Resumo

Título do Artigo

GENETIC ALGORITHM MODELLING OF EUROPEAN UNION FIRMS’ COMPETITIVE ADVANTAGE
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Palavras Chave

Competitive advantage
Competition
Investment

Área

Estratégia em Organizações

Tema

Estratégia Competitiva

Autores

Nome
1 - Alexandre Teixeira Dias
FACULDADE IBMEC (IBMEC) - Belo Horizonte
2 - Henrique Cordeiro Martins
UNIVERSIDADE FUMEC (FUMEC) - FACE
3 - Valdeci Ferreira dos Santos
UNIVERSIDADE FUMEC (FUMEC) - FACE
4 - Pedro Verga Matos
Universidade de Lisboa - ISEG - Lisbon School of Business and Economics
5 - Greiciele Macedo Morais
UNIVERSIDADE FUMEC (FUMEC) - FACE

Reumo

The competitive advantage of firms needs to be sustained over time. However, the context of competition is characterized by transitory competitive advantages (Kanuri & Mcleod, 2016) and, to achieve the best competitive positions, firms constantly adjust their strategies, considering internal and external factors (Fainshmidt et al., 2019; Wilden et al., 2016). These adjustments involve directing investment strategies and decisions to place greater emphasis on growth, profitability, or both (Brito & Brito, 2012, 2014; Dias, Souza, et al., 2019).
This research aims to identify the optimal configuration of CAPEX and R&D investments which leads firms to the best competitive positions, considering the degree of concentration of the markets in which they operate.
The themes addressed in the theory include the role of investments made by firms in determining their position of competitive advantage (Afonso et al. , 2018; Barney & Hesterly, 2011; Karmarkar & Plassmann, 2019; Santos et al., 2017; Pallant et al. , 2020), also addressing the effects of the competitive environment on investment decisions and the firm's competitive position (Alam et al. , 2020; Fainshmidt et al., 2019; Hâkansson & Snehota, 1989; Porter, 1980; Ringov, 2017; Santos et al., 2017; Sener, 2012; Wilden et al. , 2016; Wu et al. , 2020; Yuan et al., 2018).
A Genetic Algorithm model was elaborated to identify which amount of Investment in Capex and R&D (INV) maximize the mean value of the estimated Competitive Position (CP). Coefficients were estimated by structural equations modeling, for each one of the three competitive environments considered in the analysis and for the most recent available year (2017). The increase in firms’ CP that will be achieved as result of the increase or the decrease on IN, is obtained by the difference between CP estimated, and the original CP values, for each one of the firms in the samples.
It was identified, for the perfect competition environment, that the 147.66% increase in Capex and 101.19% in R&D, lead to 50.81% increase in the competitive position. For the monopolistic competition environment, a 56.97% reduction in Capex and a 104.03% reduction in R&D, lead to a 32.78% increase in the competitive position. For the oligopoly environment, a 24.51% increase in the competitive position would be achieved with an increase of 174.31% of investments in Capex and of 16.76% in R&D.
Based on the results one can affirm that investments allow firms to secure more favorable configurations of industry factors and reinforce the need for investment decision makers to consider the environment in which the firm is competing, in terms of degree of concentration and investment capacity of competitors, when defining the amount of investment that must be done to achieve and maintain a favorable competitive advantage position.
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