Innovation generating model - expanded triple helix model

Ramstad, Elise, Ph.D.


This blog presents the Innovation generating model and its principles. The model was created in order to serve as a systemic and scalable framework and tool for the broad-based innovation activity and policy. 




Figure 1. Innovation generating model - expanded triple helix

(Ramstad 2003; 2005; 2008; 2009a; 2009b).

 

Background - Need for new systemic frameworks and tools for broad-based innovation-enhancing policy
 

Today many countries agree upon the importance on innovation-enhancing policy as a source for to gain competitive advantage. In Finland and several other industrialised Western countries instead of traditional technology-oriented innovation policy, the focus is today more on broad-based perception of innovation such as technological, business, organizational, service and policy innovations (Finnish innovation policy strategy 2008). 

 

Both the national innovation system (Lundvall, 1992; Miettinen, 2002, Nelson, 1993) and the triple helix model (Leydesdorff & Etzkowitz, 1998) have played an important role for innovation research and in shaping innovation activities and policies in different countries. However, in spite of their important contributions to the innovation literature, these are not systematic frameworks in order to support innovation activities broadly. It is argued that there is a need for an improved relationship between traditional innovation policy and organizational and service development.

 

The innovation generating model differs from the traditional national innovation system concept for a number of specific reasons. 1) Firstly, social innovations and their characteristics are traditionally not included in the science and technology policy, hence, in the debate on the national innovation system. The new model is intended to emphasize the importance of social innovation (e.g. organizational, service and policy innovations) alongside technological innovations. Contrary to the traditional neoclassical explanations for economic growth, it is seen that both social and technological innovations are intertwined endogenous factors. 2) Secondly, the national innovation system concept has been criticized for focusing on public sector organizations even though private businesses, ultimately, are the key players in innovation (Steinbock, 2006; Schienstock, 2006). The innovation generating model concept sees businesses and other work organizations in relation to public-sector organizations as equal partners with different roles. Work organizations in general are at the heart of innovation; it is here where the transformation of knowledge into new innovative products and services takes place. The higher the efficiency and quality of the public sector, the better it is able to support the educated workforce entering working life and staying at work, and this way support the competitiveness of the companies that are its clients. 3) Thirdly, the innovation generating model focuses not only on the inter-organizational relationships, but also on the internal development of organizations. The focus is particularly on the high-involvement innovation practices (such as autonomous team-working, relationship between management and employees, employee-driven innovation, and the use of innovation tools, which can enhance the productivity and the quality of working life (QWL) (Ramstad, 2014). 4) Fourthly, according to Schienstock (2006) the system of innovation concept represents a top–down approach, as it focuses on establishing supportive institutional settings. What is important in the innovation generating model is that the changes on different levels are interrelated. Without knowledge about the micro-structures we might get little out of attempts to change institutions and organizations at the meso- and macro-levels.

The innovation generating model is an application of the triple helix model as it focuses on
examining the interfaces between the various parties. It is thought that the evolution of new, creative innovation environments stems from the differences and complementarities between the players involved and their practices and their integration i.e. learning from complementarities. However, in the traditional triple helix model, the idea is that knowledge is generated in cooperation between universities, businesses and policymakers. The innovation generating model differs from this narrow triple helix model in that it addresses a wider range of organizations.

Ideas leading to innovations can come from several sources and can emerge at any stage of the
innovation process. 1) Firstly, policy-makers is understood to refer not just to the public authorities but to industrial relations system i.e. the trade unions and employers’ associations. It is argued that the social partners play an important role in the field of organizational development e.g. by collective bargaining, providing guidance and taking part in improving working conditions. For example in Finland the organizing rate is high, while about 75 per cent of employees are members of trade unions. Issues of organizational development are more sensitive than the technological development, as it is closely linked to the issues of the employer’s right of direction. 2) Secondly, the challenge of achieving a productive, sustainable and innovative working life is understood to concern not only businesses but also public sector and third sector work organizations. 3) Thirdly, information disseminators (mediator organizations) are needed in addition to the information generated by universities and research institutions. These information processors may include polytechnics, other educational institutions, private consulting firms or development companies that are seen as an integral part of the knowledge infrastructure. 4) Fourthly, whereas the narrow triple helix model only involves three kinds of relationship, the expanded triple helix model may involve any number and level of network relationships and sub-systems. In this way it is scalable. In Figure 1, the six lines depict the diverse relationship constellations in the model. 5) Fifthly, the new model also suggests for potential outcomes and their interrelationship and learning mechanisms i.e. how new knowledge can be created, which is not the case of the narrower model.


