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Abstract
Key Takeaways
Figures
Introduction
Standard Analysis
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Business and Management
Management of Technology and Innovation

Knowledge creation and innovation

Profile image of Antti HautamäkiAntti Hautamäki

Abstract

Innovation is basically knowledge creation. The concepts of knowledge are analyzed from a philosophical point of view pointing out the difference between know-that and know-how. The other aspect of knowledge creation is the space where people collaborate, referring to communities of practice. Third point is the role of networks in knowledge creation. Together my considerations provide a "philosophical foundation" for innovation!

Key takeaways
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AI

  1. Innovation fundamentally stems from knowledge creation, emphasizing the interplay of know-how and know-that.
  2. Communities of practice serve as critical environments for collaborative knowledge generation and innovation.
  3. The SECI model illustrates the dynamic conversion processes between tacit and explicit knowledge.
  4. Dynamic capabilities in firms enable them to adapt and reconfigure resources for competitive advantage.
  5. Knowledge management requires a nuanced understanding of both explicit and tacit knowledge within organizational contexts.
Figures (8)
The Intellectualist Legend originates from the mind-body dualism of Descartes: mind and body are separate but parallel processing entities (Figure 1). This dualism is strongly criticized by Merleau-Ponty (1992) as well as Gilbert Ryle. But note, that rejection of the Legend doesn’t mean that know-that is irrelevant to know-how. In learning processes training and becoming to know some rules and facts might be important and even a starting point. What Ryle is saying is that this know-that or thinking needs not be present or activated in intelligent performance or just prior to it. Say, when going to swim and swimming we need not repeat or keep in mind the instructions. Because we know how to swim we just swim. Figure 1. The illustration of The Intellectualist Legend Ryle says that intelligent performance or knowing how is a disposition (Ryle, 45-51). Examples of dispositional properties are brittleness of glasses or solubility of sugar. Dispositional properties are some kind of potentialities, which are activated under certain conditions. “To say that sugar is soluble is to say that it would dissolve, or would have dissolved, if immersed in water” (Ryle, 43). These examples are simple as compared to human dispositions (skills), which are higher-grade dispositions (say playing chess, or driving a car) the exercises of which are “indefinitely heterogeneous” (Ryle, 44).
The Intellectualist Legend originates from the mind-body dualism of Descartes: mind and body are separate but parallel processing entities (Figure 1). This dualism is strongly criticized by Merleau-Ponty (1992) as well as Gilbert Ryle. But note, that rejection of the Legend doesn’t mean that know-that is irrelevant to know-how. In learning processes training and becoming to know some rules and facts might be important and even a starting point. What Ryle is saying is that this know-that or thinking needs not be present or activated in intelligent performance or just prior to it. Say, when going to swim and swimming we need not repeat or keep in mind the instructions. Because we know how to swim we just swim. Figure 1. The illustration of The Intellectualist Legend Ryle says that intelligent performance or knowing how is a disposition (Ryle, 45-51). Examples of dispositional properties are brittleness of glasses or solubility of sugar. Dispositional properties are some kind of potentialities, which are activated under certain conditions. “To say that sugar is soluble is to say that it would dissolve, or would have dissolved, if immersed in water” (Ryle, 43). These examples are simple as compared to human dispositions (skills), which are higher-grade dispositions (say playing chess, or driving a car) the exercises of which are “indefinitely heterogeneous” (Ryle, 44).
In every action there are some “particulars” (also called parts or subsidiaries) needed or used to perform the action in a successful way. These particulars could be called tools (although Polanyi doesn’t use the concept tool in this general sense). Focal target of the action constitutes also the meaning and context of particulars. The relation of a subsidiary to a focus is formed by the act of a person who integrates one to the other (Polanyi&Prosch 1975, 38). It’s a functional relation, which is called from-to relation by Polanyi (Polanyi&Prosch 1975, 34). In every action there is from-to relation and therefore there is always a personal component.
