Tag: economy

Schematic overview to understand the complexity of the Innovation Ecosystem (Infographic)

The Innovation Ecosystem

The Innovation Ecosystem is one of the most under-researched topics. One the one hand because policy researchers usually tend to focus more on polls, elections and international collaboration and business researchers usually tend to focus more on organizations and interorganizational collaborations. However, publisher Edward Elgar has repeatedly published interesting works on innovation policy, innovation systems and the like. An ecosystem of innovation could be described as, quoting Wikipedia, the flow of technology and information among people, enterprises and institutions [which] is key to an innovative process. It contains the interaction between actors who are needed in order to turn an idea into a process, product or service on the market. The Innovation Ecosystem is extremely important to the economy and welfare of a country or region. It is one of the main drivers of GDP. Over the past decades more research has been done on the dynamics behind these ecosystems and its subsystems. Below you'll find a schematic overview of the innovation ecosystem. It will take you to the download side of Innovative Dutch, where you can download it in full resolution.

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    System Dynamics within the Ecosystem

    The Innovation Ecosystem could be defined as a dynamical system. Dynamical systems are a theory first mentioned by Jay Forrester in the 50s and applied to a wide range of disciplines such as demography, ecology, evolution, economy and sociology. It suggests that systems contain complex feedback loops, causal links, flows, stocks, delays among the agents. Because these agents influence each other with complex logic, mostly non-linear, it is very hard to predict how the system will behave. Usually the basic feedback loops consist of positive loops, that will keep enhancing itself without limitation. However, the system also holds several negative loops, that will discontinue the positive processes. Systems usually continue switching between positive flows and negative flows, making fluctuations very common. For instance, in climate, is it common to have fluctuations per the hour, per the day, per the season, per the year and over long era's. The same holds for the economy or for rabbit populations. Complex dynamical systems can be mathematically programmed. The following example shows how a system with only two actors can even achieve chaos within a few cycles when there are small anomalies in its initial circumstances. This is called the chaos theory: imagine the long-term effect a small change can have. For instance, the effect of a local forest fire on the weather world-wide. Or losing a coin on the local economy.Innovation ecosystems work the same. There are many agents, that are influences by a wide range of actors. Imagine the effect of low-level corruption on a national ecosystem or the effect of a successful start-up on the world-wide ecosystem.

    Innovation subsystems

    There are many different subsystems of innovation, for instance:

    • National Innovation Systems: 'The network of institutions in the public and private sectors whose activities and interactions initiate, import, modify and diffuse new technologies' (Freeman, 1987). Another word that is used on a regular basis for NIS is 'Institutional Environment' – which describes the institutionalization of innovation policy in governments, research institutes, advisory boards and educational institutes.
    • Regional Innovation Systems: 'The regional innovation system can be thought of as the institutional infrastructure supporting innovation within the productive system of a region.' (Asheim & Gertler, 2005). While NIS focuses more on the institutional environment of innovation, RIS usually focuses more on soft factors, such as network characteristics, trust, identity, cosmopolitism, quality of life and culture. These factors are often the first things if we think about successful RIS such as Grenoble, Silicon Valley, Helsinki or Brainport.
    • Sectoral Innovation Systems: during the early zero's more attention has come to sectoral innovation systems. In contrary to NIS and RIS, SIS focus on globally active sectors that function independently of the institutional environment. For instance, the Dutch government now prolongs the Top Sector Policy, focusing on different global sectors. NIS and RIS are now mainly supportive to SIS in the Netherlands. The Top Sectors defined are Agri-Food, Chemicals, Creative Industry, Energy, High-Tech, Logistics, Life Sciences & Health, Agriculture and Water. Another institute, the EIT, is also focusing on these sectors (Climate, Digital, Health, Raw Materials and Energy).
    • Education Systems: these are the ecosystems that surround educational institutes, such as universities. This group is often referred to as the economics of education. An well-performing education system usually increases expenses because of increased income, increases in return on investments because of higher (company) incomes and increases in productivity. It enables academic inflation.
    • Macro-economical Systems: this system refers to basic economics: output and income (GDP, GRP), unemployment and inflation and deflation.
    • Start-up Systems: a startup ecosystem is a small-scale system that enables startups to arise. It involves aspects such as ideas, inventions, research, education, startups, entrepreneurs, angel investors, seed investors, mentors, advisors and events and is supported by universities, incubators, accelerators, facilitators, investors, coworking spaces and venture capitalists.
    • Innovation Management Systems: these refer to a cyclical view of turning ideas into innovation; I've wrote a post about that earlier.
    • Cluster or Science Park Systems: In 2000 Porter already wrote: 'Geographic, cultural, and institutional proximity provides companies with special access, closer relationships, better information, powerful incentives, and other advantages that are difficult to tap from a distance. […] Competitive advantage lies increasingly in local things – knowledge, relationships, and motivation – that distant rivals cannot replicate.' (Porter, 2000). Clusters usually go the four phases: emergence, growth, maturity and renewal. The reason why clusters seem to work well is proximity. Cooke et al. (2011) suggest 7 types of proximity, 1) Geographic proximity – referring to the physical distance between actors, 2) cognitive proximity – referring to the closeness in ways of thinking between the actors, 3) communicative proximity – referring to the closeness professional language between the actors, 4) organizational proximity – referring to the arrangements that organizations make to coordinate interactions and collaborate with each other, 5) functional proximity – referring to closeness in expertise in different industries/clusters, 6) cultural proximity – referring to closeness of cultural habits and virtues and 7) social proximity – referring to the intensity of trust-based social relations, such as friendship.

