Tag: Innovation

When Ten Faces flirt with Ten Types: Ten Types of Innovation Teams

When the book “Ten Types of Innovation” (Keeley et al.), in its most recent format, hit the shelves in 2013 – not only me, but many of my colleagues in higher education, embraced the work because of its clarity and integrality. It offered a much richer approach than the usual – perhaps more scientifically evidenced – approach of 4 types of innovation (product innovation, process innovation, business model innovation, service innovation). The work was, and still is, one of the most influential works used in our Business Innovation program and highly rewarded by both students and partners in the field. The infographic I made in 2014 based on this book has been one of the most downloaded infographics on this blog ever since.

Parallel to that, but completely different in its approach, the work “Ten Faces of Innovation” (Kelley), acquired the same fame over the years. It was highly rewarded as a book that offered an approach to dealing with different roles in innovation teams – roles that were not necessarily bound to 1 person and are highly practical from nature – much more practical than for instance the typology mentioned in the Innovator’s DNA – which looks at roles from a more abstract, ambidextrous, point-of-view. The Ten Faces shouldn’t be used to tag people with specific skills (something that for instance DISC does), but can be used to start a deliberate conversation with your (innovation) team members about their strengths and ambitions.

    Innovation Teams

    But something that neither of them discuss is the existence and consistence of innovation teams. In innovation science the construct of an ‘innovation team’ is often overlooked – as if there is only one sort of innovation teams: the team that innovates and is run by innovators. In reality however, I came across many distinguishing approaches to what we could call innovation teams. They all have different set-ups and different aims. Drawing on my own experience (examples below) and backed by the models of Ten Types of Innovation and Ten Faces of Innovation, I deducted 10 Types of Innovation Teams. Let me introduce them to you:

    1. Spun-off Teams

    • Ten Faces: the hurdler, the director and the anthropologist
    • Ten Types: profit model innovation, network innovation, process innovation, product innovation;

    Spun-off Innovation Teams are teams consisting of seasoned entrepreneurs who have gained experience in SME or large corporations, created or designed a highly marketable technology or business model. They usually patent their idea from within the mothership and from then on collaborate with them to spin-out their business to increase chances of bringing it to market successfully.

    2. Tiger Teams

    • Ten Faces: the hurdler, the collaborator, the director
    • Ten Types: profit model innovation, network innovation, structure innovation, process innovation, channel innovation

    Tiger Teams are one-of-a-kind. They consist of influential innovators or project managers from within your organization. Their task usually is to dive into an immediate problem and come up with an innovative solution to overcome the problems. A problem could be that one of your suppliers is financially unstable, which rings all bells in your organization’s risk analysis. A Tiger Team can then be sent to the supplier to “overtake” their current business operations, create innovative managerial solutions and get things back on track. A Tiger Team could also intervene internally in organizational redesign or when opening up your business model. Tiger Teams will be able to deal with resistance and have a strong focus on the human impact of change.

    3. Formal Innovation Teams

    • Ten Faces: the hurdler, the collaborator, the caregiver
    • Ten Types: profit model innovation, network innovation, process innovation, product innovation and product system innovation

    Formal Innovation Teams are the teams we usually refer then framing innovation teams. They consist of powerful innovators with vision and a strong internal and external network to get things done. Innovation is not something they ‘do’ fulltime: they are freed of other tasks for 1-2 days a week and use this time to create shared visions, initiate new projects or follow top-down leads that may be interesting. They usually have some kind of stage-gate-model in place to be able to monitor and report about their progress.

    4. Strategy Teams

    • Ten Faces: the collaborator, the director, the anthropologist
    • Ten Types: profit model innovation, network innovation, structure innovation, product innovation

    Strategy Teams are responsible for developing new strategic directions. They thoroughly research market trends and user experiences in order to design new visions and possible scenarios for the organizations. Their task is to report continuously about these findings and suggest the creation of new business models for the organizations. They usually operate at a high level in the organization, are usually multidisciplinary and strongly intertwined with experts from universities to help them grasp the most important findings.

    5. Product Innovation Teams

    • Ten Faces: the collaborator, the experimenter, the set designer
    • Ten Types: network innovation, product innovation, product system innovation, service innovation

    Product Innovation Teams are an export product of the Agile Movement. Many organizations have recently transformed into ‘agile communities’ which includes (temporary, but fulltime) product innovation teams who are responsible for the full development of an idea completely to a market-ready stage. In digital companies they may take the form of scrum teams. The teams are usually flexible, but dedicated and result-oriented. They are makers and make sure to test and validate the product with users before its final implementation.

    6. Accelerator Teams

    • Ten Faces: the anthropologist, the cross-polinator, the set designer
    • Ten Types: structure innovation, process innovation, product innovation, product system innovation

    Accelerator Teams operate with innovation on another level: they don’t innovate themselves, but the facilitate innovation in their organization – using an innovative approach in doing so. They create spirit, they create learning spaces, they create inspiration, they build bridges, they make seemingly unrelated relations. With their approach they create a climate for innovation within the company that, in the long run, creates a process of continuous reinvention of the organization.

    7. Startup Teams

    • Ten Faces: the hurdler, the experimenter, the caregiver, the experience architect
    • Ten Types: product innovation, channel innovation, brand innovation

    Startup Teams consist of young, usually relatively unexperienced, innovators that have a specific mission in mind and are willing to iterate as long as possible until the mission becomes reality. They focus on creating minimum viable products and building strong brands on top of that. They create a flavor of freshness around the product and do not settle for known paths to market. To start online and stay online.

    8. Informal Innovation Teams

    • Ten Faces: the experimenter, the cross-polinator, the storytellers
    • Ten Types: product innovation, product system innovation, service innovation, customer engagement innovation.

    The informal nnovation teams breath idea generation. These are hidden ‘teams’, walking between the lines of the other teams. The create ideas at a non-stop basis and their influence in the organizations to bring the ideas to the more formal teams in order to realize them. Behind the scenes, they’ll stay involve to see how their ideas end up or if they should pull some more strings. These kind of teams are highly valuable to organizations: they exist everywhere, but are only appreciated in organizations with a strong innovation climate. They don’t want to be formalized, so let them be.

    9. Community Teams

    • Ten Faces: the cross-polinator, the storyteller, the experience architect.
    • Ten Types: service innovation, customer engagement innovation

    Community Teams drive innovation through the (user) community of the organizations. They try to continuously interact with the customers and involve external users in the creation of new opportunities for offering increased service and enhanced customer satisfaction. They use visual techniques and are tech-savvy in their ways to reach out and they growth hack their way into your innovation funnel. Their ideas may just be as good as the anthropologist’s ideas.

    10. Window Teams

    • Ten Faces: the storyteller, the experience architect
    • Ten Types: brand innovation, customer engagement innovation

    Window Teams are highly specialized in reinventing your brand and reputation. They will ideate, design and implement innovations that the outside world sees when googling for your organization. They usually consist of marketing-communication experts, graphical designers and fashionista’s and usually operate at a high level in the organization, because it’s not what’s good that gets the attention of the board but what gets wrong. Not having Window Teams may be bad for your reputation: nobody still believes that your product sells itself, do you?

    The University in 2040: 6 trends & an infographic.

    On November 23, I had the honor of giving a talk at the NRC Live event for Education. I was scheduled immediately after Bert van der Zwaan, rector magnificus at the University of Utrecht. Van der Zwaan launched his book that day: the result of sabbatical he and his wife took in 2015. During that sabbatical they traveled the world and tried to speak with as many educational visionaries as possible. It led to the work: The University in 2040, does it still exist?

