaining, and developing intelligent employees. Consequently, institutional intelligence research advances ECPI management, which represents a fundamental component of the proposed multi-level management model, as represented by Fig.  5 , and determines economic benefits from institutional innovation, in line with economic theory. Although, this review incorporates studies on the need to attract top talent for innovative research in higher education (Dahm et al. 2021 ) and innovation ‘offshoring’ to emerging countries (Desai 2009 ), this line of inquiry remains limited in the context of institutional innovation research. Accordingly, we challenge academia to explore the range of data analytics for institutional innovation further, along with concepts such as institutional optimisation, innovative talent capacity building, institutional intelligence, and talent management strategies. Studies may also consider intelligence and talent management in relation to roles of actors in constructs like the quadruple helix, and control mechanisms, e.g., managerial incentives and corporate governance. Since intelligence and talent are human capital constructs, there are questions concerning effectiveness of top-down and bottom-up strategies within institutions. Some questions include ‘how effective is upper management in retaining talent for innovation?’ and ‘what is nature of team involvement in selecting and sourcing analytic capabilities for institutional innovation?’.

6.4 Institutional stewardship

For management researchers, there are future opportunities to examine institutional stewardship (mainly from reflections on ISOG ). With emphasis on responsibility and accountability, stewardship progresses ISOG management and embodies the control and sense of duty demanded by on-going shifts from government to governance (Clapp et al. 2016 ) for boosting participation and empowerment for institutional innovation. ISOG management, in the proposed model of Fig.  5 , involves governance that promotes pro-innovation institutions and is in line with agency and actor network theories. In this review, studies offer insights on related challenges for participatory governance (Forde 2020 ) and leadership (Williams 2002 ; Asiedu et al. 2020 ) that trend towards a sense of duty by institutional actors. Despite these research efforts, the literature provides limited bottom-up insights on the potential role of stewards in promoting institutional innovation and innovation contexts, i.e., organisational, environmental, social, and governmental. Future research could study specific roles of institutional stewards for radial and incremental innovations. Although, empirical evidence suggests links between stewardship behaviour and the success of innovation (Domínguez-Escrig et al. 2019 ), there are opportunities for studies to test this relationship in normative and cognitive institutional contexts. Future research may also view challenges of institutional stewardship in isolation or in conjunction with existing inadequacies due to institutional pressures, voids, and barriers.

6.5 Institutional preparedness

Another potential research direction involves studies of institutional preparedness (mainly from reflections on TRTS ), in the context of more frequently occurring macroeconomic shocks and technological transformations in society that threaten the legitimacy of institutions. Traditionally a focus of studies on agents of change (Ebegbulem 1974 ), research on readiness in an institutional context increasingly focuses on preparedness that supports trajectories of self-propagating technologies (Nagamatsu et al. 2006 ). Institutional preparedness, in this context, refers to how institutions are equipped in terms of capabilities and capacities to respond to new challenges and opportunities. The proposed multi-level model of Fig.  5 advances TRTS management for technology readiness as an element of institutional preparedness, with conceptual underpinnings from contingency and diffusion theory. Yet, there remain challenges to understand future innovation contexts and preparedness by institutions for praxis and crisis situations, proactively and reactively. For instance, recent dengue, Zika, and coronavirus outbreaks have challenged the role of traditional innovation-driven approaches, which focus on opportunity, and shifted the attention to ingenuity to cope with adversity. In addition, there are challenges to examine the infusion and routinisation (beyond the adoption and diffusion foci of current research (e.g., Genus 2012 ; Oborn et al. 2021 )) of technologies emerging due to the Fourth Industrial Revolution (e.g., synthetic data, biotechnology, and 3D printing). Thus, future studies may consider challenges such as institutional roadmaps with foresights for emerging technologies and institutional skilling needs. Other investigations could consider preparedness constructs for innovative institutions and crisis-driven innovation contexts for institutions.