    Crises

    The above-mentioned (sub)systems of innovation are in fact 'positive loops'; meaning that they will positively influence each other in an endless loop. As explained earlier, dynamic, chaotic systems, are almost always also containing negative loops, that break the positive flow. These negative loops can turn around the whole mechanism and cause crises, for instance the economic crisis. In the innovation system there are four main negative loops that create discontinuity:

    • Labour market depletion: innovation not only creates new firms which in turn increase employment, innovation also creates more automated, efficient processes that in turn lead to less employment: labour market depletion. Take a look at the book stores for instance: digital innovation has caused the traditional book stores to adjust their business to the online world, closing down book stores and reducing the amount of employees.
    • Other new (disruptive) technologies: from an industry perspective, other new technologies can cause the whole sector to be superfluous. This term is identified as disruptive innovation. Think about how the mobile phone radically made landlines superfluous.
    • Imitation: rising profits within a sector also attracts new companies to the sector that will try to copy the products – at lower costs and without the initial investment. Especially sectors with low entrance barriers are receptive to this, such as software, app development and low-tech products.
    • Policy failures: a various number of reasons can cause policy to fail. The most common ones are bureaucracy, corruption and short-term thinking.

    Innovation Policy

    The innovation policy regarding RIS and NIS involves many different aspects. One way or another, the institutional environment tries to (positively) influence the main industrial innovation system. A few of the soft factor that policy usually to focus on are:

    • Smart infrastructure: this characteristic is about all kind of infrastructures that the region has to offer. This includes hard infrastructures, soft infrastructures and technological infrastructures.
    • Quality of life: according to Sternberg and Arndt (2001) the quality of life is created by: labour quality, housing amenities, and leisure amenities. All of these factors attract highly qualified people to the region, but moreover, they also make people stay in the region.
    • Cosmopolitanism: this aspect refers to any form of feeling that is evoked by the region. The characteristics of this factor are for example attractiveness for highly educated personnel, a world-wide reputation, a good atmosphere, a shared purpose, and highly motivated people (Whitley, 2002).
    • Talented human capital: Micheals et al. (2001) describe that attracting talent, educating talent, and keeping talent is of high importance to the region. They focus on managerial talent, but they explain that technological, engineering and business talent also must be part of a regional strategy to win the war for talent.
    • Creative cultural environment: a well-developed entrepreneurial climate is attracting and exploiting personal talent and is reinforcing the strong culture of the community. Hofstede, more than 25 years ago, received worldwide praise for constructing four – although years later a fifth one was added – dimensions to characterize cultures of different nations: power distance, uncertainty avoidance, individualism, and femininity (Hofstede, 1980).
    • Trust: there is considerable evidence that a trusting relationship creates greater knowledge sharing. In a trust-based relationship, people are more willing to share useful knowledge. Trust promotes social and emotional ties on the one hand and promotes professional collaboration on the other hand, both facilitators of knowledge sharing (Chowdhury, 2005; Tsai & Ghoshal, 1998; Mayer, Davis, & Schoorman, 1995).
    • Identity: scientists claim that knowledge is more effectively generated, combined and transferred by individuals who identify with a larger collective goal. The individual members then share a sense of purpose with the collective. Ultimately, this will lead to lower network costs, and more trust and commitment (Kogut & Zander, 2003; Dyer & Nobeoka, 2000; Orr, 1990)
    • Diversity: this characteristic of knowledge refers to the extent to which a variety of knowledge, know-how, and expertise is available in a network. New opportunities and resources will be discovered more quickly with access to diverse knowledge and knowledge diversity therefore directly stimulates creativity and innovativeness of the actor in the network. (Galunic & Rodan, 2004; Galunic & Rodan, 2002; Rodan, 2002).