In every action there are some “particulars” (also called parts or subsidiaries) needed or used to perform the action in a successful way. These particulars could be called tools (although Polanyi doesn’t use the concept tool in this general sense). Focal target of the action constitutes also the meaning and context of particulars. The relation of a subsidiary to a focus is formed by the act of a person who integrates one to the other (Polanyi&Prosch 1975, 38). It’s a functional relation, which is called from-to relation by Polanyi (Polanyi&Prosch 1975, 34). In every action there is from-to relation and therefore there is always a personal component.
performances there is subsidiary knowledge, which can talk about by shifting our awareness to subsidiaries of action. Still, in all action and knowing there are parts, which we cannot tell: it’s knowing by indwelling. In some actions (B) focal awareness is dominating (like programming, inferring, counting). In some other actions (A) subsidiary awareness is dominating (like swimming, playing tennis, running). In all action from moving body to observations to thinking there does exist some component, which could be known only by dwelling in it, that is, knowing how to do it. Implicit and indwelling knowledge are tacit knowledge. Nielsen& Nielsen make a useful distinction in their article Spoken-about knowledge (Nielsen&Nielsen 2005). According to them some of our tacit knowledge is not only unspoken, but also unspeakable. They think that one could still speak about unspeakable, say by metaphors or by other clever expressions. They introduce a third kind of knowledge beside tacit and explicit knowledge, calling it spoken-about knowledge. It’s “an intermediary step in the process of making knowledge explicit and allowing reflection of tacit knowledge” (p. 253). In referring to tacit knowledge Nielsens write that “there is a dimension of spoken-about knowledge wherein comparison and reflection are enhanced by anecdotes, by incomplete linguistic expressions, or by metaphors and metonyms” (p. 251). Unspeakable knowledge is indwelling knowledge in terms of Polanyi. Spoken-about knowledge is created or made possible by shifting awareness from the focal to subsidiaries.
performances there is subsidiary knowledge, which can talk about by shifting our awareness to subsidiaries of action. Still, in all action and knowing there are parts, which we cannot tell: it’s knowing by indwelling. In some actions (B) focal awareness is dominating (like programming, inferring, counting). In some other actions (A) subsidiary awareness is dominating (like swimming, playing tennis, running). In all action from moving body to observations to thinking there does exist some component, which could be known only by dwelling in it, that is, knowing how to do it. Implicit and indwelling knowledge are tacit knowledge. Nielsen& Nielsen make a useful distinction in their article Spoken-about knowledge (Nielsen&Nielsen 2005). According to them some of our tacit knowledge is not only unspoken, but also unspeakable. They think that one could still speak about unspeakable, say by metaphors or by other clever expressions. They introduce a third kind of knowledge beside tacit and explicit knowledge, calling it spoken-about knowledge. It’s “an intermediary step in the process of making knowledge explicit and allowing reflection of tacit knowledge” (p. 253). In referring to tacit knowledge Nielsens write that “there is a dimension of spoken-about knowledge wherein comparison and reflection are enhanced by anecdotes, by incomplete linguistic expressions, or by metaphors and metonyms” (p. 251). Unspeakable knowledge is indwelling knowledge in terms of Polanyi. Spoken-about knowledge is created or made possible by shifting awareness from the focal to subsidiaries.
Figure 5. The knowledge conversions in SECI model (modified by the author) “There are two types of knowledge: explicit knowledge and tacit knowledge. Explicit knowledge can be expressed in formal and systematic language and shared in the form of data, scientific formulae, specifications, manuals, and such. It can be processed, transmitted, and stored relatively easy. On the other hand, tacit knowledge is highly personal and hard to formalize. Subjective insights, intuitions, and hunches fall into this category of knowledge. Tacit knowledge is deeply rooted in action, procedures, routines, commitment, ideal, values, or emotions. It “indwells” in a comprehensive cognizance of the human mind and body .... [T]acit knowledge and explicit knowledge are complementary to each other, and both types of knowledge are essential to knowledge creation.”