6.6 Institutional complementarities

The final challenge involves research on institutional complementarities (mainly from reflections on ISIE ) for examining the ability of institutions to supplement other institutions in the quest for innovation, or the degree to which institutional arrangements, roles, factors, and innovation emphasise or improve each other. Just as innovation complements other explanations of economic growth (e.g., geography, and international trade), opportunities exist to investigate the complementarities for institutional innovation. For this reason, studies of institutional complementarities further ISIE management, and in the proposed model of Fig.  5 , ISIE management ensures integration and incentivisation within institutions in accordance with resource-based and dynamic capabilities views. Discussions in the literature on compatibility and substitutability (Corsi and Prencipe 2019 ; Da Silva 2019 ) reinforce the role of strategies for complementarities in sustaining synergies and incentivising entrepreneurial ventures within institutions. Yet, questions remain on the scope, range, and forms of complementarities that facilitate institutional innovation. For instance, the prospect of ‘creative complementarities’ that supply creativity-driven resources and know-how (Durugbo et al. 2020a ), suggests possibilities for implementation, adoption, and continuance forms of complementarities that incentivise induced, continuous, and collective institutional innovation. Lines of inquiry could examine the nature of complementarities that (dis)incentivise entrepreneurial endeavours within institutions. Such focus is needed because the literature in this review suggests that conflicting incentives within institutions inevitably deter innovative activities (Carney and Zheng 2009 ). Further studies could also examine institutional complementariness for innovation in the context of determinants such as quality, productivity, diversity, and so on. In addition, complementary viewpoints may consider and explore the role of complementarities in addressing challenges of inequality, sustainability, security etc.

7 Conclusions

In the words of Pablo Picasso, “learn the rules like a pro, so you can break them like an artist”. This saying underscores the need for ingenuity and innovation by institutions, as the rules of societies or of organisations to deliver value for a range of stakeholders such as citizens, governmental agencies, customers, and industry. Additionally, innovation in an institutional milieu faces pressures, voids, and barriers that force institutions to shift from scalable efficiency to scalable learning in efforts to expand management strategy and policy horizons. Consequently, transdisciplinary insights on the key determinants and management priorities of institutional innovation are critical to cope with the inherent dynamic nature and tension between institutional persistence and innovative practices. These determinants and priorities aid institutions deliver breakthrough processes and outcomes that require review on an on-going basis to update scholarship and practice. With this in mind, this review confronts the following research question: “What are the main determinants and management priorities of institutional innovation in the literature?” ( RQ ).

Driven by a systematic approach that seeks to address RQ , this review summarises its findings in a multi-level management model for institutional innovation in terms of innovation contexts, institutional determinants, and management priorities. Grounded on organisational, social, environmental, and governmental contexts for innovation, the review identified four key determinants concerning (i) innovation quality and control; (ii) institutional diversity and reputation; (iii) innovation value and output; and (iv) institutional reform and improvement. Similarly, the review captured six management priorities concerning network engagement, externalities, and relationships; institutional logic, capabilities, and constraints; economic conditions, policies, and intermediaries; institutional strategies, ownership, and governance; and technology readiness, transfer, and support; and institutional synergies, incentives, and entrepreneurship.

There are two main limitations of this review. First, the review focus is limited to capturing the main determinants and management priorities of institutional innovation. In this context, there is a need for additional insights on aspects such as innovation activities, the behaviour of institutional actors, and institutional arrangements. Second, the review approach is restricted to a systematic methodology that applies thematic analysis. Hence, there are prospects for deeper insights based on other review methodologies such as meta-analyses and meta-syntheses that offer more focused and extensive knowledge on constructs, dependencies, and links between variables within qualitative and quantitative studies of institutional innovation. Further analysis of co-citations could offer knowledge on the nature of citation dynamics and potential connections between publications.

Guided by insights from the findings on management priorities, the review identifies six strategic areas for future management research on institutional contracting, reimagining, intelligence, stewardship, preparedness, and complementarities. In summary, the review anticipates that the necessities and niceties of these proposed areas will aid in strengthening existing knowledge on institutional innovation and in uncovering new and exciting institutional phenomena, prospects, and potentials as managers set ground rules on contexts for innovation and run the rule over determinants within institutions.

Innovation is defined here according to the 2018 Oslo Manual as an outcome (business innovation), i.e. “new or improved product or business process (or combination thereof) that differs significantly from the firm's previous products or business processes and that has been introduced on the market or brought into use by the firm”, and as a process (innovation activities), i.e. “developmental, financial and commercial activities undertaken by a firm that are intended to result in an innovation for the firm” (OECD/Eurostat 2018; p. 33).

Network of actors from academia, industry, government, and the public.

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AlMalki, H.A., Durugbo, C.M. Systematic review of institutional innovation literature: towards a multi-level management model. Manag Rev Q 73 , 731–785 (2023). https://doi.org/10.1007/s11301-022-00259-8

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A Systematic Literature Review of Innovation Management and Risk Management.