    Triple Helix

    Over the last decade we've heard a lot about the triple helix. More recently also the quadruple and quintuple helix have been introduced. Moreover, also Open Innovation and Co-creation have been growing over the years. What they have in common is that these theories try to integrate the different actors in the traditional dynamical view of ecosystems with each other. In that case, it won't be a 'flow' and it will therefore reduce the time delays within the flow. Simply said: deep integration between goverments and industry could result in quicker innovation. As does deep integration between education and industry; or different industries with each other, et cetera. The triple helix is a modern, 3D, view on system dynamics in the innovation ecosystem.

    Games: simulation of complex dynamical systems

    Games are a very common way to let actors in the network know how complex dynamics works. These games let you play with a few of the 'agents' in the ecosystem to experiment with the effects to better understand long-term behavior of ecosystems. Innovative Dutch creates these kinds of strategic simulation games for governments, companies and higher education; they created this infographic for their newest game; please take a look at their website.

    Top 10 Best Articles on Open Innovation in 2013

    Based on the rankings of the SSRN database, we are able to create a ranking of the best – most downloaded – Open Innovation and related topics articles that have been published in 2013 so far. Therefore, this is a list of brand new theories, recent case studies, preliminary results and pioneering research.

    1. The Theory of Crowd Capital; Prpic, J., & Shukla, P.
      Abstract: We are seeing more and more organizations undertaking activities to engage dispersed populations through Information Systems (IS). Using the knowledge-based view of the organization, this work conceptualizes a theory of Crowd Capital to explain this phenomenon. Crowd Capital is a heterogeneous knowledge resource generated by an organization, through its use of Crowd Capability, which is defined by the structure, content, and process by which an organization engages with the dispersed knowledge of individuals – the Crowd. Our work draws upon a diverse literature and builds upon numerous examples of practitioner implementations to support our theorizing. We present a model of Crowd Capital generation in organizations and discuss the implications of Crowd Capital on organizational boundary and on IS research.
    2. Leveraging External Sources of Innovation: A Review of Research on Open Innovation, West, J. & Bogers, M.
      Abstract: This article reviews research on open innovation that considers how and why firms commercialize external sources of innovations. It examines both the “outside-in” and “coupled” modes of Enkel et al. (2009). From an analysis of prior research on how firms leverage external sources of innovation, it suggests a four-phase model in which a linear process — (1) obtaining, (2) integrating and (3) commercializing external innovations — is combined with (4) interaction between the firm and its collaborators. This model is used to classify papers taken from the top 25 innovation journals identified by Linton and Thongpapan (2004), complemented by highly cited work beyond those journals. A review of 291 open innovation-related publications from these sources shows that the majority of these articles indeed address elements of this inbound open innovation process model. Specifically, it finds that researchers have front-loaded their examination of the leveraging process, with an emphasis on obtaining innovations from external sources. However, there is a relative dearth of research related to integrating and commercializing these innovations.
      Research on obtaining innovations includes searching, enabling, filtering, and acquiring — each category with its own specific set of mechanisms and conditions. Integrating innovations has been mostly studied from an absorptive capacity perspective, with less attention given to the impact of competencies and culture (including not-invented-here). Commercializing innovations puts the most emphasis on how external innovations create value rather than how firms capture value from those innovations. Finally, the interaction phase considers both feedback for the linear process and reciprocal innovation processes such as co-creation, network collaboration and community innovation.
      This review and synthesis suggests several gaps in prior research. One is a tendency to ignore the importance of business models, despite their central role in distinguishing open innovation from earlier research on inter-organizational collaboration in innovation. Another gap is a tendency in open innovation to use “innovation” in a way inconsistent with earlier definitions in innovation management. The article concludes with recommendations for future research that include examining the end-to-end innovation commercialization process, and studying the moderators and limits of leveraging external sources of innovation.
    3. The Golden Circle of Innovation: What Companies Can Learn from NGOs When It Comes to Innovation, Spruijt, J.P., Spanjaard, T.G.S. & Demouge, K.
      Abstract: This paper examines the lessons that companies can learn from NGOs when it comes to the why, the how and the what of innovation. It explains innovation from the inside out: why is it important and what are the grand challenges? Followed by the how: in what way can innovation be managed and how does the innovation process look like in a modern economy?
      This introduction is elaborated on with two case studies within NGOs in The Netherlands, Fair2 and Liliane Foundation. It leads to several conclusions and hypotheses for further research.
    4. Sustainability-Oriented Innovation, Hansen, E.G. & Grosse-Dunker, F.
      Abstract: Sustainability-oriented innovation (SOI): the commercial introduction of a new (or improved) product (service), product-service system, or pure service which – based on a traceable (qualitative or quantitative) comparative analysis – leads to environmental and (or) social benefits over the prior version’s physical life-cycle (‘from cradle to grave’).
    5. Open Innovation and Organization Design, Tushman, M., Lakhani, K. & Lifshitz-Assaf, L.
      Abstract: Abernathy’s (1978) empirical work on the automotive industry investigated relationships among an organization’s boundary (all manufacturing plants), its organizational design (fluid vs. specific), and its ability to execute product and/or process innovations. Abernathy’s ideas of dominant designs and the locus of innovation have been central to scholars of innovation, R&D, and strategic management. Similarly, building on March and Simon’s (1958) concept of organizations as decision making systems, Woodward (1965), Burns and Stalker (1966), and Lawrence and Lorsch (1967) examined relationships among organizational boundaries, organization structure, and innovation in a set of industries that varied by technology and environmental uncertainty. These and other early empirical works have led a diverse group of scholars to develop theories about firm boundaries, organization design, and the ability to innovate.
    6. Managing Crowd Innovation in Public Administration, Collm, A. & Schedler, K.
      Abstract: Governments all over the world have discovered the world of social media, for better or for worse. Whereas some of them are making every effort to prevent the unhierarchical and therefore uncontrollable (dissident) opinion-forming process in Web 2.0, others are looking for ways of putting the potentialities of this new opening-up of communication to use. One approach that is increasingly being tried out is opening up innovation processes in government. However, this opening-up of innovation processes is anything but trivial. It requires a thoroughly thought-out strategy and thus confronts government systems with extensive challenges if it is not to suffer the same fate as other unsuccessful attempts at reform in the past. In our essay, we reflect on the consequences of these challenges for public managers.
    7. Adopting Open Innovation to Stimulate Frugal Innovation and Reverse Innovation, Hossain, M.
      Abstract: Frugal innovation and reverse innovation have very recently emerged as interesting concepts. Frugal innovation is based on cost constraints to serve low-income customers in developing countries. When frugal innovation comes to developed countries and becomes commercially successful it is considered as reverse innovation. Recently, many companies, such as GE, Siemens, Procter and Gamble, etc. have engaged heavily in frugal innovation and in reverse innovation. Open innovation, on the other hand, has not been considered in the context of low-income customers in developing countries. We argue that using open innovation concept in developing countries may boast frugal innovation and reverse innovation. Consequently, quality product with low-income will be widely available not only in developing countries but also in developed countries. Hence, western companies need to change their long hold business strategies and reshape their business models. This study aims to illustrate why western companies need to be aware of and take step to become successful in the turbulent business world.
    8. The Impact of Visibility in Innovation Tournaments: Evidence from Field Experiments, Wooten, J.O. & Ulrich, K.T.
      Abstract: Contests have a long history of driving innovation, and web-based information technology has opened up new possibilities for managing tournaments. One such possibility is the visibility of entries – some web-based platforms now allow participants to observe others’ submissions while the contest is live. Seeing other entries could broaden or limit idea exploration, redirect or anchor searches, or inspire or stifle creativity. Using a unique data set from a series of field experiments, we examine whether entry visibility helps or hurts innovation contest outcomes. Our eight contests resulted in 665 contest entries for which we have 11,380 quality ratings. Based on analysis of this data set, we provide evidence that entry visibility influences the outcome of tournaments via two pathways: (1) changing the likelihood of entry from an agent and (2) shifting the quality characteristics of entries. For the first, we show that entry visibility generates more entries by increasing the number of participants. For the second, we find the effect of entry visibility depends on the setting. Seeing other entries results in more similar submissions early in a contest. For single-entry participants, entry quality “ratchets up” with the best entry submitted by other contestants previously if that entry is visible, while moving in the opposite direction if it’s not. However, for participants who submit more than once, those with better prior submissions improve more when they can not see the work of others. The variance in quality of entries also increases when entries are not visible, usually a desirable property of tournament submissions.
    9. Digital Scholarship: Exploration of Strategies and Skills for Knowledge Creation and Dissemination, Cobo, C. & Naval, C.
      Abstract: Widespread access to digital technologies has enabled digital scholars to access, create, share, and disseminate academic contents in innovative and diversified ways. Today academic teams in different places can collaborate in virtual environments by conducting scholarly work on the Internet. Two relevant dimensions that have been deeply affected by the emergence of digital scholarship are new facets of knowledge generation (wikis, e-science, online education, distributed R&D, open innovation, open science, peer-based production, online encyclopedias, user generated content) and new models of knowledge circulation and distribution (e-journals, open repositories, open licenses, academic podcasting initiatives, etc.). Despite the potential transformation of these novel practices and mechanisms of knowledge production and distribution, some authors suggest that digital scholarship can only be of significance if it marks a radical break in scholarship practices brought about through the possibilities enabled in new technologies. This paper address some of the key challenges and raise a set of recommendations to foster the development of key skills, new models of collaboration and cross-disciplinary cooperation between digital scholars.
    10. Dissenting State Patent Regimes, Hrdy, C.A.
      Abstract: Inventors who believe in open innovation should start applying for state patents instead of U.S. patents. Patenting at the state level prevents rivals from obtaining U.S. patents and generates valuable innovation spillovers in other states where the patent has no legal effect. It also creates a unique opportunity to force patent law reform from the bottom up. In exchange for filing fees, inventors can demand patents based on rules that support open innovation, like shorter terms in fast-moving industries, stricter disclosure requirements, or new restrictions on patenting by non-practicing entities. The lobbyists who stymie reform at the national level will have a much harder time blocking reform in all fifty states. Meanwhile, patent law’s dissenters need only one state to start granting patents in order to get courts, the media, and eventually Congress to pay attention.