Structure of the innovation generating model

In the system-level discussion, the parties in innovation generating model are roughly divided into

three categories based on their different knowledge bases:

• Work organizations (different sectors, different sizes, managers and employees, suppliers and customers)

• Expert organizations (universities, continuing education centres, research institutions, polytechnics, adult education centres, educational institutions and private consulting firms); and

• Policy-makers (financing organizations, industrial relation system e.g. social partners, public authorities, the European Commission, and regional players such as Employment and Economic Development Centres, State and Regional and economic development coordinators).

In the model the work organizations have practical knowledge on development and innovation activity. The work organizations (public, private and third sector) are seen as ”problem-owners” and represent organizations that carry out development and innovation activities by themselves or with the help of external expertise and with a possibility of getting financial support and other types of support for development activities from policy-makers. However, in addition to being problem owners based on the new thinking of knowledge production, work organizations can be seen as a source of knowledge that can be used in order to improve the knowledge base by expert organizations and policy-makers.

 

RDI-system i.e. expert organizations in the system are groups of experts that represent the scientific, educational, developmental and market-orientated (both private and public) expertise required in development activities and more broadly in knowledge generation. A diverse group of expert organizations can be characterized as a knowledge infrastructure that processes different types of knowledge. In the model the relationship between work organizations and expert organizations is equal, and learning can take place in both directions instead of a more traditional and hierarchical consulting relationship. Since expert organizations cover a wide variety of organizations, their role in a network may vary a great deal. In addition to their expertise in technology or organizational theory and development their role in the collaboration can be in pedagogical questions, especially the creation of the social structures of learning and learning situations and in maintaining them. From the production of the new knowledge perspective it is specifically the coalitions of different types of expert organizations that could offer a wider variety of expertise to work organizations in a network, while also supporting the development of the expertise of the expert organizations involved. In this work the focus is particularly on this type of collaboration. Collaboration between different expert organizations could reinforce multidisciplinary research and the combination of different forms of operation (research, development, dissemination of information, development of methods).

 

Policy-makers refer broadly to the governmental organizations and industrial relations system e.g. social partners in different levels (national, regional, local). The policy-makers have traditionally had an indirect and passive role in the science and innovation system and policy, while they have focused on guidance, advice, supervision and finance. For instance, legislation and comprehensive collective agreements are ways to influence the labor market, such as employment contracts, working hours, equality, cooperation, and safety and occupational health care. Today it is argued that the decision-makers could have a new, more dynamic role in organizational development (Haatanen, 2001;  Kevätsalo, 1999; Niemelä, 2003; Niiranen, Pakarinen, Kuusela & Andersson, 2002). This does not just refer to the representatives of the labor market organizations but to the authorities, funding bodies and regional players. Through participating in collaboration, the policy-makers can receive information on current problems and how legislation actually works in practice as a basis for decision-making in the future. At the same time they enjoy superior coordination and facilitation ability across a range of institutions and organization ability in a dialogue between various actors. (Ramstad, 2005; 2008.)
 

The innovation generating model offers a complex perspective on the production, use and

dissemination of knowledge. It provides a looser forum alongside the official arena for discussing how to solve complex problems in working life, and it can be examined, for instance, from the perspective of the role of various players, the learning that takes place at different levels (internal, inter-organizational, system), and the various forms of activity of the collaboration (research, teaching, policy-making, development, crowdsourcing) or the different types of collaboration. The crowdsourcing is seen as an important tool in order to obtain new ideas or solutions from the broader community. At best, the innovation generating model. can operate as a learning forum for the parties involved and thus promote innovation activity and various forms of collaboration.