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Tool support for data-driven service innovation: a systematic literature review.

• BERNDT JESENKO  and 
• STEFAN THALMANN

https://orcid.org/0000-0001-6274-9859

CAMPUS 02, University of Applied Sciences, Koerblergasse 126, 8010 Graz, Austria

E-mail Address: [email protected]

Corresponding author.

Search for more papers by this author

https://orcid.org/0000-0001-6529-7958

Karl-Franzens University, Universitätsstraße 15, 8010 Graz, Austria

Data-driven technologies changed the way how service innovation is conducted in organisations. The literature discusses the potential of Data-Driven Service Innovation (DDSI) processes, but it is not clear yet what tool support for DDSI looks like. This structured literature review examines the tool support for each phase of DDSI processes. We found clear differences between the DDSI phases and different tools for each phase. In the first phase, tools with batch processing capability are employed for methods like text mining and sentiment analysis, helping to capture evolving customer behaviour and trends to increase the speed of innovation rate. In the second phase, immersive technologies, real-time sentiment analysis and stream analytics are used for the validation of service development processes to increase the likelihood of market success. In the third phase, AI tools with the capability to continuously learn from emerging data and Big Data Analytics tools are combined.

• Big data analytics
• data-driven service innovation
• artificial intelligence
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Received 10 April 2024 Revised 11 August 2024 Accepted 16 August 2024 Published: 26 September 2024

The Scholarly Kitchen

What’s Hot and Cooking In Scholarly Publishing

Embracing Innovation: Insights from Peer Review Leaders on Managing Technological Change

• Business Models
• Organizational Management
• Peer Review

Peer Review Week 2024 celebrates a theme that is rapidly reshaping the academic publishing landscape: Innovation and Technology in Peer Review. As we look ahead, the tools and systems driving efficiency and quality in peer review are becoming increasingly sophisticated, from AI-powered manuscript checks to automated reviewer matching systems. But, as exciting as these innovations are, the real challenge lies not just in implementing the technology, but in managing the human and organizational changes required to make these innovations stick.

In this post, we go beyond the surface of technological advancements to explore what it truly takes to integrate these tools into the fabric of peer review processes. We’re talking about change management — the strategic, and sometimes complex, process of preparing teams, adjusting workflows, and aligning organizational culture to adapt to these innovations. Without careful management, even the most promising technologies can falter if the people behind them aren’t properly equipped to embrace the changes they bring.

We’ve invited three peer review managers from leading publishing groups to share their insights into how they are leading their teams through these transformative processes. Today we hear from Laurie Webby, Peer Review Manager at the American Society for Microbiology (ASM), Alison Denby, Vice President, Journals, at Oxford University Press (OUP), and my co-worker Erika Mann, Peer Review Operations Manager at the Public Library of Science (PLOS). From practical tools like checklists and plagiarism detection software, to fostering cross-departmental collaboration, their stories offer a roadmap for others navigating similar journeys. Through their perspectives, we’ll learn not only about the innovations themselves but also the critical strategies for ensuring these technologies are successfully adopted and embedded into everyday practice.

How do you drive innovation in your everyday peer review practices?

Innovation takes many forms, from incremental improvements to sweeping transformations in peer review. For these peer review leaders, innovation is not just about adopting the latest tools but also about fostering a culture of adaptability and continuous improvement.

Erika : Incremental progress towards improving processes! At PLOS, there’s been a recent shift towards agility when it comes to improvement and problem-solving, which is a relatively new method of working for us. In the past, we worked under a more ‘traditional’, linear model of solutioning; that is, identifying a problem and solution, and then tracking whether the solution works once it’s already been implemented. It can be hard to adapt to new ways of working and convince people that it might lead to better outcomes, but it’s important to keep an open mind and be willing to take some risks. 

Laurie : I believe innovation can stem from many different sources — whether it’s from colleagues, editors, authors, reviewers, or even readers. I regularly audit our peer review workflow and processes to assess what is working well for our authors and what could be improved. My primary goal is to streamline the initial submission process at ASM, making it as quick and straightforward as possible. By focusing only on the essential requirements for review, we aim to ensure that authors receive timely decisions on their submissions.

What have you learned from introducing new peer review technologies?

Implementing new technologies often reveals both the strengths and weaknesses of current workflows. Our experts reflect on the unexpected challenges they faced when bringing innovations to their teams and the lessons learned through trial, error, and eventual success.