Figure 5. The knowledge conversions in SECI model (modified by the author) “There are two types of knowledge: explicit knowledge and tacit knowledge. Explicit knowledge can be expressed in formal and systematic language and shared in the form of data, scientific formulae, specifications, manuals, and such. It can be processed, transmitted, and stored relatively easy. On the other hand, tacit knowledge is highly personal and hard to formalize. Subjective insights, intuitions, and hunches fall into this category of knowledge. Tacit knowledge is deeply rooted in action, procedures, routines, commitment, ideal, values, or emotions. It “indwells” in a comprehensive cognizance of the human mind and body .... [T]acit knowledge and explicit knowledge are complementary to each other, and both types of knowledge are essential to knowledge creation.”
Information channels (Internet, Journals etc.) Figure 6. Networks of practice between members of communities of practice based on similar practice
Information channels (Internet, Journals etc.) Figure 6. Networks of practice between members of communities of practice based on similar practice
A case in point is a linkage called a bridge, which is the sole links between two individual actors in a social network (see Burt 1992). Bridges allows individual actors in one circle to have access to resources embedded in links in another circle that otherwise would not be accessible. We make a useful distinction between direct bridges and mediated bridges. A person or an actor (b) who is the only link of a circle A to another circle C, forms a direct bridge between these two circles. On the other hand, a person or an actor (B) who has links to two separated circles A and C forms a mediated bridge between them. The actor B is in the role of broker by mediating connection between A and C (see Figure 7). A note about IT-channels is in order here. In global networked economy firms are turning to be “network enterprises” whose businesses are performed by ad hoc networks (see Castells 2001, Benkler 2006). The basis for the emergence of network enterprises is in computers and Internet-technology: economy is organized by around computer networks. These networks are global, flexible and adaptive. Computer networks provide a huge
A case in point is a linkage called a bridge, which is the sole links between two individual actors in a social network (see Burt 1992). Bridges allows individual actors in one circle to have access to resources embedded in links in another circle that otherwise would not be accessible. We make a useful distinction between direct bridges and mediated bridges. A person or an actor (b) who is the only link of a circle A to another circle C, forms a direct bridge between these two circles. On the other hand, a person or an actor (B) who has links to two separated circles A and C forms a mediated bridge between them. The actor B is in the role of broker by mediating connection between A and C (see Figure 7). A note about IT-channels is in order here. In global networked economy firms are turning to be “network enterprises” whose businesses are performed by ad hoc networks (see Castells 2001, Benkler 2006). The basis for the emergence of network enterprises is in computers and Internet-technology: economy is organized by around computer networks. These networks are global, flexible and adaptive. Computer networks provide a huge
Table 3. Properties of search and learning networks
Table 3. Properties of search and learning networks
Table 4: Modes of innovation The table 4 summarizes concepts of “open innovation”. There are three alternatives to close innovation paradigm. The most moderate step is to start to buy external ideas and sell own ideas = open innovation. Or, firms might build a collaborative multi-firm network to develop together new ideas and to share them = semi-public innovation. And finally, firm could start to work in a totally open environment sharing knowledge freely = public innovation. So we have four modes of innovation (see Table 4).
Table 4: Modes of innovation The table 4 summarizes concepts of “open innovation”. There are three alternatives to close innovation paradigm. The most moderate step is to start to buy external ideas and sell own ideas = open innovation. Or, firms might build a collaborative multi-firm network to develop together new ideas and to share them = semi-public innovation. And finally, firm could start to work in a totally open environment sharing knowledge freely = public innovation. So we have four modes of innovation (see Table 4).