    In his work, Van der Zwaan introduces 6 worldwide trends in education that will have significant impact on how we learn in the future. The book was published under a creative commons license (free for you to download in Dutch) and I decided that a ‘summary’ of the most important topics covered in the form on an infographic would be a great contribution for the reader of this blog.

    6 trends in higher education

    • Global Innovation Hubs: Through urbanisation universities move into the era of the global campus, a university that focuses on innovation and entrepreneurship and is the center of a regional ecosystem and knowledge valorisation.
    • Digitalization: IT will change the landscape of educat ion forever. Online learning and blended learning are just the first signs of a remarkeable shift in education. The future will behold exponential learning through big data, open science and serious games.
    • Debundling: Debundling is the trend towards more personalized, modular education. This trends will mark a shift towards a more global talent pool, accessible education SPOCs, shared intellectual commons and global commons.
    • Lifelong learning: Lifelong learning will solve the continuing mismatch between education and the labour market. Universities will start to offer more customized and problem-solving education and turn into the engaged university.
    • Economic Shift: In the near future governments worldwide will reduce investments in tertiary education and universities will become more privatized. Globally there are huge differences in labour market needs for employees with a higher education degree.
    • Civic University: The main function of the university of the future is unsure. Will the university a) focus on developing talent b) focus on applying research for entrepreneurship or c) focus on fundamental research for dealing with social challenges?

    Infographic: the University of 2040

    We have created an infographic on the future of education based on the work of Bert van der Zwaan.

      8 Types of Innovation Processes (Infographic)

      As part of a simulation game on innovation management we have been running at universities and in corporate training programs for over 4 years now, we have developed an integrative model for dealing with innovation management on a daily basis. Innovation Management is a strategic activity that isn’t necessarily needed to implement throughly for every company. Mostly large companies have included structured processes that include administrative stages to following the (large number of) project that are in progress and to be able to follow-up on them and calculate the effect of innovation management in general. For smaller companies however, that is not general practice: having such a formal process in place simply doesn’t weigh up to cost efficiencies will generate. But for them, innovation management is just as important – but they rather use a toolkit than a formal process. Our 8 Types of Innovation Processes model is a simple design that makes it easy to bridge the gap between a formal process and the tools available.

      Based on a visionary criteria – radical or incremental? product leadership or operational excellence? – you would be able to select approximately 2 or 3 types of processes that should be of interest to you. Scroll down to the tactics and start working on them tomorrow.

        8 Types of Innovation Processes

        • Marketing & Branding: innovating the customer experience.
        • Ideation: innovating the product idea & concept.
        • Technology: innovating the product functionality.
        • Co-creation: innovating the customer involvement.
        • Social Innovation: innovating the corporate culture.
        • Entrepreneurship: innovating through entrepreneurial thinking.
        • Open Innovation: innovating with stakeholders.
        • Business Model Innovation: innovating the purpose and strategy.
        		 This article was written by Jan Spruijt. Jan Spruijt is a senior lecturer and entrepreneur in Innovation Sciences. Connect with Jan to stay in touch:

         

         

        Book Review & Infographic: Innovation Thinking Methods by Hashmi

        A few weeks ago, a friend brought the book “Innovation Thinking Methods: disciplines of thought that can help you rethink industries and unlock 10x better solutions” from Osama A. Hashmi to my attention. I ordered it, read it and was impressed by the both the power and simplicity of the work.

        The book is thin and comprehensible. In fact, it read like a weblog post enriched with interesting personal thoughts of the author and beautiful examples from his own perspective. What I most liked is the fact that it takes another approach then we’re used to see: the book is a random list of thinking methods that could be used when dealing with innovation as an entrepreneur. The list is not categorized, nor is there a structured process that guides you through the book, nor an analysis or an advice. And therefore it is mostly an inspirational book and a homage to disruptive, non-incremental or structured thinking; the fuzzy front-end of innovation. A non-methodological list of methods. Both an obeisance for the entrepreneurial-minded free-thinkers and experienced managers looking for a solution to create passion and change in an innovation team.

