Innovation intermediaries revised: a systematic literature review on innovation intermediaries’ role for knowledge sharing

Direct innovative outcomes of intermediaries are captured through company-based innovation surveys and rely upon self-declared outcomes (Lee and Miozzo 2019). The OECD innovation manuals are central for intermediary research (OECD 2015, 2018). Namely, the introduction of new and improved products (Hsieh et al. 2015; Li et al. 2019; Chen and Lin 2018) and services (Hsieh et al. 2015; Li et al. 2019; Rodríguez et al. 2018; Shearmur and Doloreux 2019; Silva et al. 2018), processes (Li et al. 2019; Readman et al. 2018; Rodríguez et al. 2018), organizational innovation (Chichkanov et al. 2019; Readman et al. 2018; Shearmur and Doloreux 2019) and marketing innovation (Chichkanov et al. 2019; Hsieh et al. 2015; Shearmur and Doloreux 2019) are used as indicators. In addition, the introduction of new technologies (Chichkanov et al. 2019; Silva et al. 2018), registration of intellectual property rights (Li et al. 2019; Silva et al. 2018), innovation in human resources (Shearmur and Doloreux 2019) and cost innovation (Hsieh et al. 2015) were surveyed as characteristics of innovative outcomes. Studies define the quality of outcomes according to the degree of novelty, differentiating between incremental and radical progress (Bocquet et al. 2016; Lee and Miozzo 2019; Shearmur and Doloreux 2019), degree of standardization (Chichkanov et al. 2019) and new knowledge created (Silva et al. 2018).

In comparison to traditional company-based innovation surveys, studies on intermediaries have investigated innovative outcomes with a broader perspective, thereby capturing indirect innovative outcomes. Indirect innovative outcomes survey the contribution of intermediaries to clients’ innovative outcomes. The papers include intermediaries’ contributions to firms’ new services (Readman et al. 2018) and products (Landry et al. 2013), process innovation (Knockaert and Spithoven 2014; Landry et al. 2013; Matschoss and Heiskanen 2017), organizational changes (Landry et al. 2013; Matschoss and Heiskanen 2017; Readman et al. 2018) and marketing activities (Knockaert and Spithoven 2014; Landry et al. 2013). The influence on business model innovation (Landry et al. 2013), innovation speed (Knockaert and Spithoven 2014) and realization of objectives add to indirect innovative outcome. Furthermore, Russo et al. (2019) introduce the category of changing behavior induced by intermediaries and relate it to business models, the search for market niches and distribution channels, investments in new or improved products and services as well as the demand for knowledge-intensive services (Russo et al. 2019).

The impact of intermediaries also contains the integration of intermediaries into innovation systems. The effectiveness of intermediaries to contribute to specific systemic goals is discussed in some studies, such as the role to foster learning on system levels (Gao and Hu 2017) or clients’ satisfaction with intermediaries to understand its contribution to network structures (Mueller and Jungwirth 2016). A central topic is the support of entrepreneurship learning, which entails dimensions like the variety of actors, the number of new actors in the network (Matschoss and Heiskanen 2017), the number of new firms created as a result of intermediation collaboration (Sengupta and Ray 2017; Zeng et al. 2010) and the support received to develop new markets (Kanda et al. 2019). Moreover, the development of knowledge capabilities (Kanda et al. 2019; Silva et al. 2018) reflect an indirect impact on the innovative outcome. For publicly funded intermediaries, the fulfilment of public funding bodies’ requirements and goals are also used as a proxy to evaluate intermediaries’ impact (Mueller and Jungwirth 2016).

Approaches to connect intermediaries directly to regions’ performance is still in its infancy and is often argued on a conceptual level. Zeng et al. (2010) presented a novel exploratory approach to connect intermediaries’ performance with regional indicators. They measured the rate of regional investments and the use of intellectual property rights to analyze intermediaries’ impact on the regional level (Zeng et al. 2010). A broader set of regional innovation with focus on intermediaries could help understand the embeddedness of intermediaries in regional innovation systems.

