University of Leicester
Browse
- No file added yet -

SME investment best strategies. Outliers for assessing how to optimize performance

Download (399.73 kB)
journal contribution
posted on 2018-09-21, 13:49 authored by Marcel Ausloos, Roy Cerqueti, Francesca Bartolacci, Nicola G. Castellano
Any research on strategies for reaching business excellence aims at revealing the appropriate course of actions any executive should consider. Thus, discussions take place on how effective a performance measurement system can be estimated, or/and validated. Relevant questions can be raised, like: can one find an adequate measure (i) on the performance result due to whatever level of investment, and (ii) on the timing of such investments? We argue that extreme value statistics provide the answer. We demonstrate that the level and timing of investments allow to be forecasting small and medium size enterprises (SME) performance, — at financial crisis times. The ”investment level” is taken as the yearly total tangible asset (TTA). The financial/economic performance indicators defining ”growth” are the sales or total assets variations; ”profitability” is defined from returns on investments or returns on sales. Companies on the Italian Stock Exchange STAR Market serve as example. It is found from the distributions extreme values that outlier companies (with positive performance) are those with the lowest but growing TTA. In contrast, the SME with low TTA, but which did not increase its TTA, before the crisis, became a ”negative outlier”. The outcome of these statistical findings should suggest strategies to SME board members.

History

Citation

Physica A: Statistical Mechanics and its Applications, 2018, 509, pp. 754-765

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/School of Business

Version

  • AM (Accepted Manuscript)

Published in

Physica A: Statistical Mechanics and its Applications

Publisher

Elsevier

issn

0378-4371

Acceptance date

2018-04-06

Copyright date

2018

Available date

2019-06-28

Publisher version

https://www.sciencedirect.com/science/article/pii/S0378437118307635

Notes

The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

Usage metrics

    University of Leicester Publications

    Categories

    No categories selected

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC