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Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
Complex settings and the evolution of the innovation process
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Complex settings and the evolution of the innovation process

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  • Can u pls mail this ppt to me..i am taking a presentation on creativity and innovation..this ppt will be very useful for me...
    sachinvijay2006@gmail.com
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  • 1. Innovation Management in Complex Settings - The Evolution of the Innovation Process Pablo Muñoz PhD Researcher pablo.munoz@newcastle.ac.uk UDD - Santiago, Chile. v2 july ’10 Innovation Studies 2010: An overview of current perspectives on innovation and technological change. Conference Series, K3 Friday, 9 July 2010
  • 2. Agenda About us Innovation studies and technical change From Linear Models to Innovation Systems: An Examination on the Evolution of the Innovation Process Innovation management in complex settings: social construction and actor-networks Friday, 9 July 2010
  • 3. KITE was formed in 2006 to bring together the work of a number of groupings from the Business School and Geography, all of which were concerned with the management of innovation and creativity, policy and enterprise. Our focus is the way in way in which emerging technology trends are interacting with new businesses, management and policy models. You can get a flavour of what we are about from our current projects and our publications. KITE has a strong portfolio of research and consultancy projects from a variety of national and international project funders and partners and a variety of local and regional agencies. Recent studies include: • work on partnership networking architecture in multi-agency environments, • regional science policies, • university contributions to regional development, • processes of learning in city-regions, • university spin off companies, • transformative effects of ICTs on regions. Friday, 9 July 2010
  • 4. Following the centres overall agenda and vision, KITE comprises a number of linked themes. In practice this means that staff come together around specific projects and publications which reflect their interests and expertise, under the direction of the centre directors and executive. Overall these themes connect to a vision of the changing nature of innovation. These linked and cross-cutting themes include : eBusiness at Newcastle Complex Project Innovation Innovation, Sustainability and Enterprise Public Service Innovation University, Government and Industry Friday, 9 July 2010
  • 5. Innovation Studies and Technical Change: An Overview Friday, 9 July 2010
  • 6. Innovation studies and technical change: an overview The emerging structure of a new scientific field Fagerberg et al. 2009 Critical management Industrial economics studies Organisational science Theoretical perspectives: Technological determinism Sociology of science Evolutionary economics (neo-Schumpeterian) and technology Technological paradigms and trajectories Techno-economic paradigms Science and INNOVATION STUDIES Social shaping of technology technology studies Social construction of technology Actor network theory Evolutionary economics Techno-economic networks Socio-technical systems Transition theory Geography and policy Cultural studies Management studies Friday, 9 July 2010
  • 7. From Linear Models to Innovation Systems: An Examination on the Evolution of the Innovation Process Based on Munoz, P. (2009) From Linear Models to Innovation Systems: An Examination on the Evolution of the Innovation Process. Newcastle University Business School. paper id. 4553435 Friday, 9 July 2010
  • 8. The innovation process: towards new representations Friday, 9 July 2010
  • 9. Introduction This presentation critically examines the changing nature of the innovation phenomenon, both in the way it is understood and being practised. This is described, firstly, through a review of the foundations of the first generations of innovation models, especially the key arguments that support the breakdown of the linear IP and its transition to new generations of innovation models; and secondly, through a review of three comprehensive approaches to innovation: Innovation capabilities Cyclic innovation systems Socio-technical systems in transition Friday, 9 July 2010
  • 10. Linear representation The linear representation of the innovation process [IP] is an output driven model, where all the sequence of actions are directed to facilitate the movement of ideas throughout a pipeline, pushed by R&D and pulled by demand. The traditional IP is generally considered as an internal operation not necessary embedded in usual management practices. As a project-based approach, the linear process is dependent on inflows provided by both technology development and user needs; this does not ensure a continuous operation nor allows the interaction between different components and sources. Kyffin, S., & Gardien, P. (2009). Navigating the innovation matrix: An approach to design-led innovation. International Journal of Design, 3(1), 57-69. Friday, 9 July 2010
