Knowledge Management in Practice

  • Stephen C. Clark
  • Theodora Valvi
Part of the Palgrave Studies in Democracy, Innovation, and Entrepreneurship for Growth book series (DIG)


Knowledge management in practice is the overall objective of this chapter. Within this context, the authors provide the readers an overview and guidance on building a knowledge management system, organizational culture, and cultural shifts within the context of knowledge management. This includes the introduction of various models that have been introduced in business and academic literature pertaining to structure, culture, and technology. The chapter will conclude by bringing all the concepts together from Chaps.  1 to  4 through a deep dive into invention, innovation, and entrepreneurship. These three concepts will be inserted into processes of knowledge and strategic knowledge arbitrage and serendipity (SKARSE) components, processes, and strategies.


  1. Alvarez, S. A., & Barney, J. B. (2005). How do entrepreneurs organize firms under conditions of uncertainty? Journal of Management, 31(5), 776–793.CrossRefGoogle Scholar
  2. Auerswald, P. E., & Branscomb, L. M. (2003). Valleys of death and Darwinian seas: Financing the invention to innovation transition in the United States. Journal of Technology Transfer, 28(3–4), 227–239.CrossRefGoogle Scholar
  3. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120.CrossRefGoogle Scholar
  4. Barney, J., Wright, M., & Ketchen, D. J. (2001). The resource-based view of the firm: Ten years after 1991. Journal of Management, 27, 625–641.CrossRefGoogle Scholar
  5. Boutellier, R., Ullman, F., Schreiber, J., & Naef, R. (2008). Impact of office layout on communication in a science driven business. R&D Management, 38(4), 372–391.CrossRefGoogle Scholar
  6. Bratianu, C. (2011). Changing paradigm for knowledge metaphors from dynamics to thermodynamics. Systems Research and Behavioral Science, 28, 160–169.CrossRefGoogle Scholar
  7. Carayannis, E. G. (1994). The strategic management of technological learning: Transnational decision making frameworks and their empirical effectiveness. Doctoral dissertation, Rensselaer Polytechnic Institute, Troy, New York.Google Scholar
  8. Carayannis, E. G. (2008). Knowledge-driven creative destruction, or leveraging knowledge for competitive advantage: Strategic knowledge arbitrage and serendipity as real options drivers triggered by co-opetition, co-evolution and co-specialization. Industry & Higher Education, 22(6), 1–11.CrossRefGoogle Scholar
  9. Carleton, K. (2011). How to motivate and retain knowledge workers in organizations: A review of the literature. International Journal of Management, 28(2), 459–468.Google Scholar
  10. Chan, I., & Chao, C. K. (2008). Knowledge management in small and medium-sized enterprises: A balanced combination of management support, technology, and organizational structural factors is necessary for successful knowledge management program implementation. Communications of the ACM, 51(4), 83–88.CrossRefGoogle Scholar
  11. Chatterji, A. K. (2009). Spawned with a silver spoon? Entrepreneurial performance and innovation in the medical device industry. Strategic Management Journal, 30, 185–206.CrossRefGoogle Scholar
  12. Chuttur, M. Y. (2009). Overview of the technology acceptance model: Origins, developments and future directions. Sprouts: Working Papers on Information Systems, 9(37). Retrieved from
  13. Cohen, W., & Levinthal, D. (1989). Innovation and learning: The two faces of R&D. Economic Journal, Royal Economic Society, 99(397), 569–596.Google Scholar
  14. Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation, Sloan School of Management, Massachusetts Institute of Technology.Google Scholar
  15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.CrossRefGoogle Scholar
  16. Davis, F. D., Bagozzi, P. R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982–1003.CrossRefGoogle Scholar
  17. Denrell, J., Fang, C., & Winter, S. G. (2003). The economics of strategic opportunity. Strategic Management Journal, 24(10), 977–990.CrossRefGoogle Scholar
  18. Dew, N. (2009). Serendipity in entrepreneurship. Organization Studies, 30(07), 735–753.CrossRefGoogle Scholar
  19. Ding, M., & Eliashberg, J. (2002). Structuring the new product development pipeline. Management Science, 48(3), 343–363.CrossRefGoogle Scholar
  20. Dingel, K., & Spiekermann, S. (2007). Third generation knowledge management systems: Towards an augmented technology acceptance model. SSRN. Retrieved from
  21. Drucker, P. F. (1985). Innovation and entrepreneurship: Practice and principles. New York: Harper Collins.Google Scholar
  22. Earl, M. J., & Scott, I. A. (1999). What is a chief knowledge officer? Sloan Management Review, 40(2), 29–38.Google Scholar
  23. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.Google Scholar
  24. Foster, A., & Ford, N. (2003). Serendipity and information seeking: An empirical study. Journal of Documentation, 59(3), 321–340.CrossRefGoogle Scholar
  25. Freear, J., Sohl, J. E., & Wetzel, W. (2002). Angels on angles: Financing technologies-based ventures – A historical perspective. Venture Capital, 4(4), 275–287.CrossRefGoogle Scholar
  26. Gupta, B., Iyer, L. S., & Aronson, J. E. (2000). Knowledge management: Practices and challenges. Industrial Management & Data Systems, 100(1), 17–21.CrossRefGoogle Scholar
