Genetic algorithm modeling of European Union firms' competitive advantage

Purpose This research aims to identify the optimal configuration of investment which leads firms their best competitive positions, considering degree concentration in market. Design/methodology/approach The methodology was quantitative and based on secondary data with samples 124, 106 90 from environment classified as perfect competition, monopolistic competition oligopoly, respectively. Proposed models' parameters were estimated by means genetic algorithms. Findings Adjustments firm's are contingent they face. Results line existing academic affirmation that purpose investments is create exploit opportunities for positive economic rents allow protect rivals' actions reinforce need decision makers consider firm competing, when defining amount must be done achieve maintain a favorable advantage position. Originality/value brings two main original contributions. first one identification capital R&D operate, size firm. second related use algorithms estimate optimization models considers three environments studied (perfect oligopoly) variables linear quadratic forms.