  • 11. The linear innovation process The diagrammatic model of the innovation process is an effort to condense and clarify the understanding of the innovation phenomenon (Howells, 2005). Although the traditional IP diagram does not necessarily describe the way a process actually operates, it provides a general framework in which its activities and essential features are presented in an interconnected flow. The initial ideas, in which relies the linear IP model, were based on the theoretical framework developed in the 1920s for understanding the relationship between science, technology and economy (Godin, 2006). This model of IP is generally understood as a pipeline; in which a defined sequence of R&D efforts - applied research, development, production and diffusion - transforms inflows of ideas or basic research into a stream of useful innovations. The aforementioned framework was supported by a collective effort, in which industrialists, consultants, economists and academics have tried to explain the mechanism by which science translates into socio-economic progress (Godin, 2006). Godin, B. (2006) The linear model of innovation: The historical construction of an analytical framework. Science, Technology & Human Values, vol. 31(6) pp. 639-667 Howells, J. (2005) The Management of Innovation and Technology. London: Sage. Friday, 9 July 2010
  • 12. Different models From that moment, several authors have presented improved models, in which it is explained the same basic process accordingly to the context in which was created. In 1984 Saren (Buijs, 2003) introduced two different perspectives to the linear IP representation: the department-based view and the activity-based view. Two early models of product innovation: department-based view and activity-based view Source: Buijs, 2003 Buijs, J (2003) Modelling product innovation processes, from linear logic to circular chaos. Creativity and Innovation Management, vol. 12 pp. 76-93 Friday, 9 July 2010
  • 13. Different models Based on this two perspectives, different models - have emerged in the last 50 years: The Roozenburg & Eekels Product Innovation Process (Buijs, 2003) The Archer Innovation Process (Buijs, 2003) The Twiss’s Egg model of Innovation (Howells, 2005) The Schmidt-Tiedemann Concomitance Model of Innovation (Howells, 2005) The Kline Model of Technology Innovation Process (Fernandez, 2005) The Delft Step-by-Step Innovation Model (Buijs, 2003) are just some examples of the broad effort to illustrate this complex phenomenon. Buijs, J (2003) Modelling product innovation processes, from linear logic to circular chaos. Creativity and Innovation Management, vol. 12 pp. 76-93 Friday, 9 July 2010
  • 14. Different models: Roozenburg & Eekels The basic design cycle (1977) Divergence and convergence in the innovation process (1995) FUNCTION START Generation of alternatives ANALYSIS Policy formulation POLICY FORMULATION Evaluation and selection CRITERIA POLICY Generation of new SYNTHESIS product ideas IDEA FINDING Evaluation and selection PROVISIONAL DESIGN NEW PRODUCT IDEAS Generation of design SIMULATION solutions STRICT DEVELOPMENT Evaluation and selection EXPECTED PROPERTIES PRODUCT DESIGN Generation of product alternatives and marketing strategies REALISATION EVALUATION Evaluation and selection VALUE OF THE DESIGN NEW BUSINESS ACTIVITY DECISION APPROVED DESIGN Buijs, J (2003) Modelling product innovation processes, from linear logic to circular chaos. Creativity and Innovation Management, vol. 12 pp. 76-93 Friday, 9 July 2010
  • 15. Different models: Roozenburg & Eekels The Product Innovation Process (1995) PRODUCTION Production DEVELOPMENT plan GENERATING FORMULATING New Product AND PRODUCT Product DISTRIBUTION GOALS AND business PRODUCTION USE policy SELECTING DESIGNING design AND SALE STRATEGIES idea IDEAS MARKETING Marketing PLANNING plan POLICY IDEA FINDING FORMULATION PRODUCT PLANNING STRICT DEVELOPMENT PRODUCT DEVELOPMENT REALISATION INNOVATION Buijs, J (2003) Modelling product innovation processes, from linear logic to circular chaos. Creativity and Innovation Management, vol. 12 pp. 76-93 Friday, 9 July 2010
  • 16. Different models: Archer Innovation Process STRATEGIC PLANNING POLICY FORMULATION 1. establishing strategic objectives. 2. lay down outline timetables, overall budgets and guide lines for innovation. RESEARCH PRELIMINARY RESEARCH FEASIBILITY STUDY product- 1. select an invention, product idea or technological base. 2. identify an area of orientated 1. establish technical feasibility. 2. establish financial viability. 3. resolve critical need, marketing opening, product deficiency or value base. 3. establishing the only problems in principle. 4. propose outline overall solution. 5. estimate work state of the art. 4. prepare outline performance specification. 5. identify probable content of phases 4 and 5 and probably of successful outcome (risk analysis) critical problem areas. DESIGN DESIGN DEVELOPMENT PROTOTYPE DEVELOPMENT TRADING STUDY 1. expand and quantify performance specification, 2. 1. construct prototypes and mock-ups. 2. conduct 1. re-apprise market potential in light of trials. 2. re- develop detailed design. 3. predict tech. performance bench experiments. 3. evaluate technical performance. appraise costing. 3 appraise marketing/production and product cost. 4. prepare design documentation. 5. 4. conduct user trials with prototypes. 5. evaluate problem. 4. revise basic objectives and development design tech. evaluation experiments and user trials. performance in use. budget. 