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References (42)

  1. Baghramian Maria (2004): Relativism. London and New York: Routledge.
  2. Barabási Albert-László (2002): Linked, The new Science of Networks. Cambridge Mass.: Perseur Publishing.
  3. Benkler Yochai (2006): The Wealth of Networks, How Social Production Transforms Markets and Freedom. New Haven and London: Yale University Press.
  4. Blackburn Simon (2005): Truth, a Guide. New York: Oxford University Press.
  5. Brown John Seely & Duguid Paul (2001): Knowledge and Organization: A Social- Practice Perspective. Organization Science, 12(2), 198-213.
  6. Brown John Seely &Duguid Paul (2002): Local Knowledge, Innovation in the Networked Age. Management Learning, Vol. 33(4), 427-437.
  7. Burt Ronald (1992): Structural Holes: The social Structure of Competition. Cambridge: Mass.: Harvard University Press.
  8. Castells Manuel (2001): The Internet Galaxy, Reflections on the Internet, Business, and Society. New York: Oxford University Press.
  9. Chesbrough Henry (2003): Open Innovation, The new Imperative for Creating and Profiting from Technology. Boston: Harvard Business School Press.
  10. Chesbrough Henry (2006): Open Business Models: How to Thrive in the New Innovation Landscape. Boston: Harvard Business School Press.
  11. Duguid Paul (2005): "The art of Knowing": Social and Tacit Dimensions of Knowledge and the Limits of the Community of Practice. The Information Society, 21, 109-118.
  12. Dummett Michael (2004): Truth and the Past. New York: Columbia University press.
  13. Dewey John (1929): The Quest for Certainty: A Study of the Relation of Knowledge and Action.
  14. Fuller Steven (2006): The Philosophy of Science and Technology Studies. New York, London: Routledge.
  15. Geiger Roger L. (2004): Knowledge and Money, Research Universities and the Paradox of the Marketplace. Stanford: Stanford University Press.
  16. Granovetter Mark (1973): The Strength of Weak Links. American Journal of Sociology, 78, 1360-1380.
  17. Hakkarainen Kai, Palonen Tuire, Paavola Sami & Lehtinen Erno (2004): Communities of Networked Expertise, Professional and Educational Perspectives. Amsterdam-Tokyo: Elsevier.
  18. Hautamäki Antti (2010): Sustainable innovation, A new age of innovation and Finland's innovation policy. Sitra Reports 87. Helsinki: Sitra.
  19. Helpman Elhanan (2004): The Mystery of Economic Growth. Cambridge, Mass. and London, England: The Belknap Press of Harvard University Press.
  20. Kuhn Thomas S. (1962): The Structure of Scientific Revolution. Chicago: University of Chicago Press.
  21. Lehenkari Janne (2006): The Networks of Learning in Technological Innovation, The Emergence of Collaboration Across Fields of Expertise. Helsinki: Helsinki University Press.
  22. Lin Nan (2001): Social Capital, A Theory of Social Structure and Action. Cambridge University Press.
  23. Merleau-Ponty Maurice (1992): Phenomenology of Perception. London: Routledge.
  24. Miles Raymond, Miles Grant & Snow Charles C. (2005): Collaborative Entrepreneurship. Stanford: Stanford Business Books.
  25. Nielsen Niels Christian & Nielsen Maj Manage (2006): Spoken about Knowledge: Why It Takes Much More than Knowledge Management to manage Knowledge. In Zysman John and Newman Abraham (eds.) (2006): How revolutionary was the digital revolution? Stanford: Stanford Business Books. 242-266.
  26. Nonaka Ikujiro & Takeuchi H. (1995): The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York: Oxford University Press.
  27. Nonaka Ikujiro, Toyoma Ryoko & Konno Noboru (2000): SECI, Ba and leadership: A unified model of dynamic knowledge creation. Long Range Planning, 33, 1-31.
  28. Nonaka Ikujiro, Kohlbachter Florian & Holden Nigel (2006): Aging and Innovation: Recreating and Refining High-quality Tacit Knowledge through Phronetic Leadership. Paper for 2006 Annual Meeting of the Academy of Management, Atlanta.
  29. Polanyi Michael (1996): The Tacit Dimension. Garden City, NY: Doudleday.
  30. Polanyi Michael (1964): Personal Knowledge, Towards a Port-Critical Philosophy. New York: Harper & Row (First Harper Torchbook edition, orig. 1958 by Chicago Press).
  31. Polanyi Michael & Prosch Harry (1977): Meaning. Chicago: The University of Chicago Press.
  32. Powell W. W. (1990): Neither market nor hierarchy: Network forms of organization. Research in Organizational Behavior, 12, 295-336.
  33. Powell W. W., Koput K. W. & Smoth-Doerr L. (1996): Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 41, 1, 116-145.
  34. Putnam Hilary (1988): Representation and Reality. Cambridge, Mass., London, England: The MIT Press.
  35. Putnam Hilary (2004): Ethics without Ontology. Cambridge, Mass., London, England: Harvard University Press.
  36. Rorty Richard (1979): Philosophy and the Mirror of Nature. Princeton: Princeton University Press.
  37. Ryle Gilbert (1949): The Concept of Mind. London: Hutchinson. (1969, New York: Barnes & Noble).
  38. Schumpeter Joseph (1934): The Theory of Economic Development. Cambridge, Mass.: Harvard University Press.
  39. Teece David J., Pisano Gary & Shuen Amy (1997): Dynamic Capabilities and Strategic Management. Strategic Management Journal, 18, 7, 509-533.
  40. Von Hippel Eric (2005): Democratizing Innovation. Cambridge, Mass.: The MIT Press.
  41. Weber Steven (2004): The Success of Open Source. Boston: Harvard University Press.
  42. Williams Michael (2001): Problems of Knowledge, A Critical Introduction to Epistemology. Oxford: Oxford University Press.

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