In the literature, four dimensions of general characteristics have been discussed: First, the time span of intermediaries’ operation (Benassi et al. 2012; Hsieh et al. 2015; Pina and Tether 2016; Soetanto 2006), second, the number of employees (Pina and Tether 2016; Sinell et al. 2018), third, the type of ownership—public or private—(Zaichenko 2018), and fourth, annual budget (Stezano 2018). These dimensions influence the capability of intermediaries to innovate and to enable other actors to increase their innovativeness.

The strategy of intermediaries consists of three dimensions: the definition of goals, knowledge creation and innovation strategy, and finally, the commercialization strategy. The formulation of the strategy relies on the clarity of the formulated goals (Kant and Kanda 2019; Mueller and Jungwirth 2016; Chen and Lin 2018) and the specialization of intermediaries (Kanda et al. 2018; Sinell et al. 2018; Villani et al. 2017). Moreover, goal formulation relies on the intermediaries’ interaction with clients (Elmquist et al. 2016; Kant and Kanda 2019; Mossberg et al. 2018; Mueller and Jungwirth 2016; Randhawa et al. 2017), making the latter’s scope central for successful cooperation projects (Howells 2006; Sengupta and Ray 2017). This refers to the selection strategy of cooperation partners chosen according to their sectors, or chosen with a focus on economy-wide (Fukugawa 2018), international or domestic ranges (Fukugawa 2018) that focus on new or established technologies (Gao and Hu 2017). The goal-orientation also depends on the capability for rule-based selection criteria (Soetanto 2006), cooperative knowledge sources and the ability to negotiate with prospective partners (Howells 2006).

Another relevant dimension for shaping intermediary’s strategy is the innovation and knowledge creation strategy, since it determines the function in the innovation system. This includes the decision to pursue open or closed innovation strategies (Li et al. 2019; Sengupta and Ray 2017). As a consequence, the selection of external partners will depend on this choice (Parjanen et al. 2011; Sengupta and Ray 2017; van Geenhuizen 2018). In cases where intermediaries also run internal research units, strategic decisions on the range of research activities conducted—between basic and applied (Readman et al. 2018; Stezano 2018; Vivas 2016; Zaichenko 2018)—and how they are conducted need to be finalized. Specifically, the structure of research processes, level of outsourcing, strategic collaborative learning and collaboration with clients are dimensions related to the innovation and knowledge creation strategy.

Last but not least, the commercialization strategy states activities for commercialization of products and goods directly (Landry et al. 2013) or indirectly by providing information to third partners who support the commercialization of innovation (Cannavacciuolo et al. 2015; Soetanto 2006). These activities include the search for market niches, exploration of add-value services and the redirection required to attract new customers (Landry et al. 2013). Furthermore, commercialization strategies include the marketing of these activities and the screening of their development (Landry et al. 2013), making commercialization’s timing a key for successful cooperation (van Horne and Dutot 2017).

The articles discuss three dimensions of intermediaries’ structure: internal structure, communication and embeddedness in the innovation system. First, the internal structure is analyzed with regard to the degree of formalization of the mediators' organizations. The autonomy of units and employers are determinants to understanding the mode of intermediaries’ operations. (Mueller and Jungwirth 2016; Silva et al. 2018; van Horne and Dutot 2017). Moreover, different levels of centralized decision-making influences intermediaries’ function (Kant and Kanda 2019; Mueller and Jungwirth 2016; Sengupta and Ray 2017; Stezano 2018). Especially, the number of stakeholders and employers influence the degree of centralization and the establishment of structures (Mossberg et al. 2018).

Second, communicative processes shape the intermediary’s structure. Organizations differ according to the communication adopted between various internal units (O’Kane, 2018) and external stakeholders, like clients and researchers (Kant and Kanda, 2019). Intermediaries require different communicative competences depending on the use of technological and non-technological knowledge (Kant and Kanda, 2019). The inclusion of external stakeholders, such as customers and project partners, in communication processes is also highlighted (Kant and Kanda, 2019). Conflict management and its formalization, particularly in larger organizations, can also influence intermediaries’ structure (Mueller and Jungwirth, 2016).