5. revise performance specification. DEVELOPMENT PRODUCTION DEVELOPMENT 1. develop a production design. 2. execute production design documentation. 3. PRODUCTION PLANNING design technical , user and market trials. 3. construct pre-production prototypes. 1. prepare marketing plans. 2. prepare production plans. 3. design packaging, 5. conduct technical, user and market field tests. 6. appraise trials results and promotional material and instruction manuals. 4. design jigs and tools. modify design. MANUFACTURING TOOLING AND MARKET PREPARATION MARKETING 1. construct jigs and tools. 2. construct trial batch of products off tools. 3. test START-UP trail batch. 4. produce marketing materials and print. 5. install marketing machinery. 6. install production control machinery. PRODUCTION PRODUCTION AND SALE 1. initiate marketing effort. 2. commence production and sale. 3. collect market, user repair and maintenance feedback. 4. make recommendations for second generation designs. 5. make recommendations for research. Buijs, J (2003) Modelling product innovation processes, from linear logic to circular chaos. Creativity and Innovation Management, vol. 12 pp. 76-93 Friday, 9 July 2010
  • 17. Different models: TU Delft step-by-step STRATEGIC SITUATION OF DESIGN BRIEF THE COMPANY Internal External Internal External Product analysis of need analysis analysis development bottlenecks analysis Generating Generating search product ideas ideas SEARCH AREA PRODUCT Evaluation DESIGN Internal External Market analysis of need Evaluation introductio bottlenecks analysis n Generating product distribution Manufactur ideas promotion ing and sales PRODUCT LAUNCH Evaluation Evaluation PRODUCT USE Buijs, J (2003) Modelling product innovation processes, from linear logic to circular chaos. Creativity and Innovation Management, vol. 12 pp. 76-93 Friday, 9 July 2010
  • 18. Different models: Kline & Rosenberg Chain-linked model Friday, 9 July 2010
  • 19. Different models: Twiss’s Egg model of innovation EXTERNAL ENVIRONMENT INNOVATIVE INTERNAL ENVIRONMENT Project Idea proposal Project Project Evaluation management systems Project - R&D Creativity - analysis Innovation champion - Design - strategic - Production considerations - Marketing R& DD EPT EPT TD MK THE COMPANY Scientific and Knowledge technological and market knowledge needs Howells, J (2005) The Management of Innovation and Technology. London: Sage Friday, 9 July 2010
  • 20. Different models: Schmidt-Tiedemann Concomitance Model Howells, J (2005) The Management of Innovation and Technology. London: Sage Friday, 9 July 2010
  • 21. Consequences of partial understanding of the innovation process Mental models are important because they help us Problems of partial views of innovation frame the issues which need managing, but therein also lies the risk. If our mental models are limited, then our approach to managing innovation is also likely to be limited. Friday, 9 July 2010
  • 22. Consequences of partial understanding of the innovation process Mental models are important because they help us frame the issues which need managing, but therein also lies the risk. If our mental models are limited, then our approach to managing innovation is also likely to be limited. Friday, 9 July 2010
  • 23. Growing emphasis on systems integration As Rothwell’s categories show, there is growing emphasis on systems integration and collaboration as the basis of the IM. Furthermore, a great body of literature has began to observe innovation not just as a linear chain of research, technology and development; but also as an integrated structure of core competences for institutionalising innovation as an ever evolving open system (Skarzynski et al. 2008) Rothwell’s five generations of innovation models Generation Properties First/second Simple linear models – need pull, technology push Third Coupling model, recognising interaction between different elements and feedback loops between them. Fouth Parallel model, integration within the company, upstream with key suppliers and downstream with demanding and active customer, emphasis on linkages and alliances. Fifth Systems integration and extensive networking, flexible and customized response, continuous innovation. Source: Tidd et al. 2009 Friday, 9 July 2010
  • 24. The breakdown of the linear IP Even though the linear IP model has been broadly used for practice, research and education purposes, there is an extended agreement that the fundamental nature of innovation and the way it is observed, has experimented a radical change in recent years (DeCusatis, 2008). There is an emerging recognition that the source of innovation success goes beyond simply being productive at R&D, improving management practices and delivering new quality products (Teece, 2007). Even so, an increasing number of organisations are investing in innovation, without a clear idea of how these investments translate into business value (DeCusatis, 2008). The Changing Nature of Innovation DeCusatis, C. (2008) Creating, Growing, and Sustaining Efficient Innovation Teams. Creativity and Innovation Management Conference Proceedings, book1, pp. 221-235. Friday, 9 July 2010