        However, I do like analysis and created an infographic that groups the thinking methods into one model, with 4 typical innovation team assets on the vertical axis: Experience, Knowledge, Skills and Attitude. I have ranked each innovation thinking method on those 4 assets, making it possible to ‘rank’ and categorize your own team – in order to see where there are opportunities for growth and new perspectives.

          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.

            The 3 Phases of Responsible Innovation

            Over the last few month, the phrase “Responsible Innovation” has been booming on scientific social media. It has emerged from Corporate Social Responsibility as a topic that researches the effect and consequences of innovation on the long term. This could be technological effects, antropological effects or ethical effects.

            The fundament of this research topic lies in the Collingridge Dilemma:

            The Collingridge dilemma is a methodological quandary in which efforts to control technology development face a double-bind problem: an information problem – impacts cannot be easily predicted until the technology is extensively developed and widely used – and a power problem – control or change is difficult when the technology has become entrenched.

            The way to start innovating in order to enhance responsible innovation is three-fold:

            1. Value-consciousness in design, research and development: this aspect means that design or R&D should start with a clear answer to the ‘why of innovation’. In other words: does this idea or design provide a solution to one of the grand challenges that we are facing in 5, 10 or 30 years? Values are the key to those answers.

            2. Ethical Parallel Research: every step of the innovation management funnel  should be taken with the influence of ethical researchers and if possible, also researches from other parallel industries. This way, the impact that the innovation has on the long term can be easily addressed and tackeled early stage.

            3. Constructive Technology Assessment: innovation teams shouldn’t be monodisciplinary, but multidisciplinary. That way, early-stage innovation (ideas) can be assessed and tested upon. Multidisciplinary teams form the basis of Open Innovation.

            If you are interested in the material, take into account the following material:

            Responsible Innovation: Managing the Responsible Emergence of Science and Innovation in Society

            Science and innovation have the power to transform our lives and the world we live in – for better or worse – in ways that often transcend borders and generations: from the innovation of complex financial products that played such an important role in the recent financial crisis to current proposals to intentionally engineer our Earth’s climate. The promise of science and innovation brings with it ethical dilemmas and impacts which are often uncertain and unpredictable: it is often only once these have emerged that we feel able to control them. How do we undertake science and innovation responsibly under such conditions, towards not only socially acceptable, but socially desirable goals and in a way that is democratic, equitable and sustainable? Responsible innovation challenges us all to think about our responsibilities for the future, as scientists, innovators and citizens, and to act upon these.

            The Importance of Responsible-Innovation and the Necessity of ‘Innovation-Care’

            This study deals with responsibility as part of innovation. By nature, innovation gives birth to development for the organization and can only be at the core of any strategy within an ever-increasingly global economic context. However it also raises new questions stemming mostly from the impossibility to forecast the success of the innovations. More precisely, the questions raised by innovation also concern its consequences on society as a whole. Today, the innovator should understand his responsibility, the consequence of each innovation.

            Moreover, common acceptance of the word ‘responsibility’ raises some questions about its use and how it should be understood. What does ‘responsibility’ mean? Who is responsible and for what? Through the notion of ‘care’, we aim at providing an evolution of responsible-innovation. The concept of ‘innovation-care’ is centered on people and more precisely focuses on taking care of them. The purpose of innovation-care is indeed to innovate and keep up with the level of productivity necessary to any organization while taking into account the essential interdependence between the status of the innovator and that of the citizen.

            Enhancing Socially Responsible Innovation in Industry

            This thesis presents a study that aims to explore to what extent corporate researchers in the field of industrial Life Science & Technology (LST) can consider social and ethical aspects of LST innovation to improve their Research and Development (R&D) practices. Innovators, particularly those working in controversial scientific and technology fields such as industrial LST, are encouraged to adopt socially responsible innovation methods. This requires that researchers, who work in such fields, consider the broader social and ethical context of their R&D activities.