Third, the embeddedness of intermediaries in innovation systems depends on its structure. The way in which intermediaries are integrated in the innovation system decides its ability to offer complementary activities (Kant and Kanda, 2019). For example, for intermediaries that operate closely with universities, the capability to absorb knowledge from researchers can directly influence the capability to support the transformation of academic knowledge to market application (O’Kane 2018). Moreover, the embeddedness depends on the structural formation of the innovation system. The presence or absence of central actors or the willingness of incumbent actors to cooperate influences the intermediaries innovative outcome (Mossberg et al. 2018).

The intermediaries’ management team deals with leadership and staff competences, thereby influencing the intermediaries’ innovative capability. The ability to self-organize and manage work (Kant and Kanda 2019), and the competences of intermediaries’ staff (Owen et al. 2014; Readman et al. 2018; Chen and Lin 2018), concerning time management (Mueller and Jungwirth 2016; Readman et al. 2018) and conflict management (Mueller and Jungwirth 2016) in specific, have been used to account for the quality of managing innovation intermediaries. Furthermore, the commitment of responsible staff (Mueller and Jungwirth 2016; Sinell et al. 2018) and the satisfaction their payment (Mueller and Jungwirth 2016; Chen and Lin 2018) influence the intermediaries’ ability to offer their services.

As knowledge brokers interacting with actors in the innovation system, networking and boundary spanning is a relevant activity of intermediaries. Relationships with research institutions, stakeholders and clients are crucial for intermediaries’ management (Alexander and Martin 2013; Garengo 2019; O’Kane 2018; Todeva 2013). Management of knowledge creation, its processing and dissemination are at the core of the business model of innovation intermediaries. The intermediaries’ openness depends on managerial perceptions of what is valuable for the institution (Kant and Kanda 2019; Moilanen et al. 2015) and how knowledge exploitation is seen as part of the dissemination process (Kant and Kanda 2019). A substantial part of exploitation activities depend on the commercialization of close to market products and services, and their management to support successful innovation (Kant and Kanda 2019; Todeva 2013).

Funding and financing, human resources and marketing strategically influence innovative outputs and outcomes of intermediaries as functional assets. Funding and financing depends largely on the capability to mobilize these resources (Readman et al. 2018; Todeva 2013) for intermediaries’ but also for external cooperative activities. Clients’ resources for innovation activities are an important determinant for the output and outcome of the innovation cooperation (Gao and Hu 2017; Kanda et al. 2018; Kant and Kanda 2019; Todeva 2013). This entails the capability of intermediaries to find financial resources (Bush et al. 2017), to allocate them (van Horne and Dutot 2017; Yström and Aspenberg 2017) and to maintain their sustainable flow (Mossberg et al. 2018; Mueller and Jungwirth 2016). Moreover, the size of external funding (Dalziel and Parjanen 2012; Kant and Kanda 2019; Zeng et al. 2010) is decisive for the operation and offer of innovation services. Public sources play a crucial role on regional, national and international levels (Silva et al. 2018; Vivas 2016). The role of intermediaries in the seeking funding is related to the availability of internal resources (Kanda et al. 2018; Chen and Lin 2018; Sinell et al. 2018), funding from host organizations (Sinell et al. 2018), and private (Polzin et al. 2016; Sinell et al. 2018) and public–private funding organizations (Polzin et al. 2016; Sinell et al. 2018). Intermediaries focus their financial support services on different development stages of clients (Gao and Hu 2017; Howells and Bessant 2012). In cases of intermediaries conducting R&D, the relation between R&D and funding indicates the dependency of R&D activities on public funding (Pina and Tether 2016; Thurner and Zaichenko 2015; Todeva 2013; Zaichenko 2018; Zeng et al. 2010).