  • 25. The breakdown of the linear IP The literature review shows four key arguments that support the breakdown of the linear process: [i] the one-time-project nature of the IP (Davenport, 1993), and its confusion with NPD processes, generally isolate the linear IP of the usual management practices, not embedding innovation as a core competence. [ii] the influence of IT and the growing emphasis on collaboration has opened up the model, which has reshaped the traditional boundaries and has extended the internal resource base of organisations (Collins, 2006) [iii] the increasing need to decentralise innovation activities has facilitated the evolution of conventional innovation models towards complex innovation systems (Van der Duin et al. 2007) [iv] the emerging debate on the dynamism of business performance in changing environments has related innovation with the latest theories on dynamic organisational capabilities (Teece et al. 1997). Teece et al. (1997) Dynamic Capabilities and Strategic Management. Strat. Mgmt. J.vol. 18 (7) pp. 509-533 Collins, L. (2006) Opening up the innovation process. Engineering Management Journal, vol. 16 (1) pp. 14-17 Van Der Duin, P. Ortt, R. & Kok, M. (2007) he Cyclic Innovation Model: A New Challenge for a Regional Approach to Innovation Systems?. European Planning Studies, vol. 15 (2) pp. 195-215 Friday, 9 July 2010
  • 26. Towards new perspectives The following parts describe two different approaches which underpin the latest models of innovation. Firstly, an inner perspective of core competencies, activities and internal systems designed to support innovation efforts; and secondly, a view on systems of innovation, a context- based approach that explains the continuous interaction between the company and its environment. Friday, 9 July 2010
  • 27. Towards new perspectives: systemic innovation capabilities Companies must take a more systemic approach to innovation; it should be seen as a sustainable organisational capability (Skarzynski et al. 2008) instead of a condensed representation of a particular process performed independently of the usual management practices. Organisational capabilities are high level routines which comprise complex bundles of skills and knowledge. These routines give to organisational management a set of decision options for coordinate activities - inflows and processes-, make use of their assets and produce significant outputs of a particular type (Akewi et al. 2006, Winter 2003). Any organisational capability comprises a set of components, which already exist in every basic organisational structure; then the challenge for a company is to modify these organisational components towards building of a systemic capability of innovation; the above accordingly to its culture and objectives (Skarzynski et al. 2008) Winter, SG. (2003) Understanding dynamic capabilities. Strat. Mgmt. J. vol. 24 (10) pp. 991-995 Friday, 9 July 2010
  • 28. Towards new perspectives: systemic innovation capabilities Departing from the traditional IP, a comprehensive review of current literature on strategy, innovation and organisations [table 2], allows identifying new perspectives, which describe a wide range of competencies, activities and organisational resources that support innovation within companies. The aforementioned components can be structured in four interdependent basis - leadership and organisation, people and skills, processes and tools, and culture and values (Skarzynski et al. 2008) - four supporting subsystems - learning activities and knowledge management, collaboration and aquisition activities, in house innovation activities, and entrepreneurial resources deployment (Akewi et al. 2006, Teece et al. 1997, Lee et al. 2008) - and one set of dynamic capabilities, which allow companies to evolve in time by reconfiguring their resource base (Teece, 2007). According to this approach, the traditional activities described by the first IMs should now be allocated throughout the organisation, not in a linear disposition but embedded as core competencies. These, and other specific supporting systems, allow to coordinate activities in order to use the resource base to create, deliver and extract value from innovation. Akwei et al. The Process of Creating Dynamic Capabilities. Teece et al. (1997) Dynamic Capabilities and Strategic Management. Strat. Mgmt. J.vol. 18 (7) pp. 509-533 Lee, H. Kelley, D. (2008) Building dynamic capabilities for innovation: an exploratory study of key management practices. R&D Management, vol. 38 (2) pp. 155-167 Friday, 9 July 2010
  • 29. Towards new perspectives: systemic innovation capabilities Components Description Leadership and Company leaders and organisation aligned around a common organisation vision of innovation. People and Disciplined approach to building innovation capabilities across skills organisation. Recruitment, people development and training. Consistent investment in new ideas, skills, knowledge, expertise and processes. Processes and Systematic approach and supporting tools to enable idea tools generation, pipeline and portfolio management. Culture and Collaborative, open culture and incentives that reward challenging values the status quo. Inclusiveness of all employees, team thinking, team support, celebration and recognition of successes and failures, learning from failures and a positive attitude toward success. Source: The author based on Skarzynski et al. 2008, Tidd et al. 2009, Vardis et al. 2008, Akewi et al. 2006, Teece et al. 1997, Lee et al. 2008, Scott et al. 2004, Nonaka et al. 1998 and Teece 2007 Friday, 9 July 2010
