EconPapers    
Economics at your fingertips  
 

A NCaRBS analysis of SME intended innovation: Learning about the Don’t Knows

Malcolm J Beynon, Paul Jones, David Pickernell and Gary Packham

Omega, 2016, vol. 59, issue PA, 97-112

Abstract: This study demonstrates a novel form of business analytics, respecting the quality of the data available (allowing incompleteness in the data set), as well as engaging with the uncertainty in the considered outcome variable (inclusive of Don’t Know (DK) responses). The analysis employs the NCaRBS technique, based on the Dempster–Shafer theory of evidence, to investigate the relationship between Small and Medium-sized Enterprise (SME) characteristics and whether they intended to undertake future innovation. The allowed outcome response for intended innovation was either, Yes, No and DK, all of which are considered pertinent responses in this analysis. An additional consequence of the use of the NCaRBS technique is the ability to analyse an incomplete data set, with missing values in the characteristic variables considered, without the need to manage their presence. From a soft computing perspective, this study demonstrates just how exciting the business analytics field of study can be in terms of pushing the bounds of the ability to handle real ‘incomplete’ business data which has real, and sometimes uncertain, outcomes. Further, the findings also inform how different notions of ignorance in evidence are accounted for in such analysis.

Keywords: SME; NCaRBS; Don’t Know; Innovation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0305048315001206
Full text for ScienceDirect subscribers only

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:eee:jomega:v:59:y:2016:i:pa:p:97-112

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.omega.2015.04.018

Access Statistics for this article

Omega is currently edited by B. Lev

More articles in Omega from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:jomega:v:59:y:2016:i:pa:p:97-112