    The Golden Circle of Innovation

    Recently, a new article about the “The Golden Circle of Innovation” has been published in the SSRN. It provides an interesting way of combining Simon Sinek’s Golden Circle and some traditional literature on innovation science into the ‘Golden Circle of Innovation’.

    Important notice: the full article can be downloaded freely from the SSRN database: The Golden Circle of Innovation: what companies can learn from NGOs when it comes to innovation.

    Sinek’s Golden Circle

    In his work he explains why everything starts with answering the why-question. And that also means innovation, as he states it: “Knowing your why is not the only way to be successful, but it is the only way to maintain a lasting success and have a greater blend of innovation and flexibility. When a why goes fuzzy, it becomes much more difficult to maintain growth, loyalty and inspiration that helped drive the original success” (Sinek, 2009).

    Literature review of Innovation Science

    Though not focusing on the why, how and what, Crossan and Apaydin have generated an overview of all relevant theories on innovation, resulting in a framework for innovation, as depicted below.

    They mention two ‘dimensions of innovation’, both focusing on innovation itself and they mention several ‘determinants of innovation’, focusing on the way that innovation is accelerated and managed within organizations.

     

    Golden Circle of Innovation

    In attempt to combine both models with each other, we created a new framework: the golden circle for innovation.

    The why of innovation: grand challenges, trends and mission statements

    The why of innovation not only consists of leadership aspects; it also consists of embracing a mission that fulfills a more general need and therefore rectifies the necessity of innovation.

    As Einstein once stated “If you always do what you always did, you will always get what you always got”, change is a prime economic driver. “It is practically impossible to do things identically” (Hansen & Wakonen, 1997) which “makes any change an innovation per definition” (Crossan & Apaydin, 2009).

    But to what extend? Innovation drives economic growth and economic growth is a necessity because of the grand challenges that this world is facing, such as keeping up with international competition in a globalizing world – which in turn increases the need for higher productivity rates through both product innovation and process innovation (Parisi, Schiantarelli, & Sembenelli, 2006) – and megatrends such as climate change, social problems and the experience economy (Brainport, 2007; Sistermans, Maas, & Soete, 2005).