In the chosen literature, human resources has been described as a critical part for cooperative innovation processes, particularly in the case of transferring tacit knowledge. The contribution of employed staff is estimated by counting the absolute number of graduates (Fukugawa 2018; Landry et al. 2013; Thurner and Zaichenko 2015; Zaichenko 2018) or by surveying the share of graduates (Chichkanov et al. 2019; Pina and Tether 2016). Moreover, the share of R&D expenses for R&D staff is also measured (Zaichenko 2018). Knockaert and Spithoven (2014) use the share of internal R&D-staff as an indicator for the knowledge-intensity of services (Knockaert and Spithoven 2014). Moreover, with the introduction of a large number of innovation intermediaries, the specialization of intermediaries’ influences may impact outputs and outcomes. In order to specialize as proxy, papers use the field of studies (Fukugawa 2018; Readman et al. 2018; Chen and Lin 2018), the time span of experience (Chen and Lin 2018; Silva et al. 2018; Vivas 2016) and the duration required for finding specialized staff (Bocquet et al. 2016; Zaichenko 2018). Moreover, the dynamics of intermediaries is captured by the growth rate of staff (Zeng et al. 2010). The development of the internal capacity is reviewed by analyzing the role of training activities for intermediaries. This includes training of staff (Howells 2006; Silva et al. 2018), exchanging staff with other institutions (Alexander and Martin 2013), setting up post graduate programs (Stezano 2018), and training external staff (Vivas 2016) and students (Alexander and Martin 2013; Readman et al. 2018; van Horne and Dutot 2017). The share of development expenses is used as an explanatory factor (Chichkanov et al. 2019).

Marketing is relevant for intermediaries to be positioned in the innovation system and to act on the relevant markets. This is addressed by surveying the number of (new) clients, size of clients and of knowledge transfer projects (Roxas et al. 2011). Additionally, the revenues in relation to commercialization activities (Landry et al. 2013; Sinell et al. 2018; Zaichenko 2018), e.g. licensing (Stezano 2018), income from research projects (Stezano 2018), service sales (Landry et al. 2013; Stezano 2018) and products (Li et al. 2019) are examined to evaluate the intermediaries’ position in the market. Moreover, the screening of markets and competitors comprises activities such as benchmarking and scanning trending topics (Howells 2006; Readman et al. 2018), developing new markets (Lee and Miozzo 2019), technology foresight (Chen and Lin 2018) and stakeholder mapping (Sinell et al. 2018). Furthermore, challenges for intermediaries on the markets are captured by hampering knowledge creation and transfer of the intermediary, for example, by influencing domestic and international competition (Thurner and Zaichenko 2015). Branding and advertising are used by intermediaries as marketing activities to determine their competitive position. The share of expenditure for advertising (Chichkanov et al. 2019), consistent communication strategies (van Horne and Dutot 2017), creation of a brand name and reputation (Kanda et al. 2018), for example, by receiving recommendations from other clients (Readman et al. 2018) and offering best practices examples (Matschoss and Heiskanen 2017) are surveyed as drivers for innovation.

The industry and the technological field where intermediaries primarily operate determines its position in the innovation process. This depends on the technological and scientific background of the intermediary and its parent organization (Kant and Kanda 2019; Zaichenko 2018), sectoral position (Pina and Tether 2016) and sector-specific services of intermediaries (Benassi et al. 2012; Stezano 2018). In literature, the observation of client sectors are utilized to infer intermediaries’ success for knowledge transfer and value generation. Specifically, the industrial output and growth rate (Zeng et al. 2010), structural data about the competition, (Vivas 2016), size of clients and prospective clients (Landry et al. 2013; Vivas 2016), and innovative potential of sector served (Chichkanov et al. 2019) demonstrate proxies for conditions that require intermediaries’ to be involved in the innovation process. Moreover, the screening of sectorial positioning influences the transfer of knowledge according to existing products, market structure, success rate of projects and capability of human resources (Kant and Kanda 2019; van Horne and Dutot 2017).

The role of location in influencing intermediaries has been discussed in connection to economic geography literature. Innovation systems and regional development literature acknowledge regional disparities to explain the influences of location on the context in which intermediaries operate in the innovation process (Hsieh et al. 2015; Kolesnikov et al. 2019; Lee and Miozzo 2019; Pina and Tether 2016; Shearmur and Doloreux 2019; van Geenhuizen 2018). The location of intermediaries defines its capability to operate during the innovation process and to source new knowledge (Hsieh et al. 2015; Huyghe et al. 2014; Kant and Kanda 2019). Furthermore, cooperation partners (Hsieh et al. 2015; Rodríguez et al. 2018) and stakeholders (Huyghe et al. 2014) are affected by the choice of location. Moreover, the location of clients (Mueller and Jungwirth 2016; Parjanen et al. 2011; Readman et al. 2018), geographical distribution of turnover (Hsieh et al. 2015), other local intermediaries (Schaeffer and Matt 2016), and the regional innovation capability processes (Parjanen et al. 2011; Villani et al. 2017; Vivas 2016; Zeng et al. 2010) consisting of various stakeholders involved in the innovation vary between different regions and impact intermediaries’ work.

