مجلة الأعمال الإلكترونية والاقتصاد الرقمي

An Evolutionary Fuzzy Intelligence Approach To Predicting Entrepreneurial Marketing Orientation From Digital Marketing Practices

Auteurs : Derkaoui Nasreddine . Nasri Nafissa .

Résumé

This article applies a Mamdani-type fuzzy logic controller, tuned by a genetic algorithm (GA), to model how digital-marketing practices shape marketing entrepreneurship orientation (MEO) among Algerian bank employees. It follows, step by step, a fuzzy-controller and GA-optimization procedure -- triangular membership functions, a linguistic rule base, Mamdani min-max inference, centroid defuzzification, and genetic tuning of membership-function parameters -- and applies it to statistics reported in this Article (N = 73) on digital marketing and marketing entrepreneurship in Béchar, Algeria. Two sub-dimensions -- Electronic Advertising and E-mail Marketing, the Article's strongest and most significant correlates of MEO (r = 0.652, r = 0.568; both p < .001) -- were selected as fuzzy inputs. Because the Article reports only aggregate statistics rather than respondent-level data, a bounded Monte Carlo sample matching the true sample size was calibrated to reproduce its reported correlations. A baseline controller, centered on the reported construct means, was compared with a genetically-optimized controller whose parameters minimize root-mean-square error (RMSE). The optimized controller reduced RMSE by 10.6%. A worked numerical example illustrates fuzzification, rule firing, aggregation, and defuzzification before and after optimization. Results are presented as a methodological demonstration, not new empirical evidence about Algerian bank employees.

Mots clés

Fuzzy logic ; Genetic algorithm ; Mamdani inference ; Marketing entrepreneurship ; Digital marketing.