    So how are great leaders capable of embracing this necessity for innovation and embed it into their vision for the company? Dyer, Christensen and Gregerson (Dyer, Gregersen, & Christensen, 2009) undertook “a six-year study into the origins of creative – and often disruptive – business strategies in innovative companies”. They found evidence that these leaders are visionary and much more facilitating the innovation process than actually coming up with innovations themselves. They are drivers of the process. Their study results in five ‘discovery skills’ that these inspirational leaders do 50% better than their non-creative counterparts:

    • Associating
    • Questioning
    • Observing
    • Experimenting
    • Networking

    Concluding this paragraph, we can state that an effective answer the why of innovation consists of both a motivational mission statement that embraces one or more grand challenges that is functioning as the beating heart of the organization and inspirational leaders that are effective in the five before-mentioned discovery skills.

    The how of innovation: innovation history, management and processes

    Innovation has a basis in the product life cycle. Literature on this topic goes back centuries, but was first scientifically mentioned by Levitt (Levitt, 1965). In several revising studies, Perreault has elaborated on this model (Perreault, McCarthy, Parkinson, & Stewart, 2000). The model consists of the four phases a product or service are subject to: market introduction, market growth, market stability and decline. From an innovation perspective, Rogers has created a model that characterized final consumers to the extend in which they adopt to new technologies: The Diffusion of Innovation and Adopter Categories (Rogers, 2002).

    In recent decades, a lot of research has been performed into innovation processes and the steps that regularly seem to reoccur in these processes. Literature reviews show there is little consensus about the number of phases and types of phases that should be part of a regular innovation cycle (Adams, Bessant, & Phelps, 2006; Gopalakrishnan & Damanpour, 1997).

    De Brentani and Reid further elaborate on this model (Reid & De Brentani, 2004). They state that incremental, structured innovations are mostly the result of explicit and structured innovation processes and organizational processes. On the other hand, unstructured innovation processes (especially in the first one or two phases) often lead to disruptive or radical innovations. This is also called the ‘fuzzy front end’ of innovation (Brentani & Reid, 2012). Structure and organisation in later phases of innovation processes is always a pro for the success rate of innovation. In what way does the fuzzy front end of innovation differ with structured innovation?

    • There is continuous unstructured problem identification and unstructured opportunity recognition, whereas more structured innovation processes mostly use problem structuring and opportunity structuring and the early phases of the process (Hauser, Urban, & Weinberg, 1993; Leifer, O’Connor, & Rice, 2001).
    • Information collection and information exploration is generally outside-in oriented, whereas these steps are often inside-out oriented in structured processes.

    This theory is further elaborated on by Mance, Murdock and Puccio, who have generated the following model (Puccio, Mance, & Murdock, 2010).
    At this point, we have tried to deduce a model that comprises all before-mentioned models and consequently consists of four phases that each have the form of diverging-converging, but also as a total has to form of diverging-converging.
    Similar like organizations growth models, the area of innovation management has been undergoing several improvements over the years. Rothwell has stated that market changes have contributed to these improvements and he distinguishes five different generations of innovation:

    • 1st generation: technology push
    • 2nd generation: market pull
    • 3rd generation: coupled innovation
    • 4th generation: integrated innovation
    • 5th generation: open innovation

    Concluding this paragraph, we can state that as part of the how of innovation the processes should be oriented at following a pragmatic approach – such as problem finding, ideation, concepting and implementation – and should consist of both a structured inside-out approach and a more chaotic outside-in approach and that the management should be oriented at successful implementation and embedding new approaches to innovation management, such as open innovation.

    The what of innovation: innovation as a process and as an outcome

    There are various definitions of innovation. In an earlier article, we have used the following, fairly narrow defined, definition of Schilling: “Innovation is the act of introducing a new device, method or material for application to commercial or practical objectives” (M.A. Schilling, 2005; Spruijt, 2012). Crossan & Apaydin recently published a literature review on innovation literature, stating: “An unrestricted search of academic publications using the keyword innovation produces tens of thousands of articles, yet reviews and meta-analyses are rare and narrowly focused, either around the level of analysis (individual, group, firm, industry, consumer group, region, and nation) or the type of innovation (product, process, and business model)” (Crossan & Apaydin, 2009). To be specific, a current search on the keyword “innovation” results in 2.5 million articles on Google Scholar and thousands of articles using the keyword combination “definition of innovation”. Clearly, there isn’t a specific definition that is correct and many perspectives should be taken into account when defining innovation.

