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Sizing & Allocation in Labour Market: business strategies and multivariate analysis

  • Andrea Marletta

In Labour Market, the issue of Sizing and Allocation is a discussed problem. In this study, this topic has been considered from a statistical point of view. Indeed, the choice to change the number of your team of employees in a business context needs a very accurate analysis. If for example a firm decides to launch a new product on the market, it could be necessary to recruit new resources. The proposed statistical approach aims to give some hints about the total number of employees analysing the features of the existing market and the territorial geography. From a statistical point of two techniques of multivariate analysis have been presented as exploratory tools. In the application, a Principal Component Analysis has been used to investigate the business environment after some qualitative interviews to the board of the company. In a second step, some different scenarios have been proposed to determine the exact number of new resources using a data hybridization technique including internal and external sources. Finally, the allocation of the new hired of the scenarios on the Italian territory has been achieved thanks to the construction of a territorial potential index.

  • Keywords:
  • Labour Market,
  • Multivariate analysis,
  • Number of employees,
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Andrea Marletta

University of Milano-Bicocca, Italy - ORCID: 0000-0002-4050-5316

  1. Istat a. (2020). Health for All. <https://www.istat.it/it/archivio/14562>.
  2. Istat b. (2020). Geo-demo. <http://demo.istat.it/>.
  3. Jolliffe, I. T. (2002). Principal Component Analysis, 2nd edn. Series: Springer Series in Statistics, XXIX, 487. illus. Springer, NY, 28.
  4. Mariani, P., (2002). La statistica in azienda, contesti ed applicazioni. Franco Angeli, Milano.
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  • Anno di pubblicazione: 2021
  • Pagine: 121-124

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  • Anno di pubblicazione: 2021

Informazioni sul capitolo

Titolo del capitolo

Sizing & Allocation in Labour Market: business strategies and multivariate analysis

Autori

Andrea Marletta

Lingua

English

DOI

10.36253/978-88-5518-461-8.23

Opera sottoposta a peer review

Anno di pubblicazione

2021

Copyright

© 2021 Author(s)

Licenza d'uso

CC BY 4.0

Licenza dei metadati

CC0 1.0

Informazioni bibliografiche

Titolo del libro

ASA 2021 Statistics and Information Systems for Policy Evaluation

Sottotitolo del libro

BOOK OF SHORT PAPERS of the on-site conference

Curatori

Bruno Bertaccini, Luigi Fabbris, Alessandra Petrucci

Opera sottoposta a peer review

Anno di pubblicazione

2021

Copyright

© 2021 Author(s)

Licenza d'uso

CC BY 4.0

Licenza dei metadati

CC0 1.0

Editore

Firenze University Press

DOI

10.36253/978-88-5518-461-8

eISBN (pdf)

978-88-5518-461-8

eISBN (xml)

978-88-5518-462-5

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Proceedings e report

ISSN della collana

2704-601X

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2704-5846

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