Dealing with Interpretability Issues in Predicting Firm Growth: Factor Analysis Approach

Bilandžić Ana (), Marina Jeger () and Šarlija Nataša ()
Additional contact information
Bilandžić Ana: Faculty of Economics in Osijek, J.J. Strossmayer University of Osijek, Croatia
Marina Jeger: Faculty of Economics in Osijek, J.J. Strossmayer University of Osijek, Croatia
Šarlija Nataša: Faculty of Economics in Osijek, J.J. Strossmayer University of Osijek, Croatia

Business Systems Research, 2016, vol. 7, issue 2, 23-34

Abstract: Background: Alongside the theoretical progress made in understanding the factors that influence firm growth, many methodological challenges are yet to be overcome. Authors point to the notion of interpretability of growth prediction models as an important prerequisite for further advancement of the field as well as enhancement of models’ practical values.Objectives: The objective of this study is to demonstrate the application of factor analysis for the purpose of increasing overall interpretability of the logistic regression model. The comprehensive nature of the growth phenomenon implies propensity of input data to be mutually correlated. In such situations, growth prediction models can demonstrate adequate predictability and accuracy, but still lack the clarity and theoretical soundness in their structure.Methods/Approach: The paper juxtaposes two prediction models: the first one is built using solely the logistic regression procedure, while the second one includes factor analysis prior to development of a logistic regression model.Results: Factor analysis enables researchers to mitigate inconsistencies and misalignments with a theoretical background in growth prediction models.Conclusions: Incorporating factor analysis as a step preceding the building of a regression model allows researchers to lessen model interpretability issues and create a model that is easier to understand, explain and apply in real-life business situations.

Keywords: factor analysis; logistic regression; interpretability; growth prediction model (search for similar items in EconPapers)
JEL-codes: C53 C55 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/bsrj-2016-0010 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bit:bsrysr:v:7:y:2016:i:2:p:23-34

DOI: 10.1515/bsrj-2016-0010

Access Statistics for this article

Business Systems Research is currently edited by Mirjana Pejić Bach

More articles in Business Systems Research from Sciendo
Bibliographic data for series maintained by Peter Golla ().