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Analysing factors affecting the choice of emergent human resource capital

Author

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  • S Irani

    (Swansea University, Swansea, Wales, UK)

  • Y K Dwivedi

    (Swansea University, Swansea, Wales, UK)

  • M D Williams

    (Swansea University, Swansea, Wales, UK)

Abstract

Ever since the announcement that UK higher education (HE) fees were to increase up to £9000, many universities have expressed concern about how to attract the best students while offering choice and promoting student mobility through broader access. This in turn has led to questioning how such complexity might be modelled using sophisticated operational research (OR) techniques. Because higher education institutions (HEIs) are now beginning to compete ‘against’ rather than ‘with’ each other, potential students are paying increased attention to where and what they will study, as well as graduate opportunities after their degree. Hence, the quality of education services becomes increasingly vital for HEIs in order to attract potential students. This study seeks to develop a framework of those factors affecting international (non-EU) students’ choice of institution. A number of factors were identified and collated from the existing literature providing a solid foundation on which to base this research. A survey approach was utilised to determine the importance of identified factors based on data collected from students of two different types of institutions (a university and a feeder institution). Through a better understanding of factors such as social influence, financial and career opportunities, universities should be well placed to construct models underpinned by OR principles that will promote scenario modelling and planning within HE.

Suggested Citation

  • S Irani & Y K Dwivedi & M D Williams, 2014. "Analysing factors affecting the choice of emergent human resource capital," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(6), pages 935-953, June.
  • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:6:p:935-953
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    Cited by:

    1. Julio López & Sebastián Maldonado & Ricardo Montoya, 2017. "Simultaneous preference estimation and heterogeneity control for choice-based conjoint via support vector machines," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1323-1334, November.
    2. Troilo, Michael & Bouchet, Adrien & Urban, Timothy L. & Sutton, William A., 2016. "Perception, reality, and the adoption of business analytics: Evidence from North American professional sport organizations," Omega, Elsevier, vol. 59(PA), pages 72-83.

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