    Crossan and Apaydin (2009) have identified different forms of innovation and grouped them around certain dimensions, some of them related to innovation as a process, some of them to innovation as an outcome. These dimensions are:

    Innovation as a process:

    • drivers of innovation
    • levels of innovation
    • direction of innovation
    • source of innovation
    • locus of innovation

    Innovation as an outcome:

    • forms of innovation
    • magnitude of innovation
    • referent of innovation
    • type of innovation

    Golden Circle of Innovation

    This leads to a more detailed model of the one we presented earlier:

     

    Example case of NGOs

    During the studies we followed the Liliane Foundation in an innovation project aiming to create more awareness amongst high school students about the problems in third world countries. They collaborated with a group of students from Avans University in order to identify the problems. These students are high school dropouts and were able to address the problem very efficiently. In a next step, the Liliane Foundation gathered a group of high school teachers to further develop ideas and alternative programs for awareness. In a third step, they collaborated with high school executives and university executives in order to create a platform for the implementation of the alternative programs and to find financial contribution. In the last phase, the implementation, they collaborated with all parties and included some external partners, mostly sponsors, in the roll out. The whole project was successfully launched within a year.

    So what did they do? They used their why to find partners that were willing to help them executing the how. They found a way of ‘open innovation’ that is rarely seen in the corporate world, as depicted in the following figure.

    Important notice: the full article can be downloaded freely from the SSRN database: The Golden Circle of Innovation: what companies can learn from NGOs when it comes to innovation.

    Innovation Management Game: start-up of the year

    Just like last year, we’ll publish a (small) list containing the most promising start-ups of the year. Obviously, we’ll share our opinion from the perspective of Open Innovation by answering the following questions:

    • Does the start-up contribute to the field of Open Innovation?
    • Does the start-up contribute to the field of Innovation Management?
    • Does the start-up contribute to the European knowledge economy?
    • Is the product/idea innovative?
    • Does it meet customer needs?

    1st: Innovation Management Game

    This year, the number 1 position goes to the Innovation Management Game. The Innovation Management Game is a business strategy simulation game for universities, higher education, business schools and corporate/executive trainings. The game centralizes topics like Open Innovation, Co-Creation, Innovation Management and Business Model Innovation.

    Does the start-up contribute to the field of Open Innovation?5/5
    Does the start-up contribute to the field of Innovation Management?5/5
    Does the start-up contribute to the European knowledge economy?5/5
    Is the product/idea innovative?4/5
    Does it meet customer needs?5/5
    Overall:4.8/5

    2nd: Owlin

    The second position goes to Owlin; a start-up in the financial sector that scans and analyzes social data and creates insights in financial opportunities before organisations and press offices would be able to recognize it themselves. Owlin is part of the Rockstart’s Acceleration Programme and received earlier this week €200.000 euro on venture capital.

    Does the start-up contribute to the field of Open Innovation?4/5
    Does the start-up contribute to the field of Innovation Management?4/5
    Does the start-up contribute to the European knowledge economy?5/5
    Is the product/idea innovative?5/5
    Does it meet customer needs?5/5
    Overall4.6/5

     3rd: Fosbury

    Just a few months online, however already getting wide attention, Fosbury. A start-up, developed by two of the former founders of Yunoo, that enables organization to quickly segment and advertise coupons and vouchers to smartphones. We’re expecting this type of organisation to set back the traditional paper advertising markets before the end of 2013.

    Does the start-up contribute to the field of Open Innovation?4/5
    Does the start-up contribute to the field of Innovation Management?3/5
    Does the start-up contribute to the European knowledge economy?5/5
    Is the product/idea innovative?4/5
    Does it meet customer needs?5/5
    Overall:4.2/5

     

    Public policies for Innovation

    In a recent report Henry Chesbrough, Wim vanhaverbeke, Jeroen de Jong and Tarmo Kalvet explore how policy makers can enhance and leverage open innovation practices in European economies by aligning labor market policy, education policy, IP-regulation, innovation policy and other policy domains in line with the the rapidly changing needs of firms that innovate in collaboration with research institutes, suppliers, customers, innovation intermediaries, and other partners. The report provides a theoretical perspective, a policy framework and case studies for Belgium, the Netherlands and Estonia. Download the article here:

     OIPAFfinalreport.