Alison : Experiment, experiment, experiment. There’s substantial scope to improve the act of peer review and, in doing so, enhance the value we’re adding to research for authors, and attempt to reduce some of the existing biases. You should also carefully consider the type of peer review work you’re experimenting with. Often, Generative AI based on LLMs (Large Language Models) is only one tool and often it isn’t the most effective solution for specific needs, particularly within our highly technical and specialist area.  Take for example tools designed to assist editorial staff with securing reviewers. Often the biggest challenge isn’t in finding the right reviewer – it’s in how you approach a suitable person at the right time, in the right way to persuade them to act as a reviewer. While technology is rapidly evolving and we’re adapting in response, the fundamental principles remain unchanged – high-quality work, carefully reviewed and enhanced, to maximize impact in its broadest senses. 

An even more specific example is the use of language editing tools before submission, to help level the playing field for authors for whom English is not a first language. We have seen a reduction in the rejection rate for content where a language editing tool has been used.

Erika : I’ve been doing some research on what other publishers are doing, specifically what tools they use to manage peer review and ensure that papers meet journal policies and expectations. From this research, I’ve learned that a lot of organizations are creating tools that leverage AI and emphasize real-time collaboration between contributors and the journal office. I find a lot of value in a more collaborative peer review process, both on the management side and for improving research, so I’m excited to see how those tools shape up and how we can use those learnings to improve processes at PLOS.

What tools, processes, or checklists have been most critical in managing these innovations?

From AI-based plagiarism detection to automated reviewer matching, peer review teams are increasingly leveraging new tools to streamline their workflows. Our experts share which technologies have been the most impactful, why they chose them, and how these tools have reshaped their processes.

Alison : At OUP, we have introduced a wide range of tools and processes. Our primary focus has been on a plug-and-play approach to pull together a combination of best-in-class capabilities that will continue to evolve as the technologies change.

Erika : Over the last three years, PLOS has launched a new suite of journals. With each launch came new ways the Peer Review Operations Team had to learn to work. Specifically, we introduced a new mechanism in our peer review management tool, for our vendor to more effectively escalate questions to PLOS staff. Rather than add staff to discussions, we use ‘Editorial Tasks’ in Editorial Manager, a feature that allows us to directly assign work to staff. This seemingly minor innovation has allowed for much-needed accountability in our workflows. Content doesn’t get lost and we can develop better reporting. With this new tool we can effectively track submission volumes and specific types of escalations, and additionally, we can adjust any of our workflows as needed. This seemingly minor innovation in our work, I’d argue, has been essential for keeping peer review timelines intact and contributing to a better author experience than our previous method. It’s also allowed staff to prioritize their work efficiently. 

Can you provide an example of an innovation or technology you’ve introduced and the hurdles you faced during its implementation?

Transformational change doesn’t come without its challenges. Each expert shares a real-world example of a tool or process they’ve implemented, highlighting the key hurdles they encountered during the change management process and how they overcame them.

Alison : At OUP, we’ve tested and are currently using many different tools to support multiple stages of the peer review process:

• Integrity detection tools: AI in peer review from language editing and testing other things like “fact-checking” e.g., does a lab have the equipment to undertake the research presented?
•   Journal audits and checklists – understanding the nuance between disciplines – what’s an acceptable editorial practice in one field might be flagged as a concern in another – tools need to be appropriately tailored
•   Editor education and training
•  Persistent Identifiers ( PIDs) and things like CRediT – for author accountability and understanding the funder/institution – improved metadata around all content. These identifiers help to flag potentially problematic content but also help to make connections – e.g., understanding if an author has an APC discount as a society member, or as part of a Read and Publish (R&P) deals
• Collecting information on data availability

The biggest challenge we have encountered is bringing the whole community around a journal, ( authors, reviewers, editors, and society partners) along with us in the face of a lot of change. Many changes add work for an editorial team. Where possible, we try to remove the administrative work (particularly in areas where subject matter expertise is not critical) away from our editors so they can focus on content.

Laurie : One improvement we implemented across all our journals was the automatic review assignment system. I made this decision because previously, only half of our journals were utilizing it, while the other half were not. By standardizing this feature, we aimed to relieve our editors from the daily task of manually checking on reviewer availability, as the system automatically assigns a new reviewer if one declines. This also helps prevent overburdening our reviewer pool with unnecessary emails, particularly in situations where they are invited to review but later informed that their participation is no longer needed.

The most challenging aspect has been gaining full support from the editors. Some feel that this process takes longer, although data shows that journals using the system correctly have comparable turnaround times to those that do not. However, overcoming this perception has been a persistent challenge.