            The presented study explores first how corporate researchers can integrate such aspects in their daily work and how this could improve their work. Second it investigates whether such integration leads to a quantitatively assessable improvement of the quality of R&D. The results indicate that integration is possible, and leads to a measurable improvement of the quality of R&D work. In addition, researchers see a number of improvements in their R&D work, e.g. in the quality of communication and cooperation, and how to link their own work to corporate strategies and marketing. This thesis can be useful for innovators who wish to enhance socially responsible innovation practices, as it presents a tool for R&D management that allows for the operationalisation of socially responsible innovation and improved R&D performance.

            First annual conference Responsible Innovation

            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.

            Shell wants to invest in Open Innovation

            Shell indicates to be willing to invest hundreds of millions of dollars in technology-oriented companies for the next 6 to 8 years. according to belegger.nl. The website has published to following text (translated):

            This step helps Shell to enable the use of innovations on new projects, according to the company.

            Shell refers (amongst others) to the technology that enables the company to apply their resources more thoughtfully and smarter in their quest for oil and gas and in the improvement of the process of obtaining gas and oil.The investments are categorized under Shell Technology Ventures. ,,Ideas from outside our organisation are of great importance in the exploitation of R&D.. We want to be enable the brightest to develop plans and let them take advantage of our expertise and global impact of our company in order to use these technologies as quickly as possible on our projects”, according to the chief technology officer Gerald Schotman.

            Besides investing in promising technological companies, Shell wants to focus on so-called spin-outs, organisational assets that become independent and on funds of venture capitalists.

            As such a great example of Open Innovation in practise.

            Serious games effective in teaching (open) innovation & management

            Recently, an article about the effect of serious games on teaching and learning the essentials of (open) innovation and innovation management has been published on the ssrn. The authors have researched a group of students from different nationalities playing a game in the context of an education course. By playing the game, they had the following goals:

            • Creating a shared experience of social dynamics and the paradox of co-opetition for the students;
            • Enable critical reflection on social dynamics of co-opetition based on this experience;
            • Experience-based learning — enable the students to apply what they learned from their reflection and experience through iteration;
            • Create deeper understanding of open innovation;
            The study uses a series of plays and discussions and compares the results of these sessions with game theory. They round up with several interesting conclusions:
            • We argued that play can be a source of creativity, imagination and fun in a teaching setting (cf. Kolb & Kolb, 2010).
            • We found evidence that playful games can help to create such an experience through interactive experience and simple simulation — thereby helping the students to better understand the theory behind open collaborative innovation (Bogers, 2012; Chesbrough, 2003; Chesbrough et al., 2006; Dahlander & Gann, 2010; Nalebuff & Brandenburger, 1997).
            • Moreover, playful games allow understanding open innovation as interplay of complex processes of relating, social capital, and institutions (Adler & Kwon, 2002; Nahapiet & Ghoshal, 1998; Rolfstam, 2009; Searle, 2005; Stacey & Griffin, 2005).
            • They thus allow us to get a more holistic understanding of the complex social dynamics that emerge when people have to deal with novelty. (Bogers & Sproedt, 2012).
            Two of the most used innovation games in teaching (professionals) and higher education are:

             

            Creativity as a Life Skill for Innovation

            One of my favorite reads of the last couple of years is the work “Creative Leadership: Skills that drive innovation”, written by Puccio, Mance and Murdock. They argue that by making use of the right thinking skills an individual should be able to think outside their ‘area of familiarity’. The origin of radical innovation begins outside this so-called zone of comfort. By making use of the right converging techniques the individual should be able to make deliberate decisions between alternatives. See figure 1.

            Puccio et al. mention the following essential thinking skills necessesary for diverging and converging:

            Affective Skills (Puccio, Mance, Murdock)

            Cognitive Skills (Puccio, Mance, Murdock)

            Recently, Puccio gave a wonderful Ted-presentation about creativity: