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The search for skills: Knowledge stars and innovation in the hiring process

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  • Hamilton, R.H.
  • Davison, H. Kristl

Abstract

The effective utilization of knowledge has become an important part of how firms gain competitive advantage in the marketplace. However, the recruitment, search, and selection processes used to obtain workers who would develop and deploy that knowledge have not materially changed for many years, with human resources (HR) frequently automating legacy procedures. We believe that the hiring processes for exceptional knowledge workers, whom we call knowledge stars, must adapt to the current business environment. Using the framework of architectural innovation, we propose that HR’s recruitment of knowledge stars should begin before specific jobs are announced, should be done in partnership with line managers, and should be done in coordination with implementation of other workplace innovations such as the development of communities of practice and participative management. We conclude by discussing how changes in the search processes for knowledge stars fit in context with some other ongoing challenges for HR personnel.

Suggested Citation

  • Hamilton, R.H. & Davison, H. Kristl, 2018. "The search for skills: Knowledge stars and innovation in the hiring process," Business Horizons, Elsevier, vol. 61(3), pages 409-419.
  • Handle: RePEc:eee:bushor:v:61:y:2018:i:3:p:409-419
    DOI: 10.1016/j.bushor.2018.01.006
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    Cited by:

    1. Hamilton, R.H. & Sodeman, William A., 2020. "The questions we ask: Opportunities and challenges for using big data analytics to strategically manage human capital resources," Business Horizons, Elsevier, vol. 63(1), pages 85-95.
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    3. Kraft, Kornelius & Rammer, Christian, 2023. "Intended and unintended knowledge spillovers in innovation," ZEW Discussion Papers 23-015, ZEW - Leibniz Centre for European Economic Research.
    4. Rammer, Christian & Es-Sadki, Nordine, 2023. "Using big data for generating firm-level innovation indicators - a literature review," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    5. Muddassar Sarfraz & Kausar Fiaz Khawaja & Mahmoona Khalil & Heesup Han, 2023. "Knowledge-based HRM and business process innovation in the hospitality industry," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
    6. Ra'ed (Moh'd Taisir) Masa'deh, Dr. & Haneen Yaseen & Yasar Shatnawi & Bader Obeidat, Dr., 2018. "Reviewing the Literature of the Effect of Talent Management on Organizational Effectiveness," Journal of Social Sciences (COES&RJ-JSS), , vol. 7(2), pages 139-156, April.
    7. Black, J. Stewart & van Esch, Patrick, 2020. "AI-enabled recruiting: What is it and how should a manager use it?," Business Horizons, Elsevier, vol. 63(2), pages 215-226.
    8. Nick Drydakis, 2022. "Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic," Information Systems Frontiers, Springer, vol. 24(4), pages 1223-1247, August.
    9. Pietro Evangelista & Aino Kianto & Henri Hussinki & Mika Vanhala & Anna-Maija Nisula, 2023. "Knowledge-Based Human Resource Management, Logistics Capability, and Organizational Performance in Small Finnish Logistics Service Providers," Logistics, MDPI, vol. 7(1), pages 1-21, February.

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