Have you experienced cross-collaboration with teams or departments that typically don’t intersect with peer review?

The intersection of peer review with other departments and external collaborators is increasingly necessary for successful innovation. Whether working with IT, data science teams, or even external vendors, collaboration has become critical to scaling innovation across organizations. Our contributors reflect on their experiences forming new partnerships and how their teams adapted to these evolving changes.

Laurie :  Since the launch of journal portfolios — which in itself is an innovative new business model ASM introduced to better position our journals for a more sustainable future — the peer review team has been collaborating more closely with the editorial teams to implement various innovations suggested by the editors. This marks a shift for us, as the editorial teams have only been part of the strategic plan for about four years. For over half of my peer review team, this is a new experience, as they previously worked directly with the editors before this change. As a result, it has been an adjustment in terms of how they receive information, who they receive it from, and how they process and act on that information.

Alison : There’s an increasingly necessary interconnectivity from all we do to initially attract a submission, manage the submission, publish, promote, and sell. Each element relies on another – e.g., we need a Ringgold ID in the production process to know whether an author can benefit from a read-and-publish agreement. We see journal publishing as a holistic process and work across functions to support each stakeholder. We collect performance data and metadata throughout the workflow.

We are very fortunate at OUP to have exceptionally good cross-functional collaboration. Critical to success has been exceptional communication, but also a willingness for departments to understand the potential consequence of their actions elsewhere and sometimes to compromise with program objectives and success in mind over individual areas. There are painful moments and difficult decisions, but we’re fortunate to have a team prepared to tackle conflict, listen, and compromise. We are also fortunate to be a part of the University of Oxford and able to take a mid-to-long-term view in terms of strategic positioning, which has allowed us to be consistent in approach.

Erika : Absolutely! At PLOS project teams have become more cross-functional, involving folks from entirely different departments. When you’re in meetings with collaborators who perform different tasks than your own, you learn right away that you must adjust your communications to make sure everyone is on the same page. Not only in terms of styles but also in content. What may be understandable to you may be completely incomprehensible to someone else. In a way, it’s been a great form of self-reflection. 

Another essential change we’ve had to make is not being afraid of asynchronous work. We have folks from different time zones, so it’s not always feasible to meet in person. 

What else can peer review teams learn from your experience?

Our contributors wrap up their insights by reflecting on the broader implications of Peer Review Week’s 2024 theme — how innovation in technology can shape the future of peer review. Their final thoughts offer actionable advice for teams looking to navigate the rapidly changing landscape of peer review.

Alison : I’d offer three major points of advice:

• Experiment and learn
• Stay true to your mission and strategic priorities
• Don’t underestimate the human aspect of effective change management

Laurie : Don’t hesitate to explore new ideas! Take the time to thoroughly research and pilot any initiative that you believe could enhance the peer review process for authors, reviewers, and editors.

Erika : Be willing to take calculated, data-driven risks, and remember that progress, no matter how ‘small’, is progress.

Join the Conversation

As we conclude, we invite the broader peer review community to share their own experiences. What have you learned from implementing new technologies in peer review? How have you managed change, overcome hurdles, and supported your teams through these transitions? Your insights could provide valuable guidance to others on the same path, contributing to the collective knowledge around innovation and change management in peer review.

Jasmine Wallace

Jasmine Wallace is the Senior Production Manager at the Public Library of Science (PLOS). She is responsible for the production processes and day to day production and publication operations for the PLOS journal portfolio. Previously, she was the Peer Review Manager at the American Society for Microbiology (ASM). She was responsible for ensuring peer review practices, workflow, processes, and policies were up-to-date and applied consistently across the entire portfolio of journals. She served as Treasurer for the Council of Science Editors and was the creator and host of their podcast series S.P.E.A.K. In the past, she was a Teaching Assistant at George Washington University for a course on Editing for Books, Journals, and E-Products.

Laurie Webby

Laurie Webby is Peer Review Manager at the American Society for Microbiology.

Alison Denby

Alison Denby is Vice President, Journals, at Oxford University Press.

Erika Mann is a Peer Review Operations Manager at PLOS where she manages vendors, workflow optimization efforts, and a team of direct reports, alongside her fellow Peer Review Operations Managers. Prior to PLOS, Erika spent several years in the tech industry as a marketing and PR specialist. Her favorite pastime outside of work is cozying up with a good book.

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