  • 30. Towards new perspectives: systemic innovation capabilities Components Description Learning Processes of acquiring, capturing, sharing and using productive activities and knowledge. Activities to facilitate the spiral of knowledge. knowledge management Collaboration Strategic alliances, research partnership, external networking; and and acquisition search, evaluation and integration of new knowledge and new activities technology In house Consistent investment in R&D, R&T, market monitoring and new innovation product development. activities Development of innovative systems of working with customers and partners, which support collaboration and acquisition activities Internal innovations in structures and processes to support the efficiency of R&D, R&T and NPD. Entrepreneurial Set organisation’s culture, environment and objectives conducive to the resources work of empowered individuals. Promote innovation, experimentation, deployment risk taking and persistence. Dynamic Microfoundations: Distinct skills, processes, procedures, organisational capabilities structures, decision rules and disciplines which undergrid enterprise- level sensing, seizing and reconfiguring capacities; thus, allow companies evolve in time by reconfiguring their resource base. Source: The author based on Skarzynski et al. 2008, Tidd et al. 2009, Vardis et al. 2008, Akewi et al. 2006, Teece et al. 1997, Lee et al. 2008, Scott et al. 2004, Nonaka et al. 1998 and Teece 2007 Friday, 9 July 2010
  • 31. Towards new perspectives: the cyclic innovation model The traditional IP has grown in complexity and diversity of actors involved in the entire process. The performance of an innovation system depends not just on a deliberate plan to become an innovative company, but also on the ability to generate, diffuse and utilise valuable technology throughout the entire system (Carlsson et al. 2002). The IP has changed from a closed, singular innovation project to a continuous active and open innovation system (Van der Duin et al. 2007) Innovation systems [IS] consist of components, relationships, and their attributes (Carlsson et al. 2002). Depending on the level of analysis, it can be defined in several ways: national, regional, sectoral or technological. The structure of these new models relies on the idea that companies can no longer innovate on their own; they need to open up their innovation processes in order to leverage internal and external knowledge (Elmquist et al. 2009). Elmquist et al. (2009) Exploring the field of open innovation. European Journal of Innovation Management, vol. 12 (3) pp. 326-345 Van Der Duin, P. Ortt, R. & Kok, M. (2007) he Cyclic Innovation Model: A New Challenge for a Regional Approach to Innovation Systems?. European Planning Studies, vol. 15 (2) pp. 195-215 Carlsson, B. Jacobsson, S. Holmén, M. & Rickne, A (2002) Innovation systems: analytical and methodological issues. Research Policy vol. 31 (2) pp. 233-245 Friday, 9 July 2010
  • 32. Towards new perspectives: the cyclic innovation model Since early notions on innovation environments, the spatial organisation of innovation has been rising in its importance for socio-economic development. Academic research on innovation systems, such as Clusters Theory (Porter, 1990), Regional Innovation Systems (Cooke 1998), Innovative Milieu (Camagni, 1991) and Learning Regions (Florida, 1995 in Teirlinck et al. 2008), has been widely used for policy making, sectoral development and lately for business strategy. In the corporate context two types of innovation systems should be distinguished: the internal IS, which has already been described as systemic innovation capability, and the external IS, which will be described in the following paragraphs using a cyclic approach recently developed in Delft University of Technology. Friday, 9 July 2010
  • 33. Towards new perspectives: the cyclic innovation model Similar to Rothwell’s model, Van der Duin et al. (2006) analysis have identified four generations of IM from 1950s until 2000s. Even the latest integrated approach to IP, which coordinates networked innovation processes throughout symbiotic partnerships (DeCusatis, 2008), does not combine both innovation systems into a comprehensive model; therefore provides a restricted representation of what happens in the new generation of innovation models, which properties are detailed above. Properties of a new generation of innovation models Properties 1 Innovation is embedded in partnerships 2 Attention is given to an early interaction between science and business 3 Hard knowledge of emerging technologies is complemented by soft knowledge of emerging markets 4 The need for new organisational concepts is acknowledged by emphasising skills for managing networks with specialised suppliers as well as early users 5 Entrepreneurship plays a central role Source: Berkhout et al. 2006:393 Berkhout, AJ. Hartmann, D. Van de Duin, P. & Ortt, R. (2006) Innovating the innovation process. International Journal of Technology Management, vol. 34 (3) pp. 390-404. Friday, 9 July 2010