  27. Hemp, P. (2009). Death by information overload: New research and novel techniques offer a lifetime to you and your organization. Harvard Business Review, 3, 83–89.Google Scholar
  28. Hong, J. F. L., & Nguyen, T. V. (2009). Knowledge embeddedness and the transfer mechanisms in multinational corporations. Journal of World Business, 44(4), 347–356.CrossRefGoogle Scholar
  29. Huseby, T., & Chou, S. T. (2003). Applying a knowledge-focused management philosophy to immature economies. Industrial Management & Data Systems, 103(2), 126–132.CrossRefGoogle Scholar
  30. Ito, K., & Lechevalier, S. (2010). Why some firms persistently out-perform others: Investing the interactions between innovation and exporting strategies. Industrial and Corporate Change, 19(6), 1997–2039.CrossRefGoogle Scholar
  31. Jaruzelski, B., & Dehoff, K. (2010). The global innovation 1000. How the top innovators keep winning: Booz and Company’s annual study of the world’s biggest R&D spenders show why highly innovative companies are able to consistently outperform. Their secret? They’re good at the right things, not at everything. Strategy + Business, 61, 1–14.Google Scholar
  32. Karnani, F. (2012). The university’s unknown knowledge: Tacit knowledge, technology transfer and university spin-offs findings from an empirical study based on the theory of knowledge. Journal of Technology Transfer, 38(3), 235–250.CrossRefGoogle Scholar
  33. Kerin, R. A., Varadarajan, R., & Peterson, R. A. (1992). First-mover advantage: A synthesis, conceptual framework, and research propositions. Journal of Marketing, 56, 33–52.CrossRefGoogle Scholar
  34. Key, M., Thompson, H., & McCann, J. (2009). Knowledge management: A glass half full. People & Strategy, 32(4), 43–47.Google Scholar
  35. King, W. R., Marks, P. W., & McCoy, S. (2002). The most important issues in knowledge management: What can KM do for corporate memory, management thinking, and IS responsibility, as well as for overall business performance? Communications of the ACM, 45(9), 93–97.CrossRefGoogle Scholar
  36. Koen, P., Ajamian, G., Burkart, R., Clamen, A., Davidson, J., D’Amore, R., et al. (2001). Providing clarity and a common language to the “fuzzy front end”. Research Technology Management, 44(2), 46–55.CrossRefGoogle Scholar
  37. Lichtenstein, S., & Hunter, A. (2006). Toward a receiver-based theory of knowledge sharing. International Journal of Knowledge Management, 2(1), 24–40.CrossRefGoogle Scholar
  38. Lim, W. M., & Ting, D. H. (2012). E-shopping: An analysis of the technology acceptance model. Modern Applied Science, 6(4), 49–62.CrossRefGoogle Scholar
  39. Markus, M. L. (2001). Toward a theory of knowledge reuse: Types of knowledge reuse situations and factors in reuse success. Journal of Management Information Systems, 18(1), 57–93.CrossRefGoogle Scholar
  40. Plessis, M. D. (2005). Drivers of knowledge management in the corporate environment. International Journal of Information Management, 25(3), 193–202.CrossRefGoogle Scholar
  41. Porter, C. E., & Donthu, N. (2008). Cultivating trust and harvesting value in virtual communities. Management Science, 54(1), 113–128.CrossRefGoogle Scholar
  42. Rahmandad, H. (2008). Effect of delays on complexity of organizational learning. Management Science, 54(7), 1297–1312.CrossRefGoogle Scholar
  43. Schneckenberg, D. (2009). Web 2.0 and the empowerment of the knowledge worker. Journal of Knowledge Management, 13(6), 509–520.CrossRefGoogle Scholar
  44. Schumpeter, J. A. (1934). The theory of economic development. London: Oxford University Press.Google Scholar
  45. Silver, D. A. (1985). Entrepreneurial megabucks: The 100 greatest entrepreneurs of the last 25 years. New York: John Wiley and Sons.Google Scholar
  46. Song, J., Almeida, P., & Wu, G. (2003). Learning-by-hiring: When is mobility more likely to facilitate interfirm knowledge transfer? Management Science, 49(4), 351–365.CrossRefGoogle Scholar
  47. Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy, 15, 285–305.CrossRefGoogle Scholar
  48. Turner, M., Kitchenham, B., Brereton, P., Charters, S. M., & Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information & Software Technology, 52(5), 463–479.CrossRefGoogle Scholar
  49. Van de Ven, A. H. (1986). Central problems in the management of innovation. Management Science, 32(5), 590–607.CrossRefGoogle Scholar
  50. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365.CrossRefGoogle Scholar
  51. Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451–481.CrossRefGoogle Scholar
  52. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.CrossRefGoogle Scholar
  53. Vohra, M., & Mukul, K. (2009). Relevance of Peter Drucker’s work: Celebrating Drucker’s 100th birthday. Vikalpa, 34(4), 1–7.Google Scholar
  54. Wang, D., Su, Z., & Yang, D. (2011). Organizational culture and knowledge creation capacity. Journal of Knowledge Management, 15(3), 363–373.CrossRefGoogle Scholar
  55. Webster’s Dictionary Online. (2013). Retrieved from
  56. West, P. G., & Bamford, C. E. (2005). Creating a technology-based entrepreneurial economy: A resource based theory perspective. Journal of Technology Transfer, 30(4), 433–451.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2018

Authors and Affiliations

  • Stephen C. Clark
    • 1
  • Theodora Valvi
    • 2
  1. 1.California State University, SacramentoSan DiegoUSA
  2. 2.Independent ResearcherAthensGreece

Personalised recommendations