The main theoretical principles of the innovation generating model - expanded triple helix

The innovation generating model is seen as a theoretical framework and analytical tool for the new rationale of innovation studies that also acknowledges the systemic role of innovations. The innovation generating model can be viewed as a broad platform to jointly create, exchange and reflect upon information and knowledge (problems, created solutions and outcomes) across diverse knowledge systems. The model aims at long term sustainable solutions in order to get simultaneous improvements in productivity and the quality of working life (Ramstad, 2008). The sustainability perspective means that the productivy and QWL are seen as interconnected.

The main characteristics of the meta-level innovation generating model are the following:

a) Interrelationship between the knowledge systems at different levels: The innovation

generating model is a systemic framework and an analytical tool of different knowledge
systems: micro-, meso-, and macro-systems and their relationships (figure 1). The three main
knowledge systems are the policy-makers, expert organizations and work organizations,
which in turn consist of different types of subsystems (hybrids). The heterogeneity of
knowledge systems broadens the problem-solving capacity and hence makes development
possible, which is more accountable to societal needs than would be possible in more
homogeneous systems. While it is impossible to change the whole system at the same time,
the innovation generating model calls into question the interrelationships of the systems (the
subsystem and macro-level system). For example, we need to ask how the education
systems and labor markets could become more supportive to the micro-level organizations.
On the other hand there can be lot of slack and incompetence in the microstructure, whereas
interaction in a wider setting may help overcome such weaknesses. The subsystems of the
innovations are embedded in the wider set of institutions that shape people and relationships
between them. In addition to problems, also the created solutions, measures and outcomes of at micro-level need to be linked to macro-level outcomes e.g. productivity and the quality of working life (QWL). This is, however, a challenging task - how to link the micro-level effects to the macro-level measurement indicators. It is, though important the the micro-level outcomes can be shown also as national level effects in the long term. At society (macro) level, in order to success to solve complex and challenging development issues in a country, there is a need for joint understanding and same direction of the whole system. This conserns both political direction, participation of social partners, and support from workplaces and the RDI system.

b) Innovation and knowledge creation as a social matter: Contradictory to the standard
economics that assume knowledge as a property of an individual, in the innovation
generating model knowledge is seen as a social property based on interaction. Language,
common meanings, trust relationships, shared routines and standards are shared within
communities. The model does not distinguish between the producers and users of
knowledge, but sees the participants as subjects of joint knowledge creation. Innovation is
generated as the result of interaction between different complementary knowledge bases.

c) Multisubjective goal orientation approach on innovation interaction: The multisubjective

approach refers here that in addition to joint objectives (visio, goals, outcomes in P & QWL) and joint problem-solving, the players have their own interests that can be served as a part of the broader innovation system. In a complex arrangement such as innovation generating model, functions can no longer be expected to correspond in a one-to-one relation with institutions. The activities have to serve different players. The challenge with the model is to create best potential for problem-solving for reflexive with the help of different point of view and activities. The aim is not primarily intended to create consensus among players, but instead new qualitatively improved knowledge and solutions.

The integration of innovation activity and organization's development may result multiple outcomes in participating units. Outcomes of networks can be realized in different levels in terms of the actor of learning. They can create benefits in addition to workplaces, RDI units, policy makers, also to the broader society as a whole (Ramstad, 2009). The more comprehensive development of work organizations, more qualified solutions, increased innovation capabilities alongside increased productivity and the quality of working life (QWL). Reinforcing knowhow (expertise, education, methods and services) within the innovation infrastructure, i.e. the units providing innovation services. Policy-makers can get improved expertise on organizational development and innovation activities in practice, and will be able to re-direct their strategies and policies based on joint activities. The final goal of the model is to create improvements in productivity and the QWL (sustainable perspective of the model), more qualified and solutions and better knowhow in society in long term.