  • 34. Towards new perspectives: the cyclic innovation model The Cyclic (Berkhout et al. 2006) approach to IS is based on the concept that innovation is an evolutionary and social process of collective learning (Ronde, 2005), therefore dependent on the context where is carried out. Doing so, TUDelft researchers propose a model based on the principles of systems dynamics, which means that equilibrium processes, such as the linear IP, have been replaced by processes of change; where the configuration of components, attributes and relationships are constantly changing (Carlsson et al. 2002). Cyclic Innovation Model: The Innovation Arena The Cyclic Innovation Model [CIM], first developed as an instrument for continuous reform of science and technology (Berkhout et al. 2006), replaces the traditional linear diagram of IP by a circle with four nodes, connected by four interacting cycles of change. The diagram shows that innovation processes take place in synchronised networks, in which knowledge suppliers, design firms, manufacturing companies and users reinforce each other’s activities (Berkhout et al. 2006). Berkhout, AJ. Hartmann, D. Van de Duin, P. & Ortt, R. (2006) Innovating the innovation process. International Journal of Technology Management, vol. 34 (3) pp. 390-404. Ronde, P. Hussler, C (2005) Innovation in regions: what does really matter?. Research Policy, vol. 34 (8) pp. 1150-1172 Carlsson, B. Jacobsson, S. Holmén, M. & Rickne, A (2002) Innovation systems: analytical and methodological issues. Research Policy vol. 31 (2) pp. 233-245 Friday, 9 July 2010
  • 35. Towards new perspectives: the cyclic innovation model The cyclic interaction is the basis of non-linear models for innovation systems. The CIM produces high- order dependencies and as a result creates a synchronised regime of creative interactions between changes in science and industry, and between changes in technology and market; therefore, ‘hard and soft sciences as well as engineering and commercialisation are brought together in a cohesive system of creative learning processes’ (Van der Duin et al. 2007). Cyclic Innovation Model: The Innovation Arena In consequence, the CIM facilitates the interaction of ideas, knowledge, capital, work, designs, products and market needs, all of them highly valuable technical and socio-economic assets. (Berkhout et al. 2006) Berkhout, AJ. Hartmann, D. Van de Duin, P. & Ortt, R. (2006) Innovating the innovation process. International Journal of Technology Management, vol. 34 (3) pp. 390-404. Van Der Duin, P. Ortt, R. & Kok, M. (2007) he Cyclic Innovation Model: A New Challenge for a Regional Approach to Innovation Systems?. European Planning Studies, vol. 15 (2) pp. 195-215 Friday, 9 July 2010
  • 36. Reflexivity and socio-technical systems The complexity, dynamism and multi-dimensional nature of technical change, as well as the interrelated character of contemporary sustainability problems, have led scholars and policy-makers to broaden the understanding of the co-evolution of science, technology and society towards more comprehensive approaches and new forms of reflexive governance capable to comprehend innovations at longer time- scales and wider aggregation levels. Nescher, K. Munoz, P (2010) Understanding stability and change in socio-technical systems: a review on the role of rules in socio-technical dynamics Newcastle University Business School (id.6764864) pp. 1-14 The multi-actor network involved in socio-technical regimes. Geels, F. (2002) Technological transitions as evolutionary reconfiguration processes: a multi- level perspective and a case-study. Research Policy, vol. 31 (8-9) pp. 1257-1274. Friday, 9 July 2010
  • 37. Reflexivity and socio-technical systems Government-sponsored research programmes in The Netherlands and in the UK, based on insights of multiple disciplines, i.e. evolutionary economics, sociology of science and technology, political science and cultural studies, have opened up of the 'black box' of technology and institutions towards the development of new theories and methods such as socio-technical systems [STS], multi-level perspective [MLP] and transition management [TM], which are characterised by a combination of "agency, complexity, uncertainty and optimism" and have resulted useful when it comes to analysing long-term socio-technical dynamics, systems innovation and the aforementioned co-evolution. Geels et al. (2008) Editorial: The dynamics of sustainable innovation journeys. Technology Analysis & Strategic Management, vol. 20 (5) pp. 521-536. The multi-actor network involved in socio-technical regimes. Geels, F. (2004) From sectoral systems of innovation to socio- technical systems Insights about dynamics and change from sociology and institutional theory . Research Policy vol. 33 pp. 897-920 Shove, E. & Walker, G. (2007) Caution! Transitions ahead: politics, practice and transition management. Environment and planning A. Geels, F. (2002) Technological transitions as evolutionary reconfiguration processes: a multi- level perspective and a case-study. Research Policy, vol. 31 (8-9) pp. 1257-1274 Friday, 9 July 2010
