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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 111))

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Abstract

Most managers agree to that the staff’s selection is the most difficult and important decision. Why couldn’t the traditional selection method effectively predict future job performance of the candidates? Why are the recruitment decisions which emphasizing the high academic qualification and experiences often being challenged by the reality of ”high marks, high ability but low-performance”? The decision-making model is proposed in this paper as the answer. By the empirical analysis of the real practice data of one IT enterprise, we confirm that the rationality of the recruitment result can be improved and the high loss ratio of R&D staffs can be curbed from the ”source” by the use of the Model. It also proved that the scientific and reasonable evaluation model can help to inspect the candidates from multi-directional manners rather than focusing only on technical level and ability by the use of the fitful assessment tools so that it helps to improve the efficiency of the recruitment work.

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© 2011 Springer-Verlag Berlin Heidelberg

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Haiyan, W., Wu, Y. (2011). An Empirical Study on Decision-Making Model for Recruitment of R & D Staff of Enterprises. In: Jiang, L. (eds) Proceedings of the 2011, International Conference on Informatics, Cybernetics, and Computer Engineering (ICCE2011) November 19–20, 2011, Melbourne, Australia. Advances in Intelligent and Soft Computing, vol 111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25188-7_47

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  • DOI: https://doi.org/10.1007/978-3-642-25188-7_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25187-0

  • Online ISBN: 978-3-642-25188-7

  • eBook Packages: EngineeringEngineering (R0)

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