Title: Competitiveness metrics for small and medium-sized enterprises through multi-criteria decision making methods and neural networks

Authors: Jones Luís Schaefer; Elpidio Oscar Benitez Nara; Julio Cezar Mairesse Siluk; Ismael Cristofer Baierle; Matheus Becker Da Costa; João Carlos Furtado

Addresses: Production Engineering Graduate Program, Universidade Federal de Santa Maria, Avenida Roraima, 1000, Cidade Universitária, Bairro Camobi, Santa Maria, RS, 97105-900, Brazil ' Industrial Systems and Processes Graduate Program, Universidade de Santa Cruz do Sul, Avenida Independência, 2293, Bairro Universitário, Santa Cruz do Sul, RS, 96815-900, Brazil ' Production Engineering Graduate Program, Universidade Federal de Santa Maria, Avenida Roraima, 1000, Cidade Universitária, Bairro Camobi, Santa Maria, RS, 97105-900, Brazil ' Production Engineering Graduate Program, Universidade Federal de Santa Maria, Avenida Roraima, 1000, Cidade Universitária, Bairro Camobi, Santa Maria, RS, 97105-900, Brazil ' Industrial Systems and Processes Graduate Program, Universidade de Santa Cruz do Sul, Avenida Independência, 2293, Bairro Universitário, Santa Cruz do Sul, RS, 96815-900, Brazil ' Industrial Systems and Processes Graduate Program, Universidade de Santa Cruz do Sul, Avenida Independência, 2293, Bairro Universitário, Santa Cruz do Sul, RS, 96815-900, Brazil

Abstract: This paper aims to present a way to obtain competitiveness metrics for small and medium-sized enterprises (SMEs) in a country with emerging characteristics. Key performance indicators (KPIs) were selected through a bibliographical research and fuzzy-Delphi method. Competitiveness rates were obtained modelling these KPIs through a hybrid approach between VIKOR and TODIM methods, and artificial neural networks (ANNs). A set of 18 KPIs to evaluate, monitor and control SMEs competitiveness was defined. Individual competitiveness rates (ICRs) were obtained for SMEs and an average of 78.33 with the ANN × VIKOR hybridisation and 81.61 with the ANN × TODIM hybridisation (on a scale from 0 to 100). This paper can serve as parameter for other studies related to competitiveness evaluation. Through the KPIs set, it is possible to define measurement parameters, translating into better control and optimising possibilities for SMEs competitiveness, being used for comparisons and benchmarks for other similar Brazilian or global SMEs.

Keywords: competitiveness; multi-criteria decision making; MCDM; VIKOR; TODIM; artificial neural network; ANN; small and medium-sized enterprises; SMEs; key performance indicators; KPIs; individual competitiveness rate; ICR.

DOI: 10.1504/IJPMB.2022.121599

International Journal of Process Management and Benchmarking, 2022 Vol.12 No.2, pp.184 - 207

Received: 20 Mar 2020
Accepted: 09 May 2020
Published online: 21 Mar 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article