  • 38. Reflexivity and socio-technical systems The socio-technical approach to systems innovation comprises not only the production side, where innovations emerge, but also the diffusion and use of technology. The latter represent a key element in modern societies and require resources and human agency embedded in societal groups to accomplish such societal functions that constitute the basis of a modern mode of development. Nescher, K. Munoz, P (2010) Understanding stability and change in socio-technical systems: a review on the role of rules in socio-technical dynamics Newcastle University Business School (id.6764864) pp. 1-14 The multi-actor network involved in sociotechnical regimes. This perspective appears as broader than traditional sectoral approaches to system innovations. It considers a wide range of social actors and focuses particularly on the coordination activities within groups and the interdependent activities and alignments between different groups. Geels, F. (2002) Technological transitions as evolutionary reconfiguration processes: a multi- level perspective and a case-study. Research Policy, vol. 31 (8-9) pp. 1257-1274 Friday, 9 July 2010
  • 39. Reflexivity and socio-technical systems Based on the aforementioned ideas and on Nelson and Winter's (1982) conceptualisation of technological regimes, authors have widened the analytical scope to socio-technical regimes by considering not only cognitive routines, but also [i] semi-coherent sets of rules capable to drive institutionally embedded practices, product characteristics, skills, procedures and ways of defining problems (Rip et al., 1998); [ii] interdependent networks of users, scientists, policy-makers and societal groups capable to influence technological trajectories, and [iii] artefacts and technical elements (Geels, 2004). Rip, A. & Kemp, R. (1998) Technological change. Human choice and climate change (1998) vol. 2 pp. 327-399 Geels, F. (2004) From sectoral systems of innovation to The multi-actor network involved in sociotechnical regimes. socio-technical systems Insights about dynamics and change from sociology and institutional theory . Research Policy vol. 33 pp. 897-920 Geels, F. (2002) Technological transitions as evolutionary reconfiguration processes: a multi- level perspective and a case-study. Research Policy, vol. 31 (8-9) pp. 1257-1274 Friday, 9 July 2010
  • 40. Reflexivity and socio-technical systems This inter-group coordination resulting from the influence of rules, as well as stabilising mechanisms that lead to lock in and path dependency [i] allow regimes of socio-technical configurations to remain stable and working. Configurations that work, characterised by dynamic stability and incremental and cumulative changes along technological trajectories. The multi-actor network involved in sociotechnical regimes. Geels, F. (2002) Technological transitions as evolutionary reconfiguration processes: a multi- level perspective and a case-study. Research Policy, vol. 31 (8-9) pp. 1257-1274 Friday, 9 July 2010
  • 41. Socio-technical systems and the multi-level perspective However, although socio-technical regimes account for stability of STS, changes do take place within them, not only in terms of reproduction, but also as a shift from one socio- technical configuration to another. To explain these processes of change and the overall dynamics within STS, scholars have developed a multi-level approach in which socio-technical regimes interact with emergent niches and a socio-technical landscape i.e. deep structural trends that change slowly and influence the niches and regimes internal dynamics. Verbong, G. & Geels, F. (2007) The ongoing energy transition: Lessons from a socio-technical, multi-level analysis of the Dutch electricity system Multi levels as a nested hierarchy (1960-2004). Energy Policy, vol. 35 (2) pp. 1025-1037 5 regimes - Science regime - Technology regime - Market regime (user preferences) - Industrial regime - Policy regime - Socio-cultural regime Geels, F. (2002) Technological transitions as evolutionary reconfiguration processes: a multi- level perspective and a case-study. Research Policy, vol. 31 (8-9) pp. 1257-1274 Friday, 9 July 2010
  • 42. Socio-technical systems and the multi-level perspective Systems in transition A dynamic multi-level perspective on transitions As long as socio-technical regimes remain stable and aligned, radical innovations have few chances to survive in the system. However, if tensions and mis-alignments occur in the internal dynamics of socio-technical regimes, this creates windows of opportunity for radical innovations: they emerge from niches, breaking through into mainstream markets, competing with the existing regime and eventually they begin a process of replacement of a socio-technical system for another. Nescher, K. Munoz, P (2010) Understanding stability and change in socio-technical systems: a review on the role of rules in socio-technical dynamics Newcastle University Business School (id.6764864) pp. 1-14 Geels, F. & Schot, J. (2007) 'Typology of socio-technical transition pathways'. Research Policy, vol. 36 (3) pp. 399-417. Friday, 9 July 2010
  • 43. Socio-technical systems and the multi-level perspective Systems in transition Four phases can be distinguished in this process of change: A dynamic multi-level perspective on transitions 1. Radical innovations emerge in niches outside of mainstream markets but in the context of existing regime and landscape development. 2. The radical novelty moves towards small market niches, where selection criteria are different form the existing regime 3. The third phase is characterised by the emergence of windows of opportunity, in which these new technologies, developed in niches and carried by a new network of social groups, create competition with the established regime. 4. The entrance of the new technology into the mainstream market, which has created tension, instability and competitive relationships within established socio-technical regime, it may lead to replace the existing STS. Once a transition has taken place a new period of dynamic stability sets in. Geels, F. & Schot, J. (2007) 'Typology of socio-technical transition pathways'. Research Policy, vol. 36 (3) pp. 399-417. Friday, 9 July 2010