The structural characteristics of the networks have been described using the number of ties, density, centrality of intermediaries and configuration between the nodes in the networks (Barrie et al. 2019; Belso-Martinez et al. 2018; Chen et al. 2015; Minguillo and Thelwall 2012). Different organizational characteristics, such as the size (large companies), type (SMEs, research organizations, clients, investors, competitors and suppliers (Hsieh et al. 2015; Landry et al. 2013; Lee and Miozzo 2019; Readman et al. 2018; Silva et al. 2018; Todeva 2013)) can sort different nodes in the network. Furthermore, researchers differentiate between links of the network according to social and cognitive proximities (Huyghe et al. 2014; Parjanen et al. 2011; Villani et al. 2017). Criticalities and weak connections that hamper functioning of the networks may affect the intermediaries’ networking success (Pino et al. 2016; Thurner and Zaichenko 2015). Changes in the behavior of actors using and participating in networks are screened in the dynamic perspective (Barrie et al. 2019; Belso-Martinez et al. 2018).

Probing deeper, the papers explain the role and function of intermediaries in the network to clarify the positioning of innovation intermediaries. The contributions of intermediaries are perceived as difficult to capture since the direct value is difficult to measure (Kant and Kanda 2019). Scholars have discussed boundary spanning (Comacchio et al. 2012; Schaeffer and Matt 2016; van Geenhuizen 2018) and orchestrating activities in the form of matchmaking that supports network members’ knowledge transfer (Huyghe et al. 2014; Mele and Russo-Spena 2015; Silva et al. 2018; Yström and Aspenberg 2017). In order to gather knowledge about this phenomena, the brokerage value between intermediaries and two and more different stakeholders are calculated on the basis of the number of additional links set up by intermediaries (Belso-Martinez et al. 2018; Chen et al. 2015) and the influence that this exerts on their interactions (Mele and Russo-Spena 2015; Parjanen et al. 2011). Links are captured to survey the source of knowledge to diffuse innovation (O’Kane 2018). Additionally, intermediaries are asked to estimate if the connections are new to the network partners (Alexander and Martin 2013).

Networking events managed by intermediaries are used as proxies to analyze the influence of intermediaries on network building. The number of events, number of participants and new contacts resulting from networking activities have been surveyed in specific (Russo et al. 2019; Soetanto 2006). Furthermore, to evaluate intermediaries’ events, the selected literature reviews the sharing of direct contacts, the frequency at which information about events are offered and the use of resources by intermediaries to organize events(Alexander and Martin 2013; Bocquet et al. 2016; Knockaert and Spithoven 2014; Porto Gomez et al. 2016; Shearmur and Doloreux 2019). The involvement of intermediaries in knowledge networks (Kant and Kanda 2019; Readman et al. 2018; Silva et al. 2018; Todeva 2013), the capability to get involved in knowledge networks and the networks intermediaries establish with other intermediaries (Cannavacciuolo et al. 2015; Kant and Kanda 2019; Parker and Hine 2014) are also assessed.

The knowledge sharing and transferring activities have been analyzed in three different dimensions: internal knowledge capacities, knowledge cooperation, and knowledge and technology-sharing services. In innovation systems, intermediaries have been perceived as beneficial since positive knowledge externalities are expected by intermediaries’ activities (Kanda et al. 2018, 2019). Specific knowledge is key for intermediaries to offer an adequate level of quality (Mueller and Jungwirth 2016). In-house innovation activities and R&D form the basis for subsequent technology and knowledge-sharing activities. Not all innovation intermediaries conduct in-house innovation activities or aim to participate in innovation. Often intermediaries create knowledge bases to conduct supporting processes for clients (Mele and Russo-Spena 2015). Intermediaries’ knowledge is differentiated into analytical, symbolic and synthetic knowledge, or is a combination of these (Pina and Tether 2016). Moreover, whether knowledge is tacit or codified is crucial for knowledge transfer and sharing of characteristics (Alexander and Martin 2013; Barrie et al. 2019; Villani et al. 2017). The availability of different knowledge sources determines intermediaries’ capability to identify clients’ needs and match them with fitting cooperation partners (Cannavacciuolo et al. 2015; Howells 2006; Roxas et al. 2011; Chen and Lin 2018; Soetanto 2006). The availability of choice with regard to internal sources and access to external sources plays a central role in innovation for intermediaries (Bocquet et al. 2016; Garengo 2019; Knockaert and Spithoven 2014; Li et al. 2019; Parker and Hine 2014; Silva et al. 2018).