d) Reflexive learning process: In order to guarantee the quality of knowledge and participation

it is suggested that the interaction should be based on a reflexive learning process which
refers here to self-reflexivity, reflexive benchmarking and reflexion on relationships. The
self-reflexivity calls attention to one’s own knowledge and development oriented cognitive
state. Self-reflexivity is very challenging and not possible without relating to oneself as a
part of a broader system by relational thinking. That is why also reflexive benchmarking,
which is distinct from mechanistic benchmarking based on a more universalistic view of
best practices that can be transferred as ready-made objects (Schienstock, 2004). In reflexive
benchmarking, the interest of the parties involved focuses on finding operational
correspondence that give rise to generative ideas in different organizational contexts
(Alasoini et al., 2006). In the reflexive benchmarking the beliefs, values and activities of knowledge systems are related to other knowledge systems. The reflexion on relationships
refers to the quality of diverse collaboration, which is important particularly while the aim is
to create new modes of collaboration (Ramstad, 2008).

The simultaneous learning in the innovation generating model can be illustrated with first and second order learning cycles, which are connected to each other. The first order learning cycle refers to the development of the procedures of the work organizations and joint problem orientation. The first level results are context specific, local results that are difficult to disseminate to other workplaces as such, but only as general ideas. The second learning cycle, provides a learning forum for other practitioners (R&D units, policy makers, other companies) involved and interested in more abstract and meta-level analyses of development and innovation activites. Here the aim is to support generative learning and generate new practices, research ideas, strategies, approaches and improve the productivity and the QWL in a society as a whole (see more Ramstad, 2011, 202-204, 2008.)

Figure 3. Parallel learning cycles of the Innovation generating model.

 

The knowledge understood here is not restricted in the work organization, but more
broadly to all knowledge and knowledge systems related to the process of the knowing (creation,
use, dissemination) e.g. to research, consultation, education, policy-making, development
activities and crowdsourcing. Compared to some earlier models e.g. the open innovation model
(Chesbrough, 2003) the principles, players, mechanisms and potential outcomes of the model are
being specified. According to Koivisto (2008) the problem with the open innovation model is that it
remains loose, while it does not categorize the concrete preconditions or the internal social
mechanisms of the model.

 

The use of the model

The innovation generating model - expanded triple helix and its’ diverse versions have been used in several occasions. So far the model has been used as a 1) framework for broad-based innovation programme and project activity (Ramstad, 2009b), 2) a framework for the workplace development programmes in Finland (TYKE & Tykes) (Alasoini & Ramstad, 2007a; Lahtonen & Rouhiainen, 2008), as a framework for managing participatory innovation processes in the change process of social and health care sector (Saarisilta & Heikkilä (Eds.) 2015), as a framework for project of employing elderly people (Haula, 2012), as a framework for analysing and evaluating learning networks (Ramstad, 2003; 2005; 2009c), as a framework for paradigms of working life research(Alasoini, 2011), as a framework for future learning networks (Ramstad, 2011), and as a framework for studying to diverse knowledge systems and their role in knowledge production such as universities, polytechnics, education and training institutes and consultancies (Ramstad, 2007; 2009b). Recently it has been used as a framework for analyzing European innovation policies (Makó & Illéssy, 2015 forthcoming). It seems that the model can serve as broader framework for innovations in a society by increasing the understanding of the diverse policies, innovations, players, relations and activities related to the innovation process. In the future the challenge is to apply the model in the diverse policy systems levels of the society.


History of the model

The first ideas of the model were presented in 2001 in the Ph.D. research paper to Helsinki University of Technology. The basic model has been mainly the same since then. Some small adjustments to the figure and more comprehensive theoretical grounds has been added to the model. In 2003 the core ideas of the model were presented in the Learning network -seminar. The model was also used as a evaluation framework for 50 learning networks in Finland (Ramstad, 2003, 2005). The more comprehensive presentation of the model is from the year 2008. In this study the broad theoretical framework was presented. In 2011 the model was used as a framework for future learning networks (Ramstad, 2011).



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