Competitiveness Scale as a Basis for Brazilian Small and Medium-Sized Enterprises

Abstract

This paper aims to present a competitiveness scale, outlining the variables that influence competitiveness in small and medium-sized enterprises (SMEs) in Southern Brazil. Using survey data from 72 industrial SME managers, the Multi-Attribute Utility Theory (MAUT) was applied to a model to measure Brazilian SMEs’ competitiveness rates. The variables that influence their competitiveness were identified and structured in a decision tree with three levels: key performance indicators (KPIs), critical success factors (CSFs), and fundamental points of view (FPVs). It was possible to identify the KPIs, CSFs, and FPVs that are more important for SMEs’ competitiveness and measure their competitiveness rates. The managerial decision-making processes in SMEs can be defined following the competitiveness standards in this research.

Keywords:

• Multi-Attribute Utility Theory
• Key Performance Indicators
• Small and Medium-Sized Enterprises
• Individual Competitiveness Rate
• Global Competitiveness Rate
• Decision-Making

EMJ Focus Areas:

• Decision Making & Risk Management, Operations Management, Organizational & Performance Assessment, Strategic Management

Acknowledgements

The authors want to thank Coordenação de Aperfeiçoamento de Pessoal de Nível Superior for granting them scholarships, and to CNPq, CAPES, FAPERGS and Institutos Nacionais de Ciência e Tecnologia – Geração Distribuída (INCT-GD) for supporting this research.

Additional information

Funding

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. This work was also supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) [grant numbers 142448/2018-4, 308723/2017-1, 311926/2017-7 and 465640/2014-1], Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) [grant number 23038.000776/2017-54] and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS) [grant number 17/2551-0000517-1]. Baierle were supported by a post doc grant of CAPES – Brazil [CAPES process Baierle No. 88887.464876/2019-00].

Notes on contributors

J. L. Schaefer

Jones Luís Schaefer is a PhD student in Production Engineering at Federal University of Santa Maria. Master in Industrial Systems and Processes and Production Engineer from the University of Santa Cruz do Sul. Key areas of his research are multicriteria analysis, performance indicators, competitiveness, artificial intelligence, industry 4.0, neural networks, energy management, and energy cloud management.

I. C. Baierle

Ismael Cristofer Baierle is a Post-Doctoral student at Federal University of Santa Maria. He received his PhD in Production and Systems Engineering in 2019 from University of Vale do Rio dos Sinos. Master in Industrial and Systems and Processes and Production Engineer from University of Santa Cruz do Sul. Key areas of his research are multicriteria analysis, performance indicators, competitiveness, artificial intelligence, industry 4.0, and neural networks.

M. A. Sellitto

Miguel Afonso Sellitto earned his doctorate in industrial engineering. His research activities include advanced manufacturing management dealing with operations, supply chains, automation, and production management. Dr. Sellitto currently holds positions as a professor and researcher at UNISINOS University in the Production and System Engineering Graduate Program and provides consultancy services on problems related to his research line. He can be reached by e-mail at [email protected].

J. C. M. Siluk

Julio Cezar Mairesse Siluk is Graduated in Business Administration (1987) and Master in Production Engineering from Federal University of Santa Maria (2001). He concluded his PhD in Production Engineering at the Federal University of Santa Catarina (2007), and currently is a professor at the Federal University of Santa Maria. He research mainly on the following topics: Strategic Management, Innovation and Competitiveness, Performance Evaluation, Strategic Planning, Performance Indicators, Investment Analysis and Balanced Scorecard.

J. C. Furtado

João Carlos Furtado completed his doctorate in Applied Computing at the National Institute for Space Research in 1998. He is currently an Adjunct Professor at the University of Santa Cruz do Sul. and the Graduate Program in Industrial Systems and Processes - PPGSPI. Guided of scientific initiation work and master’s students. He was head of the Department of Informatics-UNISC and coordinator of PPGSPI-UNISC. He has been researching optimization methods in solving industrial problems.

E. O. B. Nara

Elpidio Oscar Benitez Nara completed his Post Doctorate at Federal University of Santa Maria in 2014. He concluded his Doctorate in Quality Management and Productivity at the Federal University of Santa Catarina in 2005. Master Degree in Production Engineering and Mechanical Engineer. He is an Adjunct Professor at the University of Santa Cruz do Sul, Brazil. He has experience in the area of management and engineering with emphasis in administration production and production engineering.