Effects on Individual CEOs

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

Abstract

The objective of this section is to present the reader with the effects of mobile devices on the individual chief executive officer (CEO), interpersonal relationships, and culture. Changes in practice occur using mobile devices. Knowledge workers and CEOs are considered one and the same. Through latent variable factor analysis, components emerge. Component 1 is absorbing information. Other factors also occurred such as cognition and intellect, reflection and learning, adaptations of learning and mobile devices, learning through problem solving, serendipity as an enhancement tool, and the process of serendipity compared to other actions. The chapter guides the reader to important areas of interest such as collective learning and face-to-face interactions, accessibility to knowledge traders and learning by hiring, and paradigm shifts within the context of mobile devices.

References

  1. 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
  2. Clough, G., Jones, A. C., McAndrew, P., & Scanlon, E. (2007). Informal learning with PDAs and Smartphones. Journal of Computer Assisted Learning, 24, 359–371.CrossRefGoogle Scholar
  3. Dew, N. (2009). Serendipity in entrepreneurship. Organization Studies, 30(07), 735–753.CrossRefGoogle Scholar
  4. Drucker, P. (2001). The essential Drucker. Oxford: Butterworth Heinemann.Google Scholar
  5. Foster, A., & Ford, N. (2003). Serendipity and information seeking: An empirical study. Journal of Documentation, 59(3), 321–340.CrossRefGoogle Scholar
  6. Giles, M. (2010). A special report on social networking: A world of connections. The Economist Print Edition. Retrieved from http://www.economist.com/node/15351002
  7. 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
  8. Ibarra, H., & Hunter, M. (2007). How leaders create and use networks. Harvard Business Review, 85(1), 40–47.Google Scholar
  9. Jobs, S. (2005). Prepared text of commencement address. Retrieved from http://news.stanford.edu/news/2005/june15/jobs-061505.html
  10. Kim, S. H. (2008). Moderating effects of job relevance and experience on mobile wireless technology acceptance: Adoption of a smartphone by individuals. Information Management, 45(6), 387–393.CrossRefGoogle Scholar
  11. 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
  12. Kuhn, T. S. (1970). The structure of scientific revolutions. Chicago, IL: University of Chicago Press.Google Scholar
  13. Leiponen, A., & Helfat, C. E. (2010). Innovation objectives, knowledge sources, and the benefits of breadth. Strategic Management Journal, 31(2), 224–236.CrossRefGoogle Scholar
  14. Liang, L. T., Huang, C. W., Yeh, Y. H., & Lin, B. (2007). Adoption of mobile technology in business: A fit-viability model. Industrial Management & Data Systems, 107(8), 1154–1169.CrossRefGoogle Scholar
  15. Liaw, S. S., Hatala, M., & Huang, H. M. (2010). Investing acceptance toward mobile learning to assist individual knowledge management: Based on activity theory approach. Computers & Education, 54(2), 446–454.CrossRefGoogle Scholar
  16. Newman, I., Ridenour, C. S., Newman, C., & DeMarco, G. M. P., Jr. (2003). A typology of research purposes and its relationship to mixed methods. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social & behavioral research (pp. 167–188). Thousand Oaks, CA: Sage.Google Scholar
  17. Nonaka, I. (1991). The knowledge-creating company. Harvard Business Review, 69(6), 96–104.Google Scholar
  18. Papert, S. (1993). The children’s machine: Rethinking the school in the age of computers. New York: Basic Books.Google Scholar
  19. Pentland, D., Forsyth, K., Maciver, D., Walsh, M., Murray, R., Irvine, L., et al. (2011). Key characteristics of knowledge transfer and exchange in healthcare: Integrative literature review. Journal of Advanced Nursing, 67(7), 1408–1425.CrossRefGoogle Scholar
  20. Polanyi, M. (1966). The tacit dimension. London: Routledge & Kegan Paul.Google Scholar
  21. Prahalad, C. K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79–91.Google Scholar
  22. Rahmandad, H. (2008). Effect of delays on complexity of organizational learning. Management Science, 54(7), 1297–1312.CrossRefGoogle Scholar
  23. Schneckenberg, D. (2009). Web 2.0 and the empowerment of the knowledge worker. Journal of Knowledge Management, 13(6), 509–520.CrossRefGoogle Scholar
  24. Silver, D. A. (1985). Entrepreneurial megabucks: The 100 greatest entrepreneurs of the last 25 years. New York: John Wiley and Sons.Google Scholar
  25. Thomas, B., Sparkes, B. T., Brooksbank, D., & Williams, R. (2002). Social aspects of the impact of information and communication technologies on agri-food SMEs in Wales. Outlook on Agriculture, 31(1), 35–41.CrossRefGoogle Scholar
  26. Wiig, K. (2004). People focused knowledge management. Boston, MA: Butterworth Heinemann.Google 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

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