Some studies have analyzed the innovation mode used by intermediaries to interact and contribute: science and technology-based (STI) or the doing-using and interacting (DUI) mode (Lee and Miozzo 2019; Owen et al. 2014). Most intermediary studies have concentrated on the STI-mode. In these cases, researchers analyze the applicability of knowledge creation on a range of basic to applied research (Readman et al. 2018; Zaichenko 2018). Furthermore, an intermediary’s capability to offer knowledge-related services is also defined by its infrastructure, such as laboratories, technical resources, test sites and meeting rooms (Howells 2006; Kanda et al. 2018; Knockaert and Spithoven 2014; Landry et al. 2013; Readman et al. 2018; Thurner and Zaichenko 2015; Vivas 2016; Yström and Aspenberg 2017), and by its application and support of innovation via intellectual property rights (Alexander and Martin 2013; Howells 2006; Li et al. 2019; Sengupta and Ray 2017; Stezano 2018; Thomas et al. 2017; Thurner and Zaichenko 2015; Vivas 2016; Zaichenko 2018).

Knowledge and technology sharing activities are central to the measurement of an intermediary’s output. Knowledge services enable the flow and communication of knowledge (Bush et al. 2017; Elmquist et al. 2016). Research has identified that intermediaries play a role of guidance during knowledge sharing activities (Kanda et al. 2019). These activities are separated into cooperative and contracting activities (Shearmur and Doloreux 2019). Also, the effects of information provision and events have been discussed to describe knowledge-sharing services (Knockaert and Spithoven 2014; Roxas et al. 2011; Silva et al. 2018).

Challenges for knowledge transfers capture the structural aspects of cooperation between intermediaries, clients and knowledge sources (Thurner and Zaichenko 2015; van Horne and Dutot 2017). The interaction for knowledge and innovation collaboration varies between formal and informal interaction (Alexander and Martin 2013). In papers using qualitative methodology, the perception of informal ties has been described as influential but difficult to measure quantitatively. It has been argued that the perception of successful and failing projects influences the dissemination of innovation (Owen et al. 2014; Randhawa et al. 2017; Yström and Aspenberg 2017).

Formal interaction is represented by the variety of collaborative activities. This entails academic and industrial conferences (Alexander and Martin 2013; Porto Gomez et al. 2016; Readman et al. 2018; Silva et al. 2018), collaborative digital platforms (Gao and Hu 2017; Silva et al. 2018), publications in scientific and practice-related journals (Alexander and Martin 2013; Silva et al. 2018; Stezano 2018; Thurner and Zaichenko 2015; Zaichenko 2018), common infrastructure (Alexander and Martin 2013), joint supervision of students with intermediaries and stakeholders (Readman et al. 2018) and collaborative trainings for knowledge-sharing.

Due to the heterogeneous nature of knowledge sharing services, depending on the characteristics of the analyzed sample, studies analyze the general characteristics of contractual services. Studies that cover general services survey the number and volume of services and projects, client’s loyalty and new clients of intermediaries (Russo et al. 2019). Furthermore, projects can be differentiated based on cooperation with competitors and their scope for internationalization (Matschoss and Heiskanen 2017; Porto Gomez et al. 2016).