  • 44. Final remarks Friday, 9 July 2010
  • 45. Final remarks The linear representation of IP, originally used to explain the relationship between science, technology and development is no longer useful to understand a multidimensional phenomenon. Radical changes across companies have generated new environments in which business processes and ideas cross traditional boundaries and interact with others actors in an ever-changing complex system. From an internal perspective, innovation can not be treated just as corporate initiative or be isolated in one-time-project generally related to R&D or NPD. Innovation has to be developed as a set of distinctive activities that has to permeate the entire organisation. (Skarzynski, et al. 2008) Friday, 9 July 2010
  • 46. Final remarks On the other hand, the growing emphasis on integration and collaboration and the increasing need to decentralise innovation activities has lead companies to cooperate closely with other actors in systems of innovation. In consequence, the linear models - technology push, demand pull, coupling, integrated and network - naturally evolve into a new interpretation of the way innovation works; which, from a business perspective, considers innovation as an internal core competence that continuously interacts with others actors in a social process of collective learning. The function of these systems is still the same: generate, diffuse and utilise technologies that have socio-economic value. For this, and considering these new scenarios, models like CIM contextualise the IP and facilitate a symbiotic interaction between knowledge, technology, capital, products and market needs across the entire system, which is difficult to achieve in a model where science is at the beginning of a pipeline and market is at the the end of it. Friday, 9 July 2010
  • 47. References AMBROSINI, V. BOWMAN, C. & COLLIER, N. (2009) ‘Dynamic Capabilities: An Exploration of How Firms Renew their Resource Base’. British Journal of Management, 20(s1), s9-s24. AKWEI, C. PEPPARD, J. & HUGHES, P. (2006) ‘The Process of Creating Dynamic Capabilities’. White paper submitted to the British Journal of Management. Bedfordshire: Cranfield University School of Management. BERKHOUT, A. HARTMANN, D. VAN DER DUIN, P. & ORTT, R. (2006) ‘Innovating the innovation process’. International Journal of Technology Management, 34(3/4), 390-404. BERKHOUT, A. VAN DER DUIN, P. & ORTT, R. (2007) ‘New ways of innovation: an application of the Cyclic Innovation Model to the mobile telecom industry’. International Journal of Technology Management, 40(4), 294-309. BUIJS, J. (2003) ‘Modelling Product Innovation Processes: from Linear Logic to Circular Chaos’. Creativity and Innovation Management, 12(2), 76-93. CAMAGNI, R. (1991) ‘Introduction: from the local milieu to innovation through cooperation networks’. In CAMAGNI, R. (ed.) (1991) Innovation Networks: Spatial Perspectives. London: Belhaven Press. CARLSSON, B. JACOBSSON, S. HOLMÉN, M. & RICKNE, A. (2002) ‘Innovation Systems: Analytical and Methodological Issues’. Research Policy, 31(2), 233-245. COLLINS, L. (2006) ‘Opening Up the Innovation Process’. IEE Engineering Management Journal, 16(1), 14- 17. COOKE, P. (1998) ‘Introduction: Origins of the Concept’. In BRACZYK, H. COOKE, P. & HEIDENREICH, M. (Eds.) (1998) Regional Innovation Systems: The role of governance in a globalized world. London: UCL Press. DAVENPORT, T. (1993) Process Innovation: Reengineering Work through Information Technology. United States: Ernst & Young. DECUSATIS, C. (2008) ‘Creating, Growing and Sustaining Efficient Innovation Teams’. Creativity and Innovation Management Journal, 17(2), 155-164. EASTERBY-SMITH, M. LYLES, M. & PETERAF, M. (2009) ‘Dynamic Capabilities: Current Debates and Future Directions’. British Journal of Management, 20(s1), s1-s8. ELMQUIST, M. FREDBERG, T. & OLLILA, S. (2009) ‘Exploring the field of open innovation’. European Journal of Innovation Management, 12(3), 326-345. EISENHARDT, K. & MARTIN, J. (2000) ‘Dynamic Capabilities: What are they?’. Strategic Management Journal, 21(10-11), 1105-1121. GODIN, B. (2006) ‘The Linear Model of Innovation, The Historical Construction of an Analytical Framework’. Science, Technology and Human Values, 31(6), 639-667. LEE, H. & KELLEY, D. (2008) ‘Building dynamic capabilities for innovation: an exploratory study of key management practices’. R&D Management, 38(2), 155-168. HELFAST, C. FINKELSTEIN, S. MITCHELL, W. PETERAF, M. SINGH, H. TEECE, D & WINTER, S. (2007) Dynamic Capabilities: Understanding Strategic Change in Organizations. Singapore: Blackwell. Friday, 9 July 2010
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  • 49. Innovation Management in Complex Settings - The Evolution of the Innovation Process Pablo Muñoz PhD Researcher UDD - Santiago, Chile. v2 july ’10 Innovation Studies 2010: An overview of current perspectives on innovation and technological change. Conference Series, K3 Friday, 9 July 2010

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