Research has developed a methodology to measure the quality and develop a model of service quality using structural equations. The research was applied at the student’s cafeteria of San Marcos University. The methodology is to develop a survey technique according to SERVQUAL of 22 questions and apply them to a representative sample. Following the exploratory factor analysis (AFE) in order to determine the dimensions of service quality is made, then confirmatory factor analysis (AFC) is applied in order to quantify the relationships between variables and dimensions; and finally, is performed the structural equation model (MEE) to find out the relationship between the dimensions, which is the model of service quality. To prepare the AFE the Lisrel and SPSS software were used; and for AFC and MEE the Lisrel software was used.

In this study we have developed a method for optimizing the parameters of quality of products that consists of five steps: 1) Determine the characteristics of product quality and process variables 2) Develop an experimental design with Taguchi Methods 3) Develop experiments with Response Surface Methodology. 4) Determine a neural network that represents the relationships between variables and quality characteristics. Using fuzzy variables if there is information not deterministic. 5) Optimize with the use of genetic algorithms. In this proposal, artificial neural networks ANN allow to estimate response functions; in the case of having the qualitative variables these are processed with fuzzy logic LD and in the optimization step genetic algorithms GA are used. An example of optimization with multiple responses is presented to verify the method.

La investigación ha desarrollado una metodología para medir la calidad y elaborar un modelo de calidad del servicio mediante el uso de ecuaciones estructurales. La investigación se aplicó en el comedor de estudiantes de la UNMSM. La metodología consiste en elaborar una encuesta según la técnica SERVQUAL de 22 preguntas y aplicarlas a una muestra representativa. Seguidamente se elabora el Análisis Factorial Exploratorio (AFE) con el objeto de determinar las dimensiones de la calidad del servicio, luego se realiza en Análisis Factorial Confirmatorio (AFC) con el objeto de cuantificar las relaciones entre las variables y las dimensiones; y finalmente, se realiza la determinación del Modelo de Ecuaciones Estructurales (MEE) que permite conocer la relación entre las dimensiones, lo cual constituye el modelo de la calidad del servicio. Para elaborar el AFE se utilizaron los software...

In this study we have developed a method for optimizing the parameters of quality of products that consists of five steps: 1) Determine the characteristics of product quality and process variables 2) Develop an experimental design with Taguchi Methods 3) Develop experiments with Response Surface Methodology. 4) Determine a neural network that represents the relationships between variables and quality characteristics. Using fuzzy variables if there is information not deterministic. 5) Optimize with the use of genetic algorithms. In this proposal, artificial neural networks ANN allow to estimate response functions; in the case of having the qualitative variables these are processed with fuzzy logic LD and in the optimization step genetic algorithms GA are used. An example of optimization with multiple responses is presented to verify the method.

Aplica los métodos Taguchi a las pequeñas y microempresas, según metodología que contempla: plantear el problema, diseño del experimento, realización de pruebas, análisis de resultados y confirmación de resultados. Esta metodología es aplicada a casos específicos: elaboración de velas artesanales y de pop corn. En el caso de velas artesanales se llegó a la combinación óptima de los factores: A2 (90% parafina- 1 O% estearina), B2 (mecha delgada), C1 (molde de latón), D2 (con agitación) y E2 (llama media). En el caso del pop corn se llegó a la combinación óptima de los afctores: A1 (aceite de soya), B2 (50 cm^3 aceite), C2 (llama alta), 01 (sin precalentamiento), E2 (con agitación) y F2 (olla oval). Las principales ventajas de la metodología propuesta son la necesidad de menos pruebas, la elaboración del diseño es más simple, al igual que los cálculos y existe mayo...

Marketing sectors need to assess the possible incidence of non-cognitive factors on complex interactions with clients. Therefore, the objective of analyzing the influence of emotional intelligence (EI) on sales force performance (SFP) through a PLS-SEM model, which relates EI components with SFP. EI was measured with EQ-I, and SFP was measured with the value (USD) of sales/year/salesperson. This analysis was applied to a sample of 58 salespeople of a supply medical equipment company in the Peruvian market. The design was cross-sectional with an explanatory scope. The results show that only the “intrapersonal” and “interpersonal” components of IE influence SFP, whereas the components “adaptability”, “stress management” and “general mood” do not correlate, which partially supports the relationship between EI and SFP.