Specific services offered by innovation intermediaries cover a broad range of supporting services to foster knowledge sharing: This includes the support of companies with testing new products and processes (Knockaert and Spithoven 2014; Landry et al. 2013; Thurner and Zaichenko 2015), offering seminars, workshops and trainings for knowledge-sharing (Knockaert and Spithoven 2014; Randhawa et al. 2017; Thurner and Zaichenko 2015; Yström and Aspenberg 2017), office facilities, administrative and legal support (Howells 2006; Soetanto 2006), and technical advice and R&D support for client innovation (Comacchio et al. 2012; Knockaert and Spithoven 2014; Landry et al. 2013; Randhawa et al. 2017; Stezano 2018; Thurner and Zaichenko 2015; Villani et al. 2017). Moreover, scanning IPR and supporting the application of IPR (Knockaert and Spithoven 2014; Landry et al. 2013; Stezano 2018), access to financial support and investors (Landry et al. 2013) and access to ICT support (Randhawa et al. 2017) is provided by innovation intermediaries. Additionally, innovation intermediaries supply technology screening and scouting activities like market research and feasibility studies (Howells 2006; Knockaert and Spithoven 2014; Landry et al. 2013; Readman et al. 2018; Villani et al. 2017), supporting stakeholders through entrepreneurial activities (Landry et al. 2013; Yström and Aspenberg 2017) and assisting with the introduction and customization of new services and products (Kanda et al. 2018; Landry et al. 2013).

Public policy shapes the context that intermediation takes (Barrie et al. 2019). Therefore, policy goals influence intermediaries directly and indirectly (Polzin et al. 2016). The relevance of intermediation in regional policies and its priorities impact the planning of intermediaries (Mossberg et al. 2018; Mueller and Jungwirth 2016). The support of related innovation and technology policies are relevant for intermediaries’ performance (Kant and Kanda 2019; Mossberg et al. 2018). Additionally, the satisfaction of intermediaries are used to evaluate the capability of innovation systems (Zeng et al. 2010).

Interactions with governments are perceived as vital for agenda-setting (Yström and Aspenberg 2017). Ties to the government and administration is necessary to receive information about funding (Todeva 2013). Too little interaction serves as a problem that prevents stronger cooperation of intermediaries with the government (Thurner and Zaichenko 2015).

Standards and regulations affect the function and operation of innovation (Polzin et al. 2016; Chen and Lin 2018; Sinell et al. 2018). This can vary between regional, national and international regulators (Thurner and Zaichenko 2015). Implementation of international standards on the national and regional level can influence the diffusion of innovation (Kant and Kanda 2019). Intermediaries also participate in standard-setting programs and shape institutions (Howells 2006).

Though innovation culture has been discussed for a long time in business contexts, studies on intermediaries have only recently discovered this topic for further analysis. To begin with, studies have analyzed communication culture of intermediaries. The clarity of communication between intermediaries and stakeholders (Mueller and Jungwirth 2016), the ability to bridge different communication cultures (Chen and Lin 2018), creative communication and the number of ideas to accelerate the innovation process (Parjanen et al. 2011) contribute to intermediaries’ communication culture. Secondly, trust development influences the interaction between various actors. Studies focused on the role of confidential processes (Randhawa et al. 2017; Readman et al. 2018), committing to users’ trust-ensuring mechanism (van Geenhuizen 2018) and the quality of work of cooperating partners (O’Kane 2018; Readman et al. 2018; van Horne and Dutot 2017) to assess the role of trust development. Thirdly, the dynamics of innovation culture changes when innovation evolves and develops. The motivation of stakeholders to be involved in innovation processes depends on the commitment of participants (Mueller and Jungwirth 2016; van Geenhuizen 2018), the intermediary’s motivation and motivating processes (Owen et al. 2014; Parjanen et al. 2011; Randhawa et al. 2017). The perception of neutrality has also been seen as a mechanism to effectively position intermediaries inside innovation systems (Kant and Kanda 2019; Mossberg et al. 2018). Furthermore, the degree of openness during knowledge creation and transferring processes (Li et al. 2019; Parjanen et al. 2011), and the participation and inclusion of different social groups (van Geenhuizen 2018) are also relevant to changes in innovation culture. Finally, the introduction of tools to support cultural dynamics of intermediaries helps foster innovation practices and supports innovation culture (Readman et al. 2018). Instruments like idea generation and storytelling are particularly relevant in this context (Antikainen et al. 2010; Yström and Aspenberg 2017).